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.
Isogenic cells show a large degree of variability in growth rate, even when cultured in the same environment. Such cell-to-cell variability in growth can alter sensitivity to antibiotics, chemotherapy and environmental stress. To characterize transcriptional differences associated with this variability, we have developed a method—FitFlow—that enables the sorting of subpopulations by growth rate. The slow-growing subpopulation shows a transcriptional stress response, but, more surprisingly, these cells have reduced RNA polymerase fidelity and exhibit a DNA damage response. As DNA damage is often caused by oxidative stress, we test the addition of an antioxidant, and find that it reduces the size of the slow-growing population. More generally, we find a significantly altered transcriptome in the slow-growing subpopulation that only partially resembles that of cells growing slowly due to environmental and culture conditions. Slow-growing cells upregulate transposons and express more chromosomal, viral and plasmid-borne transcripts, and thus explore a larger genotypic—and so phenotypic — space.
Cells responds to diverse stimuli by changing the levels of specific effector proteins. These changes are usually examined using high throughput RNA sequencing data (RNA-Seq); transcriptional regulation is generally assumed to directly influence protein abundances. However, the correlation between RNA-Seq and proteomics data is in general quite limited owing to differences in protein stability and translational regulation. Here we perform RNA-Seq, ribosome profiling and proteomics analyses in baker’s yeast cells grown in rich media and oxidative stress conditions to examine gene expression regulation at various levels. With the exception of a small set of genes involved in the maintenance of the redox state, which are regulated at the transcriptional level, modulation of protein expression is largely driven by changes in the relative ribosome density across conditions. The majority of shifts in mRNA abundance are compensated by changes in the opposite direction in the number of translating ribosomes and are predicted to result in no net change at the protein level. We also identify a subset of mRNAs which is likely to undergo specific translational repression during stress and which includes cell cycle control genes. The study suggests that post-transcriptional buffering of gene expression may be more common than previously anticipated.
Evidence has accumulated that some genes originate directly from previously non-genic sequences, or de novo, rather than by the duplication or fusion of existing genes. However, how de novo genes emerge and eventually become functional is largely unknown. Here we perform the first study on de novo genes that uses transcriptomics data from eleven different yeast species, all grown identically in both rich media and in oxidative stress conditions. The genomes of these species are densely-packed with functional elements, leaving little room for the co-option of genomic sequences into new transcribed loci. Despite this, we find that at least 213 transcripts (~ 5%) have arisen de novo in the past 20 million years of evolution of baker's yeast-or approximately 10 new transcripts every million years.Nearly half of the total newly expressed sequences are generated from regions in which both DNA strands are used as templates for transcription, explaining the apparent contradiction between the limited 'empty' genomic space and high rate of de novo gene birth. In addition, we find that 40% of these de novo transcripts are actively translated and that at least a fraction of the encoded proteins are likely to be under purifying selection. This study shows that even in very highly compact genomes, de novo transcripts are continuously generated and can give rise to new functional protein-coding genes.2
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