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Improving eukaryotic genome annotation using single molecule mRNA sequencing

Overview of attention for article published in BMC Genomics, March 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

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29 tweeters
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1 Google+ user

Citations

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7 Dimensions

Readers on

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42 Mendeley
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Title
Improving eukaryotic genome annotation using single molecule mRNA sequencing
Published in
BMC Genomics, March 2018
DOI 10.1186/s12864-018-4555-7
Pubmed ID
Authors

Vincent Magrini, Xin Gao, Bruce A. Rosa, Sean McGrath, Xu Zhang, Kymberlie Hallsworth-Pepin, John Martin, John Hawdon, Richard K. Wilson, Makedonka Mitreva

Abstract

The advantages of Pacific Biosciences (PacBio) single-molecule real-time (SMRT) technology include long reads, low systematic bias, and high consensus read accuracy. Here we use these attributes to improve on the genome annotation of the parasitic hookworm Ancylostoma ceylanicum using PacBio RNA-Seq. We sequenced 192,888 circular consensus sequences (CCS) derived from cDNAs generated using the CloneTech SMARTer system. These SMARTer-SMRT libraries were normalized and size-selected providing a robust population of expressed structural genes for subsequent genome annotation. We demonstrate PacBio mRNA sequences based genome annotation improvement, compared to genome annotation using conventional sequencing-by-synthesis alone, by identifying 1609 (9.2%) new genes, extended the length of 3965 (26.7%) genes and increased the total genomic exon length by 1.9 Mb (12.4%). Non-coding sequence representation (primarily from UTRs based on dT reverse transcription priming) was particularly improved, increasing in total length by fifteen-fold, by increasing both the length and number of UTR exons. In addition, the UTR data provided by these CCS allowed for the identification of a novel SL2 splice leader sequence for A. ceylanicum and an increase in the number and proportion of functionally annotated genes. RNA-seq data also confirmed some of the newly annotated genes and gene features. Overall, PacBio data has supported a significant improvement in gene annotation in this genome, and is an appealing alternative or complementary technique for genome annotation to the other transcript sequencing technologies.

Twitter Demographics

The data shown below were collected from the profiles of 29 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 31%
Student > Ph. D. Student 7 17%
Student > Master 5 12%
Student > Bachelor 4 10%
Professor > Associate Professor 3 7%
Other 5 12%
Unknown 5 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 48%
Biochemistry, Genetics and Molecular Biology 9 21%
Engineering 2 5%
Neuroscience 2 5%
Environmental Science 1 2%
Other 0 0%
Unknown 8 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 11 March 2018.
All research outputs
#1,097,841
of 14,524,868 outputs
Outputs from BMC Genomics
#379
of 8,460 outputs
Outputs of similar age
#36,241
of 275,773 outputs
Outputs of similar age from BMC Genomics
#1
of 12 outputs
Altmetric has tracked 14,524,868 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,460 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 95% 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 275,773 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.