Abstract
BackgroundSequence information generated from next generation sequencing is often computationally phased using haplotype-phasing algorithms. Utilizing experimentally derived allele or haplotype information improves this prediction, as routinely used in HLA typing. We recently established a large dataset of long ERMAP alleles, which code for protein variants in the Scianna blood group system. We propose the phylogeny of this set of 48 alleles and identify evolutionary steps to derive the observed alleles.MethodsThe nucleotide sequence of > 21 kb each was used for all physically confirmed 48 ERMAP alleles that we previously published. Full-length sequences were aligned and variant sites were extracted manually. The Bayesian coalescent algorithm implemented in BEAST v1.8.3 was used to estimate a coalescent phylogeny for these variants and the allelic ancestral states at the internal nodes of the phylogeny.ResultsThe phylogenetic analysis allowed us to identify the evolutionary relationships among the 48 ERMAP alleles, predict 4243 potential ancestral alleles and calculate a posterior probability for each of these unobserved alleles. Some of them coincide with observed alleles that are extant in the population.ConclusionsOur proposed strategy places known alleles in a phylogenetic framework, allowing us to describe as-yet-undiscovered alleles. In this new approach, which relies heavily on the accuracy of the alleles used for the phylogenetic analysis, an expanded set of predicted alleles can be used to infer alleles when large genotype data are analyzed, as typically generated by high-throughput sequencing. The alleles identified by studies like ours may be utilized in designing of microarray technologies, imputing of genotypes and mapping of next generation sequencing data.
Highlights
Sequence information generated from generation sequencing is often computationally phased using haplotype-phasing algorithms
The ERMAP gene, located on chromosome 1, encodes the glycoprotein carrying the antigens of the Scianna blood group system (SC; ISBT 013) in humans [13,14,15]
We propose using the phylogeny of this set of 48 alleles and identifying evolutionary steps to derive the observed alleles [22]
Summary
Sequence information generated from generation sequencing is often computationally phased using haplotype-phasing algorithms. Utilizing experimentally derived allele or haplotype information improves this prediction, as routinely used in HLA typing. We recently established a large dataset of long ERMAP alleles, which code for protein variants in the Scianna blood group system. The large genotype datasets from generation sequencing (NGS) can be phased into alleles or haplotypes [5, 6]. The ERMAP gene, located on chromosome 1, encodes the glycoprotein carrying the antigens of the Scianna blood group system (SC; ISBT 013) in humans [13,14,15]. The gene belongs to the butyrophilin (BTN) family which is a type 1 membrane protein of the immunoglobulin (Ig) superfamily [18]. The butyrophilin and butyrophilin-like proteins have recently been studied as potentially important immune regulators [19, 20]
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