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Fast turnover of genome transcription across evolutionary time exposes entire non-coding DNA to de novo gene emergence.

Neme R, Tautz D - Elife (2016)

Bottom Line: Using deep RNA sequencing we find that at a given sequencing depth transcriptome coverage becomes saturated within a taxon, but keeps extending when compared between taxa, even at this very shallow phylogenetic level.This suggests that the entire genome can be transcribed into poly-adenylated RNA when viewed at an evolutionary time scale.We conclude that any part of the non-coding genome can potentially become subject to evolutionary functionalization via de novo gene evolution within relatively short evolutionary time spans.

View Article: PubMed Central - PubMed

Affiliation: Max-Planck Institute for Evolutionary Biology, Plön, Germany.

ABSTRACT
Deep sequencing analyses have shown that a large fraction of genomes is transcribed, but the significance of this transcription is much debated. Here, we characterize the phylogenetic turnover of poly-adenylated transcripts in a comprehensive sampling of taxa of the mouse (genus Mus), spanning a phylogenetic distance of 10 Myr. Using deep RNA sequencing we find that at a given sequencing depth transcriptome coverage becomes saturated within a taxon, but keeps extending when compared between taxa, even at this very shallow phylogenetic level. Our data show a high turnover of transcriptional states between taxa and that no major transcript-free islands exist across evolutionary time. This suggests that the entire genome can be transcribed into poly-adenylated RNA when viewed at an evolutionary time scale. We conclude that any part of the non-coding genome can potentially become subject to evolutionary functionalization via de novo gene evolution within relatively short evolutionary time spans.

No MeSH data available.


Comparative analysis of lengths of regions transcribed or not transcribed across all data (including deeper brain sequencing) in all samples.Size distribution of regions not covered in any transcript (green) versus size distribution of regions with at least one transcript (blue).DOI:http://dx.doi.org/10.7554/eLife.09977.015
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fig6: Comparative analysis of lengths of regions transcribed or not transcribed across all data (including deeper brain sequencing) in all samples.Size distribution of regions not covered in any transcript (green) versus size distribution of regions with at least one transcript (blue).DOI:http://dx.doi.org/10.7554/eLife.09977.015

Mentions: The above overall statistical consideration would still allow for the possibility of the existence of a few scattered genomic islands that are not accessible to transcription because of structural reasons (so-called transcriptional deserts – Montavon and Duboule, 2012) or heterochromatically packed because they are not encoding genes required in the respective tissues. Hence, we analyzed also the size distribution of transcript-free genomic regions in our dataset. We find that the maximum observed length of non-transcribed regions is 6 kb (Figure 6), suggesting that apparent transcriptional deserts in one taxon are readily accessible to transcription in other taxa, at least for the non-repetitive windows of the genome that are analyzed here.10.7554/eLife.09977.015Figure 6.Comparative analysis of lengths of regions transcribed or not transcribed across all data (including deeper brain sequencing) in all samples.


Fast turnover of genome transcription across evolutionary time exposes entire non-coding DNA to de novo gene emergence.

Neme R, Tautz D - Elife (2016)

Comparative analysis of lengths of regions transcribed or not transcribed across all data (including deeper brain sequencing) in all samples.Size distribution of regions not covered in any transcript (green) versus size distribution of regions with at least one transcript (blue).DOI:http://dx.doi.org/10.7554/eLife.09977.015
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4829534&req=5

fig6: Comparative analysis of lengths of regions transcribed or not transcribed across all data (including deeper brain sequencing) in all samples.Size distribution of regions not covered in any transcript (green) versus size distribution of regions with at least one transcript (blue).DOI:http://dx.doi.org/10.7554/eLife.09977.015
Mentions: The above overall statistical consideration would still allow for the possibility of the existence of a few scattered genomic islands that are not accessible to transcription because of structural reasons (so-called transcriptional deserts – Montavon and Duboule, 2012) or heterochromatically packed because they are not encoding genes required in the respective tissues. Hence, we analyzed also the size distribution of transcript-free genomic regions in our dataset. We find that the maximum observed length of non-transcribed regions is 6 kb (Figure 6), suggesting that apparent transcriptional deserts in one taxon are readily accessible to transcription in other taxa, at least for the non-repetitive windows of the genome that are analyzed here.10.7554/eLife.09977.015Figure 6.Comparative analysis of lengths of regions transcribed or not transcribed across all data (including deeper brain sequencing) in all samples.

Bottom Line: Using deep RNA sequencing we find that at a given sequencing depth transcriptome coverage becomes saturated within a taxon, but keeps extending when compared between taxa, even at this very shallow phylogenetic level.This suggests that the entire genome can be transcribed into poly-adenylated RNA when viewed at an evolutionary time scale.We conclude that any part of the non-coding genome can potentially become subject to evolutionary functionalization via de novo gene evolution within relatively short evolutionary time spans.

View Article: PubMed Central - PubMed

Affiliation: Max-Planck Institute for Evolutionary Biology, Plön, Germany.

ABSTRACT
Deep sequencing analyses have shown that a large fraction of genomes is transcribed, but the significance of this transcription is much debated. Here, we characterize the phylogenetic turnover of poly-adenylated transcripts in a comprehensive sampling of taxa of the mouse (genus Mus), spanning a phylogenetic distance of 10 Myr. Using deep RNA sequencing we find that at a given sequencing depth transcriptome coverage becomes saturated within a taxon, but keeps extending when compared between taxa, even at this very shallow phylogenetic level. Our data show a high turnover of transcriptional states between taxa and that no major transcript-free islands exist across evolutionary time. This suggests that the entire genome can be transcribed into poly-adenylated RNA when viewed at an evolutionary time scale. We conclude that any part of the non-coding genome can potentially become subject to evolutionary functionalization via de novo gene evolution within relatively short evolutionary time spans.

No MeSH data available.