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Transcriptome Sequencing and Annotation for the Jamaican Fruit Bat (Artibeus jamaicensis)

Overview of attention for article published in PLOS ONE, November 2012
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Title
Transcriptome Sequencing and Annotation for the Jamaican Fruit Bat (Artibeus jamaicensis)
Published in
PLOS ONE, November 2012
DOI 10.1371/journal.pone.0048472
Pubmed ID
Authors

Timothy I. Shaw, Anuj Srivastava, Wen-Chi Chou, Liang Liu, Ann Hawkinson, Travis C. Glenn, Rick Adams, Tony Schountz

Abstract

The Jamaican fruit bat (Artibeus jamaicensis) is one of the most common bats in the tropical Americas. It is thought to be a potential reservoir host of Tacaribe virus, an arenavirus closely related to the South American hemorrhagic fever viruses. We performed transcriptome sequencing and annotation from lung, kidney and spleen tissues using 454 and Illumina platforms to develop this species as an animal model. More than 100,000 contigs were assembled, with 25,000 genes that were functionally annotated. Of the remaining unannotated contigs, 80% were found within bat genomes or transcriptomes. Annotated genes are involved in a broad range of activities ranging from cellular metabolism to genome regulation through ncRNAs. Reciprocal BLAST best hits yielded 8,785 sequences that are orthologous to mouse, rat, cattle, horse and human. Species tree analysis of sequences from 2,378 loci was used to achieve 95% bootstrap support for the placement of bat as sister to the clade containing horse, dog, and cattle. Through substitution rate estimation between bat and human, 32 genes were identified with evidence for positive selection. We also identified 466 immune-related genes, which may be useful for studying Tacaribe virus infection of this species. The Jamaican fruit bat transcriptome dataset is a resource that should provide additional candidate markers for studying bat evolution and ecology, and tools for analysis of the host response and pathology of disease.

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Mendeley readers

The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 3%
United Kingdom 2 2%
China 2 2%
India 1 <1%
Hungary 1 <1%
Brazil 1 <1%
United States 1 <1%
Unknown 105 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 25%
Researcher 22 19%
Student > Master 18 16%
Student > Bachelor 9 8%
Other 7 6%
Other 17 15%
Unknown 14 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 62 53%
Immunology and Microbiology 13 11%
Biochemistry, Genetics and Molecular Biology 12 10%
Nursing and Health Professions 3 3%
Computer Science 3 3%
Other 7 6%
Unknown 16 14%