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Heterozygous Mapping Strategy (HetMappS) for High Resolution Genotyping-By-Sequencing Markers: A Case Study in Grapevine.

Hyma KE, Barba P, Wang M, Londo JP, Acharya CB, Mitchell SE, Sun Q, Reisch B, Cadle-Davidson L - PLoS ONE (2015)

Bottom Line: To overcome these issues, we developed a publicly available, modular approach called HetMappS, which functions independently of parental genotypes and corrects for genotyping errors associated with heterozygosity.Flower sex was mapped in three families and correctly localized to the known sex locus in all cases.The HetMappS pipeline could have wide application for genetic mapping in highly heterozygous species, and its modularity provides opportunities to adapt portions of the pipeline to other family types, genotyping technologies or applications.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics Facility, Institute of Biotechnology, Cornell University, Ithaca, New York, United States of America; Genomic Diversity Facility, Institute of Biotechnology, Cornell University, Ithaca, New York, United States of America.

ABSTRACT
Genotyping by sequencing (GBS) provides opportunities to generate high-resolution genetic maps at a low genotyping cost, but for highly heterozygous species, missing data and heterozygote undercalling complicate the creation of GBS genetic maps. To overcome these issues, we developed a publicly available, modular approach called HetMappS, which functions independently of parental genotypes and corrects for genotyping errors associated with heterozygosity. For linkage group formation, HetMappS includes both a reference-guided synteny pipeline and a reference-independent de novo pipeline. The de novo pipeline can be utilized for under-characterized or high diversity families that lack an appropriate reference. We applied both HetMappS pipelines in five half-sib F1 families involving genetically diverse Vitis spp. Starting with at least 116,466 putative SNPs per family, the HetMappS pipelines identified 10,440 to 17,267 phased pseudo-testcross (Pt) markers and generated high-confidence maps. Pt marker density exceeded crossover resolution in all cases; up to 5,560 non-redundant markers were used to generate parental maps ranging from 1,047 cM to 1,696 cM. The number of markers used was strongly correlated with family size in both de novo and synteny maps (r = 0.92 and 0.91, respectively). Comparisons between allele and tag frequencies suggested that many markers were in tandem repeats and mapped as single loci, while markers in regions of more than two repeats were removed during map curation. Both pipelines generated similar genetic maps, and genetic order was strongly correlated with the reference genome physical order in all cases. Independently created genetic maps from shared parents exhibited nearly identical results. Flower sex was mapped in three families and correctly localized to the known sex locus in all cases. The HetMappS pipeline could have wide application for genetic mapping in highly heterozygous species, and its modularity provides opportunities to adapt portions of the pipeline to other family types, genotyping technologies or applications.

No MeSH data available.


Overview of the HetMappS pipelines.(A) shared initial steps resulting in identification of pseudo-testcross markers, (B) linkage group creation and phasing steps, either (B1) synteny or (B2) de novo, and (C) genetic ordering and formatting for R/qtl.
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pone.0134880.g001: Overview of the HetMappS pipelines.(A) shared initial steps resulting in identification of pseudo-testcross markers, (B) linkage group creation and phasing steps, either (B1) synteny or (B2) de novo, and (C) genetic ordering and formatting for R/qtl.

Mentions: Quality-filtered GBS SNP datasets for each F1 family were analyzed independently with the HetMappS pipeline using two approaches (Fig 1). Following (A) pseudo-testcross marker identification, marker grouping and ordering for each family was performed using one of two pipelines: (B1) a synteny pipeline, for which markers were initially separated into chromosomal groups based on alignment to the reference genome, filtered based on linkage, and then phased; or (B2) de novo genetic map pipeline, with linkage group (LG) formation based solely on progeny genotypes, regardless of alignment position, followed by phasing within LG. For both pipelines, although optionally for the synteny pipeline, (C) genetic ordering was carried out using MSTMap [48], and resulting maps were exported as cross files for analysis in R/qtl [14]. Documentation for HetMappS, developed for a Linux operating system, can be found in S1 File.


Heterozygous Mapping Strategy (HetMappS) for High Resolution Genotyping-By-Sequencing Markers: A Case Study in Grapevine.

Hyma KE, Barba P, Wang M, Londo JP, Acharya CB, Mitchell SE, Sun Q, Reisch B, Cadle-Davidson L - PLoS ONE (2015)

Overview of the HetMappS pipelines.(A) shared initial steps resulting in identification of pseudo-testcross markers, (B) linkage group creation and phasing steps, either (B1) synteny or (B2) de novo, and (C) genetic ordering and formatting for R/qtl.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4526651&req=5

pone.0134880.g001: Overview of the HetMappS pipelines.(A) shared initial steps resulting in identification of pseudo-testcross markers, (B) linkage group creation and phasing steps, either (B1) synteny or (B2) de novo, and (C) genetic ordering and formatting for R/qtl.
Mentions: Quality-filtered GBS SNP datasets for each F1 family were analyzed independently with the HetMappS pipeline using two approaches (Fig 1). Following (A) pseudo-testcross marker identification, marker grouping and ordering for each family was performed using one of two pipelines: (B1) a synteny pipeline, for which markers were initially separated into chromosomal groups based on alignment to the reference genome, filtered based on linkage, and then phased; or (B2) de novo genetic map pipeline, with linkage group (LG) formation based solely on progeny genotypes, regardless of alignment position, followed by phasing within LG. For both pipelines, although optionally for the synteny pipeline, (C) genetic ordering was carried out using MSTMap [48], and resulting maps were exported as cross files for analysis in R/qtl [14]. Documentation for HetMappS, developed for a Linux operating system, can be found in S1 File.

Bottom Line: To overcome these issues, we developed a publicly available, modular approach called HetMappS, which functions independently of parental genotypes and corrects for genotyping errors associated with heterozygosity.Flower sex was mapped in three families and correctly localized to the known sex locus in all cases.The HetMappS pipeline could have wide application for genetic mapping in highly heterozygous species, and its modularity provides opportunities to adapt portions of the pipeline to other family types, genotyping technologies or applications.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics Facility, Institute of Biotechnology, Cornell University, Ithaca, New York, United States of America; Genomic Diversity Facility, Institute of Biotechnology, Cornell University, Ithaca, New York, United States of America.

ABSTRACT
Genotyping by sequencing (GBS) provides opportunities to generate high-resolution genetic maps at a low genotyping cost, but for highly heterozygous species, missing data and heterozygote undercalling complicate the creation of GBS genetic maps. To overcome these issues, we developed a publicly available, modular approach called HetMappS, which functions independently of parental genotypes and corrects for genotyping errors associated with heterozygosity. For linkage group formation, HetMappS includes both a reference-guided synteny pipeline and a reference-independent de novo pipeline. The de novo pipeline can be utilized for under-characterized or high diversity families that lack an appropriate reference. We applied both HetMappS pipelines in five half-sib F1 families involving genetically diverse Vitis spp. Starting with at least 116,466 putative SNPs per family, the HetMappS pipelines identified 10,440 to 17,267 phased pseudo-testcross (Pt) markers and generated high-confidence maps. Pt marker density exceeded crossover resolution in all cases; up to 5,560 non-redundant markers were used to generate parental maps ranging from 1,047 cM to 1,696 cM. The number of markers used was strongly correlated with family size in both de novo and synteny maps (r = 0.92 and 0.91, respectively). Comparisons between allele and tag frequencies suggested that many markers were in tandem repeats and mapped as single loci, while markers in regions of more than two repeats were removed during map curation. Both pipelines generated similar genetic maps, and genetic order was strongly correlated with the reference genome physical order in all cases. Independently created genetic maps from shared parents exhibited nearly identical results. Flower sex was mapped in three families and correctly localized to the known sex locus in all cases. The HetMappS pipeline could have wide application for genetic mapping in highly heterozygous species, and its modularity provides opportunities to adapt portions of the pipeline to other family types, genotyping technologies or applications.

No MeSH data available.