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Despite strong vetting for disease activity, only 10% of candidate new molecular entities in early stage clinical trials are eventually approved. Analyzing historical pipeline data, Nelson et al. 2015 (Nat. Genet.) concluded pipeline drug targets with human genetic evidence of disease association are twice as likely to lead to approved drugs. Taking advantage of recent clinical development advances and rapid growth in GWAS datasets, we extend the original work using updated data, test whether genetic evidence predicts future successes and introduce statistical models adjusting for target and indication-level properties. Our work confirms drugs with genetically supported targets were more likely to be successful in Phases II and III. When causal genes are clear (Mendelian traits and GWAS associations linked to coding variants), we find the use of human genetic evidence increases approval by greater than two-fold, and, for Mendelian associations, the positive association holds prospectively. Our findings suggest investments into genomics and genetics are likely to be beneficial to companies deploying this strategy. Author summary: The growth of human genetics resources has the potential to help us develop better drugs. By looking at whether and how historical drug approvals could have been predicted from our current knowledge of human genetics, we can validate this approach and assess which types of genetic evidence are most likely to be useful in guiding drug discovery. Validation is important because we are often uncertain about the biological mechanisms behind genetic variants linked to disease. Most associated variants do not occur within protein-coding regions of the genome, and it is difficult to tell which of many nearby genes is contributing to disease risk. In this paper, we confirm previous correlations between genetic evidence and historical drug approvals. We find genetic evidence from severe genetic disorders and from genetic variants that alter protein sequence is more strongly associated with historical approvals. We offer statistical approaches for prioritizing new drug candidates based on whether their mechanisms are supported by human genetic evidence. [ABSTRACT FROM AUTHOR]

Although introns are typically tens to thousands of nucleotides, there are notable exceptions. In flies as well as humans, a small number of genes contain introns that are more than 1000 times larger than typical introns, exceeding hundreds of kilobases (kb) to megabases (Mb). It remains unknown why gigantic introns exist and how cells overcome the challenges associated with their transcription and RNA processing. The Drosophila Y chromosome contains some of the largest genes identified to date: multiple genes exceed 4Mb, with introns accounting for over 99% of the gene span. Here we demonstrate that co-transcriptional splicing of these gigantic Y-linked genes is important to ensure successful transcription: perturbation of splicing led to the attenuation of transcription, leading to a failure to produce mature mRNA. Cytologically, defective splicing of the Y-linked gigantic genes resulted in disorganization of transcripts within the nucleus suggestive of entanglement of transcripts, likely resulting from unspliced long RNAs. We propose that co-transcriptional splicing maintains the length of nascent transcripts of gigantic genes under a critical threshold, preventing their entanglement and ensuring proper gene expression. Our study reveals a novel biological significance of co-transcriptional splicing. Author summary: A small number of genes in our genome are characterized by excessively large introns, sometimes exceeding megabases. It remains poorly understood why such large introns exist or how they are processed during gene expression. By examining genes on Drosophila Y chromosome that contain gigantic introns, it is shown that the transcripts of these genes are co-transcriptionally spliced, and co-transcriptional splicing of these genes is critical for proper gene expression. Perturbation of splicing led to attenuation of transcription specifically in genes with gigantic introns, but not genes with average-sized introns. Whereas transcripts of genes with gigantic introns normally form separate nuclear domains, splicing perturbation led to intermingling of these domains, leading to a proposal that co-transcriptional splicing may function to keep transcript length short to avoid entanglement of transcripts, which may stall the progression of RNA polymerase II. Taken together, these results reveal a novel function of co-transcriptional splicing that specifically impacts the expression of genes with gigantic introns. [ABSTRACT FROM AUTHOR]

Cartilage-hair hypoplasia (CHH) is a pleiotropic disease caused by recessive mutations in the RMRP gene that result in a wide spectrum of manifestations including short stature, sparse hair, metaphyseal dysplasia, anemia, immune deficiency, and increased incidence of cancer. Molecular diagnosis of CHH has implications for management, prognosis, follow-up, and genetic counseling of affected patients and their families. We report 20 novel mutations in 36 patients with CHH and describe the associated phenotypic spectrum. Given the high mutational heterogeneity (62 mutations reported to date), the high frequency of variations in the region (eight single nucleotide polymorphisms in and around RMRP), and the fact that RMRP is not translated into protein, prediction of mutation pathogenicity is difficult. We addressed this issue by a comparative genomic approach and aligned the genomic sequences of RMRP gene in the entire class of mammals. We found that putative pathogenic mutations are located in highly conserved nucleotides, whereas polymorphisms are located in non-conserved positions. We conclude that the abundance of variations in this small gene is remarkable and at odds with its high conservation through species; it is unclear whether these variations are caused by a high local mutation rate, a failure of repair mechanisms, or a relaxed selective pressure. The marked diversity of mutations in RMRP and the low homozygosity rate in our patient population indicate that CHH is more common than previously estimated, but may go unrecognized because of its variable clinical presentation. Thus, RMRP molecular testing may be indicated in individuals with isolated metaphyseal dysplasia, anemia, or immune dysregulation. [ABSTRACT FROM AUTHOR]

The honey bee trypanosomatid parasite, Lotmaria passim, contains two genes that encode the flagellar calcium binding protein (FCaBP) through tandem duplication in its genome. FCaBPs localize in the flagellum and entire body membrane of L. passim through specific N-terminal sorting sequences. This finding suggests that this is an example of protein subcellular relocalization resulting from gene duplication, altering the intracellular localization of FCaBP. However, this phenomenon may not have occurred in Leishmania, as one or both of the duplicated genes have become pseudogenes. Multiple copies of the FCaBP gene are present in several Trypanosoma species and Leptomonas pyrrhocoris, indicating rapid evolution of this gene in trypanosomatid parasites. The N-terminal flagellar sorting sequence of L. passim FCaBP1 is in close proximity to the BBSome complex, while that of Trypanosoma brucei FCaBP does not direct GFP to the flagellum in L. passim. Deletion of the two FCaBP genes in L. passim affected growth and impaired flagellar morphogenesis and motility, but it did not impact host infection. Therefore, FCaBP represents a duplicated gene with a rapid evolutionary history that is essential for flagellar structure and function in a trypanosomatid parasite. Author summary: Protein subcellular relocalization (PSR) was proposed as a mechanism for the functional divergence and retention of duplicate genes. We explored this hypothesis using flagellar calcium binding protein (FCaBP) genes duplicated in many trypanosomatid parasites. FCaBPs localize in the flagellum and entire body membrane of honey bee trypanosomatid parasite, Lotmaria passim through specific N-terminal sorting sequences. However, this is not common with all trypanosomatid parasites since one or both of the duplicated genes have become pseudogenes in Leishmania. N-terminal flagellar sorting sequence of FCaBP1 interacts with BBSome complex, and thus they must have co-evolved in each trypanosomatid species. FCaBPs are essential for the normal growth, flagellar morphogenesis, and motility but not host infection of L. passim. Our findings demonstrate that duplicated FCaBP genes have undergone PSR by changing amino acids in the N-terminal end with some but not all trypanosomatid parasites. In the parasites with multiple FCaBP genes, they play critical roles for the growth control as well as flagellar structure and function. [ABSTRACT FROM AUTHOR]

In high-throughput spatial transcriptomics (ST) studies, it is of great interest to identify the genes whose level of expression in a tissue covaries with the spatial location of cells/spots. Such genes, also known as spatially variable genes (SVGs), can be crucial to the biological understanding of both structural and functional characteristics of complex tissues. Existing methods for detecting SVGs either suffer from huge computational demand or significantly lack statistical power. We propose a non-parametric method termed SMASH that achieves a balance between the above two problems. We compare SMASH with other existing methods in varying simulation scenarios demonstrating its superior statistical power and robustness. We apply the method to four ST datasets from different platforms uncovering interesting biological insights. Author summary: In recent years, spatial transcriptomics (ST) has become increasingly popular to study the expression profile of genes across different spatial locations of a tissue. Many of the genes exhibit spatially varying expression patterns making them immensely valuable for understanding the structural and functional properties of the tissue. The proposed method termed SMASH enables powerful and scalable detection of such genes in high-dimensional ST datasets. [ABSTRACT FROM AUTHOR]

The detection of epistatic interactive effects of multiple genetic variants on the susceptibility of human complex diseases is a great challenge in genome-wide association studies (GWAS). Although methods have been proposed to identify such interactions, the lack of an explicit definition of epistatic effects, together with computational difficulties, makes the development of new methods indispensable. In this paper, we introduce epistatic modules to describe epistatic interactive effects of multiple loci on diseases. On the basis of this notion, we put forward a Bayesian marker partition model to explain observed case-control data, and we develop a Gibbs sampling strategy to facilitate the detection of epistatic modules. Comparisons of the proposed approach with three existing methods on seven simulated disease models demonstrate the superior performance of our approach. When applied to a genome-wide case-control data set for Age-related Macular Degeneration (AMD), the proposed approach successfully identifies two known susceptible loci and suggests that a combination of two other loci-one in the gene SGCD and the other in SCAPER-is associated with the disease. Further functional analysis supports the speculation that the interaction of these two genetic variants may be responsible for the susceptibility of AMD. When applied to a genome-wide case-control data set for Parkinson's disease, the proposed method identifies seven suspicious loci that may contribute independently to the disease. [ABSTRACT FROM AUTHOR]

It is now widely recognized that robustness is an inherent property of biological systems [1,2,3]. The contribution of close sequence homologs to genetic robustness against null mutations has been previously demonstrated in simple organisms [4,5]. In this paper we investigate in detail the contribution of gene duplicates to back-up against deleterious human mutations. Our analysis demonstrates that the functional compensation by close homologs may play an important role in human genetic disease. Genes with a 90% sequence identity homolog are about 3 times less likely to harbor known disease mutations compared to genes with remote homologs. Moreover, close duplicates affect the phenotypic consequences of deleterious mutations by making a decrease in life expectancy significantly less likely. We also demonstrate that similarity of expression profiles across tissues significantly increases the likelihood of functional compensation by homologs. [ABSTRACT FROM AUTHOR]

The recent revelation that there are small, noncoding RNAs that regulate the expression of many other genes has led to an exciting, emerging body of literature defining the biological role for these molecules within signaling networks. In a flurry of recent papers, a microRNA polycistron induced by the oncogenic transcription factor c-myc has been found to be involved in an unusually structured network of interactions. This network includes the seemingly paradoxical transcriptional induction and translational inhibition of the same molecule, the E2F1 transcription factor. This microRNA cluster has been implicated in inhibiting proliferation, as well as inhibiting apoptosis, and promoting angiogenesis. Consistent with its seemingly paradoxical functions, the region of the genome in which it is encoded is deleted in some tumors and overexpressed in others. We consider the possibility that members of this polycistronic microRNA cluster help cells to integrate signals from the environment and decide whether a signal should be interpreted as proliferative or apoptotic. [ABSTRACT FROM AUTHOR]

Due to the increasing power of personal computers, as well as the availability of flexible forward-time simulation programs like simuPOP, it is now possible to simulate the evolution of complex human diseases using a forward-time approach. This approach is potentially more powerful than the coalescent approach since it allows simulations of more than one disease susceptibility locus using almost arbitrary genetic and demographic models. However, the application of such simulations has been deterred by the lack of a suitable simulation framework. For example, it is not clear when and how to introduce disease mutants--especially those under purifying selection--to an evolving population, and how to control the disease allele frequencies at the last generation. In this paper, we introduce a forward-time simulation framework that allows us to generate large multi-generation populations with complex diseases caused by unlinked disease susceptibility loci, according to specified demographic and evolutionary properties. Unrelated individuals, small or large pedigrees can be drawn from the resulting population and provide samples for a wide range of study designs and ascertainment methods. We demonstrate our simulation framework using three examples that map genes associated with affection status, a quantitative trait, and the age of onset of a hypothetical cancer, respectively. Nonadditive fitness models, population structure, and gene-gene interactions are simulated. Case-control, sibpair, and large pedigree samples are drawn from the simulated populations and are examined by a variety of gene-mapping methods. [ABSTRACT FROM AUTHOR]

The formation of long-term memories requires changes in the transcriptional program and de novo protein synthesis. One of the critical regulators for long-term memory (LTM) formation and maintenance is the transcription factor CREB. Genetic studies have dissected the requirement of CREB activity within memory circuits, however less is known about the genetic mechanisms acting downstream of CREB and how they may contribute defining LTM phases. To better understand the downstream mechanisms, we here used a targeted DamID approach (TaDa). We generated a CREB-Dam fusion protein using the fruit fly Drosophila melanogaster as model. Expressing CREB-Dam in the mushroom bodies (MBs), a brain center implicated in olfactory memory formation, we identified genes that are differentially expressed between paired and unpaired appetitive training paradigm. Of those genes we selected candidates for an RNAi screen in which we identified genes causing increased or decreased LTM. Author summary: CREB dependent regulation of gene expression is a key step in long-term memory formation and consolidation. Using a Dam::CREB fusion protein we identified genes that are differentially expressed in the mushroom body one day and two days after appetitive olfactory conditioning. We found candidate genes that cause memory enhancement and genes that cause memory suppression. Thus, we identified potential new regulators of memory formation and maintenance. [ABSTRACT FROM AUTHOR]

Changes in gene regulation represent an important path to generate developmental differences affecting anatomical traits. Interspecific divergence in gene expression often results from changes in transcription-stimulating enhancer elements. While gene repression is crucial for precise spatiotemporal expression patterns, the relative contribution of repressive transcriptional silencers to regulatory evolution remains to be addressed. Here, we show that the Drosophila pigmentation gene ebony has mainly evolved through changes in the spatial domains of silencers patterning its abdominal expression. By precisely editing the endogenous ebony locus of D. melanogaster, we demonstrate the requirement of two redundant abdominal enhancers and three silencers that repress the redundant enhancers in a patterned manner. We observe a role for changes in these silencers in every case of ebony evolution observed to date. Our findings suggest that negative regulation by silencers likely has an under-appreciated role in gene regulatory evolution. Author summary: A central concept in the evo-devo field is that morphological evolution often involves changes in gene regulation. For a variety of reasons, most of the work has focused on the function of enhancers which activate gene expression in discrete patterns. However, this is because enhancers are easier to identify and characterize than other cis-regulatory elements that depend on the activity of multiple elements through long-range interactions. Here, we examined the role of interacting cis-regulatory elements in the regulation and evolution of the pigmentation gene ebony in Drosophila. We showed that in D. melanogaster, ebony abdominal expression is regulated by five cis-regulatory elements. Surprisingly, we found that evolutionary changes to the ebony silencers are sufficient to explain inter specific differences in expression patterns. Our results highlight the importance of silencers in the evolution of ebony regulation and point to a broader possible impact of silencers in the evolution of gene expression that may be prevalent but yet unnoticed. [ABSTRACT FROM AUTHOR]

Prostate cancer is the most inheritable cancer with approximately 42% of disease risk attributed to inherited factors by studies of twins, indicating the importance of additional genetic screening to identify predisposition variants. However, only DNA damage repair (DDR) genes have been investigated thoroughly in prostate cancer. To determine the comprehensive germline mutation landscape in Chinese prostate cancer patients, we performed whole exome sequencing in 100 Han Chinese patients with prostate cancer in Hong Kong and identified deleterious germline mutations. A total of 36 deleterious germline variants in 25 genes were identified in 29% patients. Variants were found in eight pathways, including DNA methylation, DDR, and tyrosine-protein kinase. These findings were validated in an independent Chinese cohort of 167 patients with prostate cancer in Shanghai. Seven common deleterious-variant-containing genes were found in discovery cohort (7/25, 28%) and validation cohort (7/28, 25%) with three genes not described before (LDLR, MYH7 and SUGCT) and four genes previously reported (FANCI, ITGA6, PABPC1 and RAD54B). When comparing with that of a cohort of East Asian healthy individuals, 12 non-DDR novel potential predisposition genes (ADGRG1, CHD4, DNMT3A, ERBB3, GRHL1, HMBS, LDLR, MYH7, MYO6, NT5C2, NUP98 and SUGCT) were identified using the discovery and validation cohorts, which have not been previously reported in prostate cancer patients in all ethnic groups. Taken together, this study reveals a comprehensive germline mutation landscape in Chinese prostate cancer patients and discovers 12 novel non-DDR predisposition genes to lay the groundwork for the optimization of genetic screening. Author summary: Prostate cancer is the most inheritable cancer with about 42% of disease risk attributed to inherited factors, indicating the importance of additional genetic screening to identify predisposition variants. However, only DNA damage repair (DDR) genes have been studied thoroughly in prostate cancer. To determine the comprehensive germline mutation landscape in Chinese prostate cancer patients, we performed whole exome sequencing in 100 Han Chinese patients with prostate cancer in Hong Kong and identified deleterious germline mutations. A total of 36 deleterious germline variants in 25 genes were identified in 29% patients. Variants were found in eight pathways, including DNA methylation, DDR, and tyrosine-protein kinase. These findings were validated in an independent Chinese cohort of 167 patients with prostate cancer in Shanghai. Seven common deleterious-variant-containing genes were found in discovery cohort and validation cohort with three genes not described before (LDLR, MYH7 and SUGCT) and four genes previously reported. When comparing with that of a cohort of East Asian healthy individuals, 12 non-DDR novel potential predisposition genes were identified using the discovery and validation cohorts, which have not been previously reported in prostate cancer patients in all ethnic groups. [ABSTRACT FROM AUTHOR]

Gene drives for mosquito population modification are novel tools for malaria control. Strategies to safely test antimalarial effectors in the field are required. Here, we modified the Anopheles gambiae zpg locus to host a CRISPR/Cas9 integral gene drive allele (zpgD) and characterized its behaviour and resistance profile. We found that zpgD dominantly sterilizes females but can induce efficient drive at other loci when it itself encounters resistance. We combined zpgD with multiple previously characterized non-autonomous payload drives and found that, as zpgD self-eliminates, it leads to conversion of mosquito cage populations at these loci. Our results demonstrate how self-eliminating drivers could allow safe testing of non-autonomous effector-traits by local population modification. They also suggest that after engendering resistance, gene drives intended for population suppression could nevertheless serve to propagate subsequently released non-autonomous payload genes, allowing modification of vector populations initially targeted for suppression. Author summary: Gene drive is a method that allows the genetic modification of entire populations of harmful organisms. Their application to tackle invasive species, agricultural pests or insect disease vectors has been suggested. For example, they could reduce the capacity of malaria mosquitoes to transmit this deadly disease to humans by producing effector molecules inhibiting the development of the Plasmodium parasite in the mosquito vector. We describe a strategy to modularize and test multiple transgenes destined for release, and to introduce only the minimal set of modifications needed into a mosquito population. We show how some elements, once no longer needed, can be made to self-eliminate from populations and we also study how several independent gene drive traits, located in different parts of the genome, can interact and propagate at the level of mosquito cage populations. [ABSTRACT FROM AUTHOR]

The fission yeast TOR complex 2 (TORC2) is required for gene silencing at subtelomeric regions and for the induction of gene transcription in response to DNA replication stress. Thus, TORC2 affects transcription regulation both negatively and positively. Whether these two TORC2-dependent functions share a common molecular mechanism is currently unknown. Here, we show that Gad8 physically interacts with proteins that regulate transcription, including subunits of the Spt-Ada-Gcn5-acetyltransferase (SAGA) complex and the BET bromodomain protein Bdf2. We demonstrate that in the absence of TORC2, Gcn5, the histone acetyltransferase subunit of SAGA, accumulates at subtelomeric genes and at non-induced promoters of DNA replication genes. Remarkably, the loss of Gcn5 in TORC2 mutant cells restores gene silencing as well as transcriptional induction in response to DNA replication stress. Loss of Bdf2 alleviates excess of Gcn5 binding in TORC2 mutant cells and also rescues the aberrant regulation of transcription in these cells. Furthermore, the loss of either SAGA or Bdf2 suppresses the sensitivity of TORC2 mutant cells to a variety of stresses, including DNA replication, DNA damage, temperature and nutrient stresses. We suggest a role of TORC2 in transcriptional regulation that is critical for gene silencing and gene induction in response to stress and involves the binding of Gcn5 to the chromatin. Author summary: A fundamental characteristic of signaling pathways is their role in the regulation of gene expression. Target of rapamycin (TOR), an atypical protein kinase, is a component of two highly conserved TOR complexes: TORC1 and TORC2. These complexes affect nuclear functions through their activity in the cytoplasm as well as directly, through nuclear TOR pools. We previously showed that in fission yeast, TORC2 and its downstream substrate Gad8 associate with the chromatin fraction. We have also demonstrated that TORC2-Gad8 is required for gene silencing and transcriptional induction in response to stresses. Here, we demonstrate that Gad8 physically associates with proteins of the transcriptional machinery. We found that the loss of two positive transcriptional regulators, the SAGA complex and the bromodomain protein Bdf2, restored gene silencing as well as stress-induced transcriptional induction in TORC2 mutant cells. Our data suggests that TORC2-Gad8 contributes to gene regulation through a mechanism involving the inhibition of the accumulation of Gcn5 at the chromatin. These findings suggest a novel and possibly conserved functional relationship between TORC2, Gcn5 and Bdf2. These proteins and protein complexes are key targets in cancer therapies, thus, deciphering their functional relationship may be valuable for combination therapy in personalized medicine. [ABSTRACT FROM AUTHOR]

Diploid organisms contain a maternal and a paternal genome complement that is thought to provide robustness and allow developmental progression despite genetic perturbations that occur in heterozygosity. However, changes affecting gene dosage from the chromosome down to the individual gene level possess a significant pathological potential and can lead to developmental disorders (DDs). This indicates that expression from a balanced gene complement is highly relevant for proper cellular and organismal function in eukaryotes. Paradoxically, gene and whole chromosome duplications are a principal driver of evolution, while heteromorphic sex chromosomes (XY and ZW) are naturally occurring aneuploidies important for sex determination. Here, we provide an overview of the biology of gene dosage at the crossroads between evolutionary benefit and pathogenicity during disease. We describe the buffering mechanisms and cellular responses to alterations, which could provide a common ground for the understanding of DDs caused by copy number alterations. [ABSTRACT FROM AUTHOR]

It is a conventionally held dogma that the genetic basis underlying development is conserved in a long evolutionary time scale. Ample experiments based on mutational, biochemical, functional, and complementary knockdown/knockout approaches have revealed the unexpectedly important role of recently evolved new genes in the development of Drosophila. The recent progress in the genome-wide experimental testing of gene effects and improvements in the computational identification of new genes (< 40 million years ago, Mya) open the door to investigate the evolution of gene essentiality with a phylogenetically high resolution. These advancements also raised interesting issues in techniques and concepts related to phenotypic effect analyses of genes, particularly of those that recently originated. Here we reported our analyses of these issues, including reproducibility and efficiency of knockdown experiment and difference between RNAi libraries in the knockdown efficiency and testing of phenotypic effects. We further analyzed a large data from knockdowns of 11,354 genes (~75% of the Drosophila melanogaster total genes), including 702 new genes (~66% of the species total new genes that aged < 40 Mya), revealing a similarly high proportion (~32.2%) of essential genes that originated in various Sophophora subgenus lineages and distant ancestors beyond the Drosophila genus. The transcriptional compensation effect from CRISPR knockout were detected for highly similar duplicate copies. Knockout of a few young genes detected analogous essentiality in various functions in development. Taken together, our experimental and computational analyses provide valuable data for detection of phenotypic effects of genes in general and further strong evidence for the concept that new genes in Drosophila quickly evolved essential functions in viability during development. Author summary: It is conventionally believed that the genes in control of important biological functions, processes and structures are conserved in evolution. Using recently developed RNAi knockdown libraries in combination of CRISPR knockout analyses, we showed that a high proportion in a large number of evolutionary new genes (~32.2% in 702 new genes, aged < 40 million years ago) in D. melanogaster are essential for the survival in development. We found that the frequency of essentiality in gene functions is stable in the species' various ancestral stages and unchanged among ancient genes, unveiling a constant gene evolution that has driven evolution of Drosophila species in the Sophophora subgenus. We detected the transcriptional compensation effect from CRISPR knockout for highly similar duplicate copies. We experimentally examined the reproducibility, knockdown efficiency and performance of knockdown libraries, revealing the validness of RNAi knockdown in detection of essential phenotypic effects of genes. Our experimental and computational analyses provided strong evidence for the concept that evolutionary new genes in Drosophila quickly evolved essential functions. [ABSTRACT FROM AUTHOR]

The article discusses a research paper on the continuous generation of antigenic diversity during persistent malaria infections. It references the study "Generation of Antigenic Diversity in Plasmodium Falciparum by Structured Rearrangement of Var Genes During Mitosis," by A. Claessens et al. in the same issue of "PLOS Genetics." It discusses the link between antigenic variation, sequestration and pathology, and analysis of subclones of the 3D7 parent clone.

The article discusses a research paper on the use of a reverse genetic approach to examine reproductive aging. It references the study "Gene Pathways That Delay Caemorhabditis Elegans Reproductive Senescence," in the same issue of "PLOS Genetics". It discusses the important health consequences of reproductive aging, and two approaches in identifying genes that modulate reproductive aging in Caenorhabditis elegans.

The rapid decrease in sequencing cost has enabled genetic studies to discover rare variants associated with complex diseases and traits. Once this association is identified, the next step is to understand the genetic mechanism of rare variants on how the variants influence diseases. Similar to the hypothesis of common variants, rare variants may affect diseases by regulating gene expression, and recently, several studies have identified the effects of rare variants on gene expression using heritability and expression outlier analyses. However, identifying individual genes whose expression is regulated by rare variants has been challenging due to the relatively small sample size of expression quantitative trait loci studies and statistical approaches not optimized to detect the effects of rare variants. In this study, we analyze whole-genome sequencing and RNA-seq data of 681 European individuals collected for the Genotype-Tissue Expression (GTEx) project (v8) to identify individual genes in 49 human tissues whose expression is regulated by rare variants. To improve statistical power, we develop an approach based on a likelihood ratio test that combines effects of multiple rare variants in a nonlinear manner and has higher power than previous approaches. Using GTEx data, we identify many genes regulated by rare variants, and some of them are only regulated by rare variants and not by common variants. We also find that genes regulated by rare variants are enriched for expression outliers and disease-causing genes. These results suggest the regulatory effects of rare variants, which would be important in interpreting associations of rare variants with complex traits. Author summary: It has been shown that rare variants may affect many diseases including both rare and common diseases with the advent of next-generation sequencing technology. An important question is how rare variants affect diseases or traits, especially whether or how they regulate gene expression as they may affect diseases through gene regulation. However, it is challenging to identify the regulatory effects of rare variants because it often requires large sample sizes and the existing statistical approaches are not optimized for it. Here, we develop a novel method, LRT-q, based on a likelihood ratio test that aggregates the effects of multiple rare variants nonlinearly to achieve higher statistical power than previous rare variant association methods. We apply LRT-q to the latest GTEx v8 dataset and identify regulatory effect of rare variants on individual genes. We also observe that genes regulated by rare variants are likely to be disease-causing genes. These results demonstrate the functional effects of rare variants, especially on gene expression, which provides important biological insights in understanding the genetic mechanism of rare variants in complex traits and diseases. [ABSTRACT FROM AUTHOR]

Fisher's partitioning of genotypic values and genetic variance is highly relevant in the current era of genome-wide association studies (GWASs). However, despite being more than a century old, a number of persistent misconceptions related to nonadditive genetic effects remain. We developed a user-friendly web tool, the Falconer ShinyApp, to show how the combination of gene action and allele frequencies at causal loci translate to genetic variance and genetic variance components for a complex trait. The app can be used to demonstrate the relationship between a SNP effect size estimated from GWAS and the variation the SNP generates in the population, i.e., how locus-specific effects lead to individual differences in traits. In addition, it can also be used to demonstrate how within and between locus interactions (dominance and epistasis, respectively) usually do not lead to a large amount of nonadditive variance relative to additive variance, and therefore, that these interactions usually do not explain individual differences in a population. [ABSTRACT FROM AUTHOR]

Expression quantitative trait loci (eQTL) studies are used to understand the regulatory function of non-coding genome-wide association study (GWAS) risk loci, but colocalization alone does not demonstrate a causal relationship of gene expression affecting a trait. Evidence for mediation, that perturbation of gene expression in a given tissue or developmental context will induce a change in the downstream GWAS trait, can be provided by two-sample Mendelian Randomization (MR). Here, we introduce a new statistical method, MRLocus, for Bayesian estimation of the gene-to-trait effect from eQTL and GWAS summary data for loci with evidence of allelic heterogeneity, that is, containing multiple causal variants. MRLocus makes use of a colocalization step applied to each nearly-LD-independent eQTL, followed by an MR analysis step across eQTLs. Additionally, our method involves estimation of the extent of allelic heterogeneity through a dispersion parameter, indicating variable mediation effects from each individual eQTL on the downstream trait. Our method is evaluated against other state-of-the-art methods for estimation of the gene-to-trait mediation effect, using an existing simulation framework. In simulation, MRLocus often has the highest accuracy among competing methods, and in each case provides more accurate estimation of uncertainty as assessed through interval coverage. MRLocus is then applied to five candidate causal genes for mediation of particular GWAS traits, where gene-to-trait effects are concordant with those previously reported. We find that MRLocus's estimation of the causal effect across eQTLs within a locus provides useful information for determining how perturbation of gene expression or individual regulatory elements will affect downstream traits. The MRLocus method is implemented as an R package available at https://mikelove.github.io/mrlocus. Author summary: Genome-wide association studies (GWAS) have identified many loci associated with complex traits and diseases. Expression quantitative trait loci (eQTL) may help to explain mechanisms of GWAS associations, if the gene has a role as a mediator of the trait or disease. Loci that exhibit allelic heterogeneity, that is, loci containing multiple causal variants, offer the opportunity to investigate whether effects are concordant and proportional across eQTL and GWAS; if the gene is a partial mediator of the trait, the sign and size of the effects across distinct eQTL variants should be reflected in GWAS associations. Such a Mendelian Randomization (MR) analysis of individual loci is complicated by moderate sample sizes in eQTL studies and linkage disequilibrium (LD), resulting in complex patterns of estimated effect sizes for eQTL and GWAS. We develop a statistical model, MRLocus, with two steps: selection of eQTL SNPs to act as instruments in the MR analysis of a genetic locus, and estimation of the gene-to-trait mediation effect taking instrument uncertainty into account. In simulation, the method has higher accuracy and better uncertainty measures compared to other competing methods, and we compare its estimates on candidate causal gene-trait pairs from literature. [ABSTRACT FROM AUTHOR]

In mammals, cellular identity is defined through strict regulation of chromatin modifications and DNA methylation that control gene expression. Methylation of cytosines at CpG sites in the genome is mainly associated with suppression; however, the reason for enhancer-specific methylation is not fully understood. We used sequential ChIP-bisulfite-sequencing for H13K4me1 and H3K27ac histone marks. By collecting data from the same genomic region, we identified enhancers differentially methylated between these two marks. We observed a global gain of CpG methylation primarily in H3K4me1-marked nucleosomes during mouse embryonic stem cell differentiation. This gain occurred largely in enhancer regions that regulate genes critical for differentiation. The higher levels of DNA methylation in H3K4me1- versus H3K27ac-marked enhancers, despite it being the same genomic region, indicates cellular heterogeneity of enhancer states. Analysis of single-cell RNA-seq profiles demonstrated that this heterogeneity correlates with gene expression during differentiation. Furthermore, heterogeneity of enhancer methylation correlates with transcription start site methylation. Our results provide insights into enhancer-based functional variation in complex biological systems. Author summary: Cellular dynamics are underlined by numerous regulatory layers. The regulatory mechanism of interest in this work are enhancers. Enhancers are regulatory regions responsible, mainly, for increasing the possibility of transcription of a certain gene. Enhancers are marked by two distinct chemical groups-H3K4me1 and H3K27ac on the tail of histones. Histones are the proteins responsible for DNA packaging into condensed chromatin structure. In contrast, DNA methylation is a chemical modification often found on enhancers, and is traditionally associated with repression. A long-debated question revolves around the functional relevance of DNA methylation in the context of enhancers. Here, we combined the two regulatory layers, histone marks and DNA methylation, to a single measurement that can highlight DNA methylation separately on each histone mark but at the same genomic region. When isolated with H3K4me1, enhancers showed higher levels of methylation compared to H3K27ac. As we measured the same genomic locations, we show that differences of DNA methylation between these marks can only be explained by cellular heterogeneity. We also demonstrated that these enhancers tend to play roles in stem cell differentiation and expression levels of the genes they control correlate with cell-to-cell variation. [ABSTRACT FROM AUTHOR]

Chronic pain is highly prevalent worldwide and imparts a significant socioeconomic and public health burden. Factors influencing susceptibility to, and mechanisms of, chronic pain development, are not fully understood, but sex is thought to play a significant role, and chronic pain is more prevalent in women than in men. To investigate sex differences in chronic pain, we carried out a sex-stratified genome-wide association study of Multisite Chronic Pain (MCP), a derived chronic pain phenotype, in UK Biobank on 178,556 men and 209,093 women, as well as investigating sex-specific genetic correlations with a range of psychiatric, autoimmune and anthropometric phenotypes and the relationship between sex-specific polygenic risk scores for MCP and chronic widespread pain. We also assessed whether MCP-associated genes showed expression pattern enrichment across tissues. A total of 123 SNPs at five independent loci were significantly associated with MCP in men. In women, a total of 286 genome-wide significant SNPs at ten independent loci were discovered. Meta-analysis of sex-stratified GWAS outputs revealed a further 87 independent associated SNPs. Gene-level analyses revealed sex-specific MCP associations, with 31 genes significantly associated in females, 37 genes associated in males, and a single gene, DCC, associated in both sexes. We found evidence for sex-specific pleiotropy and risk for MCP was found to be associated with chronic widespread pain in a sex-differential manner. Male and female MCP were highly genetically correlated, but at an rg of significantly less than 1 (0.92). All 37 male MCP-associated genes and all but one of 31 female MCP-associated genes were found to be expressed in the dorsal root ganglion, and there was a degree of enrichment for expression in sex-specific tissues. Overall, the findings indicate that sex differences in chronic pain exist at the SNP, gene and transcript abundance level, and highlight possible sex-specific pleiotropy for MCP. Results support the proposition of a strong central nervous-system component to chronic pain in both sexes, additionally highlighting a potential role for the DRG and nociception. Author summary: Chronic pain is a highly prevalent and debilitating condition, which is more common in women than in men. Sex differences in this condition may be a result of several factors, including differences between the sexes in genetic variation related to chronic pain and gene expression differences related to sex. To explore sex differences in chronic pain from a genetic perspective, we looked for genetic variants associated with chronic pain in men and women separately in a large general-population cohort, and compared the variants we identified between the sexes. We assessed the degree of overlap between genetic variants associated with chronic pain in each sex and those associated with a wide range of other traits, including major depression, body-mass index and suicidality. We also investigated gene expression patterns across a range of tissues for genes associated with chronic pain in each sex, in particular examining expression in neural and non-neural human and mouse tissues and assessing the degree of Dorsal Root Ganglion (DRG) enrichment, an important peripheral nervous system component involved in chronic pain. This work contributes to understanding of chronic pain as a trait and of sex differences in chronic pain at the levels of genetics and gene expression. [ABSTRACT FROM AUTHOR]

Transcriptome-wide association studies (TWAS) test the association between traits and genetically predicted gene expression levels. The power of a TWAS depends in part on the strength of the correlation between a genetic predictor of gene expression and the causally relevant gene expression values. Consequently, TWAS power can be low when expression quantitative trait locus (eQTL) data used to train the genetic predictors have small sample sizes, or when data from causally relevant tissues are not available. Here, we propose to address these issues by integrating multiple tissues in the TWAS using sparse canonical correlation analysis (sCCA). We show that sCCA-TWAS combined with single-tissue TWAS using an aggregate Cauchy association test (ACAT) outperforms traditional single-tissue TWAS. In empirically motivated simulations, the sCCA+ACAT approach yielded the highest power to detect a gene associated with phenotype, even when expression in the causal tissue was not directly measured, while controlling the Type I error when there is no association between gene expression and phenotype. For example, when gene expression explains 2% of the variability in outcome, and the GWAS sample size is 20,000, the average power difference between the ACAT combined test of sCCA features and single-tissue, versus single-tissue combined with Generalized Berk-Jones (GBJ) method, single-tissue combined with S-MultiXcan, UTMOST, or summarizing cross-tissue expression patterns using Principal Component Analysis (PCA) approaches was 5%, 8%, 5% and 38%, respectively. The gain in power is likely due to sCCA cross-tissue features being more likely to be detectably heritable. When applied to publicly available summary statistics from 10 complex traits, the sCCA+ACAT test was able to increase the number of testable genes and identify on average an additional 400 additional gene-trait associations that single-trait TWAS missed. Our results suggest that aggregating eQTL data across multiple tissues using sCCA can improve the sensitivity of TWAS while controlling for the false positive rate. Author summary: Transcriptome-wide association studies (TWAS) can improve the statistical power of genetic association studies by leveraging the relationship between genetically predicted transcript expression levels and an outcome. We propose a new TWAS pipeline that integrates data on the genetic regulation of expression levels across multiple tissues. We generate cross-tissue expression features using sparse canonical correlation analysis and then combine evidence for expression-outcome association across cross- and single-tissue features using the aggregate Cauchy association test. We show that this approach has substantially higher power than traditional single-tissue TWAS methods. Application of these methods to publicly available summary statistics for ten complex traits also identifies associations missed by single-tissue methods. [ABSTRACT FROM AUTHOR]

Transcriptome-wide association studies (TWAS) have been widely used to integrate transcriptomic and genetic data to study complex human diseases. Within a test dataset lacking transcriptomic data, traditional two-stage TWAS methods first impute gene expression by creating a weighted sum that aggregates SNPs with their corresponding cis-eQTL effects on reference transcriptome. Traditional TWAS methods then employ a linear regression model to assess the association between imputed gene expression and test phenotype, thereby assuming the effect of a cis-eQTL SNP on test phenotype is a linear function of the eQTL's estimated effect on reference transcriptome. To increase TWAS robustness to this assumption, we propose a novel Variance-Component TWAS procedure (VC-TWAS) that assumes the effects of cis-eQTL SNPs on phenotype are random (with variance proportional to corresponding reference cis-eQTL effects) rather than fixed. VC-TWAS is applicable to both continuous and dichotomous phenotypes, as well as individual-level and summary-level GWAS data. Using simulated data, we show VC-TWAS is more powerful than traditional TWAS methods based on a two-stage Burden test, especially when eQTL genetic effects on test phenotype are no longer a linear function of their eQTL genetic effects on reference transcriptome. We further applied VC-TWAS to both individual-level (N = ~3.4K) and summary-level (N = ~54K) GWAS data to study Alzheimer's dementia (AD). With the individual-level data, we detected 13 significant risk genes including 6 known GWAS risk genes such as TOMM40 that were missed by traditional TWAS methods. With the summary-level data, we detected 57 significant risk genes considering only cis-SNPs and 71 significant genes considering both cis- and trans- SNPs; these findings also validated our findings with the individual-level GWAS data. Our VC-TWAS method is implemented in the TIGAR tool for public use. Author summary: Traditional Transcriptome-wide association studies (TWAS) tools make strong assumptions about the relationships among genetic variants, transcriptome, and phenotype that may be violated in practice, thereby substantially reducing the power. Here, we propose a Variance-Component TWAS method (VC-TWAS) that relaxes these assumptions and can be implemented with both individual-level and summary-level GWAS data, which is suitable for studying both continuous and dichotomous phenotypes. Our simulation studies showed that VC-TWAS achieved higher power compared to traditional TWAS methods based on a two-stage Burden test, when the underlying assumptions required by traditional TWAS tools were violated. We further applied VC-TWAS to both individual-level (N = ~3.4K) and summary-level (N = ~54K) GWAS data to study Alzheimer's dementia (AD). With individual-level data, we detected 13 significant risk genes including 6 known GWAS risk genes such as TOMM40 that were missed by traditional TWAS methods. Interestingly, 5 of these genes were shown to possess significant pleiotropic effects on AD pathology phenotypes, revealing possible biological mechanisms. With summary-level data of a larger sample size, we detected 57 significant risk genes considering only cis-SNPs and 71 significant genes considering both cis- and trans- SNPs, which also validated our findings with the individual-level GWAS data. In conclusion, VC-TWAS provides an important analytic tool for identifying risk genes whose effects on phenotypes might be mediated through transcriptomes. [ABSTRACT FROM AUTHOR]

The tumor suppressor IKAROS binds and represses multiple NOTCH target genes. For their induction upon NOTCH signaling, IKAROS is removed and replaced by NOTCH Intracellular Domain (NICD)-associated proteins. However, IKAROS remains associated to other NOTCH activated genes upon signaling and induction. Whether IKAROS could participate to the induction of this second group of NOTCH activated genes is unknown. We analyzed the combined effect of IKAROS abrogation and NOTCH signaling on the expression of NOTCH activated genes in erythroid cells. In IKAROS-deleted cells, we observed that many of these genes were either overexpressed or no longer responsive to NOTCH signaling. IKAROS is then required for the organization of bivalent chromatin and poised transcription of NOTCH activated genes belonging to either of the aforementioned groups. Furthermore, we show that IKAROS-dependent poised organization of the NOTCH target Cdkn1a is also required for its adequate induction upon genotoxic insults. These results highlight the critical role played by IKAROS in establishing bivalent chromatin and transcriptional poised state at target genes for their activation by NOTCH or other stress signals. Author summary: NOTCH1 deregulation can favor hematological malignancies. In addition to RBP-Jκ/NICD/MAML1, other regulators are required for the measured activation of NOTCH target genes. IKAROS is a known repressor of many NOTCH targets. Since it can also favor transcriptional activation and control gene expression levels, we questioned whether IKAROS could participate to the activation of specific NOTCH target genes. We are reporting that upon NOTCH induction, the absence of IKAROS impairs the measured activation of two groups of NOTCH target genes: (i) those overexpressed and characterized by an additive effect imposed by the absence of IKAROS and NOTCH induction; and (ii) those 'desensitized' and no more activated by NOTCH. At genes of both groups, IKAROS controls the timely recruitment of the chromatin remodelers CHD4 and BRG1. IKAROS then influences the activation of these genes through the organization of chromatin and poised transcription or through transcriptional elongation control. The importance of the IKAROS controlled and measured activation of genes is not limited to NOTCH signaling as it also characterizes Cdkn1a expression upon genotoxic stress. Thus, these results provide a new perspective on the importance of IKAROS for the adequate cellular response to stress, whether imposed by NOTCH or genotoxic insults. [ABSTRACT FROM AUTHOR]

Fission yeast Cleavage and Polyadenylation Factor (CPF), a 13-subunit complex, executes the cotranscriptional 3' processing of RNA polymerase II (Pol2) transcripts that precedes transcription termination. The three-subunit DPS sub-complex of CPF, consisting of a PP1-type phosphoprotein phosphatase Dis2, a WD-repeat protein Swd22, and a putative phosphatase regulatory factor Ppn1, associates with the CPF core to form the holo-CPF assembly. Here we probed the functional, physical, and genetic interactions of DPS by focusing on the Ppn1 subunit, which mediates association of DPS with the core. Transcriptional profiling by RNA-seq defined limited but highly concordant sets of protein-coding genes that were dysregulated in ppn1Δ, swd22Δ and dis2Δ cells, which included the DPSΔ down-regulated phosphate homeostasis genes pho1 and pho84 that are controlled by lncRNA-mediated transcriptional interference. Essential and inessential modules of the 710-aa Ppn1 protein were defined by testing the effects of Ppn1 truncations in multiple genetic backgrounds in which Ppn1 is required for growth. An N-terminal 172-aa disordered region was dispensable and its deletion alleviated hypomorphic phenotypes caused by deleting C-terminal aa 640–710. A TFIIS-like domain (aa 173–330) was not required for viability but was important for Ppn1 activity in phosphate homeostasis. Distinct sites within Ppn1 for binding to Dis2 (spanning Ppn1 aa 506 to 532) and Swd22 (from Ppn1 aa 533 to 578) were demarcated by yeast two-hybrid assays. Dis2 interaction-defective missense mutants of full-length Ppn1 (that retained Swd22 interaction) were employed to show that binding to Dis2 (or its paralog Sds21) was necessary for Ppn1 biological activity. Ppn1 function was severely compromised by missense mutations that selectively affected its binding to Swd22. Author summary: Multi-layered regulatory inputs to eukaryal gene expression target the initiation, elongation, and termination steps of RNA polymerase II transcription. Termination is coupled to, and ensues from, the 3' processing of nascent RNA by multi-protein assemblies. The fission yeast Cleavage and Polyadenylation Factor complex, CPF, is an exemplary 3' processing machine composed of 13 protein subunits, three of which (named Dis2, Ppn1, and Swd22) form a DPS sub-complex within CPF. In this study, we interrogated the effects of DPS null mutations on the fission yeast transcriptome. We probed the physical interactions of Ppn1 and its genetic interactions with other components of the transcription and RNA processing machinery. We delineated distinct binding sites within Ppn1 for Dis2 and Swd22 and then showed that perturbation of these sites interdicts Ppn1's essential activities in vivo. [ABSTRACT FROM AUTHOR]

The evolution of insect resistance to insecticides is frequently associated with overexpression of one or more cytochrome P450 enzyme genes. Although overexpression of CYP450 genes is a well-known mechanism of insecticide resistance, the underlying regulatory mechanisms are poorly understood. Here we uncovered the mechanisms of overexpression of the P450 gene, CYP321A8 in a major pest insect, Spodoptera exigua that is resistant to multiple insecticides. CYP321A8 confers resistance to organophosphate (chlorpyrifos) and pyrethroid (cypermethrin and deltamethrin) insecticides in this insect. Constitutive upregulation of transcription factors CncC/Maf are partially responsible for upregulated expression of CYP321A8 in the resistant strain. Reporter gene assays and site-directed mutagenesis analyses demonstrated that CncC/Maf enhanced the expression of CYP321A8 by binding to specific sites in the promoter. Additional cis-regulatory elements resulting from a mutation in the CYP321A8 promoter in the resistant strain facilitates the binding of the orphan nuclear receptor, Knirps, and enhances the promoter activity. These results demonstrate that two independent mechanisms; overexpression of transcription factors and mutations in the promoter region resulting in a new cis-regulatory element that facilitates binding of the orphan nuclear receptor are involved in overexpression of CYP321A8 in insecticide-resistant S. exigua. Author summary: Insect pests developing resistance to insecticides used for their control is a major problem in agriculture. Many pests including the beet armyworm, Spodoptera exigua have developed resistance to insecticides used for their control. Information on the mechanisms of resistance would help in resistance management programs. Overexpression of detoxifying enzymes were associated with insecticide resistance, but their functions and regulatory mechanisms are still unidentified. The expression levels of P450 genes between susceptible and resistant strains of S. exigua were compared and CYP321A8 was identified as the major contributor to resistance to organophosphate and pyrethroid insecticides. Further studies uncovered two independent but synergistic mechanisms; constitutive upregulation of b-Zip transcription factors and mutations in the promoter that facilitates the binding of an orphan nuclear receptor, Knirps contributing to increase in the expression of CYP321A8 and resistance to multiple insecticides in S. exigua. [ABSTRACT FROM AUTHOR]

Allelic expression imbalance (AEI), quantified by the relative expression of two alleles of a gene in a diploid organism, can help explain phenotypic variations among individuals. Traditional methods detect AEI using bulk RNA sequencing (RNA-seq) data, a data type that averages out cell-to-cell heterogeneity in gene expression across cell types. Since the patterns of AEI may vary across different cell types, it is desirable to study AEI in a cell-type-specific manner. Although this can be achieved by single-cell RNA sequencing (scRNA-seq), it requires full-length transcript to be sequenced in single cells of a large number of individuals, which are still cost prohibitive to generate. To overcome this limitation and utilize the vast amount of existing disease relevant bulk tissue RNA-seq data, we developed BSCET, which enables the characterization of cell-type-specific AEI in bulk RNA-seq data by integrating cell type composition information inferred from a small set of scRNA-seq samples, possibly obtained from an external dataset. By modeling covariate effect, BSCET can also detect genes whose cell-type-specific AEI are associated with clinical factors. Through extensive benchmark evaluations, we show that BSCET correctly detected genes with cell-type-specific AEI and differential AEI between healthy and diseased samples using bulk RNA-seq data. BSCET also uncovered cell-type-specific AEIs that were missed in bulk data analysis when the directions of AEI are opposite in different cell types. We further applied BSCET to two pancreatic islet bulk RNA-seq datasets, and detected genes showing cell-type-specific AEI that are related to the progression of type 2 diabetes. Since bulk RNA-seq data are easily accessible, BSCET provided a convenient tool to integrate information from scRNA-seq data to gain insight on AEI with cell type resolution. Results from such analysis will advance our understanding of cell type contributions in human diseases. Author summary: Detection of allelic expression imbalance (AEI), a phenomenon where the two alleles of a gene differ in their expression magnitude, is a key step towards the understanding of phenotypic variations among individuals. Existing methods detect AEI use bulk RNA sequencing (RNA-seq) data and ignore AEI variations among different cell types. Although single-cell RNA sequencing (scRNA-seq) has enabled the characterization of cell-to-cell heterogeneity in gene expression, the high costs have limited its application in AEI analysis. To overcome this limitation, we developed BSCET to characterize cell-type-specific AEI using the widely available bulk RNA-seq data by integrating cell-type composition information inferred from scRNA-seq samples. Since the degree of AEI may vary with disease phenotypes, we further extended BSCET to detect genes whose cell-type-specific AEIs are associated with clinical factors. Through extensive benchmark evaluations and analyses of two pancreatic islet bulk RNA-seq datasets, we demonstrated BSCET's ability to refine bulk-level AEI to cell-type resolution, and to identify genes whose cell-type-specific AEIs are associated with the progression of type 2 diabetes. With the vast amount of easily accessible bulk RNA-seq data, we believe BSCET will be a valuable tool for elucidating cell type contributions in human diseases. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWASs) have identified multiple susceptibility loci for Alzheimer's disease (AD), which is characterized by early and progressive damage to the hippocampus. However, the association of hippocampal gene expression with AD and the underlying neurobiological pathways remain largely unknown. Based on the genomic and transcriptomic data of 111 hippocampal samples and the summary data of two large-scale meta-analyses of GWASs, a transcriptome-wide association study (TWAS) was performed to identify genes with significant associations between hippocampal expression and AD. We identified 54 significantly associated genes using an AD-GWAS meta-analysis of 455,258 individuals; 36 of the genes were confirmed in another AD-GWAS meta-analysis of 63,926 individuals. Fine-mapping models further prioritized 24 AD-related genes whose effects on AD were mediated by hippocampal expression, including APOE and two novel genes (PTPN9 and PCDHA4). These genes are functionally related to amyloid-beta formation, phosphorylation/dephosphorylation, neuronal apoptosis, neurogenesis and telomerase-related processes. By integrating the predicted hippocampal expression and neuroimaging data, we found that the hippocampal expression of QPCTL and ERCC2 showed significant difference between AD patients and cognitively normal elderly individuals as well as correlated with hippocampal volume. Mediation analysis further demonstrated that hippocampal volume mediated the effect of hippocampal gene expression (QPCTL and ERCC2) on AD. This study identifies two novel genes associated with AD by integrating hippocampal gene expression and genome-wide association data and reveals candidate hippocampus-mediated neurobiological pathways from gene expression to AD. Author summary: The hippocampus is a potential neuroimaging endophenotype for Alzheimer's disease (AD). This study identifies genes whose expression in hippocampal tissue is associated with AD and establishes the pathways from hippocampal gene expression to hippocampal volume to AD. We demonstrate that 24 genes are associated with AD in hippocampal tissue, and these genes are enriched for AD-related biological processes of amyloid-beta formation, phosphorylation/dephosphorylation, neuronal apoptosis, neurogenesis and telomerase-related processes. We further show that hippocampal volume mediates the effects of the hippocampal gene expression of QPCTL and ERCC2 on AD. These findings improve our understanding of the genetic and neural mechanisms of AD. [ABSTRACT FROM AUTHOR]

The transcriptome-wide association study (TWAS) has emerged as one of several promising techniques for integrating multi-scale 'omics' data into traditional genome-wide association studies (GWAS). Unlike GWAS, which associates phenotypic variance directly with genetic variants, TWAS uses a reference dataset to train a predictive model for gene expressions, which allows it to associate phenotype with variants through the mediating effect of expressions. Although effective, this core innovation of TWAS is poorly understood, since the predictive accuracy of the genotype-expression model is generally low and further bounded by expression heritability. This raises the question: to what degree does the accuracy of the expression model affect the power of TWAS? Furthermore, would replacing predictions with actual, experimentally determined expressions improve power? To answer these questions, we compared the power of GWAS, TWAS, and a hypothetical protocol utilizing real expression data. We derived non-centrality parameters (NCPs) for linear mixed models (LMMs) to enable closed-form calculations of statistical power that do not rely on specific protocol implementations. We examined two representative scenarios: causality (genotype contributes to phenotype through expression) and pleiotropy (genotype contributes directly to both phenotype and expression), and also tested the effects of various properties including expression heritability. Our analysis reveals two main outcomes: (1) Under pleiotropy, the use of predicted expressions in TWAS is superior to actual expressions. This explains why TWAS can function with weak expression models, and shows that TWAS remains relevant even when real expressions are available. (2) GWAS outperforms TWAS when expression heritability is below a threshold of 0.04 under causality, or 0.06 under pleiotropy. Analysis of existing publications suggests that TWAS has been misapplied in place of GWAS, in situations where expression heritability is low. Author summary: We compared the effectiveness of three methods for finding genetic effects on disease in order to quantify their strengths and help researchers choose the best protocol for their data. The genome-wide association study (GWAS) is the standard method for identifying how the genetic differences between individuals relate to disease. Recently, the transcriptome-wide association study (TWAS) has improved GWAS by also estimating the effect of each genetic variant on the activity level (or expression) of genes related to disease. The effectiveness of TWAS is surprising because its estimates of gene expressions are very inaccurate, so we ask if a method using real expression data instead of estimates would perform better. Unlike past studies, which only use simulation to compare these methods, we incorporate novel statistical calculations to make our comparisons more accurate and universally applicable. We discover that depending on the type of relationship between genetics, gene expression, and disease, the estimates used by TWAS could be actually more relevant than real gene expressions. We also find that TWAS is not always better than GWAS when the relationship between genetics and expression is weak and identify specific turning points where past studies have incorrectly used TWAS instead of GWAS. [ABSTRACT FROM AUTHOR]

The prospect of utilizing CRISPR-based gene-drive technology for controlling populations has generated much excitement. However, the potential for spillovers of gene-drive alleles from the target population to non-target populations has raised concerns. Here, using mathematical models, we investigate the possibility of limiting spillovers to non-target populations by designing differential-targeting gene drives, in which the expected equilibrium gene-drive allele frequencies are high in the target population but low in the non-target population. We find that achieving differential targeting is possible with certain configurations of gene drive parameters, but, in most cases, only under relatively low migration rates between populations. Under high migration, differential targeting is possible only in a narrow region of the parameter space. Because fixation of the gene drive in the non-target population could severely disrupt ecosystems, we outline possible ways to avoid this outcome. We apply our model to two potential applications of gene drives—field trials for malaria-vector gene drives and control of invasive species on islands. We discuss theoretical predictions of key requirements for differential targeting and their practical implications. Author summary: CRISPR-based gene drive is an emerging genetic engineering technology that enables engineered genetic variants, which are usually designed to be harmful to the organism carrying them, to be spread rapidly in populations. Although this technology is promising for controlling disease vectors and invasive species, there is a considerable risk that the gene drive could unintentionally spillover from the target population, where it was deployed, to other non-target populations. We develop mathematical models of gene-drive dynamics that incorporate migration between a target and non-target populations to investigate the possibility of effectively applying a gene drive in the target population while limiting its spillovers to the non-target population ('differential targeting'). We observe that the feasibility of differential targeting depends on the gene-drive design specification, as well as on the migration rates between the populations. Even when differential targeting is possible, as migration increases, the possibility for differential targeting disappears. We find that differential targeting can be effective for low migration rates, and that it is sensitive to the design of the gene drive under high migration rates. We suggest that differential targeting could be used, in combination with other mitigation measures, as an additional safeguard to limit gene drive spillovers. [ABSTRACT FROM AUTHOR]

Gene drive elements promote the spread of linked traits, providing methods for changing the composition or fate of wild populations. Drive mechanisms that are self-limiting are attractive because they allow control over the duration and extent of trait spread in time and space, and are reversible through natural selection as drive wanes. Self-sustaining Cleave and Rescue (ClvR) elements include a DNA sequence-modifying enzyme such as Cas9/gRNAs that disrupts endogenous versions of an essential gene, a tightly linked recoded version of the essential gene resistant to cleavage (the Rescue), and a Cargo. ClvR spreads by creating loss-of-function (LOF) conditions in which those without ClvR die because they lack functional copies of the essential gene. We use modeling to show that when the Rescue-Cargo and one or both components required for LOF allele creation (Cas9 and gRNA) reside at different locations (split ClvR), drive of Rescue-Cargo is self-limiting due to a progressive decrease in Cas9 frequency, and thus opportunities for creation of LOF alleles, as spread occurs. Importantly, drive strength and duration can be extended in a measured manner—which is still self-limiting—by moving the two components close enough to each other that they experience some degree of linkage. With linkage, Cas9 transiently experiences drive by hitchhiking with Rescue-Cargo until linkage disequilibrium between the two disappears, a function of recombination frequency and number of generations, creating a novel point of control. We implement split ClvR in Drosophila, with key elements on different chromosomes. Cargo/Rescue/gRNAs spreads to high frequency in a Cas9-dependent manner, while the frequency of Cas9 decreases. These observations show that measured, transient drive, coupled with a loss of future drive potential, can be achieved using the simple toolkit that make up ClvR elements—Cas9 and gRNAs and a Rescue/Cargo. Author summary: There is great interest in being able to spread beneficial traits throughout wild populations. However, many traits of interest do not provide a fitness benefit to those who carry them, and thus require some kind of a "push" to drive them to high frequency in the population. Selfish genetic elements are transmitted to viable, fertile progeny at rates greater than those of other genes, and can spread to high frequency even when they result in fitness costs to carriers—a phenomenon known as gene drive. If genes encoding traits of interest are incorporated into a selfish genetic element, they too can be forced to spread. Gene drive methods that provide a driving force that ultimately wanes to nothing over time (that are self-limiting) are attractive because they ensure that spread to high frequency will be limited in time and space, features that are likely to be important in many regulatory and social environments. Here we use modeling and experiments in Drosophila melanogaster to show how split versions of a gene drive method known as Cleave and Rescue (ClvR) can be used to bring about self-limiting drive whose strength and duration can be tailored to specific economic, ecological and/or regulatory needs. [ABSTRACT FROM AUTHOR]

In the fruit fly Drosophila melanogaster, male-specific splicing and translation of the Fruitless transcription factor (FruM) alters the presence, anatomy, and/or connectivity of >60 types of central brain neurons that interconnect to generate male-typical behaviors. While the indispensable function of FruM in sex-specific behavior has been understood for decades, the molecular mechanisms underlying its activity remain unknown. Here, we take a genome-wide, brain-wide approach to identifying regulatory elements whose activity depends on the presence of FruM. We identify 436 high-confidence genomic regions differentially accessible in male fruitless neurons, validate candidate regions as bona-fide, differentially regulated enhancers, and describe the particular cell types in which these enhancers are active. We find that individual enhancers are not activated universally but are dedicated to specific fru+ cell types. Aside from fru itself, genes are not dedicated to or common across the fru circuit; rather, FruM appears to masculinize each cell type differently, by tweaking expression of the same effector genes used in other circuits. Finally, we find FruM motifs enriched among regulatory elements that are open in the female but closed in the male. Together, these results suggest that FruM acts cell-type-specifically to decommission regulatory elements in male fruitless neurons. Author summary: Courtship behavior in male Drosophila melanogaster is controlled by a well-defined neural circuit that is labeled by the male-specific transcription factor Fruitless (FruM). While FruM is known to change the number, anatomy and connectivity of neurons which comprise the circuit and has been suggested to repress the expression of a few gene targets, the mechanism of how FruM regulates genes across many different kinds of neurons is unknown. Using an approach to identify gene regulatory elements based on their chromatin accessibility states (ATAC-seq), we identified a large set of chromatin accessibility changes downstream of Fruitless. By examining the activity of these regulatory elements in-vivo, we found that their activity was 1) sexually dimorphic and 2) specific to a single class of FruM neurons, suggesting that FruM acts on different chromatin targets in different neuron classes comprising the courtship circuit. Further, we found a known FruM-regulated enhancer of the FruM-repressed gene Lgr3 to have closed chromatin specifically in FruM neurons. Combined with an enrichment of FruM motifs in regions which are closed in FruM neurons, we present a mechanism where FruM directs the decommissioning of sex-shared regulatory elements to masculinize neurons in a cell-type specific manner. [ABSTRACT FROM AUTHOR]

During the development of a holometabolous insect such as Drosophila, specific group of cells in the larva survive during metamorphosis, unlike the other larval cells, and finally give rise to the differentiated adult structures. These cells, also known as Adult Progenitor Cells (APCs), maintain their multipotent capacity, differentially respond to hormonal and nutritional signals, survive the intrinsic and environmental stress and respond to the final differentiation cues. However, not much is known about the specific molecular mechanisms that account for their unique characteristics. Here we show that a specific Drosophila APC gene, headcase (hdc), has a dual role in the normal development of these cells. It acts at a systemic level by controlling the hormone ecdysone in the prothoracic gland and at the same time it acts locally as a tissue growth suppressor in the APC clusters, where it modulates the activity of the TOR pathway and promotes their survival by contributing in the regulation of the Unfolded Protein Response. We also show that hdc provides protection against stress in the APCs and that its ectopic expression in cells that do not usually express hdc can confer these cells with an additional stress protection. Hdc is the founding member of a group of homolog proteins identified from C. elegans to humans, where has been found associated with cancer progression. The finding that the Drosophila hdc is specifically expressed in progenitor cells and that it provides protection against stress opens up a new hypothesis to be explored regarding the role of the human Heca and its contribution to carcinogenesis. Author summary: In all organisms there are sets of "reserve" cells that have the capacity to self-renew and eventually differentiate to repair or provide new structures. Here we report that the Drosophila headcase gene provides such kinds of cells with a stress protective mechanism. Interestingly, headcase is also involved in providing such "reserve" cells with the signal required for initiating their differentiation into new structures. Thus, headcase establishes a fine equilibrium between differentiation and stress protection of these "reserve" cells. Of note headcase is the founding member of a group of homolog proteins identified in many animals. In humans, the headcase homolog is associated with different kinds of cancers but its function and role remains unknown. The finding that the Drosophila headcase confers stress protection opens up a new way to be explored regarding the role of the human headcase as it could also act as a stress protector and its drop-off may induce stress conditions favouring the initiation and progression of tumorigenesis. [ABSTRACT FROM AUTHOR]

Killer toxins are extracellular antifungal proteins that are produced by a wide variety of fungi, including Saccharomyces yeasts. Although many Saccharomyces killer toxins have been previously identified, their evolutionary origins remain uncertain given that many of these genes have been mobilized by double-stranded RNA (dsRNA) viruses. A survey of yeasts from the Saccharomyces genus has identified a novel killer toxin with a unique spectrum of activity produced by Saccharomyces paradoxus. The expression of this killer toxin is associated with the presence of a dsRNA totivirus and a satellite dsRNA. Genetic sequencing of the satellite dsRNA confirmed that it encodes a killer toxin with homology to the canonical ionophoric K1 toxin from Saccharomyces cerevisiae and has been named K1-like (K1L). Genomic homologs of K1L were identified in six non-Saccharomyces yeast species of the Saccharomycotina subphylum, predominantly in subtelomeric regions of the genome. When ectopically expressed in S. cerevisiae from cloned cDNAs, both K1L and its homologs can inhibit the growth of competing yeast species, confirming the discovery of a family of biologically active K1-like killer toxins. The sporadic distribution of these genes supports their acquisition by horizontal gene transfer followed by diversification. The phylogenetic relationship between K1L and its genomic homologs suggests a common ancestry and gene flow via dsRNAs and DNAs across taxonomic divisions. This appears to enable the acquisition of a diverse arsenal of killer toxins by different yeast species for potential use in niche competition. Author summary: Antifungal killer toxins produced by Saccharomyces yeasts can be found mostly encoded by cytoplasmic double-stranded RNAs (dsRNAs) rather than the DNA genome. A survey of Saccharomyces yeasts has identified a new dsRNA-encoded killer toxin that has a unique antifungal activity and is related in structure and function to the canonical K1 killer toxin. This "K1-like" (K1L) killer toxin was identified to be part of a larger family of DNA-encoded "K1 killer toxin-like" (KKT) genes in more distantly related yeasts. KKT genes encode active killer toxins and appear to have been acquired sporadically during the evolution of each yeast species, with evidence of ongoing gene duplication. The common ancestry of K1L and homologous killer toxins suggests the transfer of these genes via dsRNAs and DNAs between different yeast species that inhabit similar natural and artificial environments. The potential evolutionary advantage of acquiring killer toxins for niche competition rationalizes the ongoing acquisition and diversification of these genes in yeasts. [ABSTRACT FROM AUTHOR]

Transcriptional dynamic in response to environmental and developmental cues are fundamental to biology, yet many mechanistic aspects are poorly understood. One such example is fungal plant pathogens, which use secreted proteins and small molecules, termed effectors, to suppress host immunity and promote colonization. Effectors are highly expressed in planta but remain transcriptionally repressed ex planta, but our mechanistic understanding of these transcriptional dynamics remains limited. We tested the hypothesis that repressive histone modification at H3-Lys27 underlies transcriptional silencing ex planta, and that exchange for an active chemical modification contributes to transcription of in planta induced genes. Using genetics, chromatin immunoprecipitation and sequencing and RNA-sequencing, we determined that H3K27me3 provides significant local transcriptional repression. We detail how regions that lose H3K27me3 gain H3K27ac, and these changes are associated with increased transcription. Importantly, we observed that many in planta induced genes were marked by H3K27me3 during axenic growth, and detail how altered H3K27 modification influences transcription. ChIP-qPCR during in planta growth suggests that H3K27 modifications are generally stable, but can undergo dynamics at specific genomic locations. Our results support the hypothesis that dynamic histone modifications at H3K27 contributes to fungal genome regulation and specifically contributes to regulation of genes important during host infection. Author summary: Fungal pathogens of crops and humans pose annual threats to our food and health. There are many steps to the host infection process, during which fungal pathogens display unique growth, and use specific genes to cause disease. Despite this knowledge, many aspects of how pathogens regulate their genome to enact this process remain unknown. Here, we demonstrate how chemical modification of lysine residues on the histone H3, which helps organize and control DNA usage, play an important regulatory role in the model fungal pathogen causing rice blast disease. Our analysis shows a significant association between genes important for host infection and H3 lysine 27 methylation. We show that by experimentally changing histone modifications, many fungal genes normally used during plant infection are turned on outside of the host. Furthermore, we detail how histone modifications can change naturally in the fungus during plant infection. These findings help broaden our knowledge of genome regulation for these pathogens, and advances the goal of a more comprehensive understanding of the infection process. [ABSTRACT FROM AUTHOR]

Homing-based gene drives use a germline source of nuclease to copy themselves at specific target sites in a genome and bias their inheritance. Such gene drives can be designed to spread and deliberately suppress populations of malaria mosquitoes by impairing female fertility. However, strong unintended fitness costs of the drive and a propensity to generate resistant mutations can limit a gene drive's potential to spread. Alternative germline regulatory sequences in the drive element confer improved fecundity of carrier individuals and reduced propensity for target site resistance. This is explained by reduced rates of end-joining repair of DNA breaks from parentally deposited nuclease in the embryo, which can produce heritable mutations that reduce gene drive penetrance. We tracked the generation and selection of resistant mutations over the course of a gene drive invasion of a population. Improved gene drives show faster invasion dynamics, increased suppressive effect and later onset of target site resistance. Our results show that regulation of nuclease expression is as important as the choice of target site when developing a robust homing-based gene drive for population suppression. Author summary: Gene drives are selfish genetic elements that are able to drastically bias their own inheritance. They can rapidly invade populations, even starting from a very low frequency. Recent advances have allowed the engineering of gene drives deliberately designed to spread genetic traits of choice into populations of malaria-transmitting mosquito species–for example traits that impair a mosquito's ability to reproduce or its ability to transmit parasites. The class of gene drive in question uses a very precise cutting and copying mechanism, termed 'homing', that allows it to increase its numbers in the cells that go on to form sperm or eggs, thereby increasing the chances that a copy of the gene drive is transmitted to offspring. However, while this type of gene drive can rapidly invade a mosquito population, mosquitoes can also eventually become resistant to the gene drive in some cases. Here we show that restricting the cutting activity of the gene drive to the germline tissue is crucial to maintaining its potency and we illustrate how failure to restrict this activity can lead to the generation of mutations that can make mosquitoes resistant to the gene drive. [ABSTRACT FROM AUTHOR]

Traditional univariate genome-wide association studies generate false positives and negatives due to difficulties distinguishing associated variants from variants with spurious nonzero effects that do not directly influence the trait. Recent efforts have been directed at identifying genes or signaling pathways enriched for mutations in quantitative traits or case-control studies, but these can be computationally costly and hampered by strict model assumptions. Here, we present gene-ε, a new approach for identifying statistical associations between sets of variants and quantitative traits. Our key insight is that enrichment studies on the gene-level are improved when we reformulate the genome-wide SNP-level null hypothesis to identify spurious small-to-intermediate SNP effects and classify them as non-causal. gene-ε efficiently identifies enriched genes under a variety of simulated genetic architectures, achieving greater than a 90% true positive rate at 1% false positive rate for polygenic traits. Lastly, we apply gene-ε to summary statistics derived from six quantitative traits using European-ancestry individuals in the UK Biobank, and identify enriched genes that are in biologically relevant pathways. Author summary: Enrichment tests augment the standard univariate genome-wide association (GWA) framework by identifying groups of biologically interacting mutations that are enriched for associations with a trait of interest, beyond what is expected by chance. These analyses model local linkage disequilibrium (LD), allow many different mutations to be disease-causing across patients, and generate biologically interpretable hypotheses for disease mechanisms. However, existing enrichment analyses are hampered by high computational costs, and rely on GWA summary statistics despite the high false positive rate of the standard univariate GWA framework. Here, we present the gene-level association framework gene-ε (pronounced "genie"), an empirical Bayesian approach for identifying statistical associations between sets of mutations and quantitative traits. The central innovation of gene-ε is reformulating the GWA null model to distinguish between (i) mutations that are statistically associated with the disease but are unlikely to directly influence it, and (ii) mutations that are most strongly associated with a disease of interest. We find that, with our reformulated SNP-level null hypothesis, our gene-level enrichment model outperforms existing enrichment methods in simulation studies and scales well for application to emerging biobank datasets. We apply gene-ε to six quantitative traits in the UK Biobank and recover novel and functionally validated gene-level associations. [ABSTRACT FROM AUTHOR]

Genetic linkage maps are cornerstones of a wide spectrum of biotechnology applications, including map-assisted breeding, association genetics, and map-assisted gene cloning. During the past several years, the adoption of high-throughput genotyping technologies has been paralleled by a substantial increase in the density and diversity of genetic markers. New genetic mapping algorithms are needed in order to efficiently process these large datasets and accurately construct high-density genetic maps. In this paper, we introduce a novel algorithm to order markers on a genetic linkage map. Our method is based on a simple yet fundamental mathematical property that we prove under rather general assumptions. The validity of this property allows one to determine efficiently the correct order of markers by computing the minimum spanning tree of an associated graph. Our empirical studies obtained on genotyping data for three mapping populations of barley (Hordeum vulgare), as well as extensive simulations on synthetic data, show that our algorithm consistently outperforms the best available methods in the literature, particularly when the input data are noisy or incomplete. The software implementing our algorithm is available in the public domain as a web tool under the name MSTmap.

Long non-coding (lnc) RNAs are numerous and found throughout the mammalian genome, and many are thought to be involved in the regulation of gene expression. However, the majority remain relatively uncharacterised and of uncertain function making the use of model systems to uncover their mode of action valuable. Imprinted lncRNAs target and recruit epigenetic silencing factors to a cluster of imprinted genes on the same chromosome, making them one of the best characterized lncRNAs for silencing distant genes in cis. In this study we examined silencing of the distant imprinted gene Slc22a3 by the lncRNA Airn in the Igf2r imprinted cluster in mouse. Previously we proposed that imprinted lncRNAs may silence distant imprinted genes by disrupting promoter-enhancer interactions by being transcribed through the enhancer, which we called the enhancer interference hypothesis. Here we tested this hypothesis by first using allele-specific chromosome conformation capture (3C) to detect interactions between the Slc22a3 promoter and the locus of the Airn lncRNA that silences it on the paternal chromosome. In agreement with the model, we found interactions enriched on the maternal allele across the entire Airn gene consistent with multiple enhancer-promoter interactions. Therefore, to test the enhancer interference hypothesis we devised an approach to delete the entire Airn gene. However, the deletion showed that there are no essential enhancers for Slc22a2, Pde10a and Slc22a3 within the Airn gene, strongly indicating that the Airn RNA rather than its transcription is responsible for silencing distant imprinted genes. Furthermore, we found that silent imprinted genes were covered with large blocks of H3K27me3 on the repressed paternal allele. Therefore we propose an alternative hypothesis whereby the chromosome interactions may initially guide the lncRNA to target imprinted promoters and recruit repressive chromatin, and that these interactions are lost once silencing is established. [ABSTRACT FROM AUTHOR]

Y chromosomes often contain amplified genes which can increase dosage of male fertility genes and counteract degeneration via gene conversion. Here we identify genes with increased copy number on both X and Y chromosomes in various species of Drosophila, a pattern that has previously been associated with sex chromosome drive involving the Slx and Sly gene families in mice. We show that recurrent X/Y co-amplification appears to be an important evolutionary force that has shaped gene content evolution of sex chromosomes in Drosophila. We also demonstrate that convergent acquisition and amplification of testis expressed gene families are common on Drosophila sex chromosomes, and especially on recently formed ones, and we carefully characterize one putative novel X/Y co-amplification system. We find that co-amplification of the S-Lap1/GAPsec gene pair on both the X and the Y chromosome occurred independently several times in members of the D. obscura group, where this normally autosomal gene pair is sex-linked due to a sex chromosome—autosome fusion. We explore several evolutionary scenarios that would explain this pattern of co-amplification. Investigation of gene expression and short RNA profiles at the S-Lap1/GAPsec system suggest that, like Slx/Sly in mice, these genes may be remnants of a cryptic sex chromosome drive system, however additional transgenic experiments will be necessary to validate this model. Regardless of whether sex chromosome drive is responsible for this co-amplification, our findings suggest that recurrent gene duplications between X and Y sex chromosomes could have a widespread effect on genomic and evolutionary patterns, including the epigenetic regulation of sex chromosomes, the distribution of sex-biased genes, and the evolution of hybrid sterility. [ABSTRACT FROM AUTHOR]

The article reports that Wnts are secreted, lipidated glycoproteins that are essential for cell–cell communication in development and tissue homeostasis throughout metazoans. The W in Wnt comes from the wingless (wg) gene, which is required for proper formation of most tissues and appendages in Drosophila.

Y chromosomes are widely believed to evolve from a normal autosome through a process of massive gene loss (with preservation of some male genes), shaped by sex-antagonistic selection and complemented by occasional gains of male-related genes. The net result of these processes is a male-specialized chromosome. This might be expected to be an irreversible process, but it was found in 2005 that the Drosophila pseudoobscura Y chromosome was incorporated into an autosome. Y chromosome incorporations have important consequences: a formerly male-restricted chromosome reverts to autosomal inheritance, and the species may shift from an XY/XX to X0/XX sex-chromosome system. In order to assess the frequency and causes of this phenomenon we searched for Y chromosome incorporations in 400 species from Drosophila and related genera. We found one additional large scale event of Y chromosome incorporation, affecting the whole montium subgroup (40 species in our sample); overall 13% of the sampled species (52/400) have Y incorporations. While previous data indicated that after the Y incorporation the ancestral Y disappeared as a free chromosome, the much larger data set analyzed here indicates that a copy of the Y survived as a free chromosome both in montium and pseudoobscura species, and that the current Y of the pseudoobscura lineage results from a fusion between this free Y and the neoY. The 400 species sample also showed that the previously suggested causal connection between X-autosome fusions and Y incorporations is, at best, weak: the new case of Y incorporation (montium) does not have X-autosome fusion, whereas nine independent cases of X-autosome fusions were not followed by Y incorporations. Y incorporation is an underappreciated mechanism affecting Y chromosome evolution; our results show that at least in Drosophila it plays a relevant role and highlight the need of similar studies in other groups. [ABSTRACT FROM AUTHOR]

Two-component signaling systems (TCS) regulate bacterial responses to environmental signals through the process of protein phosphorylation. Specifically, sensor histidine kinases (SK) recognize signals and propagate the response via phosphorylation of a cognate response regulator (RR) that functions to initiate transcription of specific genes. Signaling within a single TCS is remarkably specific and cross-talk between TCS is limited. However, regulation of the flow of information through complex signaling networks that include closely related TCS remains largely unknown. Additionally, many bacteria utilize multi-component signaling networks which provide additional genetic and biochemical interactions that must be regulated for signaling fidelity, input and output specificity, and phosphorylation kinetics. Here we describe the characterization of an NtrC-like RR that participates in regulation of Type-IV pilus-dependent motility of Myxococcus xanthus and is thus named NmpR, trC odulator of ili egulator. A complex multi-component signaling system including NmpR was revealed by suppressor mutations that restored motility to cells lacking PilR, an evolutionarily conserved RR required for expression of pilA encoding the major Type-IV pilus monomer found in many bacterial species. The system contains at least four signaling proteins: a SK with a protoglobin sensor domain (NmpU), a hybrid SK (NmpS), a phospho-sink protein (NmpT), and an NtrC-like RR (NmpR). We demonstrate that ΔpilR bypass suppressor mutations affect regulation of the NmpRSTU multi-component system, such that NmpR activation is capable of restoring expression of pilA in the absence of PilR. Our findings indicate that pilus gene expression in M. xanthus is regulated by an extended network of TCS which interact to refine control of pilus function. [ABSTRACT FROM AUTHOR]

Multipotent neural crest (NC) progenitors generate an astonishing array of derivatives, including neuronal, skeletal components and pigment cells (chromatophores), but the molecular mechanisms allowing balanced selection of each fate remain unknown. In zebrafish, melanocytes, iridophores and xanthophores, the three chromatophore lineages, are thought to share progenitors and so lend themselves to investigating the complex gene regulatory networks (GRNs) underlying fate segregation of NC progenitors. Although the core GRN governing melanocyte specification has been previously established, those guiding iridophore and xanthophore development remain elusive. Here we focus on the iridophore GRN, where mutant phenotypes identify the transcription factors Sox10, Tfec and Mitfa and the receptor tyrosine kinase, Ltk, as key players. Here we present expression data, as well as loss and gain of function results, guiding the derivation of an initial iridophore specification GRN. Moreover, we use an iterative process of mathematical modelling, supplemented with a Monte Carlo screening algorithm suited to the qualitative nature of the experimental data, to allow for rigorous predictive exploration of the GRN dynamics. Predictions were experimentally evaluated and testable hypotheses were derived to construct an improved version of the GRN, which we showed produced outputs consistent with experimentally observed gene expression dynamics. Our study reveals multiple important regulatory features, notably a sox10-dependent positive feedback loop between tfec and ltk driving iridophore specification; the molecular basis of sox10 maintenance throughout iridophore development; and the cooperation between sox10 and tfec in driving expression of pnp4a, a key differentiation gene. We also assess a candidate repressor of mitfa, a melanocyte-specific target of sox10. Surprisingly, our data challenge the reported role of Foxd3, an established mitfa repressor, in iridophore regulation. Our study builds upon our previous systems biology approach, by incorporating physiologically-relevant parameter values and rigorous evaluation of parameter values within a qualitative data framework, to establish for the first time the core GRN guiding specification of the iridophore lineage. [ABSTRACT FROM AUTHOR]

Cyanobacteria are a monophyletic phylogenetic group of global importance and have received considerable attention as potential host organisms for the renewable synthesis of chemical bulk products from atmospheric CO2. The cyanobacterial phylum exhibits enormous metabolic diversity with respect to morphology, lifestyle and habitat. As yet, however, research has mostly focused on few model strains and cyanobacterial diversity is insufficiently understood. In this respect, the increasing availability of fully sequenced bacterial genomes opens new and unprecedented opportunities to investigate the genetic inventory of organisms in the context of their pan-genome. Here, we seek understand cyanobacterial diversity using a comparative genome analysis of 77 fully sequenced and assembled cyanobacterial genomes. We use phylogenetic profiling to analyze the co-occurrence of clusters of likely ortholog genes (CLOGs) and reveal novel functional associations between CLOGs that are not captured by co-localization of genes. Going beyond pair-wise co-occurrences, we propose a network approach that allows us to identify modules of co-occurring CLOGs. The extracted modules exhibit a high degree of functional coherence and reveal known as well as previously unknown functional associations. We argue that the high functional coherence observed for the modules is a consequence of the similar-yet-diverse nature of cyanobacteria. Our approach highlights the importance of a multi-strain analysis to understand gene functions and environmental adaptations, with implications beyond the cyanobacterial phylum. The analysis is augmented with a simple toolbox that facilitates further analysis to investigate the co-occurrence neighborhood of specific CLOGs of interest. [ABSTRACT FROM AUTHOR]

A common occurrence in metazoan development is the rise of multiple tissues/organs from a single uniform precursor field. One example is the anterior forebrain of vertebrates, which produces the eyes, hypothalamus, diencephalon, and telencephalon. Another instance is the Drosophila wing disc, which generates the adult wing blade, the hinge, and the thorax. Gene regulatory networks (GRNs) that are comprised of signaling pathways and batteries of transcription factors parcel the undifferentiated field into discrete territories. This simple model is challenged by two observations. First, many GRN members that are thought to control the fate of one organ are actually expressed throughout the entire precursor field at earlier points in development. Second, each GRN can simultaneously promote one of the possible fates choices while repressing the other alternatives. It is therefore unclear how GRNs function to allocate tissue fates if their members are uniformly expressed and competing with each other within the same populations of cells. We address this paradigm by studying fate specification in the Drosophila eye-antennal disc. The disc, which begins its development as a homogeneous precursor field, produces a number of adult structures including the compound eyes, the ocelli, the antennae, the maxillary palps, and the surrounding head epidermis. Several selector genes that control the fates of the eye and antenna, respectively, are first expressed throughout the entire eye-antennal disc. We show that during early stages, these genes are tasked with promoting the growth of the entire field. Upon segregation to distinct territories within the disc, each GRN continues to promote growth while taking on the additional roles of promoting distinct primary fates and repressing alternate fates. The timing of both expression pattern restriction and expansion of functional duties is an elemental requirement for allocating fates within a single field. [ABSTRACT FROM AUTHOR]

In this article, the author discusses the study on gene gains, losses and rearrangements on the evolutionary route of Saccharomyces cerevisiae genomes by Gordon and colleagues. He notes that the authors chose a manual approach to reconstruct the ancestral genomes despite the availability of rapid algorithms. He says that numerous of the structural analyses could be repeated for all data species to permit assessment of the quantitative parallels and differences across the phylogenetic domain.

The many subcomponents of the human cortex are known to follow an anatomical pattern and functional relationship that appears to be highly conserved between individuals. This suggests that this pattern and the relationship among cortical regions are important for cortical function and likely shaped by genetic factors, although the degree to which genetic factors contribute to this pattern is unknown. We assessed the genetic relationships among 12 cortical surface areas using brain images and genotype information on 2,364 unrelated individuals, brain images on 466 twin pairs, and transcriptome data on 6 postmortem brains in order to determine whether a consistent and biologically meaningful pattern could be identified from these very different data sets. We find that the patterns revealed by each data set are highly consistent (p<10−3), and are biologically meaningful on several fronts. For example, close genetic relationships are seen in cortical regions within the same lobes and, the frontal lobe, a region showing great evolutionary expansion and functional complexity, has the most distant genetic relationship with other lobes. The frontal lobe also exhibits the most distinct expression pattern relative to the other regions, implicating a number of genes with known functions mediating immune and related processes. Our analyses reflect one of the first attempts to provide an assessment of the biological consistency of a genetic phenomenon involving the brain that leverages very different types of data, and therefore is not just statistical replication which purposefully use very similar data sets. [ABSTRACT FROM AUTHOR]