2019
DOI: 10.1007/s00425-019-03164-9
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Genome-wide association study and quantitative trait loci mapping of seed dormancy in common wheat (Triticum aestivum L.)

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Cited by 27 publications
(21 citation statements)
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“…The colocation between seed dormancy and seed longevity had been reported in several studies (Börner et al, ; Singh et al, ). Utilizing the same population, several loci associated with seed dormancy were reported on chromosome 3DS ( Qgr.cas‐3DS.1 ), 4A ( Qgr.cas‐4A ), 5Al ( Qgr.cas‐5Al.1 , Qgr.cas‐5Al.2 ) and 6AS ( Qgr.cas‐6AS ) in our previous study (Zuo et al, ), and those loci were overlapped with QlgGR.cas‐3D.1 , QlgGR.cas‐3D.2 , QlgGR.cas‐4A.2 , QlgGR.cas‐5A.1 , QlgGR.cas‐5A.2 and QlgGR.cas‐6A.1 in the present study (Table S5). Besides, QlgGR.cas‐1A and QlgGR.cas‐2B.2 were close to seed dormancy‐related loci Qphs.usask‐1A (Singh et al, ) and MPHS.ipk‐2B (Lohwasser, Rehman Arif, & Börner, ).…”
Section: Discussionmentioning
confidence: 72%
“…The colocation between seed dormancy and seed longevity had been reported in several studies (Börner et al, ; Singh et al, ). Utilizing the same population, several loci associated with seed dormancy were reported on chromosome 3DS ( Qgr.cas‐3DS.1 ), 4A ( Qgr.cas‐4A ), 5Al ( Qgr.cas‐5Al.1 , Qgr.cas‐5Al.2 ) and 6AS ( Qgr.cas‐6AS ) in our previous study (Zuo et al, ), and those loci were overlapped with QlgGR.cas‐3D.1 , QlgGR.cas‐3D.2 , QlgGR.cas‐4A.2 , QlgGR.cas‐5A.1 , QlgGR.cas‐5A.2 and QlgGR.cas‐6A.1 in the present study (Table S5). Besides, QlgGR.cas‐1A and QlgGR.cas‐2B.2 were close to seed dormancy‐related loci Qphs.usask‐1A (Singh et al, ) and MPHS.ipk‐2B (Lohwasser, Rehman Arif, & Börner, ).…”
Section: Discussionmentioning
confidence: 72%
“…Qphs.caas-4AL , as a stable QTL, accounted for 4.6–10.6% of the phenotypic variances. Although quite a few QTL for wheat PHS resistance on chromosome 4A have also been reported (Kato et al, 2001 ; Mares et al, 2005 ; Torada et al, 2005 ; Imtiaz et al, 2008 ; Rasul et al, 2009 ; Singh et al, 2010 ; Kulwal et al, 2012 ; Cabral et al, 2014 ; Jiang et al, 2015 ; Cao et al, 2016 ; Zhou et al, 2017 ; Martinez et al, 2018 ; Zuo et al, 2019 ; Liton et al, 2021 ), Qphs.caas-4AL appears to be unique based on genetic mapping and physical locations of the flanking SNPs according to IWGSC RefSeq 1.0 ( Supplementary Table 9 ). QTL pyramiding plays an important role in breeding, and resistance allele combinations of QTL for PHS have been reported previously (Imtiaz et al, 2008 ; Shao et al, 2018 ; Liton et al, 2021 ).…”
Section: Discussionmentioning
confidence: 88%
“…其产量与品质备受关注 [1][2] 。近年来, 随着全球气候 变暖以及极端天气频发, 小麦成熟至收获期间穗上 发芽现象越发频繁, 严重降低小麦产量, 劣化小麦 品质, 穗发芽已成为全球性危害 [3] 。穗发芽促使籽粒 内部水解酶活性增加, 籽粒内部储藏物质被分解消 耗, 从而造成籽粒容重和千粒重下降, 导致小麦减 产 [4] 。同时, 由于蛋白质被降减, 小麦制粉后的 SDS 沉降值和面筋含量逐渐降低, 用发芽小麦粉加工的 面制品如馒头、面包等, 外形和口感较差, 严重影响 其营养品质和加工品质 [5][6] 。全球每年因穗发芽而造 成的直接经济损失约 10 亿美元 [7] 。培育抗穗发芽小 麦新品种是解决这一问题最有效的途径之一。 小麦穗发芽是受种子休眠水平、种子结构、种 皮颜色等内部因素以及温度、湿度、光照等外界环 境因素共同作用的结果 [8][9] 。种子的休眠特性是影响 小麦穗发芽抗性的主要遗传因素 [10] 。目前对于小麦 穗发芽鉴定的方法主要有籽粒发芽法、整穗发芽法 和 α-淀粉酶活性测定法 [10] 。籽粒发芽主要反映小麦 籽粒的休眠情况, 并不能表现出颖壳、麦芒等抑制 物的作用 [10] 。α-淀粉酶活性测定可以鉴定胚乳抑制 物对穗发芽的影响, 但操作复杂, 不适合进行批量 化测定 [11] 。整穗发芽不仅能综合性反映小麦穗发芽 的抗性, 而且操作简单, 适合批量化测定, 因此常 用来鉴定小麦的穗发芽抗性。测定小麦整穗发芽常 用的方法有沙培法、发芽纸发芽法、塑料袋保湿法、 模拟降雨法、纱布保湿法等 [11][12] 。 小麦穗发芽是受多基因调控的数量性状, 存在 微效和主效基因 [13] 。连锁分析与全基因组关联分析目 前已成为数量性状基因定位和挖掘的重要途径 [14] 。许 多研究通过双单倍体(doubled haploid, DH)或重组自 交系(recombinant inbred lines, RIL)等人工作图群体, 将穗发芽相关基因定位于 2AL、2BS、3AS、3AL、 4AL、5D、6BS 及 7DL 染色体上 [14][15][16][17][18][19][20] 。但连锁作图 受限于遗传群体亲本间的差异度及标记密度等的不 同, QTL 定位的区间较大, 仅能分析部分等位基因。 全基因组关联分析(genome-wide association study, GWAS)与连锁分析互补, 可以高效定位和挖掘多个 小麦穗发芽相关的优异等位基因 [10] 。Kulwal 等 [21] 利用 1166 个简单序列重复(simple sequence repeat, SSR)和多样性芯片(diversity arrays technology, DArT) 分子标记, 对 208 份白皮冬小麦品种 4 年的穗发芽 率进行测定, 定位了8个与穗发芽相关的数量性状 基因座(quantitative trait locus, QTL), 分布在 1BS、 2DS、4AL、6DL、7BS 和 7DS 染色体上, 并证实了 7BS 是新的 QTL 位点。 Jaiswal 等 [22] 通过对 242 份普 通小麦的穗发芽率进行鉴定, 并结合 250 个 SSR 标 记对穗发芽性状进行 QTL 分析, 发现了 30 个小麦穗 发芽抗性相关的主效位点, 其中仅有 8 个标记位点 与前人研究结果相同, 其余 22 个标记位点均处在前 人未报道的染色体区域。Lin 等 [23] 首次使用 9K 和 90K 单核苷酸多态性(single nucleotide polymorphism, SNP)基因芯片对 155 份美国冬小麦品种(系)的穗发芽 率进行全基因组关联分析, 共检测到 12 个与穗发芽相 关的 QTL, 其中 3AS、3AL、3B、4AL 和 7A 是 QTL 分布频率较大的区域。Zhu 等 [24] 利用 90K SNP 基因芯 片对 192 份小麦品种(系)的穗发芽率进行全基因组关联 分析, 检测到 23 个显著关联位点, 解释了 6.0%~18.9% 的表型变异, 其中 1A、3B 和 6B 是抗性位点的热点区 域。Zuo 等 [25] 对周 8425B×中国春重组自交系群体家系…”
Section: 小麦是我国乃至世界最重要的粮食作物之一unclassified