Multiplexed SNP Typing of Ancient DNA Clarifies the Origin of Andaman mtDNA Haplogroups amongst South Asian Tribal Populations

The issue of errors in genetic data sets is of growing concern, particularly in population genetics where whole genome mtDNA sequence data is coming under increased scrutiny. Multiplexed PCR reactions, combined with SNP typing, are currently under-exploited in this context, but have the potential to genotype whole populations rapidly and accurately, significantly reducing the amount of errors appearing in published data sets. To show the sensitivity of this technique for screening mtDNA genomic sequence data, 20 historic samples of the enigmatic Andaman Islanders and 12 modern samples from three Indian tribal populations (Chenchu, Lambadi and Lodha) were genotyped for 20 coding region sites after provisional haplogroup assignment with control region sequences. The genotype data from the historic samples significantly revise the topologies for the Andaman M31 and M32 mtDNA lineages by rectifying conflicts in published data sets. The new Indian data extend the distribution of the M31a lineage to South Asia, challenging previous interpretations of mtDNA phylogeography. This genetic connection between the ancestors of the Andamanese and South Asian tribal groups ∼30 kya has important implications for the debate concerning migration routes and settlement patterns of humans leaving Africa during the late Pleistocene, and indicates the need for more detailed genotyping strategies. The methodology serves as a low-cost, high-throughput model for the production and authentication of data from modern or ancient DNA, and demonstrates the value of museum collections as important records of human genetic diversity

Minisequencing mitochondrial DNA pathogenic mutations

<p>Abstract</p> <p>Background</p> <p>There are a number of well-known mutations responsible of common mitochondrial DNA (mtDNA) diseases. In order to overcome technical problems related to the analysis of complete mtDNA genomes, a variety of different techniques have been proposed that allow the screening of coding region pathogenic mutations.</p> <p>Methods</p> <p>We here propose a minisequencing assay for the analysis of mtDNA mutations. In a single reaction, we interrogate a total of 25 pathogenic mutations distributed all around the whole mtDNA genome in a sample of patients suspected for mtDNA disease.</p> <p>Results</p> <p>We have detected 11 causal homoplasmic mutations in patients suspected for Leber disease, which were further confirmed by standard automatic sequencing. Mutations m.11778G>A and m.14484T>C occur at higher frequency than expected by change in the Galician (northwest Spain) patients carrying haplogroup J lineages (Fisher's Exact test, <it>P</it>-value < 0.01). The assay performs well in mixture experiments of wild:mutant DNAs that emulate heteroplasmic conditions in mtDNA diseases.</p> <p>Conclusion</p> <p>We here developed a minisequencing genotyping method for the screening of the most common pathogenic mtDNA mutations which is simple, fast, and low-cost. The technique is robust and reproducible and can easily be implemented in standard clinical laboratories. </p

A Note on Encodings of Phylogenetic Networks of Bounded Level

Driven by the need for better models that allow one to shed light into the question how life's diversity has evolved, phylogenetic networks have now joined phylogenetic trees in the center of phylogenetics research. Like phylogenetic trees, such networks canonically induce collections of phylogenetic trees, clusters, and triplets, respectively. Thus it is not surprising that many network approaches aim to reconstruct a phylogenetic network from such collections. Related to the well-studied perfect phylogeny problem, the following question is of fundamental importance in this context: When does one of the above collections encode (i.e. uniquely describe) the network that induces it? In this note, we present a complete answer to this question for the special case of a level-1 (phylogenetic) network by characterizing those level-1 networks for which an encoding in terms of one (or equivalently all) of the above collections exists. Given that this type of network forms the first layer of the rich hierarchy of level-k networks, k a non-negative integer, it is natural to wonder whether our arguments could be extended to members of that hierarchy for higher values for k. By giving examples, we show that this is not the case

Quarnet Inference Rules for Level-1 Networks

An important problem in phylogenetics is the construction of phylogenetic trees. One way to approach this problem, known as the supertree method, involves inferring a phylogenetic tree with leaves consisting of a set X of species from a collection of trees, each having leaf-set some subset of X. In the 1980s, Colonius and Schulze gave certain inference rules for deciding when a collection of 4-leaved trees, one for each 4-element subset of X, can be simultaneously displayed by a single supertree with leaf-set X. Recently, it has become of interest to extend this and related results to phylogenetic networks. These are a generalization of phylogenetic trees which can be used to represent reticulate evolution (where species can come together to form a new species). It has recently been shown that a certain type of phylogenetic network, called a (unrooted) level-1 network, can essentially be constructed from 4-leaved trees. However, the problem of providing appropriate inference rules for such networks remains unresolved. Here, we show that by considering 4-leaved networks, called quarnets, as opposed to 4-leaved trees, it is possible to provide such rules. In particular, we show that these rules can be used to characterize when a collection of quarnets, one for each 4-element subset of X, can all be simultaneously displayed by a level-1 network with leaf-set X. The rules are an intriguing mixture of tree inference rules, and an inference rule for building up a cyclic ordering of X from orderings on subsets of X of size 4. This opens up several new directions of research for inferring phylogenetic networks from smaller ones, which could yield new algorithms for solving the supernetwork problem in phylogenetics

Potential pitfalls in MitoChip detected tumor-specific somatic mutations: a call for caution when interpreting patient data

<p>Abstract</p> <p>Background</p> <p>Several investigators have employed high throughput mitochondrial sequencing array (MitoChip) in clinical studies to search mtDNA for markers linked to cancers. In consequence, a host of somatic mtDNA mutations have been identified as linked to different types of cancers. However, closer examination of these data show that there are a number of potential pitfalls in the detection tumor-specific somatic mutations in clinical case studies, thus urging caution in the interpretation of mtDNA data to the patients. This study examined mitochondrial sequence variants demonstrated in cancer patients, and assessed the reliability of using detected patterns of polymorphisms in the early diagnosis of cancer.</p> <p>Methods</p> <p>Published entire mitochondrial genomes from head and neck, adenoid cystic carcinoma, sessile serrated adenoma, and lung primary tumor from clinical patients were examined in a phylogenetic context and compared with known, naturally occurring mutations which characterize different populations.</p> <p>Results</p> <p>The phylogenetic linkage analysis of whole arrays of mtDNA mutations from patient cancerous and non-cancerous tissue confirmed that artificial recombination events occurred in studies of head and neck, adenoid cystic carcinoma, sessile serrated adenoma, and lung primary tumor. Our phylogenetic analysis of these tumor and control leukocyte mtDNA haplotype sequences shows clear cut evidence of mixed ancestries found in single individuals.</p> <p>Conclusions</p> <p>Our study makes two prescriptions: both in the clinical situation and in research 1. more care should be taken in maintaining sample identity and 2. analysis should always be undertaken with respect to all the data available and within an evolutionary framework to eliminate artifacts and mix-ups.</p

Circular Networks from Distorted Metrics

Trees have long been used as a graphical representation of species relationships. However complex evolutionary events, such as genetic reassortments or hybrid speciations which occur commonly in viruses, bacteria and plants, do not fit into this elementary framework. Alternatively, various network representations have been developed. Circular networks are a natural generalization of leaf-labeled trees interpreted as split systems, that is, collections of bipartitions over leaf labels corresponding to current species. Although such networks do not explicitly model specific evolutionary events of interest, their straightforward visualization and fast reconstruction have made them a popular exploratory tool to detect network-like evolution in genetic datasets. Standard reconstruction methods for circular networks, such as Neighbor-Net, rely on an associated metric on the species set. Such a metric is first estimated from DNA sequences, which leads to a key difficulty: distantly related sequences produce statistically unreliable estimates. This is problematic for Neighbor-Net as it is based on the popular tree reconstruction method Neighbor-Joining, whose sensitivity to distance estimation errors is well established theoretically. In the tree case, more robust reconstruction methods have been developed using the notion of a distorted metric, which captures the dependence of the error in the distance through a radius of accuracy. Here we design the first circular network reconstruction method based on distorted metrics. Our method is computationally efficient. Moreover, the analysis of its radius of accuracy highlights the important role played by the maximum incompatibility, a measure of the extent to which the network differs from a tree.Comment: Submitte

Sequential Deliberation for Social Choice

In large scale collective decision making, social choice is a normative study of how one ought to design a protocol for reaching consensus. However, in instances where the underlying decision space is too large or complex for ordinal voting, standard voting methods of social choice may be impractical. How then can we design a mechanism - preferably decentralized, simple, scalable, and not requiring any special knowledge of the decision space - to reach consensus? We propose sequential deliberation as a natural solution to this problem. In this iterative method, successive pairs of agents bargain over the decision space using the previous decision as a disagreement alternative. We describe the general method and analyze the quality of its outcome when the space of preferences define a median graph. We show that sequential deliberation finds a 1.208- approximation to the optimal social cost on such graphs, coming very close to this value with only a small constant number of agents sampled from the population. We also show lower bounds on simpler classes of mechanisms to justify our design choices. We further show that sequential deliberation is ex-post Pareto efficient and has truthful reporting as an equilibrium of the induced extensive form game. We finally show that for general metric spaces, the second moment of of the distribution of social cost of the outcomes produced by sequential deliberation is also bounded

Triangle-Free Penny Graphs: Degeneracy, Choosability, and Edge Count

We show that triangle-free penny graphs have degeneracy at most two, list coloring number (choosability) at most three, diameter $D=\Omega(\sqrt n)$, and at most $\min\bigl(2n-\Omega(\sqrt n),2n-D-2\bigr)$ edges.Comment: 10 pages, 2 figures. To appear at the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017

Reassessing the role of mitochondrial DNA mutations in autism spectrum disorder

<p>Abstract</p> <p>Background</p> <p>There is increasing evidence that impairment of mitochondrial energy metabolism plays an important role in the pathophysiology of autism spectrum disorders (ASD; OMIM number: 209850). A significant proportion of ASD cases display biochemical alterations suggestive of mitochondrial dysfunction and several studies have reported that mutations in the mitochondrial DNA (mtDNA) molecule could be involved in the disease phenotype.</p> <p>Methods</p> <p>We analysed a cohort of 148 patients with idiopathic ASD for a number of mutations proposed in the literature as pathogenic in ASD. We also carried out a case control association study for the most common European haplogroups (hgs) and their diagnostic single nucleotide polymorphisms (SNPs) by comparing cases with 753 healthy and ethnically matched controls.</p> <p>Results</p> <p>We did not find statistical support for an association between mtDNA mutations or polymorphisms and ASD.</p> <p>Conclusions</p> <p>Our results are compatible with the idea that mtDNA mutations are not a relevant cause of ASD and the frequent observation of concomitant mitochondrial dysfunction and ASD could be due to nuclear factors influencing mitochondrion functions or to a more complex interplay between the nucleus and the mitochondrion/mtDNA.</p