Private haplotypes can reveal local adaptation
1 Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
2 UMR 7206 Eco-anthropologie et Ethnobiologie, CNRS-MNHN-Université Paris VII, Paris, France
3 Laboratoire TIMC-IMAG, Centre National de la Recherche Scientifique, Université Joseph Fourier, Grenoble, France
4 Science for Life Laboratory, Uppsala University, Uppsala, Sweden
BMC Genetics 2014, 15:61 doi:10.1186/1471-2156-15-61Published: 22 May 2014
Genome-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.
We 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.
From 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.