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Full name: WheatCompDB
Description: WheatCompDB was built for researchers to conveniently access similar genetic regions (SGRs), polymorphism hotspot regions (PHRs), sample-specific deletion CNV regions, sample-specific duplication CNV regions, shared deletion CNV regions and shared duplication CNV regions between wheat accessions.
Year founded: 2022
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Country/Region: China

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Contact information

University/Institution: China Agricultural University
City: Beijing
Country/Region: China
Contact name (PI/Team): Yang, Zhengzhao
Contact email (PI/Helpdesk):


ggComp enables dissection of germplasm resources and construction of a multiscale germplasm network in wheat. [PMID: 35088857]
Zhengzhao Yang, Zihao Wang, Wenxi Wang, Xiaoming Xie, Lingling Chai, Xiaobo Wang, Xibo Feng, Jinghui Li, Huiru Peng, Zhenqi Su, Mingshan You, Yingyin Yao, Mingming Xin, Zhaorong Hu, Jie Liu, Rongqi Liang, Zhongfu Ni, Qixin Sun, Weilong Guo

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 (, is available for researchers to exploit the identified gIBDs with a multi-scale network.

Plant Physiol. 2022:188(4) | 0 Citations (from Europe PMC, 2022-07-02)



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Created on: 2022-04-25
Curated by:
Lina Ma [2022-06-01]
sun yongqing [2022-05-15]
Qianpeng Li [2022-04-25]