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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/14604

Title: Simultaneous Mapping of Multiple Gene Loci with Pooled Segregants
Authors: Claesen, Jürgen
Clement, Lieven
Shkedy, Ziv
Foulquié-Moreno, Maria R.
Burzykowski, Tomasz
Issue Date: 2013
Citation: PloS one, 8 (2 (e55133)), p. 1-9
Abstract: The analysis of polygenic, phenotypic characteristics such as quantitative traits or inheritable diseases remains an important challenge. It requires reliable scoring of many genetic markers covering the entire genome. The advent of high-throughput secuencing technologies provides a new way to evaluate large numbers of single nucleotide polymorphisms (SNPs) as genetic markers. Combining the technologies with pooling of segregants, as performed in bulked segregant analysis (BSA), should, in principle, allow the simultaneous mapping of multiple genetic loci present throughout the genome. The gene mapping process, applied here, consists of three steps: First, a controlled crossing of parents with and without a trait. Second, selection based on phenotypic screening of the offspring, followed by the mapping of short offspring sequences against the parental reference. The final step aims at detecting genetic markers such as SNPs, insertions and deletions with next generation sequencing(NGS). Markers in close proximity of genomic loci that are associated to the trait have a higher probability to be inherited together. Hence, these markers are very useful for discovering the loci and the genetic mechanism underlying the characteristic of interest. Within this context, NGS produces binomial counts along the genome, i.e. the number of sequenced reads that matches with the SNP of the parental reference strain, which is proxy for the number of individuals in the offspring that share the SNP with the parent. Genomic loci associated with the trait can thus be discovered by analyzing trends in the counts along the genome. We exploit the link between smoothing splines and generalized mixed models for estimating the underlying structure present in the SNP scatterplots.
URI: http://hdl.handle.net/1942/14604
DOI: 10.1371/journal.pone.0055133
ISI #: 000315159200007
ISSN: 1932-6203
Category: A1
Type: Journal Contribution
Validation: ecoom, 2014
Appears in Collections: Research publications

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