Evidence map›Paper›PMID 27534529›Full record

ArticleGenetics, selection, evolution : GSE2016

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

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

Open access · goldAbstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.0field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 36 citations in OpenAlex.

  1. Review
  2. Molecular Cytogenetics in Domestic Bovids: A Review.Animals : an open access journal from MDPI · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 2 countries.

Jeremy F TaylorDivision of Animal Sciences, University of Missouri, Columbia, MO, USA. taylorjerr@missouri.edu.
Lynsey K WhitacreDivision of Animal Sciences, University of Missouri, Columbia, MO, USA.
Jesse L HoffDivision of Animal Sciences, University of Missouri, Columbia, MO, USA.
Polyana C TiziotoDivision of Animal Sciences, University of Missouri, Columbia, MO, USA.
JaeWoo KimDivision of Animal Sciences, University of Missouri, Columbia, MO, USA.
Jared E DeckerDivision of Animal Sciences, University of Missouri, Columbia, MO, USA.
Robert D SchnabelDivision of Animal Sciences, University of Missouri, Columbia, MO, USA.
University of Missouri · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDecreasing 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.

methodsWe 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.

resultsWe 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.

conclusionsAssembly 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.

Indexed as

AnimalsBisonBreedingBuffaloesCanidaeCattleFemaleGenetic Association StudiesGenomeGenomicsLivestockMalePolymorphism, Single NucleotideRatsSequence Analysis, DNATranscriptome

Identifiers

PMID27534529
PMCPMC4989351
OpenAlexW2517305685

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.