Epistasis-aware genome-wide association studies provide insights into the efficient breeding of high-yield and high-quality rice

Marker-assisted selection(MAS)and genomic selection(GS)breeding have greatly improved the efficiency of rice breeding.Due to the influences of epistasis and gene pleiotropy,ensuring the actual breeding effect of MAS and GS is still a difficult challenge to overcome.In this study,113 indica rice varieties(V)and their 565 testcross hybrids(TC)were used as the materials to investigate the genetic basis of 12 quality traits and nine agronomic traits.The original traits and general combining ability of the parents,as well as the original traits and midparent heterosis of TC,were subjected to genome-wide association analysis.In total,381 primary significantly associated loci(SAL)and 1,759 secondary SALs that had epistatic interactions with these primary SALs were detected.Among these loci,322 candidate genes located within or nearby the SALs were screened,204 of which were cloned genes.A total of 39 MAS molecular modules that are beneficial for trait improvement were identified by pyramiding the superior haplotypes of candidate genes and desirable epistatic alleles of the secondary SALs.All the SALs were used to construct genetic networks,in which 91 pleiotropic loci were investigated.Additionally,we estimated the accuracy of genomic prediction in the parent V and TC by incorporating either no SALs,primary SALs,secondary SALs or epistatic effect SALs as covariates.Although the prediction accuracies of the four models were generally not significantly different in the TC dataset,the incorporation of primary SALs,secondary SALs,and epistatic effect SALs significantly improved the prediction accuracies of 5(26%),3(16%),and 11(58%)traits in the V dataset,respectively.These results suggested that SALs and epistatic effect SALs identified based on an additive genotype can provide considerable predictive power for the parental lines.They also provide insights into the genetic basis of complex traits and valuable information for molecular breeding in rice.

Leveraging the potential of big genomic and phenotypic data for genome-wide association mapping in wheat

Genome-wide association mapping studies(GWAS)based on Big Data are a potential approach to improve marker-assisted selection in plant breeding.The number of available phenotypic and genomic data sets in which medium-sized populations of several hundred individuals have been studied is rapidly increasing.Combining these data and using them in GWAS could increase both the power of QTL discovery and the accuracy of estimation of underlying genetic effects,but is hindered by data heterogeneity and lack of interoperability.In this study,we used genomic and phenotypic data sets,focusing on Central European winter wheat populations evaluated for heading date.We explored strategies for integrating these data and subsequently the resulting potential for GWAS.Establishing interoperability between data sets was greatly aided by some overlapping genotypes and a linear relationship between the different phenotyping protocols,resulting in high quality integrated phenotypic data.In this context,genomic prediction proved to be a suitable tool to study relevance of interactions between genotypes and experimental series,which was low in our case.Contrary to expectations,fewer associations between markers and traits were found in the larger combined data than in the individual experimental series.However,the predictive power based on the marker-trait associations of the integrated data set was higher across data sets.Therefore,the results show that the integration of medium-sized to Big Data is an approach to increase the power to detect QTL in GWAS.The results encourage further efforts to standardize and share data in the plant breeding community.

Genome-wide association study of seedling nitrogen-use efficiency-associated traits in common wheat(Triticum aestivum L.)

Nitrogen(N)fertilizer application is essential for crop-plant growth and development.Identifying genetic loci associated with N-use efficiency(NUE)could increase wheat yields and reduce environmental pollution caused by overfertilization.We subjected a panel of 389 wheat accessions to N and chlorate(a nitrate analog)treatments to identify quantitative trait loci(QTL)controlling NUE-associated traits at the wheat seedling stage.Genotyping the panel with a 660K single-nucleotide polymorphism(SNP)array,we identified 397 SNPs associated with N-sensitivity index and chlorate inhibition rate.These SNPs were merged into 49 QTL,of which eight were multi-environment stable QTL and 27 were located near previously reported QTL.A set of 135 candidate genes near the 49 QTL included TaBOX(F-box family protein)and TaERF(ethylene-responsive transcription factor).A Tabox mutant was more sensitive to low-N stress than the wild-type plant.We developed two functional markers for Hap 1,the favorable allele of TaBOX.

Genome-wide association mapping and genomic prediction of stalk rot in two mid-altitude tropical maize populations

Maize stalk rot reduces grain yield and quality.Information about the genetics of resistance to maize stalk rot could help breeders design effective breeding strategies for the trait.Genomic prediction may be a more effective breeding strategy for stalk-rot resistance than marker-assisted selection.We performed a genome-wide association study(GWAS)and genomic prediction of resistance in testcross hybrids of 677 inbred lines from the Tuxpe?o and non-Tuxpe?o heterotic pools grown in three environments and genotyped with 200,681 single-nucleotide polymorphisms(SNPs).Eighteen SNPs associated with stalk rot shared genomic regions with gene families previously associated with plant biotic and abiotic responses.More favorable SNP haplotypes traced to tropical than to temperate progenitors of the inbred lines.Incorporating genotype-by-environment(G×E)interaction increased genomic prediction accuracy.

Genome-Wide Association Study of Cooked Rice Textural Attributes and Starch Physicochemical Properties in indica Rice

Rice cooking and eating qualities(CEQ)are mainly determined by cooked rice textural parameters and starch physicochemical properties.However,the genetic bases of grain texture and starch properties in rice have not been fully understood.We conducted a genome-wide association study for apparent amylose content(AAC),starch pasting viscosities,and cooked rice textural parameters using 279 indica rice accessions from the 3000 Rice Genome Project.We identified 26 QTLs in the whole population and detected single nucleotide polymorphisms(SNPs)with the lowest P-value at the Waxy(Wx)locus for all traits except pasting temperature and cohesiveness.Additionally,we detected significant SNPs at the SUBSTANDARD STARCH GRAIN6(SSG6)locus for AAC,setback(SB),hardness,adhesiveness,chewiness(CHEW),gumminess(GUM),and resilience.We subsequently divided the population using a SNP adjacent to the Waxy locus,and identified 23 QTLs and 12 QTLs in two sub-panels,WxT and WxA,respectively.In these sub-panels,SSG6 was also identified to be associated with pasting parameters,including peak viscosity,hot paste viscosity,cold paste viscosity,and consistency viscosity.Furthermore,a candidate gene encoding monosaccharide transporter 5(OsMST5)was identified to be associated with AAC,breakdown,SB,CHEW,and GUM.In total,39 QTLs were co-localized with known genes or previously reported QTLs.These identified genes and QTLs provide valuable information for genetic manipulation to improve rice CEQ.

Genetic Parameters and Genome-Wide Association Studies for Body Size Traits of Shuxuan Cattle in China

In domestic cattle,the body size traits have important implications in terms of breed characteristics and production performance.Shuxuan cattle is a dual-purpose breed mainly raised in Sichuan province,China,for which we have known less about the genetic parameters and underlying candidate genes in relation to the body size traits.In this study,we obtained the genome-wide single nucleotide polymorphisms(SNPs)using the Illumina Bovine BeadChip in 275 Shuxuan cattle.These SNPs were first used for estimating genetic parameters for the withers height(WH)and diagonal body length(BL).Using the bivariate animal model,the estimates(±standard error)of heritabilities were 0.71±0.22 and 0.49±0.29 for BL,and their genetic correlation was 0.64±0.37.Second,the genome-wide association study(GWAS)was performed.However,these did not result into genome-wide significant SNPs for both WH and BL traits.According to a less stringent suggestive significance,some positional candidate genes were found,and some of them(such as FAM110B,TAS1R2,PAX3,and FHIT)were previously reported in literature to be associated with body size traits in cattle.In conclusion,we estimated the genetic parameters in Shuxuan cattle using genomic information for the first time,which are required for implementing the genomic selection programs in the future.

Genome-wide association with transcriptomics reveals a shade-tolerance gene network in soybean

Shade tolerance is essential for soybeans in inter/relay cropping systems.A genome-wide association study(GWAS)integrated with transcriptome sequencing was performed to identify genes and construct a genetic network governing the trait in a set of recombinant inbred lines derived from two soybean parents with contrasting shade tolerance.An improved GWAS procedure,restricted two-stage multi-locus genome-wide association study based on gene/allele sequence markers(GASM-RTM-GWAS),identified 140 genes and their alleles associated with shade-tolerance index(STI),146 with relative pith cell length(RCL),and nine with both.Annotation of these genes by biological categories allowed the construction of a protein–protein interaction network by 187 genes,of which half were differentially expressed under shading and non-shading conditions as well as at different growth stages.From the identified genes,three ones jointly identified for both traits by both GWAS and transcriptome and two genes with maximum links were chosen as beginners for entrance into the network.Altogether,both STI and RCL gene systems worked for shade-tolerance with genes interacted each other,this confirmed that shadetolerance is regulated by more than single group of interacted genes,involving multiple biological functions as a gene network.

Genetic Diversity,Population Structure,and Genome-Wide Association Study of Seven Agronomic Traits in 273 Diverse Upload Cotton Accessions

Upland cotton(Gossypium hirsutum)is the most important plant producing natural fibers for the textile industry.In this study,we first investigated the phenotypic variation of seven agronomic traits of 273 diverse cotton accessions in the years 2017 and 2018,which were from 18 geographical regions.We found large variations among the traits in different geographical regions and only half of the traits in either years 2017 or 2018 followed a normal distribution.We then genotyped the collection with 81,612 high quality SNPs.Phylogenetic tree and population structure revealed a diverse genetic structure of the core collection,and geographical diversification was an important factor,but account for part of the variances of genetic diversification.We then performed genome-wide association study for the seven traits in the years 2017 and 2018,and the average values of each trait in the two years,respectively.We identified a total of 19 significant marker-trait associations and found that Pollen Ole e 1 allergen/extension could be the candidate gene associated with the fall-off cotton bolls from the last three branches.In addition,large variations were observed for the heritability of traits in the years 2017 and 2018.These results provide new potential candidate genes for further functional validation,which could be useful for genetic improvement and breeding of new cotton cultivars with better agronomic performances.

Genome-wide associations, polygenic risk, and Mendelian randomization reveal limited interactions between John Henryism and cynicism

BACKGROUND John Henryism(JH)is a strategy for dealing with chronic psychological stress characterized by high levels of physical effort and work.Cynicism is a belief that people are motivated primarily by self-interest.High scores on the JH scale and cynicism measures correlate with an increased risk of cardiovascular disease.High cynicism is also a hallmark of burnout syndrome,another known risk factor for heart disease.AIM To evaluate possible interactions between JH and cynicism hoping to clarify risk factors of burnout.METHODS We analyzed genetic and psychological data available from the Database of Genotypes and Phenotypes for genome-wide associations with these traits.We split the total available samples and used plink to perform the association studies on the discovery set(n=1852,80%)and tested for replication using the validation set(n=465).We used scikit-learn to perform supervised machine learning for developing genetic risk algorithms.RESULTS We identified 2,727,and 204 genetic associations for scores on the JH,cynicism and cynical distrust(CD)scales,respectively.We also found 173 associations with high cynicism,109 with high CD,but no associations with high JH.We also produced polygenic classifiers for high cynicism using machine learning with areas under the receiver operator characteristics curve greater than 0.7.CONCLUSION We found significant genetic components to these traits but no evidence of an interaction.Therefore,while there may be a genetic risk,JH is not likely a burnout risk factor.

Genome-wide association studies reveal the genetic basis of amino acid content variation in tea plants

Tea is one of the most popular non-alcoholic beverages in the world,and free amino acids,especially theanine,make a major contribution to the umami taste of tea.However,the genetic basis of the variation in amino acid content in tea plants remains largely unknown.Here,we measured the free amino acid content in fresh leaves of 174 tea accessions over two years using a targeted metabolomics approach and obtained genotype data via RNA sequencing.Genome-wide association studies were conducted to investigate loci affecting the content of free amino acids.A total of 69 quantitative trait loci(–log10(P-value)>5)were identified.Functional annotation revealed that branched-chain amino acid aminotransferase,glutamine synthetase,nitrate transporter,and glutamate decarboxylase might be important for amino acid metabolism.Two significant loci,glutamine synthetase(Glu1,P=3.71×10^(−4);Arg1,P=4.61×10^(−5))and branched-chain amino acid aminotransferase(Val1,P=4.67×10^(−5);I_Leu1,P=3.56×10^(−6)),were identified,respectively.Based on the genotyping result,two alleles of CsGS(CsGS-L and CsGS-H)and CsBCAT(CsBCAT-L and CsBCAT-H)were selected to perform function verification.Overexpression of CsGS-L and CsGS-H enhanced the contents of glutamate and arginine in transgenic plants,and overexpression of CsBCAT-L and CsBCAT-H promoted the accumulation of valine,isoleucine and leucine.Enzyme activity assay uncovered that SNP1054 is important for CsGS catalyzing glutamate into glutamine.Furthermore,CsGS-L and CsGS-H differentially regulated the accumulation of glutamine,and CsBCAT-L and CsBCAT-H differentially regulated the accumulation of branched-chain amino acids.In summary,the findings in our study would provide new insights into the genetic basis of amino acids contents variation in tea plants and facilitate the identification of elite genes to enhance amino acids content.

Host genetic factors affecting hepatitis B infection outcomes:Insights from genome-wide association studies

The clinical outcome of hepatitis B virus(HBV) infection depends on the success or failure of the immune responses to HBV,and varies widely among individuals,ranging from asymptomatic self-limited infection,inactive carrier state,chronic hepatitis,cirrhosis,hepatocellular carcinoma,to liver failure,depending on the success or failure of immune response to HBV.Genome-wide association studies(GWAS) identified key genetic factors influencing the pathogenesis of HBV-related traits.In this review,we discuss GWAS for persistence of HBV infection,antibody response to hepatitis B vaccine,and HBV-related advanced liver diseases.HBV persistence is associated with multiple genes with diverse roles in immune mechanisms.The strongest associations are found within the classical human leukocyte antigen(HLA) genes,highlighting the central role of antigen presentation in the immune response to HBV.Associated variants affect both epitope binding specificities and expression levels of HLA molecules.Several other susceptibility genes regulate the magnitude of adaptive immune responses,determining immunity vs tolerance.HBV persistence and nonresponse to vaccine share the same risk variants,implying overlapping genetic bases.On the other hand,the risk variants for HBV-related advanced liver diseases are largely different,suggesting different host-virus dynamics in acute vs chronic HBV infections.The findings of these GWAS are likely to pave the way for developing more effective preventive and therapeutic interventions by personalizing the management of HBV infection.

Genetic dissection of rice appearance quality and cooked rice elongation by genome-wide association study

Appearance and cooked rice elongation are key quality traits of rice. Although some QTL for these traits have been identified, understanding of the genetic relationship between them remains limited. In the present study, large phenotypic variation was observed in 760 accessions from the 3 K Rice Genomes Project for both appearance quality and cooked rice elongation. Most component traits of appearance quality and cooked rice elongation showed significant pairwise correlations, but a low correlation was found between appearance quality and cooked rice elongation. A genome-wide association study identified 74 QTL distributed on all 12 chromosomes for grain length, grain width, length to width ratio, degree of endosperm with chalkiness, rice elongation difference, and elongation index. Thirteen regions containing QTL stably expressed in multiple environments and/or exerting pleiotropic effects on multiple traits were detected. By gene-based association analysis and haplotype analysis, 46 candidate genes, including five cloned genes, and 49 favorable alleles were identified for these 13 QTL. The effect of the candidate gene Wx on rice elongation difference was validated by a transgenic strategy. These results shed light on the genetic bases of appearance quality and cooked rice elongation and provide gene resources for improving rice quality by molecular breeding.

Genome-wide association study and genomic prediction of Fusarium ear rot resistance in tropical maize germplasm

Fusarium ear rot(FER)is a destructive maize fungal disease worldwide.In this study,three tropical maize populations consisting of 874 inbred lines were used to perform genomewide association study(GWAS)and genomic prediction(GP)analyses of FER resistance.Broad phenotypic variation and high heritability for FER were observed,although it was highly influenced by large genotype-by-environment interactions.In the 874 inbred lines,GWAS with general linear model(GLM)identified 3034 single-nucleotide polymorphisms(SNPs)significantly associated with FER resistance at the P-value threshold of 1×10^(-5),the average phenotypic variation explained(PVE)by these associations was 3%with a range from 2.33%to 6.92%,and 49 of these associations had PVE values greater than 5%.The GWAS analysis with mixed linear model(MLM)identified 19 significantly associated SNPs at the P-value threshold of 1×10^(-4),the average PVE of these associations was 1.60%with a range from 1.39%to 2.04%.Within each of the three populations,the number of significantly associated SNPs identified by GLM and MLM ranged from 25 to 41,and from 5 to 22,respectively.Overlapping SNP associations across populations were rare.A few stable genomic regions conferring FER resistance were identified,which located in bins 3.04/05,7.02/04,9.00/01,9.04,9.06/07,and 10.03/04.The genomic regions in bins 9.00/01 and 9.04 are new.GP produced moderate accuracies with genome-wide markers,and relatively high accuracies with SNP associations detected from GWAS.Moderate prediction accuracies were observed when the training and validation sets were closely related.These results implied that FER resistance in maize is controlled by minor QTL with small effects,and highly influenced by the genetic background of the populations studied.Genomic selection(GS)by incorporating SNP associations detected from GWAS is a promising tool for improving FER resistance in maize.

Genome-Wide Association Study for Certain Carcass Traits and Organ Weights in a Large White×Minzhu Intercross Porcine Population

Porcine carcass traits and organ weights have important economic roles in the swine industry. A total of 576 animals from a Large White×Minzhu intercross population were genotyped using the Illumina PorcineSNP60K Beadchip and were phenotyped for 10 traits, speciifcally, backfat thickness （6-7 libs）, carcass length, carcass weight, foot weight, head weight, heart weight, leaf fat weight, liver weight, lung weight and slaughter body weight. The genome-wide association study （GWAS） was assessed by Genome Wide Rapid Association using the mixed model and regression-genomic control approach. A total of 31 single nucleotide polymorphisms （SNPs） （with the most signiifcant SNP being MARC0033464, P value=6.80×10-13） were located in a 9.76-Mb （31.24-41.00 Mb） region on SSC7 and were found to be signiifcantly associated with one or more carcass traits and organ weights. High percentage of phenotypic variance explanation was observed for each trait ranging from 31.21 to 67.42%. Linkage analysis revealed one haplotype block of 495 kb, in which the most signiifcant SNP being MARC0033464 was contained, on SSC7 at complete linkage disequilibrium. Annotation of the pig reference genome suggested 6 genes （GRM4, HMGA1, NUDT3, RPS10, SPDEF and PACSIN1） in this candidate linkage disequilibrium （LD） interval. Functional analysis indicated that the HMGA1 gene presents the prime biological candidate for carcass traits and organ weights in pig, with potential application in breeding programs.

Genetic dissection of the grain-filling rate and related traits through linkage analysis and genome-wide association study in bread wheat

Wheat grain yield is generally sink-limited during grain filling.The grain-filling rate(GFR)plays a vital role but is poorly studied due to the difficulty of phenotype surveys.This study explored the grain-filling traits in a recombinant inbred population and wheat collection using two highly saturated genetic maps for linkage analysis and genome-wide association study(GWAS).Seventeen stable additive quantitative trait loci(QTLs)were identified on chromosomes 1B,4B,and 5A.The linkage interval between IWB19555 and IWB56078 showed pleiotropic effects on GFR_(1),GFR_(max),kernel length(KL),kernel width(KW),kernel thickness(KT),and thousand kernel weight(TKW),with the phenotypic variation explained(PVE)ranging from 13.38%(KW)to 33.69%(TKW).198 significant marker-trait associations(MTAs)were distributed across most chromosomes except for 3D and 4D.The major associated sites for GFR included IWB44469(11.27%),IWB8156(12.56%)and IWB24812(14.46%).Linkage analysis suggested that IWB35850,identified through GWAS,was located in approximately the same region as QGFR_(max)2B.3-11,where two high-confidence candidate genes were present.Two important grain weight(GW)-related QTLs colocalized with grain-filling QTLs.The findings contribute to understanding the genetic architecture of the GFR and provide a basic approach to predict candidate genes for grain yield trait QTLs.

Evaluation of maize root growth and genome-wide association studies of root traits in response to low nitrogen supply at seedling emergence

Nitrogen(N) deficiency is one of the main factors limiting maize(Zea mays L.) productivity. Genetic improvement of root traits could improve nitrogen use efficiency. An association panel of 461 maize inbred lines was assayed for root growth at seedling emergence under high-nitrate(HN, 5 mmol L^(-1))and low-nitrate(LN, 0.05 mmol L^(-1)) conditions. Twenty-one root traits and three shoot traits were measured. Under LN conditions, the root-to-shoot ratio, root dry weight, total root length, axial root length,and lateral root length on the primary root were all increased. Under LN conditions, the heritability of the plant traits ranged from 0.43 to 0.82, a range much wider than that of 0.27 to 0.55 observed under HN conditions. The panel was genotyped with 542,796 high-density single-nucleotide polymorphism(SNP) markers. Totally 328 significant SNP markers were identified using either mixed linear model(MLM) or general linear model analysis, with 34 detected by both methods. In the 100-kb intervals flanking these SNP markers, four candidate genes were identified. Under LN conditions, the protoporphyrinogen IX oxidase 2 gene was associated with total root surface area and the DELLA protein-encoding gene was associated with the length of the visible lateral root zone of the primary root. Under HN conditions, a histone deacetylase gene was associated with plant height. Under both LN and HN conditions, the gene encoding MA3 domain-containing protein was associated with the first whorl crown root number. The phenotypic and genetic information from this study may be exploited for genetic improvement of root traits aimed at increasing NUE in maize.

Comparison of dimension reduction-based logistic regression models for case-control genome-wide association study:principal components analysis vs.partial least squares

With recent advances in biotechnology, genome-wide association study （GWAS） has been widely used to identify genetic variants that underlie human complex diseases and traits. In case-control GWAS, typical statistical strategy is traditional logistical regression （LR） based on single-locus analysis. However, such a single-locus analysis leads to the well-known multiplicity problem, with a risk of inflating type I error and reducing power. Dimension reduction-based techniques, such as principal component-based logistic regression （PC-LR）, partial least squares-based logistic regression （PLS-LR）, have recently gained much attention in the analysis of high dimensional genomic data. However, the perfor- mance of these methods is still not clear, especially in GWAS. We conducted simulations and real data application to compare the type I error and power of PC-LR, PLS-LR and LR applicable to GWAS within a defined single nucleotide polymorphism （SNP） set region. We found that PC-LR and PLS can reasonably control type I error under null hypothesis. On contrast, LR, which is corrected by Bonferroni method, was more conserved in all simulation settings. In particular, we found that PC-LR and PLS-LR had comparable power and they both outperformed LR, especially when the causal SNP was in high linkage disequilibrium with genotyped ones and with a small effective size in simulation. Based on SNP set analysis, we applied all three methods to analyze non-small cell lung cancer GWAS data.

Genome-Wide Association Study of Nitrogen Use Efficiency and Agronomic Traits in Upland Rice

Genome-wide association study(GWAS)was performed for 16 agronomic traits including nitrogen use efficiency(NUE)and yield-related components using a panel of 190 mainly japonica rice varieties and a set of 38390 single nucleotide polymorphism(SNP)markers.This panel was evaluated under rainfed upland conditions in Madagascar in two consecutive cropping seasons with two contrasted nitrogen input levels.Using another set of five grain traits,we identified previously known genes(GW5,GS3,Awn1 and Glabrous1),thus validating the pertinence and accuracy of our datasets for GWAS.A total of 369 significant associations were detected between SNPs and agronomic traits,gathered into 46 distinct haplotype groups and 28 isolated markers.Few association signals were identified for the complex quantitative trait NUE,however,larger number of quantitative trait loci(QTLs)were detected for its component traits,with 10 and 2 association signals for nitrogen utilization efficiency and nitrogen uptake efficiency,respectively.Several detected association signals co-localized with genes involved in nitrogen transport or nitrogen remobilization within 100 kb.The present study thus confirmed the potential of GWAS to identify candidate genes and new loci associated with agronomic traits.However,because of the quantitative and complex nature of NUE-related traits,GWAS might have not captured a large number of QTLs with limited effects.

Pathway-based analysis of genome-wide association study of circadian phenotypes

Sleepiness affects normal social life, which attracts more and more attention. Circadian phenotypes contribute to obvious individual differences in susceptibility to sleepiness. We aimed to identify candidate single nucleotide polymorphisms（SNPs） which may cause circadian phenotypes, elucidate the potential mechanisms, and generate corresponding SNP-gene-pathways. A genome-wide association studies（GWAS） dataset of circadian phenotypes was utilized in the study. Then, the Identify Candidate Causal SNPs and Pathways analysis was employed to the GWAS dataset after quality control filters. Furthermore, genotype-phenotype association analysis was performed with HapMap database. Four SNPs in three different genes were determined to correlate with usual weekday bedtime,totally providing seven hypothetical mechanisms. Eleven SNPs in six genes were identified to correlate with usual weekday sleep duration, which provided six hypothetical pathways. Our results demonstrated that fifteen candidate SNPs in eight genes played vital roles in six hypothetical pathways implicated in usual weekday bedtime and six potential pathways involved in usual weekday sleep duration.

Genome-wide association study for rib eye muscle area in a Large White×Minzhu F_2 pig resource population

Rib eye muscle area（REMA） is an economically important trait and one of the main selection criteria for breeding in the swine industry. In the genome-wide association study（GWAS）, the Illumina Porcine SNP60 Bead Chip containing 62 163 single nucleotide polymorphisms（SNPs） was used to genotype 557 pigs from a porcine Large White×Minzhu intercross population. The REMA（at the 5th–6th, 10th–11th and the last ribs） was measured after slaughtered at the age of（240±7） d for each animal. Association tests between REMA trait and SNPs were performed via the Genome-Wide Rapid Association using the Mixed Model and Regression-Genomic Control（GRAMMAR-GC） approach. From the Ensembl porcine database, SNP annotation was implemented using Sus scrofa Build 10.2. Thirty-three SNPs on SSC12 and 3 SNPs on SSC2 showed significant association with REMA at the last rib at the chromosome-wide significance level. None of the SNPs of REMA at the 5th–6th rib and only a few numbers of the SNPs of REMA at the 10th–11th ribs were found in this study. The Haploview V3.31 program and the Haplo.Stats R package were used to detect and visualize haplotype blocks and to analyze the association of the detected haplotype blocks with REMA at the last rib. A linkage analysis revealed that 4 haplotype blocks contained 4, 4, 2, and 4 SNPs, respectively. Annotations from pig reference genome suggested 2 genes（NOS2, NLK） in block 1（266 kb）, one gene（TMIGD1） in block 2（348 kb）, and one gene（MAP2K4） in block 3（453 kb）. A functional analysis indicated that MYH3 and MYH13 genes are the potential genes controlling REMA at the last rib. We screened several candidate intervals and genes based on the SNPs location and the gene function, and inferred that NOS2 and NLK genes maybe the main genes of REMA at the last ribs.