bioRxivPlant BiologyPreprint
Scaling up orphan crop research: A global genetic perspective of cowpea (Vigna unguiculata) diversity from 10,617 accessions
Sofie M. Pearson, Adrian HathorniD, Shichao SuniD, Alan CruickshankiD, Tracey ShatteiD, Paulino Munisse, Mercy Wairimu MachariaiD, Joann A. ConneriD, Anna M. KoltunowiD, Jean‐Philippe Vielle‐CalzadaiD, Peggy Ozias‐AkinsiD, Takayoshi IshiiiD, Matteo Dell’AcquaiD, Sally NortoniD, Yongfu TaoiD, David Robert JordaniD, Emma MaceiD
Abstract
Cowpea (Vigna unguiculata L. Walp) is a dryland legume crop, providing essential food and nutritional security for millions of people across the semi-arid tropics, in Africa, Asia, and Latin America. However, as a typical "orphan crop", cowpea has long remained underrepresented in global genomic research to support crop improvement. Here, we conducted the largest genetic diversity analysis of cowpea to date, comprising 10,617 accessions sourced from seven international collections. Using genotyping-by-sequencing, we characterized the global patterns of genetic diversity, assessed redundancy within and across collections, and examined the geographic structure of the cowpea global allele pool. Our results revealed nine distinct genetic groups with clear geographic associations and fine-scale population differentiation, reflecting dispersal history, regional adaptation and the influence of modern breeding. Duplication across collections was detected, highlighting the need for improved curation and integration of germplasm resources. Landraces from sub-Saharan Africa do not fully capture the genetic diversity present in several other geographic regions, indicating the existence of abundant and untapped genetic resources worldwide. These findings not only provide insights into the genetic structure and evolutionary history of cowpea but also offer a valuable foundation for harnessing global germplasm diversity to enhance breeding potential and accelerate crop improvement.
- organism: plant (other)
- assay: whole-genome sequencing
- research focus: clustering
- approach: statistical model
- Citations
- 0
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