Evidence map›Paper›PMID 28709397›Full record

ArticleGenetics, selection, evolution : GSE2017

Use of haplotypes to identify regions harbouring lethal recessive variants in pigs.

David M Howard, Ricardo Pong-Wong, Pieter W Knap, John A Woolliams

Open access · goldAbstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.5field-weighted citation impact, top 15% 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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 11 citations in OpenAlex.

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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

4 authors at 2 institutions in 2 countries.

David M HowardThe Roslin Institute, R(D)SVS, The University of Edinburgh, Midlothian, UK. d.howard@ed.ac.uk.
Ricardo Pong-WongThe Roslin Institute, R(D)SVS, The University of Edinburgh, Midlothian, UK.
Pieter W KnapGenus-PIC, Ratsteich 31, 24837, Schleswig, Germany.
John A WoolliamsThe Roslin Institute, R(D)SVS, The University of Edinburgh, Midlothian, UK.
Roslin Institute · GBGender Studies · CZ

Funding

Biotechnology and Biological Sciences Research Council 1115658Biotechnology and Biological Sciences Research Council BBS/E/D/20211553Biotechnology and Biological Sciences Research Council BBS/E/D/20211554
6 · The paper itself

Abstract

backgroundLethal recessive genetic variants are maintained at relatively low frequencies in a population in the heterozygous state, but by definition are fatal and therefore unobserved in the homozygous state. Since haplotypes allow the tagging of rare and untyped genetic variants, they have potential for studying lethal recessive variants. In this study, we used a large commercial population to identify putative lethal recessive haplotypes that impact either the total number born (TNB) or the number born alive (NBA) as a proportion of the total number born (NBA/TNB). We also compared the use of haplotypes with a single nucleotide polymorphism (SNP)-by-SNP approach and examined the benefits of using additional haplotypes imputed from low-density genotype data for the detection of lethal recessive variants. Candidate haplotypes were identified using population-wide haplotype frequencies and within-family analyses. These candidate haplotypes were subsequently assessed for putative lethal recessive effects on TNB and NBA/TNB by comparing carrier-to-carrier matings with carrier-to-non-carrier matings.

resultsUsing both medium-density and imputed low-density genotype data six regions were identified as containing putative lethal recessive haplotypes that had an effect on TNB. It is likely that these regions were related to at least four putative lethal recessive variants, each located on a different chromosome. Evidence for putative lethal recessive effects on TNB was found on chromosomes 1, 6, 10 and 14 using haplotypes. Using haplotypes from individuals genotyped only at medium-density or a SNP-by-SNP approach did not detect any lethal recessive effects. No lethal recessive haplotypes or SNPs were detected that had an effect on NBA/TNB.

conclusionsWe show that the use of haplotypes from combining medium-density and imputed low-density genotype data is superior for the identification of lethal recessive variants compared to both a SNP-by-SNP approach and to the use of only medium-density data. We developed a formal statistical framework that provided sufficient power to detect lethal recessive variants in species, which produce large full-sib families, while reducing false positive or type I errors. Applying this framework results in improvements in reproductive performance by purging lethal recessive alleles from a population in a timely and cost-effective manner.

Indexed as

AnimalsGene FrequencyGenes, LethalGenes, RecessiveGenotypeHaplotypesPolymorphism, Single NucleotideSus scrofaSwine

Identifiers

PMID28709397
PMCPMC5512953
OpenAlexW2736105212

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.