Integrative genomics for mango genetics and breeding

TL;DR

This paper reviews how genomics and multiomics can improve mango breeding to address challenges like disease resistance and climate adaptation.

Contribution

The paper proposes integrative strategies combining pangenomics, multiomics, and machine learning to accelerate mango improvement.

Findings

High-quality genome assemblies and pangenomics have advanced mango genetics.

Multiomics and quantitative genetics integration is key for crop improvement.

Breeding efficiency is hindered by long juvenile periods and outdated systems.

Abstract

Mango is the second most important tropical fruit crop. Due to ever-changing environmental conditions, world mango production is facing challenges such as diseases (anthracnose and mango malformation), physiological disorders (alternate bearing), low fruit setting, poor fruit quality, short shelf life, and climate change adaptation. Breeding efforts are hindered by the long juvenile period, outdated breeding system, and high heterozygosity, resulting in a slow pace of mango improvement programs. However, over the last decade, significant advances in high-quality genome assemblies, pangenomics, genetic mapping, multiomics data, and phenomics of large populations have accelerated crop genetics and breeding. Here, we summarize recent progress on the origin and domestication of mango, advancements in genome assemblies, development of genetic maps, functional and comparative genomics, evolutionary insights, and assessments of global phenotypic and genotypic diversity, including species at risk. We also discuss the integration of multiomics approaches with quantitative genetics for crop improvement. Furthermore, we highlight the key research gaps that limit breeding efficiency and propose integrative strategies combining pangenomics, multiomics, and machine learning with improved transformation protocols and multienvironment testing to accelerate the development of climate-resilient, high-quality mango cultivars.

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