Evidence map›Paper›PMID 24149650›Full record

ArticleHeredity2014

Estimating genome-wide heterozygosity: effects of demographic history and marker type.

J M Miller, R M Malenfant, P David, C S Davis, J Poissant, J T Hogg, M Festa-Bianchet, D W Coltman

Abstract read
In one paragraph

Article in Heredity, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
–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

43 citing papers in PubMed.

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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

8 authors.

J M MillerDepartment of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
R M MalenfantDepartment of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
P DavidCentre d'Ecologie Fonctionnelle et Evolutive, UMR 5175, Montpellier, France.
C S DavisDepartment of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.
J PoissantDepartment of Animal and Plant Sciences, University of Sheffield, Sheffield, UK.
J T HoggMontana Conservation Science Institute, Missoula, MT, USA.
M Festa-BianchetDépartement de biologie et Centre d'Études Nordiques, Université de Sherbrooke, Sherbrooke, Québec, Canada.
D W ColtmanDepartment of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heterozygosity-fitness correlations (HFCs) are often used to link individual genetic variation to differences in fitness. However, most studies examining HFCs find weak or no correlations. Here, we derive broad theoretical predictions about how many loci are needed to adequately measure genomic heterozygosity assuming different levels of identity disequilibrium (ID), a proxy for inbreeding. We then evaluate the expected ability to detect HFCs using an empirical data set of 200 microsatellites and 412 single nucleotide polymorphisms (SNPs) genotyped in two populations of bighorn sheep (Ovis canadensis), with different demographic histories. In both populations, heterozygosity was significantly correlated across marker types, although the strength of the correlation was weaker in a native population compared with one founded via translocation and later supplemented with additional individuals. Despite being bi-allelic, SNPs had similar correlations to genome-wide heterozygosity as microsatellites in both populations. For both marker types, this association became stronger and less variable as more markers were considered. Both populations had significant levels of ID; however, estimates were an order of magnitude lower in the native population. As with heterozygosity, SNPs performed similarly to microsatellites, and precision and accuracy of the estimates of ID increased as more loci were considered. Although dependent on the demographic history of the population considered, these results illustrate that genome-wide heterozygosity, and therefore HFCs, are best measured by a large number of markers, a feat now more realistically accomplished with SNPs than microsatellites.

Indexed as

GenomeHeterozygoteModels, GeneticPolymorphism, Single NucleotideAlbertaAnimalsGenetic FitnessGenetics, PopulationInbreedingMicrosatellite RepeatsMontanaSheep, Bighorn

Identifiers

PMID24149650
PMCPMC3931164

What OpenQuestion holds

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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.