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Lessons for livestock genomics from genome and transcriptome sequencing in cattle and other mammals

Overview of attention for article published in Genetics Selection Evolution, August 2016
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Title
Lessons for livestock genomics from genome and transcriptome sequencing in cattle and other mammals
Published in
Genetics Selection Evolution, August 2016
DOI 10.1186/s12711-016-0237-6
Pubmed ID
Authors

Jeremy F. Taylor, Lynsey K. Whitacre, Jesse L. Hoff, Polyana C. Tizioto, JaeWoo Kim, Jared E. Decker, Robert D. Schnabel

Abstract

Decreasing sequencing costs and development of new protocols for characterizing global methylation, gene expression patterns and regulatory regions have stimulated the generation of large livestock datasets. Here, we discuss experiences in the analysis of whole-genome and transcriptome sequence data. We analyzed whole-genome sequence (WGS) data from 132 individuals from five canid species (Canis familiaris, C. latrans, C. dingo, C. aureus and C. lupus) and 61 breeds, three bison (Bison bison), 64 water buffalo (Bubalus bubalis) and 297 bovines from 17 breeds. By individual, data vary in extent of reference genome depth of coverage from 4.9X to 64.0X. We have also analyzed RNA-seq data for 580 samples representing 159 Bos taurus and Rattus norvegicus animals and 98 tissues. By aligning reads to a reference assembly and calling variants, we assessed effects of average depth of coverage on the actual coverage and on the number of called variants. We examined the identity of unmapped reads by assembling them and querying produced contigs against the non-redundant nucleic acids database. By imputing high-density single nucleotide polymorphism data on 4010 US registered Angus animals to WGS using Run4 of the 1000 Bull Genomes Project and assessing the accuracy of imputation, we identified misassembled reference sequence regions. We estimate that a 24X depth of coverage is required to achieve 99.5 % coverage of the reference assembly and identify 95 % of the variants within an individual's genome. Genomes sequenced to low average coverage (e.g., <10X) may fail to cover 10 % of the reference genome and identify <75 % of variants. About 10 % of genomic DNA or transcriptome sequence reads fail to align to the reference assembly. These reads include loci missing from the reference assembly and misassembled genes and interesting symbionts, commensal and pathogenic organisms. Assembly errors and a lack of annotation of functional elements significantly limit the utility of the current draft livestock reference assemblies. The Functional Annotation of Animal Genomes initiative seeks to annotate functional elements, while a 70X Pac-Bio assembly for cow is underway and may result in a significantly improved reference assembly.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
New Zealand 1 1%
Hungary 1 1%
United States 1 1%
Unknown 68 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 24%
Student > Ph. D. Student 11 15%
Student > Master 7 10%
Student > Doctoral Student 6 8%
Student > Postgraduate 4 6%
Other 11 15%
Unknown 15 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 41%
Biochemistry, Genetics and Molecular Biology 12 17%
Veterinary Science and Veterinary Medicine 7 10%
Immunology and Microbiology 3 4%
Medicine and Dentistry 2 3%
Other 0 0%
Unknown 18 25%
Attention Score in Context

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 19 August 2016.
All research outputs
#16,721,717
of 25,374,647 outputs
Outputs from Genetics Selection Evolution
#523
of 822 outputs
Outputs of similar age
#221,518
of 354,260 outputs
Outputs of similar age from Genetics Selection Evolution
#7
of 19 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 822 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 33rd percentile – i.e., 33% 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 354,260 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 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 63% of its contemporaries.