Evidence map›Paper›PMID 27877200›Full record

ReviewEvolutionary applications2016

Genomics advances the study of inbreeding depression in the wild.

Marty Kardos, Helen R Taylor, Hans Ellegren, Gordon Luikart, Fred W Allendorf

Abstract readReview
In one paragraph

Review in Evolutionary applications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers.

0numbers the graph read from it
0cells of the map it votes in
137citing 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

137 citing papers in PubMed.

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77 more citing papers are in PubMed but not listed here.

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

5 authors.

Marty KardosDepartment of Evolutionary Biology Evolutionary Biology Centre Uppsala University Uppsala Sweden.
Helen R TaylorDepartment of Anatomy University of Otago Dunedin New Zealand.
Hans EllegrenDepartment of Evolutionary Biology Evolutionary Biology Centre Uppsala University Uppsala Sweden.
Gordon LuikartDivision of Biological Sciences University of Montana Missoula MT USA; Flathead Lake Biological Station Division of Biological Sciences University of Montana Polson MT USA.
Fred W AllendorfDivision of Biological Sciences University of Montana Missoula MT USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inbreeding depression (reduced fitness of individuals with related parents) has long been a major focus of ecology, evolution, and conservation biology. Despite decades of research, we still have a limited understanding of the strength, underlying genetic mechanisms, and demographic consequences of inbreeding depression in the wild. Studying inbreeding depression in natural populations has been hampered by the inability to precisely measure individual inbreeding. Fortunately, the rapidly increasing availability of high-throughput sequencing data means it is now feasible to measure the inbreeding of any individual with high precision. Here, we review how genomic data are advancing our understanding of inbreeding depression in the wild. Recent results show that individual inbreeding and inbreeding depression can be measured more precisely with genomic data than via traditional pedigree analysis. Additionally, the availability of genomic data has made it possible to pinpoint loci with large effects contributing to inbreeding depression in wild populations, although this will continue to be a challenging task in many study systems due to low statistical power. Now that reliably measuring individual inbreeding is no longer a limitation, a major focus of future studies should be to more accurately quantify effects of inbreeding depression on population growth and viability.

Indexed as

conservation geneticsfitnessidentity by descentpedigree analysiswhole‐genome resequencing

Identifiers

PMID27877200
PMCPMC5108213

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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.