Reversed sex-biased mutation rates for indels and base substitutions in Drosophila melanogaster

Sex biases in mutation rates may affect the rate of adaptive evolution. In many species, males have higher mutation rates than females when single nucleotide variants (SNVs) are considered. In contrast, indel mutations in humans and chimpanzees are female-biased. In Drosophila melanogaster, direct estimates of mutation rates did not uncover sex differences, but a recent analysis suggested the presence of male-biased SNVs mutations. Here we study the sex-specific mutation processes using mutation accumulation data from mismatch-repair deficient D. melanogaster. We find that sex differences in flies are similar to the ones observed in humans: a higher mutation rate for SNVs in males and a higher indel rate in females. These results have major implications for the study of neutral variation and adaptation in Drosophila.

ntEdit: scalable genome sequence polishing

Motivation In the modern genomics era, genome sequence assemblies are routine practice. However, depending on the methodology, resulting drafts may contain considerable base errors. Although utilities exist for genome base polishing, they work best with high read coverage and do not scale well. We developed ntEdit, a Bloom filter-based genome sequence editing utility that scales to large mammalian and conifer genomes. Results We first tested ntEdit and the state-of-the-art assembly improvement tools GATK, Pilon and Racon on controlled Escherichia coli and Caenorhabditis elegans sequence data. Generally, ntEdit performs well at low sequence depths (<20×), fixing the majority (>97%) of base substitutions and indels, and its performance is largely constant with increased coverage. In all experiments conducted using a single CPU, the ntEdit pipeline executed in <14 s and <3 m, on average, on E.coli and C.elegans, respectively. We performed similar benchmarks on a sub-20× coverage human genome sequence dataset, inspecting accuracy and resource usage in editing chromosomes 1 and 21, and whole genome. ntEdit scaled linearly, executing in 30–40 m on those sequences. We show how ntEdit ran in <2 h 20 m to improve upon long and linked read human genome assemblies of NA12878, using high-coverage (54×) Illumina sequence data from the same individual, fixing frame shifts in coding sequences. We also generated 17-fold coverage spruce sequence data from haploid sequence sources (seed megagametophyte), and used it to edit our pseudo haploid assemblies of the 20 Gb interior and white spruce genomes in <4 and <5 h, respectively, making roughly 50M edits at a (substitution+indel) rate of 0.0024. Availability and implementation https://github.com/bcgsc/ntedit Supplementary information Supplementary data are available at Bioinformatics online.

Mismatch-repair signature mutations activate gene enhancers across colorectal cancer epigenomes

Commonly-mutated genes have been found for many cancers, but less is known about mutations in cis-regulatory elements. We leverage gains in tumor-specific enhancer activity, coupled with allele-biased mutation detection from H3K27ac ChIP-seq data, to pinpoint potential enhancer-activating mutations in colorectal cancer (CRC). Analysis of a genetically-diverse cohort of CRC specimens revealed that microsatellite instable (MSI) samples have a high indel rate within active enhancers. Enhancers with indels show evidence of positive selection, increased target gene expression, and a subset is highly recurrent. The indels affect short homopolymer tracts of A/T and increase affinity for FOX transcription factors. We further demonstrate that signature mismatch-repair (MMR) mutations activate enhancers using a xenograft tumor metastasis model, where mutations are induced naturally via CRISPR/Cas9 inactivation of MLH1 prior to tumor cell injection. Our results suggest that MMR signature mutations activate or augment enhancers in CRC tumor epigenomes to provide a selective advantage.

Protocol: Genome-scale CRISPR-Cas9 Knockout and Transcriptional Activation Screening

Forward genetic screens are powerful tools for the unbiased discovery and functional characterization of specific genetic elements associated with a phenotype of interest. Recently, the RNA-guided endonuclease Cas9 from the microbial immune system CRISPR (clustered regularly interspaced short palindromic repeats) has been adapted for genome-scale screening by combining Cas9 with guide RNA libraries. Here we describe a protocol for genome-scale knockout and transcriptional activation screening using the CRISPR-Cas9 system. Custom-or ready-made guide RNA libraries are constructed and packaged into lentivirus for delivery into cells for screening. As each screen is unique, we provide guidelines for determining screening parameters and maintaining sufficient coverage. To validate candidate genes identified from the screen, we further describe strategies for confirming the screening phenotype as well as genetic perturbation through analysis of indel rate and transcriptional activation. Beginning with library design, a genome-scale screen can be completed in 6-10 weeks followed by 3-4 weeks of validation.

Perturbative formulation of general continuous-time Markov model of sequence evolution via insertions/deletions, Part I: Theoretical basis

BackgroundInsertions and deletions (indels) account for more nucleotide differences between two related DNA sequences than substitutions do, and thus it is imperative to develop a stochastic evolutionary model that enables us to reliably calculate the probability of the sequence evolution through indel processes. Recently, such probabilistic models are mostly based on either hidden Markov models (HMMs) or transducer theories, both of which give the indel component of the probability of a given sequence alignment as a product of either probabilities of column-to-column transitions or block-wise contributions along the alignment. However, it is not a priori clear how these models are related with any genuine stochastic evolutionary model, which describes the stochastic evolution of an entire sequence along the time-axis. Moreover, none of these models can fully accommodate biologically realistic features, such as overlapping indels, power-law indel-length distributions, and indel rate variation across regions.ResultsHere, we theoretically tackle the ab initio calculation of the probability of a given sequence alignment under a genuine evolutionary model, more specifically, a general continuous-time Markov model of the evolution of an entire sequence via insertions and deletions. Our model allows general indel rate parameters including length distributions but does not impose any unrealistic restrictions on indels. Using techniques of the perturbation theory in physics, we expand the probability into a series over different numbers of indels. Our derivation of this perturbation expansion elegantly bridges the gap between Gillespie’s (1977) intuitive derivation of his own stochastic simulation method, which is now widely used in evolutionary simulators, and Feller’s (1940) mathematically rigorous theorems that underpin Gillespie′s method. We find a sufficient and nearly necessary set of conditions under which the probability can be expressed as the product of an overall factor and the contributions from regions separated by gapless columns of the alignment. The indel models satisfying these conditions include those with some kind of rate variation across regions, as well as space-homogeneous models. We also prove that, though with a caveat, pairwise probabilities calculated by the method of Miklós et al. (2004) are equivalent to those calculated by our ab initio formulation, at least under a space-homogenous model.ConclusionsOur ab initio perturbative formulation provides a firm theoretical ground that other indel models can rest on.[This paper and three other papers (Ezawa, Graur and Landan 2015a,b,c) describe a series of our efforts to develop, apply, and extend the ab initio perturbative formulation of a general continuous-time Markov model of indels.]