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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.


Related in: MedlinePlus

Visualization of 'Horizon' x Illinois 547–1 genomic data.Data are shown on 1 Mb windows with a 100 Kb slide. A) Number of unique tags aligned, B) Mean tag depth calculated as total tag depth over number of unique tags aligned, C) Density of SNPs entering the HetMappS pipeline, D) Minor allele frequency (MAF) of SNPs entering the pipeline, E-J) SNP output from the synteny pipeline: E) SNP density ‘Horizon’, F) MAF ‘Horizon’ SNPs, G) Recombination frequency ‘Horizon’, calculated as the number of obligate crossovers per progeny per Mb, H) SNP density Illinois 547–1, I) MAF Illinois 547–1 SNPs, J) recombination frequency Illinois 547–1, calculated as the number of obligate crossovers per progeny per Mb.
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pone.0134880.g004: Visualization of 'Horizon' x Illinois 547–1 genomic data.Data are shown on 1 Mb windows with a 100 Kb slide. A) Number of unique tags aligned, B) Mean tag depth calculated as total tag depth over number of unique tags aligned, C) Density of SNPs entering the HetMappS pipeline, D) Minor allele frequency (MAF) of SNPs entering the pipeline, E-J) SNP output from the synteny pipeline: E) SNP density ‘Horizon’, F) MAF ‘Horizon’ SNPs, G) Recombination frequency ‘Horizon’, calculated as the number of obligate crossovers per progeny per Mb, H) SNP density Illinois 547–1, I) MAF Illinois 547–1 SNPs, J) recombination frequency Illinois 547–1, calculated as the number of obligate crossovers per progeny per Mb.

Mentions: Unique tag alignment density, mean tag depth, SNP density entering the pipeline, and minor allele frequency (MAF) of SNPs entering the pipeline were visualized on 1 MB sliding windows with a 100 KB slide using Circos [53]. Additionally, for both parents, phased SNP density (output of HetMappS synteny pipeline), MAF, and recombination frequency (obligate crossovers per progeny per MB) were visualized across these windows (Fig 4, S5 Fig, S6 Fig and S7 Fig).


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)

Visualization of 'Horizon' x Illinois 547–1 genomic data.Data are shown on 1 Mb windows with a 100 Kb slide. A) Number of unique tags aligned, B) Mean tag depth calculated as total tag depth over number of unique tags aligned, C) Density of SNPs entering the HetMappS pipeline, D) Minor allele frequency (MAF) of SNPs entering the pipeline, E-J) SNP output from the synteny pipeline: E) SNP density ‘Horizon’, F) MAF ‘Horizon’ SNPs, G) Recombination frequency ‘Horizon’, calculated as the number of obligate crossovers per progeny per Mb, H) SNP density Illinois 547–1, I) MAF Illinois 547–1 SNPs, J) recombination frequency Illinois 547–1, calculated as the number of obligate crossovers per progeny per Mb.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0134880.g004: Visualization of 'Horizon' x Illinois 547–1 genomic data.Data are shown on 1 Mb windows with a 100 Kb slide. A) Number of unique tags aligned, B) Mean tag depth calculated as total tag depth over number of unique tags aligned, C) Density of SNPs entering the HetMappS pipeline, D) Minor allele frequency (MAF) of SNPs entering the pipeline, E-J) SNP output from the synteny pipeline: E) SNP density ‘Horizon’, F) MAF ‘Horizon’ SNPs, G) Recombination frequency ‘Horizon’, calculated as the number of obligate crossovers per progeny per Mb, H) SNP density Illinois 547–1, I) MAF Illinois 547–1 SNPs, J) recombination frequency Illinois 547–1, calculated as the number of obligate crossovers per progeny per Mb.
Mentions: Unique tag alignment density, mean tag depth, SNP density entering the pipeline, and minor allele frequency (MAF) of SNPs entering the pipeline were visualized on 1 MB sliding windows with a 100 KB slide using Circos [53]. Additionally, for both parents, phased SNP density (output of HetMappS synteny pipeline), MAF, and recombination frequency (obligate crossovers per progeny per MB) were visualized across these windows (Fig 4, S5 Fig, S6 Fig and S7 Fig).

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.


Related in: MedlinePlus