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Genetic polyploid phasing from low-depth progeny samples

An important challenge in genome assembly is haplotype phasing, that is, to reconstruct the different haplotype sequences of an individual genome. Phasing becomes considerably more difficult with increasing ploidy, which makes polyploid phasing a notoriously hard computational problem. We present a...

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Detalles Bibliográficos
Autores principales: Schrinner, Sven, Serra Mari, Rebecca, Finkers, Richard, Arens, Paul, Usadel, Björn, Marschall, Tobias, Klau, Gunnar W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9184567/
https://www.ncbi.nlm.nih.gov/pubmed/35692633
http://dx.doi.org/10.1016/j.isci.2022.104461
Descripción
Sumario:An important challenge in genome assembly is haplotype phasing, that is, to reconstruct the different haplotype sequences of an individual genome. Phasing becomes considerably more difficult with increasing ploidy, which makes polyploid phasing a notoriously hard computational problem. We present a novel genetic phasing method for plant breeding with the aim to phase two deep-sequenced parental samples with the help of a large number of progeny samples sequenced at low depth. The key ideas underlying our approach are to (i) integrate the individually weak Mendelian progeny signals with a Bayesian log-likelihood model, (ii) cluster alleles according to their likelihood of co-occurrence, and (iii) assign them to haplotypes via an interval scheduling approach. We show on two deep-sequenced parental and 193 low-depth progeny potato samples that our approach computes high-quality sparse phasings and that it scales to whole genomes.