QTL mapping for soybean (Glycine max L.) leaf chlorophyll-content traits in a genotyped RIL population by using RAD-seq based high-density linkage map.
QTL mapping for soybean (Glycine max L.) leaf chlorophyll-content traits in a genotyped RIL population by using RAD-seq based high-density linkage map.
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DOI:
10.1186/s12864-020-07150-4
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发表时间:
2020-10-23
期刊:
影响因子:
4.4
通讯作者:
Nian H
中科院分区:
文献类型:
--
作者:
Wang L;Conteh B;Fang L;Xia Q;Nian H
Different soybean (Glycine max L.) leaf chlorophyll-content traits are considered to be significantly linked to soybean yield. To map the quantitative trait loci (QTLs) of soybean leaf chlorophyll-content traits, an advanced recombinant inbred line (RIL, ZH, Zhonghuang 24 × Huaxia 3) population was adopted to phenotypic data acquisitions for the target traits across six distinct environments (seasons and soybean growth stages). Moreover, the restriction site-associated DNA sequencing (RAD-seq) based high-density genetic linkage map of the RIL population was utilized for QTL mapping by carrying out the composite interval mapping (CIM) approach. Correlation analyses showed that most traits were correlated with each other under specific chlorophyll assessing method and were regulated both by hereditary and environmental factors. In this study, 78 QTLs for soybean leaf chlorophyll-content traits were identified. Furthermore, 13 major QTLs and five important QTL hotspots were classified and highlighted from the detected QTLs. Finally, Glyma01g15506, Glyma02g08910, Glyma02g11110, Glyma07g15960, Glyma15g19670 and Glyma15g19810 were predicted from the genetic intervals of the major QTLs and important QTL hotspots. The detected QTLs and candidate genes may facilitate to gain a better understanding of the hereditary basis of soybean leaf chlorophyll-content traits and may be valuable to pave the way for the marker-assisted selection (MAS) breeding of the target traits. Supplementary information accompanies this paper at 10.1186/s12864-020-07150-4.
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影响因子:
4.4
作者:
Delourme R;Falentin C;Fomeju BF;Boillot M;Lassalle G;André I;Duarte J;Gauthier V;Lucante N;Marty A;Pauchon M;Pichon JP;Ribière N;Trotoux G;Blanchard P;Rivière N;Martinant JP;Pauquet J
通讯作者:
Pauquet J
影响因子:
3
作者:
Carter, GA;Knapp, AK
通讯作者:
Knapp, AK
影响因子:
4.4
作者:
Jiang, Bingzhi;Cheng, Yanbo;Nian, Hai
通讯作者:
Nian, Hai
影响因子:
2.4
作者:
Hu Z;Zhang D;Zhang G;Kan G;Hong D;Yu D
通讯作者:
Yu D
影响因子:
3.7
作者:
Elshire RJ;Glaubitz JC;Sun Q;Poland JA;Kawamoto K;Buckler ES;Mitchell SE
通讯作者:
Mitchell SE