Evidence map›Paper›PMID 24885734›Full record

ArticleBMC genetics2014

Private haplotypes can reveal local adaptation.

Agnès E Sjöstrand, Per Sjödin, Mattias Jakobsson

Abstract read
In one paragraph

Article in BMC genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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  6. Population Genetics ofMicroorganisms · 2020
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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

3 authors.

Agnès E Sjöstrand
Per Sjödin
Mattias JakobssonDepartment of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden. mattias.jakobsson@ebc.uu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenome-wide scans for regions that demonstrate deviating patterns of genetic variation have become common approaches for finding genes targeted by selection. Several genomic patterns have been utilized for this purpose, including deviations in haplotype homozygosity, frequency spectra and genetic differentiation between populations.

resultsWe describe a novel approach based on the Maximum Frequency of Private Haplotypes--MFPH--to search for signals of recent population-specific selection. The MFPH statistic is straightforward to compute for phased SNP- and sequence-data. Using both simulated and empirical data, we show that MFPH can be a powerful statistic to detect recent population-specific selection, that it performs at the same level as other commonly used summary statistics (e.g. FST, iHS and XP-EHH), and that MFPH in some cases capture signals of selection that are missed by other statistics. For instance, in the Maasai, MFPH reveals a strong signal of selection in a region where other investigated statistics fail to pick up a clear signal that contains the genes DOCK3, MAPKAPK3 and CISH. This region has been suggested to affect height in many populations based on phenotype-genotype association studies. It has specifically been suggested to be targeted by selection in Pygmy groups, which are on the opposite end of the human height spectrum compared to the Maasai.

conclusionsFrom the analysis of both simulated and publicly available empirical data, we show that MFPH represents a summary statistic that can provide further insight concerning population-specific adaptation.

Indexed as

HaplotypesSelection, GeneticAdaptation, PhysiologicalGenetics, PopulationHumansModels, GeneticPolymorphism, Single Nucleotide

Identifiers

PMID24885734
PMCPMC4040116

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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.