Caister Academic Press

Cataloging Plant Genome Structural Variations

Authors: Xingtan ZhangCenter for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China, and Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou Fujian Province, China Xuequn ChenCenter for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China, and Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou Fujian Province, China Pingping LiangCenter for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China, and Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou Fujian Province, China Haibao TangCenter for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China, and Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou Fujian Province, China.
Abstract:
Open-access article
Structural variation (SV) is a type of genetic variation identified through the comparison of genome structures which often have direct and significant associations with phenotypic variations. Building on the next generation sequencing (NGS) technologies, research on plant structural variations are gaining momentum and have revolutionized our view on the functional impact of the 'hidden' diversity that were largely understudied before. Herein, we first describe the current state of plant genomic SV research based on NGS and in particular focus on the biological insights gained from the large-scale identification of various types of plant SVs. Specific examples are chosen to demonstrate the genetic basis for phenotype diversity in model plant and major agricultural crops. Additionally, development of new genomic mapping technologies, including optical mapping and long read sequencing, as well as improved computational algorithms associated with these technologies have helped to pinpoint the exact nature and location of genomic SVs with much better resolution and precision. Future direction of plant research on SVs should focus on the population level to build a comprehensive catalog of SVs, leading to full assessment of their impact on biological diversity.
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