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 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.

Genome-wide association studies - A summary for the clinical gastroenterologist

Genome-wide association studies (GWAS) have been applied to various gastrointestinal and liver diseases in recent years. A large number of susceptibility genes and key biological pathways in disease development have been identified. So far, studies in inflammatory bowel diseases, and in particular Crohn’s disease, have been especially successful in def ining new susceptibility loci using the GWAS design. The identification of associations related to autophagy as well as several genes involved in immunological response will be important to future research on Crohn’s disease. In this review, key methodological aspects of GWAS, the importance of proper cohort collection, genotyping issues and statistical methods are summarized. Ways of addressing the shortcomings of the GWAS design, when it comes to rare variants, are also discussed. For each of the relevant conditions, fi ndings from the various GWAS are summarized with a focus on the affected biological systems.

Genome-wide Association Studies of Common Obesity: Now and Future

Obesity has become a major public health concern worldwide. Obesity is a complex disease influenced by both genetic and environmental factors. Epidemiological studies have indicated that environmental factors, such as excessive energy intake and lack of physical activity, might contribute to the development of obesity. Genetic factors also play an important role in the pathogenesis of obesity Indeed, approximately 40%-70% of the variation in body mass index （BMI） can be attributed to genetic factors.

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.

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.

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.

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.

Validation of the Red Pericarp Gene from 419 Rice Landraces in Guangxi via Genome-wide Association Studies

Rice has different colors of pericarp, such as red, white and black. Red rice pericarp is rich in proanthocyanins, which have antioxidant properties and are beneficial to human health. In the present study, we analyzed the red-pericarp gene Rc of 419 rice landraces in Guangxi by genome-wide association study （GWAS）, and validated that the Rc gene regulated the red periearp trait in flee. By analyzing the genomie DNA of 97 red-pericarp flee eultivars, we identified two new alleles in C139 and C323. Then, the exons of Rcc＇9 and Rcc were sequenced with Sanger method, and the results demonstrated that the natural mutations within Re ene resulted in the two alleles Rcc and Rcc.

Genome-wide association studies of hypertension:Achievements,difficulties and strategies

Estimated from family studies,the heritability of hypertension ranges from 31%to 68%.Linkage studies and candidate gene association studies were once widely used to investigate the genetic mechanisms of hypertension.However,results from these studies could only explain 1%-2%heritability.With the technological advances and subsequently the accomplishment of the Human Genome Project,genome-wide association studies(GWA studies)have been applied to find genome-wide significant signals for many common diseases.Current GWA studies of hypertension have identified dozens of hypertension or blood pressure associated variants.However,different GWA study identified different variants and the results could hardly be replicated in other studies.Therefore,a debate took place on whether GWA studies will unlock the genetic basis of hypertension and whether we shall continue throwing millions of dollars on GWA studies.This review gives a short introduction to the history of genetic study on hypertension and summarizes the current findings for GWA studies of hypertension or blood pressure.Finally,we will discuss that debate and try to find alternative strategies and technologies that may hold a greater chance to make progress in understanding the genetic risk factors of hypertension and blood pressure regulation.

Genome-Wide Association Studies Reveal New Genetic Targets for Five Panicle Traits of International Rice Varieties

Narrow genetic background is a key limiting factor in breeding stable high-yielding rice. The introduction and utilization of international rice core germplasm is an important way to increase the genetic diversity of domestic rice varieties. We conducted a genome-wide association study on 5 panicle traits of 315 rice accessions introduced from the international rice micro-core germplasm bank. Based on the tests from Yangzhou of China and Arkansas of American, environment exhibited a significant impacts on panicle length and primary branch number, while grain length, grain width and grain length/width ratio were insensitive to environment changes. We discovered a total of 7, 5, 10, 8 and 6 chromosomal regions or single nucleotide polymorphism marker loci that were significantly associated with primary branch number, panicle length, grain length, grain width and grain length/width ratio, respectively. Among them, eleven regions were associated with grain shape and one region associated with primary branch number, showing the good consistence in two different environments. Significant linear correlation was discovered between the average trait value and the number of favorable alleles carried by the varieties in all associated loci. Among the associated loci, varieties in aromatic and tropical japonica sub-groups possessed most favorable alleles, while those in temperate japonica sub-group contained the least. The domestic varieties mainly harbored unfavorable alleles in six of the associated loci being detected. On the contrary, 15 varieties from 11 different countries harbored more favorable alleles （as many as 30 or more） than the others. Remarkably, all these 15 varieties belonged to the tropical japonica sub-group. In conclusion, our study demonstrates that varieties in the tropical japonica sub-group had high potentials for breeding stable high-yielding rice. Based on this discovery, we proposed a new approach for improving the panicle traits of domestic rice by using tropical japonica varieties.

Genome-wide association studies:Where we are heading?

wide association studies(GWAS)in recent years.Since the identification of variants in the complement factor H gene on the risk of age-related macular degeneration,GWAS have become ubiquitous in genetic studies and have led to the identification of genetic variants that are associated with a variety of complex human diseases and traits.These discoveries have changed our understanding of the biological architecture of common,complex diseases and have also provided new hypotheses to test.New tools,such as next-generation sequencing,will be an important part of the future of genetics research;however,GWAS studies will continue to play an important role in disease gene discovery.Many traits have yet to be explored by GWAS,especially in minority populations,and large collaborative studies are currently being conducted to maximize the return from existing GWAS data.In addition,GWAS technology continues to improve,increasing genomic coverage for major global populations and decreasing the cost of experiments.Although much of the variance attributable to genetic factors for many important traits is still unexplained,GWAS technology has been instrumental in mapping over a thousand genes to hundreds of traits.More discoveries are made each month and the scale,quality and quantity of current work has a steady trend upward.We briefly review the current key trends in GWAS,which can be summarized with three goals:increase power,increase collaborations and increase populations.

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.

BLUPmrMLM:A Fast mrMLM Algorithm in Genome-wide Association Studies

Multilocus genome-wide association study has become the state-of-the-art tool for dissecting the genetic architecture of complex and multiomic traits.However,most existing multilocus methods require relatively long computational time when analyzing large datasets.To address this issue,in this study,we proposed a fast mrMLM method,namely,best linear unbiased prediction multilocus random-SNP-effect mixed linear model(BLUPmrMLM).First,genome-wide single-marker scanning in mrMLM was replaced by vectorized Wald tests based on the best linear unbiased prediction(BLUP)values of marker effects and their variances in BLUPmrMLM.Then,adaptive best subset selection(ABESS)was used to identify potentially associated markers on each chromosome to reduce computational time when estimating marker effects via empirical Bayes.Finally,shared memory and parallel computing schemes were used to reduce the computational time.In simulation studies,BLUPmrMLM outperformed GEMMA,EMMAX,mrMLM,and FarmCPU as well as the control method(BLUPmrMLM with ABESS removed),in terms of computational time,power,accuracy for estimating quantitative trait nucleotide positions and effects,false positive rate,false discovery rate,false negative rate,and F1 score.In the reanalysis of two large rice datasets,BLUPmrMLM significantly reduced the computational time and identified more previously reported genes,compared with the aforementioned methods.This study provides an excellent multilocus model method for the analysis of large-scale and multiomic datasets.The software mrMLM v5.1 is available at BioCode(https://ngdc.cncb.ac.cn/biocode/tool/BT007388)or GitHub(https://github.com/YuanmingZhang65/mrMLM).

A Meta-Analysis of the Genome-Wide Association Studies on Two Genetically Correlated Phenotypes Suggests Four New Risk Loci for Headaches

Headache is one of the commonest complaints that doctors need to address in clinical settings.The genetic mechanisms of different types of headache are not well understood while it has been suggested that self-reported headache and self-reported migraine were genetically correlated.In this study,we performed a meta-analysis of genome-wide association studies(GWAS)on the self-reported headache phenotype from the UK Biobank and the self-reported migraine phenotype from the 23andMe using the Unified Score-based Association Test(metaUSAT)software for genetically correlated phenotypes(N=397,385).We identified 38 loci for headaches,of which 34 loci have been reported before and four loci were newly suggested.The LDL receptor related protein 1(LRP1)-Signal Transducer and Activator of Transcription 6(STAT6)-Short chain Dehydrogenase/Reductase family 9C member 7(SDR9C7)region in chromosome 12 was the most significantly associated locus with a leading p value of 1.24×10^(-62)of rs11172113.The One Cut homeobox 2(ONECUT2)gene locus in chromosome 18 was the strongest signal among the four new loci with a p value of 1.29×10^(-9)of rs673939.Our study demonstrated that the genetically correlated phenotypes of self-reported headache and self-reported migraine can be meta-analysed together in theory and in practice to boost study power to identify more variants for headaches.This study has paved way for a large GWAS meta-analysis involving cohorts of different while genetically correlated headache phenotypes.

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 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 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.