Results Of Genome-wide Association Studies Research Articles

Comparative Analysis of Multiple GWAS Results Identifies Metabolic Pathways Associated with Resistance to A. flavus Infection and Aflatoxin Accumulation in Maize.

Aflatoxins are carcinogenic secondary metabolites produced by several species of Aspergillus, including Aspergillus flavus, an important ear rot pathogen in maize. Most commercial corn hybrids are susceptible to infection by A. flavus, and aflatoxin contaminated grain causes economic damage to farmers. The creation of inbred lines resistant to Aspergillus fungal infection or the accumulation of aflatoxins would be aided by knowing the pertinent alleles and metabolites associated with resistance in corn lines. Multiple Quantitative Trait Loci (QTL) and association mapping studies have uncovered several dozen potential genes, but each with a small effect on resistance. Metabolic pathway analysis, using the Pathway Association Study Tool (PAST), was performed on aflatoxin accumulation resistance using data from four Genome-wide Association Studies (GWAS). The present research compares the outputs of these pathway analyses and seeks common metabolic mechanisms underlying each. Genes, pathways, metabolites, and mechanisms highlighted here can contribute to improving phenotypic selection of resistant lines via measurement of more specific and highly heritable resistance-related traits and genetic gain via marker assisted or genomic selection with multiple SNPs linked to resistance-related pathways.

177 GENOME-WIDE ASSOCIATION ANALYSIS OF THE FRAILTY PHENOTYPE IN UK BIOBANK HIGHLIGHTS CARDIOMETABOLIC AND AUTOIMMUNE SIGNATURES IN AGEING

Abstract Background Frailty is a state of advanced biological age that is characterized by multisystem physiological decline and advanced risk to adverse health outcomes. One approach to defining frailty is using the Fried frailty phenotype, a five-point list of health-related criteria used to score individuals as non-frail, pre-frail, or frail. The biological basis of frailty is not fully understood, nor why some experience frailty at younger ages. Between 30%-45% of frailty risk is estimated to be genetic. This study aimed to investigate the genetic basis of frailty phenotype risk using data from UK Biobank. Methods UK Biobank is a large-scale biomedical database of community dwelling adults (n = 502,529, age range: 37-73 years, 54% female). UK Biobank has genome-wide genotyping (approx. 93 million variants), health, and demographic data for all participants. A genome-wide association study (GWAS) of the frailty phenotype was performed on British and Irish adults aged 60 to 70 years (n = 157,720) to identify heritable factors which predict frailty progression in later life. Functional mapping was performed to determine genes and biological pathways enriched in GWAS results. Results 95 single nucleotide polymorphisms (SNPs) from three independent genomic risk loci were significantly associated (p < 5e-8) with the frailty phenotype in UK Biobank participants. Three genes, PPP1R3A, LONRF2, and AIF1 were statistically enriched with genetic variants. Tissue-specific expression analysis indicated genes differentially expressed in blood vessels were enriched. Linkage Disequilibrium Score Regression (lambda = 1.2005, intercept = 1.0006) indicated GWAS test statistic inflation resulting from polygenicity. SNP-based heritability was estimated to be 6.34% (SE: 0.36%). Conclusion SNP-based heritability of the frailty phenotype was lower than expected in comparison to previous reports of 30%-45%. Statistically significant genomic risk loci, genes, and tissue-enrichment pointed towards dysregulation of cardiometabolic, cardiovascular, and immunological processes in frailty risk, contrasting to brain pathways enriched in previous genomic analyses of the frailty index.

Polygenic power calculator: Statistical power and polygenic prediction accuracy of genome-wide association studies of complex traits.

Power calculation is a necessary step when planning genome-wide association studies (GWAS) to ensure meaningful findings. Statistical power of GWAS depends on the genetic architecture of phenotype, sample size, and study design. While several computer programs have been developed to perform power calculation for single SNP association testing, it might be more appropriate for GWAS power calculation to address the probability of detecting any number of associated SNPs. In this paper, we derive the statistical power distribution across causal SNPs under the assumption of a point-normal effect size distribution. We demonstrate how key outcome indices of GWAS are related to the genetic architecture (heritability and polygenicity) of the phenotype through the power distribution. We also provide a fast, flexible and interactive power calculation tool which generates predictions for key GWAS outcomes including the number of independent significant SNPs, the phenotypic variance explained by these SNPs, and the predictive accuracy of resulting polygenic scores. These results could also be used to explore the future behaviour of GWAS as sample sizes increase further. Moreover, we present results from simulation studies to validate our derivation and evaluate the agreement between our predictions and reported GWAS results.

Gene–environment correlations across geographic regions affect genome-wide association studies

Gene–environment correlations affect associations between genetic variants and complex traits in genome-wide association studies (GWASs). Here we showed in up to 43,516 British siblings that educational attainment polygenic scores capture gene–environment correlations, and that migration extends these gene–environment correlations beyond the family to broader geographic regions. We then ran GWASs on 56 complex traits in up to 254,387 British individuals. Controlling for geographic regions significantly decreased the heritability for socioeconomic status (SES)-related traits, most strongly for educational attainment and income. For most traits, controlling for regions significantly reduced genetic correlations with educational attainment and income, most significantly for body mass index/body fat, sedentary behavior and substance use, consistent with gene–environment correlations related to regional socio-economic differences. The effects of controlling for birthplace and current address suggest both passive and active sources of gene–environment correlations. Our results show that the geographic clustering of DNA and SES introduces gene–environment correlations that affect GWAS results.

Natural variation identifies new effectors of water-use efficiency in Arabidopsis

Water-use efficiency (WUE) is the ratio of biomass produced per unit of water consumed; thus, it can be altered by genetic factors that affect either side of the ratio. In the present study, we exploited natural variation for WUE to discover loci affecting either biomass accumulation or water use as factors affecting WUE. Genome-wide association studies (GWAS) using integrated WUE measured through carbon isotope discrimination (δ13C) of Arabidopsis thaliana accessions identified genomic regions associated with WUE. Reverse genetic analysis of 70 candidate genes selected based on the GWAS results and transcriptome data identified 25 genes affecting WUE as measured by gravimetric and δ13C analyses. Mutants of four genes had higher WUE than wild type, while mutants of the other 21 genes had lower WUE. The differences in WUE were caused by either altered biomass or water consumption (or both). Stomatal density (SD) was not a primary cause of altered WUE in these mutants. Leaf surface temperatures indicated that transpiration differed for mutants of 16 genes, but generally biomass accumulation had a greater effect on WUE. The genes we identified are involved in diverse cellular processes, including hormone and calcium signaling, meristematic activity, photosynthesis, flowering time, leaf/vasculature development, and cell wall composition; however, none of them had been previously linked to WUE. Thus, our study successfully identified effectors of WUE that can be used to understand the genetic basis of WUE and improve crop productivity.

A Phylogeny-aware GWAS Framework to Correct for Heritable Pathogen Effects on Infectious Disease Traits.

Infectious diseases are particularly challenging for genome-wide association studies (GWAS) because genetic effects from two organisms (pathogen and host) can influence a trait. Traditional GWAS assume individual samples are independent observations. However, pathogen effects on a trait can be heritable from donor to recipient in transmission chains. Thus, residuals in GWAS association tests for host genetic effects may not be independent due to shared pathogen ancestry. We propose a new method to estimate and remove heritable pathogen effects on a trait based on the pathogen phylogeny prior to host GWAS, thus restoring independence of samples. In simulations, we show this additional step can increase GWAS power to detect truly associated host variants when pathogen effects are highly heritable, with strong phylogenetic correlations. We applied our framework to data from two different host–pathogen systems, HIV in humans and X. arboricola in A. thaliana. In both systems, the heritability and thus phylogenetic correlations turn out to be low enough such that qualitative results of GWAS do not change when accounting for the pathogen shared ancestry through a correction step. This means that previous GWAS results applied to these two systems should not be biased due to shared pathogen ancestry. In summary, our framework provides additional information on the evolutionary dynamics of traits in pathogen populations and may improve GWAS if pathogen effects are highly phylogenetically correlated amongst individuals in a cohort.

Identification of novel rare copy number variants associated with sporadic tetralogy of Fallot and clinical implications

Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart disease. Highly penetrant copy number variants (CNVs) and genes related to the etiology of TOF likely exist with differences among populations. We aimed to identify CNV contributions to sporadic TOF cases in Han Chinese. Genomic DNA was extracted from peripheral blood in 605 subjects (303 sporadic TOF and 302 unaffected Han Chinese [Control] from cardiac centers in China) and analyzed by genome-wide association study (GWAS). The GWAS results were compared with existing Database of Genetic Variants. These CNVs were further validated by qPCR. Bioinformatics analyses were performed with protein-protein interaction (PPI) network and KEGG pathway enrichment. Across all chromosomes 119 novel "TOF-specific CNVs" were identified with prevalence of CNVs of 21.5% in chromosomes 1-20 and 37.0% including Chr21/22. In chromosomes 1-20, CNVs on 11q25 (encompasses genes ACAD8, B3GAT1, GLB1L2, GLB1L3, IGSF9B, JAM3, LOC100128239, LOC283177, MIR4697, MIR4697HG, NCAPD3, OPCML, SPATA19, THYN1, and VPS26B) and 14q32.33 (encompasses genes THYN1, OPCML, and NCAPD3) encompass genes most likely to be associated with TOF. Specific CNVs found on the chromosome 21 (6.3%) and 22(11.9%) were also identified in details. PPI network analysis identified the genes covering the specific CNVs related to TOF and the signaling pathways. This study for first time identified novel TOF-specific CNVs in the Han Chinese with higher frequency than in Caucasians and with 11q25 and 14q32.33 not reported in TOF of Caucasians. These novel CNVs identify new candidate genes for TOF and provide new insights into genetic basis of TOF.

Polygenic resilience scores capture protective genetic effects for Alzheimer’s disease

Polygenic risk scores (PRSs) can boost risk prediction in late-onset Alzheimer’s disease (LOAD) beyond apolipoprotein E (APOE) but have not been leveraged to identify genetic resilience factors. Here, we sought to identify resilience-conferring common genetic variants in (1) unaffected individuals having high PRSs for LOAD, and (2) unaffected APOE-ε4 carriers also having high PRSs for LOAD. We used genome-wide association study (GWAS) to contrast “resilient” unaffected individuals at the highest genetic risk for LOAD with LOAD cases at comparable risk. From GWAS results, we constructed polygenic resilience scores to aggregate the addictive contributions of risk-orthogonal common variants that promote resilience to LOAD. Replication of resilience scores was undertaken in eight independent studies. We successfully replicated two polygenic resilience scores that reduce genetic risk penetrance for LOAD. We also showed that polygenic resilience scores positively correlate with polygenic risk scores in unaffected individuals, perhaps aiding in staving off disease. Our findings align with the hypothesis that a combination of risk-independent common variants mediates resilience to LOAD by moderating genetic disease risk.

Genome sequence-based genome-wide association study of feed efficiency in Pacific abalone

The Pacific abalone (Haliotis discus hannai) is the most commonly farmed abalone species in China. Seaweed, which is the feed for abalone, accounts for the highest costs in commercial farming. Genetic improvement of feed efficiency (FE) related traits in abalone could result in significant cost and energy savings. We performed a genome-wide association study (GWAS) of the FE traits in Pacific abalone. A total of 25 significant single-nucleotide polymorphisms (SNPs) were detected as being associated with the feed efficiency ratio (FER), and 30 significant SNPs were associated with residual feed intake (RFI). A total of 64 genes, including copb1, megf10, prxs, prdx4, myo19, ptp, ggt, aps, perlucin, and nimul, were identified as candidate genes that may affect FER or RFI traits through biological processes such as cell proliferation, nutrition metabolism, and the immune system. Furthermore, an overlapped gene (apol3) was identified as being associated with RFI by combining the results of GWAS and comparative transcriptomic analyses between the high-FE and low-FE groups. This study will not only improve our understanding of the genetics of abalone FE but will also provide valuable SNPs for molecular marker selection and breeding in the Pacific abalone.

The first broad replication study of SNPs and a pilot genome-wide association study for androgenetic alopecia in Asian populations.

Many candidate genes for androgenetic alopecia (AGA) have been identified in studies of the Caucasians and some Asian populations. This study aimed to confirm the known susceptibility genes reported in previous studies and find additional candidate genes for high-risk individuals for AGA in Korean population. We recapitulated the previously reported SNPs and identified the novel Korean AGA risk genetic variants using a Korean hospital-based AGA case and control samples. The population was consisting of 494 individuals (275 AGA cases and 146 controls). Using the 800 K SNPs of precision medical research array (PMRA SNP microarray chip) and imputation-based SNPs, 12 previous GWAS reports for AGA and a total of 62 160 SNPs were examined in our study samples. Also, we conducted the genome-wide association study (GWAS) by the logistic regression analyses for AGA cases and controls with controlling the age as the covariates. Among the 62 160 SNPs, a total of 1143 SNPs in 76 gene regions showed weak replication tendency with the p-values <0.05 and same direction of effects. Additionally, the GWAS results showed 110 SNPs in 13 independent regions with the suggestive p-values <1.00 × 10-5 . The most significantly replicated SNP resided on chromosome 20, which were similar to other AGA replication studies including Chinese study. The GWAS identified two SNPs (rs11010734 and rs2420640) increasing the risk for AGA in our study population. Our study would be a reference of the non-European studies to better understand AGA in different populations and ancestral contexts.

The GWAS-MAP|ovis platform for aggregation and analysis of genome-wide association study results in sheep.

In recent years, the number of genome-wide association studies (GWAS) carried out for various economically important animal traits has been increasing. GWAS discoveries provide summary statistics that can be used both for targeted marker-oriented selection and for studying the genetic control of economically important traits of farm animals. In contrast to research in human genetics, GWAS on farm animals often does not meet generally accepted standards (availability of information about effect and reference alleles, the size and direction of the effect, etc.). This greatly complicates the use of GWAS results for breeding needs. Within the framework of human genetics, there are several technological solutions for researching the harmonized results of GWAS, including one of the largest, the GWAS-MAP platform. For other types of living organisms, including economically important agricultural animals, there are no similar solutions. To our knowledge, no similar solution has been proposed to date for any of the species of economically important animals. As part of this work, we focused on creating a platform similar to GWAS-MAP for working with the results of GWAS of sheep, since sheep breeding is one of the most important branches of agriculture. By analogy with the GWAS-MAP platform for storing, unifying and analyzing human GWAS, we have created the GWAS-MAP|ovis platform. The platform currently contains information on more than 34 million associations between genomic sequence variants and traits of meat production in sheep. The platform can also be used to conduct colocalization analysis, a method that allows one to determine whether the association of a particular locus with two different traits is the result of pleiotropy or whether these traits are associated with different variants that are in linkage disequilibrium. This platform will be useful for breeders to select promising markers for breeding, as well as to obtain information for the introduction of genomic breeding and for scientists to replicate the results obtained.

Abstract 1446: Genetic risk factors for the development of multiple primary cancers

Abstract Introduction: Individuals with one cancer are at greater risk of new primary cancers than the general population. While several hereditary cancer syndromes are known, genetic risk factors for multiple primary cancers in an individual are not well understood. Identification of susceptibility variants to multiple primary tumors could enhance screening for subsequent cancers among those at highest risk. Methods: We conducted a pan-cancer genome-wide association study (GWAS) of multiple primary cancers among participants from 2 prospective cohorts: Kaiser Permanente and the UK Biobank. The primary GWAS within cohorts used logistic regression to estimate associations for diagnosis with ≥2 invasive or in situ primary cancers other than non-melanoma skin (N=11,773, 8,928 invasive only) compared to cancer-free controls (N=420,101). Case-case analyses were conducted to distinguish associations with multiple cancers from single-cancer (N=90,576) susceptibility signals. Regression models were adjusted for age, sex, first 10 genetic ancestry principal components, and array. Cohort-specific GWAS results were meta-analyzed. We highlight genome-wide significant (p&amp;lt;5×10-8) results with consistent effect direction across the 2 studies. Results: We identified 8 variants associated with multiple primary cancers. Discussion: To our knowledge, rs192703567 has no previous cancer associations. Three identified variants are in known cancer predisposition genes (rs2293607 in TERC, rs6983267 in CASC8, rs35850753 in TP53). Three variants (rs34379047, rs612611, and rs9419958) are previously associated with multiple cancers, 2 (rs2293607 and rs6983267) with cancer pleiotropy, and 2 (rs283732 and rs35850753) with individual cancers. Most variants from the cancer-free control analyses had consistent effects in the single-cancer case-case analyses, suggesting pleiotropic mechanisms. Our preliminary findings offer insight into genetic risk factors associated with developing multiple primary cancers. Multiple vs. none Multiple invasive vs. none Multiple vs. single Multiple invasive vs. single Chr Position rsID A1 A2 Gene OR P OR P OR P OR P 3 169482335 rs2293607 T C TERC 1.11 1.0×10-9 1.10 2.2×10-7 1.06 2.0×10-3 1.05 0.01 8 128281644 rs283732 C T Intergenic 1.09 2.3×10-7 1.11 9.2×10-9 1.06 3.8×10-4 1.09 3.9×10-5 8 128413305 rs6983267 G T CASC8 POU5F1B CCAT2 PCAT1 1.08 4.1×10-7 1.09 2.9×10-8 1.00 0.83 1.02 0.34 10 105644473 rs34379047 T A OBFC1 1.16 8.5×10-12 1.19 6.0×10-11 1.19 2.3×10-4 1.10 4.0×10-4 10 105675946 rs9419958 T C STN1 1.14 1.8×10-11 1.16 4.5×10-11 1.08 3.1×10-4 1.09 2.8×10-4 11 69307463 rs612611 G A Intergenic 1.11 3.7×10-8 1.10 5.3×10-6 1.06 9.6×10-4 1.05 0.02 17 7578671 rs35850753 T C TP53 1.27 4.9×10-7 1.34 1.6×10-8 1.16 2.8×10-3 1.24 8.8×10-5 22 40738280 rs192703567 C T Intergenic 1.37 5.2×10-8 1.37 1.8×10-6 1.43 4.9×10-9 1.43 2.8×10-7 Chr=Chromosome; A1=Effect allele; A2=Other allele; OR=Odds ratio. Citation Format: Jovia L. Nierenberg, Linda Kachuri, Taylor B. Cavazos, Rebecca E. Graff, Thomas J. Hoffmann, Jie Zhang, Stacey Alexeeff, Laurel Habel, Douglas Corley, Stephen Van Den Eeden, Elad Ziv, Lori C. Sakoda, John S. Witte. Genetic risk factors for the development of multiple primary cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1446.

Genome‐wide association study for desirable traits in the Pacific oysterCrassostrea gigas(Thunberg)

The Pacific oyster, Crassostrea gigas (Thunberg), from the northwest Pacific Ocean has been introduced for aquaculture in many areas. Despite its economic importance, genetic dissection for growth, shell shape and yield traits have not been reported thoroughly. To explore single nucleotide polymorphisms (SNPs) associated with desired traits in Pacific oyster, a genome-wide association study (GWAS) was conducted based on the 190 K high-density SNP array. Growth, shell shape and yield traits, including shell height, condition index and dressing percentage, were studied. Moderate to high phenotypic correlations between shell height and other growth-related traits in the studied wild population were observed (r = 0.38–0.77, p < 0.05), and the dressing percentage was correlated with the condition index (r = 0.6, p < 0.05). The condition index had a moderate positive correlation with glycogen and fat content (r = 0.22–0.35, p < 0.05). The results of GWAS indicated that 11 SNPs were significantly associated with the studied traits. Shell height, body weight and soft body weight were all associated with a significant nonsynonymous SNP (scaffold731_92759), phenotypic variation explanations associated with this single SNP are 8.59%, 8.12% and 8.13%, respectively. This SNP is located in the protein-coding region of the serine protease inhibitor dipetalogastin, which is thought to be involved in food digestion and absorption. This polymorphism may affect the ability of dipetalogastin to inhibit serine proteases, thereby affecting the oyster's growth. This study identified new candidate genes and SNPs related to oyster growth, which is useful for marker-assisted selection.

Single-Nucleotide Polymorphism on Spermatogenesis Associated 16 Gene-Coding Region Affecting Bovine Leukemia Virus Proviral Load.

Bovine leukemia virus (BLV) is an etiological agent of malignant lymphoma in cattle and is endemic in many cattle-breeding countries. Thus, the development of cattle genetically resistant to BLV is desirable. The purpose of this study was to identify novel single-nucleotide polymorphisms (SNPs) related to resistance to BLV. A total of 146 DNA samples from cattle with high BLV proviral loads (PVLs) and 142 samples from cattle with low PVLs were used for a genome-wide association study (GWAS). For the verification of the GWAS results, an additional 1342 and 456 DNA samples from BLV-infected Japanese Black and Holstein cattle, respectively, were used for an SNP genotyping PCR to compare the genotypes for the identified SNPs and PVLs. An SNP located on the spermatogenesis associated 16 (SPATA16)-coding region on bovine chromosome 1 was found to exceed the moderate threshold (p < 1.0 × 10−5) in the Additive and Dominant models of the GWAS. The SNP genotyping PCR revealed that the median values of the PVL were 1278 copies/50 ng of genomic DNA for the major homozygous, 843 for the heterozygous, and 621 for the minor homozygous genotypes in the Japanese Black cattle (p < 0.0001). A similar tendency was also observed in the Holstein cattle. We found that cattle with the minor allele for this SNP showed 20–25% lower PVLs. Although the mechanisms through which this SNP impacts the PVL remain unknown, we found a novel SNP related to BLV resistance located on the SPATA16 gene-coding region on bovine chromosome 1.

Genome-Wide Association Study of Potential Meat Quality Trait Loci in Ducks.

With continuously increasing living standards and health requirements of consumers, meat quality is becoming an important consideration while buying meat products. To date, no genome-wide association study (GWAS) for copy number variants (CNVs) and single nucleotide polymorphisms (SNPs) has been conducted to reveal the genetic effects on meat quality in ducks. This study analyzed the phenotypic correlation and heritability of fat, water, collagen, and protein content of duck breast muscle. To identify the candidate variants for meat quality, we performed a GWAS using 273 ducks from an F2 population. The results of the SNP GWAS showed that the BARHL2, COPS7B, and CCDC50 genes were associated with fat content; BLM, WDR76, and EOMES with water content; CAMTA1, FGD5, GRM7, and RAPGEF5 with collagen production; and RIMS2, HNRNPU, and SPTBN1 with protein content. Additionally, 3, 7, 1, and 3 CNVs were associated with fat, water, collagen, and protein content, respectively, in duck breast muscle. The genes identified in this study can serve as markers for meat quality. Furthermore, our findings may help devise effective breeding plans and selection strategies to improve meat quality.

Impact of Human Genetic Variation on C-Reactive Protein Concentrations and Acute Appendicitis.

BackgroundAcute appendicitis is one of the most common abdominal emergencies worldwide. Both environmental and genetic factors contribute to the disease. C-reactive protein (CRP) is an important biomarker in the diagnosis of acute appendicitis. CRP concentrations are significantly affected by genetic variation. However, whether such genetic variation is causally related to appendicitis risk remains unclear. In this study, the causal relationship between single-nucleotide polymorphisms (SNPs) associated with circulating CRP concentrations and the risk and severity of acute appendicitis was investigated.MethodsCRP concentrations in serum of appendicitis patients (n = 325) were measured. Appendicitis was categorized as complicated/uncomplicated and gangrenous/non-gangrenous. Imputed SNP data (n = 287) were generated. A genome-wide association study (GWAS) on CRP concentrations and appendicitis severity was performed. Intersection and colocalization of the GWAS results were performed with appendicitis and CRP-associated loci from the Pan-UKBB cohort. A functional-genomics approach to prioritize genes was employed.ResultsThirteen percent of significant CRP quantitative trait loci (QTLs) that were previously identified in a large cohort of healthy individuals were replicated in our small patient cohort. Significant enrichment of CRP-QTLs in association with appendicitis was observed. Among these shared loci, the two top loci at chromosomes 1q41 and 8p23.1 were characterized. The top SNP at chromosome 1q41 is located within the promoter of H2.0 Like Homeobox (HLX) gene, which is involved in blood cell differentiation, and liver and gut organogeneses. The expression of HLX is increased in the appendix of appendicitis patients compared to controls. The locus at 8p23.1 contains multiple genes, including cathepsin B (CTSB), which is overexpressed in appendix tissue from appendicitis patients. The risk allele of the top SNP in this locus also increases CTSB expression in the sigmoid colon of healthy individuals. CTSB is involved in collagen degradation, MHC class II antigen presentation, and neutrophil degranulation.ConclusionsThe results of this study prioritize HLX and CTSB as potential causal genes for appendicitis and suggest a shared genetic mechanism between appendicitis and CRP concentrations.

Genomic selection applications can improve the environmental performance of aquatics: A case study on the heat tolerance of abalone.

Aquaculture is one of the world's fastest‐growing and most traded food industries, but it is under the threat of climate‐related risks represented by global warming, marine heatwave (MHW) events, ocean acidification, and deoxygenation. For the sustainable development of aquaculture, selective breeding may be a viable method to obtain aquatic economic species with greater tolerance to environmental stressors. In this study, we estimated the heritability of heat tolerance trait of Pacific abalone Haliotis discus hannai, performed genome‐wide association studies (GWAS) analysis for heat tolerance to detect single nucleotide polymorphisms (SNPs) and candidate genes, and assessed the potential of genomic selection (GS) in the breeding of abalone industry. A total of 1120 individuals were phenotyped for their heat tolerance and genotyped with 64,788 quality‐controlled SNPs. The heritability of heat tolerance was moderate (0.35–0.42) and the predictive accuracy estimated using BayesB (0.55 ± 0.05) was higher than that using GBLUP (0.40 ± 0.01). A total of 11 genome‐wide significant SNPs and 2 suggestive SNPs were associated with heat tolerance of abalone, and 13 candidate genes were identified, including got2,znfx1,l(2)efl, and lrp5. Based on GWAS results, the prediction accuracy using the top 5K SNPs was higher than that using randomly selected SNPs and higher than that using all SNPs. These results suggest that GS is an efficient approach for improving the heat tolerance of abalone and pave the way for abalone selecting breeding programs in rapidly changing oceans.

AgReg-SNPdb-Plants: A Database of Regulatory SNPs for Agricultural Plant Species.

Simple SummaryIn breeding research, the investigation of regulatory SNPs (rSNPs) is becoming increasingly important due to their potential causal role for specific functional traits. Especially for crop species, there is still a lack of systematic analyses to detect rSNPs and their predicted effects on the binding of transcription factors. In this study, we present agReg-SNPdb-Plants, a database storing genome-wide collections of regulatory SNPs for agricultural plant species which can be queried via a web interface.Single nucleotide polymorphisms (SNPs) that are located in the promoter regions of genes and affect the binding of transcription factors (TFs) are called regulatory SNPs (rSNPs). Their identification can be highly valuable for the interpretation of genome-wide association studies (GWAS), since rSNPs can reveal the biologically causative variant and decipher the regulatory mechanisms behind a phenotype. In our previous work, we presented agReg-SNPdb, a database of regulatory SNPs for agriculturally important animal species. To complement this previous work, in this study we present the extension agReg-SNPdb-Plants storing rSNPs and their predicted effects on TF-binding for 13 agriculturally important plant species and subspecies (Brassica napus, Helianthus annuus, Hordeum vulgare, Oryza glaberrima, Oryza glumipatula, Oryza sativa Indica, Oryza sativa Japonica, Solanum lycopersicum, Sorghum bicolor, Triticum aestivum, Triticum turgidum, Vitis vinifera, and Zea mays). agReg-SNPdb-Plants can be queried via a web interface that allows users to search for SNP IDs, chromosomal regions, or genes. For a comprehensive interpretation of GWAS results or larger SNP-sets, it is possible to download the whole list of SNPs and their impact on transcription factor binding sites (TFBSs) from the website chromosome-wise.

Integrating human brain proteomes with genome-wide association data implicates novel proteins in post-traumatic stress disorder.

Genome-wide association studies (GWAS) have identified several risk loci for post-traumatic stress disorder (PTSD); however, how they confer PTSD risk remains unclear. We aimed to identify genes that confer PTSD risk through their effects on brain protein abundance to provide new insights into PTSD pathogenesis. To that end, we integrated human brain proteomes with PTSD GWAS results to perform a proteome-wide association study (PWAS) of PTSD, followed by Mendelian randomization, using a discovery and confirmatory study design. Brain proteomes (N=525) were profiled from the dorsolateral prefrontal cortex using mass spectrometry. The Million Veteran Program (MVP) PTSD GWAS (n=186,689) was used for the discovery PWAS, and the Psychiatric Genomics Consortium PTSD GWAS (n=174,659) was used for the confirmatory PWAS. To understand whether genes identified at the protein-level were also evident at the transcript-level, we performed a transcriptome-wide association study (TWAS) using human brain transcriptomes (N=888) and the MVP PTSD GWAS results. We identified 11 genes that contribute to PTSD pathogenesis via their respective cis-regulated brain protein abundance. Seven of 11 genes (64%) replicated in the confirmatory PWAS and 4 of 11 also had their cis-regulated brain mRNA levels associated with PTSD. High confidence level was assigned to 9 of 11 genes after considering evidence from the confirmatory PWAS and TWAS. Most of the identified genes are expressed in other PTSD-relevant brain regions and several are preferentially expressed in excitatory neurons, astrocytes, and oligodendrocyte precursor cells. These genes are novel, promising targets for mechanistic and therapeutic studies to find new treatments for PTSD.

Genome-wide association studies for egg quality traits in White Leghorn layers using low-pass sequencing and SNP chip data.

Low-pass sequencing data have been proposed as an alternative to single nucleotide polymorphism (SNP) chips in genome-wide association studies (GWAS) of several species. However, it has not been used in layer chickens yet. This study aims at comparing the GWAS results of White Leghorn chickens using low-pass sequencing data (1×) and 54 k SNP chip data. Ten commercially relevant egg quality traits including albumen height, shell strength, shell colour, egg weight and yolk weight collected from up to 1,420 White Leghorn chickens were analysed. The results showed that the genomic heritability estimates based on low-pass sequencing data were higher than those based on SNP chip data. Although two GWAS analyses showed similar overall landscape for most traits, low-pass sequencing captured some significant SNPs that were not on the SNP chip. In GWAS analysis using 54 k SNP chip data, after including more individuals (up to 5,700), additional significant SNPs not detected by low-pass sequencing data were found. In conclusion, GWAS using low-pass sequencing data showed similar results to those with SNP chip data and may require much larger sample sizes to show measurable advantages.