The bigger picture of population genomics

ScienceDaily (Jan. 5, 2012) ? With the availability of rapid-throughput methods and the associated drop in sequencing costs, more and more laboratories are generating more and more data relating to the sequence of DNA, the hereditary material responsible for the differences between species and individuals. But making sense of the mass of data remains tricky and attention is switching to automatic procedures to help researchers understand large amounts of sequence information. The group of Christian Schl?tterer at the University of Veterinary Medicine, Vienna has now developed a tool to compare data from sequences of pooled samples.

The program is described in the current issue of the journal Bioinformatics.

Not so long ago it was the work of many years to sequence the genome of a single organism: the human genome project, for example, took many laboratories a total of 13 years to complete. The availability of so-called next-generation sequencing methods makes it easy -- and comparatively cheap -- to sequence DNA, although sequencing the large number of individuals required for population genetics studies is still time-consuming and costly and has thus been restricted to few organisms.

The group of Christian Schl?tterer of the Institute of Population Genetics at the University of Veterinary Medicine, Vienna has shown previously that pooling samples enables population genetics studies to be undertaken at significantly reduced costs. Despite the wide applicability and obvious power of the method, however, it has so far proven possible to apply next-generation sequencing at the scale of populations to only few model systems. The problem lies in the interpretation of the data. And this is where the latest work from Schl?tterer's group comes in. Robert Kofler, Ram Vinay Pandey and Schl?tterer now report the development of a software package -- catchily termed "PoPoolation2" -- that makes it possible even for non-experts to compare populations.

The package offers a wide range of statistical methods to determine how the frequencies of particular forms -- termed alleles -- of genes vary between populations. The program has been tested on the sequences of a single chromosome from two distinct populations of the fruit fly Drosophila melanogaster and the results confirm that the program can correctly predict the levels of divergence between the samples. As Schl?tterer says, "PoPoolation2 helps us compare the allele frequencies between populations. It will enable us quickly and cheaply to compare how populations of different species have adapted differently to their environments, giving us better information on the big picture of evolution in practice."

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Story Source:

The above story is reprinted from materials provided by Veterin?rmedizinische Universit?t Wien, via AlphaGalileo.

Note: Materials may be edited for content and length. For further information, please contact the source cited above.

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Journal Reference:

1. R. Kofler, R. V. Pandey, C. Schlotterer. PoPoolation2: identifying differentiation between populations using sequencing of pooled DNA samples (Pool-Seq). Bioinformatics, 2011; 27 (24): 3435 DOI: 10.1093/bioinformatics/btr589

Note: If no author is given, the source is cited instead.

Disclaimer: This article is not intended to provide medical advice, diagnosis or treatment. Views expressed here do not necessarily reflect those of ScienceDaily or its staff.

Source: http://www.sciencedaily.com/releases/2012/01/120105101445.htm

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