How good are indirect tests at detecting recombination in human mtDNA?

Empirical proof of human mitochondrial DNA (mtDNA) recombination in somatic tissues was obtained in 2004; however, a lack of irrefutable evidence exists for recombination in human mtDNA at the population level. Our inability to demonstrate convincingly a signal of recombination in population data sets of human mtDNA sequence may be due, in part, to the ineffectiveness of current indirect tests. Previously, we tested some well-established indirect tests of recombination (linkage disequilibrium vs. distance using D' and r(2), Homoplasy Test, Pairwise Homoplasy Index, Neighborhood Similarity Score, and Max χ(2)) on sequence data derived from the only empirically confirmed case of human mtDNA recombination thus far and demonstrated that some methods were unable to detect recombination. Here, we assess the performance of these six well-established tests and explore what characteristics specific to human mtDNA sequence may affect their efficacy by simulating sequence under various parameters with levels of recombination (ρ) that vary around an empirically derived estimate for human mtDNA (population parameter ρ = 5.492). No test performed infallibly under any of our scenarios, and error rates varied across tests, whereas detection rates increased substantially with ρ values > 5.492. Under a model of evolution that incorporates parameters specific to human mtDNA, including rate heterogeneity, population expansion, and ρ = 5.492, successful detection rates are limited to a range of 7-70% across tests with an acceptable level of false-positive results: the neighborhood similarity score incompatibility test performed best overall under these parameters. Population growth seems to have the greatest impact on recombination detection probabilities across all models tested, likely due to its impact on sequence diversity. The implications of our findings on our current understanding of mtDNA recombination in humans are discussed.

Fiji: an open-source platform for biological-image analysis.

Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.

Can indirect tests detect a known recombination event in human mtDNA?

Whether human mitochondrial DNA (mtDNA) recombines sufficiently to influence its evolution, evolutionary analysis, and disease etiology, remains equivocal. Overall, evidence from indirect studies of population genetic data suggests that recombination is not occurring at detectable levels. This may be explained by no, or low, recombination or, alternatively, current indirect tests may be incapable of detecting recombination in human mtDNA. To investigate the latter, we have tested whether six well-established indirect tests of recombination could detect recombination in a human mtDNA data set, in which its occurrence had been empirically confirmed. Three showed statistical evidence for recombination (r(2) vs. distance, the Homoplasy test, Neighborhood Similarity Score), and three did not (D' vs. distance, Max Chi Squared, Pairwise Homoplasy Index). Possible reasons for detection failure are discussed. Further, evidence from earlier studies suggesting a lack of recombination in mtDNA in humans is reconsidered, taking into account the appropriateness of the tests used, based on our new findings.

Revealing the hidden complexities of mtDNA inheritance.

Mitochondrial DNA (mtDNA) is a pivotal tool in molecular ecology, evolutionary and population genetics. The power of mtDNA analyses derives from a relatively high mutation rate and the apparent simplicity of mitochondrial inheritance (maternal, without recombination), which has simplified modelling population history compared to the analysis of nuclear DNA. However, in biology things are seldom simple, and advances in DNA sequencing and polymorphism detection technology have documented a growing list of exceptions to the central tenets of mitochondrial inheritance, with paternal leakage, heteroplasmy and recombination now all documented in multiple systems. The presence of paternal leakage, recombination and heteroplasmy can have substantial impact on analyses based on mtDNA, affecting phylogenetic and population genetic analyses, estimates of the coalescent and the myriad of other parameters that are dependent on such estimates. Here, we review our understanding of mtDNA inheritance, discuss how recent findings mean that established ideas may need to be re-evaluated, and we assess the implications of these new-found complications for molecular ecologists who have relied for decades on the assumption of a simpler mode of inheritance. We show how it is possible to account for recombination and heteroplasmy in evolutionary and population analyses, but that accurate estimates of the frequencies of biparental inheritance and recombination are needed. We also suggest how nonclonal inheritance of mtDNA could be exploited, to increase the ways in which mtDNA can be used in analyses.