How far from the SNP may the causative genes be?

Genome-wide association study for milking speed in Fleckvieh cattle

Milking speed is an important trait influencing udder health of dairy cows as well as labor efficiency. Yet, it has received little attention in genomic association studies. The main objective of this study was to determine regions and genes on the genome with a potential effect on milking speed in Fleckvieh (dual purpose Simmental) cattle. Genome-wide association studies were conducted using de-regressed breeding values of bulls as phenotypes. Six SNP on 4 autosomes were significantly associated with milking speed for additive effects. Significant regions on BTA4 and BTA19 correspond with findings for other dairy cattle breeds. Based on the observation of Fleckvieh breed managers, variation of milking speed in batches of daughters of some bulls is much higher than in daughter groups of other bulls. This difference in within family variation may be caused by transmission of alternative alleles of bulls being heterozygous for a gene affecting milking speed. To check on this, we considered standard deviation of yield deviations in milking speed of half-sib daughters as a new trait and performed GWAS for dominance effects. One signal on BTA5 passed the genome wide Bonferroni threshold that corresponded to the significant signal from standard GWAS on de-regressed breeding values. The key conclusion of this study is that several strong genomic signals were found for milking speed in Fleckvieh cattle and that the strongest of them are supported by similar findings in Brown Swiss and Holstein Friesian cattle. Milking speed is a complex trait whose sub-processes have not yet been elucidated in detail. Hence, it remains a challenge to link the associated regions on the genome with causal genes and their functions.

Genetic variants for head size share genes and pathways with cancer

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.

The broken Alzheimer's disease genome

The complex pathobiology of late-onset Alzheimer's disease (AD) poses significant challenges to therapeutic and preventative interventions. Despite these difficulties, genomics and related disciplines are allowing fundamental mechanistic insights to emerge with clarity, particularly with the introduction of high-resolution sequencing technologies. After all, the disrupted processes at the interface between DNA and gene expression, which we call the broken AD genome, offer detailed quantitative evidence unrestrained by preconceived notions about the disease. In addition to highlighting biological pathways beyond the classical pathology hallmarks, these advances have revitalized drug discovery efforts and are driving improvements in clinical tools. We review genetic, epigenomic, and gene expression findings related to AD pathogenesis and explore how their integration enables a better understanding of the multicellular imbalances contributing to this heterogeneous condition. The frontiers opening on the back of these research milestones promise a future of AD care that is both more personalized and predictive.

Synergizing drug repurposing and target identification for neurodegenerative diseases

Despite dedicated research efforts, the absence of disease-curing remedies for neurodegenerative diseases (NDDs) continues to jeopardize human society and stands as a challenge. Drug repurposing is an attempt to find new functionality of existing drugs and take it as an opportunity to discourse the clinically unmet need to treat neurodegeneration. However, despite applying this approach to rediscover a drug, it can also be used to identify the target on which a drug could work. The primary objective of target identification is to unravel all the possibilities of detecting a new drug or repurposing an existing drug. Lately, scientists and researchers have been focusing on specific genes, a particular site in DNA, a protein, or a molecule that might be involved in the pathogenesis of the disease. However, the new era discusses directing the signaling mechanism involved in the disease progression, where receptors, ion channels, enzymes, and other carrier molecules play a huge role. This review aims to highlight how target identification can expedite the whole process of drug repurposing. Here, we first spot various target-identification methods and drug-repositioning studies, including drug-target and structure-based identification studies. Moreover, we emphasize various drug repurposing approaches in NDDs, namely, experimental-based, mechanism-based, and in silico approaches. Later, we draw attention to validation techniques and stress on drugs that are currently undergoing clinical trials in NDDs. Lastly, we underscore the future perspective of synergizing drug repurposing and target identification in NDDs and present an unresolved question to address the issue.

The Immunometabolic Gene N-Acetylglucosamine Kinase Is Uniquely Involved in the Heritability of Multiple Sclerosis Severity

The clinical severity of multiple sclerosis (MS), an autoimmune disorder of the central nervous system, is thought to be determined by environmental and genetic factors that have not yet been identified. In a recent genome-wide association study (GWAS), a single nucleotide polymorphism (SNP), rs10191329, has been associated with MS severity in two large independent cohorts of patients. Different approaches were followed by the authors to prioritize the genes that are transcriptionally regulated by such an SNP. It was concluded that the identified SNP regulates a group of proximal genes involved in brain resilience and cognitive abilities rather than immunity. Here, by conducting an alternative strategy for gene prioritization, we reached the opposite conclusion. According to our re-analysis, the main target of rs10191329 is N-Acetylglucosamine Kinase (NAGK), a metabolic gene recently shown to exert major immune functions via the regulation of the nucleotide-binding oligomerization domain-containing protein 2 (NOD2) pathway. To gain more insights into the immunometabolic functions of NAGK, we analyzed the currently known list of NAGK protein partners. We observed that NAGK integrates a dense network of human proteins that are involved in glucose metabolism and are highly expressed by classical monocytes. Our findings hold potentially major implications for the understanding of MS pathophysiology.

Examination of a novel expression-based gene-SNP annotation strategy to identify tissue-specific contributions to heritability in multiple traits

Complex traits show clear patterns of tissue-specific expression influenced by single nucleotide polymorphisms (SNPs), yet current strategies aggregate SNP effects to genes by employing simple physical proximity-based windows. Here, we examined whether incorporating SNPs with effects on tissue-specific cis-expression would improve our ability to detect trait-relevant tissues across 31 complex traits using stratified linkage disequilibrium score regression (S-LDSC). We found that a physical proximity annotation produced more significant tissue enrichments and larger S-LDSC regression coefficients, as compared to an expression-based annotation. Furthermore, we showed that our expression-based annotation did not outperform an annotation strategy in which an equal number of randomly chosen SNPs were annotated to genes within the same genomic window, suggesting extensive redundancy among SNP effect estimates due to linkage disequilibrium. That said, current sample sizes limit estimation of cis-genetic SNP effects; therefore, we recommend reexamination of the expression-based annotation when larger tissue-specific expression datasets become available. To examine the influence of sample size, we used a large whole blood eQTL reference panel (N = 31,684) applying a similar expression-based annotation strategy. We found that significant cis-expression QTLs in whole blood did not outperform the physical proximity annotation when estimating tissue-specific SNP heritability enrichment for either high- or low-density lipoprotein phenotypes but performed similarly for inflammatory bowel disease. Finally, we report new and updated tissue enrichment estimates across 31 complex traits, such as significant heritability enrichment of the frontal cortex for cognitive performance, educational attainment, and intelligence, providing further evidence of this structure's importance in higher cognitive function.

Refining the genomic profiles of North African sheep breeds through meta-analysis of worldwide genomic SNP data

Introduction

The development of reproducible tools for the rapid genotyping of thousands of genetic markers (SNPs) has promoted cross border collaboration in the study of sheep genetic diversity on a global scale.

Methods

In this study, we collected a comprehensive dataset of 239 African and Eurasian sheep breeds genotyped at 37,638 filtered SNP markers, with the aim of understanding the genetic structure of 22 North African (NA) sheep breeds within a global context.

Results and discussion

We revealed asubstantial enrichment of the gene pool between the north and south shores of the Mediterranean Sea, which corroborates the importance of the maritime route in the history of livestock. The genetic structure of North African breeds mirrors the differential composition of genetic backgrounds following the breed history. Indeed, Maghrebin sheep stocks constitute a geographically and historically coherent unit with any breed-level genetic distinctness among them due to considerable gene flow. We detected a broad east-west pattern describing the most important trend in NA fat-tailed populations, exhibited by the genetic closeness of Egyptian and Libyan fat-tailed sheep to Middle Eastern breeds rather than Maghrebin ones. A Bayesian FST scan analysis revealed a set of genes with potentially key adaptive roles in lipid metabolism (BMP2, PDGFD VEGFA, TBX15, and WARS2), coat pigmentation (SOX10, PICK1, PDGFRA, MC1R, and MTIF) and horn morphology RXFP2) in Tunisian sheep. The local ancestry method detected a Merino signature in Tunisian Noire de Thibar sheep near the SULF1gene introgressed by Merino's European breeds. This study will contribute to the general picture of worldwide sheep genetic diversity.

Combined ATAC-seq, RNA-seq, and GWAS analysis reveals glycogen metabolism regulatory network in Jinjiang oyster ( Crassostrea ariakensis)

Glycogen serves as the principal energy reserve for metabolic processes in aquatic shellfish and substantially contributes to the flavor and quality of oysters. The Jinjiang oyster ( Crassostrea ariakensis) is an economically and ecologically important species in China. In the present study, RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) were performed to investigate gene expression and chromatin accessibility variations in oysters with different glycogen contents. Analysis identified 9 483 differentially expressed genes (DEGs) and 7 215 genes with significantly differential chromatin accessibility (DCAGs) were obtained, with an overlap of 2 600 genes between them. Notably, a significant proportion of these genes were enriched in pathways related to glycogen metabolism, including "Glycogen metabolic process" and "Starch and sucrose metabolism". In addition, genome-wide association study (GWAS) identified 526 single nucleotide polymorphism (SNP) loci associated with glycogen content. These loci corresponded to 241 genes, 63 of which were categorized as both DEGs and DCAGs. This study enriches basic research data and provides insights into the molecular mechanisms underlying the regulation of glycogen metabolism in C. ariakensis.

Investigating the role of genetic variation in vgll3 and six6 in the domestication of gilthead seabream (Sparus aurata Linnaeus) and European seabass (Dicentrarchus labrax Linnaeus)

Gene function conservation is crucial in molecular ecology, especially for key traits like growth and maturation in teleost fish. The vgll3 and six6 genes are known to influence age-at-maturity in Atlantic salmon, but their impact on other fish species is poorly understood. Here, we investigated the association of vgll3 and six6 in the domestication of gilthead seabream and European seabass, both undergoing selective breeding for growth-related traits in the Mediterranean. We analysed two different sets of samples using two different genotyping approaches. The first dataset comprised farmed and wild populations from Greece, genotyped for SNPs within the two genes ('gene-level genotyping'). The second dataset examined 300-600 k SNPs located in the chromosomes of the two genes, derived from a meta-analysis of a Pool-Seq experiment involving farmed and wild populations distributed widely across the Mediterranean ('chromosome-level genotyping'). The gene-level analysis revealed a statistically significant allele frequency differences between farmed and wild populations on both genes in each species. This finding was partially supported by the chromosome-level analysis, identifying highly differentiated regions may be involved in the domestication process at varying distances from the candidate genes. Noteworthy genomic features were found, such as a CpG island in gilthead seabream and novel candidate genes in European seabass, warranting further investigation. These findings support a putative role of vgll3 and six6 in the maturation and growth of gilthead seabream and European seabass, emphasizing the need for further research on their conserved function.

Computational analysis of five neurodegenerative diseases reveals shared and specific genetic loci

Neurodegenerative diseases (ND) are heterogeneous disorders of the central nervous system that share a chronic and selective process of neuronal cell death. A computational approach to investigate shared genetic and specific loci was applied to 5 different ND: Amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), Parkinson's disease (PD), Multiple sclerosis (MS), and Lewy body dementia (LBD). The datasets were analyzed separately, and then we compared the obtained results. For this purpose, we applied a genetic correlation analysis to genome-wide association datasets and revealed different genetic correlations with several human traits and diseases. In addition, a clumping analysis was carried out to identify SNPs genetically associated with each disease. We found 27 SNPs in AD, 6 SNPs in ALS, 10 SNPs in PD, 17 SNPs in MS, and 3 SNPs in LBD. Most of them are located in non-coding regions, with the exception of 5 SNPs on which a protein structure and stability prediction was performed to verify their impact on disease. Furthermore, an analysis of the differentially expressed miRNAs of the 5 examined pathologies was performed to reveal regulatory mechanisms that could involve genes associated with selected SNPs. In conclusion, the results obtained constitute an important step toward the discovery of diagnostic biomarkers and a better understanding of the diseases.

Genomic Signatures of Local Adaptation under High Gene Flow in Lumpfish-Implications for Broodstock Provenance Sourcing and Larval Production

Aquaculture of the lumpfish (Cyclopterus lumpus L.) has become a large, lucrative industry owing to the escalating demand for "cleaner fish" to minimise sea lice infestations in Atlantic salmon mariculture farms. We used over 10K genome-wide single nucleotide polymorphisms (SNPs) to investigate the spatial patterns of genomic variation in the lumpfish along the coast of Norway and across the North Atlantic. Moreover, we applied three genome scans for outliers and two genotype-environment association tests to assess the signatures and patterns of local adaptation under extensive gene flow. With our 'global' sampling regime, we found two major genetic groups of lumpfish, i.e., the western and eastern Atlantic. Regionally in Norway, we found marginal evidence of population structure, where the population genomic analysis revealed a small portion of individuals with a different genetic ancestry. Nevertheless, we found strong support for local adaption under high gene flow in the Norwegian lumpfish and identified over 380 high-confidence environment-associated loci linked to gene sets with a key role in biological processes associated with environmental pressures and embryonic development. Our results bridge population genetic/genomics studies with seascape genomics studies and will facilitate genome-enabled monitoring of the genetic impacts of escapees and allow for genetic-informed broodstock selection and management in Norway.

Genome-Wide Association Study to Identify QTL for Carcass Traits in Korean Hanwoo Cattle

This study aimed to identify genetic associations with carcass traits in Hanwoo cattle using a genome-wide association study. A total of 9302 phenotypes were analyzed, and all animals were genotyped using the Illumina Bovine 50K v.3 SNP chip. Heritabilities for carcass weight (CWT), eye muscle area (EMA), backfat thickness (BF), and marbling score (MS) were estimated as 0.42, 0.36, 0.36, and 0.47, respectively, using the GBLUP model, and 0.47, 0.37, 0.36, and 0.42, respectively, using the Bayes B model. We identified 129 common SNPs using DGEBV and 118 common SNPs using GEBV on BTA6, BTA13, and BTA14, suggesting their potential association with the traits of interest. No common SNPs were found between the GBLUP and Bayes B methods when using residuals as a response variable in GWAS. The most promising candidate genes for CWT included SLIT2, PACRGL, KCNIP4, RP1, XKR4, LYN, RPS20, MOS, FAM110B, UBXN2B, CYP7A1, SDCBP, NSMAF, TOX, CA8, LAP3, FAM184B, and NCAPG. For EMA, the genes IBSP, LAP3, FAM184B, LCORL, NCAPG, SLC30A9, and BEND4 demonstrated significance. Similarly, CYP7B1, ARMC1, PDE7A, and CRH were associated with BF, while CTSZ, GNAS, VAPB, and RAB22A were associated with MS. This finding offers valuable insights into genomic regions and molecular mechanisms influencing Hanwoo carcass traits, aiding efficient breeding strategies.

GSTM1 and GSTT1 polymorphisms associated with pain in a chemotherapy-induced peripheral neuropathy cohort

PURPOSE

Chemotherapy induced peripheral neuropathy (CIPN) is a debilitating condition that is a direct consequence of receiving cancer treatment. The molecular aetiology of CIPN is not well understood, and it is theorised that there may be a genetic component. Genetic polymorphisms in Glutathione-S Transferase (GST) genes, including GSTT1, GSTM1 and GSTP1, encode for enzymes known to metabolise drugs used in chemotherapy, and have been theorised to be associated with CIPN. This study aimed to investigate four markers in these genes for an association in a mixed cancer cohort in relation to CIPN (n = 172).

METHODS

CIPN was measured using the neuropathy item from the Patient Reported Outcome Common Terminology Criteria for Adverse Event (PRO-CTCAE) assessment. Genotyping for all samples was performed using PCR for the GSTM1 and GSTT1 null variants and restriction fragment length polymorphisms for the GSTP1 and GSTM1 polymorphisms.

RESULTS

No associations were found for the GST gene markers in relation to CIPN within our study, or CIPN severity. Longitudinal stratification of the CIPN phenotypes to examine links for neuropathy, identified nominally significant protective associations with the GSTM* null allele (p-value = 0.038, OR = 0.55) and the presence of pain at month 2 of treatment, as well as a risk factor for pain related month 2 of treatment for individuals with the GSTT1*null allele (p-value = 0.030, OR = 1.64). Higher severity of pain in patients with CIPN persisted at each time-point compared to those without CIPN.

CONCLUSION

No significant results for an association between CIPN with polymorphisms in GSTM1, GSTT1 and GSTP1 were identified. However, associations for the GSTM1¬-null and GSTT1-null polymorphisms with pain at month 2 following chemotherapy were identified.

Mapping genetic variants for nonsense-mediated mRNA decay regulation across human tissues

BACKGROUND

Nonsense-mediated mRNA decay (NMD) was originally conceived as an mRNA surveillance mechanism to prevent the production of potentially deleterious truncated proteins. Research also shows NMD is an important post-transcriptional gene regulation mechanism selectively targeting many non-aberrant mRNAs. However, how natural genetic variants affect NMD and modulate gene expression remains elusive.

RESULTS

Here we elucidate NMD regulation of individual genes across human tissues through genetical genomics. Genetic variants corresponding to NMD regulation are identified based on GTEx data through unique and robust transcript expression modeling. We identify genetic variants that influence the percentage of NMD-targeted transcripts (pNMD-QTLs), as well as genetic variants regulating the decay efficiency of NMD-targeted transcripts (dNMD-QTLs). Many such variants are missed in traditional expression quantitative trait locus (eQTL) mapping. NMD-QTLs show strong tissue specificity especially in the brain. They are more likely to overlap with disease single-nucleotide polymorphisms (SNPs). Compared to eQTLs, NMD-QTLs are more likely to be located within gene bodies and exons, especially the penultimate exons from the 3' end. Furthermore, NMD-QTLs are more likely to be found in the binding sites of miRNAs and RNA binding proteins.

CONCLUSIONS

We reveal the genome-wide landscape of genetic variants associated with NMD regulation across human tissues. Our analysis results indicate important roles of NMD in the brain. The preferential genomic positions of NMD-QTLs suggest key attributes for NMD regulation. Furthermore, the overlap with disease-associated SNPs and post-transcriptional regulatory elements implicates regulatory roles of NMD-QTLs in disease manifestation and their interactions with other post-transcriptional regulators.

Two transects reveal remarkable variation in gene flow on opposite ends of a European toad hybrid zone

Speciation entails a reduction in gene flow between lineages. The rates at which genomic regions become isolated varies across space and time. Barrier markers are linked to putative genes involved in (processes of) reproductive isolation, and, when observed over two transects, indicate species-wide processes. In contrast, transect-specific putative barrier markers suggest local processes. We studied two widely separated transects along the 900 km hybrid zone between Bufo bufo and B. spinosus, in northern and southern France, for ~1200 RADseq markers. We used genomic and geographic cline analyses to identify barrier markers based on their restricted introgression, and found that some markers are transect-specific, while others are shared between transects. Twenty-six barrier markers were shared across both transects, of which some are clustered in the same chromosomal region, suggesting that their associated genes are involved in reduced gene flow across the entire hybrid zone. Transect-specific barrier markers were twice as numerous in the southern than in the northern transect, suggesting that the overall barrier effect is weaker in northern France. We hypothesize that this is consistent with a longer period of secondary contact in southern France. The smaller number of introgressed genes in the northern transect shows considerably more gene flow towards the southern (B. spinosus) than the northern species (B. bufo). We hypothesize that hybrid zone movement in northern France and hybrid zone stability in southern France explain this pattern. The Bufo hybrid zone provides an excellent opportunity to separate a general barrier effect from localized gene flow-reducing conditions.

Expression quantitative trait locus studies in the era of single-cell omics

Genome-wide association studies have revealed that the regulation of gene expression bridges genetic variants and complex phenotypes. Profiling of the bulk transcriptome coupled with linkage analysis (expression quantitative trait locus (eQTL) mapping) has advanced our understanding of the relationship between genetic variants and gene regulation in the context of complex phenotypes. However, bulk transcriptomics has inherited limitations as the regulation of gene expression tends to be cell-type-specific. The advent of single-cell RNA-seq technology now enables the identification of the cell-type-specific regulation of gene expression through a single-cell eQTL (sc-eQTL). In this review, we first provide an overview of sc-eQTL studies, including data processing and the mapping procedure of the sc-eQTL. We then discuss the benefits and limitations of sc-eQTL analyses. Finally, we present an overview of the current and future applications of sc-eQTL discoveries.

Major locus on ECA18 influences effectiveness of GonaCon vaccine in feral horses

Contraceptive vaccines are used to reduce birth rates in wild and feral animal populations. While the immunocontraceptive GonaCon-Equine has proven effective in reducing fertility among female feral horses, there is individual variation in the duration of infertility following treatment. To identify genetic factors influencing the effectiveness of GonaCon-Equine, we conducted a genome-wide association study of 88 mares from a feral population genotyped using the Illumina GGP Equine 70k SNP array. Contraceptive treatment schedules and long-term foaling rates have been recorded for each individual. We used mixed linear models to control for relatedness among mares. We found a significant association (p < 5 ×10^-8) with a locus on equine chromosome 18. The most likely candidate genes in this region are STAT1 and STAT4, which are both involved in immune system function. Variation in STAT function could affect the immune response to the vaccine, leading to variation in contraceptive efficacy. Additional SNPs reaching a less stringent threshold of significance (p < 5 ×10^-6) were located on other chromosomes near known immune system genes, supporting the hypothesis that variation in immunocontraceptive efficacy can be attributed to genetic variation in immune response rather than fertility genes.

CRISPR/Cas9 genome editing demonstrates functionality of the autoimmunity-associated SNP rs12946510

Genome-wide association studies (GWAS) map genetic associations of complex traits with precision limited to a linkage disequilibrium group. To translate GWAS results into new understanding of disease mechanisms, individual causative polymorphisms and their target genes should be identified. CRISPR/Cas9 genome editing can be used to create isogenic cell lines bearing alternative genotypes of candidate single-nucleotide polymorphisms to test their causality and to reveal gene targets. An intergenic polymorphism rs12946510 is associated with multiple sclerosis, inflammatory bowel disease and asthma. We created sublines of the T-helper cell line bearing alternative genotypes of rs12946510 and showed that its risk ("T") allele is associated with lower expression of IKZF3 and ORMDL3 genes and reduced cell activation. Our editing procedure can become an effective tool for discovering new genes involved in pathogenesis of complex diseases.

Genome-phenotype-environment associations identify signatures of selection in a panmictic population of threespine stickleback

Adaptive genetic divergence occurs when selection imposed by the environment causes the genomic component of the phenotype to differentiate. However, genomic signatures of natural selection are usually identified without information on which trait is responding to selection by which selective agent(s). Here, we integrate whole-genome sequencing with phenomics and measures of putative selective agents to assess the extent of adaptive divergence in threespine stickleback occupying the highly heterogeneous lake Mývatn, NE Iceland. We find negligible genome wide divergence, yet multiple traits (body size, gill raker structure and defence traits) were divergent along known ecological gradients (temperature, predatory bird densities and water depth). SNP based heritability of all measured traits was high (h²  = 0.42-0.65), indicating adaptive potential for all traits. Environment-association analyses further identified thousands of loci putatively involved in selection, related to genes linked to, for instance, neuron development and protein phosphorylation. Finally, we found that loci linked to water depth were concurrently associated with pelvic spine length variation - supporting the conclusion that divergence in pelvic spine length occurred in the face of gene flow. Our results suggest that whilst there is substantial genetic variation in the traits measured, phenotypic divergence of Mývatn stickleback is mostly weakly associated with environmental gradients, potentially as a result of substantial gene flow. Our study illustrates the value of integrative studies that combine genomic assays of multivariate trait variation with landscape genomics.

Common and ethnic-specific genetic determinants of hemoglobin concentration between Taiwanese Han Chinese and European Whites: findings from comparative two-stage genome-wide association studies

Human iron nutrition is a result of interplays between genetic and environmental factors. However, there has been scarcity of data on the genetic variants associated with altered iron homeostasis and ethnic-specific associations are further lacking. In this study, we compared between the Taiwanese Han Chinese (HC) and European Whites the genetic determinants of hemoglobin (Hb) concentration, a biochemical parameter that in part reflects the amount of functional iron in the body. Through sex-specific two-stage genome-wide association studies (2S-GWAS), we observed the consistent Hb-association of SNPs in TMPRSS6 (chr 22), ABO (chr 9), and PRKCE (chr 2) across sexes in both ethnic groups. Specific to the Taiwanese HC, the Hb-association of AXIN1, together with other loci near the chr 16 alpha-globin gene cluster, was found novel. On the other hand, majority of the Hb-associated SNPs among Europeans were identified along the chr 6 major histocompatibility complex (MHC) region, which has established roles in immune system control. We report here strong Hb-associations of HFE and members of gene families (SLC17; H2A, H2B, H3, H4, H1; TRIM; ZSCAN, ZKSCAN, ZNF; HLA; BTN, OR), numerous SNPs in/nearby CARMIL1, PRRC2A, PSORS1C1, NOTCH4, TSBP1, C6orf15, and distinct associations with non-coding RNA genes. Our findings provide evidence for both common and ethnic-specific genetic determinants of Hb between East Asians and Caucasians. These will help to further our understanding of the iron and/or erythropoiesis physiology in humans and to identify high risk subgroups for iron imbalances - a primary requirement to meet the goal of precision nutrition for optimal health.

Benchmarking post-GWAS analysis tools in major depression: Challenges and implications

Our knowledge of complex disorders has increased in the last years thanks to the identification of genetic variants (GVs) significantly associated with disease phenotypes by genome-wide association studies (GWAS). However, we do not understand yet how these GVs functionally impact disease pathogenesis or their underlying biological mechanisms. Among the multiple post-GWAS methods available, fine-mapping and colocalization approaches are commonly used to identify causal GVs, meaning those with a biological effect on the trait, and their functional effects. Despite the variety of post-GWAS tools available, there is no guideline for method eligibility or validity, even though these methods work under different assumptions when accounting for linkage disequilibrium and integrating molecular annotation data. Moreover, there is no benchmarking of the available tools. In this context, we have applied two different fine-mapping and colocalization methods to the same GWAS on major depression (MD) and expression quantitative trait loci (eQTL) datasets. Our goal is to perform a systematic comparison of the results obtained by the different tools. To that end, we have evaluated their results at different levels: fine-mapped and colocalizing GVs, their target genes and tissue specificity according to gene expression information, as well as the biological processes in which they are involved. Our findings highlight the importance of fine-mapping as a key step for subsequent analysis. Notably, the colocalizing variants, altered genes and targeted tissues differed between methods, even regarding their biological implications. This contribution illustrates an important issue in post-GWAS analysis with relevant consequences on the use of GWAS results for elucidation of disease pathobiology, drug target prioritization and biomarker discovery.

Analysis of chromatin data supports a role for CD14+ monocytes/macrophages in mediating genetic risk for juvenile idiopathic arthritis

Introduction

Genome wide association studies (GWAS) have identified multiple regions that confer genetic risk for the polyarticular/oligoarticular forms of juvenile idiopathic arthritis (JIA). However, genome-wide scans do not identify the cells impacted by genetic polymorphisms on the risk haplotypes or the genes impacted by those variants. We have shown that genetic variants driving JIA risk are likely to affect both innate and adaptive immune functions. We provide additional evidence that JIA risk variants impact innate immunity.

Materials and methods

We queried publicly available H3K4me1/H3K27ac ChIP-seq data in CD14+ monocytes to determine whether the linkage disequilibrium (LD) blocks incorporating the SNPs that tag JIA risk loci showed enrichment for these epigenetic marks. We also queried monocyte/macrophage GROseq data, a functional readout of active enhancers. We defined the topologically associated domains (TADs) encompassing enhancers on the risk haplotypes and identified genes within those TADs expressed in monocytes. We performed ontology analyses of these genes to identify cellular processes that may be impacted by these variants. We also used whole blood RNAseq data from the Genotype-Tissue Expression (GTEx) data base to determine whether SNPs lying within monocyte GROseq peaks influence plausible target genes within the TADs encompassing the JIA risk haplotypes.

Results

The LD blocks encompassing the JIA genetic risk regions were enriched for H3K4me1/H3K27ac ChIPseq peaks (p=0.00021 and p=0.022) when compared to genome background. Eleven and sixteen JIA were enriched for resting and activated macrophage GROseq peaks, respectively risk regions (p=0.04385 and p=0.00004). We identified 321 expressed genes within the TADs encompassing the JIA haplotypes in human monocytes. Ontological analysis of these genes showed enrichment for multiple immune functions. Finally, we found that SNPs lying within the GROseq peaks are strongly associated with expression levels of plausible target genes in human whole blood.

Conclusions

These findings support the idea that both innate and adaptive immunity are impacted by JIA genetic risk variants.

Structural network alterations in focal and generalized epilepsy assessed in a worldwide ENIGMA study follow axes of epilepsy risk gene expression

Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-transcriptomic signatures could potentially guide diagnosis or tailor therapeutic approaches to specific epilepsy syndromes.

Functional Genomics Analysis to Disentangle the Role of Genetic Variants in Major Depression

Understanding the molecular basis of major depression is critical for identifying new potential biomarkers and drug targets to alleviate its burden on society. Leveraging available GWAS data and functional genomic tools to assess regulatory variation could help explain the role of major depression-associated genetic variants in disease pathogenesis. We have conducted a fine-mapping analysis of genetic variants associated with major depression and applied a pipeline focused on gene expression regulation by using two complementary approaches: cis-eQTL colocalization analysis and alteration of transcription factor binding sites. The fine-mapping process uncovered putative causally associated variants whose proximal genes were linked with major depression pathophysiology. Four colocalizing genetic variants altered the expression of five genes, highlighting the role of SLC12A5 in neuronal chlorine homeostasis and MYRF in nervous system myelination and oligodendrocyte differentiation. The transcription factor binding analysis revealed the potential role of rs62259947 in modulating P4HTM expression by altering the YY1 binding site, altogether regulating hypoxia response. Overall, our pipeline could prioritize putative causal genetic variants in major depression. More importantly, it can be applied when only index genetic variants are available. Finally, the presented approach enabled the proposal of mechanistic hypotheses of these genetic variants and their role in disease pathogenesis.

Identifying genes targeted by disease-associated non-coding SNPs with a protein knowledge graph

Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) that play important roles in the genetic heritability of traits and diseases. With most of these SNPs located on the non-coding part of the genome, it is currently assumed that these SNPs influence the expression of nearby genes on the genome. However, identifying which genes are targeted by these disease-associated SNPs remains challenging. In the past, protein knowledge graphs have often been used to identify genes that are associated with disease, also referred to as “disease genes”. Here, we explore whether protein knowledge graphs can be used to identify genes that are targeted by disease-associated non-coding SNPs by testing and comparing the performance of six existing methods for a protein knowledge graph, four of which were developed for disease gene identification. We compare our performance against two baselines: (1) an existing state-of-the-art method that is based on guilt-by-association, and (2) the leading assumption that SNPs target the nearest gene on the genome. We test these methods with four reference sets, three of which were obtained by different means. Furthermore, we combine methods to investigate whether their combination improves performance. We find that protein knowledge graphs that include predicate information perform comparable to the current state of the art, achieving an area under the receiver operating characteristic curve (AUC) of 79.6% on average across all four reference sets. Protein knowledge graphs that lack predicate information perform comparable to our other baseline (genetic distance) which achieved an AUC of 75.7% across all four reference sets. Combining multiple methods improved performance to 84.9% AUC. We conclude that methods for a protein knowledge graph can be used to identify which genes are targeted by disease-associated non-coding SNPs.

Large-Scale Multi-Omics Studies Provide New Insights into Blood Pressure Regulation

Recent genome-wide association studies uncovered part of blood pressure’s heritability. However, there is still a vast gap between genetics and biology that needs to be bridged. Here, we followed up blood pressure genome-wide summary statistics of over 750,000 individuals, leveraging comprehensive epigenomic and transcriptomic data from blood with a follow-up in cardiovascular tissues to prioritise likely causal genes and underlying blood pressure mechanisms. We first prioritised genes based on coding consequences, multilayer molecular associations, blood pressure-associated expression levels, and coregulation evidence. Next, we followed up the prioritised genes in multilayer studies of genomics, epigenomics, and transcriptomics, functional enrichment, and their potential suitability as drug targets. Our analyses yielded 1880 likely causal genes for blood pressure, tens of which are targets of the available licensed drugs. We identified 34 novel genes for blood pressure, supported by more than one source of biological evidence. Twenty-eight (82%) of these new genes were successfully replicated by transcriptome-wide association analyses in a large independent cohort (n = ~220,000). We also found a substantial mediating role for epigenetic regulation of the prioritised genes. Our results provide new insights into genetic regulation of blood pressure in terms of likely causal genes and involved biological pathways offering opportunities for future translation into clinical practice.

Identification of healthspan-promoting genes in Caenorhabditis elegans based on a human GWAS study

To find drivers of healthy ageing, a genome-wide association study (GWAS) was performed in healthy and unhealthy older individuals. Healthy individuals were defined as free from cardiovascular disease, stroke, heart failure, major adverse cardiovascular event, diabetes, dementia, cancer, chronic obstructive pulmonary disease (COPD), asthma, rheumatism, Crohn’s disease, malabsorption or kidney disease. Six single nucleotide polymorphisms (SNPs) with unknown function associated with ten human genes were identified as candidate healthspan markers. Thirteen homologous or closely related genes were selected in the model organism C. elegans for evaluating healthspan after targeted RNAi-mediated knockdown using pathogen resistance, muscle integrity, chemotaxis index and the activity of known longevity and stress response pathways as healthspan reporters. In addition, lifespan was monitored in the RNAi-treated nematodes. RNAi knockdown of yap-1, wwp-1, paxt-1 and several acdh genes resulted in heterogeneous phenotypes regarding muscle integrity, pathogen resistance, chemotactic behaviour, and lifespan. Based on these observations, we hypothesize that their human homologues WWC2, CDKN2AIP and ACADS may play a role in health maintenance in the elderly.

Genetics of Base Coat Colour Variations and Coat Colour-Patterns of the South African Nguni Cattle Investigated Using High-Density SNP Genotypes

Nguni cattle are a Sanga type breed with mixed B. taurus and B. indicus ancestry and proven resistance to ticks, diseases and other harsh conditions of the African geographical landscape. The multi-coloured Nguni coats have found a niche market in the leather industry leading to breeding objectives towards the promotion of such diversity. However, there is limited studies on the genomic architecture underlying the coat colour and patterns hampering any potential breeding and improvement of such trait. This study investigated the genetics of base coat colour, colour-sidedness and the white forehead stripe in Nguni cattle using coat colour phenotyped Nguni cattle and Illumina Bovine HD (770K) genotypes. Base coat colour phenotypes were categorised into eumelanin (n = 45) and pheomelanin (n = 19). Animals were categorised into either colour-sided (n = 46) or non-colour-sided (n = 94) and similarly into presence (n = 15) or absence (n = 67) of white forehead stripe. Genome-wide association tests were conducted using 622,103 quality controlled SNPs and the Efficient Mixed Model Association eXpedited method (EMMAX) implemented in Golden Helix SNP Variation Suite. The genome-wide association studies for base coat colour (eumelanin vs. pheomelanin) resulted into four indicative SNPs on BTA18 and a well-known gene, MC1R, was observed within 1 MB from the indicative SNPs (p < 0.00001) and found to play a role in the melanogenesis (core pathway for melanin production) and the MAPK signalling pathway. GWAS for colour-sidedness resulted in four indicative SNPs, none of which were in close proximity to the KIT candidate gene known for colour-sidedness. GWAS for the white forehead stripe resulted in 17 indicative SNPs on BTA6. Four genes MAPK10, EFNA5, PPP2R3C and PAK1 were found to be associated with the white forehead stripe and were part of the MAPK, adrenergic and Wnt signalling pathways that are synergistically associated with the synthesis of melanin. Overall, our results prove prior knowledge of the role of MC1R in base coat colours in cattle and suggested a different genetic mechanism for forehead stripe phenotypes in Nguni cattle.

Association of PTPN22 SNP1858 (rs2476601) and Gene SNP1123 (rs2488457) Polymorphism With Primary Immune Thrombocytopenia Susceptibility: A Meta-Analysis of Case-Control Studies and Trial Sequential Analysis

Objective: Systematic review of the association of protein tyrosine phosphatase non-receptor type 22 (PTPN22) gene 1858 and 1123 sites single nucleotide polymorphism (SNP) with the susceptibility of primary immune thrombocytopenia (ITP).

Method: Database searched includes PubMed, Embase, Web of Science, CNKI, CBM, VIP and WanFang Data. The retrieval period is from the establishment of the database to 30 June 2021. After screening articles according to inclusion and exclusion criteria, the data were extracted and methodological quality of the included studies was evaluated. Meta-analysis was performed using RevMan 5.4 and Stata 16.0 software. The combined OR value and its 95%CI were calculated. Sensitivity analysis and publication bias assessment were performed. Trial sequential analysis (TSA) was performed using TSA 0.9.5.10 Beta software.

Results: A total of 10 studies with 10 articles were included, with a total of 932 cases and 2,112 controls. The results of meta-analysis showed that for SNP1858, the susceptibility of TT genotype to ITP was 5.01 times higher than CC genotype [95%CI (1.81, 13.86), p = 0.002]. For SNP1123, G allele carriers were more susceptible to ITP than C allele carriers [OR = 1.23, 95%CI (1.05, 1.45), p = 0.01], and GG genotype carriers were 1.51 times more susceptible to ITP than CC genotype carriers [95%CI (1.11, 2.06), p = 0.009]. Although the results are statistically significant, the results of sensitivity analysis showed certain limitations of stability, and the TSA analysis still indicated the possibility of false positive. No significant publication bias was observed.

Conclusion: PTPN22 gene SNP1858 (rs2476601) and SNP1123 (rs2488457) polymorphisms are associated with susceptibility to primary immune thrombocytopenia. Due to the limitation of the number and quality of the included studies, the above conclusions need to be verified by more high-quality studies.

Genomic Regions, Molecular Markers, and Flanking Genes of Metribuzin Tolerance in Wheat (Triticum aestivum L.)

Understanding the genetics of metribuzin (a group C herbicide) tolerance in wheat is vital in developing tolerant cultivars to improve wheat productivity in dryland farming systems. This study investigated metribuzin tolerance in wheat by conducting a Genome-wide Association Studies (GWAS) with a panel of 150 wheat genotypes of diverse genetic backgrounds and genotyped them with the wheat 90 K SNP genotyping assay. The phenotyping was conducted in a temperature-controlled glasshouse at the University of Western Australia (UWA). Genotypes were sprayed with a metribuzin dose of 400 grams of active ingredient (g. a.i.) ha^-1 as pre-emergent in a specialized spraying cabinet and transferred to the glasshouse where the tolerance level of the genotypes was assessed by measuring the relative reduction in chlorophyll content of the leaves. The decrease in chlorophyll content of the treated plants compared to the control was regarded as the phytotoxic effects of metribuzin. GWAS analysis following a mixed linear model revealed 19 genomic regions with significant marker-trait associations (MTAs), including ten on chromosome 6A, three on chromosome 2B, and one on chromosomes 3A, 5B, 6B 6D, 7A, and 7B, respectively. Sequences of the significant markers were blasted against the wheat genome, IWGSC RefSeq V1.0, and candidate genes having annotations related to herbicide tolerance in wheat, especially in pathways reported to be involved in metribuzin tolerance, such as cytochrome P450 pathways and ATP Binding Cassette (ABC) superfamilies, were identified in these genomic regions. These included TraesCS6A01G028800, TraesCS6A02G353700, TraesCS6A01G326200, TraesCS7A02G331000, and TraesCS2B01G465200. These genomic regions were validated on 30 top tolerant and 30 most susceptible genotypes using the five closest SSR makers to the flanked SNPs. Sufficient polymorphism was detected on two markers (wms193 and barc1036) that were found to differentiate between the susceptible and tolerant alleles and a t-test analysis of the phenotypic data shows a significant (value of p < 0.001) difference suggesting that these markers can be used for marker-assisted selection (MAS) in metribuzin studies and wheat breeding programs.

Dissecting Meta-Analysis in GWAS Era: Bayesian Framework for Gene/Subnetwork-Specific Meta-Analysis

Over the past decades, advanced high-throughput technologies have continuously contributed to genome-wide association studies (GWASs). GWAS meta-analysis has been increasingly adopted, has cross-ancestry replicability, and has power to illuminate the genetic architecture of complex traits, informing about the reliability of estimation effects and their variability across human ancestries. However, detecting genetic variants that have low disease risk still poses a challenge. Designing a meta-analysis approach that combines the effect of various SNPs within genes or genes within pathways from multiple independent population GWASs may be helpful in identifying associations with small effect sizes and increasing the association power. Here, we proposed ancMETA, a Bayesian graph-based framework, to perform the gene/pathway-specific meta-analysis by combining the effect size of multiple SNPs within genes, and genes within subnetwork/pathways across multiple independent population GWASs to deconvolute the interactions between genes underlying the pathogenesis of complex diseases across human populations. We assessed the proposed framework on simulated datasets, and the results show that the proposed model holds promise for increasing statistical power for meta-analysis of genetic variants underlying the pathogenesis of complex diseases. To illustrate the proposed meta-analysis framework, we leverage seven different European bipolar disorder (BD) cohorts, and we identify variants in the angiotensinogen (AGT) gene to be significantly associated with BD across all 7 studies. We detect a commonly significant BD-specific subnetwork with the ESR1 gene as the main hub of a subnetwork, associated with neurotrophin signaling (p = 4e⁻¹⁴) and myometrial relaxation and contraction (p = 3e⁻⁰⁸) pathways. ancMETA provides a new contribution to post-GWAS methodologies and holds promise for comprehensively examining interactions between genes underlying the pathogenesis of genetic diseases and also underlying ethnic differences.

Identification and Validation of a Chromosome 4D Quantitative Trait Locus Hotspot Conferring Heat Tolerance in Common Wheat (Triticum aestivum L.)

Understanding of the genetic mechanism of heat tolerance (HT) can accelerate and improve wheat breeding in dealing with a warming climate. This study identified and validated quantitative trait loci (QTL) responsible for HT in common wheat. The International Triticeae Mapping Initiative (ITMI) population, recombinant inbreed lines (RILs) derived from a cross between Synthetic W7984 and Opata M85, was phenotyped for shoot length, root length, whole plant length under heat stress and corresponding damage indices (DIs) to compare HT performances of individuals. Wide variations among the RILs were shown for all the traits. A total of 13 QTL including 9 major QTL and 4 minor QTL were identified, distributed on 6 wheat chromosomes. The six major QTL with the highest R² were associated with different traits under heat stress. They were all from Opata M85 background and located within a 2.2 cm interval on chromosome 4D, making up a QTL hotspot conferring HT in common wheat. The QTL hotspot was validated by genotyping-phenotyping association analysis using single-nucleotide-polymorphism (SNP) assays. The QTL, especially the 4D QTL hotspot identified and validated in this study, are valuable for the further fine mapping and identification of key genes and exploring genetic mechanism of HT in wheat.

The functional insight into the genetics of cardiovascular disease: results from the post-GWAS study

Cardiovascular diseases (CVDs), the leading cause of death worldwide, generally refer to a range of pathological conditions with the involvement of the heart and the blood vessels. A sizable fraction of the susceptibility loci is known, but the underlying mechanisms have been established only for a small proportion. Therefore, there is an increasing need to explore the functional relevance of trait-associated variants and, moreover, to search for novel risk genetic variation. We have reported the bioinformatic approach allowing effective identification of functional non-coding variants by integrated analysis of genome-wide data. Here, the analysis of 1361 previously identified regulatory SNPs (rSNPs) was performed to provide new insights into cardiovascular risk. We found 773,471 coding co-segregating markers for input rSNPs using the 1000 Genomes Project. The intersection of GWAS-derived SNPs with a relevance to cardiovascular traits with these markers was analyzed within a window of 10 Kbp. The effects on the transcription factor (TF) binding sites were explored by DeFine models. Functional pathway enrichment and protein– protein interaction (PPI) network analyses were performed on the targets and the extended genes by STRING and DAVID. Eighteen rSNPs were functionally linked to cardiovascular risk. A significant impact on binding sites of thirteen TFs including those involved in blood cells formation, hematopoiesis, macrophage function, inflammation, and vasoconstriction was found in K562 cells. 21 rSNP gene targets and 5 partners predicted by PPI were enriched for spliceosome and endocytosis KEGG pathways, endosome sorting complex and mRNA splicing REACTOME pathways. Related Gene Ontology terms included mRNA splicing and processing, endosome transport and protein catabolic processes. Together, the findings provide further insight into the biological basis of CVDs and highlight the importance of the precise regulation of splicing and alternative splicing.

Chromatin architecture around stroke haplotypes provides evidence that genetic risk is conferred through vascular cells

Introduction: Genome-wide association studies (GWAS) have identified numerous stroke-associated SNPs. To understand how SNPs affect gene expression related to increased stroke risk, we studied epigenetic landscapes surrounding 26 common, validated stroke-associated loci. Methods: We mapped the SNPs to linkage disequilibrium (LD) blocks and examined H3K27ac, H3K4me1, H3K9ac, and H3K4me3 histone marks and transcription-factor binding-sites in pathologically relevant cell types (hematopoietic and vascular cells). Hi-C data were used to identify topologically associated domains (TADs) encompassing the LD blocks and overlapping genes. Results: Fibroblasts, smooth muscle, and endothelial cells showed significant enrichment for enhancer-associated marks within stroke-associated LD blocks. Genes within encompassing TADs reflected vessel homeostasis, cellular turnover, and enzymatic activity. Conclusions: Stroke-associated genetic variants confer risk predominantly through vascular cells rather than hematopoietic cell types.

Historical museum samples enable the examination of divergent and parallel evolution during invasion

During the Anthropocene, Earth has experienced unprecedented habitat loss, native species decline and global climate change. Concurrently, greater globalization is facilitating species movement, increasing the likelihood of alien species establishment and propagation. There is a great need to understand what influences a species’ ability to persist or perish within a new or changing environment. Examining genes that may be associated with a species’ invasion success or persistence informs invasive species management, assists with native species preservation and sheds light on important evolutionary mechanisms that occur in novel environments. This approach can be aided by coupling spatial and temporal investigations of evolutionary processes. Here we use the common starling, Sturnus vulgaris, to identify parallel and divergent evolutionary change between contemporary native and invasive range samples and their common ancestral population. To do this, we use reduced‐representation sequencing of native samples collected recently in northwestern Europe and invasive samples from Australia, together with museum specimens sampled in the UK during the mid‐19th century. We found evidence of parallel selection on both continents, possibly resulting from common global selective forces such as exposure to pollutants. We also identified divergent selection in these populations, which might be related to adaptive changes in response to the novel environment encountered in the introduced Australian range. Interestingly, signatures of selection are equally as common within both invasive and native range contemporary samples. Our results demonstrate the value of including historical samples in genetic studies of invasion and highlight the ongoing and occasionally parallel role of adaptation in both native and invasive ranges.

OUP accepted manuscript

Non-coding variants have long been recognized as important contributors to common disease risks, but with the expansion of clinical whole genome sequencing, examples of rare, high-impact non-coding variants are also accumulating. Despite recent advances in the study of regulatory elements and the availability of specialized data collections, the systematic annotation of non-coding variants from genome sequencing remains challenging. Here, we propose a new framework for the prioritization of non-coding regulatory variants that integrates information about regulatory regions with prediction scores and HPO-based prioritization. Firstly, we created a comprehensive collection of annotations for regulatory regions including a database of 2.4 million regulatory elements (GREEN-DB) annotated with controlled gene(s), tissue(s) and associated phenotype(s) where available. Secondly, we calculated a variation constraint metric and showed that constrained regulatory regions associate with disease-associated genes and essential genes from mouse knock-outs. Thirdly, we compared 19 non-coding impact prediction scores providing suggestions for variant prioritization. Finally, we developed a VCF annotation tool (GREEN-VARAN) that can integrate all these elements to annotate variants for their potential regulatory impact. In our evaluation, we show that GREEN-DB can capture previously published disease-associated non-coding variants as well as identify additional candidate disease genes in trio analyses.

Integration of genome-wide association studies and gene coexpression networks unveils promising soybean resistance genes against five common fungal pathogens

Soybean is one of the most important legume crops worldwide. However, soybean yield is dramatically affected by fungal diseases, leading to economic losses of billions of dollars yearly. Here, we integrated publicly available genome-wide association studies and transcriptomic data to prioritize candidate genes associated with resistance to Cadophora gregata, Fusarium graminearum, Fusarium virguliforme, Macrophomina phaseolina, and Phakopsora pachyrhizi. We identified 188, 56, 11, 8, and 3 high-confidence candidates for resistance to F. virguliforme, F. graminearum, C. gregata, M. phaseolina and P. pachyrhizi, respectively. The prioritized candidate genes are highly conserved in the pangenome of cultivated soybeans and are heavily biased towards fungal species-specific defense responses. The vast majority of the prioritized candidate resistance genes are related to plant immunity processes, such as recognition, signaling, oxidative stress, systemic acquired resistance, and physical defense. Based on the number of resistance alleles, we selected the five most resistant accessions against each fungal species in the soybean USDA germplasm. Interestingly, the most resistant accessions do not reach the maximum theoretical resistance potential. Hence, they can be further improved to increase resistance in breeding programs or through genetic engineering. Finally, the coexpression network generated here is available in a user-friendly web application ( https://soyfungigcn.venanciogroup.uenf.br/ ) and an R/Shiny package ( https://github.com/almeidasilvaf/SoyFungiGCN ) that serve as a public resource to explore soybean-pathogenic fungi interactions at the transcriptional level.

Effects of Maternal Nutrition on Female Offspring Weight Gain and Sexual Development

Maternal nutrition during pregnancy influences postnatal life of animals; nevertheless, few studies have investigated its effects on the productive performance and reproductive development of heifers. This study evaluated the performance, reproductive development, and correlation between reproduction × fat thickness and performance × ribeye area (REA) traits of heifers. We also performed an exploratory genomic association during the rearing period in heifers submitted to fetal programming. The study comprised 55 Nellore heifers born to dams exposed to one of the following nutritional planes: control, without protein-energy supplementation; PELT, protein-energy last trimester, protein-energy supplementation offered in the final third of pregnancy; and PEWG, protein-energy whole gestation, protein-energy supplementation upon pregnancy confirmation. Protein-energy supplementation occurred at the level of 0.3% live weight. After weaning, heifers were submitted to periodic evaluations of weight and body composition by ultrasonography. From 12 to 18 months, we evaluated the reproductive tract of heifers to monitor its development for sexual precocity and ovarian follicle population. The treatments had no effect (p > 0.05) on average daily gain; however, the weight of the animals showed a significant difference over time (p = 0.017). No differences were found between treatments for REA, backfat, and rump fat thickness, nor for puberty age, antral follicular count, and other traits related to reproductive tract development (p > 0.05). The correlation analysis between performance traits and REA showed high correlations (r > 0.37) between REA at weaning and year versus weight from weaning until yearling; however, no correlation was found for reproductive development traits versus fat thickness (p > 0.05). The exploratory genomic association study showed one single-nucleotide polymorphism (SNP) for each treatment on an intergenic region for control and PEWG, and the one for PELT on an intronic region of RAPGEF1 gene. Maternal nutrition affected only the weight of the animals throughout the rearing period.

A Genome-Wide Association Study Identifies Novel Risk Loci for Sarcopenia in a Taiwanese Population

Purpose

A genome-wide association study (GWAS) of sarcopenia unraveled the importance of genetic contribution to decline in muscle. The current study investigated sarcopenia-related single nucleotide polymorphisms (SNPs) in Asian older adults, and further constructed a genotype score that tests the combined effect of these SNPs on risk of sarcopenia.

Patients and Methods

Ninety-six subjects aged 60 or above were recruited from the database of annual geriatric health examination at Tri-Service General Hospital during 2020. Eligible criteria included: 1) not having severe comorbidities; 2) agreed to join the Taiwan Precision Medicine Initiative project; and 3) having sufficient information of required sarcopenic measurements. Genotype–phenotype association analysis was performed to find SNPs that were significantly associated with each of three sarcopenic indices (low muscle mass, muscle strength, and physical performance). Subsequently, these SNPs comprised a sarcopenia-related genotype score that summed up the number of SNPs carrying unfavorable allele(s).

Results

Twelve SNPs revealed suggestive genome-wide significance with the three sarcopenic indices, and eight of them revealed a relationship with more than one index. Low muscle strength was the item that had the most (eight) related SNPs. Among them, rs10282247 affects cholesterol binding and rs7022373 participates in cellular apoptosis. In addition, higher genotype score demonstrated higher risk of sarcopenia (≥4 points: OR=630.6; 2–3 points: OR=408, p-value<0.001).

Conclusion

Several newly discovered SNPs suggest that genetic contribution plays a part in the pathogenesis of sarcopenia. Further studies are warranted to verify the underlying mechanisms. Moreover, a genotype score provides an estimate of the combined effect of genetic association with sarcopenia, which may modestly improve clinical risk classification.

Host genetic factors associated with the range limit of a European hantavirus

The natural host ranges of many viruses are restricted to very specific taxa. Little is known about the molecular barriers between species that lead to the establishment of this restriction or generally prevent virus emergence in new hosts. Here, we identify genomic polymorphisms in a natural rodent host associated with a strong genetic barrier to the transmission of European Tula orthohantavirus (TULV). We analysed the very abrupt spatial transition between two major phylogenetic clades in TULV across the comparatively much wider natural hybrid zone between evolutionary lineages of their reservoir host, the common vole (Microtus arvalis). Genomic scans of 79,225 single nucleotide polymorphisms (SNPs) in 323 TULV‐infected host individuals detected 30 SNPs that were consistently associated with the TULV clades CEN.S or EST.S in two replicate sampling transects. Focusing the analysis on 199 voles with evidence of genomic admixture at the individual level (0.1–0.9) supported statistical significance for all 30 loci. Host genomic variation at these SNPs explained up to 37.6% of clade‐specific TULV infections. Genes in the vicinity of associated SNPs include SAHH, ITCH and two members of the Syngr gene family, which are involved in functions related to immune response or membrane transport. This study demonstrates the relevance of natural hybrid zones as systems not only for studying processes of evolutionary divergence and speciation, but also for the detection of evolving genetic barriers for specialized parasites.

Genome-Wide Association Study to Map Genomic Regions Related to the Initiation Time of Four Growth Stage Traits in Soybean

The time to flowering (DF), pod beginning (DPB), seed formation (DSF), and maturity initiation (DMI) in soybean (Glycine max [L.] Merr) are important characteristics of growth stage traits (GSTs) in Chinese summer-sowing soybean, and are influenced by genetic as well as environmental factors. To better understand the molecular mechanism underlying the initiation times of GSTs, we investigated four GSTs of 309 diverse soybean accessions in six different environments and Best Linear Unbiased Prediction values. Furthermore, the genome-wide association study was conducted by a Fixed and random model Circulating Probability Unification method using over 60,000 single nucleotide polymorphism (SNP) markers to identify the significant quantitative trait nucleotide (QTN) regions with phenotypic data. As a result, 212 SNPs within 102 QTN regions were associated with four GSTs. Of which, eight stable regions were repeatedly detected in least three datasets for one GST. Interestingly, half of the QTN regions overlapped with previously reported quantitative trait loci or well-known soybean growth period genes. The hotspots associated with all GSTs were concentrated on chromosome 10. E2 (Glyma10g36600), a gene with a known function in regulating flowering and maturity in soybean, is also found on this chromosome. Thus, this genomic region may account for the strong correlation among the four GSTs. All the significant SNPs in the remaining 7 QTN regions could cause the significant phenotypic variation with both the major and minor alleles. Two hundred and seventy-five genes in soybean and their homologs in Arabidopsis were screened within ± 500 kb of 7 peak SNPs in the corresponding QTN regions. Most of the genes are involved in flowering, response to auxin stimulus, or regulation of seed germination, among others. The findings reported here provide an insight for genetic improvement which will aid in breeding of soybean cultivars that can be adapted to the various summer sowing areas in China and beyond.

Transcription Factor-7-Like-2 (TCF7L2) in Atherosclerosis: A Potential Biomarker and Therapeutic Target

Transcription factor-7-like-2 (TCF7L2), a vital member of the T-cell factor/lymphoid enhancer factor (TCF/LEF) family, plays an important role in normal human physiological and pathological processes. TCF7L2 exhibits multiple anti-atherosclerotic effects through the activation of specific molecular mechanisms, including regulation of metabolic homeostasis, macrophage polarization, and neointimal hyperplasia. A single-nucleotide substitution of TCF7L2, rs7903146, is a genetic high-risk factor for type 2 diabetes and indicates susceptibility to cardiovascular disease as a link between metabolic disorders and atherosclerosis. In this review, we summarize the anti-atherosclerosis effect and novel mechanisms underlying the function of TCF7L2 to elucidate its potential as an anti-atherosclerosis biomarker and provide a novel therapeutic target for cardiovascular diseases.

Mapping gene and gene pathways associated with coronary artery disease: a CARDIoGRAM exome and multi-ancestry UK biobank analysis

Coronary artery disease (CAD) genome-wide association studies typically focus on single nucleotide variants (SNVs), and many potentially associated SNVs fail to reach the GWAS significance threshold. We performed gene and pathway-based association (GBA) tests on publicly available Coronary ARtery DIsease Genome wide Replication and Meta-analysis consortium Exome (n = 120,575) and multi ancestry pan UK Biobank study (n = 442,574) summary data using versatile gene-based association study (VEGAS2) and Multi-marker analysis of genomic annotation (MAGMA) to identify novel genes and pathways associated with CAD. We included only exonic SNVs and excluded regulatory regions. VEGAS2 and MAGMA ranked genes and pathways based on aggregated SNV test statistics. We used Bonferroni corrected gene and pathway significance threshold at 3.0 × 10^-6 and 1.0 × 10^-5, respectively. We also report the top one percent of ranked genes and pathways. We identified 17 top enriched genes with four genes (PCSK9, FAM177, LPL, ARGEF26), reaching statistical significance (p ≤ 3.0 × 10^-6) using both GBA tests in two GWAS studies. In addition, our analyses identified ten genes (DUSP13, KCNJ11, CD300LF/RAB37, SLCO1B1, LRRFIP1, QSER1, UBR2, MOB3C, MST1R, and ABCC8) with previously unreported associations with CAD, although none of the single SNV associations within the genes were genome-wide significant. Among the top 1% non-lipid pathways, we detected pathways regulating coagulation, inflammation, neuronal aging, and wound healing.

Understanding the impact of SNPs associated with autism spectrum disorder on biological pathways in the human fetal and adult cortex

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by significant and complex genetic etiology. GWAS studies have identified genetic variants associated with ASD, but the functional impacts of these variants remain unknown. Here, we integrated four distinct levels of biological information (GWAS, eQTL, spatial genome organization and protein-protein interactions) to identify potential regulatory impacts of ASD-associated SNPs (p < 5 × 10^-8) on biological pathways within fetal and adult cortical tissues. We found 80 and 58 SNPs that mark regulatory regions (i.e. expression quantitative trait loci or eQTLs) in the fetal and adult cortex, respectively. These eQTLs were also linked to other psychiatric disorders (e.g. schizophrenia, ADHD, bipolar disorder). Functional annotation of ASD-associated eQTLs revealed that they are involved in diverse regulatory processes. In particular, we found significant enrichment of eQTLs within regions repressed by Polycomb proteins in the fetal cortex compared to the adult cortex. Furthermore, we constructed fetal and adult cortex-specific protein-protein interaction networks and identified that ASD-associated regulatory SNPs impact on immune pathways, fatty acid metabolism, ribosome biogenesis, aminoacyl-tRNA biosynthesis and spliceosome in the fetal cortex. By contrast, in the adult cortex they largely affect immune pathways. Overall, our findings highlight potential regulatory mechanisms and pathways important for the etiology of ASD in early brain development and adulthood. This approach, in combination with clinical studies on ASD, will contribute to individualized mechanistic understanding of ASD development.

The effects of climate and demographic history in shaping genomic variation across populations of the Desert Horned Lizard (Phrynosoma platyrhinos)

Species often experience spatial environmental heterogeneity across their range, and populations may exhibit signatures of adaptation to local environmental characteristics. Other population genetic processes, such as migration and genetic drift, can impede the effects of local adaptation. Genetic drift in particular can have a pronounced effect on population genetic structure during large-scale geographic expansions, where a series of founder effects leads to decreases in genetic variation in the direction of the expansion. Here, we explore the genetic diversity of a desert lizard that occupies a wide range of environmental conditions and that has experienced post-glacial expansion northwards along two colonization routes. Based on our analyses of a large SNP data set, we find evidence that both climate and demographic history have shaped the genetic structure of populations. Pronounced genetic differentiation was evident between populations occupying cold versus hot deserts, and we detected numerous loci with significant associations with climate. The genetic signal of founder effects, however, is still present in the genomes of the recently expanded populations, which comprise subsets of genetic variation found in the southern populations.

A Panel of rSNPs Demonstrating Allelic Asymmetry in Both ChIP-seq and RNA-seq Data and the Search for Their Phenotypic Outcomes through Analysis of DEGs

Currently, the detection of the allele asymmetry of gene expression from RNA-seq data or the transcription factor binding from ChIP-seq data is one of the approaches used to identify the functional genetic variants that can affect gene expression (regulatory SNPs or rSNPs). In this study, we searched for rSNPs using the data for human pulmonary arterial endothelial cells (PAECs) available from the Sequence Read Archive (SRA). Allele-asymmetric binding and expression events are analyzed in paired ChIP-seq data for H3K4me3 mark and RNA-seq data obtained for 19 individuals. Two statistical approaches, weighted z-scores and predicted probabilities, were used to improve the efficiency of finding rSNPs. In total, we identified 14,266 rSNPs associated with both allele-specific binding and expression. Among them, 645 rSNPs were associated with GWAS phenotypes; 4746 rSNPs were reported as eQTLs by GTEx, and 11,536 rSNPs were located in 374 candidate transcription factor binding motifs. Additionally, we searched for the rSNPs associated with gene expression using an SRA RNA-seq dataset for 281 clinically annotated human postmortem brain samples and detected eQTLs for 2505 rSNPs. Based on these results, we conducted Gene Ontology (GO), Disease Ontology (DO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and constructed the protein-protein interaction networks to represent the top-ranked biological processes with a possible contribution to the phenotypic outcome.

GWAS of pod morphological and color characters in common bean

BACKGROUND

Common bean (Phaseolus vulgaris L.) is an important legume species which can be consumed as immature pods and dry seeds after re-hydration and cooking. Many genes and QTL, and epistatic interactions among them, condition pod morphological traits. However, not all them have been mapped or validated nor candidate genes proposed. We sought to investigate the genomic regions conditioning pod morphological and color characters through GWAS.

RESULTS

Single and multi-locus genome wide association analysis was used to investigate pod traits for a set of 301 bean lines of the Spanish Diversity Panel (SDP). The SDP was genotyped with 32,812 SNPs obtained from Genotyping by Sequencing. The panel was grown in two seasons and phenotypic data were recorded for 17 fresh pods traits grouped in four pod characters: pod length, pod cross-section, pod color, and number of seeds per pod. In all, 23 QTL for pod length, 6 for cross-section, 18 for pod color, 6 for number of seeds per pod and 9 associated to two or more pod characters were detected. Most QTL were located in the telomeric region of chromosomes Pv01, Pv02, Pv04, Pv08, Pv09 and Pv10. Eighteen detected QTL co-localized with 28 previously reported QTL. Twenty-one potential candidate genes involving developmental processes were detected underlying 11 QTL for pod morphological characters, four of them homologous to A. thaliana genes FIS2, SPL10, TTG2 and AML4 affecting silique size. Eight potential candidate genes involved in pigment synthesis, were found underlying five QTL for pod color.

CONCLUSIONS

GWAS for pod morphological and color characters in the bean Spanish Diversity Panel revealed 62 QTL, 18 co-localized with previously reported QTL, and 16 QTL were underlain by 25 candidate genes. Overall 44 new QTL identified and 18 existing QTL contribute to a better understanding of the complex inheritance of pod size and color traits in common bean and open the opportunity for future validation works.

Identifying high-confidence capture Hi-C interactions using CHiCANE

The ability to identify regulatory interactions that mediate gene expression changes through distal elements, such as risk loci, is transforming our understanding of how genomes are spatially organized and regulated. Capture Hi-C (CHi-C) is a powerful tool to delineate such regulatory interactions. However, primary analysis and downstream interpretation of CHi-C profiles remains challenging and relies on disparate tools with ad-hoc input/output formats and specific assumptions for statistical modeling. Here we present a data processing and interaction calling toolkit (CHiCANE), specialized for the analysis and meaningful interpretation of CHi-C assays. In this protocol, we demonstrate applications of CHiCANE to region capture Hi-C (rCHi-C) and promoter capture Hi-C (pCHi-C) libraries, followed by quality assessment of interaction peaks, as well as downstream analysis specific to rCHi-C and pCHi-C to aid functional interpretation. For a typical rCHi-C/pCHi-C dataset this protocol takes up to 3 d for users with a moderate understanding of R programming and statistical concepts, although this is dependent on dataset size and compute power available. CHiCANE is freely available at https://cran.r-project.org/web/packages/chicane .

Identification of Candidate Genes for Root Traits Using Genotype-Phenotype Association Analysis of Near-Isogenic Lines in Hexaploid Wheat (Triticum aestivum L.)

Global wheat (Triticum aestivum L.) production is constrained by different biotic and abiotic stresses, which are increasing with climate change. An improved root system is essential for adaptability and sustainable wheat production. In this study, 10 pairs of near-isogenic lines (NILs)-targeting four genomic regions (GRs) on chromosome arms 4BS, 4BL, 4AS, and 7AL of hexaploid wheat-were used to phenotype root traits in a semi-hydroponic system. Seven of the 10 NIL pairs significantly differed between their isolines for 11 root traits. The NIL pairs targeting qDSI.4B.1 GR varied the most, followed by the NIL pair targeting qDT.4A.1 and QHtscc.ksu-7A GRs. For pairs 5-7 targeting qDT.4A.1 GR, pair 6 significantly differed in the most root traits. Of the 4 NIL pairs targeting qDSI.4B.1 GR, pairs 2 and 4 significantly differed in 3 and 4 root traits, respectively. Pairs 9 and 10 targeting QHtscc.ksu-7A GR significantly differed in 1 and 4 root traits, respectively. Using the wheat 90K Illumina iSelect array, we identified 15 putative candidate genes associated with different root traits in the contrasting isolines, in which two UDP-glycosyltransferase (UGT)-encoding genes, TraesCS4A02G185300 and TraesCS4A02G442700, and a leucine-rich repeat receptor-like protein kinase (LRR-RLK)-encoding gene, TraesCS4A02G330900, also showed important functions for root trait control in other crops. This study characterized, for the first time, that these GRs control root traits in wheat, and identified candidate genes, although the candidate genes will need further confirmation and validation for marker-assisted wheat breeding.