Biology subjects

Gunsalus, K.

Publications and source records attributed to Gunsalus, K..

3 recordsLinked to original sources

bioRxiv2018

Tissue- and sex-specific small RNAomes reveal sex differences in response to the environment

BackgroundRNA interference (RNAi) related pathways are essential for germline development and fertility in metazoa and can contribute to inter-and trans-generational inheritance. In the nematode Caenorhabditis elegans environmental double-stranded RNA provided by feeding can lead to heritable changes in phenotype and gene expression. Notably, transmission efficiency differs between the male and female germline, yet the underlying mechanisms remain elusive.\n\nResultsHere we use high-throughput sequencing of dissected gonads to quantify sex-specific endogenous piRNAs, miRNAs and siRNAs in the C. elegans germline and the somatic gonad. We identify genes with exceptionally high levels of 22G RNAs that are associated with low mRNA expression, a signature compatible with silencing. We further demonstrate that contrary to the hermaphrodite germline, the male germline, but not male soma, is resistant to environmental RNAi triggers provided by feeding. This sex-difference in silencing efficacy is associated with lower levels of gonadal RNAi amplification products. Moreover, this tissue-and sex-specific RNAi resistance is regulated by the germline, since mutant males with a feminized germline are RNAi sensitive.\n\nConclusionThis study provides important sex-and tissue-specific expression data of miRNA, piRNA and siRNA as well as mechanistic insights into sex-differences of gene regulation in response to environmental cues.

genomics↗

bioRxiv2018

Evolutionary analysis implicates RNA polymerase II pausing and chromatin structure in nematode piRNA biogenesis

Piwi-interacting RNAs (piRNAs) control transposable elements widely across metazoans but have rapidly evolving biogenesis pathways. In Caenorhabditis elegans, almost all piRNA loci are found within two 3Mb clusters on Chromosome IV. Each piRNA locus possesses an upstream motif that recruits RNA polymerase II to produce a [~]28 nt precursor transcript. Here, we use comparative epigenomics across nematodes to gain insight into piRNA biogenesis. We show that the piRNA upstream motif is derived from core promoter elements controlling snRNA biogenesis. We describe two alternative modes of piRNA organisation in nematodes: in C. elegans and closely related nematodes, piRNAs are clustered within repressive H3K27me3 chromatin, whilst in other species, typified by Pristionchus pacificus, piRNAs are distributed genome-wide within introns of actively transcribed genes. In both groups, piRNA production depends on downstream sequence signals associated with RNA polymerase II pausing, which synergise with the chromatin environment to control piRNA precursor transcription.

genomics↗

bioRxiv2017

Pheniqs: Fast and flexible quality-aware sequence demultiplexing

1MotivationOutput from high throughput sequencing instruments often exceeds what is necessary to assay a single sample. To better utilize this capacity, multiple samples are independently tagged with a unique \"barcode\" sequence and are then pooled, or \"multiplexed\", and sequenced together. Classifying, or \"demultiplexing\", the reads involves decoding the barcode sequence. Although instruments estimate the probability of incorrectly calling each nucleobase, available demultiplexers do not consult those estimates or report classification error probabilities.\n\nResultsWe present Pheniqs, a fast and flexible sequence demultiplexer and quality analyzer. In addition to providing an efficient implementation of the widespread minimum distance decoder, Pheniqs introduces a novel Phred-adjusted maximum likelihood decoder that consults base calling quality scores and estimates the probability of a barcode decoding error. Setting an upper bound on the permissible error provides an intuitive way to control demultiplexing confidence and directly influence precision and recall. Pheniqs supports FASTQ and multiple Sequence Alignment/Map formats and uses auxiliary SAM tags to report both library classification and demultiplexing error probability. Evaluation on both real and semi-synthetic data indicates that Pheniqs is faster than existing demultiplexers, substantially when demultiplexing longer reads, and achieves greater accuracy by correctly reflecting quality measurements.\n\nAvailability and ImplementationImplemented in multithreaded C++ and available under the terms of the AGPL-3.0 license agreement at http://github.com/biosails/pheniqs. Manual and examples are available at http://biosails.github.io/pheniqs.

bioinformatics↗