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Cardiometabolic diseases encompass a range of interrelated conditions that arise from underlying metabolic perturbations precipitated by genetic, environmental, and lifestyle factors. While obesity, dyslipidaemia, smoking, and insulin resistance are major risk factors for cardiometabolic diseases, individuals still present in the absence of such traditional risk factors, making it difficult to determine those at greatest risk of disease. Thus, it is crucial to elucidate the genetic, environmental, and molecular underpinnings to better understand, diagnose, and treat cardiometabolic diseases. Much of this information can be garnered using systems genetics, which takes population-based approaches to investigate how genetic variance contributes to complex traits. Despite the important advances made by human genome-wide association studies (GWAS) in this space, corroboration of these findings has been hampered by limitations including the inability to control environmental influence, limited access to pertinent metabolic tissues, and often, poor classification of diseases or phenotypes. A complementary approach to human GWAS is the utilisation of model systems such as genetically diverse mouse panels to study natural genetic and phenotypic variation in a controlled environment. Here, we review mouse genetic reference panels and the opportunities they provide for the study of cardiometabolic diseases and related traits. We discuss how the post-GWAS era has prompted a shift in focus from discovery of novel genetic variants to understanding gene function. Finally, we highlight key advantages and challenges of integrating complementary genetic and multi-omics data from human and mouse populations to advance biological discovery., Competing Interests: AJ, MS, CG, PM, BD, AC No competing interests declared, (© 2023, Jurrjens et al.)

Introduction: Acute myeloid leukemia (AML) is the most common type of leukemia in adults. However, there is a gap in understanding the molecular basis of the disease, partly because key genes associated with AML have not been extensively explored. In the current study, we aimed to identify genes that have strong association with AML based on a cross-species integrative approach. Methods: We used Weighted Gene Co-Expression Network Analysis (WGCNA) to identify co-expressed gene modules significantly correlated with human AML, and further selected the genes exhibiting a significant difference in expression between AML and healthy mouse. Protein-protein interactions, transcription factors, gene function, genetic regulation, and coding sequence variants were integrated to identify key hub genes in AML. Results: The cross-species approach identified a total of 412 genes associated with both human and mouse AML. Enrichment analysis confirmed an association of these genes with hematopoietic and immune-related functions, phenotypes, processes, and pathways. Further, the integrated analysis approach identified a set of important module genes including Nfe2 , Trim27 , Mef2c , Ets1 , Tal1 , Foxo1 , and Gata1 in AML. Six of these genes (except ETS1 ) showed significant differential expression between human AML and healthy samples in an independent microarray dataset. All of these genes are known to be involved in immune/hematopoietic functions, and in transcriptional regulation. In addition, Nfe2 , Trim27 , Mef2c , and Ets1 harbor coding sequence variants, whereas Nfe2 and Trim27 are cis -regulated, making them attractive candidates for validation. Furthermore, subtype-specific analysis of the hub genes in human AML indicated high expression of NFE2 across all the subtypes (M0 through M7) and enriched expression of ETS1 , LEF1 , GATA1 , and TAL1 in M6 and M7 subtypes. A significant correlation between methylation status and expression level was observed for most of these genes in AML patients. Conclusion: Findings from the current study highlight the importance of our cross-species approach in the identification of multiple key candidate genes in AML, which can be further studied to explore their detailed role in leukemia/AML., 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 © 2023 Wang, Bajpai, Gu, Ashbrook, Starlard-Davenport and Lu.)

Background: Copper (Cu) is essential for the functioning of various enzymes involved in important cellular and physiological processes. Although critical for normal cardiac function, excessive accumulation, or deficiency of Cu in the myocardium is detrimental to the heart. Fluctuations in cardiac Cu content have been shown to cause cardiac pathologies and imbalance in systemic Cu metabolism. However, the genetic basis underlying cardiac Cu levels and their effects on heart traits remain to be understood. Representing the largest murine genetic reference population, BXD strains have been widely used to explore genotype-phenotype associations and identify quantitative trait loci (QTL) and candidate genes., Methods: Cardiac Cu concentration and heart function in BXD strains were measured, followed by QTL mapping. The candidate genes modulating Cu homeostasis in mice hearts were identified using a multi-criteria scoring/filtering approach., Results: Significant correlations were identified between cardiac Cu concentration and left ventricular (LV) internal diameter and volumes at end-diastole and end-systole, demonstrating that the BXDs with higher cardiac Cu levels have larger LV chamber. Conversely, cardiac Cu levels negatively correlated with LV posterior wall thickness, suggesting that lower Cu concentration in the heart is associated with LV hypertrophy. Genetic mapping identified six QTLs containing a total of 217 genes, which were further narrowed down to 21 genes that showed a significant association with cardiac Cu content in mice. Among those, Prex1 and Irx3 are the strongest candidates involved in cardiac Cu modulation., Conclusion: Cardiac Cu level is significantly correlated with heart chamber size and hypertrophy phenotypes in BXD mice, while being regulated by multiple genes in several QTLs. Prex1 and Irx3 may be involved in modulating Cu metabolism and its downstream effects and warrant further experimental and functional validations., 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 © 2023 Bajpai, Gu, Orgil, Xu, Torres-Rojas, Zhao, Chen, Starlard-Davenport, Jones, Lebeche, Towbin, Purevjav, Lu and Zhang.)

An individual's genetic makeup plays an important role in determining susceptibility to cognitive aging. Identifying the specific genes that contribute to cognitive aging may aid in early diagnosis of at-risk patients, as well as identify novel therapeutics targets to treat or prevent development of symptoms. Challenges to identifying these specific genes in human studies include complex genetics, difficulty in controlling environmental factors, and limited access to human brain tissue. Here, we identify Hp1bp3 as a novel modulator of cognitive aging using a genetically diverse population of mice and confirm that HP1BP3 protein levels are significantly reduced in the hippocampi of cognitively impaired elderly humans relative to cognitively intact controls. Deletion of functional Hp1bp3 in mice recapitulates memory deficits characteristic of aged impaired mice and humans, further supporting the idea that Hp1bp3 and associated molecular networks are modulators of cognitive aging. Overall, our results suggest Hp1bp3 may serve as a potential target against cognitive aging and demonstrate the utility of genetically diverse animal models for the study of complex human disease. [ABSTRACT FROM AUTHOR]

Natural genetic variation is randomly distributed and gene expression patterns vary widely in natural populations. These variations are an effect of multifactorial genetic perturbations resulting in different phenotypes. Genome-wide analysis can be used to comprehend the genetic basis governing this naturally occurring developmental variation. Secondary growth is a highly complex trait and systems genetics models are presently being applied to understand the molecular architecture of wood formation. In the present study, the natural variation in expression patterns of 18,987 transcripts expressed in the developing xylem tissues were documented across four phenotypes of Eucalyptus tereticornis with distinct holocellulose/klason lignin content. The differentially expressed genes across all the phenotypes were used to construct co-expression networks and sub-network 2 with 380 nodes and 17,711 edges was determined as the network of relevance, including 30 major cell wall biogenesis related transcripts with 2394 interactions and 10 families of transcription factors with 3360 interactions. EYE [ EMBRYO YELLOW] was identified as major hub transcript with 173 degrees which interacted with known cell wall biogenesis genes. K-mean clustering was also performed for differentially expressed transcripts and two clusters discriminated the phenotypes based on their holocellulose/klason lignin content. The cluster based networks were enriched with GOs related to cell wall biogenesis and sugar metabolism. The networks developed in the present study enabled identification of critical regulators and novel transcripts whose expression variation could presumably govern the phenotypic variation in wood properties across E. tereticornis. [ABSTRACT FROM AUTHOR]

Scans of the Drosophila melanogaster genome have identified organophosphate resistance loci among those with the most pronounced signature of positive selection. In this study, the molecular basis of resistance to the organophosphate insecticide azinphos-methyl was investigated using the Drosophila Genetic Reference Panel, and genome-wide association. Recently released full transcriptome data were used to extend the utility of the Drosophila Genetic Reference Panel resource beyond traditional genome-wide association studies to allow systems genetics analyses of phenotypes. We found that both genomic and transcriptomic associations independently identified Cyp6g1, a gene involved in resistance to DDT and neonicotinoid insecticides, as the top candidate for azinphos-methyl resistance. This was verified by transgenically overexpressing Cyp6g1 using natural regulatory elements from a resistant allele, resulting in a 6.5-fold increase in resistance. We also identified four novel candidate genes associated with azinphosmethyl resistance, all of which are involved in either regulation of fat storage, or nervous system development. In Cyp6g1, we find a demonstrable resistance locus, a verification that transcriptome data can be used to identify variants associated with insecticide resistance, and an overlap between peaks of a genomewide association study, and a genome-wide selective sweep analysis. [ABSTRACT FROM AUTHOR]

Advances in high-throughput sequencing have facilitated large-scale surveys of genomic variation in the budding yeast, Saccharomyces cerevisiae. These surveys have revealed extensive sequence variation between yeast strains. However, much less is known about how such variation influences the amount and nature of variation for functional genomic traits within and between yeast lineages. We review population-level studies of functional genomic variation, with a particular focus on how population functional genomic approaches can provide insights into both genome function and the evolutionary process. Although variation in functional genomics phenotypes is pervasive, our understanding of the consequences of this variation, either in physiological or evolutionary terms, is still rudimentary and thus motivates increased attention to appropriate null models. To date, much of the focus of population functional genomic studies has been on gene expression variation, but other functional genomic data types are just as likely to reveal important insights at the population level, suggesting a pressing need for more studies that go beyond transcription. Finally, we discuss how a population functional genomic perspective can be a powerful approach for developing a mechanistic understanding of the processes that link genomic variation to organismal phenotypes through gene networks. [ABSTRACT FROM AUTHOR]

Loss of retinal ganglion cells ( RGCs) is one of the hallmarks of retinal neurodegenerative diseases, glaucoma being one of the most common. Mechanistic studies on RGCs are hindered by the lack of sufficient primary cells and consensus regarding their signature markers. Recently, γ-synuclein ( SNCG) has been shown to be highly expressed in the somas and axons of RGCs. In various mouse models of glaucoma, downregulation of Sncg gene expression correlates with RGC loss. To investigate the role of Sncg in RGCs, we used a novel systems genetics approach to identify a gene that modulates Sncg expression, followed by confirmatory studies in both healthy and diseased retinae. We found that chromosome 1 harbors an expression quantitative trait locus that modulates Sncg expression in the mouse retina, and identified the prefoldin-2 ( PFDN2) gene as the candidate upstream modulator of Sncg expression. Our immunohistochemical analyses revealed similar expression patterns in both mouse and human healthy retinae, with PFDN2 colocalizing with SNCG in RGCs and their axons. In contrast, in retinae from glaucoma subjects, SNCG levels were significantly reduced, although PFDN2 levels were maintained. Using a novel flow cytometry-based RGC isolation method, we obtained viable populations of murine RGCs. Knocking down Pfdn2 expression in primary murine RGCs significantly reduced Sncg expression, confirming that Pfdn2 regulates Sncg expression in murine RGCs. Gene Ontology analysis indicated shared mitochondrial function associated with Sncg and Pfdn2. These data solidify the relationship between Sncg and Pfdn2 in RGCs, and provide a novel mechanism for maintaining RGC health. [ABSTRACT FROM AUTHOR]

Background Roots are essential organs for higher plants. They provide the plant with nutrients and water, anchor the plant in the soil, and can serve as energy storage organs. One remarkable feature of roots is that they are able to adjust their growth to changing environments. This adjustment is possible through mechanisms that modulate a diverse set of root traits such as growth rate, diameter, growth direction and lateral root formation. The basis of these traits and their modulation are at the cellular level, where a multitude of genes and gene networks precisely regulate development in time and space and tune it to environmental conditions. Scope This review first describes the root system and then presents fundamental work that has shed light on the basic regulatory principles of root growth and development. It then considers emerging complexities and how they have been addressed using systems-biology approaches, and then describes and argues for a systems-genetics approach. For reasons of simplicity and conciseness, this review is mostly limited to work from the model plant Arabidopsis thaliana, in which much of the research in root growth regulation at the molecular level has been conducted. Conclusions While forward genetic approaches have identified key regulators and genetic pathways, systemsbiology approaches have been successful in shedding light on complex biological processes, for instance molecular mechanisms involving the quantitative interaction of several molecular components, or the interaction of large numbers of genes. However, there are significant limitations in many of these methods for capturing dynamic processes, as well as relating these processes to genotypic and phenotypic variation. The emerging field of systems genetics promises to overcome some of these limitations by linking genotypes to complex phenotypic and molecular data using approaches from different fields, such as genetics, genomics, systems biology and phenomics [ABSTRACT FROM AUTHOR]

Adult neurogenesis, the lifelong production of new neurons in the adult brain, is under complex genetic control but many of the genes involved remain to be identified. In this study, we have integrated publicly available gene expression data from the BXD and CXB recombinant inbred mouse lines to discover genes co-expressed in the adult hippocampus with Nestin, a common marker of the neural precursor cell population. In addition, we incorporated spatial expression information to restrict candidates to genes with high differential gene expression in the hippocampal dentate gyrus. Incorporating data from curated protein-protein interaction databases revealed interactions between our candidate genes and those already known to be involved in adult neurogenesis. Enrichment analysis suggested a link to the Wnt/β-catenin pathway, known to be involved in adult neurogenesis. In particular, our candidates were enriched in targets of Lef1, a modulator of the Wnt pathway. In conclusion, our combination of bioinformatics approaches identified six novel candidate genes involved in adult neurogenesis; Amer3, Eya3, Mtdh, Nr4a3, Polr2a, and Tbkbp1. Further, we propose a role for Lef1 transcriptional control in the regulation of adult hippocampal precursor cell proliferation.

Background: Shiga toxin (Stx)-producing E. coli (STEC) are responsible for foodborne outbreaks that can result in severe human disease. During an outbreak, differential disease outcomes are observed after infection with the same STEC strain. One question of particular interest is why some infected people resolve infection after hemorrhagic colitis whereas others progress to the hemolytic uremic syndrome (HUS). Host age and infection dose have been implicated; however, these parameters do not appear to fully account for all of the observed variation in disease severity. Therefore, we hypothesized that additional host genetic factors may play a role in progression to HUS. Methods and Results: To mimic the genetic diversity in the human response to infection by STEC, we measured the capacity of an O157:H7 outbreak isolate to colonize mouse strains from the advanced recombinant inbred (ARI) BXD panel. We first infected the BXD parental strains C57BL/6 J (B6) and DBA/2 J (D2) with either 86-24 (Stx2a+) or TUV86-2, an Stx2a-negative isogenic mutant. Colonization levels were determined in an intact commensal flora (ICF) infection model. We found a significant difference in colonization levels between the parental B6 and D2 strains after infection with TUV86-2 but not with 86-24. This observation suggested that a host factor that may be masked by Stx2a affects O157:H7 colonization in some genetic backgrounds. We then determined the TUV86-2 colonization levels of 24 BXD strains in the ICF model. We identified several quantitative trait loci (QTL) associated with variation in colonization by correlation analyses. We found a highly significant QTL on proximal chromosome 9 (12.5-26.7 Mb) that strongly predicts variation in colonization levels and accounts for 15-20 % of variance. Linkage, polymorphism and co-citation analyses of the mapped region revealed 36 candidate genes within the QTL, and we identified five genes that are most likely responsible for the differential colonization. Conclusions: The identification of the QTL on chromosome 9 supports our hypothesis that individual genetic makeup affects the level of colonization after infection with STEC O157:H7. [ABSTRACT FROM AUTHOR]

Variation in hippocampal neuroanatomy correlates well with spatial learning ability in mice. Here, we have studied both hippocampal neuroanatomy and behavior in 53 isogenic BXD recombinant strains derived from C57BL/6J and DBA/2J parents. A combination of experimental, neuroinformatic and systems genetics methods was used to test the genetic bases of variation and covariation among traits. Data were collected on seven hippocampal subregions in CA3 and CA4 after testing spatial memory in an eight-armradial maze task. Quantitative trait lociwere identified for hippocampal structure, including the areas of the intra- and infrapyramidal mossy fibers (IIPMFs), stratum radiatum and stratum pyramidale, and for a spatial learning parameter, error rate. We identified multiple loci and gene variants linked to either structural differences or behavior. Gpc4 and Tenm2 are strong candidate genes that may modulate IIPMF areas. Analysis of gene expression networks and trait correlations highlight several processes influencing morphometrical variation and spatial learning. [ABSTRACT FROM AUTHOR]

Bile acids (BAs) are complex and incompletely understood enterohepatic-derived hormones that control whole-body metabolism. Here, we profiled postprandial BAs in the liver, feces, and plasma of 360 chow- or high-fat-diet-fed BXD male mice and demonstrated that both genetics and diet strongly influence BA abundance, composition, and correlation with metabolic traits. Through an integrated systems approach, we mapped hundreds of quantitative trait loci that modulate BAs and identified both known and unknown regulators of BA homeostasis. In particular, we discovered carboxylesterase 1c (Ces1c) as a genetic determinant of plasma tauroursodeoxycholic acid (TUDCA), a BA species with established disease-preventing actions. The association between Ces1c and plasma TUDCA was validated using data from independent mouse cohorts and a Ces1c knockout mouse model. Collectively, our data are a unique resource to dissect the physiological importance of BAs as determinants of metabolic traits, as underscored by the identification of CES1C as a master regulator of plasma TUDCA levels. [Display omitted] • Multi-omics data and bile acid profiles were collected from ∼360 male BXD mice • Bile acid levels are strongly influenced by genetics and environment • Numerous genetic loci associate to bile acid abundance • CES1C is identified as a modulator for tauroursodeoxycholic acid plasma abundance Li et al. use the BXD mouse reference population to evaluate how genetics and diet regulate bile acid homeostasis. Through this integrated systems genetics approach, they mapped hundreds of genetic loci associated with bile acids and identified carboxylesterase 1C as a modulator for tauroursodeoxycholic acid plasma abundance. [ABSTRACT FROM AUTHOR]

Heavy metals, various pesticide and herbicides are implicated as risk factors for human health. Paraquat, maneb, and rotenone, carbamate and organophospherous insecticides are examples of toxicants for which acute and chronic exposure are associated with multiple neurological disorders including Parkinson’s disease (PD). Nevertheless, the role of pesticide exposure in neurodegenerative diseases is not clear-cut, as there are inconsistencies in both the epidemiological and preclinical research. The aim of this short review is to show that the inconsistencies are related to individual differences in susceptibility to the effects of neurotoxicants, individual differences that can be traced to the genetic constitution of the individuals and animals studies, i.e., host-based susceptibility.

Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome investigations focusing on single genetic variants have achieved limited success, and the importance of including genetic interactions is becoming evident. Here, the aim was to perform an integrative genomic analysis in an F2 pig resource population that was constructed with an aim to maximize genetic variation of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA) analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation of haplotype blocks. We built Weighted Interaction SNP Hub (WISH) and differentially wired (DW) networks using genotypic correlations amongst obesity-associated SNPs resulting from GWA analysis. GWA results and SNP modules detected by WISH and DW analyses were further investigated by functional enrichment analyses. The functional annotation of SNPs revealed several genes associated with obesity, e.g. NPC2 and OR4D10. Moreover, gene enrichment analyses identified several significantly associated pathways, over and above the GWA study results, that may influence obesity and obesity related diseases, e.g. metabolic processes. WISH networks based on genotypic correlations allowed further identification of various gene ontology terms and pathways related to obesity and related traits, which were not identified by the GWA study. In conclusion, this is the first study to develop a (genetic) obesity index and employ systems genetics in a porcine model to provide important insights into the complex genetic architecture associated with obesity and many biological pathways that underlie it.

It was recently shown that monotone gene action, i.e. order-preservation between allele content and corresponding genotypic values in the mapping from genotypes to phenotypes, is a prerequisite for achieving a predictable parent-offspring relationship across the whole allele frequency spectrum. Here we test the consequential prediction that the design principles underlying gene regulatory networks are likely to generate highly monotone genotype-phenotype maps. To this end we present two measures of the monotonicity of a genotype-phenotype map, one based on allele substitution effects, and the other based on isotonic regression. We apply these measures to genotype-phenotype maps emerging from simulations of 1881 different 3-gene regulatory networks. We confirm that in general, genotype-phenotype maps are indeed highly monotonic across network types. However, regulatory motifs involving incoherent feedforward or positive feedback, as well as pleiotropy in the mapping between genotypes and gene regulatory parameters, are clearly predisposed for generating non-monotonicity. We present analytical results confirming these deep connections between molecular regulatory architecture and monotonicity properties of the genotype-phenotype map. These connections seem to be beyond reach by the classical distinction between additive and non-additive gene action.

Pooled genetic screens have revolutionized the field of functional genomics, yet perturbations that decrease fitness, such as those leading to synthetic lethality, have remained difficult to quantify at the genomic level. We and colleagues previously developed "death screening," a protocol based on the purification of dead cells in genetic screens, and used it to identify a set of genes necessary for mitochondrial gene expression, translation, and oxidative phosphorylation (OXPHOS), thus offering new possibilities for the diagnosis of mitochondrial disorders. Here, we describe Dead-Seq, a refined protocol for death screening that is compatible with most pooled screening protocols, including genome-wide CRISPR/Cas9 screening. Dead-Seq converts negative-selection screens into positive-selection screens and generates high-quality data directly from dead cells, at limited sequencing costs., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology. [ABSTRACT FROM AUTHOR]

To ensure rice food security, the target outputs of future rice breeding programmes should focus on developing climate-resilient rice varieties with emphasis on increased head rice yield coupled with superior grain quality. This challenge is made greater by a world that is increasingly becoming warmer. Such environmental changes dramatically impact head rice and milling yield as well as increasing chalkiness because of impairment in starch accumulation and other storage biosynthetic pathways in the grain. This review highlights the knowledge gained through gene discovery via quantitative trait locus (QTL) cloning and structural-functional genomic strategies to reduce chalk, increase head rice yield, and develop stable lines with optimum grain quality in challenging environments. The newly discovered genes and the knowledge gained on the influence of specific alleles related to stability of grain quality attributes provide a robust platform for marker-assisted selection in breeding to design heat-tolerant rice varieties with superior grain quality. Using the chalkiness trait in rice as a case study, we demonstrate here that the emerging field of systems genetics can help fast-track the identification of novel alleles and gene targets that can be pyramided for the development of environmentally robust rice varieties that possess improved grain quality. [ABSTRACT FROM AUTHOR]

Background: The pig, which shares greater similarities with human than with mouse, is important for agriculture and for studying human diseases. However, similarities in the genetic architecture and molecular regulations underlying phenotypic variations in humans and swine have not been systematically assessed. Results: We systematically surveyed ~500 F2 pigs genetically and phenotypically. By comparing candidates for anemia traits identified in swine genome-wide SNP association and human genome-wide association studies (GWAS), we showed that both sets of candidates are related to the biological process “cellular lipid metabolism” in liver. Human height is a complex heritable trait; by integrating genome-wide SNP data and human adipose Bayesian causal network, which closely represents bone transcriptional regulations, we identified PLAG1 as a causal gene for limb bone length. This finding is consistent with GWAS findings for human height and supports the common genetic architecture between swine and humans. By leveraging a human protein-protein interaction network, we identified two putative candidate causal genes TGFB3 and DAB2IP and the known regulators MESP1 and MESP2 as responsible for the variation in rib number and identified the potential underlying molecular mechanisms. In mice, knockout of Tgfb3 and Tgfb2 together decreases rib number. Conclusion: Our findings show that integrative network analyses reveal causal regulators underlying the genetic association of complex traits in swine and that these causal regulators have similar effects in humans. Thus, swine are a potentially good animal model for studying some complex human traits that are not under intense selection. [ABSTRACT FROM AUTHOR]

Endometriosis is a condition in which cells derived from the endometrium grow outside the uterus, e.g. in the peritoneum (external genital endometriosis). As these cells are under the influence of female hormones, major symptoms of endometriosis are pain, especially during the cycle, and infertility. Numerous hypotheses for the formation of endometriosis can be found in the literature, but there is growing evidence of serious genetic contributions to endometriosis susceptibility. The involvement of genes, steroid hormone metabolism, immunological reactions, receptor formation, inflammation, proliferation, apoptosis, intercellular adhesion, cell invasion and angiogenesis as well as genes regulating the activity of aforementioned enzymes have been suggested. Some more recently suggested candidate genes picked up in genome-wide association studies are involved in oncogenesis, metaplasia of endometrium cells and pathways of embryonic development of the female reproductive system. However, gene mutations proven to be causative for endometriosis have not been identified so far, even though the abnormal expression of candidate genes for endometriosis could be provoked by different epigenetic modifications including DNA methylation, heterochromatization or introduction of regulatory miRNA. We hypothesize that endometriosis is induced by a combination of abnormal genetic and/or epigenetic mutations: the latter pave the way for pathological changes which become irreversible, and according to the “epigenetic landscape” theory, this proceeds to the typical clinical manifestations. Two stages in the endometriosis pathway are suggested: (1) induction of primary endometrial cells toward endometriosis, and (2) implantation and progression of these cells into endometriosis lesions. The model favors endometriosis as an outgrowth of primary cells different in their origin, canalization of pathological processes, manifestation diversity provoked by unique genetic background and epigenetic influences, which result in many different clinical forms of the disease. [ABSTRACT FROM AUTHOR]

Adult neurogenesis, the lifelong production of new neurons in the adult brain, is under complex genetic control but many of the genes involved remain to be identified. In this study, we have integrated publicly available gene expression data from the BXD and CXB recombinant inbred mouse lines to discover genes co-expressed in the adult hippocampus with Nestin, a common marker of the neural precursor cell population. In addition, we incorporated spatial expression information to restrict candidates to genes with high differential gene expression in the hippocampal dentate gyrus. Incorporating data from curated protein-protein interaction databases revealed interactions between our candidate genes and those already known to be involved in adult neurogenesis. Enrichment analysis suggested a link to the Wnt/β-catenin pathway, known to be involved in adult neurogenesis. In particular, our candidates were enriched in targets of Lef1, a modulator of the Wnt pathway. In conclusion, our combination of bioinformatics approaches identified six novel candidate genes involved in adult neurogenesis; Amer3, Eya3, Mtdh, Nr4a3, Polr2a, and Tbkbp1. Further, we propose a role for Lef1 transcriptional control in the regulation of adult hippocampal precursor cell proliferation. [ABSTRACT FROM AUTHOR]

Abstract The rate of change in genomics, and 'omics generally, shows no signs of slowing down. Related analysis software is struggling to keep apace. This paper provides a brief review of the field.

Improving muscle function has great potential to improve the quality of life. To identify novel regulators of skeletal muscle metabolism and function, we performed a proteomic analysis of gastrocnemius muscle from 73 genetically distinct inbred mouse strains, and integrated the data with previously acquired genomics and >300 molecular/phenotypic traits via quantitative trait loci mapping and correlation network analysis. These data identified thousands of associations between protein abundance and phenotypes and can be accessed online (https://muscle.coffeeprot.com/) to identify regulators of muscle function. We used this resource to prioritize targets for a functional genomic screen in human bioengineered skeletal muscle. This identified several negative regulators of muscle function including UFC1, an E2 ligase for protein UFMylation. We show UFMylation is up-regulated in a mouse model of amyotrophic lateral sclerosis, a disease that involves muscle atrophy. Furthermore, in vivo knockdown of UFMylation increased contraction force, implicating its role as a negative regulator of skeletal muscle function., Competing Interests: JM, RB, RM, YN, KW, DC, PG, PC, JH, LL, PZ, KR, AL, JH, MS, BP No competing interests declared, DJ Senior editor, eLife, (© 2022, Molendijk et al.)

Background: Long noncoding RNAs (lncRNAs) are a diverse class of RNAs that are critical for gene regulation, DNA repair, and splicing, and have been implicated in development, stress response, and cancer. However, the functions of many lncRNAs remain unknown. In Drosophila melanogaster, U snoRNA host gene 4 (Uhg4) encodes an antisense long noncoding RNA that is host to seven small nucleolar RNAs (snoRNAs). Uhg4 is expressed ubiquitously during development and in all adult tissues, with maximal expression in ovaries; however, it has no annotated function(s)., Results: We used CRISPR-Cas9 germline gene editing to generate multiple deletions spanning the promoter region and first exon of Uhg4. Females showed arrested egg development and both males and females were sterile. In addition, Uhg4 deletion mutants showed delayed development and decreased viability, and changes in sleep and responses to stress. Whole-genome RNA sequencing of Uhg4 deletion flies and their controls identified co-regulated genes and genetic interaction networks associated with Uhg4. Gene ontology analyses highlighted a broad spectrum of biological processes, including regulation of transcription and translation, morphogenesis, and stress response., Conclusion: Uhg4 is a lncRNA essential for reproduction with pleiotropic effects on multiple fitness traits., (© 2022. The Author(s).)

Most common diseases are complex, involving multiple genetic and environmental factors and their interactions. In the past decade, genome-wide association studies (GWAS) have successfully identified thousands of genetic variants underlying susceptibility to complex diseases. However, the results from these studies often do not provide evidence on how the variants affect downstream pathways and lead to the disease. Therefore, in the post-GWAS era the greatest challenge lies in combining GWAS findings with additional molecular data to functionally characterize the associations. The advances in various ~omics techniques have made it possible to investigate the effect of risk variants on intermediate molecular levels, such as gene expression, methylation, protein abundance or metabolite levels. As disease aetiology is complex, no single molecular analysis is expected to fully unravel the disease mechanism. Multiple molecular levels can interact and also show plasticity in different physiological conditions, cell types and disease stages. There is therefore a great need for new integrative approaches that can combine data from different molecular levels and can help construct the causal inference from genotype to phenotype. Systems genetics is such an approach; it is used to study genetic effects within the larger scope of systems biology by integrating genotype information with various ~omics datasets as well as with environmental and physiological variables. In this review, we describe this approach and discuss how it can help us unravel the molecular mechanisms through which genetic variation causes disease. This article is part of a Special Issue entitled: From Genome to Function. [ABSTRACT FROM AUTHOR]

Heavy metals, various pesticide and herbicides are implicated as risk factors for human health. Paraquat, maneb, and rotenone, carbamate, and organophosphorous insecticides are examples of toxicants for which acute and chronic exposure are associated with multiple neurological disorders including Parkinson's disease. Nevertheless, the role of pesticide exposure in neurodegenerative diseases is not clear-cut, as there are inconsistencies in both the epidemiological and preclinical research. The aim of this short review is to show that at least, some of the inconsistencies are related to individual differences in susceptibility to the effects of neurotoxicants, individual differences that can be traced to the genetic constitution of the individuals and animals studies, i.e., host-based susceptibility. [ABSTRACT FROM AUTHOR]

Background: Phenotypic plasticity allows organisms to respond rapidly to changing environmental circumstances, and understanding its genomic basis can yield insights regarding the underlying genes and genetic networks affecting complex phenotypes. Female Drosophila melanogaster undergo dramatic physiological changes mediated by seminal fluid components transferred upon mating, including decreased longevity. Their physiological and behavioral effects have been well characterized, but little is known about resulting changes in regulation of gene expression or the extent to which mating-induced changes in gene expression are the same as those occurring during aging. Results: We assessed genome-wide mRNA, microRNA, and three common histone modifications implicated in gene activation for young and aged virgin and mated female D. melanogaster in a factorial design. We identified phenotypically plastic transcripts and epigenetic modifications associated with mating and aging. We used these data to derive phenotypically plastic regulatory networks associated with mating of young flies, and aging of virgin and mated flies. Many of the mRNAs, microRNAs and epigenetic modifications associated with mating of young flies also occur with age in virgin flies, which may reflect mating-induced accelerated aging. We functionally tested the plastic regulatory networks by overexpressing environmentally sensitive microRNAs. Overexpression resulted in altered expression of ~70% of candidate target genes, and in all cases affected oviposition. Conclusions: Our results implicate microRNAs as mediators of phenotypic plasticity associated with mating and provide a comprehensive documentation of the genomic and epigenomic changes that accompany mating- and aging-induced physiological changes in female D. melanogaster. [ABSTRACT FROM AUTHOR]

Highlights: [•] Defines the field of systems genetics. [•] Describes the need for knowledge independent selection of candidate genes and discovery. [•] Describes two systems genetics approaches: eQTL and co-expression module mapping. [Copyright &y& Elsevier]