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QTL mapping for agronomic traits using multi-parent advanced generation inter-cross (MAGIC) populations derived from diverse elite indica rice lines

机译:利用来自不同diverse稻优良品系的多亲本代杂交(MAGIC)群体对农艺性状进行QTL定位

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In rice many QTL have been reported for yield and related traits using various bi-parental mapping populations. However, few of the well characterized genes/QTL have been successfully used in breeding for improved trait performance. One of the reasons is that the mapping populations used are irrelevant to breeding. Association mapping has also been used in identifying marker-trait associations that are effective in more complex background. However, the results from association mapping using diversity panels are difficult to be exploited inbreeding, since most of the accessions had poor performance in many important agronomic traits. In this study, a genome-wide association study (GWAS) was performed using three multi-parent advanced generation inter-cross (MAGIC) populations derived from elite indica lines (DC1, DC2 and 8-way) to identify QTL for 14 traits including yield, yield components and other related traits. The three MAGIC populations were phenotyped in the dry season (DS) and wet season (WS) of 2014 at the headquarters of the International Rice Research Institute (IRRI) and genotyped with a Rice SNP chip containing 4,500 markers. A total of 26 QTL on all chromosomes except 7, 9 and 11 were identified for 10 traits in the DS or WS. Six, two, 12,10 and 20 out of the 26 QTL were identified in the DC1, DC2, 8-way, DC12 (DC1 + DC2) and RMPRIL (DC1 + DC2 + 8-way) populations, respectively. Nine of the QTL corresponded to known QTL/genes, including qFLW4 for FLW, qTGW3 and qTGW5 for TGW, qFGN4 for FGN, qSBN4 for SBN, qPH1.1 and qPH1.2 for PH, qHD3 and qHD6 for HD. All these nine QTL were identifiable using the RMPRIL population while only eight, seven, six and one could be identified using the 8-way, DC12, DC1 and DC2 populations, respectively. The 8-way population was more powerful than the DC1, DC2 and DC12 populations. The joint analysis, which combines different populations (e.g., DC12 and RMPRIL), increased the number of QTL identified and mapping resolution. The study showed that MAGIC populations derived from diverse elite parental lines can be used to detect QTL, which are ideal for linking gene identification and practical breeding. GWAS using such MAGIC populations had higher detection power (compared to assembled populations) and higher resolution (compared to biparental populations). The identified QTL are directly applicable, since the populations are good breeding populations as well. (C) 2016 Elsevier B.V. All rights reserved.
机译:在水稻中,使用各种双亲作图群体已经报道了许多QTL的产量和相关性状。但是,很少有特征明确的基因/ QTL成功用于育种以提高性状表现。原因之一是所使用的作图种群与育种无关。关联映射也已用于识别在更复杂的背景中有效的标记-性状关联。然而,由于大多数种质在许多重要的农艺性状上的表现较差,因此使用多样性面板进行关联作图的结果很难被用于近交。在这项研究中,使用源自in稻优良品系(DC1,DC2和8向)的三个多亲高级杂交(MAGIC)群体进行了全基因组关联研究(GWAS),以鉴定14个性状的QTL,包括产量,产量构成及其他相关性状。在国际水稻研究所(IRRI)总部于2014年的旱季(DS)和雨季(WS)对三个MAGIC种群进行了表型分析,并用包含4,500个标记的Rice SNP芯片进行了基因分型。在DS或WS中,除7、9和11外,所有染色体上共有26个QTL,鉴定出10个性状。在DC1,DC2、8路,DC12(DC1 + DC2)和RMPRIL(DC1 + DC2 + 8路)人群中分别确定了26个QTL中的六个,两个,12、10和20个。 QTL中的九个对应于已知的QTL /基因,包括FLW的qFLW4,TGW的qTGW3和qTGW5,FGN的qFGN4,SBN的qSBN4,PH的qPH1.1和qPH1.2,HD的qHD3和qHD6。使用RMPRIL群体可以识别所有这9个QTL,而分别使用8路,DC12,DC1和DC2群体则只能识别8、7、6和1个。 8路人口比DC1,DC2和DC12人口要强大。联合分析结合了不同的人群(例如DC12和RMPRIL),从而增加了识别出的QTL数量和作图分辨率。研究表明,来自多种优良亲本系的MAGIC群体可用于检测QTL,这对于将基因鉴定与实际育种联系起来是理想的。使用此类MAGIC种群的GWAS具有更高的检测能力(与集合种群相比)和更高的分辨率(与双亲种群相比)。所确定的QTL可直接应用,因为这些种群也是良好的繁殖种群。 (C)2016 Elsevier B.V.保留所有权利。

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