PSMC (pairwise sequentially Markovian coalescent) analysis of RAD (restriction site associated DNA) sequencing data

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The pairwise sequentially Markovian coalescent (PSMC) method uses the genome sequence of a single individual to estimate demographic history covering a time span of thousands of generations. Although originally designed for whole-genome data, we here use simulations to investigate its applicability to reference genome-aligned restriction site associated DNA (RAD) data. We find that RAD data can potentially be used for PSMC analysis, but at present with limitations. The key factor is the proportion (p) of the genome that the RAD data covers. In our simulations, a proportion of 10% can still retain a substantial amount of coalescent information, whereas for 1% estimation becomes unreliable. The performance depends strongly on mutation rate (mu) and recombination rate (r) and is proportional to mu*p/r. When the value of this term is low, increasing the amount of data and number of iterations helps restoring the power of the estimation. We subsequently analyse one whole-genome-sequenced and 17 RAD-sequenced three-spined sticklebacks (Gasterosteus aculeatus) from a lake in Greenland. The whole-genome sequence suggests a relatively recent expansion and decline within ca. 4000-40 000 generations ago, possibly reflecting postglacial expansion and founding of the lake population. RAD data, where chromosomes from 10 individuals are combined, identify a similar pattern. Our study provides guidance about the use of PSMC analysis and suggests measures that can improve its utility for RAD data. Finally, the study shows that RAD loci in general contain coalescent information that can be used for developing more targeted methods.

Original languageEnglish
JournalMolecular Ecology Resources
Pages (from-to)631-641
Number of pages11
Publication statusPublished - Jul 2017

    Research areas

  • demographic history, pairwise sequentially Markovian coalescent (PSMC), RAD sequencing, three-spined stickleback, whole-genome sequencing, WHOLE-GENOME SEQUENCES, POPULATION GENOMICS, HISTORY, STICKLEBACKS, REVEAL, NUCLEOTIDE, SIGNATURES, EVOLUTION, DISCOVERY, IMPACT

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