The Genetic Diversity of African Common Bean Germplasm: A Systematic Review of Reported Molecular Studies

TL;DR

This paper reviews genetic diversity in African common bean germplasm using molecular studies to guide future crop improvements.

Contribution

A systematic review of genetic diversity in African common beans using PRISMA guidelines and molecular data synthesis.

Findings

Common bean studies show moderate to high genetic diversity with Andean and Mesoamerican gene pools.

AMOVA results highlight significant within-population genetic variation.

Admixture and high gene flow are common in African common bean populations.

Abstract

Background: Common bean (Phaseolus vulgaris L.) is an important grain legume crop of nutritional and economic value across Africa. Genetic improvements of the crop to enhance productivity and resilience depend on understanding the diversity within the African germplasm. Methods: Following PRISMA guidelines, the genetic diversity and population structure of common bean in Africa were reviewed systematically based on existing research. A protocol for conducting the systematic review was developed registered in OSF. Twenty-nine studies met the inclusion criteria after a comprehensive search in ScienceDirect, PubMed, Google Scholar, PubMed, AGRICOLA, Taylor & Francis, and SpringerLink. Data on molecular markers and diversity metrics, thus PIC, He, and AMOVA, were extracted and synthesized qualitatively. Results: Despite substantial heterogeneity in panel sizes, reporting completeness, and marker systems (SSR, SNP, POX, ISSR), consistent patterns emerged. Studies revealed moderate to high levels of genetic diversity. Population-structure analyses recovered the canonical Andean and Mesoamerican gene pools with extensive admixture and high gene flow. AMOVA results indicated that a substantial proportion of total genetic variation was attributed to within-population components. Conclusions: The results are consistent with previous studies, but the sample size and types of markers make direct comparisons impossible. More future studies should use standardized genotyping approaches to increase data consistency. These insights are useful for yield improvement under both non-stress and stress conditions and for developing Africa’s diverse environments.

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