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High-resolution genetic mapping of maize pan-genome sequence anchors

Author: Fei Lu
Author: Romay, M.C.
Author: Glaubitz, J.C.
Author: Bradbury, P.J.
Author: Elshire, R.J.
Author: Wang, T.
Author: Yu Li
Author: Yongxiang Li
Author: Semagn, K.
Author: Xuecai Zhang
Author: Hernández, A.G.
Author: Mikel, M.A.
Author: Soifer, I.
Author: Barad, O.
Author: Buckler, E.S.
Year: 2015
ISSN: 2041-1723
URI: https://hdl.handle.net/10883/19719
Descriptors: GWAS
Descriptors: Pheotypic Traits
Descriptors: Genetic Maping
Descriptors: Phenotypes
Abstract: In addition to single-nucleotide polymorphisms, structural variation is abundant in many plant genomes. The structural variation across a species can be represented by a ‘pan-genome’, which is essential to fully understand the genetic control of phenotypes. However, the pan-genome’s complexity hinders its accurate assembly via sequence alignment. Here we demonstrate an approach to facilitate pan-genome construction in maize. By performing 18 trillion association tests we map 26 million tags generated by reduced representation sequencing of 14,129 maize inbred lines. Using machine-learning models we select 4.4 million accurately mapped tags as sequence anchors, 1.1 million of which are presence/absence variations. Structural variations exhibit enriched association with phenotypic traits, indicating that it is a significant source of adaptive variation in maize. The ability to efficiently map ultrahigh-density pan-genome sequence anchors enables fine characterization of structural variation and will advance both genetic research and breeding in many crops.
Abstract: In addition to single-nucleotide polymorphisms, structural variation is abundant in many plant genomes. The structural variation across a species can be represented by a ‘pan-genome’, which is essential to fully understand the genetic control of phenotypes. However, the pan-genome’s complexity hinders its accurate assembly via sequence alignment. Here we demonstrate an approach to facilitate pan-genome construction in maize. By performing 18 trillion association tests we map 26 million tags generated by reduced representation sequencing of 14,129 maize inbred lines. Using machine-learning models we select 4.4 million accurately mapped tags as sequence anchors, 1.1 million of which are presence/absence variations. Structural variations exhibit enriched association with phenotypic traits, indicating that it is a significant source of adaptive variation in maize. The ability to efficiently map ultrahigh-density pan-genome sequence anchors enables fine characterization of structural variation and will advance both genetic research and breeding in many crops.
Language: English
Publisher: Nature Research
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Type: Article
Place: United Kingdom
Journal: Nature Communications
Journal volume: 6
DOI: 10.1038/ncomms7914
Audicence: Researchers


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    Wheat - breeding, phytopathology, physiology, quality, biotech

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