ArticleGenetics, selection, evolution : GSE2017
A method for the allocation of sequencing resources in genotyped livestock populations.
Article in Genetics, selection, evolution : GSE, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 38 citations in OpenAlex.
- A primer on sequencing and genotype imputation in cattle.Journal of animal science · 2025Review
- Genomic prediction with whole-genome sequence data in intensely selected pig lines.Genetics, selection, evolution : GSE · 2022Article
- Rare and population-specific functional variation across pig lines.Genetics, selection, evolution : GSE · 2022Article
- Comparison of the choice of animals for re-sequencing in two maternal pig lines.Genetics, selection, evolution : GSE · 2022Article
- Characterization of a haplotype-reference panel for genotyping by low-pass sequencing in Swiss Large White pigs.BMC genomics · 2021Article
- TrainSel: An R Package for Selection of Training Populations.Frontiers in genetics · 2021Article
- Impact of Genomic Prediction Model, Selection Intensity, and Breeding Strategy on the Long-Term Genetic Gain and Genetic Erosion in Soybean Breeding.Frontiers in genetics · 2021Article
- Optimizing Sequencing Resources in Genotyped Livestock Populations Using Linear Programming.Frontiers in genetics · 2021Article
- Accuracy of whole-genome sequence imputation using hybrid peeling in large pedigreed livestock populations.Genetics, selection, evolution : GSE · 2020Article
- Evaluation of sequencing strategies for whole-genome imputation with hybrid peeling.Genetics, selection, evolution : GSE · 2020Article
- Optimizing Selection of the Reference Population for Genotype Imputation From Array to Sequence Variants.Frontiers in genetics · 2019Article
- Sequence variation, evolutionary constraint, and selection at the CD163 gene in pigs.Genetics, selection, evolution : GSE · 2018Article
- Hybrid peeling for fast and accurate calling, phasing, and imputation with sequence data of any coverage in pedigrees.Genetics, selection, evolution : GSE · 2018Article
- Impact of index hopping and bias towards the reference allele on accuracy of genotype calls from low-coverage sequencing.Genetics, selection, evolution : GSE · 2018Article
- A method for allocating low-coverage sequencing resources by targeting haplotypes rather than individuals.Genetics, selection, evolution : GSE · 2017Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThis paper describes a method, called AlphaSeqOpt, for the allocation of sequencing resources in livestock populations with existing phased genomic data to maximise the ability to phase and impute sequenced haplotypes into the whole population.
methodsWe present two algorithms. The first selects focal individuals that collectively represent the maximum possible portion of the haplotype diversity in the population. The second allocates a fixed sequencing budget among the families of focal individuals to enable phasing of their haplotypes at the sequence level. We tested the performance of the two algorithms in simulated pedigrees. For each pedigree, we evaluated the proportion of population haplotypes that are carried by the focal individuals and compared our results to a variant of the widely-used key ancestors approach and to two haplotype-based approaches. We calculated the expected phasing accuracy of the haplotypes of a focal individual at the sequence level given the proportion of the fixed sequencing budget allocated to its family.
resultsAlphaSeqOpt maximises the ability to capture and phase the most frequent haplotypes in a population in three ways. First, it selects focal individuals that collectively represent a larger portion of the population haplotype diversity than existing methods. Second, it selects focal individuals from across the pedigree whose haplotypes can be easily phased using family-based phasing and imputation algorithms, thus maximises the ability to impute sequence into the rest of the population. Third, it allocates more of the fixed sequencing budget to focal individuals whose haplotypes are more frequent in the population than to focal individuals whose haplotypes are less frequent. Unlike existing methods, we additionally present an algorithm to allocate part of the sequencing budget to the families (i.e. immediate ancestors) of focal individuals to ensure that their haplotypes can be phased at the sequence level, which is essential for enabling and maximising subsequent sequence imputation.
conclusionsWe present a new method for the allocation of a fixed sequencing budget to focal individuals and their families such that the final sequenced haplotypes, when phased at the sequence level, represent the maximum possible portion of the haplotype diversity in the population that can be sequenced and phased at that budget.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.