Open AccessNovel Methods to Optimize Genotypic Imputation for Low‐Coverage, Next‐Generation Sequence Data in Crop Plants
Author(s) -
Swarts Kelly,
Li Huihui,
Romero Navarro J. Alberto,
An Dong,
Romay Maria Cinta,
Hearne Sarah,
Acharya Charlotte,
Glaubitz Jeffrey C.,
Mitchell Sharon,
Elshire Robert J.,
Buckler Edward S.,
Bradbury Peter J.
Publication year - 2014
Publication title -
the plant genome
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 41
ISSN - 1940-3372
DOI - 10.3835/plantgenome2014.05.0023
Subject(s) - imputation (statistics) , biology , inbreeding , missing data , genotyping , genotype , haplotype , genetics , microbiology and biotechnology , statistics , population , gene , mathematics , demography , sociology
Next‐generation sequencing technology such as genotyping‐by‐sequencing (GBS) made low‐cost, but often low‐coverage, whole‐genome sequencing widely available. Extensive inbreeding in crop plants provides an untapped, high quality source of phased haplotypes for imputing missing genotypes. We introduce Full‐Sib Family Haplotype Imputation (FSFHap), optimized for full‐sib populations, and a generalized method, Fast Inbred Line Library ImputatioN (FILLIN), to rapidly and accurately impute missing genotypes in GBS‐type data with ordered markers. FSFHap and FILLIN impute missing genotypes with high accuracy in GBS‐genotyped maize ( Zea mays L.) inbred lines and breeding populations, while Beagle v. 4 is still preferable for diverse heterozygous populations. FILLIN and FSFHap are implemented in TASSEL 5.0.