Genotyping-by-sequencing and SNP-arrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studies
Abstract Background Single Nucleotide Polymorphism (SNP) array and re-sequencing technologies have different properties (e.g. calling rate, minor allele frequency profile) and drawbacks (e.g. ascertainment bias). This lead us to study their complementarity and the consequences of using them separate...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2019-07-01
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| Series: | BMC Plant Biology |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12870-019-1926-4 |
| _version_ | 1818382974618435584 |
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| author | Sandra S. Negro Emilie J. Millet Delphine Madur Cyril Bauland Valérie Combes Claude Welcker François Tardieu Alain Charcosset Stéphane D. Nicolas |
| author_facet | Sandra S. Negro Emilie J. Millet Delphine Madur Cyril Bauland Valérie Combes Claude Welcker François Tardieu Alain Charcosset Stéphane D. Nicolas |
| author_sort | Sandra S. Negro |
| collection | DOAJ |
| description | Abstract Background Single Nucleotide Polymorphism (SNP) array and re-sequencing technologies have different properties (e.g. calling rate, minor allele frequency profile) and drawbacks (e.g. ascertainment bias). This lead us to study their complementarity and the consequences of using them separately or combined in diversity analyses and Genome-Wide Association Studies (GWAS). We performed GWAS on three traits (grain yield, plant height and male flowering time) measured in 22 environments on a panel of 247 F1 hybrids obtained by crossing 247 diverse dent maize inbred lines with a same flint line. The 247 lines were genotyped using three genotyping technologies (Genotyping-By-Sequencing, Illumina Infinium 50 K and Affymetrix Axiom 600 K arrays). Results The effects of ascertainment bias of the 50 K and 600 K arrays were negligible for deciphering global genetic trends of diversity and for estimating relatedness in this panel. We developed an original approach based on linkage disequilibrium (LD) extent in order to determine whether SNPs significantly associated with a trait and that are physically linked should be considered as a single Quantitative Trait Locus (QTL) or several independent QTLs. Using this approach, we showed that the combination of the three technologies, which have different SNP distributions and densities, allowed us to detect more QTLs (gain in power) and potentially refine the localization of the causal polymorphisms (gain in resolution). Conclusions Conceptually different technologies are complementary for detecting QTLs by tagging different haplotypes in association studies. Considering LD, marker density and the combination of different technologies (SNP-arrays and re-sequencing), the genotypic data available were most likely enough to well represent polymorphisms in the centromeric regions, whereas using more markers would be beneficial for telomeric regions. |
| first_indexed | 2024-12-14T02:59:00Z |
| format | Article |
| id | doaj.art-11ba66b919aa45bb8fe07e0f39b4f10f |
| institution | Directory Open Access Journal |
| issn | 1471-2229 |
| language | English |
| last_indexed | 2024-12-14T02:59:00Z |
| publishDate | 2019-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Plant Biology |
| spelling | doaj.art-11ba66b919aa45bb8fe07e0f39b4f10f2022-12-21T23:19:33ZengBMCBMC Plant Biology1471-22292019-07-0119112210.1186/s12870-019-1926-4Genotyping-by-sequencing and SNP-arrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studiesSandra S. Negro0Emilie J. Millet1Delphine Madur2Cyril Bauland3Valérie Combes4Claude Welcker5François Tardieu6Alain Charcosset7Stéphane D. Nicolas8GQE – Le Moulon, INRA, Univ. Paris-Sud, CNRS, AgroParisTech, Université Paris-SaclayLaboratoire d’Ecophysiologie des Plantes sous Stress Environnementaux (LEPSE), UMR759, INRA, SupAgroGQE – Le Moulon, INRA, Univ. Paris-Sud, CNRS, AgroParisTech, Université Paris-SaclayGQE – Le Moulon, INRA, Univ. Paris-Sud, CNRS, AgroParisTech, Université Paris-SaclayGQE – Le Moulon, INRA, Univ. Paris-Sud, CNRS, AgroParisTech, Université Paris-SaclayLaboratoire d’Ecophysiologie des Plantes sous Stress Environnementaux (LEPSE), UMR759, INRA, SupAgroLaboratoire d’Ecophysiologie des Plantes sous Stress Environnementaux (LEPSE), UMR759, INRA, SupAgroGQE – Le Moulon, INRA, Univ. Paris-Sud, CNRS, AgroParisTech, Université Paris-SaclayGQE – Le Moulon, INRA, Univ. Paris-Sud, CNRS, AgroParisTech, Université Paris-SaclayAbstract Background Single Nucleotide Polymorphism (SNP) array and re-sequencing technologies have different properties (e.g. calling rate, minor allele frequency profile) and drawbacks (e.g. ascertainment bias). This lead us to study their complementarity and the consequences of using them separately or combined in diversity analyses and Genome-Wide Association Studies (GWAS). We performed GWAS on three traits (grain yield, plant height and male flowering time) measured in 22 environments on a panel of 247 F1 hybrids obtained by crossing 247 diverse dent maize inbred lines with a same flint line. The 247 lines were genotyped using three genotyping technologies (Genotyping-By-Sequencing, Illumina Infinium 50 K and Affymetrix Axiom 600 K arrays). Results The effects of ascertainment bias of the 50 K and 600 K arrays were negligible for deciphering global genetic trends of diversity and for estimating relatedness in this panel. We developed an original approach based on linkage disequilibrium (LD) extent in order to determine whether SNPs significantly associated with a trait and that are physically linked should be considered as a single Quantitative Trait Locus (QTL) or several independent QTLs. Using this approach, we showed that the combination of the three technologies, which have different SNP distributions and densities, allowed us to detect more QTLs (gain in power) and potentially refine the localization of the causal polymorphisms (gain in resolution). Conclusions Conceptually different technologies are complementary for detecting QTLs by tagging different haplotypes in association studies. Considering LD, marker density and the combination of different technologies (SNP-arrays and re-sequencing), the genotypic data available were most likely enough to well represent polymorphisms in the centromeric regions, whereas using more markers would be beneficial for telomeric regions.http://link.springer.com/article/10.1186/s12870-019-1926-4GWASLinkage disequilibriumGenome coverageMaizeHigh-throughput genotyping technologies |
| spellingShingle | Sandra S. Negro Emilie J. Millet Delphine Madur Cyril Bauland Valérie Combes Claude Welcker François Tardieu Alain Charcosset Stéphane D. Nicolas Genotyping-by-sequencing and SNP-arrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studies BMC Plant Biology GWAS Linkage disequilibrium Genome coverage Maize High-throughput genotyping technologies |
| title | Genotyping-by-sequencing and SNP-arrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studies |
| title_full | Genotyping-by-sequencing and SNP-arrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studies |
| title_fullStr | Genotyping-by-sequencing and SNP-arrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studies |
| title_full_unstemmed | Genotyping-by-sequencing and SNP-arrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studies |
| title_short | Genotyping-by-sequencing and SNP-arrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studies |
| title_sort | genotyping by sequencing and snp arrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studies |
| topic | GWAS Linkage disequilibrium Genome coverage Maize High-throughput genotyping technologies |
| url | http://link.springer.com/article/10.1186/s12870-019-1926-4 |
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