SUMMARY: We describe a novel computational method for genotyping repeats using sequence graphs. This method addresses the long-standing need to accurately genotype medically important loci containing repeats adjacent to other variants or imperfect DNA repeats such as polyalanine repeats. Here we introduce a new version of our repeat genotyping software, ExpansionHunter, that uses this method to perform targeted genotyping of a broad class of such loci. AVAILABILITY AND IMPLEMENTATION: ExpansionHunter is implemented in C++ and is available under the Apache License Version 2.0. The source code, documentation, and Linux/macOS binaries are available at https://github.com/Illumina/ExpansionHunter/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: Genomic information allows population relatedness to be inferred and selected genes to be identified. Single nucleotide polymorphism microarray (SNP-chip) data, a proxy for genome composition, contains patterns in allele order and proportion. These patterns can be quantified by compression efficiency (CE). In principle, the composition of an entire genome can be represented by a CE number quantifying allele representation and order. RESULTS: We applied a compression algorithm (DEFLATE) to genome-wide high-density SNP data from 4,155 human, 1,800 cattle, 1,222 sheep, 81 dogs and 49 mice samples. All human ethnic groups can be clustered by CE and the clusters recover phylogeography based on traditional fixation index (FST) analyses. CE analysis of other mammals results in segregation by breed or species, and is sensitive to admixture and past effective population size. This clustering is a consequence of individual patterns such as runs of homozygosity. Intriguingly, a related approach can also be used to identify genomic loci that show population-specific CE segregation. A high resolution CE 'sliding window' scan across the human genome, organised at the population level, revealed genes known to be under evolutionary pressure. These include SLC24A5 (European and Gujarati Indian skin pigmentation), HERC2 (European eye color), LCT (European and Maasai milk digestion) and EDAR (Asian hair thickness). We also identified a set of previously unidentified loci with high population-specific CE scores including the chromatin remodeler SCMH1 in Africans and EDA2R in Asians. Closer inspection reveals that these prioritised genomic regions do not correspond to simple runs of homozygosity but rather compositionally complex regions that are shared by many individuals of a given population. Unlike FST, CE analyses do not require ab initio population comparisons and are amenable to the hemizygous X chromosome. CONCLUSIONS: We conclude with a discussion of the implications of CE for a complex systems science view of genome evolution. CE allows one to clearly visualise the evolution of individual genomes and populations through a formal, mathematically-rigorous information space. Overall, CE makes a set of biological predictions, some of which are unique and await functional validation.

MOTIVATION: Comparing transcriptomic data with proteomic data to identify protein-coding sequences is a long-standing challenge in molecular biology, one that is exacerbated by the increasing size of high-throughput datasets. To address this challenge, and thereby to improve the quality of genome annotation and understanding of genome biology, we have developed an integrated suite of programs, called Pinstripe. We demonstrate its application, utility and discovery power using transcriptomic and proteomic data from publicly available datasets. RESULTS: To demonstrate the efficacy of Pinstripe for large-scale analysis, we applied Pinstripe's reverse peptide mapping pipeline to a transcript library including de novo assembled transcriptomes from the human Illumina Body Atlas (IBA2) and GENCODE v10 gene annotations, and the EBI Proteomics Identifications Database (PRIDE) peptide database. This analysis identified 736 canonical open reading frames (ORFs) supported by three or more PRIDE peptide fragments that are positioned outside any known coding DNA sequence (CDS). Because of the unfiltered nature of the PRIDE database and high probability of false discovery, we further refined this list using independent evidence for translation, including the presence of a Kozak sequence or functional domains, synonymous/non-synonymous substitution ratios and ORF length. Using this integrative approach, we observed evidence of translation from a previously unknown let7e primary transcript, the archetypical lncRNA H19, and a homolog of RD3. Reciprocally, by exclusion of transcripts with mapped peptides or significant ORFs (>80 codon), we identify 32 187 loci with RNAs longer than 2000 nt that are unlikely to encode proteins. AVAILABILITY AND IMPLEMENTATION: Pinstripe (pinstripe.matticklab.com) is freely available as source code or a Mono binary. Pinstripe is written in C# and runs under the Mono framework on Linux or Mac OS X, and both under Mono and .Net under Windows. CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.