Standardized microhaplotype databases and frameworks for assessing and mining crop genetic diversity
Journal
THEORETICAL AND APPLIED GENETICS
Journal Volume
139
Journal Issue
9
Start Page
244
ISSN
1432-2242
Date Issued
2026-08-25
Author(s)
Zhao, Dongyan
Lin, Meng
Taniguti, Cristiane H
Sandercock, Alexander M
Chen, Shufen
Babiker, Ebrahiem
Bassil, Nahla V
Brummer, E Charles
Camacho, Jose Roberto
Chatwin, Warren
Chen, Shu-Yun
Clare, Shaun J
da Silva Pereira, Guilherme
David, Maria
Fraher, Simon Phillip
Hardigan, Michael
Hilton, Angelyn
Hislop, Lillian M
Irish, Brian M
Kante, Moctar
Kim, Tae Hwa
Lee, Chong-Wei
Lindqvist-Kreuze, Hannele
Loarca, Jenyne
嘉義農業試驗分所
Medina Culma, Cesar Agusto
Jiménez Morales, Jose Fabián
Polashock, James
Price, John H
Riday, Heathcliffe
Samac, Deborah A
Sandhu, Devinder
Ssali, Reuben
Castro Vásquez, Ruth Mayela
Wadl, Phillip A
Wang, Xinwang
Webster, Seymour A
Xu, Zhanyou
Yencho, G Craig
Beil, Craig T
Sheehan, Moira J
Abstract
Standardized microhaplotype databases for eight diverse crops enable multiallelic analyses, comparative genetics, and breeding decisions. Microhaplotypes are short genomic segments that contain multiple tightly linked variants, providing multi-allelic data that can enhance genetic resolution compared to traditional biallelic single nucleotide polymorphism (SNP) markers. Here, we present the creation and utilization of separate microhaplotype databases for eight crop species representing diverse genome sizes, ploidy levels, and breeding systems. We developed a standardized, species-agnostic pipeline for processing, filtering, and databasing microhaplotypes generated using the DArTag targeted genotyping platform. To enhance user accessibility, we developed a no-code, user-friendly application, HapApp, that uses an R Shiny front-end interface to allow breeders and researchers to add unique, standardized microhaplotype identities from raw DArTag reports and iteratively update the existing crop-specific database with the newly discovered microhaplotypes. Selected case studies with these databases highlight the operational advantages of microhaplotypes, especially for challenging, highly heterozygous, or polyploid species. They offer an informative alternative to traditional biallelic SNP analyses for resolving population structures and improving linkage map ordering. This integrated framework provides a reproducible and scalable foundation for managing and exploiting microhaplotype data in plant breeding and genetic research, enabling robust cross-project comparisons and facilitating trait discovery in both simple and complex crop genomes, while enabling comparative genomics and cross-species functional transfer that accelerates genetic gains across all crop species.
Publisher
Springer
Type
journal article