Mutational Patterns in RNA Secondary Structure Evolution Examined in Three RNA Families

The goal of this work was to study mutational patterns in the evolution of RNA secondary structure. We analyzed bacterial tmRNA, RNaseP and eukaryotic telomerase RNA secondary structures, mapping structural variability onto phylogenetic trees constructed primarily from rRNA sequences. We found that secondary structures evolve both by whole stem insertion/deletion, and by mutations that create or disrupt stem base pairing. We analyzed the evolution of stem lengths and constructed substitution matrices describing the changes responsible for the variation in the RNA stem length. In addition, we used principal component analysis of the stem length data to determine the most variable stems in different families of RNA. This data provides new insights into the evolution of RNA secondary structures and patterns of variation in the lengths of double helical regions of RNA molecules. Our findings will facilitate design of improved mutational models for RNA structure evolution

Phylogenetic Codivergence Supports Coevolution of Mimetic Heliconius Butterflies

The unpalatable and warning-patterned butterflies _Heliconius erato_ and _Heliconius melpomene_ provide the best studied example of mutualistic Müllerian mimicry, thought – but rarely demonstrated – to promote coevolution. Some of the strongest available evidence for coevolution comes from phylogenetic codivergence, the parallel divergence of ecologically associated lineages. Early evolutionary reconstructions suggested codivergence between mimetic populations of _H. erato_ and _H. melpomene_, and this was initially hailed as the most striking known case of coevolution. However, subsequent molecular phylogenetic analyses found discrepancies in phylogenetic branching patterns and timing (topological and temporal incongruence) that argued against codivergence. We present the first explicit cophylogenetic test of codivergence between mimetic populations of _H. erato_ and _H. melpomene_, and re-examine the timing of these radiations. We find statistically significant topological congruence between multilocus coalescent population phylogenies of _H. erato_ and _H. melpomene_, supporting repeated codivergence of mimetic populations. Divergence time estimates, based on a Bayesian coalescent model, suggest that the evolutionary radiations of _H. erato_ and _H. melpomene_ occurred over the same time period, and are compatible with a series of temporally congruent codivergence events. This evidence supports a history of reciprocal coevolution between Müllerian co-mimics characterised by phylogenetic codivergence and parallel phenotypic change

Rebooting the human mitochondrial phylogeny: an automated and scalable methodology with expert knowledge

<p>Abstract</p> <p>Background</p> <p>Mitochondrial DNA is an ideal source of information to conduct evolutionary and phylogenetic studies due to its extraordinary properties and abundance. Many insights can be gained from these, including but not limited to screening genetic variation to identify potentially deleterious mutations. However, such advances require efficient solutions to very difficult computational problems, a need that is hampered by the very plenty of data that confers strength to the analysis.</p> <p>Results</p> <p>We develop a systematic, automated methodology to overcome these difficulties, building from readily available, public sequence databases to high-quality alignments and phylogenetic trees. Within each stage in an autonomous workflow, outputs are carefully evaluated and outlier detection rules defined to integrate expert knowledge and automated curation, hence avoiding the manual bottleneck found in past approaches to the problem. Using these techniques, we have performed exhaustive updates to the human mitochondrial phylogeny, illustrating the power and computational scalability of our approach, and we have conducted some initial analyses on the resulting phylogenies.</p> <p>Conclusions</p> <p>The problem at hand demands careful definition of inputs and adequate algorithmic treatment for its solutions to be realistic and useful. It is possible to define formal rules to address the former requirement by refining inputs directly and through their combination as outputs, and the latter are also of help to ascertain the performance of chosen algorithms. Rules can exploit known or inferred properties of datasets to simplify inputs through partitioning, therefore cutting computational costs and affording work on rapidly growing, otherwise intractable datasets. Although expert guidance may be necessary to assist the learning process, low-risk results can be fully automated and have proved themselves convenient and valuable.</p

Integrated multiple sequence alignment

Sammeth M. Integrated multiple sequence alignment. Bielefeld (Germany): Bielefeld University; 2005.The thesis presents enhancements for automated and manual multiple sequence alignment: existing alignment algorithms are made more easily accessible and new algorithms are designed for difficult cases. Firstly, we introduce the QAlign framework, a graphical user interface for multiple sequence alignment. It comprises several state-of-the-art algorithms and supports their parameters by convenient dialogs. An alignment viewer with guided editing functionality can also highlight or print regions of the alignment. Also phylogenetic features are provided, e.g., distance-based tree reconstruction methods, corrections for multiple substitutions and a tree viewer. The modular concept and the platform-independent implementation guarantee an easy extensibility. Further, we develop a constrained version of the divide-and-conquer alignment such that it can be restricted by anchors found earlier with local alignments. It can be shown that this method shares attributes of both, local and global aligners, in the quality of results as well as in the computation time. We further modify the local alignment step to work on bipartite (or even multipartite) sets for sequences where repeats overshadow valuable sequence information. In the end a technique is established that can accurately align sequences containing eventually repeated motifs. Finally, another algorithm is presented that allows to compare tandem repeat sequences by aligning them with respect to their possible repeat histories. We describe an evolutionary model including tandem duplications and excisions, and give an exact algorithm to compare two sequences under this model

Homology inference with specific molecular constraints

Evolutionary processes can be considered at multiple levels of biological organization. The work developed in this thesis focuses on protein molecular evolution. Although proteins are linear polymers composed from a basic set of 20 amino acids, they generate an enormous variety of form and function. Proteins that have arisen by a common descent are classified into families; they often share common properties including similarities in sequence, structure, and function. Multiple methods have been developed to infer evolutionary relationships between proteins and classify them into families. Yet, those generic methods are often inaccurate, especially when specific protein properties limit their applications. In this thesis, we analyse two protein classes that are often difficult for the evolutionary analysis: the coiled-coils – repetitive protein domains defined by a simple widespread peptide motif (chapters 2 and 3) and Rab small GTPases – a large family of closely related proteins (chapters 4 and 5). In both cases, we analyse the specific properties that determine protein structure and function and use them to improve their evolutionary inference