Combing a new exome capture panel with an effective varBScore algorithm accelerates BSA-based gene cloning in wheat

Authors: DONG, CHUNHAO - Chinese Academy Of Agricultural Sciences; ZHANG, LICHAO - Chinese Academy Of Agricultural Sciences; CHEN, ZHONGXU - Sichuan Academy Of Agricultural Science; XIA, CHUAN - Chinese Academy Of Agricultural Sciences; Gu, Yong; WANG, JIRUI - Sichuan Academy Of Agricultural Science; LI, DANPING - Chinese Academy Of Agricultural Sciences; XIE, ZHENGCHENG - Chinese Academy Of Agricultural Sciences; ZHANG, QIANG - Chinese Academy Of Agricultural Sciences; ZHANG, XUEYING - Chinese Academy Of Agricultural Sciences; GUI, LIXUAN - Sichuan Academy Of Agricultural Science; LIU, XU - Chinese Academy Of Agricultural Sciences; KONG, XIUYING - Chinese Academy Of Agricultural Sciences

Submitted to: Frontiers in Plant Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/29/2020
Publication Date: 8/13/2020
Citation: Dong, C., Zhang, L., Chen, Z., Xia, C., Gu, Y.Q., Wang, J., Li, D.L., Xie, Z., Zhang, Q., Zhang, X., Gui, L., Liu, X., Kong, X. 2020. Combing a new exome capture panel with an effective varBScore algorithm accelerates BSA-based gene cloning in wheat. Frontiers in Plant Science. 11:1249. https://doi.org/10.3389/fpls.2020.01249.
DOI: https://doi.org/10.3389/fpls.2020.01249

Interpretive Summary: Wheat is an important staple crop, providing 20% of all calories consumed by the world population. Identification of genes underlying desirable agronomic traits is of great significance for genetic improvement of wheat. However, wheat functional genome research lags far behind model plants due to its large genome size and complex polyploid nature. In this work, we developed an effective approach to mapping and cloning wheat genes using targeted genome sequencing technology and a novel data analysis method. The data analysis algorithm, varBScore, developed in this work can significantly enhance call accuracy for SNP variations. The utility of this approach was successfully demonstrated in cloning the wheat yellowing mutant gene using an ethyl methanesulfonate (EMS) mutant population in this work.

Technical Abstract: The discovery of functional genes underlying agronomic traits is of great importance for wheat improvement. Here we designed a new wheat exome capture probe panel based on IWGSC RefSeq v1.0 genome sequence information and developed an effective algorithm varBScore that can sufficiently reduce the background noise in gene mapping and identification. An effective method, termed bulked segregant exome capture sequencing (BSE-Seq) for identifying causal mutations or candidate genes was established by combining the use of new designed wheat exome capture panel, sequencing of bulked segregant pools from segregating populations, and the robust algorithm varBScore. We evaluated the effectiveness of varBScore algorithm on SNP call using the published dataset for mapping and cloning the yellow rust resistance gene Yr7 in wheat. Furthermore, using BSE-Seq, we rapidly identified a wheat yellow leaf mutant gene ygl1 in an ethyl methanesulfonate (EMS) mutant population and found that a single mutation of G to A at 921 position in the wild type YGL1 gene encoding magnesium-chelatase subunit chlI caused the leaf yellowing phenotype. We further showed that mutation of YGL1 through CRISPR/Cas9 gene editing led to a yellow phenotype on the leaves of transgenic wheat, indicating that ygl1 is the correct causal gene responsible for the mutant phenotype. The results demonstrated that our approach is highly efficient for discovering the causal mutation or gene cloning in wheat.