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.

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.

Genome-wide and candidate gene association studies identify BnPAP17 as conferring the utilization of organic phosphorus in oilseed rape

Phosphorus(P)is essential for living plants,and P deficiency is one of the key factors limiting the yield in rapeseed production worldwide.As the most important organ for plants,root morphology traits(RMTs)play a key role in P absorption.To investigate the genetic variability of RMT under low P availability,we dissected the genetic structure of RMTs by genome-wide association studies(GWAS),linkage mapping and candidate gene association studies(CGAS).A total of 52 suggestive loci were associated with RMTs under P stress conditions in 405 oilseed rape accessions.The purple acid phosphatase gene BnPAP17 was found to control the lateral root number(LRN)and root dry weight(RDW)under low P stress.The expression of BnPAP17 was increased in shoot tissue in P-efficient cultivars compared to root tissue and P-inefficient cultivars in response to low P stress.Moreover,the haplotype of BnPAP17^(Hap3)was detected for the selective breeding of P efficiency in oilseed rape.Over-expression of the BnPAP17^(Hap3)could promote the shoot and root growth with enhanced tolerance to low P stress and organic phosphorus(Po)utilization in oilseed rape.Collectively,these findings increase our understanding of the mechanisms underlying BnPAP17-mediated low P stress tolerance in oilseed rape.

An Adaptive Weighted Sum Test for Family-Based Multi-Marker Association Studies

Backgrounds: Although many disease-associated common variants have been discovered through genome-wide association studies, much of the genetic effects of complex diseases have not been explained. Population-based association studies are vulnerable to population stratification. A possible solution is to use family-based tests. However, if tests only estimate the genetic effect from the within-family variation to avoid population stratification, they may ignore the useful genetic information from between-family variation and lose power. Methods: We have developed an adaptive weighted sum test for family-based association studies. The new test uses data driven weights to combine two test statistics, and the weights measure the strength of population stratification. When population stratification is strong, the proposed test will automatically put more weight on one statistic derived from within-family variation to maintain robustness against spurious positives. On the other hand, when the effect of population stratification is relatively weak, the proposed test will automatically put more weight on the other statistic derived from both within-family and between-family variation to make use of both sources of genetic variation;and at the same time, the degrees of freedom of the test will be reduced and power of the test will be increased. Results: In our study, the proposed method achieves a higher power in most scenarios of linkage disequilibrium structure as well as Hap Map data from different genes under different population structures while still keeping its robustness against population stratification.

Implicit Hypotheses Are Hidden Power Droppers in Family-Based Association Studies of Secondary Outcomes

Family-based tests of association between a genetic marker and a disease constitute a common design to dissect the genetic architecture of complex traits. The FBAT software is one of the most popular tools to perform such studies. However, researchers are also often interested in the genetic contribution to a more specific manifestation of the phenotype (e.g. severe vs. non-severe form) known as a secondary outcome. Here, what we demonstrate is the limited power of the classical formulation of the FBAT statistic to detect the effect of genetic variants that influence a secondary outcome, in particular when these variants also impact on the onset of the disease, the primary outcome. We prove that this loss of power is driven by an implicit hypothesis, and we propose a derivation of the original FBAT statistic, free from this implicit hypothesis. Finally, we demonstrate analytically that our new statistic is robust and more powerful than FBAT for the detection of association between a genetic variant and a secondary outcome.

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.

Casual associations between blood metabolites and colon cancer

BACKGROUND Limited knowledge exists regarding the casual associations linking blood metabolites and the risk of developing colorectal cancer.AIM To investigate causal associations between blood metabolites and colon cancer.METHODS The study utilized a two-sample Mendelian randomization(MR)analysis to investigate the causal impact of 486 blood metabolites on colorectal cancer.The primary method of analysis used was the inverse variance weighted model.To further validate the results several sensitivity analyses were performed,including Cochran's Q test,MR-Egger intercept test,and MR robust adjusted profile score.These additional analyses were conducted to ensure the reliability and robustness of the findings.RESULTS After rigorous selection for genetic variation,486 blood metabolites were included in the MR analysis.We found Mannose[odds ratio(OR)=2.09(1.10-3.97),P=0.024],N-acetylglycine[OR=3.14(1.78-5.53),P=7.54×10^(-8)],X-11593-O-methylascorbate[OR=1.68(1.04-2.72),P=0.034],1-arachidonoylglycerophosphocholine[OR=4.23(2.51-7.12),P=6.35×10^(-8)]and 1-arachidonoylglycerophosphoethanolamine 4[OR=3.99(1.17-13.54),P=0.027]were positively causally associated with colorectal cancer,and we also found a negative causal relationship between Tyrosine[OR=0.08(0.01-0.63),P=0.014],Urate[OR=0.25(0.10-0.62),P=0.003],N-acetylglycine[0.73(0.54-0.98),P=0.033],X-12092[OR=0.89(0.81-0.99),P=0.028],Succinylcarnitine[OR=0.48(0.27-0.84),P=0.09]with colorectal cancer.A series of sensitivity analyses were performed to confirm the rigidity of the results.CONCLUSION This study showed a causal relationship between 10 blood metabolites and colorectal cancer,of which 5 blood metabolites were found to be causal for the development of colorectal cancer and were confirmed as risk factors.The other five blood metabolites are protective factors.

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.

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.

Causal associations between inflammatory bowel disease and anxiety:A bidirectional Mendelian randomization study

BACKGROUND Anxiety is common in patients with inflammatory bowel disease(IBD),including those with ulcerative colitis(UC)and Crohn’s disease(CD);however,the causal relationship between IBD and anxiety remains unknown.AIM To investigate the causal relationship between IBD and anxiety by using bidirectional Mendelian randomization analysis.METHODS Single nucleotide polymorphisms retrieved from genome-wide association studies(GWAS)of the European population were identified as genetic instrument variants.GWAS statistics for individuals with UC(6968 patients and 20464 controls;adults)and CD(5956 patients and 14927 controls;adults)were obtained from the International IBD Genetics Consortium.GWAS statistics for individuals with anxiety were obtained from the Psychiatric Genomics Consortium(2565 patients and 14745 controls;adults)and FinnGen project(20992 patients and 197800 controls;adults),respectively.Inverse-variance weighted was applied to assess the causal relationship,and the results were strengthened by heterogeneity,pleiotropy and leave-one-out analyses.RESULTS Genetic susceptibility to UC was associated with an increased risk of anxiety[odds ratio:1.071(95%confidence interval:1.009-1.135),P=0.023],while genetic susceptibility to CD was not associated with anxiety.Genetic susceptibility to anxiety was not associated with UC or CD.No heterogeneity or pleiotropy was observed,and the leave-one-out analysis excluded the potential influence of a particular variant.CONCLUSION This study revealed that genetic susceptibility to UC was significantly associated with anxiety and highlighted the importance of early screening for anxiety in patients with UC.

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.

Association mapping of lignin response to Verticillium wilt through an eight-way MAGIC population in Upland cotton

Lignin metabolism plays a pivotal role in plant defense against pathogens and is always positively correlated as a response to pathogen infection. Thus, understanding resistance genes against plant pathogens depends on a genetic analysis of the lignin response. This study used eight Upland cotton lines to construct a multi-parent advanced generation intercross(MAGIC) population(n=280), which exhibited peculiar characteristics from the convergence of various alleles coding for advantageous traits. In order to measure the lignin response to Verticillium wilt(LRVW), the artificial disease nursery(ADN) and rotation nursery(RN) were prepared for MAGIC population planting in four environments. The stem lignin contents were collected, and the LRVW was measured with the lignin value of ADN/RN in each environment, which showed significant variations. We employed 9 323 high-quality single-nucleotide polymorphism(SNP) markers obtained from the Cotton-SNP63K array for genotyping the MAGIC population. The SNPs were distributed through the whole genome with 4.78 SNP/Mb density, ranging from 1.14(ChrA06) to 10.08(ChrD08). In addition, a genome-wide association study was performed using a Mixed Linear Model(MLM) for LRVW. Three stable quantitative trait loci(QTLs), qLRVW-A04, qLRVW-A10, and qLRVW-D05, were identified in more than two environments. Two key candidate genes, Ghi_D05G01046 and Ghi_D05G01221, were selected within the QTLs through the combination of variations in the coding sequence, induced expression patterns, and function annotations. Both genes presented nonsynonymous mutations in coding regions and were strongly induced by Verticillium dahliae. Ghi_D05G01046 encodes a leucine-rich extensin(LRx) protein involved in Arabidopsis cell wall biosynthesis and organization. Ghi_D05G01221 encodes a transcriptional co-repressor novel interactor of novel interactor of jasmonic acid ZIM-domain(JAZ–NINJA), which functions in the jasmonic acid(JA) signaling pathway. In summary, the study creates valuable genetic resources for breeding and QTL mapping and opens up a new perspective to uncover the genetic basis of VW resistance in Upland cotton.

Macrophage migration inhibitory factor gene polymorphisms in inflammatory bowel disease: An association study in New Zealand Caucasians and meta-analysis

AIM:To investigate the association of macrophage migration inhibitory factor(MIF)promoter polymorphisms with inflammatory bowel disease(IBD)risk.METHODS:One thousand and six New Zealand Caucasian cases and 540 Caucasian controls were genotyped for the MIF SNP-173G>C(rs755622)and the repeat polymorphism CATT5-8(rs5844572)using a predesigned TaqMan SNP assay and capillary electrophoresis,respectively.Data were analysed for single site and haplotype association with IBD risk and phenotype.Meta-analysis was employed,to assess cumulative evidence of association of MIF-173G>C with IBD.All published genotype data for MIF-173G>C in IBD were identified using PubMed and subsequently searching the references of all PubMed-identified studies.Imputed genotypes for MIF-173G>C were generated from the Wellcome Trust Case Control Consortium(and National Institute of Diabetes and Digestive and Kidney Diseases).Separate meta-analyses were performed on Caucasian Crohn’s disease(CD)(3863 patients,6031controls),Caucasian ulcerative colitis(UC)(1260 patients,1987 controls),and East Asian UC(416 patients and 789 controls)datasets using the Mantel-Haenszel method.The New Zealand dataset had 93%power,and the meta-analyses had 100%power to detect an effect size of OR=1.40 atα=0.05,respectively.RESULTS:In our New Zealand dataset,single-site analysis found no evidence of association of MIF polymorphisms with overall risk of CD,UC,and IBD or disease phenotype(all P values>0.05).Haplotype analysis found the CATT5/-173C haplotype occurred at a higher frequency in New Zealand controls compared to IBD patients(0.6 vs 0.01;P=0.03,OR=0.22;95%CI:0.05-0.99),but this association did not survive bonferroni correction.Meta-analysis of our New Zealand MIF-173G>C data with data from seven additional Caucasian datasets using a random effects model found no association of MIF polymorphisms with CD,UC,or overall IBD.Similarly,meta-analysis of all published MIF-173G>C data from East Asian datasets(416UC patients,789 controls)found no association of this promoter polymorphism with UC.

Epidemiological studies of esophageal cancer in the era of genome-wide association studies

Esophageal cancer(EC) caused about 395000 deaths in 2010. China has the most cases of EC and EC is the fourth leading cause of cancer death in China. Esophageal squamous cell carcinoma(ESCC) is the predominant histologic type(90%-95%), while the incidence of esophageal adenocarcinoma(EAC) remains extremely low in China. Traditional epidemiological studies have revealed that environmental carcinogens are risk factors for EC. Molecular epidemiological studies revealed that susceptibility to EC is influenced by both environmental and genetic risk factors. Of all the risk factors for EC, some are associated with the risk of ESCC and others with the risk of EAC. However, the details and mechanisms of risk factors involved in the process for EC are unclear. The advanced methods and techniques used in human genome studies bring a great opportunity for researchers to explore and identify the details of those risk factors or susceptibility genes involved inthe process of EC. Human genome epidemiology is a new branch of epidemiology, which leads the epidemiology study from the molecular epidemiology era to the era of genome wide association studies(GWAS). Here we review the epidemiological studies of EC(especially ESCC) in the era of GWAS, and provide an overview of the general risk factors and those genomic variants(genes, SNPs, miRNAs, proteins) involved in the process of ESCC.

Genetic polymorphisms and gastric cancer risk: a comprehensive review synopsis from meta-analysis and genome-wide association studies

Objective: In the past few decades, more than 500 reports have been published on the relationship between single nucleotide polymorphisms(SNPs) on candidate genes and gastric cancer(GC) risk. Previous findings have been disputed and are controversial. Therefore, we performed this article to summarize and assess the credibility and strength of genetic polymorphisms on the risk of GC.Methods: We used Web of Science, PubMed, and Medline to identify meta-analyses published before July 30 th, 2018 that assessed associations between variants on candidate genes and the risk of GC. Cumulative epidemiological evidence of statistical associations was assessed combining Venice criteria and a false-positive report probability(FPRP) test.Results: Sixty-one variants demonstrated a significant association with GC risk, whereas 29 demonstrated no association. Nine variants on nine genes were rated as presenting strong cumulative epidemiological evidence for a nominally significant association with GC risk, including APE1(rs1760944), DNMT1(rs16999593), ERCC5(rs751402), GSTT1(null/presence), MDM2(rs2278744), PPARG(rs1801282), TLR4(rs4986790), IL-17 F(rs763780), and CASP8(rs3834129). Eleven SNPs were rated as moderate, and 33 SNPs were rated as weak. We also used the FPRP test to identify 13 noteworthy SNPs in five genome-wide association studies.Conclusions: Sixty-one variants are significantly associated with GC risk, and 29 variants are not associated with GC risk;however, five variants on five genes presented strong evidence for an association upgraded from moderate. Further study of these variants may be needed in the future. Our study also provides referenced information for the genetic predisposition to GC.

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.

Implications of discoveries from genome-wide association studies in current cardiovascular practice

Genome-wide association studies(GWAS)have identified several genetic variants associated with coronary heart disease(CHD),and variations in plasma lipoproteins and blood pressure(BP).Loci corresponding to CDKN2A/CDKN2B/ANRIL,MTHFD1L,CELSR2,PSRC1 and SORT1 genes have been associated with CHD,and TMEM57,DOCK7,CELSR2,APOB,ABCG5,HMGCR,TRIB1,FADS2/S3,LDLR,NCAN and TOMM40-APOE with total cholesterol.Similarly,CELSR2-PSRC1-SORT1,PCSK9,APOB,HMGCR,NCAN-CILP2-PBX4,LDLR,TOMM40-APOE,and APOC1-APOE are associated with variations in low-density lipoprotein cholesterol levels.Altogether,forty,forty three and twenty loci have been associated with high-density lipoprotein cholesterol,triglycerides and BP phenotypes,respectively.Some of these identified loci are common for all the traits,some do not map to functional genes,and some are located in genes that encode for proteins not previously known to be involved in the biological pathway of the trait.GWAS have been successful at identifying new and unexpected genetic loci common to diseases and traits,thus rapidly providing key novel insights into disease biology.Since genotype information is fixed,with minimum biological variability,it is useful in early life risk prediction.However,these variants explain only a small proportion of the observed variance of these traits.Therefore,the utility of genetic determinants in assessing risk at later stages of life has limited immediate clinical impact.The future application of genetic screening will be in identifying risk groups early in life to direct targeted preventive measures.

Identification of New Resistance Loci Against Sheath Blight Disease in Rice Through Genome-Wide Association Study

Sheath blight(SB) caused by the soil borne pathogen Rhizoctonia solani is one of the most serious global rice diseases. Breeding resistant cultivar is the most economical and effective strategy to control the disease. However, no rice varieties are completely resistant to SB, and only a few reliable quantitative trait loci(QTLs) linked with SB resistance have been identified to date. In this study, we conducted a genome-wide association study(GWAS) of SB resistance using 299 varieties from the rice diversity panel 1(RDP1) that were genotyped using 44 000 high-density single nucleotide polymorphism(SNP) markers. Through artificial inoculation, we found that only 36.5% of the tested varieties displayed resistance or moderate resistance to SB. In particular, the aromatic and aus sub-populations displayed higher SB resistance than the tropical japonica(TRJ), indica and temperate japonica sub-populations. Seven varieties showed similar resistance levels to the resistant control YSBR1. GWAS identified at least 11 SNP loci significantly associated with SB resistance in the three independent trials, leading to the identification of two reliable QTLs, qSB-3 and qSB-6, on chromosomes 3 and 6. Using favorable alleles or haplotypes of significantly associated SNP loci, we estimated that both QTLs had obvious effects on reducing SB disease severity and can be used for enhancing SB resistance, especially in improving SB resistance of TRJ sub-population rice varieties. These results provided important information and genetic materials for developing SB resistant varieties through breeding.

Myopia genetics in genome-wide association and postgenome-wide association study era

Genome-wide association studies(GWAS) of myopia and refractive error have generated exciting results and identified novel risk-associated loci. However, the interpretation of the findings of GWAS of complex diseases is not straightforward and has remained challenging. This review provides a brief summary of the main focus on the advantages and limitations of GWAS of myopia, with potential strategies that may contribute to further insight into the genetics of myopia in the post-GWAS or omics era.