Two decades of association mapping: Insights on disease resistance in major crops

Front Plant Sci. 2022 Dec 6:13:1064059. doi: 10.3389/fpls.2022.1064059. eCollection 2022.

Abstract

Climate change across the globe has an impact on the occurrence, prevalence, and severity of plant diseases. About 30% of yield losses in major crops are due to plant diseases; emerging diseases are likely to worsen the sustainable production in the coming years. Plant diseases have led to increased hunger and mass migration of human populations in the past, thus a serious threat to global food security. Equipping the modern varieties/hybrids with enhanced genetic resistance is the most economic, sustainable and environmentally friendly solution. Plant geneticists have done tremendous work in identifying stable resistance in primary genepools and many times other than primary genepools to breed resistant varieties in different major crops. Over the last two decades, the availability of crop and pathogen genomes due to advances in next generation sequencing technologies improved our understanding of trait genetics using different approaches. Genome-wide association studies have been effectively used to identify candidate genes and map loci associated with different diseases in crop plants. In this review, we highlight successful examples for the discovery of resistance genes to many important diseases. In addition, major developments in association studies, statistical models and bioinformatic tools that improve the power, resolution and the efficiency of identifying marker-trait associations. Overall this review provides comprehensive insights into the two decades of advances in GWAS studies and discusses the challenges and opportunities this research area provides for breeding resistant varieties.

Keywords: genome wide association studies; haplotypes; k-mers; multi-parent populations; pangenomes; plant diseases.

Publication types

  • Review

Grants and funding

MT acknowledges financial support from Science Engineering Research Board (SERB; Grant No: CRG/2018/003056), Department of Science and Technology, Government of India and CZ is grateful to National Natural Science Foundation of China (31861143009, 32072090) for funding his research.