Genome-wide Association Study and Candidate Gene Prediction for Plant Height in Wheat (Triticum aestivum)
CHE Zhuo1,2, WANG Peng1, TIAN Tian1, ZHANG Pei-Pei3, CHEN Tao1, LIU Yuan1, YANG De-Long1,3,*
1 College of Life Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; 2 Plant Seed Master Station of Gansu Province, Lanzhou 730070, China; 3 State Key Laboratory of Aridland Crop Science, Lanzhou 730070, China
Abstract：Plant height (PH) is one of the important agronomic traits in wheat (Triticum aestivum) and is highly correlated with wheat yield. In order to further illustrate the genetic basis of wheat PH, 132 wheat cultivars (lines) were phenotyped under 4 environmental conditions in this study, and genome-wide association analysis (GWAS) of PH was performed based on the mixed liner model (MLM) using a wheat 35K single nucleotide polymorphism (SNP) assay. The results showed that the phenotypic variation of wheat PH was significantly affected by environment and was significantly correlated with the environment, with a broad-sense heritability (h2B) of 0.60. A total of 22 SNPs significantly associated with PH (P≤0.001) were identified in this study, among which 7 SNPs were identified in 2 or 3 environments, which were stably associated SNPs and distributed on chromosomes 1A, 1B, 1D, 2D, and 4A. One to 3 stably associated SNPs identified on each chromosome, and a single stably associated SNP could explain 9.15%~15.07% of the phenotypic variation. 4 stably associated SNPs overlapped with reported QTLs for PH, and the remaining 3 stably associated SNPs were new loci probably. 265 genes in the 1 Mb interval upstream and downstream of the stably associated loci were analyzed for functional homology in rice (Oryza sativa), and 7 candidate genes were screened for possible effects on PH development. This study may provide new markers and genetic resources for wheat PH improvement.
车卓, 王鹏, 田甜, 张沛沛, 陈涛, 刘媛, 杨德龙. 小麦株高全基因组关联分析与候选基因预测[J]. 农业生物技术学报, 2024, 32(2): 259-272.
CHE Zhuo, WANG Peng, TIAN Tian, ZHANG Pei-Pei, CHEN Tao, LIU Yuan, YANG De-Long. Genome-wide Association Study and Candidate Gene Prediction for Plant Height in Wheat (Triticum aestivum). 农业生物技术学报, 2024, 32(2): 259-272.
[1] 廖思敏, 冯波, 徐智斌, 等. 2022. 基于55K SNP芯片检测小麦株高QTL[J]. 应用与环境生物学报, 28(3): 576-581. (Liao S M, Feng B, Xu Z B, et al.2022. Detection of QTLs for plant height in wheat based on the 55K SNP array[J]. Chinese Journal of Applied and Environmental Biology, 28(3): 576-581.) [2] 刘易科, 朱展望, 陈泠, 等. 2020. 基于 SNP 标记揭示我国小麦品种(系)的遗传多样性[J]. 作物学报, 46(2): 307-314. (Liu Y K, Zhu Z W, Chen L, et al.2020. Revealing the genetic diversity of wheat varieties (lines) in China based on SNP markers[J]. Acta Agronomica Sinica, 46(2): 307-314.) [3] 武炳瑾, 冯洁, 崔紫霞, 等. 2017. 利用90K芯片进行株高QTL分析[J]. 麦类作物学报, 37(5): 578-584. (Wu B J, Feng J, Cui Z X, et al.2017. QTL analysis of plant height by using 90K chip technology[J]. Journal of Triticeae Crops, 37(5): 578-584.) [4] 于海飞, 杜晓宇, 殷贵鸿, 等. 2022. 普通小麦抗倒伏相关性状的全基因组关联分析[J]. 植物遗传资源学报, 23(1): 147-159. (Yu H F, Du X Y, Yin G H, et al.2022. Genome-wide association mapping for lodging-resistance related traits in common wheat[J]. Journal of Plant Genetic Resources, 23(1): 147-159.) [5] 翟俊鹏, 李海霞, 毕惠惠, 等. 2019. 普通小麦主要农艺性状的全基因组关联分析[J]. 作物学报, 45(10): 1488-1503. (Zhai J P, Li H X, Bi H H, et al.2019. Genome-wide association study for main agronomic traits in common wheat[J]. Acta Agronomica Sinica, 45(10): 1488-1503.) [6] Fang L B, Ma L Y, Zhao S L, et al.2022. Alanine aminotransferase (OsAlaAT1) modulates nitrogen utilization, grain yield, and quality in rice[J]. Journal of Genetics and Genomics, 49(5): 510-513. [7] Gao F M, Ma D Y, Yin G H, et al.2016. Genetic progress in grain yield and physiological traits in Chinese wheat cultivars of Southern Yellow and Huai valley winter wheat zone since 1950[J]. Crop Science, 57(2): 760-773. [8] Gao F M, Wen W E, Liu J D, et al.2015. Genome-wide linkage mapping of QTL for yield components, plant height and yield-related physiological traits in the chinese wheat cross Zhou8425B/Chinese Spring[J]. Frontiers in Plant Science, 6: 1099. [9] Hao C Y, Wang L F, Ge H M, et al.2011. Genetic diversity and linkage disequilibrium in Chinese bread wheat (Triticum aestivum L.) revealed by SSR markers[J]. PLOS ONE, 6(2): e17279. [10] Hu J M, Wang X Q, Zhang G X, et al.2020. QTL mapping for yield-related traits in wheat based on four RIL populations[J]. Theoretical and Applied Genetics, 133(3): 917-933. [11] Kudo T, Makita N, Kojima M, et al.2012. Cytokinin activity of cis-zeatin and phenotypic alterations induced by overexpression of putative cis-zeatin-o-glucosyltransferase in rice[J]. Plant Physiology, 160(1): 319-331. [12] Li C, Tang H P, Luo W, et al.2020. A novel, validated, and plant height-independent QTL for spike extension length is associated with yield-related traits in wheat[J]. Theoretical and Applied Genetics, 133(12): 3381-3393. [13] Li Y L, Gao J, Zhang R Z, et al.2020. Identification of new QTL for yield related traits in Chinese landrace and elite wheat varieties through a genome-wide linkage mapping[J]. Euphytica, 216(8): 1-14. [14] Liu K, Muse S V.2005. Power Marker: An integrated analysis environment for genetic marker analysis[J]. Bioinformatics, 21(9): 2128-2129. [15] Liu W Z, Wu C, Fu Y P, et al.2009. Identification and characterization of HTD2: A novel gene negatively regulating tiller bud outgrowth in rice[J]. Planta, 230(4): 649-658. [16] Mackay I, Powell W.2007. Methods for linkage disequilibrium mapping in crops[J]. Trends in Plant Science, 12(2): 57-63. [17] Miao Y P, Jing F L, Ma J F, et al.2022. Major genomic regions for wheat grain weight as revealed by QTL linkage mapping and meta-analysis[J]. Frontiers in Plant Science, 13: 802310. [18] Passaia G, Caverzan A, Fonini L S, et al.2014. Chloroplastic and mitochondrial GPX genes play a critical role in rice development[J]. Biologia Plantarum, 58(2): 375-378. [19] Qu P P, Wang J K, Wen W E, et al.2021. Construction of cnsensus genetic map with applications in gene mapping of wheat (Triticum aestivum L.) using 90K SNP array[J]. Frontiers in Plant Science, 12: 727077. [20] Rabbi S M H A, Kumar A, Naraghi S M, et al.2021. Genome-wide association mapping for yield and related traits under drought stressed and non-stressed environments in wheat[J]. Frontiers in Genetics, 12: 649988. [21] Ren T H, Fan T, Chen S L, et al.2021. Utilization of a wheat 55K SNP array-derived high-density genetic map for high resolution mapping of quantitative trait loci for important kernel-related traits in common wheat[J]. Theoretical and Applied Genetics, 134(3): 807-821. [22] Saghai-Maroof M A, Soliman K M, Jorgensen R A, et al.1984. Ribosomal DNA spacer-length polymorphisms in barley: Mendelian inheritance, chromosomal location, and population dynamics[J]. Proceedings of the National Academy of Sciences of the USA, 81(24): 8014-8018. [23] Shiferaw B, Smale M, Braun H J, et al.2013. Crops that feed the world 10. Past successes and future challenges to the role played by wheat in global food security[J]. Food Security, 5(3): 291-317. [24] Sukumaran S, Dreisigacker S, Lopes M, et al.2015. Genome-wide association study for grain yield and related traits in an elite spring wheat population grown in temperate irrigated environments[J]. Theoretical and Applied Genetics, 128(2): 353-363. [25] Sun C W, Zhang F Y, Yan X F, et al.2017. Genome-wide association study for 13 agronomic traits reveals distribution of superior alleles in bread wheat from the Yellow and Huai Valley of China[J]. Plant Biotechnology Journal, 15(8): 953-969. [26] Toker C.2004. Estimates of broad-sense heritability for seed yield and yield criteria in faba bean (Vicia faba L.)[J]. Hereditas, 140(3): 222-225. [27] Wang P, Tian T, Ma J F, et al.2022. Genome-wide association study of kernel traits using a 35K SNP array in bread wheat (Triticum aestivum L.)[J]. Frontiers in Plant Science, 13: 905660. [28] Xiao J, Liu B, Yao Y Y, et al.2022. Wheat genomic study for genetic improvement of traits in China[J]. Science China-life Sciences, 65(9): 1718-1775. [29] Xiong H C, Li Y T, Guo H J, et al.2021. Genetic mapping by integration of 55K SNP array and KASP markers reveals candidate genes for important agronomic traits in hexaploid wheat[J]. Frontiers in Plant Science, 12: 6284781.
