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Identifying and characterising key alternative splicing events in Drosophila development

Overview of attention for article published in BMC Genomics, August 2015
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Title
Identifying and characterising key alternative splicing events in Drosophila development
Published in
BMC Genomics, August 2015
DOI 10.1186/s12864-015-1674-2
Pubmed ID
Authors

Jonathan G. Lees, Juan A. Ranea, Christine A. Orengo

Abstract

In complex Metazoans a given gene frequently codes for multiple protein isoforms, through processes such as alternative splicing. Large scale functional annotation of these isoforms is a key challenge for functional genomics. This annotation gap is increasing with the large numbers of multi transcript genes being identified by technologies such as RNASeq. Furthermore attempts to characterise the functions of splicing in an organism are complicated by the difficulty in distinguishing functional isoforms from those produced by splicing errors or transcription noise. Tools to help prioritise candidate isoforms for testing are largely absent. In this study we implement a Time-course Switch (TS) score for ranking isoforms by their likelihood of producing additional functions based on their developmental expression profiles, as reported by modENCODE. The TS score allows us to better investigate functional roles of different isoforms expressed in multi transcript genes. From this analysis, we find that isoforms with high TS scores have sequence feature changes consistent with more deterministic splicing and functional changes and tend to gain domains or whole exons which could carry additional functions. Furthermore these functions appear to be particularly important for essential regulatory roles, establishing functional isoform switching as key for regulatory processes. Based on the TS score we develop a Transcript Annotations Pipeline for Alternative Splicing (TAPAS) that identifies functional neighbourhoods of potentially interesting isoforms. We have identified a subset of protein isoforms which appear to have high functional significance, particularly in regulation. This has been made possible through the development of novel methods that make use of transcript expression profiles. The methods and analyses we present here represent important first steps in the development of tools to address the near complete lack of isoform specific function annotation. In turn the tools allow us to better characterise the regulatory functions of alternative splicing in more detail.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Spain 1 3%
Unknown 33 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 31%
Student > Ph. D. Student 10 29%
Student > Master 5 14%
Student > Postgraduate 2 6%
Student > Doctoral Student 1 3%
Other 4 11%
Unknown 2 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 54%
Biochemistry, Genetics and Molecular Biology 10 29%
Unspecified 1 3%
Computer Science 1 3%
Immunology and Microbiology 1 3%
Other 1 3%
Unknown 2 6%
Attention Score in Context

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 17 August 2015.
All research outputs
#14,218,482
of 24,276,163 outputs
Outputs from BMC Genomics
#5,033
of 10,937 outputs
Outputs of similar age
#113,250
of 242,222 outputs
Outputs of similar age from BMC Genomics
#124
of 251 outputs
Altmetric has tracked 24,276,163 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,937 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 52% 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 242,222 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 52% of its contemporaries.
We're also able to compare this research output to 251 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.