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 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 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 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.

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 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.

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.

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.

Statistical analysis for genome-wide association study

In the past few years, genome-wide association study （GWAS） has made great successes in identifying genetic susceptibility loci underlying many complex diseases and traits. The findings provide important genetic insights into understanding pathogenesis of diseases. In this paper, we present an overview of widely used approaches and strategies for analysis of GWAS, offered a general consideration to deal with GWAS data. The issues regarding data quality control, population structure, association analysis, multiple comparison and visual presentation of GWAS results are discussed; other advanced topics including the issue of missing heritability, meta-analysis, setbased association analysis, copy number variation analysis and GWAS cohort analysis are also briefly introduced.

Use of stochastic simulations to investigate the power and design of a whole genome association study using single nucleotide polymorphism arrays in farm animals

This paper presents a quick, easy to implement and versatile way of using stochastic simulations to investigate the power and design of using single nucleotide polymorphism (SNP) arrays for genome-wide association studies in farm animals. It illustrates the methodology by discussing a small example where 6 experimental designs are considered to analyse the same resource consisting of 6006 animals with pedigree and phenotypic records: (1) genotyping the 30 most widely used sires in the population and all of their progeny (515 animals in total), (2) genotyping the 100 most widely used sires in the population and all of their progeny (1102 animals in total), genotyping respectively (3) 515 and (4) 1102 animals selected randomly or genotyping respectively (5) 515 and (6) 1102 animals from the tails of the phenotypic distribution. Given the resource at hand, designs where the extreme animals are genotyped perform the best, followed by designs selecting animals at random. Designs where sires and their progeny are genotyped perform the worst, as even genotyping the 100 most widely used sires and their progeny is not as powerful of genotyping 515 extreme animals.

Genome-wide association study and metabolic pathway prediction of barrenness in maize as a response to high planting density

Increasing the planting density is one way to enhance grain production in maize.However,high planting density brings about growth and developmental defects such as barrenness,which is the major factor limiting grain yield.In this study,the barrenness was characterized in an association panel comprising 280 inbred lines under normal(67500 plants ha–1,ND)and high(120000 plants ha–1,HD)planting densities in 2017 and 2018.The population was genotyped using 776254 single nucleotide polymorphism(SNP)markers with criteria of minor allele frequency>5%and<20%missing data.A genome-wide association study(GWAS)was conducted for barrenness under ND and HD,as well as the barrenness ratio(HD/ND),by applying a Mixed Linear Model that controls both population structure and relative kinship(Q+K).In total,20 SNPs located in nine genes were significantly(P<6.44×10–8)associated with barrenness under the different planting densities.Among them,seven SNPs for barrenness at ND and HD were located in two genes,four of which were common under both ND and HD.In addition,13 SNPs for the barrenness ratio were located in seven genes.A complementary pathway analysis indicated that the metabolic pathways of amino acids,such as glutamate and arginine,and the mitogen-activated protein kinase(MAPK)signaling pathway might play important roles in tolerance to high planting density.These results provide insights into the genetic basis of high planting density tolerance and will facilitate high yield maize breeding.

A genome-wide association study identifies novel genetic loci that modify pharmacokinetic-pharmacodynamic responses to clopidogrel

OBJECTIVE Genetic variants in the pharmacokinetic(PK)mechanism are the main underlying factors that modify the antiplatelet efficacy of clopidogrel.Hence,joint analysis of genetic variants that modify pharmacodynamic(PD)and PK responses to clopidogrel should be effective for identifying the genetic variants affecting the antiplatelet response to the drug.METHODS A genome-wide association study was conducted to identify new genetic loci that modify PD responses to clopidogrel and its active metabolite H4 in 115 Chinese patients with coronary heart disease(CHD).RESULTS We identified novel variants in two transporter genes(rs12456693 in SLC14A2 and rs2487032 in ABCA1)and in N6AMT1(rs2254638)associated with clopidogrel-treated P2Y12reaction unit(PRU)and plasma H4 concentration.The associations between these single nucleotide polymorphisms(SNPs)and PK parameters of clopidogrel and H4 were observed in 31 additional CHD patients(P<0.05).The new variants,together with CYP2C19*2 and clinical factors,dramatically improved the predictability of PRU variability to 37.7%compared with the published value of approximately 20%.The function of these SNPs on the activation of clopidogrel was validated in 32 liver S9 fractions,and the N6AMT1 rs2254638 T variant was found to be associated with decreased formation of H4(P=0.0386).Meanwhile,N6AMT1 rs2254638 was further identified to exert a marginal risk effect for MACE in an independent CHD patient cohort(OR:1.428,95%CI:0.978-2.086,P=0.0653,FDR=0.4726).In conclusion,we systematically identified new genetic variants as risk factors for the reduced efficacy of clopidogrel.CONCLUSION Our study findings enhanced the understanding of the absorption and metabolic mechanisms that influence PD responses to clopidogrel treatment.

A pilot exome-wide association study of age-related cataract in Koreans

Age-related cataract （ARC） is the most common cause of visual impairment and blindness worldwide. A previous study reported that genetic factors could explain approximately 50% of the heritability of cataract. However, a genetic predisposition to ARC and the contributing factors have not yet been elucidated in the Korean population. In this study, we assessed the influence of genetic polymorphisms on the risk of ARC in Koreans, including 156 cataract cases and 138 healthy adults. We conducted an exome-wide association study using Illumina Human Exome-12v1.2 platform to screen 244,770 single nucleotide polymorphisms （SNPs）. No SNPs reached exome-wide significance level of association （P 〈 l x 10 6）. B3GNT4 rs7136356 showed the most significant association with ARC （P = 6.54x 10 5）. Two loci （MUC16 and P2RY2） among the top 20 ARC-associated SNPs were recognized as probably linked to cata- ractogenesis. Functions of these genes were potentially related to regulating dehydration or homeostasis of the eyes, and showed a potential association with dry eye disease. This finding suggests that mucin- and dry eye disease-related genes may play a significant role in cataractogenesis. Our study provides insight into the genetic predisposition of ARC in Koreans. Additional studies with larger sample sizes are required to confirm the results of this study.

Genetic Dissection of Grain Size Traits Through Genome-Wide Association Study Based on Genic Markers in Rice

Grain size plays a significant role in rice,starting from affecting yield to consumer preference,which is the driving force for deep investigation and improvement of grain size characters.Quantitative inheritance makes these traits complex to breed on account of several alleles contributing to the complete trait expression.We employed genome-wide association study in an association panel of 88 rice genotypes using 142 new candidate gene based SSR(cgSSR)markers,derived from yield-related candidate genes,with the efficient mixed-model association coupled mixed linear model for dissecting complete genetic control of grain size traits.A total of 10 significant associations were identified for four grain size-related characters(grain weight,grain length,grain width,and length-width ratio).Among the identified associations,seven marker trait associations explain more than 10%of the phenotypic variation,indicating major putative QTLs for respective traits.The allelic variations at genes OsBC1L4,SHO1 and OsD2 showed association between 1000-grain weight and grain width,1000-grain weight and grain length,and grain width and length-width ratio,respectively.The cgSSR markers,associated with corresponding traits,can be utilized for direct allelic selection,while other significantly associated cgSSRs may be utilized for allelic accumulation in the breeding programs or grain size improvement.The new cgSSR markers associated with grain size related characters have a significant impact on practical plant breeding to increase the number of causative alleles for these traits through marker aided rice breeding programs.

Integrated linkage mapping and genome-wide association study to dissect the genetic basis of zinc deficiency tolerance in maize at seedling stage

Zinc(Zn)deficiency is the most widespread micronutrient deficiency,affecting yield and quality of crops worldwide.Identifying genes associated with Zn-deficiency tolerance in maize is a basis for elucidating its genetic mechanism.A K22×CI7 recombinant inbred population consisting of 210 lines and an association panel of 508 lines were used to identify genetic loci influencing Zn-deficiency tolerance.Under-Zn and-Zn/CK conditions,15 quantitative trait loci(QTL)were detected,each explaining 5.7%-12.6%of phenotypic variation.Sixty-one significant single-nucleotide polymorphisms(SNPs)were identified at P<10^(-5)by genome-wide association study(GWAS),accounting for 5%-14%of phenotypic variation.Among respectively 198 and 183 candidate genes identified within the QTL regions and the 100-kb regions flanking these significant SNPs,12 were associated with Zn-deficiency tolerance.Among these candidate genes,four genes associated with hormone signaling in response to Zn-deficiency stress were co-localized with QTL or SNPs,including the genes involved in the auxin(ZmARF7),and ethylene(ZmETR5,ZmESR14,and ZmEIN2)signaling pathways.Three candidate genes were identified as being responsible for Zn transport,including ZmNAS3 detected by GWAS,ZmVIT and ZmYSL11 detected by QTL mapping.Expression of ZmYSL11 was up-regulated in Zn-deficient shoots.Four candidate genes that displayed different expression patterns in response to Zn deficiency were detected in the regions overlapping peak GWAS signals,and the haplotypes for each candidate gene were further analyzed.

Genome-wide association study reveals novel loci for adult type 1 diabetes in a 5-year nested case-control study

BACKGROUND Type 1 diabetes(T1D)is a severe and prevalent metabolic disease.Due to its high heredity,an increasing number of genome-wide association studies have been performed,most of which were from hospital-based case-control studies with a relatively small sample size.The association of single nucleotide polymorphisms(SNPs)and T1D has been less studied and is less understood in natural cohorts.AIM To investigate the significant variants of T1D,which could be potential biomarkers for T1D prediction or even therapy.METHODS A genome-wide association study(GWAS)of adult T1D was performed in a nested case-control study(785 cases vs 804 controls)from a larger 5-year cohort study in Suzhou,China.Potential harmful or protective SNPs were evaluated for T1D.Subsequent expression and splicing quantitative trait loci(eQTL and sQTL)analyses were carried out to identify target genes modulated by these SNPs.RESULTS A harmful SNP for T1D,rs3117017[odds ratio(OR)=3.202,95%confidence interval(CI):2.296-4.466,P=9.33×10-4]and three protective SNPs rs55846421(0.113,0.081-0.156,1.76×10-9),rs75836320(0.283,0.205-0.392,1.07×10-4),rs362071(0.568,0.495-0.651,1.66×10-4)were identified.Twenty-two genes were further identified as potential candidates for T1D onset.CONCLUSION We identified a potential genetic basis of T1D,both protective and harmful,using a GWAS in a larger nested case-control study of a Chinese population.

A Hybrid Algorithm for Disease Association Study

Single nucleotide polymorphisms (SNPs), which are the most common form of DNA variations, have great potential as a medical diagnostic tool. However, compared to the number of SNPs involved, the available training data sets generally have a fairly small sample size, which is a main challenge to traditional data analysis methods. This paper proposed an improved univariate marginal distribution algorithm (UMDA) named multi-population UMDA (MPUMDA) for disease association study. In order to illustrate the effectiveness of our algorithm, we compared it with some current known methods, and the results showed that our method is potentially interesting as an alter-native tool in disease association study.

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.