Developing and applying heterogeneous phylogenetic models with XRate

Modeling sequence evolution on phylogenetic trees is a useful technique in computational biology. Especially powerful are models which take account of the heterogeneous nature of sequence evolution according to the "grammar" of the encoded gene features. However, beyond a modest level of model complexity, manual coding of models becomes prohibitively labor-intensive. We demonstrate, via a set of case studies, the new built-in model-prototyping capabilities of XRate (macros and Scheme extensions). These features allow rapid implementation of phylogenetic models which would have previously been far more labor-intensive. XRate's new capabilities for lineage-specific models, ancestral sequence reconstruction, and improved annotation output are also discussed. XRate's flexible model-specification capabilities and computational efficiency make it well-suited to developing and prototyping phylogenetic grammar models. XRate is available as part of the DART software package: http://biowiki.org/DART .Comment: 34 pages, 3 figures, glossary of XRate model terminolog

A Case-by-Case Evolutionary Analysis of Four Imprinted Retrogenes

Retroposition is a widespread phenomenon resulting in the generation of new genes that are initially related to a parent gene via very high coding sequence similarity. We examine the evolutionary fate of four retrogenes generated by such an event; mouse Inpp5f_v2, Mcts2, Nap1l5, and U2af1-rs1. These genes are all subject to the epigenetic phenomenon of parental imprinting. We first provide new data on the age of these retrogene insertions. Using codon-based models of sequence evolution, we show these retrogenes have diverse evolutionary trajectories, including divergence from the parent coding sequence under positive selection pressure, purifying selection pressure maintaining parent-retrogene similarity, and neutral evolution. Examination of the expression pattern of retrogenes shows an atypical, broad pattern across multiple tissues. Protein 3D structure modeling reveals that a positively selected residue in U2af1-rs1, not shared by its parent, may influence protein conformation. Our case-by-case analysis of the evolution of four imprinted retrogenes reveals that this interesting class of imprinted genes, while similar in regulation and sequence characteristics, follow very varied evolutionary paths

Estimation of DNA Sequence Context-dependent Mutation Rates Using Primate Genomic Sequences: Application to Estimation of Selection Bias in Protein (Human TP53) Evolution

Understanding of the mechanism of DNA mutation process is critical for studying the functional consequences of genetic variation in clinical medicine (eg. drug response) as well as other complex traits (eg. gene expression and cause of common diseases). During the last several decades, many probabilistic models of DNA nucleotide substitution have been proposed for studying this process. A common feature of these mutation models is that they assume the nucleotides evolve independently at each site. In other words, they are sequence context-independent models. However, based on various biochemical studies, it is now recognized that the DNA mutation process resulting in substitutions in both coding and non-coding regions may depend on sequence context. We proposed here a more realistic sequence context-dependent mutation model, which could contribute to the better understanding of the DNA mutation spectrum in genomes.We also showed its application to protein evolution by separating the mutation bias and selection bias in amino acid substitutions.
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Ancient Pbx-Hox signatures define hundreds of vertebrate developmental enhancers

Background: Gene regulation through cis-regulatory elements plays a crucial role in development and disease. A major aim of the post-genomic era is to be able to read the function of cis-regulatory elements through scrutiny of their DNA sequence. Whilst comparative genomics approaches have identified thousands of putative regulatory elements, our knowledge of their mechanism of action is poor and very little progress has been made in systematically de-coding them. Results: Here, we identify ancient functional signatures within vertebrate conserved non-coding elements (CNEs) through a combination of phylogenetic footprinting and functional assay, using genomic sequence from the sea lamprey as a reference. We uncover a striking enrichment within vertebrate CNEs for conserved binding-site motifs of the Pbx-Hox hetero-dimer. We further show that these predict reporter gene expression in a segment specific manner in the hindbrain and pharyngeal arches during zebrafish development. Conclusions: These findings evoke an evolutionary scenario in which many CNEs evolved early in the vertebrate lineage to co-ordinate Hox-dependent gene-regulatory interactions that pattern the vertebrate head. In a broader context, our evolutionary analyses reveal that CNEs are composed of tightly linked transcription-factor binding-sites (TFBSs), which can be systematically identified through phylogenetic footprinting approaches. By placing a large number of ancient vertebrate CNEs into a developmental context, our findings promise to have a significant impact on efforts toward de-coding gene-regulatory elements that underlie vertebrate development, and will facilitate building general models of regulatory element evolution

Biological Sequence Simulation for Testing Complex Evolutionary Hypotheses: indel-Seq-Gen Version 2.0

Sequence simulation is an important tool in validating biological hypotheses as well as testing various bioinformatics and molecular evolutionary methods. Hypothesis testing relies on the representational ability of the sequence simulation method. Simple hypotheses are testable through simulation of random, homogeneously evolving sequence sets. However, testing complex hypotheses, for example, local similarities, requires simulation of sequence evolution under heterogeneous models. To this end, we previously introduced indel-Seq-Gen version 1.0 (iSGv1.0; indel, insertion/deletion). iSGv1.0 allowed heterogeneous protein evolution and motif conservation as well as insertion and deletion constraints in subsequences. Despite these advances, for complex hypothesis testing, neither iSGv1.0 nor other currently available sequence simulation methods is sufficient. indel-Seq-Gen version 2.0 (iSGv2.0) aims at simulating evolution of highly divergent DNA sequences and protein superfamilies. iSGv2.0 improves upon iSGv1.0 through the addition of lineage-specific evolution, motif conservation using PROSITE-like regular expressions, indel tracking, subsequence-length constraints, as well as coding and noncoding DNA evolution. Furthermore, we formalize the sequence representation used for iSGv2.0 and uncover a flaw in the modeling of indels used in current state of the art methods, which biases simulation results for hypotheses involving indels. We fix this flaw in iSGv2.0 by using a novel discrete stepping procedure. Finally, we present an example simulation of the calycin-superfamily sequences and compare the performance of iSGv2.0 with iSGv1.0 and random model of sequence evolution

Ittero: multippelt sammenstillingsprogram for kodende nukleinsyresekvenser basert på evolusjonære modeller

This thesis addresses programs and algorithms for multiple alignments and models of sequence evolution. The first part of the thesis is about multiple alignment algorithms and programs in general. Some programs for multiple alignments are presented. This part also contains a presentation of models for nucletide substitution and codon-substitution models. The other part is a study of how one can use these models of sequence evolution in a multiple alignment program Ittero. Ittero is a program made especially for this thesis. It is used only for coding DNA sequences and because of that, it allows only gaps that are x times the length of a codon

The genome of cultivated peanut provides insight into legume karyotypes, polyploid evolution and crop domestication

High oil and protein content make tetraploid peanut a leading oil and food legume. Here we report a high-quality peanut genome sequence, comprising 2.54 Gb with 20 pseudomolecules and 83,709 protein-coding gene models. We characterize gene functional groups implicated in seed size evolution, seed oil content, disease resistance and symbiotic nitrogen fixation. The peanut B subgenome has more genes and general expression dominance, temporally associated with long-terminal-repeat expansion in the A subgenome that also raises questions about the A-genome progenitor. The polyploid genome provided insights into the evolution of Arachis hypogaea and other legume chromosomes. Resequencing of 52 accessions suggests that independent domestications formed peanut ecotypes. Whereas 0.42–0.47 million years ago (Ma) polyploidy constrained genetic variation, the peanut genome sequence aids mapping and candidate-gene discovery for traits such as seed size and color, foliar disease resistance and others, also providing a cornerstone for functional genomics and peanut improvement

PhyloCSF: a comparative genomics method to distinguish protein-coding and non-coding regions

As high-throughput transcriptome sequencing provides evidence for novel transcripts in many species, there is a renewed need for accurate methods to classify small genomic regions as protein-coding or non-coding. We present PhyloCSF, a novel comparative genomics method that analyzes a multi-species nucleotide sequence alignment to determine whether it is likely to represent a conserved protein-coding region, based on a formal statistical comparison of phylogenetic codon models. We show that PhyloCSF's classification performance in 12-species _Drosophila_ genome alignments exceeds all other methods we compared in a previous study, and we provide a software implementation for use by the community. We anticipate that this method will be widely applicable as the transcriptomes of many additional species, tissues, and subcellular compartments are sequenced, particularly in the context of ENCODE and modENCODE

Modeling the Evolution of Regulatory Elements by Simultaneous Detection and Alignment with Phylogenetic Pair HMMs

The computational detection of regulatory elements in DNA is a difficult but important problem impacting our progress in understanding the complex nature of eukaryotic gene regulation. Attempts to utilize cross-species conservation for this task have been hampered both by evolutionary changes of functional sites and poor performance of general-purpose alignment programs when applied to non-coding sequence. We describe a new and flexible framework for modeling binding site evolution in multiple related genomes, based on phylogenetic pair hidden Markov models which explicitly model the gain and loss of binding sites along a phylogeny. We demonstrate the value of this framework for both the alignment of regulatory regions and the inference of precise binding-site locations within those regions. As the underlying formalism is a stochastic, generative model, it can also be used to simulate the evolution of regulatory elements. Our implementation is scalable in terms of numbers of species and sequence lengths and can produce alignments and binding-site predictions with accuracy rivaling or exceeding current systems that specialize in only alignment or only binding-site prediction. We demonstrate the validity and power of various model components on extensive simulations of realistic sequence data and apply a specific model to study Drosophila enhancers in as many as ten related genomes and in the presence of gain and loss of binding sites. Different models and modeling assumptions can be easily specified, thus providing an invaluable tool for the exploration of biological hypotheses that can drive improvements in our understanding of the mechanisms and evolution of gene regulation

A Sequence-Based, Population Genetic Model of Regulatory Pathway Evolution

Complex phenotypes with genetic cause are understood through many processes, including regulatory pathways, but our evolutionary understanding of these critical structures is undermined by poor models which fail to preserve the underlying sequence structure and to incorporate population genetics. In response, this thesis builds a pathway model of evolution from its underlying sequence structure and validates it against a pertinent problem in genome evolution which uniquely leverage the developed model. Specifically, my model preserves sequence characteristics through a novel data structure and pathway-level mutation and recombination rates which are functions of sequence properties. The utility of the model is validated with a study quantifying the advantages and disadvantages of expansive non-coding DNA regions on the establishment of optimal pathways. Because the model presented in this thesis rectifies many fundamental problems in previous models, it may serve as a critical tool for future work in pathway evolution