A pipeline for high throughput detection and mapping of SNPs from EST databases

Single nucleotide polymorphisms (SNPs) represent the most abundant type of genetic variation that can be used as molecular markers. The SNPs that are hidden in sequence databases can be unlocked using bioinformatic tools. For efficient application of these SNPs, the sequence set should be error-free as much as possible, targeting single loci and suitable for the SNP scoring platform of choice. We have developed a pipeline to effectively mine SNPs from public EST databases with or without quality information using QualitySNP software, select reliable SNP and prepare the loci for analysis on the Illumina GoldenGate genotyping platform. The applicability of the pipeline was demonstrated using publicly available potato EST data, genotyping individuals from two diploid mapping populations and subsequently mapping the SNP markers (putative genes) in both populations. Over 7000 reliable SNPs were identified that met the criteria for genotyping on the GoldenGate platform. Of the 384 SNPs on the SNP array approximately 12% dropped out. For the two potato mapping populations 165 and 185 SNPs segregating SNP loci could be mapped on the respective genetic maps, illustrating the effectiveness of our pipeline for SNP selection and validation

Association between Knops blood group polymorphisms and susceptibility to malaria in an endemic area of the Brazilian Amazon

Complement receptor 1 (CR1) gene polymorphisms that are associated with Knops blood group antigens may influence the binding of Plasmodium parasites to erythrocytes, thereby affecting susceptibility to malaria. The aim of this study was to evaluate the genotype and allele and haplotype frequencies of single-nucleotide polymorphisms (SNPs) of Knops blood group antigens and examine their association with susceptibility to malaria in an endemic area of Brazil. One hundred and twenty-six individuals from the Brazilian Amazon were studied. The CR1-genomic fragment was amplified by PCR and six SNPs and haplotypes were identified after DNA sequence analysis. Allele and haplotype frequencies revealed that the Knb allele and H8 haplotype were possibly associated with susceptibility to Plasmodium falciparum. The odds ratios were reasonably high, suggesting a potentially important association between two Knops blood antigens (Knb and KAM+) that confer susceptibility to P. falciparum in individuals from the Brazilian Amazon

Processing and analyzing multiple genomes alignments with MafFilter

As the number of available genome sequences from both closely related species and individuals withinspecies increased, theoretical and methodological convergences between the fields of phylogenomics andpopulation genomics emerged. Population genomics typically focuses on the analysis of variants, whilephylogenomics heavily relies on genome alignments. However, these are playing an increasingly importantrole in studies at the population level. Multiple genome alignments of individuals are used when structuralvariation is of primary interest and when genome architecture permits to assemblede novogenomesequences. Here I describe MafFilter, a command-line-driven program allowing to process genome align-ments in the Multiple Alignment Format (MAF). Using concrete examples based on publicly availabledatasets, I demonstrate how MafFilter can be used to develop efficient and reproducible pipelines withquality assurance for downstream analyses. I further show how MafFilter can be used to perform both basicand advanced population genomic analyses in order to infer the patterns of nucleotide diversity alonggenomes

Next generation sequencing has lower sequence coverage and poorer SNP-detection capability in the regulatory regions

The rapid development of next generation sequencing (NGS) technology provides a new chance to extend the scale and resolution of genomic research. How to efficiently map millions of short reads to the reference genome and how to make accurate SNP calls are two major challenges in taking full advantage of NGS. In this article, we reviewed the current software tools for mapping and SNP calling, and evaluated their performance on samples from The Cancer Genome Atlas (TCGA) project. We found that BWA and Bowtie are better than the other alignment tools in comprehensive performance for Illumina platform, while NovoalignCS showed the best overall performance for SOLiD. Furthermore, we showed that next-generation sequencing platform has significantly lower coverage and poorer SNP-calling performance in the CpG islands, promoter and 5′-UTR regions of the genome. NGS experiments targeting for these regions should have higher sequencing depth than the normal genomic region

Improved Detection of Rare Genetic Variants for Diseases

Technology advances have promoted gene-based sequencing studies with the aim of identifying rare mutations responsible for complex diseases. A complication in these types of association studies is that the vast majority of non-synonymous mutations are believed to be neutral to phenotypes. It is thus critical to distinguish potential causative variants from neutral variation before performing association tests. In this study, we used existing predicting algorithms to predict functional amino acid substitutions, and incorporated that information into association tests. Using simulations, we comprehensively studied the effects of several influential factors, including the sensitivity and specificity of functional variant predictions, number of variants, and proportion of causative variants, on the performance of association tests. Our results showed that incorporating information regarding functional variants obtained from existing prediction algorithms improves statistical power under certain conditions, particularly when the proportion of causative variants is moderate. The application of the proposed tests to a real sequencing study confirms our conclusions. Our work may help investigators who are planning to pursue gene-based sequencing studies

Genome-culture coevolution promotes rapid divergence of killer whale ecotypes.

Analysing population genomic data from killer whale ecotypes, which we estimate have globally radiated within less than 250,000 years, we show that genetic structuring including the segregation of potentially functional alleles is associated with socially inherited ecological niche. Reconstruction of ancestral demographic history revealed bottlenecks during founder events, likely promoting ecological divergence and genetic drift resulting in a wide range of genome-wide differentiation between pairs of allopatric and sympatric ecotypes. Functional enrichment analyses provided evidence for regional genomic divergence associated with habitat, dietary preferences and post-zygotic reproductive isolation. Our findings are consistent with expansion of small founder groups into novel niches by an initial plastic behavioural response, perpetuated by social learning imposing an altered natural selection regime. The study constitutes an important step towards an understanding of the complex interaction between demographic history, culture, ecological adaptation and evolution at the genomic level

A Comprehensive Map of Mobile Element Insertion Polymorphisms in Humans

As a consequence of the accumulation of insertion events over evolutionary time, mobile elements now comprise nearly half of the human genome. The Alu, L1, and SVA mobile element families are still duplicating, generating variation between individual genomes. Mobile element insertions (MEI) have been identified as causes for genetic diseases, including hemophilia, neurofibromatosis, and various cancers. Here we present a comprehensive map of 7,380 MEI polymorphisms from the 1000 Genomes Project whole-genome sequencing data of 185 samples in three major populations detected with two detection methods. This catalog enables us to systematically study mutation rates, population segregation, genomic distribution, and functional properties of MEI polymorphisms and to compare MEI to SNP variation from the same individuals. Population allele frequencies of MEI and SNPs are described, broadly, by the same neutral ancestral processes despite vastly different mutation mechanisms and rates, except in coding regions where MEI are virtually absent, presumably due to strong negative selection. A direct comparison of MEI and SNP diversity levels suggests a differential mobile element insertion rate among populations