小麦耐低磷相关性状的全基因组关联分析

通过对小麦耐低磷相关性状进行全基因组关联分析(GWAS,genome-wide association study),挖掘与小麦耐低磷性显著相关的单核苷酸多态性标记(SNP,single nucleotide polymorphism)位点及候选基因,为小麦耐低磷性状的遗传基础和分子机制研究提供理论参考。本试验以198份黄淮麦区小麦品种(系)为试验材料,设置低磷和正常磷营养液水培试验,利用小麦35K芯片对分布于小麦全基因组的11896个SNP,采用Q+K关联模型对小麦耐低磷性相关性状进行关联分析。结果表明,小麦耐低磷性状表现出广泛的表型变异,变异系数为15.65%~26.59%,多态性信息含量(PIC,polymorphic information content)为0.095~0.500。群体结构分析表明,试验所用自然群体可分为2个亚群,GWAS共检测到67个与小麦耐低磷相关性状显著关联的SNP位点(P≤0.001),这些位点分布在除3A、3B和3D以外的18条染色体上,单个SNP位点可解释5.826%~9.552%的表型变异。在这些显著位点中有4个SNP位点同时关联到了2个不同的耐低磷性状。对67个SNP位点进行发掘,筛选到7个可能与小麦耐低磷性有关的候选基因。TraesCS6A02G001000和TraesCS6A02G001100在锌指合成中有重要作用;TraesCS6A02G118100可能为低磷胁迫诱导基因;TraesCS5D02G536400、TraesCS1B02G154200和TraesCS5D02G536500与低磷胁迫相关酶类基因家族有关;TraesCS1D02G231200与植物DUF 538结构域蛋白有关,是植物胁迫相关调控蛋白候选基因。     

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。     

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。     

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。     

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。     

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。     

水稻苗期抗稻瘟病基因全基因组关联分析

含抗性基因的水稻品种易被病原菌克服,因此为进一步发掘新的稻瘟病抗性基因,利用水稻多样性群体Ⅱ(RDP-Ⅱ)中的470份种质资源,在湖南省桃江县稻瘟病高发区的自然病圃中进行水稻苗期的抗病性鉴定,并通过全基因组关联分析(GWAS)鉴定稻瘟病的抗性相关位点,最终鉴定出25份苗期抗性较好的品种,可作为抗性育种材料。采用混合线性模型(MLM)对700 000个单核苷酸多态性(SNP)基因型和苗期的稻瘟病表型数据进行GWAS研究,在水稻基因组中鉴定了24个抗性关联位点,除4号和7号染色体外,在其余10条染色体上均有分布。在这些关联位点中,5个位点包含已克隆或定位的6个稻瘟病基因,其余19个位点是新的抗性位点。此外,通过对水稻亚群抗性规律分析发现,热带粳稻亚群的平均抗性水平最高,温带粳稻亚群的平均抗性水平最低。这些研究结果为分子辅助抗稻瘟病育种提供了分子标记,也为后续抗稻瘟病基因的克隆提供了基因组定位信息。     

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。     

复杂疾病的遗传易感基因区域的精细定位

以单核苷酸多态性(Single-nucleotide polymorphism, SNP)为遗传标记, 采用全基因组关联研究(Genome-wide association studies, GWAS)的策略, 已经在660多种疾病(或性状)中发现了3800多个遗传易感基因区域。但是, 其中最显著关联的遗传变异或致病性的遗传变异位点及其生物学功能并不完全清楚。这些位点的鉴定有助于阐明复杂疾病的生物学机制, 以及发现新的疾病标记物。后GWAS时代的主要任务之一就是通过精细定位研究找到复杂疾病易感基因区域内最显著关联的易感位点或致病性的易感位点并阐明其生物学功能。针对常见变异, 可通过推断或重测序增加SNP密度, 寻找最显著关联的SNP位点, 并通过功能元件分析、表达数量性状位点(Expression quantitative trait locus, eQTL)分析和单体型分析等方法寻找功能性的SNP位点和易感基因。针对罕见变异, 则可采用重测序、罕见单体型分析、家系分析和负荷检验等方法进行精细定位。文章对这些策略和所面临的问题进行了综述。     

羊重要性状全基因组关联分析研究进展

全基因组关联分析(genome-wide association study, GWAS)是一种复杂性状功能基因鉴定的分析策略,已成为挖掘畜禽重要经济性状候选基因的重要手段。随着绵羊和山羊基因组完成和公布,以及不同密度的SNP (single nucleotide polymorphism)芯片的推出并进行商业化推广,不仅大大丰富了羊标记辅助选择可利用的分子标记,而且还为开展重要性状的分子机理的探索提供了重要技术支撑。本文主要针对羊角、羊毛、羊奶、生长发育、肉质、繁殖和疾病等重要性状的GWAS研究所用的群体、主要研究方法和研究结果进行了综述,并对GWAS方法研究现状进行了归纳,以期为进一步利用GWAS进行羊的各种性状的遗传基础研究提供参考。     

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 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.

     

Genome-wide association mapping reveals key genomic regions for physiological and yield-related traits under salinity stress in wheat (Triticum aestivum L.)

A genome-wide association study (GWAS) was conducted using six different multi-locus GWAS models and 35K SNP array to demarcate genomic regions underlying reproductive stage salinity tolerance. Marker-trait association analysis was performed for salt tolerance indices (STI) of 11 morpho-physiological traits, and the actual concentrations of Na⁺ and K⁺, and the Na⁺/K⁺ ratio in flag leaf. A total of 293 significantly associated quantitative trait nucleotides (QTNs) for 14 morpho-physiological traits were identified. Of these 293 QTNs, 12 major QTNs with R² ≥ 10.0% were detected in three or more GWAS models. Novel major QTNs were identified for plant height, number of effective tillers, biomass, grain yield, thousand grain weight, Na⁺ and K⁺ content, and the Na⁺/K⁺ ratio in flag leaf. Moreover, 48 candidate genes were identified from the associated genomic regions. The QTNs identified in this study could potentially be targeted for improving salinity tolerance in wheat.     

Control of sodium transport in durum wheat

In many species, salt sensitivity is associated with the accumulation of sodium (Na(+)) in photosynthetic tissues. Na(+) uptake to leaves involves a series of transport steps and so far very few candidate genes have been implicated in the control of these processes. In this study, Na(+) transport was compared in two varieties of durum wheat (Triticum turgidum) L. subsp. durum known to differ in salt tolerance and Na(+) accumulation; the relatively salt tolerant landrace line 149 and the salt sensitive cultivar Tamaroi. Genetic studies indicated that these genotypes differed at two major loci controlling leaf blade Na(+) accumulation (R. Munns, G.J. Rebetzke, S. Husain, R.A. James, R.A. Hare [2003] Aust J Agric Res 54: 627-635). The physiological traits determined by these genetic differences were investigated using measurements of unidirectional (22)Na(+) transport and net Na(+) accumulation. The major differences in Na(+) transport between the genotypes were (1) the rate of transfer from the root to the shoot (xylem loading), which was much lower in the salt tolerant genotype, and (2) the capacity of the leaf sheath to extract and sequester Na(+) as it entered the leaf. The genotypes did not differ significantly in unidirectional root uptake of Na(+) and there was no evidence for recirculation of Na(+) from shoots to roots. It is likely that xylem loading and leaf sheath sequestration are separate genetic traits that interact to control leaf blade Na(+).     

Genome-Wide Association Study for Wool Production Traits in a Chinese Merino Sheep Population

Genome-wide association studies (GWAS) provide a powerful approach for identifying quantitative trait loci without prior knowledge of location or function. To identify loci associated with wool production traits, we performed a genome-wide association study on a total of 765 Chinese Merino sheep (JunKen type) genotyped with 50 K single nucleotide polymorphisms (SNPs). In the present study, five wool production traits were examined: fiber diameter, fiber diameter coefficient of variation, fineness dispersion, staple length and crimp. We detected 28 genome-wide significant SNPs for fiber diameter, fiber diameter coefficient of variation, fineness dispersion, and crimp trait in the Chinese Merino sheep. About 43% of the significant SNP markers were located within known or predicted genes, including YWHAZ, KRTCAP3, TSPEAR, PIK3R4, KIF16B, PTPN3, GPRC5A, DDX47, TCF9, TPTE2, EPHA5 and NBEA genes. Our results not only confirm the results of previous reports, but also provide a suite of novel SNP markers and candidate genes associated with wool traits. Our findings will be useful for exploring the genetic control of wool traits in sheep.     

小麦矮秆突变体jm22d响应赤霉素处理的转录组学分析

为拓宽小麦矮秆遗传资源,利用γ射线辐照济麦22获得了一个赤霉素不敏感型矮秆突变体jm22d。株高相关性状调查结果及茎秆细胞学试验显示,jm22d株高为53±1.8 cm,比野生型（WT）低约20 cm。jm22d整株茎秆共有4节,比WT少一节且各节间长度显著小于WT。与WT相比,jm22d茎秆细胞长度缩短。赤霉素含量测定发现,jm22d叶片中赤霉素含量高于WT,而茎秆中赤霉素含量低于WT（P<0.01）,因此,jm22d株高降低与赤霉素转运途径出现异常有关。为了深入研究jm22d对赤霉素的响应机理,对jm22d和WT幼苗进行赤霉素处理,分别收取处理0（D0）、1（D1）和3 d（D3）的样品进行转录组学分析。结果表明,与WT相比,在jm22d中共筛选到696个上调和1 067个下调的表达基因,其中62个和349个基因在3个时间点分别表现为上调和下调表达。叶绿素含量测定表明,jm22d中叶绿素含量随赤霉素处理时间的延长而降低,聚类分析结果表明,差异表达基因主要富集在光合作用-天线蛋白（photosynthesis-antenna proteins,ko00196）、卟啉和叶绿素代谢（porphyrin and chlorophyll metabolism,ko00860）、亚油酸新陈代谢（linoleic acid metabolism,ko00591）等通路,因此赤霉素处理对jm22d体内叶绿素含量的积累具有抑制作用。通过KEGG分析在植物激素信号转导途径中挖掘到5个差异表达基因（TraesCS2B01G582300、TraesCS2B01G600800、TraesCS2B01G556600、TraesCS2B01G630000和TraesCS6B01G439600）参与生长素、细胞分裂素等激素代谢途径,这些基因在jm22d中显著下调,这可能是jm22d矮化的重要原因。研究结果为矮秆突变体矮化机制的解析提供了重要参考。     

Multi-locus genome-wide association studies reveal novel genomic regions associated with vegetative stage salt tolerance in bread wheat (Triticum aestivum L.)

Soil salinity is one of the typical abiotic stresses affecting sustainability of wheat production worldwide. In the present study, we performed a 35 K SNP genotyping assay on association panel of 135 diverse wheat genotypes evaluated for vegetative stage tolerance in hydroponics. Association analyses using five multi-locus GWAS models revealed 42 reliable QTNs for 10 salt tolerance associated traits. Among these 42 reliable QTNs, 9, 17 and 16 QTNs were associated with physiological, biomass and shoot ionic traits respectively. Novel major QTNs were identified for chlorophyll content, shoot fresh weight, seedling total biomass, Na⁺ and K⁺ concentration and Na⁺/K⁺ ratio in shoots. Further, 10 major QTNs showed significant effect on the corresponding salt tolerance traits. Gene ontology analysis of the associated genomic regions identified 58 candidate genes. The information generated in this study will be of potential value for improvement of salt tolerance of wheat cultivars using marker assisted selection.