Faced with inequality: chicken do not have a general dosage compensation of sex-linked genes

<p>Abstract</p> <p>Background</p> <p>The contrasting dose of sex chromosomes in males and females potentially introduces a large-scale imbalance in levels of gene expression between sexes, and between sex chromosomes and autosomes. In many organisms, dosage compensation has thus evolved to equalize sex-linked gene expression in males and females. In mammals this is achieved by X chromosome inactivation and in flies and worms by up- or down-regulation of X-linked expression, respectively. While otherwise widespread in systems with heteromorphic sex chromosomes, the case of dosage compensation in birds (males ZZ, females ZW) remains an unsolved enigma.</p> <p>Results</p> <p>Here, we use a microarray approach to show that male chicken embryos generally express higher levels of Z-linked genes than female birds, both in soma and in gonads. The distribution of male-to-female fold-change values for Z chromosome genes is wide and has a mean of 1.4–1.6, which is consistent with absence of dosage compensation and sex-specific feedback regulation of gene expression at individual loci. Intriguingly, without global dosage compensation, the female chicken has significantly lower expression levels of Z-linked compared to autosomal genes, which is not the case in male birds.</p> <p>Conclusion</p> <p>The pronounced sex difference in gene expression is likely to contribute to sexual dimorphism among birds, and potentially has implication to avian sex determination. Importantly, this report, together with a recent study of sex-biased expression in somatic tissue of chicken, demonstrates the first example of an organism with a lack of global dosage compensation, providing an unexpected case of a viable system with large-scale imbalance in gene expression between sexes.</p

Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota

In recent years, several associations between common chronic human disorders and altered gut microbiome composition and function have been reported(1,2). In most of these reports, treatment regimens were not controlled for and conclusions could thus be confounded by the effects of various drugs on the microbiota, which may obscure microbial causes, protective factors or diagnostically relevant signals. Our study addresses disease and drug signatures in the human gut microbiome of type 2 diabetes mellitus (T2D). Two previous quantitative gut metagenomics studies of T2D patients that were unstratified for treatment yielded divergent conclusions regarding its associated gut microbial dysbiosis(3,4). Here we show, using 784 available human gut metagenomes, how antidiabetic medication confounds these results, and analyse in detail the effects of the most widely used antidiabetic drug metformin. We provide support for microbial mediation of the therapeutic effects of metformin through short-chain fatty acid production, as well as for potential microbiota-mediated mechanisms behind known intestinal adverse effects in the form of a relative increase in abundance of Escherichia species. Controlling for metformin treatment, we report a unified signature of gut microbiome shifts in T2D with a depletion of butyrate-producing taxa(3,4). These in turn cause functional microbiome shifts, in part alleviated by metformin-induced changes. Overall, the present study emphasizes the need to disentangle gut microbiota signatures of specific human diseases from those of medication

MOSCA: an automated pipeline for integrated metagenomics and metatranscriptomics data analysis

Metagenomics (MG) and Metatranscriptomics (MT) approaches open new perspectives on the interpretation of biological systems composed by complex microbial communities. Dealing with large sequencing datasets, to extract the desired information and interpret the results are big challenges associated with meta-omics studies. There are several bioinformatics pipelines for MG data analysis and less to MT. Up to date, none performs a complete analysis integrating both MG and MT data, including the assembly of reads into contigs, functional and taxonomic annotation of identified genes, differential gene expression analysis and the comparison of multiple samples. Here, we present Meta-Omics Software for Community Analysis (MOSCA) that was designed with this purpose. It integrates RNA-Seq analysis with Whole Genome Sequencing as reference. Raw sequencing reads are submitted to preprocessing for quality trimming and rRNA removal, and assembled into contigs, which afterwards are annotated by using a reference database. MOSCA performs differential gene expression and provides graphical visualization of the results and comparison of multiple samples. Validation and reproducibility of the pipeline was obtained by using simulated MG and MT datasets.This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte, and by the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement no. 323009.info:eu-repo/semantics/publishedVersio

Metagenomic species profiling using universal phylogenetic marker genes

To quantify known and unknown microorganisms at species-level resolution using shotgun sequencing data, we developed a method that establishes metagenomic operational taxonomic units (mOTUs) based on single-copy phylogenetic marker genes. Applied to 252 human fecal samples, the method revealed that on average 43% of the species abundance and 58% of the richness cannot be captured by current reference genome-based methods. An implementation of the method is available at http://www.bork.embl.de/software/mOTU