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We introduce the Maximum Frequency of Private Haplotypes (MFPH) statistic to identify recent population-specific selection. MFPH performs comparably to existing methods and can detect selection signals missed by other approaches.

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Area of Science:

  • Population genetics
  • Genomics
  • Evolutionary biology

Background:

  • Genome-wide scans identify genes under selection by analyzing genetic variation patterns.
  • Common methods include haplotype homozygosity, frequency spectra, and genetic differentiation.

Purpose of the Study:

  • To introduce and evaluate a novel statistic, Maximum Frequency of Private Haplotypes (MFPH), for detecting recent population-specific selection.
  • To compare MFPH performance against established selection detection statistics.

Main Methods:

  • The MFPH statistic was developed for phased SNP and sequence data.
  • Performance was assessed using both simulated and empirical genomic datasets.
  • MFPH was compared with established statistics like FST, iHS, and XP-EHH.

Main Results:

  • MFPH is a powerful statistic for detecting recent population-specific selection.
  • It performs comparably to FST, iHS, and XP-EHH.
  • MFPH identified a selection signal in Maasai populations (genes DOCK3, MAPKAPK3, CISH) missed by other statistics, potentially related to height adaptation.

Conclusions:

  • MFPH provides valuable insights into population-specific adaptation.
  • It serves as a complementary tool to existing methods for identifying genomic regions under selection.