↓ Skip to main content

Annotation of the goat genome using next generation sequencing of microRNA expressed by the lactating mammary gland: comparison of three approaches

Overview of attention for article published in BMC Genomics, April 2015
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
30 Dimensions

Readers on

mendeley
50 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Annotation of the goat genome using next generation sequencing of microRNA expressed by the lactating mammary gland: comparison of three approaches
Published in
BMC Genomics, April 2015
DOI 10.1186/s12864-015-1471-y
Pubmed ID
Authors

Lenha Mobuchon, Sylvain Marthey, Mekki Boussaha, Sandrine Le Guillou, Christine Leroux, Fabienne Le Provost

Abstract

MicroRNAs (miRNA) are small endogenous non-coding RNA involved in the post-transcriptional regulation of specific mRNA targets. The first whole goat genome sequence became available in 2013, with few annotations. Our goal was to establish a list of the miRNA expressed in the mammary gland of lactating goats, thus enabling implementation of the goat miRNA repertoire and considerably enriching annotation of the goat genome. Here, we performed high throughput RNA sequencing on 10 lactating goat mammary glands. The bioinformatic detection of miRNA was carried out using miRDeep2 software. Three different methods were used to predict, quantify and annotate the sequenced reads. The first was a de novo approach based on the prediction of miRNA from the goat genome only. The second approach used bovine miRNA as an external reference whereas the last one used recently available goat miRNA. The three methods enabled the prediction and annotation of hundreds of miRNA, more than 95% were commonly identified. Using bovine miRNA, 1,178 distinct miRNA were detected, together with the annotation of 88 miRNA for which corresponding precursors could not be retrieved in the goat genome, and which were not detected using the de novo approach or with the use of goat miRNA. Each chromosomal coordinate of the precursors determined here were generated and depicted on a reference localisation map. Forty six goat miRNA clusters were also reported. The study revealed 263 precursors located in goat protein-coding genes, amongst which the location of 43 precursors was conserved between human, mouse and bovine, revealing potential new gene regulations in the goat mammary gland. Using the publicly available cattle QTL database, and cow precursors conserved in the goat and expressed in lactating mammary gland, 114 precursors were located within known QTL regions for milk production and composition. The results reported here represent the first major identification study on miRNA expressed in the goat mammary gland at peak lactation. The elements generated by this study will now be used as references to decipher the regulation of miRNA expression in the goat mammary gland and to clarify their involvement in the lactation process.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 28%
Student > Ph. D. Student 8 16%
Student > Doctoral Student 5 10%
Student > Master 5 10%
Student > Postgraduate 3 6%
Other 9 18%
Unknown 6 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 44%
Biochemistry, Genetics and Molecular Biology 9 18%
Veterinary Science and Veterinary Medicine 7 14%
Nursing and Health Professions 1 2%
Unknown 11 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 20 April 2015.
All research outputs
#12,219,110
of 19,211,930 outputs
Outputs from BMC Genomics
#5,556
of 9,730 outputs
Outputs of similar age
#127,899
of 237,705 outputs
Outputs of similar age from BMC Genomics
#1
of 1 outputs
Altmetric has tracked 19,211,930 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,730 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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 237,705 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them