Characterising the contribution of rare protein-coding germline variants to prostate cancer risk and severity in 37,184 cases

The etiology of prostate cancer, the second most common cancer in men globally, has a strong heritable component. While rare coding germline variants in several genes have been identified as risk factors from candidate gene and linkage studies, the exome-wide spectrum of causal rare variants remains to be fully explored. To more comprehensively address their contribution, we analysed data from 37,184 prostate cancer cases and 331,329 male controls from five cohorts with germline exome/genome sequencing and one cohort with imputed array data from a population enriched in low-frequency deleterious variants. Our gene-level collapsing analysis revealed that rare damaging variants in SAMHD1 as well as genes in the DNA damage response pathway ( BRCA2 , ATM and CHEK2 ) are associated with the risk of overall prostate cancer. We also found that rare damaging variants in AOX1 and BRCA2 were associated with increased severity of prostate cancer in a case-only analysis of aggressive versus non-aggressive prostate cancer. At the single-variant level, we found rare non-synonymous variants in three genes ( HOXB13 , CHEK2 , BIK ) significantly associated with increased risk of overall prostate cancer and in four genes ( ANO7 , SPDL1 , AR , TERT ) with decreased risk. Altogether, this study provides deeper insights into the genetic architecture and biological basis of prostate cancer risk and severity.

Ancestry adjustment improves genome-wide estimates of regional intolerance

Genomic regions subject to purifying selection are more likely to carry disease-causing mutations than regions not under selection. Cross species conservation is often used to identify such regions but with limited resolution to detect selection on short evolutionary timescales such as that occurring in only one species. In contrast, genetic intolerance looks for depletion of variation relative to expectation within a species, allowing species-specific features to be identified. When estimating the intolerance of noncoding sequence, methods strongly leverage variant frequency distributions. As the expected distributions depend on ancestry, if not properly controlled for, ancestral population source may obfuscate signals of selection. We demonstrate that properly incorporating ancestry in intolerance estimation greatly improved variant classification. We provide a genome-wide intolerance map that is conditional on ancestry and likely to be particularly valuable for variant prioritization.

meaRtools: An R package for the analysis of neuronal networks recorded on microelectrode arrays

Here we present an open-source R package 'meaRtools' that provides a platform for analyzing neuronal networks recorded on Microelectrode Arrays (MEAs). Cultured neuronal networks monitored with MEAs are now being widely used to characterize in vitro models of neurological disorders and to evaluate pharmaceutical compounds. meaRtools provides core algorithms for MEA spike train analysis, feature extraction, statistical analysis and plotting of multiple MEA recordings with multiple genotypes and treatments. meaRtools functionality covers novel solutions for spike train analysis, including algorithms to assess electrode cross-correlation using the spike train tiling coefficient (STTC), mutual information, synchronized bursts and entropy within cultured wells. Also integrated is a solution to account for bursts variability originating from mixed-cell neuronal cultures. The package provides a statistical platform built specifically for MEA data that can combine multiple MEA recordings and compare extracted features between different genetic models or treatments. We demonstrate the utilization of meaRtools to successfully identify epilepsy-like phenotypes in neuronal networks from Celf4 knockout mice. The package is freely available under the GPL license (GPL> = 3) and is updated frequently on the CRAN web-server repository. The package, along with full documentation can be downloaded from: https://cran.r-project.org/web/packages/meaRtools/.

Codon usage in plant peroxidase genes

Codon preference and asymmetry in usage in the DNA sequences encoding the mature enzyme protein of 24 plant peroxidases from 12 different species were examined. Codon usage in highly conserved/non-conserved areas of the sequences was analysed, as well as possible deficiency/excess in CpG dinucleotides in the pairs of codon positions. Sequence relationships displayed by overall codon usage, dinucleotide frequencies within codons, and amino acid sequences were also studied. The main findings were: (1) Monocots clustered separately from dicots for overall codon usage and dinucleotide frequencies in codon positions 2 and 3, with six and seven clusters respectively discernible among these 24 peroxidase sequences. The monocot/dicot distinction disappeared in the four clusters among the mature protein amino acid sequences. Overall codon usage in sequences from monocotyledon and dicotyledon species differed, the monocots favouring codons with C or G in the third position. (2) Codon usage was biassed in many sequences, asymmetry was particularly noticeable in the monocots. (3) For repeated amino acids within conserved areas, codon preference appeared dependent on the order in which the repeated amino acid occurred, so that its usage of synonymous codons frequently balanced out.