4 research outputs found

    Uncovering de novo gene birth in yeast using deep transcriptomics

    Get PDF
    De novo gene origination has been recently established as an important mechanism for the formation of new genes. In organisms with a large genome, intergenic and intronic regions provide plenty of raw material for new transcriptional events to occur, but little is know about how de novo transcripts originate in more densely-packed genomes. Here, we identify 213 de novo originated transcripts in Saccharomyces cerevisiae using deep transcriptomics and genomic synteny information from multiple yeast species grown in two different conditions. We find that about half of the de novo transcripts are expressed from regions which already harbor other genes in the opposite orientation; these transcripts show similar expression changes in response to stress as their overlapping counterparts, and some appear to translate small proteins. Thus, a large fraction of de novo genes in yeast are likely to co-evolve with already existing genes

    Evolution of new proteins from translated sORFs in long non-coding RNAs

    No full text
    High throughput RNA sequencing techniques have revealed that a large fraction of the genome is transcribed into long non-coding RNAs (lncRNAs). Unlike canonical protein-coding genes, lncRNAs do not contain long open reading frames (ORFs) and tend to be poorly conserved across species. However, many of them contain small ORFs (sORFs) that exhibit translation signatures according to ribosome profiling or proteomics data. These sORFs are a source of putative novel proteins; some of them may confer a selective advantage and be maintained over time, a process known as de novo gene birth. Here we review the mechanisms by which randomly occurring sORFs in lncRNAs can become new functional proteins

    Evaluation of the Integrated Tuberculosis Research Program Sponsored by the Spanish society of pulmonology and thoracic surgery: 11 years on

    No full text

    The value of the continuous genotyping of multi-drug resistant tuberculosis over 20 years in Spain

    No full text
    Molecular epidemiology of circulating clinical isolates is crucial to improve prevention strategies. The Spanish Working Group on multidrug resistant tuberculosis (MDR-TB) is a network that monitors the MDR-TB isolates in Spain since 1998. The aim of this study was to present the study of the MDR-TB and extensively drug-resistant tuberculosis (XDR-TB) patterns in Spain using the different recommended genotyping methods over time by a national coordinated system. Based on the proposed genotyping methods in the European Union until 2018, the preservation of one method, MIRU-VNTR, applied to selected clustered strains permitted to maintain our study open for 20 years. The distribution of demographic, clinical and epidemiological characteristics of clustered and non-clustered cases of MDR/XDR tuberculosis with proportion differences as assessed by Pearson’s chi-squared or Fisher’s exact test was compared. The differences in the quantitative variables using the Student's-t test and the Mann–Whitney U test were evaluated. The results obtained showed a total of 48.4% of the cases grouped in 77 clusters. Younger age groups, having a known TB case contact (10.2% vs 4.7%) and XDR-TB (16.5% vs 1.8%) were significantly associated with clustering. The largest cluster corresponded to a Mycobacterium bovis strain mainly spread during the nineties. A total of 68.4% of the clusters detected were distributed among the different Spanish regions and six clusters involving 104 cases were grouped in 17 and 18 years. Comparison of the genotypes obtained with those European genotypes included in The European Surveillance System (TESSy) showed that 87 cases had become part of 20 European clusters. The continuity of MDR strain genotyping in time has offered a widespread picture of the situation that allows better management of this public health problem. It also shows the advantage of maintaining one genotyping method over time, which allowed the comparison between ancient, present and future samples
    corecore