scholarly journals Pedigree-based genetic dissection of quantitative loci for seed quality and yield characters in improved soybean

2021 ◽  
Vol 41 (2) ◽  
Author(s):  
Wenxuan Huang ◽  
Jingjing Hou ◽  
Quan Hu ◽  
Jie An ◽  
Yanwei Zhang ◽  
...  

AbstractAs soybean plays an indispensable role in the supply of vegetable oil and protein, balancing the relationship between seed quality and yield traits according to human demand has become an important breeding goal for soybean improvement. Here, 256 intraspecific recombinant inbred lines (RILs), derived from a cross between Qi Huang No.34 (QH34) and Ji Dou No.17 (JD17), were used for quantitative trait loci (QTLs) mapping with remarkable four chemical and physical properties with a purpose for exploring the distribution of excellent alleles in germplasm resources in China. A total of 25 QTLs were detected, of which 10 QTLs inherited the alleles from the parent QH34. Pedigree research on favorable alleles on these QTLs showed the process of excellent alleles pyramided into QH34. Meta-analysis of the 25 QTLs by comparing with existed QTLs in previous study identified 17 novel QTLs. QTLs with pleiotropic effects have been detected. Furthermore, three representative elite recombinant inbred lines in different locations that have great potential in soybean breeding were selected, and finally, four seed weight-related candidate genes were identified. The discovery of these QTLs provides a new guidance for combining the diversity and rarity of germplasm resources, which can effectively increase population genetic diversity and broaden genetic basis of varieties.

2019 ◽  
Vol 39 (3) ◽  
Author(s):  
Caiyun Liu ◽  
Sivakumar Sukumaran ◽  
Etienne Claverie ◽  
Carolina Sansaloni ◽  
Susanne Dreisigacker ◽  
...  

Euphytica ◽  
2016 ◽  
Vol 210 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Xian-Qun Huang ◽  
Tuan Huang ◽  
Guo-Zuo Hou ◽  
Li Li ◽  
Yan Hou ◽  
...  

Euphytica ◽  
2006 ◽  
Vol 155 (1-2) ◽  
pp. 117-124 ◽  
Author(s):  
Tang Ji-hua ◽  
Teng Wen-tao ◽  
Yan Jian-bing ◽  
Ma Xi-qing ◽  
Meng Yi-jiang ◽  
...  

Genetics ◽  
2006 ◽  
Vol 174 (3) ◽  
pp. 1671-1683 ◽  
Author(s):  
Yan Fu ◽  
Tsui-Jung Wen ◽  
Yefim I. Ronin ◽  
Hsin D. Chen ◽  
Ling Guo ◽  
...  

2004 ◽  
Vol 54 (4) ◽  
pp. 399-407 ◽  
Author(s):  
Satoshi Watanabe ◽  
Teuku Tajuddin ◽  
Naoki Yamanaka ◽  
Masaki Hayashi ◽  
Kyuya Harada

Genome ◽  
2008 ◽  
Vol 51 (8) ◽  
pp. 599-615 ◽  
Author(s):  
A. Ebrahimi ◽  
P. Maury ◽  
M. Berger ◽  
S. Poormohammad Kiani ◽  
A. Nabipour ◽  
...  

The objectives of the present research were to determine the effects of water stress on seed-quality traits and to map QTLs controlling the studied traits under two different water treatments in a population of sunflower recombinant inbred lines (RILs). Two experiments were conducted in greenhouse and field conditions, each with well-watered and water-stressed treatments. The experiments consisted of a split-plot design (water treatment and RIL) with three blocks. Analyses of variance showed significant variation among genotypes, and a water treatment × genotype interaction was also observed for most of the traits. Two to 15 QTLs were found, depending on trait and growth conditions, and the percentage of phenotypic variance explained by the QTLs ranged from 5% to 31%. Several QTLs for oil content overlapped with QTLs for palmitic and stearic acid contents in all four conditions. An overlapping region on linkage group 3 (QTLs 2.OC.3.1 and 4.SA.3.1) was linked to an SSR marker (ORS657). A principal component analysis was performed on four fatty acid traits. Two principal components, P1 and P2, were used for QTL analysis. This method improved the ability to identify chromosomal regions affecting the fatty acids. We also detected the principal-component QTLs that did not overlap with the fatty acid QTLs. The results highlight genomic regions of interest in marker-based breeding programmes for increasing oil content in sunflower.


2021 ◽  
Vol 41 (12) ◽  
Author(s):  
Quan Hu ◽  
Yanwei Zhang ◽  
Ruirui Ma ◽  
Jie An ◽  
Wenxuan Huang ◽  
...  

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