Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in individual and meta-analysis studies

<p>Abstract</p> <p>Background</p> <p>In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focused on the identification of significant differentially expressed genes. Later, researchers moved toward the systematic integration of gene expression profiles with additional biological information, such as chromosomal location, ontological annotations or sequence features. The analysis of gene expression linked to physical location of genes on chromosomes allows the identification of transcriptionally imbalanced regions, while, Gene Set Analysis focuses on the detection of coordinated changes in transcriptional levels among sets of biologically related genes.</p> <p>In this field, meta-analysis offers the possibility to compare different studies, addressing the same biological question to fully exploit public gene expression datasets.</p> <p>Results</p> <p>We describe STEPath, a method that starts from gene expression profiles and integrates the analysis of imbalanced region as an <it>a priori </it>step before performing gene set analysis. The application of STEPath in individual studies produced gene set scores weighted by chromosomal activation. As a final step, we propose a way to compare these scores across different studies (meta-analysis) on related biological issues. One complication with meta-analysis is batch effects, which occur because molecular measurements are affected by laboratory conditions, reagent lots and personnel differences. Major problems occur when batch effects are correlated with an outcome of interest and lead to incorrect conclusions. We evaluated the power of combining chromosome mapping and gene set enrichment analysis, performing the analysis on a dataset of leukaemia (example of individual study) and on a dataset of skeletal muscle diseases (meta-analysis approach).</p> <p>In leukaemia, we identified the Hox gene set, a gene set closely related to the pathology that other algorithms of gene set analysis do not identify, while the meta-analysis approach on muscular disease discriminates between related pathologies and correlates similar ones from different studies.</p> <p>Conclusions</p> <p>STEPath is a new method that integrates gene expression profiles, genomic co-expressed regions and the information about the biological function of genes. The usage of the STEPath-computed gene set scores overcomes batch effects in the meta-analysis approaches allowing the direct comparison of different pathologies and different studies on a gene set activation level.</p

A thorough annotation of the krill transcriptome offers new insights for the study of physiological processes

The krill species Euphausia superba plays a critical role in the food chain of the Antarctic ecosystem. Significant changes in climate conditions observed in the Antarctic Peninsula region in the last decades have already altered the distribution of krill and its reproductive dynamics. A deeper understanding of the adaptation capabilities of this species is urgently needed. The availability of a large body of RNA-seq assays allowed us to extend the current knowledge of the krill transcriptome. Our study covered the entire developmental process providing information of central relevance for ecological studies. Here we identified a series of genes involved in different steps of the krill moulting cycle, in the reproductive process and in sexual maturation in accordance with what was already described in previous works. Furthermore, the new transcriptome highlighted the presence of differentially expressed genes previously unknown, playing important roles in cuticle development as well as in energy storage during the krill life cycle. The discovery of new opsin sequences, specifically rhabdomeric opsins, one onychopsin, and one non-visual arthropsin, expands our knowledge of the krill opsin repertoire. We have collected all these results into the KrillDB2 database, a resource combining the latest annotation of the krill transcriptome with a series of analyses targeting genes relevant to krill physiology. KrillDB2 provides in a single resource a comprehensive catalog of krill genes; an atlas of their expression profiles over all RNA-seq datasets publicly available; a study of differential expression across multiple conditions. Finally, it provides initial indications about the expression of microRNA precursors, whose contribution to krill physiology has never been reported before

BrewerIX enables allelic expression analysis of imprinted and X-linked genes from bulk and single-cell transcriptomes

Genomic imprinting and X chromosome inactivation (XCI) are two prototypical epigenetic mechanisms whereby a set of genes is expressed mono-allelically in order to fine-tune their expression levels. Defects in genomic imprinting have been observed in several neurodevelopmental disorders, in a wide range of tumours and in induced pluripotent stem cells (iPSCs). Single Nucleotide Variants (SNVs) are readily detectable by RNA-sequencing allowing the determination of whether imprinted or X-linked genes are aberrantly expressed from both alleles, although standardised analysis methods are still missing. We have developed a tool, named BrewerIX, that provides comprehensive information about the allelic expression of a large, manually-curated set of imprinted and X-linked genes. BrewerIX does not require programming skills, runs on a standard personal computer, and can analyze both bulk and single-cell transcriptomes of human and mouse cells directly from raw sequencing data. BrewerIX confirmed previous observations regarding the bi-allelic expression of some imprinted genes in naive pluripotent cells and extended them to preimplantation embryos. BrewerIX also identified misregulated imprinted genes in breast cancer cells and in human organoids and identified genes escaping XCI in human somatic cells. We believe BrewerIX will be useful for the study of genomic imprinting and XCI during development and reprogramming, and for detecting aberrations in cancer, iPSCs and organoids. Due to its ease of use to non-computational biologists, its implementation could become standard practice during sample assessment, thus raising the robustness and reproducibility of future studies

Seasonal and Form-Specific Gene Expression Signatures Uncover Different Generational Strategies of the Pelagic Tunicate Salpa thompsoni During the Southern Ocean Winter

The pelagic tunicate Salpa thompsoni is recognized as a major metazoan grazer in the Southern Ocean. Long term observations show an increase in this species’ biomass and a southward shift in its distribution both of which are positively correlated with ocean warming and winter sea ice decline around the Antarctic Peninsula. However, our understanding on how salps adapt their life cycle to the extreme seasonality of the Southern Ocean and the putative differences between its two reproductive forms (aggregates, solitaries) is rudimentary. In particular, our current knowledge of whether and how S. thompsoni overwinter is limited, largely due to winter sampling constraints. In this study, we investigated the form-specific gene expression profiles of Salpa thompsoni during the austral autumn and winter. Between the seasons, genes related to translation showed the biggest difference in gene expression. We found more genes were upregulated in solitaries compared to aggregates, indicating a potentially form-specific overwintering strategy. Our data provide first insights into the seasonal and form-specific physiology of salps by considering their complex life cycle, thereby contributing to a more comprehensive understanding of the response of salps to seasonal changes in their environment and to anthropogenic induced global climate change