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Analytical and Decision Support Tools for Genomics-Assisted Breeding

期刊

TRENDS IN PLANT SCIENCE
卷 21, 期 4, 页码 354-363

出版社

ELSEVIER SCIENCE LONDON
DOI: 10.1016/j.tplants.2015.10.018

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资金

  1. CGIAR Generation Challenge Programme (GCP)
  2. US Agency for International Development (USAID)
  3. Department of Biotechnology, Government of India
  4. BBSRC [BBS/E/D/20211551, BBS/E/D/20211554, BBS/E/D/20211553] Funding Source: UKRI
  5. Biotechnology and Biological Sciences Research Council [BBS/E/D/20211551, BBS/E/D/20211554, BBS/E/D/20211553] Funding Source: researchfish
  6. Medical Research Council [MR/M000370/1] Funding Source: researchfish

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To successfully implement genomics-assisted breeding (GAB) in crop improvement programs, efficient and effective analytical and decision support tools (ADSTs) are 'must haves' to evaluate and select plants for developing next generation crops. Here we review the applications and deployment of appropriate ADSTs for GAB, in the context of next-generation sequencing (NGS), an emerging source of massive genomic information. We discuss suitable software tools and pipelines for marker-based approaches (markers/haplotypes), including large-scale genotypic and phenotypic, data management, and molecular breeding approaches. Although phenotyping remains expensive and time consuming, prediction of allelic effects on phenotypes opens new doors to enhance genetic gain across crop cycles, building on reliable phenotyping approaches and good crop information systems, including pedigree information and target haplotypes.

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