High-specificity detection of rare alleles with Paired-End Low Error Sequencing (PELE-Seq).

BACKGROUND: Polymorphic loci exist throughout the genomes of a population and provide the raw genetic material needed for a species to adapt to changes in the environment. The minor allele frequencies of rare Single Nucleotide Polymorphisms (SNPs) within a population have been difficult to track with Next-Generation Sequencing (NGS), due to the high error rate of standard methods such as Illumina sequencing. RESULTS: We have developed a wet-lab protocol and variant-calling method that identifies both sequencing and PCR errors, called Paired-End Low Error Sequencing (PELE-Seq). To test the specificity and sensitivity of the PELE-Seq method, we sequenced control E. coli DNA libraries containing known rare alleles present at frequencies ranging from 0.2-0.4 % of the total reads. PELE-Seq had higher specificity and sensitivity than standard libraries. We then used PELE-Seq to characterize rare alleles in a Caenorhabditis remanei nematode worm population before and after laboratory adaptation, and found that minor and rare alleles can undergo large changes in frequency during lab-adaptation. CONCLUSION: We have developed a method of rare allele detection that mitigates both sequencing and PCR errors, called PELE-Seq. PELE-Seq was evaluated using control E. coli populations and was then used to compare a wild C. remanei population to a lab-adapted population. The PELE-Seq method is ideal for investigating the dynamics of rare alleles in a broad range of reduced-representation sequencing methods, including targeted amplicon sequencing, RAD-Seq, ddRAD, and GBS. PELE-Seq is also well-suited for whole genome sequencing of mitochondria and viruses, and for high-throughput rare mutation screens.

Genome-wide identification of hypoxia-induced enhancer regions.

Here we present a genome-wide method for de novo identification of enhancer regions. This approach enables massively parallel empirical investigation of DNA sequences that mediate transcriptional activation and provides a platform for discovery of regulatory modules capable of driving context-specific gene expression. The method links fragmented genomic DNA to the transcription of randomer molecule identifiers and measures the functional enhancer activity of the library by massively parallel sequencing. We transfected a Drosophila melanogaster library into S2 cells in normoxia and hypoxia, and assayed 4,599,881 genomic DNA fragments in parallel. The locations of the enhancer regions strongly correlate with genes up-regulated after hypoxia and previously described enhancers. Novel enhancer regions were identified and integrated with RNAseq data and transcription factor motifs to describe the hypoxic response on a genome-wide basis as a complex regulatory network involving multiple stress-response pathways. This work provides a novel method for high-throughput assay of enhancer activity and the genome-scale identification of 31 hypoxia-activated enhancers in Drosophila.

Brazilian Anopheles darlingi Root (Diptera: Culicidae) Clusters by Major Biogeographical Region.

The major drivers of the extensive biodiversity of the Neotropics are proposed to be geological and tectonic events together with Pliocene and Pleistocene environmental and climatic change. Geographical barriers represented by the rivers Amazonas/Solimões, the Andes and the coastal mountain ranges in eastern Brazil have been hypothesized to lead to diversification within the primary malaria vector, Anopheles (Nyssorhynchus) darlingi Root, which primarily inhabits rainforest. To test this biogeographical hypothesis, we analyzed 786 single nucleotide polymorphisms (SNPs) in 12 populations of An. darlingi from across the complex Brazilian landscape. Both model-based (STRUCTURE) and non-model-based (Principal Components and Discriminant Analysis) analysis of population structure detected three major genetic clusters that correspond with newly described Neotropical biogeographical regions: 1) Atlantic Forest province (= southeast population); 2) Parana Forest province (= West Atlantic forest population, with one Chacoan population - SP); and 3) Brazilian dominion population (= Amazonian population with one Chacoan population - TO). Significant levels of pairwise genetic divergences were found among the three clusters, allele sharing among clusters was negligible, and geographical distance did not contribute to differentiation. We infer that the Atlantic forest coastal mountain range limited dispersal between the Atlantic Forest province and the Parana Forest province populations, and that the large, diagonal open vegetation region of the Chacoan dominion dramatically reduced dispersal between the Parana and Brazilian dominion populations. We hypothesize that the three genetic clusters may represent three putative species.