Alignment-Free Population Genomics: An Efficient Estimator of Sequence Diversity

G3: Genes, Genomes, Genetics

Bernhard Haubold¹  Peter Pfaffelhuber² 

[1] Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, 24306 Plön, GermanyDepartment of Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, 24306 Plön, GermanyDepartment of Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, 24306 Plön, Germany;Mathematical Stochastics, Mathematical Institute, Albert-Ludwigs University, 79085 Freiburg, GermanyMathematical Stochastics, Mathematical Institute, Albert-Ludwigs University, 79085 Freiburg, GermanyMathematical Stochastics, Mathematical Institute, Albert-Ludwigs University, 79085 Freiburg, Germany

关键词: genetic diversity;    alignment-free;    maximum-likelihood;    Drosophila;    match length distribution;   

DOI  :  10.1534/g3.112.002527

学科分类：生物科学（综合）

来源: Genetics Society of America

【 摘 要 】

Comparative sequencing contributes critically to the functional annotation of genomes. One prerequisite for successful analysis of the increasingly abundant comparative sequencing data is the availability of efficient computational tools. We present here a strategy for comparing unaligned genomes based on a coalescent approach combined with advanced algorithms for indexing sequences. These algorithms are particularly efficient when analyzing large genomes, as their run time ideally grows only linearly with sequence length. Using this approach, we have derived and implemented a maximum-likelihood estimator of the average number of mismatches per site between two closely related sequences, π. By allowing for fluctuating coalescent times, we are able to improve a previously published alignment-free estimator of π. We show through simulation that our new estimator is fast and accurate even with moderate recombination (ρ ≤ π). To demonstrate its applicability to real data, we compare the unaligned genomes of Drosophila persimilis and D. pseudoobscura. In agreement with previous studies, our sliding window analysis locates the global divergence minimum between these two genomes to the pericentromeric region of chromosome 3.

【 授权许可】

Unknown