Novel Methods to Optimize Genotypic Imputation for Low‐Coverage, Next‐Generation Sequence Data in Crop Plants

By Kelly L Swarts, Huihui Li, J. Romero Navarro, Dong An, M. Romay, Sarah Hearne, C. Acharya, Jeffrey Glaubitz, S. Mitchell, Robert Elshire and 2 more. 2014

259 citations recorded by the source corpus.

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.

Subfields: Genetics, Plant Science

View Paper: https://www.semanticscholar.org/paper/fb232af5d8a3500e5521753749ddd6253726ab9e

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Citations in the corpus

Genome‐wide Association for Plant Height and Flowering Time across 15 Tropical Maize Populations under Managed Drought Stress and Well‐Watered Conditions in Sub‐Saharan Africa (2016, methodology): “FSFhap (Swarts et al. 2014) showed the highest accuracy (0.”
Sustaining the Future of Plant Breeding: The Critical Role of the USDA-ARS National Plant Germplasm System (2018, background): “As sequencing costs continue to plummet, entire core collections can be resequenced at lower coverage, followed by efficient imputation of missing marker genotypes (Swarts et al., 2014).”