Investigating Drought Tolerance in Chickpea Using Genome-Wide Association Mapping and Genomic Selection Based on Whole-Genome Resequencing Data

被引:160
|
作者
Li, Yongle [1 ]
Ruperao, Pradeep [2 ]
Batley, Jacqueline [3 ,4 ,5 ]
Edwards, David [3 ,4 ,5 ]
Khan, Tanveer [4 ,5 ]
Colmer, Timothy D. [4 ,5 ]
Pang, Jiayin [4 ,5 ]
Siddique, Kadambot H. M. [4 ,5 ]
Sutton, Tim [1 ,6 ]
机构
[1] Univ Adelaide, Sch Agr Food & Wine, Adelaide, SA, Australia
[2] Univ Queensland, Sch Agr & Food Sci, Brisbane, Qld, Australia
[3] Univ Western Australia, Sch Biol Sci, Perth, WA, Australia
[4] Univ Western Australia, UWA Inst Agr, Perth, WA, Australia
[5] Univ Western Australia, UWA Sch Agr & Environm, Perth, WA, Australia
[6] South Australian Res & Dev Inst, Adelaide, SA, Australia
来源
FRONTIERS IN PLANT SCIENCE | 2018年 / 9卷
关键词
drought tolerance; genome-wide association mapping; genomic selection; chickpea; whole-genome resequencing; auxin; CICER-ARIETINUM L; TERMINAL DROUGHT; GENETIC ARCHITECTURE; PHOTOTROPIC RESPONSE; PLANT DEVELOPMENT; SEED DEVELOPMENT; AUXIN; ARABIDOPSIS; PREDICTION; TRAITS;
D O I
10.3389/fpls.2018.00190
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought tolerant varieties. Using a whole-genome resequencing approach, we sequenced 132 chickpea varieties and advanced breeding lines and found more than 144,000 single nucleotide polymorphisms (SNPs). We measured 13 yield and yield-related traits in three drought-prone environments of Western Australia. The genotypic effects were significant for all traits, and many traits showed highly significant correlations, ranging from 0.83 between grain yield and biomass to -0.67 between seed weight and seed emergence rate. To identify candidate genes, the SNP and trait data were incorporated into the SUPER genome-wide association study (GWAS) model, a modified version of the linear mixed model. We found that several SNPs from auxin-related genes, including auxin efflux carrier protein (PIN3), p-glycoprotein, and nodulin MtN21/EamA-like transporter, were significantly associated with yield and yield-related traits under drought-prone environments. We identified four genetic regions containing SNPs significantly associated with several different traits, which was an indication of pleiotropic effects. We also investigated the possibility of incorporating the GWAS results into a genomic selection (GS) model, which is another approach to deal with complex traits. Compared to using all SNPs, application of the GS model using subsets of SNPs significantly associated with the traits under investigation increased the prediction accuracies of three yield and yield-related traits by more than twofold. This has important implication for implementing GS in plant breeding programs.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Genomic Selection for Drought Tolerance Using Genome-Wide SNPs in Maize
    Shikha, Mittal
    Kanika, Arora
    Rao, Atmakuri Ramakrishna
    Mallikarjuna, Mallane Gowdra
    Gupta, Hari Shanker
    Nepolean, Thirunavukkarasu
    FRONTIERS IN PLANT SCIENCE, 2017, 8
  • [2] Genome-wide analysis of CNVs in three populations of Tibetan sheep using whole-genome resequencing
    Hu, Linyong
    Zhang, Liangzhi
    Li, Qi
    Liu, Hongjin
    Xu, Tianwei
    Zhao, Na
    Han, Xueping
    Xu, Shixiao
    Zhao, Xinquan
    Zhang, Cunfang
    FRONTIERS IN GENETICS, 2022, 13
  • [3] First genome-wide association study and genomic prediction for growth traits in spotted sea bass (Lateolabrax maculatus) using whole-genome resequencing
    Zhang, Chong
    Wen, Haishen
    Zhang, Yonghang
    Zhang, Kaiqiang
    Qi, Xin
    Li, Yun
    AQUACULTURE, 2023, 566
  • [4] Whole-Genome Resequencing Analysis of Hanwoo and Yanbian Cattle to Identify Genome-Wide SNPs and Signatures of Selection
    Choi, Jung-Woo
    Choi, Bong-Hwan
    Lee, Seung-Hwan
    Lee, Seung-Soo
    Kim, Hyeong-Cheol
    Yu, Dayeong
    Chung, Won-Hyong
    Lee, Kyung-Tai
    Chai, Han-Ha
    Cho, Yong-Min
    Lim, Dajeong
    MOLECULES AND CELLS, 2015, 38 (05) : 466 - 473
  • [5] Genome-wide association and genomic selection in animal breeding
    Hayes, Ben
    Goddard, Mike
    GENOME, 2010, 53 (11) : 876 - 883
  • [6] Genetic Dissection of Drought and Heat Tolerance in Chickpea through Genome-Wide and Candidate Gene-Based Association Mapping Approaches
    Thudi, Mahendar
    Upadhyaya, Hari D.
    Rathore, Abhishek
    Gaur, Pooran Mal
    Krishnamurthy, Lakshmanan
    Roorkiwal, Manish
    Nayak, Spurthi N.
    Chaturvedi, Sushil Kumar
    Basu, Partha Sarathi
    Gangarao, N. V. P. R.
    Fikre, Asnake
    Kimurto, Paul
    Sharma, Prakash C.
    Sheshashayee, M. S.
    Tobita, Satoshi
    Kashiwagi, Junichi
    Ito, Osamu
    Killian, Andrzej
    Varshney, Rajeev Kumar
    PLOS ONE, 2014, 9 (05):
  • [7] Whole-genome resequencing of grass carp (Ctenopharyngodon idella) for genome-wide association study on GCRV resistance
    Yu, Chengchen
    Jiang, Yuchen
    Zhang, Chenyang
    Wu, Minglin
    Gui, Lang
    Xu, Xiaoyan
    Li, Jiale
    Shen, Yubang
    AQUACULTURE, 2024, 592
  • [8] A genome-wide association study of heat tolerance in Pacific abalone based on genome resequencing
    Yu, Feng
    Peng, Wenzhu
    Tang, Bin
    Zhang, Yifang
    Wang, Yi
    Gan, Yang
    Luo, Xuan
    You, Weiwei
    Gwo, Jin-Chywan
    Chen, Nan
    Ke, Caihuan
    AQUACULTURE, 2021, 536
  • [9] Genome-Wide Scan for Genetic Signatures Based on the Whole-Genome Resequencing of Salt- and Drought-Tolerant Rice Varieties
    Jiang, Conghui
    Wang, Yulong
    Zhou, Jinjun
    Rashid, Muhammad Abdul Rehman
    Li, Yaping
    Peng, Yongbin
    Xie, Lixia
    Zhou, Guanhua
    He, Yanan
    Sun, Wei
    Zheng, Chongke
    Xie, Xianzhi
    AGRONOMY-BASEL, 2023, 13 (07):
  • [10] Identification of candidate genes for drought tolerance by whole-genome resequencing in maize
    Jie Xu
    Yibing Yuan
    Yunbi Xu
    Gengyun Zhang
    Xiaosen Guo
    Fengkai Wu
    Qi Wang
    Tingzhao Rong
    Guangtang Pan
    Moju Cao
    Qilin Tang
    Shibin Gao
    Yaxi Liu
    Jing Wang
    Hai Lan
    Yanli Lu
    BMC Plant Biology, 14