小麦根部耐盐性状全基因组关联分析

为了解小麦耐盐相关性状的遗传机理,挖掘与小麦耐盐性显著相关的SNP位点及候选基因,本研究利用浓度200 mmol/L的NaCl溶液和正常营养液对全国300份小麦品种(系)进行耐盐性试验,并利用小麦90 K芯片对分布于小麦全基因组的16650个SNP,采用Q+K关联混合模型对小麦最长根长、根干重、根鲜重、根平均直径、根尖数、根表面积、根体积和总根长等8个根部耐盐性相关性状进行全基因组关联分析(GWAS,genome-wide association study)。研究结果表明,小麦根部性状表现出广泛的表型变异,变异系数为24.3%~50.0%,多态性信息含量(PIC,polymorphic information content)为0.170~0.562,全基因组LD衰减距离为6 Mb;群体结构分析表明,试验所用300份小麦品种(系)可分为3个亚群,亚群1包含143个(47.67%)试验材料,主要来自河南、陕西和四川;亚群2包含74个(24.67%)试验材料,主要来自北京;亚群3包含83个(27.67%)试验材料,主要来自河南。GWAS共检测到77个与小麦耐盐相关性状显著关联的SNP位点(P≤0.001),这些位点分布在小麦除6D外的20条染色体上,单个SNP位点可解释3.70%~19.45%的表型变异,其中位于1A、3A、4A、7A、3D和5D染色体上的RAC875_c13169_459等6个位点同时关联到2个或2个以上性状,贡献率为3.78%~19.45%;对77个SNP位点进行发掘,筛选到17个可能与小麦耐盐性有关的候选基因。TraesCS5B01G031800(阳离子反转运蛋白)在Na+等阳离子转运中起重要作用,TraesCS5A01G329000(防御素)可以在阻断Na+等阳离子进入过程中起作用,TraesCS2A01G079000(重复富脯氨酸细胞壁蛋白)在细胞壁的形成中起重要作用,这些候选基因可作为耐盐性重要基因。     

小麦主胚根生长及主要性状全基因组关联分析

为解析小麦初生根系建成的遗传机制,本研究以黄淮麦区的198份小麦自然群体为材料,对在室内人工气候箱内水培21 d的小麦主胚根的一级分枝根数、分枝密度、长度、表面积、体积和平均直径6个性状进行调查分析,结合660K基因芯片用Q+K混合线性模型对主胚根性状进行全基因组关联分析,并对显著且稳定的关联位点进行功能注释和候选基因挖掘。结果表明,主胚根不同性状呈正态或近似正态分布,变异系数为5.56%～22.10%。通过全基因组关联分析,共检测到136个显著关联位点,这些位点分布在除7B以外的染色体上,可解释5.10%～13.60%的表型变异,同时检测到13个显著的多效位点,挖掘到TraesCS4A01G023100、TraesCS1B01G294400、TraesCS4A01G006200等16个可能与主胚根生长相关的候选基因,这些基因可能通过调控DNA拓扑结构异构酶、泛素结合酶E2、磷酸肌醇磷酸酶家族蛋白等参与小麦主胚根系的建成。本研究结果为小麦根系调控网络构建,以及优化根系构型和发挥根系功能提供了参考。     

甘蓝型油菜籽粒着生密度及其相关性状全基因组关联分析

油菜角果内籽粒着生密度影响每果粒数,对油菜产量有直接或间接影响。本研究以不同遗传背景和地理来源的213份甘蓝型油菜品种(系)构成的自然群体为研究对象,利用芸薹属60 K Illumina Infinium SNP芯片进行群体结构、亲缘关系以及连锁不平衡分析;然后基于最优模型对籽粒着生密度及其相关性状进行全基因组关联(GWAS)分析。通过GWAS分析,共检测到10个SNP位点与籽粒着生密度及其相关性状关联。其中与籽粒着生密度关联的标记有2个,表型贡献率分别为9.49%和11.17%;与角果有效长关联的标记有6个,单个位点可解释9.81%~12.17%的表型变异;与每果粒数相关联的标记有2个,分别解释10.44%和10.87%的表型变异。通过分析关联SNP位点的LD区间的基因信息,筛选出16个与籽粒着生密度及其相关性状有关的候选基因,其中KMD4和UGT76C2基因与细胞分裂素的调控有关;AGL104和ADC2基因参与种子的形成过程;MCCB、NGA2和MATE等基因参与侧生器官的生长发育过程,它们的异常表达会导致一些侧生器官的变异。ADC2和UGT76C2两个候选基因可能对籽粒着生密度和每果粒数一因多效性。     

中国人群肝功能检测指标全基因组关联分析研究

肝功能检测(liver function test,LFTs)指标是受遗传和环境影响的复杂性状,具有个体差异性。为系统性研究中国人群全基因组范围内单核苷酸多态性(single nucleotide polymorphism,SNP)与肝功能指标之间的联系,本研究利用英国生物银行(UK Biobank)中1653名中国人的基因分型数据和表型数据为研究对象,利用PLINK软件进行全关联分析研究(genome-wide association study,GWAS),发现229个SNP与中国人群血液中的总胆红素(total bilirubin,TB)相关,27个SNP与中国人群血液中碱性磷酸酶(alkaline phosphatase,ALP)相关,36个SNP与中国人群血液中的γ-谷氨酰转肽酶(γ-glutamyl transpeptidase,GGT)相关,1个SNP与中国人群血液中的门冬氨酸氨基转移酶(aspartate transaminase,AST)相关,最显著的位点中有11个位点是新的LFTs关联位点。通过功能基因组分析,发现这些位点的临床意义(如吉尔伯特综合征),确定了候选基因(UGT1A,ABO,GGT1),为从遗传角度理解中国人群LFTs的个体差异性和肝功能指标临床精准检测提供了前期研究基础。     

甘蓝型油菜每角果粒数全基因组关联分析

为挖掘甘蓝型油菜每角果粒数显著关联单核苷酸多态性（SNP）位点及相关候选基因。本研究以300份甘蓝型油菜自交系为试验材料,对甘蓝油菜每角果粒数进行一年两地表型考察,并结合该群体前期开发的201 817个SNPs标记,采用一般线性模型（GLM）和混合线性模型（MLM）进行全基因组关联分析（GWAS）,此外,对性状显著关联SNP位点两侧100 kb区域内相关候选基因进行功能预测。300份甘蓝型油菜每角果粒数在两地均表现出广泛的表型变异,筛选出2份每角果粒数较多的油菜种质资源。基于GLM模型检测到39个与油菜每角果粒数显著关联SNPs,采用MLM分析发现,两地共检测到的3个每角果粒数显著关联SNPs位点均在GLM检测到。8个位点附近找到CIK,ERF022和EDE1等19个拟南芥已报道角果籽粒发育相关的同源基因。研究结果有助于解析甘蓝型油菜每角果粒数的遗传基础,为研究每角果粒数的调控机制、指导每角果粒数的遗传改良奠定基础。     

生物信息学分析方法I: 全基因组关联分析概述

全基因组关联分析(GWAS)是动植物复杂性状相关基因定位的常用手段。高通量基因分型技术的应用极大地推动了GWAS的发展。在植物中, 利用GWAS不仅能够以较高的分辨率在全基因组水平鉴定出各种自然群体特定性状相关的基因或区间, 而且可揭示表型变异的遗传架构全景图。目前, 人们利用GWAS分析方法已在拟南芥(Arabidopsis thaliana)、水稻(Oryza sativa)、小麦(Triticum aestivum)、玉米(Zea mays)和大豆(Glycine max)等模式植物和重要农作物品系中发掘出与各种性状显著相关的数量性状座位(QTL)及其候选基因位点, 阐明了这些性状的遗传基础, 并为揭示这些性状背后的分子机理提供候选基因, 也为作物高产优质品种的选育提供了理论依据。该文对GWAS的方法、影响因素及数据分析流程进行了详细描述, 以期为相关研究提供参考。     

基于简化基因组测序的大黄鱼耐高温性状全基因组关联分析

利用Illumina HiSeqTM 2500测序平台, 对通过高温胁迫实验筛选得到的20尾耐高温和20尾不耐高温的大黄鱼(Larimichthys crocea)进行了简化基因组测序(SLAF-seq), 每个样本的平均测序深度达到10.26×, 共获得419211个高质量的群体单核苷酸多态性(SNP)位点 。利用TASSEL软件的混合线性模型(MLM)进行全基因组关联分析(GWAS), 共筛选到38个与大黄鱼耐高温性状显著相关的SNP位点(P<2.39E–08)。利用BLAST程序定位每个SNP位点在大黄鱼基因组中的位置, 并分析其周围的功能基因。结果在38个SNPs附近共找到26个已知的功能基因, 这些基因主要与细胞转录、代谢、免疫等功能相关。研究结果可为下一步大黄鱼耐高温分子机制解析及耐高温品种的选育提供参考。     

普通小麦根系建成相关性状的全基因组关联分析

根系建成(RSA,Root system architecture)决定根系系统的构成,在作物生长发育过程中起着不可替代的作用。解析小麦根系建成遗传机制、选育具有较好根系建成的品种对于小麦高产、抗逆育种具有十分重要的意义。全基因组关联分析(GWAS)是解析小麦复杂数量遗传性状遗传机制的有效方法。本研究基于全基因组关联分析方法,发掘根系建成相关性状关联位点,以期为小麦根系建成分子育种提供参考。对160份来自于河南和山东等地的小麦品种根系建成相关性状(总根长、总根表面积、总根体积、平均根直径和根尖数)进行统计评价,并结合660K SNP芯片数据进行全基因组关联分析。检测到23个关联位点,分布于1A、2A、2B、3B、4A、5A、5B、5D、6A、6B和7B染色体上,解释7.2%～12.8%的表型变异。其中,11个位点与已报道的位点一致,其他12个位点为新的位点。本研究对于解析根系建成遗传机制,选育高产、抗逆小麦品种具有重要意义。     

玉米穗部性状及其一般配合力的关联分析

穗部性状是影响玉米产量的重要性状,一般配合力是评价玉米自交系利用价值的重要指标。为解析穗部性状及其一般配合力的遗传基础,本研究对248份玉米自交系组成的自然群体和以其中100份自交系为母本按照NCⅡ遗传交配设计与4个测验种(Mo17、昌7-2、E28和郑58)组配的400份F1杂交组合的穗部性状进行研究,并利用分布于全基因组的83057个SNP标记进行穗部性状及其一般配合力的关联分析。结果表明,穗长、穗粗2个穗部性状基因型间、环境间差异达极显著水平,其广义遗传率分别为81.22%和87.70%。母本间、父本间及不同杂交组合间穗长、穗粗差异均达极显著水平,在基因型方差中特殊配合力贡献率较大。利用2年2点4个环境下的数据分别进行关联分析,检测到34个性状SNP关联,利用BLUP值检测到7个性状SNP关联。这些性状SNP关联可解释的表型变异为0.01%～19.42%,其中有5个性状SNP关联的表型贡献率大于10%,未检测到穗部性状本身与一般配合力性状的相同SNP位点。基于该群体的LD衰减距离在显著关联SNP位点上下游各120 kb范围内进行候选基因搜索,共发现158个候选基因,推测可能的候选基因涉及泛素代谢相关基因(GRMZM2G360374、GRMZM2G049568、GRMZM2G178120),β半乳糖苷酶(GRMZM2G178106),丝氨酸苏氨酸蛋白激酶(GRMZM2G127050),赖氨酸和组氨酸特异性转运体(GRMZM2G116004)。研究结果为解析玉米穗长和穗粗及其一般配合力的遗传基础和分子辅助选择育种提供了参考。     

京海黄鸡体重性状全基因组关联分析

体重性状是肉鸡重要的经济性状。为了寻找可用于京海黄鸡体重性状遗传改良的分子标记及候选基因,本文以400只京海黄鸡核心群母鸡为基础,测定了0~14周龄体重,利用简化基因组测序技术(Specific-locus amplified fragment sequencing, SLAF-seq)对京海黄鸡体重性状进行全基因组关联研究(Genome-wide association stndy, GWAS),筛选与京海黄鸡体重性状相关的SNPs位点。结果共检测到100个与京海黄鸡体重相关的SNPs位点,其中15个位点效应达到全基因组显著水平(P<1.87E-06),85个位点效应达到全基因组潜在显著水平(P<3.73E-05)。通过筛选每个显著SNP周围1 Mb区域内的基因,共找到9个可能的候选基因,其中FAM124A(Family with sequence similarity 124A)、QDPR(Quinoid dihydropteridine reductase)、WDR1(WD repeat domain 1)和SLC2A9(Solute carrier family 2 (facilitated glucose transporter), member 9) 4个基因可能是影响体重性状的重要候选基因。同时还发现,4号染色体75.6~80.7 Mb区域集中了大部分与京海黄鸡中后期体重性状显著相关的SNPs位点,该区域可能是影响京海黄鸡中后期生长体重的重要候选区域。     

Genome‐wide association study for 13 agronomic traits reveals distribution of superior alleles in bread wheat from the Yellow and Huai Valley of China

Bread wheat is a leading cereal crop worldwide. Limited amount of superior allele loci restricted the progress of molecular improvement in wheat breeding. Here, we revealed new allelic variation distribution for 13 yield‐related traits in series of genome‐wide association studies (GWAS) using the wheat 90K genotyping assay, characterized in 163 bread wheat cultivars. Agronomic traits were investigated in 14 environments at three locations over 3 years. After filtering SNP data sets, GWAS using 20 689 high‐quality SNPs associated 1769 significant loci that explained, on average, ~20% of the phenotypic variation, both detected already reported loci and new promising genomic regions. Of these, repetitive and pleiotropic SNPs on chromosomes 6AS, 6AL, 6BS, 5BL and 7AS were significantly linked to thousand kernel weight, for example BS00021705_51 on 6BS and wsnp_Ex_c32624_41252144 on 6AS, with phenotypic variation explained (PVE) of ~24%, consistently identified in 12 and 13 of the 14 environments, respectively. Kernel length‐related SNPs were mainly identified on chromosomes 7BS, 6AS, 5AL and 5BL. Plant height‐related SNPs on chromosomes 4DS, 6DL, 2DS and 1BL were, respectively, identified in more than 11 environments, with averaged PVE of ~55%. Four SNPs were confirmed to be important genetic loci in two RIL populations. Based on repetivity and PVE, a total of 41 SNP loci possibly played the key role in modulating yield‐related traits of the cultivars surveyed. Distribution of superior alleles at the 41 SNP loci indicated that superior alleles were getting popular with time and modern cultivars had integrated many superior alleles, especially for peduncle length‐ and plant height‐related superior alleles. However, there were still 19 SNP loci showing less than percentages of 50% in modern cultivars, suggesting they should be paid more attention to improve yield‐related traits of cultivars in the Yellow and Huai wheat region. This study could provide useful information for dissection of yield‐related traits and valuable genetic loci for marker‐assisted selection in Chinese wheat breeding programme.     

Genome-wide association mapping of salinity tolerance in rice (Oryza sativa)

Salinity tolerance in rice is highly desirable to sustain production in areas rendered saline due to various reasons. It is a complex quantitative trait having different components, which can be dissected effectively by genome-wide association study (GWAS). Here, we implemented GWAS to identify loci controlling salinity tolerance in rice. A custom-designed array based on 6,000 single nucleotide polymorphisms (SNPs) in as many stress-responsive genes, distributed at an average physical interval of <100 kb on 12 rice chromosomes, was used to genotype 220 rice accessions using Infinium high-throughput assay. Genetic association was analysed with 12 different traits recorded on these accessions under field conditions at reproductive stage. We identified 20 SNPs (loci) significantly associated with Na⁺/K⁺ ratio, and 44 SNPs with other traits observed under stress condition. The loci identified for various salinity indices through GWAS explained 5–18% of the phenotypic variance. The region harbouring Saltol, a major quantitative trait loci (QTLs) on chromosome 1 in rice, which is known to control salinity tolerance at seedling stage, was detected as a major association with Na⁺/K⁺ ratio measured at reproductive stage in our study. In addition to Saltol, we also found GWAS peaks representing new QTLs on chromosomes 4, 6 and 7. The current association mapping panel contained mostly indica accessions that can serve as source of novel salt tolerance genes and alleles. The gene-based SNP array used in this study was found cost-effective and efficient in unveiling genomic regions/candidate genes regulating salinity stress tolerance in rice.     

A genome-wide association study uncovers novel genomic regions and candidate genes of yield-related traits in upland cotton

Key message

A total of 62 SNPs associated with yield-related traits were identified by a GWAS. Based on significant SNPs, two candidate genes pleiotropically increase lint yield.

Abstract

Improved fibre yield is considered a constant goal of upland cotton (Gossypium hirsutum) breeding worldwide, but the understanding of the genetic basis controlling yield-related traits remains limited. To better decipher the molecular mechanism underlying these traits, we conducted a genome-wide association study to determine candidate loci associated with six yield-related traits in a population of 719 upland cotton germplasm accessions; to accomplish this, we used 10,511 single-nucleotide polymorphisms (SNPs) genotyped by an Illumina CottonSNP63K array. Six traits, including the boll number, boll weight, lint percentage, fruit branch number, seed index and lint index, were assessed in multiple environments; large variation in all phenotypes was detected across accessions. We identified 62 SNP loci that were significantly associated with different traits on chromosomes A07, D03, D05, D09, D10 and D12. A total of 689 candidate genes were screened, and 27 of them contained at least one significant SNP. Furthermore, two genes (Gh_D03G1064 and Gh_D12G2354) that pleiotropically increase lint yield were identified. These identified SNPs and candidate genes provide important insights into the genetic control underlying high yields in G. hirsutum, ultimately facilitating breeding programmes of high-yielding cotton.

     

A large‐scale genomic association analysis identifies the candidate causal genes conferring stripe rust resistance under multiple field environments

The incorporation of resistance genes into wheat commercial varieties is the ideal strategy to combat stripe or yellow rust (YR). In a search for novel resistance genes, we performed a large‐scale genomic association analysis with high‐density 660K single nucleotide polymorphism (SNP) arrays to determine the genetic components of YR resistance in 411 spring wheat lines. Following quality control, 371 972 SNPs were screened, covering over 50% of the high‐confidence annotated gene space. Nineteen stable genomic regions harbouring 292 significant SNPs were associated with adult‐plant YR resistance across nine environments. Of these, 14 SNPs were localized in the proximity of known loci widely used in breeding. Obvious candidate SNP variants were identified in certain confidence intervals, such as the cloned gene Yr18 and the major locus on chromosome 2BL, despite a large extent of linkage disequilibrium. The number of causal SNP variants was refined using an independent validation panel and consideration of the estimated functional importance of each nucleotide polymorphism. Interestingly, four natural polymorphisms causing amino acid changes in the gene TraesCS2B01G513100 that encodes a serine/threonine protein kinase (STPK) were significantly involved in YR responses. Gene expression and mutation analysis confirmed that STPK played an important role in YR resistance. PCR markers were developed to identify the favourable TraesCS2B01G513100 haplotype for marker‐assisted breeding. These results demonstrate that high‐resolution SNP‐based GWAS enables the rapid identification of putative resistance genes and can be used to improve the efficiency of marker‐assisted selection in wheat disease resistance breeding.     

Genome‐wide detection of genetic loci and candidate genes for teat number and body conformation traits at birth in Chinese Sushan pigs

Body conformation at birth and teat number are economically important traits in the pig industry, as these traits are usually explored to evaluate the growth and reproductive potential of piglets. To detect genetic loci and candidate genes for these traits, we performed a GWAS on 269 pigs from a recently developed Chinese breed (Sushan) using 38  128 informative SNPs on the Affymetrix Porcine SNP 55K Array. In total, we detected one genome‐wide significant (P = 1.31e‐6) SNP for teat number on chromosome X and 15 chromosome‐wide significant SNPs for teat number, body weight, body length, chest circumference and cannon circumference at birth on chromosomes 1, 3, 4, 6, 7, 9, 10, 13, 14, 15, 17 and 18. The most significant SNP had an additive effect of 0.74 × total teat number, explaining 20% of phenotypic variance. Five significant SNPs resided in the previously reported quantitative trait loci for these traits and seven significant SNPs had a pleiotropic effect on multiple traits. Intriguingly, 12 of the genes nearest to the significant SNPs are functionally related to body conformation and teat number traits, including SPRED2, MKX, TMSB4X and ESR1. GO analysis revealed that candidate genes proximal to the significant SNPs were enriched in the G‐protein coupled receptor and steroid hormone‐mediated signaling pathway. Our findings shed light on the genetic basis of the measured traits and provide molecular markers especially for the genetic improvement of teat number in Sushan and related pigs.     

Mapping QTLs for chlorophyll content and chlorophyll fluorescence in wheat under heat stress

Heat stress, one of the major abiotic stresses in wheat, affects chlorophyll fluorescence and chlorophyll content and thereby photosynthesis. To identify quantitative trait loci (QTLs) associated with these traits under terminal heat stress, 251 recombinant inbred lines (RILs) derived from a cross HD 2808/HUW510 were phenotyped. Using composite interval mapping, 40 QTLs were identified; 17 were related to conditions after timely sowing and 23 to heat stress after late sowing. The various parameters of chlorophyll fluorescence were associated with 23 QTLs, which were located on chromosomes 1A, 2A, 3A, and 2D and explained 3.67 to 18.04 % of phenotypic variation, whereas chlorophyll content was associated with 17 QTLs on chromosomes 2A, 2B, 2D, 5B, and 7A explaining 3.49 to 31.36 % of phenotypic variation. Most of the identified QTLs were clustered on chromosome 2D followed by 2A and 1A. The QTL Qchc.iiwbr-2A for chlorophyll content linked with marker gwm372 was stable over conditions and explained 3.81 to 18.05 % of phenotypic variation. In addition, 7 epistatic QTL pairs were also detected which explained 1.67 to 11.0 % of phenotypic variance. These identified genomic regions can be used in marker assisted breeding after validation for heat tolerance in wheat.     

A genome-wide association study of early-maturation traits in upland cotton based on the CottonSNP8oK array

Genome-wide association studies(GWASs)efficiently identify genetic loci controlling traits at a relatively high resolution.In this study,variations in major early-maturation traits,including seedling period(SP),bud period(BP),flower and boll period(FBP),and growth period(GP),of 169 upland cotton accessions were investigated,and a GWAS of early maturation was performed based on a CottonSNP80K array.A total of49,650 high-quality single-nucleotide polymorphisms(SNPs)were screened,and 29 significant SNPs located on chromosomes A6,A7,A8,D1,D2,and D9,were repeatedly identified as associated with early-maturation traits,in at least two environments or two algorithms.Of these 29 significant SNPs,1,12,11,and 5 were related to SP,BP,FBP,and GP,respectively.Six peak SNPs,TM47967,TM13732,TM20937,TM28428,TM50283,and TM72552,exhibited phenotypic contributions of approximately 10%,which could allow them to be used for marker-assisted selection.One of these,TM72552,as well as four other SNPs,TM72554,TM72555,TM72558,and TM72559,corresponded to the quantitative trait loci previously reported.In total,274 candidate genes were identified from the genome sequences of upland cotton and were categorized based on their functional annotations.Finally,our studies identified Gh_D01G0340 and Gh_D01G0341 as potential candidate genes for improving cotton early maturity.