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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.


Performance of NextGenMap compared to Bowtie2.DOI:http://dx.doi.org/10.7554/eLife.09977.021
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fig7: Performance of NextGenMap compared to Bowtie2.DOI:http://dx.doi.org/10.7554/eLife.09977.021

Mentions: Reads were subsequently mapped to the chromosome 19 reference sequence with NextGenMap using the default parameters except for --strata 1 --silent-clip to obtain uniquely mapping reads and to remove the non-mapping regions from reads. Reads were also mapped with Bowtie2, following default parameters except for --very-sensitive. Information about uniquely mapping reads from NGM was derived directly from the bam files and from Bowtie2 was derived from the standard error log files. From Appendix 1—table 1 and Appendix 1—figure 1, we observe that NextGenMap performs extremely well with increasing divergences, and greatly outperforms the standard mapper. While the average difference between the most distant genomes analyzed is about 6%, it must be noted that fast evolving regions of the genome can quickly exceed the mean. NextGenMap is able to capture most of the regions of the genome to allow comparisons across very divergent taxa.


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

Neme R, Tautz D - Elife (2016)

Performance of NextGenMap compared to Bowtie2.DOI:http://dx.doi.org/10.7554/eLife.09977.021
© Copyright Policy
Related In: Results  -  Collection

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

fig7: Performance of NextGenMap compared to Bowtie2.DOI:http://dx.doi.org/10.7554/eLife.09977.021
Mentions: Reads were subsequently mapped to the chromosome 19 reference sequence with NextGenMap using the default parameters except for --strata 1 --silent-clip to obtain uniquely mapping reads and to remove the non-mapping regions from reads. Reads were also mapped with Bowtie2, following default parameters except for --very-sensitive. Information about uniquely mapping reads from NGM was derived directly from the bam files and from Bowtie2 was derived from the standard error log files. From Appendix 1—table 1 and Appendix 1—figure 1, we observe that NextGenMap performs extremely well with increasing divergences, and greatly outperforms the standard mapper. While the average difference between the most distant genomes analyzed is about 6%, it must be noted that fast evolving regions of the genome can quickly exceed the mean. NextGenMap is able to capture most of the regions of the genome to allow comparisons across very divergent taxa.

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.