Bioinformatics for plant genetics and breeding research - Naik, Y.D.; Zhao, C.; Channale, S.; Nayak, S.N.; Bhutia, K.L.; Gautam, A.; Kumar, R.; Niranjan, V.; Shah, T.M.; Mott, R.; Punnuri, S.; Pandey, M.K.; et al. (Springer, 2024)
Global food demand is expected to increase between 55 and 70% by 2050. Plant breeders and geneticists are constantly under pressure to develop high-yielding climate-resilient varieties using novel approaches. The quest for simplifying complex traits and efforts for developing high-yielding varieties during the twenty-first century led to a paradigm shift from phenotypic-based selection to genome-based breeding. On one hand, the development and utilization of diverse genetic resources, and advances in genomics on the other hand provided a kick start for the understanding the genetics of economically important complex traits at a faster pace. Further, the next-generation sequencing revolutionized our understanding of the genome architecture. As a result, there has been an increasing demand for statistical and bioinformatics tools to analyse and manage the enormous amount of data generated from sequencing of genomes, transcriptomes, proteome and metabolomes. In this chapter, we review the intervention of bioinformatics and computational tools for deploying the tremendous wealth of data for plant genetics and breeding research.