Evidence map›Paper›PMID 23826801›Full record

ArticleBMC genomics2013

Assessment of the genomic variation in a cattle population by re-sequencing of key animals at low to medium coverage.

Sandra Jansen, Bernhard Aigner, Hubert Pausch, Michal Wysocki, Sebastian Eck, Anna Benet-Pagès, Elisabeth Graf, Thomas Wieland, Tim M Strom, Thomas Meitinger and 1 more

Abstract read
In one paragraph

Article in BMC genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

39 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  12. Genome-wide mapping of large deletions and their population-genetic properties in dairy cattle.DNA research : an international journal for rapid publication of reports on genes and genomes · 2018
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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

11 authors.

Sandra JansenTechnische Universität München, Liesel-Beckmann-Strasse 1, Freising, 85354, Germany.
Bernhard Aigner
Hubert Pausch
Michal Wysocki
Sebastian Eck
Anna Benet-Pagès
Elisabeth Graf
Thomas Wieland
Tim M Strom
Thomas Meitinger
Ruedi Fries

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenome- and population-wide re-sequencing would allow for most efficient detection of causal trait variants. However, despite a strong decrease of costs for next-generation sequencing in the last few years, re-sequencing of large numbers of individuals is not yet affordable. We therefore resorted to re-sequencing of a limited number of bovine animals selected to explain a major proportion of the population's genomic variation, so called key animals, in order to provide a catalogue of functional variants and a substrate for population- and genome-wide imputation of variable sites.

resultsForty-three animals accounting for about 69 percent of the genetic diversity of the Fleckvieh population, a cattle breed of Southern Germany and Austria, were sequenced with coverages ranging from 4.17 to 24.98 and averaging 7.46. After alignment to the reference genome (UMD3.1) and multi-sample variant calling, more than 17 million variant positions were identified, about 90 percent biallelic single nucleotide variants (SNVs) and 10 percent short insertions and deletions (InDels). The comparison with high-density chip data revealed a sensitivity of at least 92 percent and a specificity of 81 percent for sequencing based genotyping, and 97 percent and 93 percent when a imputation step was included. There are 91,733 variants in coding regions of 18,444 genes, 46 percent being non-synonymous exchanges, of which 575 variants are predicted to cause premature stop codons. Three variants are listed in the OMIA database as causal for specific phenotypes.

conclusionsLow- to medium-coverage re-sequencing of individuals explaining a major fraction of a population's genomic variation allows for the efficient and reliable detection of most variants. Imputation strongly improves genotype quality of lowly covered samples and thus enables maximum density genotyping by sequencing. The functional annotation of variants provides the basis for exhaustive genotype imputation in the population, e.g., for highest-resolution genome-wide association studies.

Indexed as

GenomicsAnimalsCattleGenetic VariationGenotypeINDEL MutationMalePolymorphism, Single NucleotideSequence Analysis, DNA

Identifiers

PMID23826801
PMCPMC3716689

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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.