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The phenotypic effect of any genetic variant can be altered by variation at other genomic loci. Known as epistasis, these genetic interactions shape the genotype-phenotype map of every species, yet their origins remain poorly understood. To investigate this, we employed high-throughput genome editing to measure the fitness effects of 1,826 naturally polymorphic variants in four strains of Saccharomyces cerevisiae . About 31% of variants affect fitness, of which 24% have strain-specific fitness effects indicative of epistasis. We found that beneficial variants are more likely to exhibit genetic interactions and that these interactions can be mediated by specific traits such as flocculation ability. This work suggests that adaptive evolution will often involve trade-offs where a variant is only beneficial in some genetic backgrounds, potentially explaining why many beneficial variants remain polymorphic. In sum, we provide a framework to understand the factors influencing epistasis with single-nucleotide resolution, revealing widespread epistasis among beneficial variants., Competing Interests: H.B.F. is a coinventor of a patent application describing the CRISPEY approach (application number 16/293,550). S.-A.A.C., A.F.K., and H.B.F. are coinventors of a patent application describing the CRISPEY-BAR approach (application number 63/344,470)., (© 2023 The Authors.)

Background & Aims: Hirschsprung disease (HSCR) is a congenital disorder characterized by the absence of the enteric nervous system (ENS). HSCR potentially involves multiple gene aberrations and displays complex patterns of inheritance. Mutations of the RET gene, encoding the RET receptor tyrosine kinase, play a central role in the pathogenesis of HSCR. Although a wide variety of coding RET mutations have been identified, their pathogenetic significance in vivo has remained largely unclear., Methods: We introduced a HSCR-associated RET missense mutation, RET(S811F), into the corresponding region (S812) of the mouse Ret gene. Pathogenetic impact of Ret(S812F) was assessed by histologic and functional analyses of the ENS and by biochemical analyses. Interactions of the Ret(S812F) allele with HSCR susceptibility genes, the RET9 allele and the Ednrb gene, were examined by genetic crossing in mice., Results: Ret S812F/+ mice displayed intestinal aganglionosis (incidence, 50%) or hypoganglionosis (50%), impaired differentiation of enteric neurons, defecation deficits, and increased lethality. Biochemical analyses revealed that Ret(S811F) protein was not only kinase-deficient but also abrogated function of wild-type RET in trans. Moreover, the Ret(S812F) allele interacted with other HSCR susceptibility genes and caused intestinal aganglionosis with full penetrance., Conclusions: This study demonstrates that a single RET missense mutation alone induces intestinal aganglionosis via a dominant-negative mechanism. The Ret S812F/+ mice model HSCR displays dominant inheritance with incomplete penetrance and serves as a valuable platform for better understanding of the pathogenetic mechanism of HSCR caused by coding RET mutations., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Cells must quickly respond and efficiently adapt to environmental changes. The yeast Saccharomyces cerevisiae has multiple pathways that respond to specific environmental insults, as well as a generic stress response program. The later is regulated by two transcription factors, Msn2 and Msn4, that integrate information from upstream pathways to produce fast, tunable, and robust response to different environmental changes. To understand this integration, we employed a systematic approach to genetically dissect the contribution of various cellular pathways to Msn2/4 regulation under a range of stress and growth conditions. We established a high-throughput liquid handling and automated flow cytometry system and measured GFP levels in 68 single-knockout and 1,566 double-knockout strains that carry an HSP12-GFP allele as a reporter for Msn2/4 activity. Based on the expression of this Msn2/4 reporter in five different conditions, we identified numerous genetic and epistatic interactions between different components in the network upstream to Msn2/4. Our analysis gains new insights into the functional specialization of the RAS paralogs in the repression of stress response and identifies a three-way crosstalk between the Mediator complex, the HOG MAPK pathway, and the cAMP/PKA pathway. [ABSTRACT FROM AUTHOR]

Synthetic dosage lethality (SDL) denotes a genetic interaction between two genes whereby the underexpression of gene A combined with the overexpression of gene B is lethal. SDLs offer a promising way to kill cancer cells by inhibiting the activity of SDL partners of activated oncogenes in tumors, which are often difficult to target directly. As experimental genome-wide SDL screens are still scarce, here we introduce a network-level computational modeling framework that quantitatively predicts human SDLs in metabolism. For each enzyme pair (A, B) we systematically knock out the flux through A combined with a stepwise flux increase through B and search for pairs that reduce cellular growth more than when either enzyme is perturbed individually. The predictive signal of the emerging network of 12,000 SDLs is demonstrated in five different ways. (i) It can be successfully used to predict gene essentiality in shRNA cancer cell line screens. Moving to clinical tumors, we show that (ii) SDLs are significantly underrepresented in tumors. Furthermore, breast cancer tumors with SDLs active (iii) have smaller sizes and (iv) result in increased patient survival, indicating that activation of SDLs increases cancer vulnerability. Finally, (v) patient survival improves when multiple SDLs are present, pointing to a cumulative effect. This study lays the basis for quantitative identification of cancer SDLs in a model-based mechanistic manner. The approach presented can be used to identify SDLs in species and cell types in which "omics" data necessary for data-driven identification are missing. [ABSTRACT FROM AUTHOR]

Partial resistance genes often need to be 'pyramided' into a crop cultivar to obtain commercially acceptable levels of disease resistance. Analysis of data from four different wheat mapping populations, segregating for partial resistance to four contrasting foliar pathogens, showed a diminishing benefit to disease control from increasing the numbers of resistance loci in wheat lines. To test whether a general function could describe the efficacy benefit from pyramiding, a simple multiplicative survival model ( MSM) was used to predict disease severities on mapping population lines carrying various combinations of two, three or four resistance loci. The effectiveness of each resistance locus was expressed as the disease severity in lines carrying resistance alleles at one locus, as a proportion of the severity in lines carrying no detectable resistance alleles. The predicted severity from any given combination of multiple resistance loci was calculated as the product of the proportional severities for the relevant single loci. A regression line fitted to transformed observed against predicted values explained 93% of the variation, with a slope and intercept not significantly different from 1 and 0, respectively. MSM may therefore provide a simple method to test contrasting types of partial resistance and search for synergistic combinations. The analysis suggests that diminishing returns are a general feature of partial resistance to foliar pathogens in wheat, a finding that is likely to apply to other crop pathosystems. Identifying and combining ever more QTL is likely to provide limited gains. The consequences of these findings for QTL analysis are described. [ABSTRACT FROM AUTHOR]

Genetic interaction screens have been applied with great success in several organisms to study gene function and the genetic architecture of the cell. However, most studies have been performed under optimal growth conditions even though many functional interactions are known to occur under specific cellular conditions. In this study, we have performed a large-scale genetic interaction analysis in Saccharomyces cerevisiae involving approximately 49 × 1,200 double mutants in the presence of five different stress conditions, including osmotic, oxidative and cell wall-altering stresses. This resulted in the generation of a differential E-MAP (or dE-MAP) comprising over 250,000 measurements of conditional interactions. We found an extensive number of conditional genetic interactions that recapitulate known stress-specific functional associations. Furthermore, we have also uncovered previously unrecognized roles involving the phosphatase regulator Bud14, the histone methylation complex COMPASS and membrane trafficking complexes in modulating the cell wall integrity pathway. Finally, the osmotic stress differential genetic interactions showed enrichment for genes coding for proteins with conditional changes in phosphorylation but not for genes with conditional changes in gene expression. This suggests that conditional genetic interactions are a powerful tool to dissect the functional importance of the different response mechanisms of the cell. [ABSTRACT FROM AUTHOR]

Signaling pathways enable cells to sense and respond to their environment. Many cellular signaling strategies are conserved from fungi to humans, yet their activity and phenotypic consequences can vary extensively among individuals within a species. A systematic assessment of the impact of naturally occurring genetic variation on signaling pathways remains to be conducted. In S. cerevisiae, both response and resistance to stressors that activate signaling pathways differ between diverse isolates. Here, we present a quantitative trait locus (QTL) mapping approach that enables us to identify genetic variants underlying such phenotypic differences across the genetic and phenotypic diversity of S. cerevisiae. Using a Round-robin cross between twelve diverse strains, we identified QTL that influence phenotypes critically dependent on MAPK signaling cascades. Genetic variants under these QTL fall within MAPK signaling networks themselves as well as other interconnected signaling pathways. Finally, we demonstrate how the mapping results from multiple strain background can be leveraged to narrow the search space of causal genetic variants. [ABSTRACT FROM AUTHOR]

Many complex human diseases are highly sexually dimorphic, suggesting a potential contribution of the X chromosome to disease risk. However, the X chromosome has been neglected or incorrectly analyzed in most genome-wide association studies (GWAS). We present tailored analytical methods and software that facilitate X-wide association studies (XWAS), which we further applied to reanalyze data from 16 GWAS of different autoimmune and related diseases (AID). We associated several X-linked genes with disease risk, among which (1) ARHGEF6 is associated with Crohn's disease and replicated in a study of ulcerative colitis, another inflammatory bowel disease (IBD). Indeed, ARHGEF6 interacts with a gastric bacterium that has been implicated in IBD. (2) CENPI is associated with three different AID, which is compelling in light of known associations with AID of autosomal genes encoding centromere proteins, as well as established autosomal evidence of pleiotropy between autoimmune diseases. (3) We replicated a previous association of FOXP3, a transcription factor that regulates T-cell development and function, with vitiligo; and (4) we discovered that C1GALT1C1 exhibits sex-specific effect on disease risk in both IBDs. These and other X-linked genes that we associated with AID tend to be highly expressed in tissues related to immune response, participate in major immune pathways, and display differential gene expression between males and females. Combined, the results demonstrate the importance of the X chromosome in autoimmunity, reveal the potential of extensive XWAS, even based on existing data, and provide the tools and incentive to properly include the X chromosome in future studies. [ABSTRACT FROM AUTHOR]

The human ATRX gene encodes hATRX, a chromatin-remodeling protein harboring an helicase/ATPase and ADD domains. The ADD domain has two zinc fingers that bind to histone tails and mediate hATRX binding to chromatin. dAtrx, the putative ATRX homolog in Drosophila melanogaster, has a conserved helicase/ATPase domain but lacks the ADD domain. A bioinformatic search of the Drosophila genome using the human ADD sequence allowed us to identify the CG8290 annotated gene, which encodes three ADD harboring- isoforms generated by alternative splicing. This Drosophila ADD domain is highly similar in structure and in the amino acids which mediate the histone tail contacts to the ADD domain of hATRX as shown by 3D modeling. Very recently the CG8290 annotated gene has been named dadd1. We show through pull-down and CoIP assays that the products of the dadd1 gene interact physically with dAtrxL and HP1a and all of them mainly co-localize in the chromocenter, although euchromatic localization can also be observed through the chromosome arms. We confirm through ChIP analyses that these proteins are present in vivo in the same heterochromatic regions. The three isoforms are expressed throughout development. Flies carrying transheterozygous combinations of the dadd1 and atrx alleles are semi-viable and have different phenotypes including the appearance of melanotic masses. Interestingly, the dAdd1-b and c isoforms have extra domains, such as MADF, which suggest newly acquired functions of these proteins. These results strongly support that, in Drosophila, the atrx gene diverged and that the dadd1-encoded proteins participate with dAtrx in some cellular functions such as heterochromatin maintenance. [ABSTRACT FROM AUTHOR]

Breast cancer is the most common cancer and the second leading cause of death in women worldwide. The disease is caused by a combination of genetic, environmental, lifestyle, and reproductive risk factors. Linkage and family-based studies have identified many pathological germline mutations, which account for around 20% of the genetic risk of familial breast cancer. In recent years, single nucleotide polymorphism-based genetic association studies, especially genome-wide association studies (GWASs), have been very successful in uncovering low-penetrance common variants associated with breast cancer risk. These common variants alone may explain up to an additional 30% of the familial risk of breast cancer. With the advent of available genetic resources and growing collaborations among researchers across the globe, the much needed large sample size to capture variants with small effect sizes and low population frequencies is being addressed, and hence many more common variants are expected to be discovered in the coming days. Here, major GWASs conducted for breast cancer predisposition and prognosis until 2013 are summarized. Few studies investigating other forms of genetic variations contributing to breast cancer predisposition and disease outcomes are also discussed. Finally, the potential utility of the GWAS-identified variants in disease risk models and some future perspectives are presented. © 2014 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Understanding the genetic basis of complex quantitative traits is a central problem in evolutionary biology, particularly for traits that may lead to adaptations in natural populations. The annual and perennial ecotypes of Mimulus guttatus provide an excellent experimental system for characterizing the genetic components of population divergence. The 2 life history ecotypes coexist throughout the geographic range. Focusing on population differences in life history traits, I examined the strength and direction of pairwise epistatic interactions between 2 target chromosomal regions (DIV1 and DIV2) when singly and cointrogressed into the alternate population’s genetic background. I measured a suite of flowering and vegetative traits related to life history divergence in 804 plants from 18 reciprocal near-isogenic lines. I detected pleiotropic main effects for the DIV1 QTL in both genetic backgrounds and weaker main effects of the DIV2 QTL, primarily in the perennial background. Many of the traits showed epistatic interactions between alleles at the DIV1 and DIV2 QTL. Finally, for many traits, the magnitude of effect size was greater in the perennial background. I evaluate these results in the context of their potential role in population divergence in M. guttatus and adaptive evolution in natural populations. [ABSTRACT FROM PUBLISHER]

Natural variation for primary root growth response to high Ca stress in Arabidopsis thaliana was studied by screening a series of accessions (ecotypes) under high Calcium (40 mM CaCl2 ) conditions. The genetic basis of this variation was further investigated by QTL analysis using recombinant inbred lines from Landsberg erecta (Ler)×Cape Verde Islands (Cvi) cross. Four QTLs were identified in chromosome 1, 2 and 5,and named response to high Calcium (RHCA) 1–4. The three QTLs (RHCA1, RHCA2 and RHCA4) were further confirmed by analysis of near isogenic lines harboring Cvi introgression fragments in Ler background. Real-time PCR analysis showed that several genes associated with high Ca response including SMT1 and XHT25 have changed expression pattern between Ler and near isogenic lines. These results were useful for detecting molecular mechanisms of plants for high Ca adaption. [ABSTRACT FROM AUTHOR]

Background Interactions between aboveground and belowground terrestrial communities are often mediated by plants, with soil organisms interacting via the roots and aboveground organisms via the shoots and leaves. Many studies now show that plant genetics can drive changes in the structure of both above and belowground communities; however, the role of plant genetic variation in mediating aboveground-belowground interactions is still unclear. We used an earthworm-plant-aphid model system with two aphid species (Aphis fabae and Acyrthosiphon pisum) to test the effect of host-plant (Vicia faba) genetic variation on the indirect interaction between the belowground earthworms (Eisenia veneta) on the aboveground aphid populations. Results Our data shows that host-plant variety mediated an indirect ecological effect of earthworms on generalist black bean aphids (A. fabae), with earthworms increasing aphid growth rate in three plant varieties but decreasing it in another variety. We found no effect of earthworms on the second aphid species, the pea aphid (A. pisum), and no effect of competition between the aphid species. Plant biomass was increased when earthworms were present, and decreased when A. pisum was feeding on the plant (mediated by plant variety). Although A. fabae aphids were influenced by the plants and worms, they did not, in turn, alter plant biomass. Conclusions Previous work has shown inconsistent effects of earthworms on aphids, but we suggest these differences could be explained by plant genetic variation and variation among aphid species. This study demonstrates that the outcome of belowground-aboveground interactions can be mediated by genetic variation in the host-plant, but depends on the identity of the species involved. [ABSTRACT FROM AUTHOR]

Background: Age changes in expression of inflammatory, synaptic, and neurotrophic genes are not well characterized during human brain development and senescence. Knowing these changes may elucidate structural, metabolic, and functional brain processes over the lifespan, as well vulnerability to neurodevelopmental or neurodegenerative diseases. Hypothesis: Expression levels of inflammatory, synaptic, and neurotrophic genes in the human brain are coordinated over the lifespan and underlie changes in phenotypic networks or cascades. Methods: We used a large-scale microarray dataset from human prefrontal cortex, BrainCloud, to quantify age changes over the lifespan, divided into Development (0 to 21 years, 87 brains) and Aging (22 to 78 years, 144 brains) intervals, in transcription levels of 39 genes. Results: Gene expression levels followed different trajectories over the lifespan. Many changes were intercorrelated within three similar groups or clusters of genes during both Development and Aging, despite different roles of the gene products in the two intervals. During Development, changes were related to reported neuronal loss, dendritic growth and pruning, and microglial events; TLR4, IL1R1, NFKB1, MOBP, PLA2G4A, and PTGS2 expression increased in the first years of life, while expression of synaptic genes GAP43 and DBN1 decreased, before reaching plateaus. During Aging, expression was upregulated for potentially pro-inflammatory genes such as NFKB1, TRAF6, TLR4, IL1R1, TSPO, and GFAP, but downregulated for neurotrophic and synaptic integrity genes such as BDNF, NGF, PDGFA, SYN, and DBN1. Conclusions: Coordinated changes in gene transcription cascades underlie changes in synaptic, neurotrophic, and inflammatory phenotypic networks during brain Development and Aging. Early postnatal expression changes relate to neuronal, glial, and myelin growth and synaptic pruning events, while late Aging is associated with pro-inflammatory and synaptic loss changes. Thus, comparable transcriptional regulatory networks that operate throughout the lifespan underlie different phenotypic processes during Aging compared to Development. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value<1 · 10−8 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30,011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS. [ABSTRACT FROM AUTHOR]

Despite extensive theory, little is known about the empirical accumulation and evolutionary timing of mutations that contribute to speciation. Here we combined QTL (Quantitative Trait Loci) analyses of reproductive isolation, with information on species evolutionary relationships, to reconstruct the order and timing of mutations contributing to reproductive isolation between three plant (Solanum) species. To evaluate whether reproductive isolation QTL that appear to coincide in more than one species pair are homologous, we used cross-specific tests of allelism and found evidence for both homologous and lineage-specific (non-homologous) alleles at these co-localized loci. These data, along with isolation QTL unique to single species pairs, indicate that >85% of isolation-causing mutations arose later in the history of divergence between species. Phylogenetically explicit analyses of these data support non-linear models of accumulation of hybrid incompatibility, although the specific best-fit model differs between seed (pairwise interactions) and pollen (multi-locus interactions) sterility traits. Our findings corroborate theory that predicts an acceleration (‘snowballing’) in the accumulation of isolation loci as lineages progressively diverge, and suggest different underlying genetic bases for pollen versus seed sterility. Pollen sterility in particular appears to be due to complex genetic interactions, and we show this is consistent with a snowball model where later arising mutations are more likely to be involved in pairwise or multi-locus interactions that specifically involve ancestral alleles, compared to earlier arising mutations. [ABSTRACT FROM AUTHOR]

The construction and analysis of networks is increasingly widespread in biological research. We have developed esyN (“easy networks”) as a free and open source tool to facilitate the exchange of biological network models between researchers. esyN acts as a searchable database of user-created networks from any field. We have developed a simple companion web tool that enables users to view and edit networks using data from publicly available databases. Both normal interaction networks (graphs) and Petri nets can be created. In addition to its basic tools, esyN contains a number of logical templates that can be used to create models more easily. The ability to use previously published models as building blocks makes esyN a powerful tool for the construction of models and network graphs. Users are able to save their own projects online and share them either publicly or with a list of collaborators. The latter can be given the ability to edit the network themselves, allowing online collaboration on network construction. esyN is designed to facilitate unrestricted exchange of this increasingly important type of biological information. Ultimately, the aim of esyN is to bring the advantages of Open Source software development to the construction of biological networks. [ABSTRACT FROM AUTHOR]

We have achieved a residue-level resolution of genetic interaction mapping - a technique that measures how the function of one gene is affected by the alteration of a second gene - by analyzing point mutations. Here, we describe how to interpret point mutant genetic interactions, and outline key applications for the approach, including interrogation of protein interaction interfaces and active sites, and examination of post-translational modifications. Genetic interaction analysis has proven effective for characterizing cellular processes; however, to date, systematic high-throughput genetic interaction screens have relied on gene deletions or knockdowns, which limits the resolution of gene function analysis and poses problems for multifunctional genes. Our point mutant approach addresses these issues, and further provides a tool for in vivo structure-function analysis that complements traditional biophysical methods. We also discuss the potential for genetic interaction mapping of point mutations in human cells and its application to personalized medicine. [ABSTRACT FROM AUTHOR]

Background Global noise in gene expression and chromosome duplication during cell-cycle progression cause inevitable fluctuations in the effective number of copies of gene networks in cells. These indirect and direct alterations of network copy numbers have the potential to change the output or activity of a gene network. For networks whose specific activity levels are crucial for optimally maintaining cellular functions, cells need to implement mechanisms to robustly compensate the effects of network dosage fluctuations. Results Here, we determine the necessary conditions for generalized N-component gene networks to be network-dosage compensated and show that the compensation mechanism can robustly operate over large ranges of gene expression levels. Furthermore, we show that the conditions that are necessary for network-dosage compensation are also sufficient. Finally, using genome-wide protein-DNA and protein-protein interaction data, we search the yeast genome for the abundance of specific dosage-compensation motifs and show that a substantial percentage of the natural networks identified contain at least one dosage-compensation motif. Conclusions Our results strengthen the hypothesis that the special network topologies that are necessary for network-dosage compensation may be recurrent network motifs in eukaryotic genomes and therefore may be an important design principle in gene network assembly in cells. [ABSTRACT FROM AUTHOR]

Pathways are a universal paradigm for functionally describing cellular processes. Even though advances in high-throughput data generation have transformed biology, the core of our biological understanding, and hence data interpretation, is still predicated on human-defined pathways. Here, we introduce an unbiased, pathway structure for genome-scale metabolic networks defined based on principles of parsimony that do not mimic canonical human-defined textbook pathways. Instead, these minimal pathways better describe multiple independent pathway-associated biomolecular interaction datasets suggesting a functional organization for metabolism based on parsimonious use of cellular components. We use the inherent predictive capability of these pathways to experimentally discover novel transcriptional regulatory interactions in Escherichia coli metabolism for three transcription factors, effectively doubling the known regulatory roles for Nac and MntR. This study suggests an underlying and fundamental principle in the evolutionary selection of pathway structures; namely, that pathways may be minimal, independent, and segregated. [ABSTRACT FROM AUTHOR]

Background: Friedreich ataxia (FRDA), the most common autosomal recessive ataxia disorder, is caused by a dynamic GAA repeat expansion mutation within intron 1 of FXN gene, resulting in down-regulation of frataxin expression. Studies of cell and mouse models have revealed a role for the mismatch repair (MMR) MutS-heterodimer complexes and the PMS2 component of the MutLα complex in the dynamics of intergenerational and somatic GAA repeat expansions: MSH2, MSH3 and MSH6 promote GAA repeat expansions, while PMS2 inhibits GAA repeat expansions. Methodology/Principal Findings: To determine the potential role of the other component of the MutLα complex, MLH1, in GAA repeat instability in FRDA, we have analyzed intergenerational and somatic GAA repeat expansions from FXN transgenic mice that have been crossed with Mlh1 deficient mice. We find that loss of Mlh1 activity reduces both intergenerational and somatic GAA repeat expansions. However, we also find that loss of either Mlh1 or Pms2 reduces FXN transcription, suggesting different mechanisms of action for Mlh1 and Pms2 on GAA repeat expansion dynamics and regulation of FXN transcription. Conclusions/Significance: Both MutLα components, PMS2 and MLH1, have now been shown to modify the molecular phenotype of FRDA. We propose that upregulation of MLH1 or PMS2 could be potential FRDA therapeutic approaches to increase FXN transcription. [ABSTRACT FROM AUTHOR]

The impact of cell cycle on plant immunity was indicated by the enhancement of disease resistance with overexpressing OSD1 and UVI4 genes that are negative regulators of cell cycle controller APC (anaphase promoting complex). CPR5 is another gene that is implicated in cell cycle regulation and plant immunity, but its mode of action is not known. Here we report the analysis of genetic requirement for the function of UVI4 and OSD1 in cell cycle progression control and in particular the involvement of CPR5 in this regulation. We show that the APC activator CCS52A1 partially mediates the function of OSD1 and UVI4 in female gametophyte development. We found that the cpr5 mutation suppresses the endoreduplication defect in the uvi4 single mutant and partially rescued the gametophyte development defect in the osd1 uvi4 double mutant while the uvi4 mutation enhances the cpr5 defects in trichome branching and plant disease resistance. In addition, cyclin B1 genes CYCB1;1, CYCB1;2, and CYCB1;4 are upregulated in cpr5. Therefore, CPR5 has a large role in cell cycle regulation and this role has a complex interaction with that of UVI4 and OSD1. This study further indicates an intrinsic link between plant defense responses and cell cycle progression. [ABSTRACT FROM AUTHOR]

The measurement of any nonchromosomal genetic contribution to the heritability of a trait is often confounded by the inability to control both the chromosomal and nonchromosomal information in a population. We have designed a unique system in yeast where we can control both sources of information so that the phenotype of a single chromosomal polymorphism can be measured in the presence of different cytoplasmic elements. With this system, we have shown that both the source of the mitochondrial genome and the presence or absence of a dsRNA virus influence the phenotype of chromosomal variants that affect the growth of yeast. Moreover, by considering this nonchromosomal information that is passed from parent to offspring and by allowing chromosomal and nonchromosomal information to exhibit nonadditive interactions, we are able to account for much of the heritability of growth traits. Taken together, our results highlight the importance of including all sources of heritable information in genetic studies and suggest a possible avenue of attack for finding additional missing heritability. [ABSTRACT FROM AUTHOR]

Background: Reported odds ratios and population attributable fractions (PAF) for late-onset Alzheimer’s disease (LOAD) risk loci (BIN1, ABCA7, CR1, MS4A4E, CD2AP, PICALM, MS4A6A, CD33, and CLU) come from clinically ascertained samples. Little is known about the combined PAF for these LOAD risk alleles and the utility of these combined markers for case–control prediction. Here we evaluate these loci in a large population-based sample to estimate PAF and explore the effects of additive and nonadditive interactions on LOAD status prediction performance. Methods: 2419 samples from the Cache County Memory Study were genotyped for APOE and nine LOAD risk loci from AlzGene.org. We used logistic regression and receiver operator characteristic analysis to assess the LOAD status prediction performance of these loci using additive and nonadditive models and compared odds ratios and PAFs between AlzGene.org and Cache County. Results: Odds ratios were comparable between Cache County and AlzGene.org when identical single nucleotide polymorphisms were genotyped. PAFs from AlzGene.org ranged from 2.25% to 37%; those from Cache County ranged from .05% to 20%. Including non-APOE alleles significantly improved LOAD status prediction performance (area under the curve = .80) over APOE alone (area under the curve = .78) when not constrained to an additive relationship (p < .03). We identified potential allelic interactions (p values uncorrected): CD33-MS4A4E (synergy factor = 5.31; p < .003) and CLU-MS4A4E (synergy factor = 3.81; p < .016). Conclusions: Although nonadditive interactions between loci significantly improve diagnostic ability, the improvement does not reach the desired sensitivity or specificity for clinical use. Nevertheless, these results suggest that understanding gene–gene interactions may be important in resolving Alzheimer’s disease etiology. [Copyright &y& Elsevier]

Highlights: [•] New model systems address evolution in changing environments. [•] The environment can have a dramatic effect on genetic epistasis. [•] Variable selection and evolutionary constraint are key to understanding regulatory systems. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate whether the genetic, epigenetic and environmental factors that give rise to supernumeraries in the maxillary incisor region and larger dimensions of the adjacent maxillary incisors are also associated with variations in the morphology of the mandibular incisors. If so, this would contribute to understanding the distribution and interactions of factors during dental development and how these can be modelled. The sample consisted of 34 patients with supernumerary teeth in the maxillary anterior region, matched for gender, age and White Caucasian ethnicity with 34 control subjects. The average ages of the supernumerary and control groups were 12.8 and 12.2 years, respectively. Study models of all subjects were constructed and imaged using a previously validated system. Using custom software, each of the mandibular incisor teeth were measured to obtain 17 parameters from the labial view and 17 from the occlusal view. Principal component analysis (PCA) was used to summarize the measurements into a smaller set representing distinct features of the clinical crowns, followed by a comparison between the supernumerary and control groups using 2-way ANOVA. Seven factors of tooth size of the mandibular central incisors and six factors of the mandibular lateral incisors were identified as major features of the clinical crowns. All parameters of both mandibular incisors were greater in the supernumerary group than in the control, with three of these, located in the incisal and cervical regions of the mandibular lateral incisors, being statistically significantly larger. The findings of this study indicate that the aetiological factors associated with supernumerary teeth in the maxillary anterior region also affect tooth crown dimensions of mandibular incisors. This new evidence enhances several models of the interactions of genetic, epigenetic and environmental components of dental development and supports a multi-model approach to increase understanding of this process and its variations., Competing Interests: The authors declare no conflict of interest.

The natural ends of the linear eukaryotic chromosomes are protected by telomeres, which also play an important role in aging and cancer development. Telomere length varies between species, but it is strictly controlled in all organisms. The process of Telomere Length Maintenance (TLM) involves many pathways, protein complexes and interactions that were first discovered in budding and fission yeast model organisms ( Saccharomyces cerevisiae , Schizosaccharomyces pombe ). In particular, large-scale systematic genetic screens in budding yeast uncovered a network of ≈ 500 genes that, when mutated, cause telomeres to lengthen or to shorten. In contrast, the TLM network in fission yeast remains largely unknown and systematic data is still lacking. In this work we try to close this gap and develop a unified interpretable machine learning framework for TLM gene discovery and phenotype prediction in both species. We demonstrate the utility of our framework in pinpointing the pathways by which TLM homeostasis is maintained and predicting novel TLM genes in fission yeast. The results of this study could be used for better understanding of telomere biology and serve as a step towards the adaptation of computational methods based on telomeric data for human prognosis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Peretz, Kupiec and Sharan.)

Background: Asthma with severe exacerbation is one of the most common causes of hospitalization among young children. Exacerbations are typically triggered by respiratory infections, but the host factors causing recurrent infections and exacerbations in some children are poorly understood. As a result, current treatment options and preventive measures are inadequate., Objective: We sought to identify genetic interaction associated with the development of childhood asthma., Methods: We performed an exhaustive search for pairwise interaction between genetic single nucleotide polymorphisms using 1204 cases of a specific phenotype of early childhood asthma with severe exacerbations in patients aged 2 to 6 years combined with 5328 nonasthmatic controls. Replication was attempted in 3 independent populations, and potential underlying immune mechanisms were investigated in the COPSAC2010 and COPSAC2000 birth cohorts., Results: We found evidence of interaction, including replication in independent populations, between the known childhood asthma loci CDHR3 and GSDMB. The effect of CDHR3 was dependent on the GSDMB genotype, and this interaction was more pronounced for severe and early onset of disease. Blood immune analyses suggested a mechanism related to increased IL-17A production after viral stimulation., Conclusions: We found evidence of interaction between CDHR3 and GSDMB in development of early childhood asthma, possibly related to increased IL-17A response to viral infections. This study demonstrates the importance of focusing on specific disease subtypes for understanding the genetic mechanisms of asthma., (Copyright © 2022 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

Results: Abruption cases were more likely to experience preeclampsia, have shorter gestational age, and deliver infants with lower birthweight compared with controls. Models with MFGI effects provided improved fit than models with only maternal and fetal genotype main effects for SNP rs12530904 ( p -value = 1.2e-04) in calcium/calmodulin-dependent protein kinase [CaM kinase] II beta ( CAMK2B ), and, SNP rs73136795 ( p -value = 1.9e-04) in peroxisome proliferator-activated receptor-gamma ( PPARG ), both MB genes. We identified 320 SNPs in 45 maternally-imprinted genes (including potassium voltage-gated channel subfamily Q member 1 [ KCNQ1 ], neurotrimin [ NTM ], and, ATPase phospholipid transporting 10 A [ ATP10A ]) associated with abruption. Top hits included rs2012323 ( p -value = 1.6E-16) and rs12221520 ( p -value1.3e-13) in KCNQ1 , rs8036892 ( p -value = 9.3E-17) and rs188497582 in ATP10A , rs12589854 ( p -value = 2.9E-11) and rs80203467 ( p -value = 4.6e-11) in maternally expressed 8, small nucleolar RNA host ( MEG8 ), and rs138281088 in solute carrier family 22 member 2 ( SLC22A2 ) ( p -value = 6.8e-9)., Conclusions: We identified novel PA-related maternal-fetal MB gene interactions and imprinting effects that highlight the role of the fetus in PA risk development. Findings can inform mechanistic investigations to understand the pathogenesis of PA.

Understanding how diversity emerges in a single niche is not fully understood. Rugged fitness landscapes and epistasis between beneficial mutations could explain coexistence among emerging lineages. To provide an experimental test of this notion, we investigated epistasis among four pleiotropic mutations in rpoS, mglD, malT, and hfq present in two coexisting lineages that repeatedly fixed in experimental populations of Escherichia coli. The mutations were transferred into the ancestral background individually or in combination of double or triple alleles. The combined competitive fitness of two or three beneficial mutations from the same lineage was consistently lower than the sum of the competitive fitness of single mutants-a clear indication of negative epistasis within lineages. We also found sign epistasis (i.e., the combined fitness of two beneficial mutations lower than the ancestor), not only from two different lineages (i.e., hfq and rpoS) but also from the same lineage (i.e., mglD and malT). The sign epistasis between loci of different lineages indeed indicated a rugged fitness landscape, providing an epistatic explanation for the coexistence of distinct rpoS and hfq lineages in evolving populations. The negative and sign epistasis between beneficial mutations within the same lineage can further explain the order of mutation acquisition. [ABSTRACT FROM AUTHOR]