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Background: Boar taint is principally caused by accumulation of androstenone and skatole in adipose tissues. Studies have shown high heritability estimates for androstenone whereas skatole production is mainly dependent on nutritional factors. Androstenone is a lipophilic steroid mainly metabolized in liver. Majority of the studies on hepatic androstenone metabolism focus only on a single breed and very few studies account for population similarities/differences in gene expression patterns. In this work, we concentrated on population similarities in gene expression to identify the common genes involved in hepatic androstenone metabolism of multiple pig populations. Based on androstenone measurements, publicly available gene expression datasets from three porcine populations were compiled into either low or high androstenone dataset. Gene expression correlation coefficients from these datasets were converted to rank ratios and joint probabilities of these rank ratios were used to generate dataset specific co-expression clusters. Finally, these networks were clustered using a graph clustering technique. Results: Cluster analysis identified a number of statistically significant co-expression clusters in the dataset. Further enrichment analysis of these clusters showed that one of the clusters from low androstenone dataset was highly enriched for xenobiotic, drug, cholesterol and lipid metabolism and cytochrome P450 associated metabolism of drugs and xenobiotics. Literature references revealed that a number of genes in this cluster were involved in phase I and phase II metabolism. Physical and functional similarity assessment showed that the members of this cluster were dispersed across multiple clusters in high androstenone dataset, possibly indicating a weak co-expression of these genes in high androstenone dataset. Conclusions: Based on these results we hypothesize that majority of the genes in this cluster forms a signature co-expression cluster in low androstenone dataset in our experiment and that majority of the members of this cluster might be responsible for hepatic androstenone metabolism across all the three populations used in our study. We propose these results as a background work towards understanding breed similarities in hepatic androstenone metabolism. Additional large scale experiments using data from multiple porcine breeds are necessary to validate these findings. [ABSTRACT FROM AUTHOR]

Summary: Transcriptome-wide detection of binding sites of RNA-binding proteins is achieved using Individual-nucleotide crosslinking and immunoprecipitation (iCLIP) and its derivative enhanced CLIP (eCLIP) sequencing methods. Here, we introduce htseq-clip, a python package developed for preprocessing, extracting and summarizing crosslink site counts from i/eCLIP experimental data. The package delivers crosslink site count matrices along with other metrics, which can be directly used for filtering and downstream analyses such as the identification of differential binding sites., Availability and Implementation: The Python package htseq-clip is available via pypi (python package index), bioconda and the Galaxy Tool Shed under the open source MIT License. The code is hosted at https://github.com/EMBL-Hentze-group/htseq-clip and documentation is available under https://htseq-clip.readthedocs.io/en/latest., (© The Author(s) 2022. Published by Oxford University Press.)