About this Research Topic
The transcriptome of an organism is the full set of expressed RNAs – coding, non-coding, long and short. Well-studied mammalian, plant, bacterial, and fungal genomes have revealed that the majority of the genome loci are transcribed into RNA molecules. However, the majority of genomes are still only annotated with genes that are well conserved or expressed sufficiently under different conditions while transcripts expressed from yet unannotated genomic regions are disregarded as transcriptional noise. Transcripts expressed selectively under specific environmental conditions may provide an organism with evolutionary novelty and help the organism adapt to changing conditions. However, the functional characterization of such transcripts is a difficult task.
RNA sequencing (RNA-Seq) is the state-of-the-art method to detect expressed transcripts in organs, tissues, or even single cells. RNA-Seq provides a snapshot of the expressed genome loci under any given biological, physiological, or pathological condition. Petabytes of publicly available RNA-Seq data provide an opportunity to explore the dynamic landscape of transcription. The genomic sequence enables the anchoring or such transcripts in evolution.
A plethora of studies have reported the pervasive and dynamic nature of transcription in species across evolution. However, a significant proportion of the transcriptome remains “dark”, unannotated, and functionally uncharacterized even in well-studied organisms like yeast, Arabidopsis, and humans.
Because they often do not encode proteins, or they have no protein homologs in other species, the identification and characterization of these transcripts remain a challenging task. Methods are being developed to systematically capture these as-yet-undefined transcripts. Other approaches are being applied to computationally characterize the transcripts, with the goal to facilitate experimental validation of their functions.
This special issue focuses on the analyses of dynamically expressed, yet functionally unannotated RNAs in any eukaryotic, archaeal, bacterial species, or virus. Topics can encompass (but are not limited to) the following themes:
1. Species-specific protein-coding and non-coding orphan genes
2. Non-coding and long non-coding RNAs
3. Small, upstream, downstream ORFs
4. miRNAs
5. mtRNAs
6. Evolution and functionalization of novel genes.
7. Pseudogenization of genes
We welcome Original Research, Methods, Software, and Brief Reports, as well as Reviews.
RNA sequencing (RNA-Seq) is the state-of-the-art method to detect expressed transcripts in organs, tissues, or even single cells. RNA-Seq provides a snapshot of the expressed genome loci under any given biological, physiological, or pathological condition. Petabytes of publicly available RNA-Seq data provide an opportunity to explore the dynamic landscape of transcription. The genomic sequence enables the anchoring or such transcripts in evolution.
A plethora of studies have reported the pervasive and dynamic nature of transcription in species across evolution. However, a significant proportion of the transcriptome remains “dark”, unannotated, and functionally uncharacterized even in well-studied organisms like yeast, Arabidopsis, and humans.
Because they often do not encode proteins, or they have no protein homologs in other species, the identification and characterization of these transcripts remain a challenging task. Methods are being developed to systematically capture these as-yet-undefined transcripts. Other approaches are being applied to computationally characterize the transcripts, with the goal to facilitate experimental validation of their functions.
This special issue focuses on the analyses of dynamically expressed, yet functionally unannotated RNAs in any eukaryotic, archaeal, bacterial species, or virus. Topics can encompass (but are not limited to) the following themes:
1. Species-specific protein-coding and non-coding orphan genes
2. Non-coding and long non-coding RNAs
3. Small, upstream, downstream ORFs
4. miRNAs
5. mtRNAs
6. Evolution and functionalization of novel genes.
7. Pseudogenization of genes
We welcome Original Research, Methods, Software, and Brief Reports, as well as Reviews.
Keywords: Orphan Genes, Non-Coding RNA, De Novo, Disease, Expression Analysis, Novel, Unannotated
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