QTL-allele matrix detected from RTM-GWAS is a powerful tool for studies in genetics, evolution, and breeding by design of crops

doi:10.1016/S2095-3119(20)63199-9

Journal of Integrative Agriculture ›› 2020, Vol. 19 ›› Issue (5): 1407-1410.DOI: 10.1016/S2095-3119(20)63199-9

• 论文 • 上一篇

收稿日期:2020-01-08 出版日期:2020-04-01 发布日期:2020-03-25

QTL-allele matrix detected from RTM-GWAS is a powerful tool for studies in genetics, evolution, and breeding by design of crops

HE Jian-bo, GAI Jun-yi

Soybean Research Institute/National Center for Soybean Improvement, Ministry of Agriculture and Rural Affairs (MARA)/Key Laboratory of Biology and Genetic Improvement of Soybean (General), MARA/State Key Laboratory for Crop Genetics and Germplasm Enhancement/Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, P.R.China

Received:2020-01-08 Online:2020-04-01 Published:2020-03-25
Contact: Correspondence GAI Jun-yi, Tel/Fax: +86-25-84395405, E-mail: sri@njau.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (31701447), the National R&D Program of China (2016YFD0100201, 2016YFD0100304, 2017YFD0100500, and 2017YFD0102002), the 111 Project of Ministry of Education, China (B08025), the Program for Changjiang Scholars and Innovative Research Team in University, China (PCSIRT_17R55), the earmarked fund for China Agriculture Research System (CARS-04), the Fundamental Research Funds for the Central Universities, China (KYT201801), and the Jiangsu Collaborative Innovation Center for Modern Crop Production, China.

摘要/Abstract

. [J]. Journal of Integrative Agriculture, 2020, 19(5): 1407-1410.

HE Jian-bo, GAI Jun-yi.

QTL-allele matrix detected from RTM-GWAS is a powerful tool for studies in genetics, evolution, and breeding by design of crops

[J]. Journal of Integrative Agriculture, 2020, 19(5): 1407-1410.

Fu M, Wang Y, Ren H, Du W, Yang X, Wang D, Cheng Y, Zhao J, Gai J. 2020. Exploring the QTL-allele constitution of main stem node number and its differentiation among maturity groups in Northeast China soybean population. Crop Science, doi:10.1002/csc2.20024.
Gai J, Chen L, Zhang Y, Zhao T, Xing G, Xing H. 2012. Genome-wide genetic dissection of germplasm resources and implications for breeding by design in soybean. Breeding Science, 61, 495–510.
He J, Liu F, Xing G, Wang W, Zhao T, Guan R, Gai J. 2018. Characterization and analytical programs of the restricted two-stage multi-locus genome-wide association analysis. Acta Agronomica Sinica, 44, 1274–1289. (in Chinese)
He J, Meng S, Zhao T, Xing G, Yang S, Li Y, Guan R, Lu J, Wang Y, Xia Q, Yang B, Gai J. 2017. An innovative procedure of genome-wide association analysis fits studies on germplasm population and plant breeding. Theoretical and Applied Genetics, 130, 2327–2343.
Huang X, Han B. 2014. Natural variations and genome-wide association studies in crop plants. Annual Review of Plant Biology, 65, 531–551.
Li S, Cao Y, He J, Zhao T, Gai J. 2017. Detecting the QTL-allele system conferring flowering date in a nested association mapping population of soybean using a novel procedure. Theoretical and Applied Genetics, 130, 2297–2314.
Manolio T A, Collins F S, Cox N J, Goldstein D B, Hindorff L A, Hunter D J, McCarthy M I, Ramos E M, Cardon L R, Chakravarti A, Cho J H, Guttmacher A E, Kong A, Kruglyak L, Mardis E, Rotimi C N, Slatkin M, Valle D, Whittemore A S, Boehnke M, et al. 2009. Finding the missing heritability of complex diseases. Nature, 461, 747–753.
Meng S, He J, Zhao T, Xing G, Li Y, Yang S, Lu J, Wang Y, Gai J. 2016. Detecting the QTL-allele system of seed isoflavone content in Chinese soybean landrace population for optimal cross design and gene system exploration. Theoretical and Applied Genetics, 129, 1557–1576.
Pan L, He J, Zhao T, Xing G, Wang Y, Yu D, Chen S, Gai J. 2018. Efficient QTL detection of flowering date in a soybean RIL population using the novel restricted two-stage multi-locus GWAS procedure. Theoretical and Applied Genetics, 131, 2581–2599.
Price A L, Zaitlen N A, Reich D, Patterson N. 2010. New approaches to population stratification in genome-wide association studies. Nature Reviews Genetics, 11, 459–463.
Sul J H, Martin L S, Eskin E. 2018. Population structure in genetic studies: Confounding factors and mixed models. Plos Genetics, 14, e1007309.
Yang J, Bakshi A, Zhu Z, Hemani G, Vinkhuyzen A A, Lee S H, Robinson M R, Perry J R, Nolte I M, van Vliet-Ostaptchouk J V, Snieder H, The LifeLines Cohort Study, Esko T, Milani L, Magi R, Metspalu A, Hamsten A, Magnusson P K, Pedersen N L, Ingelsson E, et al. 2015. Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index. Nature Genetics, 47, 1114–1120.
Zhang Y, He J, Meng S, Liu M, Xing G, Li Y, Yang S, Yang J, Zhao T, Gai J. 2018a. Identifying QTL-allele system of seed protein content in Chinese soybean landraces for population differentiation studies and optimal cross predictions. Euphytica, 214, 157.
Zhang Y, He J, Wang H, Meng S, Xing G, Li Y, Yang S, Zhao J, Zhao T, Gai J. 2018b. Detecting the QTL-allele system of seed oil traits using multi-locus genome-wide association analysis for population characterization and optimal cross prediction in soybean. Frontiers in Plant Science, 9, 1793.

QTL-allele matrix detected from RTM-GWAS is a powerful tool for studies in genetics, evolution, and breeding by design of crops

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