Abstract
BackgroundRecombination plays an important role in the maintenance of genetic diversity in many types of organisms, especially diploid eukaryotes. Recombination can be studied and used to map diseases. However, recombination adds a great deal of complexity to the genetic information. This renders estimation of evolutionary parameters more difficult. After the coalescent process was formulated, models capable of describing recombination using graphs, such as ancestral recombination graphs (ARG) were also developed. There are two typical models based on which to simulate ARG: back-in-time model such as ms and spatial model including Wiuf&Hein’s, SMC, SMC’, and MaCS.ResultsIn this study, a new method of modeling coalescence with recombination, Spatial Coalescent simulator (SC), was developed, which considerably improved the algorithm described by Wiuf and Hein. The present algorithm constructs ARG spatially along the sequence, but it does not produce any redundant branches which are inevitable in Wiuf and Hein’s algorithm. Interestingly, the distribution of ARG generated by the present new algorithm is identical to that generated by a typical back-in-time model adopted by ms, an algorithm commonly used to model coalescence. It is here demonstrated that the existing approximate methods such as the sequentially Markov coalescent (SMC), a related method called SMC′, and Markovian coalescent simulator (MaCS) can be viewed as special cases of the present method. Using simulation analysis, the time to the most common ancestor (TMRCA) in the local trees of ARGs generated by the present algorithm was found to be closer to that produced by ms than time produced by MaCS. Sample-consistent ARGs can be generated using the present method. This may significantly reduce the computational burden.ConclusionIn summary, the present method and algorithm may facilitate the estimation and description of recombination in population genomics and evolutionary biology.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2105-15-273) contains supplementary material, which is available to authorized users.
Highlights
Recombination plays an important role in the maintenance of genetic diversity in many types of organisms, especially diploid eukaryotes
(3) The present algorithm was designed under the infinite sites model, in which the mutation is independent of the coalescent with recombination so that it occurs with a Poisson distribution on the ancestral recombination graphs (ARG)
(4) In the present algorithm, a gene copies the genetic information of its parents if recombination does not occur
Summary
Recombination plays an important role in the maintenance of genetic diversity in many types of organisms, especially diploid eukaryotes. Recombination adds a great deal of complexity to the genetic information. This renders estimation of evolutionary parameters more difficult. After the coalescent process was formulated, models capable of describing recombination using graphs, such as ancestral recombination graphs (ARG) were developed. The genealogical relationship among a number of sampled sequences drawn from a particular generation. Due to the increased complexity added by recombination, a graph rather than a single tree is needed to describe the genealogical relationship. This graph, called an ancestral recombination graph (ARG), is made up of many local coalescent trees [4]. The node in ARG at which two branches converge denotes a coalescent event, and the node at which one branch splits into two denotes a recombination event
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