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Fusion transcript loci share many genomic features with non-fusion loci

Overview of attention for article published in BMC Genomics, December 2015
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  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

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Title
Fusion transcript loci share many genomic features with non-fusion loci
Published in
BMC Genomics, December 2015
DOI 10.1186/s12864-015-2235-4
Pubmed ID
Authors

John Lai, Jiyuan An, Inge Seim, Carina Walpole, Andrea Hoffman, Leire Moya, Srilakshmi Srinivasan, Joanna L. Perry-Keene, Chenwei Wang, Melanie L. Lehman, Colleen C. Nelson, Judith A. Clements, Jyotsna Batra

Abstract

Fusion transcripts are found in many tissues and have the potential to create novel functional products. Here, we investigate the genomic sequences around fusion junctions to better understand the transcriptional mechanisms mediating fusion transcription/splicing. We analyzed data from prostate (cancer) cells as previous studies have shown extensively that these cells readily undergo fusion transcription. We used the FusionMap program to identify high-confidence fusion transcripts from RNAseq data. The RNAseq datasets were from our (N = 8) and other (N = 14) clinical prostate tumors with adjacent non-cancer cells, and from the LNCaP prostate cancer cell line that were mock-, androgen- (DHT), and anti-androgen- (bicalutamide, enzalutamide) treated. In total, 185 fusion transcripts were identified from all RNAseq datasets. The majority (76 %) of these fusion transcripts were 'read-through chimeras' derived from adjacent genes in the genome. Characterization of sequences at fusion loci were carried out using a combination of the FusionMap program, custom Perl scripts, and the RNAfold program. Our computational analysis indicated that most fusion junctions (76 %) use the consensus GT-AG intron donor-acceptor splice site, and most fusion transcripts (85 %) maintained the open reading frame. We assessed whether parental genes of fusion transcripts have the potential to form complementary base pairing between parental genes which might bring them into physical proximity. Our computational analysis of sequences flanking fusion junctions at parental loci indicate that these loci have a similar propensity as non-fusion loci to hybridize. The abundance of repetitive sequences at fusion and non-fusion loci was also investigated given that SINE repeats are involved in aberrant gene transcription. We found few instances of repetitive sequences at both fusion and non-fusion junctions. Finally, RT-qPCR was performed on RNA from both clinical prostate tumors and adjacent non-cancer cells (N = 7), and LNCaP cells treated as above to validate the expression of seven fusion transcripts and their respective parental genes. We reveal that fusion transcript expression is similar to the expression of parental genes. Fusion transcripts maintain the open reading frame, and likely use the same transcriptional machinery as non-fusion transcripts as they share many genomic features at splice/fusion junctions.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 3%
Unknown 30 97%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 26%
Student > Ph. D. Student 7 23%
Student > Master 5 16%
Professor > Associate Professor 3 10%
Researcher 2 6%
Other 2 6%
Unknown 4 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 26%
Agricultural and Biological Sciences 6 19%
Medicine and Dentistry 4 13%
Engineering 3 10%
Computer Science 1 3%
Other 1 3%
Unknown 8 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 December 2015.
All research outputs
#7,390,150
of 14,565,263 outputs
Outputs from BMC Genomics
#3,292
of 8,479 outputs
Outputs of similar age
#123,967
of 360,988 outputs
Outputs of similar age from BMC Genomics
#382
of 1,006 outputs
Altmetric has tracked 14,565,263 research outputs across all sources so far. This one is in the 48th percentile – i.e., 48% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,479 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 60% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 360,988 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 1,006 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.