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47 results on '"Cai, Zhandong"'

4. Identification of quantitative trait loci for lodging and related agronomic traits in soybean (Glycine max [L.] Merr.)

Author

Chen, Bo, primary, Chai, Cheng, additional, Duan, Mingming, additional, Yang, Ximeng, additional, Cai, Zhandong, additional, Jia, Jia, additional, Xia, Qiuju, additional, Luo, Shilin, additional, Yin, Lu, additional, Li, Yunxia, additional, Huang, Nianen, additional, Ma, Qibin, additional, Nian, Hai, additional, and Cheng, Yanbo, additional

Published
2024
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45. Identification and Mapping of Stable QTLs for Seed Oil and Protein Content in Soybean [Glycine max(L.) Merr.]

Author

Huang, Jinghua, Ma, Qibin, Cai, Zhandong, Xia, Qiuju, Li, Shuxian, Jia, Jia, Chu, Li, Lian, Tengxiang, Nian, Hai, and Cheng, Yanbo

Abstract

This research aimed to identify stable quantitative trait loci (QTL) associated with oil and protein content in soybean. A population of 196 recombinant inbred lines (RILs) derived from Huachun 2 × Wayao was used to evaluate these target traits. A high-density genetic linkage map was constructed by using high-throughput genome-wide sequencing technology, which contained 3413 recombination bin markers and spanned 5400.4 cM with an average distance of 1.58 cM between markers. Eighteen stable QTLs controlling oil and protein content were detected. Among them, qOil-11-1was identified for the first time as a novel QTL, while qOil-5-1, qPro-10-1, and qPro-14-1were strong and stable QTLs with high log-likelihood (LOD) values. Sixteen differentially expressed genes (DEGs) within these four QTLs were shown to be highly expressed during seed development based on RNA sequencing (RNA-seq) data analysis. Our results may contribute toward gene mining and marker-assisted selection (MAS) for breeding a high-quality soybean in the future.

Published
2020
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46. Fine-mapping of QTLs for individual and total isoflavone content in soybean (<italic>Glycine max L.</italic>) using a high-density genetic map.

Author

Cai, Zhandong, Cheng, Yanbo, Ma, Zhuwen, Liu, Xinguo, Ma, Qibin, Xia, Qiuju, Zhang, Gengyun, Mu, Yinghui, and Nian, Hai

Subjects
CROP genetics, SOYBEAN, GENE mapping, NUCLEOTIDE sequencing, ISOFLAVONES, GLYCINE (Plants)
Abstract

Key message: Fifteen stable QTLs were identified using a high-density soybean genetic map across multiple environments. One major QTL, qIF5-1, contributing to total isoflavone content explained phenotypic variance 49.38, 43.27, 46.59, 45.15 and 52.50%, respectively.Abstract: Soybeans (Glycine max L.) are a major source of dietary isoflavones. To identify novel quantitative trait loci (QTL) underlying isoflavone content, and to improve the accuracy of marker-assisted breeding in soybean, a valuable mapping population comprised of 196 F7:8–10 recombinant inbred lines (RILs, Huachun 2 × Wayao) was utilized to evaluate individual and total isoflavone content in plants grown in four different environments in Guangdong. A high-density genetic linkage map containing 3469 recombination bin markers based on 0.2 × restriction site-associated DNA tag sequencing (RAD-seq) technology was used to finely map QTLs for both individual and total isoflavone contents. Correlation analyses showed that total isoflavone content, and that of five individual isoflavone, was significantly correlated across the four environments. Based on the high-density genetic linkage map, a total of 15 stable quantitative trait loci (QTLs) associated with isoflavone content across multiple environments were mapped onto chromosomes 02, 05, 07, 09, 10, 11, 13, 16, 17, and 19. Further, one of them, qIF5-1, localized to chromosomes 05 (38,434,171–39,045,620 bp) contributed to almost all isoflavone components across all environments, and explained 6.37–59.95% of the phenotypic variance, especially explained 49.38, 43.27, 46.59, 45.15 and 52.50% for total isoflavone. The results obtained in the present study will pave the way for a better understanding of the genetics of isoflavone accumulation and reveals the scope available for improvement of isoflavone content through marker-assisted selection. [ABSTRACT FROM AUTHOR]

Published
2018
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