GgComp enables dissection of germplasm resources and construction of a multiscale germplasm network in wheat. Issue 4 (28th January 2022)

• Record Type: Journal Article
• Authors: Yang, Zhengzhao; Wang, Zihao; Wang, Wenxi; Xie, Xiaoming; Chai, Lingling; Wang, Xiaobo; Feng, Xibo; Li, Jinghui; Peng, Huiru; Su, Zhenqi; You, Mingshan; Yao, Yingyin; Xin, Mingming; Hu, Zhaorong; Liu, Jie; Liang, Rongqi; Ni, Zhongfu; Sun, Qixin; Guo, Weilong
• Is Part Of: Plant physiology. Volume 188:Issue 4(2022)
• Page Start: 1950
• Page End: 1965
• Publication Date: 2022-01-28
• Subjects: Plant physiology -- Periodicals; Botany -- Periodicals; Periodicals; Electronic journals; 571.2
• DOI: 10.1093/plphys/kiac029
• Languages: English
• ISSNs: 0032-0889

Abstract

Abstract: Accurate germplasm characterization is a vital step for accelerating crop genetic improvement, which remains largely infeasible for crops such as bread wheat ( Triticum aestivum L.), which has a complex genome that undergoes frequent introgression and contains many structural variations. Here, we propose a genomic strategy called ggComp, which integrates resequencing data with copy number variations and stratified single-nucleotide polymorphism densities to enable unsupervised identification of pairwise germplasm resource-based Identity-By-Descent (gIBD) blocks. The reliability of ggComp was verified in wheat cultivar Nongda5181 by dissecting parental-descent patterns represented by inherited genomic blocks. With gIBD blocks identified among 212 wheat accessions, we constructed a multi-scale genomic-based germplasm network. At the whole-genome level, the network helps to clarify pedigree relationship, demonstrate genetic flow, and identify key founder lines. At the chromosome level, we were able to trace the utilization of 1RS introgression in modern wheat breeding by hitchhiked segments. At the single block scale, the dissected germplasm-based haplotypes nicely matched with previously identified alleles of "Green Revolution" genes and can guide allele mining and dissect the trajectory of beneficial alleles in wheat breeding. Our work presents a model-based framework for precisely evaluating germplasm resources with genomic data. A database, WheatCompDB (http://wheat.cau.edu.cn/WheatCompDB/ ), is available for researchers to exploit the identified gIBDs with a multi-scale network. Abstract : ggComp is a genomic-based approach that enables multi-scale germplasm network construction and promotes germplasm resource utilization in crop breeding.