Bioinformatics for plant genetics and breeding research

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...

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Autores principales: 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., Wang, X., Varshney, R.K., Thudi, M.
Formato: Capítulo de libro
Lenguaje:Inglés
Publicado: Springer 2024
Materias:
Acceso en línea:https://hdl.handle.net/10568/159490
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author 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.
Wang, X.
Varshney, R.K.
Thudi, M.
author_browse Bhutia, K.L.
Channale, S.
Gautam, A.
Kumar, R.
Mott, R.
Naik, Y.D.
Nayak, S.N.
Niranjan, V.
Pandey, M.K.
Punnuri, S.
Shah, T.M.
Thudi, M.
Varshney, R.K.
Wang, X.
Zhao, C.
author_facet 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.
Wang, X.
Varshney, R.K.
Thudi, M.
author_sort Naik, Y.D.
collection Repository of Agricultural Research Outputs (CGSpace)
description 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.
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spelling CGSpace1594902024-11-11T11:13:44Z 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. Wang, X. Varshney, R.K. Thudi, M. bioinformatics plant genetics breeding genomes 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. 2024 2024-11-11T11:13:43Z 2024-11-11T11:13:43Z Book Chapter https://hdl.handle.net/10568/159490 en Limited Access Springer Naik, Y.D., Zhao, C., Channale, S., Nayak, S.N., Bhutia, K.L., Gautam, A., ... & Thudi, M. (2024). Bioinformatics for plant genetics and breeding research. In: M.K. Pandey, A. Bentley, H. Desmae, M. Roorkiwal, and R.K. Varshney (eds), Frontier technologies for crop improvement. Sustainability sciences in Asia and Africa. Singapore: Springer Nature Singapore, (pp. 35-64).
spellingShingle bioinformatics
plant genetics
breeding
genomes
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.
Wang, X.
Varshney, R.K.
Thudi, M.
Bioinformatics for plant genetics and breeding research
title Bioinformatics for plant genetics and breeding research
title_full Bioinformatics for plant genetics and breeding research
title_fullStr Bioinformatics for plant genetics and breeding research
title_full_unstemmed Bioinformatics for plant genetics and breeding research
title_short Bioinformatics for plant genetics and breeding research
title_sort bioinformatics for plant genetics and breeding research
topic bioinformatics
plant genetics
breeding
genomes
url https://hdl.handle.net/10568/159490
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