Changes in gene expression shift and switch genetic interactions, bioRxiv, 2019-03-15

SummaryAn important goal in disease genetics and evolutionary biology is to understand how mutations combine to alter phenotypes and fitness. Non-additive interactions between mutations occur extensively and change across conditions, cell types, and species, making genetic prediction a difficult challenge. To understand the reasons for this, we reduced the problem to a minimal system where we combined mutations in a single protein performing a single function (a transcriptional repressor inhibiting a target gene). Even in this minimal system, a change in gene expression altered both the strength and type of genetic interactions. These seemingly complicated changes could, however, be predicted by a mathematical model that propagates the effects of mutations on protein folding to the cellular phenotype. We show that similar changes will be observed for many genes. These results provide fundamental insights into genotype-phenotype maps and illustrate how changes in genetic interactions can be predicted using hierarchical mechanistic models.One sentence SummaryDeep mutagenesis of the lambda repressor reveals that changes in gene expression will alter the strength and direction of genetic interactions between mutations in many genes.Highlights<jatslist list-type=bullet><jatslist-item>Deep mutagenesis of the lambda repressor at two expression levels reveals extensive changes in mutational effects and genetic interactions<jatslist-item><jatslist-item>Genetic interactions can switch from positive (suppressive) to negative (enhancing) as the expression of a gene changes<jatslist-item><jatslist-item>A mathematical model that propagates the effects of mutations on protein folding to the cellular phenotype accurately predicts changes in mutational effects and interactions<jatslist-item><jatslist-item>Changes in expression will alter mutational effects and interactions for many genes<jatslist-item><jatslist-item>For some genes, perfect mechanistic models will never be able to predict how mutations of known effect combine without measurements of intermediate phenotypes<jatslist-item>

biorxiv genetics 0-100-users 2019

Frequent birth of de novo genes in the compact yeast genome, bioRxiv, 2019-03-13

AbstractEvidence 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.

biorxiv evolutionary-biology 0-100-users 2019

Frequent birth ofde novogenes in the compact yeast genome, bioRxiv, 2019-03-13

AbstractEvidence has accumulated that some genes originate directly from previously non-genic sequences, orde novo, rather than by the duplication or fusion of existing genes. However, howde novogenes emerge and eventually become functional is largely unknown. Here we perform the first study onde novogenes 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 arisende novoin 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 ofde novogene birth. In addition, we find that 40% of thesede novotranscripts 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 novotranscripts are continuously generated and can give rise to new functional protein-coding genes.

biorxiv evolutionary-biology 0-100-users 2019

 

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