Sampling strategies for accurate computational inferences of gametic phase across highly polymorphic major histocompatibility complex loci

<p>Abstract</p> <p>Background</p> <p>Genes of the Major Histocompatibility Complex (MHC) are very popular genetic markers among evolutionary biologists because of their potential role in pathogen confrontation and sexual selection. However, MHC genotyping still remains...

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Main Authors: Rodríguez Airam, Alcaide Miguel, Negro Juan J
Format: Article
Language:English
Published: BMC 2011-05-01
Series:BMC Research Notes
Online Access:http://www.biomedcentral.com/1756-0500/4/151
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spelling doaj-5b0a5c7b46cc423aac200a354f6452e72020-11-24T21:50:06ZengBMCBMC Research Notes1756-05002011-05-014115110.1186/1756-0500-4-151Sampling strategies for accurate computational inferences of gametic phase across highly polymorphic major histocompatibility complex lociRodríguez AiramAlcaide MiguelNegro Juan J<p>Abstract</p> <p>Background</p> <p>Genes of the Major Histocompatibility Complex (MHC) are very popular genetic markers among evolutionary biologists because of their potential role in pathogen confrontation and sexual selection. However, MHC genotyping still remains challenging and time-consuming in spite of substantial methodological advances. Although computational haplotype inference has brought into focus interesting alternatives, high heterozygosity, extensive genetic variation and population admixture are known to cause inaccuracies. We have investigated the role of sample size, genetic polymorphism and genetic structuring on the performance of the popular Bayesian PHASE algorithm. To cover this aim, we took advantage of a large database of known genotypes (using traditional laboratory-based techniques) at single MHC class I (N = 56 individuals and 50 alleles) and MHC class II B (N = 103 individuals and 62 alleles) loci in the lesser kestrel <it>Falco naumanni</it>.</p> <p>Findings</p> <p>Analyses carried out over real MHC genotypes showed that the accuracy of gametic phase reconstruction improved with sample size as a result of the reduction in the allele to individual ratio. We then simulated different data sets introducing variations in this parameter to define an optimal ratio.</p> <p>Conclusions</p> <p>Our results demonstrate a critical influence of the allele to individual ratio on PHASE performance. We found that a minimum allele to individual ratio (1:2) yielded 100% accuracy for both MHC loci. Sampling effort is therefore a crucial step to obtain reliable MHC haplotype reconstructions and must be accomplished accordingly to the degree of MHC polymorphism. We expect our findings provide a foothold into the design of straightforward and cost-effective genotyping strategies of those MHC loci from which locus-specific primers are available.</p> http://www.biomedcentral.com/1756-0500/4/151
collection DOAJ
language English
format Article
sources DOAJ
author Rodríguez Airam
Alcaide Miguel
Negro Juan J
spellingShingle Rodríguez Airam
Alcaide Miguel
Negro Juan J
Sampling strategies for accurate computational inferences of gametic phase across highly polymorphic major histocompatibility complex loci
BMC Research Notes
author_facet Rodríguez Airam
Alcaide Miguel
Negro Juan J
author_sort Rodríguez Airam
title Sampling strategies for accurate computational inferences of gametic phase across highly polymorphic major histocompatibility complex loci
title_short Sampling strategies for accurate computational inferences of gametic phase across highly polymorphic major histocompatibility complex loci
title_full Sampling strategies for accurate computational inferences of gametic phase across highly polymorphic major histocompatibility complex loci
title_fullStr Sampling strategies for accurate computational inferences of gametic phase across highly polymorphic major histocompatibility complex loci
title_full_unstemmed Sampling strategies for accurate computational inferences of gametic phase across highly polymorphic major histocompatibility complex loci
title_sort sampling strategies for accurate computational inferences of gametic phase across highly polymorphic major histocompatibility complex loci
publisher BMC
series BMC Research Notes
issn 1756-0500
publishDate 2011-05-01
description <p>Abstract</p> <p>Background</p> <p>Genes of the Major Histocompatibility Complex (MHC) are very popular genetic markers among evolutionary biologists because of their potential role in pathogen confrontation and sexual selection. However, MHC genotyping still remains challenging and time-consuming in spite of substantial methodological advances. Although computational haplotype inference has brought into focus interesting alternatives, high heterozygosity, extensive genetic variation and population admixture are known to cause inaccuracies. We have investigated the role of sample size, genetic polymorphism and genetic structuring on the performance of the popular Bayesian PHASE algorithm. To cover this aim, we took advantage of a large database of known genotypes (using traditional laboratory-based techniques) at single MHC class I (N = 56 individuals and 50 alleles) and MHC class II B (N = 103 individuals and 62 alleles) loci in the lesser kestrel <it>Falco naumanni</it>.</p> <p>Findings</p> <p>Analyses carried out over real MHC genotypes showed that the accuracy of gametic phase reconstruction improved with sample size as a result of the reduction in the allele to individual ratio. We then simulated different data sets introducing variations in this parameter to define an optimal ratio.</p> <p>Conclusions</p> <p>Our results demonstrate a critical influence of the allele to individual ratio on PHASE performance. We found that a minimum allele to individual ratio (1:2) yielded 100% accuracy for both MHC loci. Sampling effort is therefore a crucial step to obtain reliable MHC haplotype reconstructions and must be accomplished accordingly to the degree of MHC polymorphism. We expect our findings provide a foothold into the design of straightforward and cost-effective genotyping strategies of those MHC loci from which locus-specific primers are available.</p>
url http://www.biomedcentral.com/1756-0500/4/151
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