Phylogenetic reconstruction of ancestral character states for gene expression and mRNA splicing data

BACKGROUND: As genomes evolve after speciation, gene content, coding sequence, gene expression, and splicing all diverge with time from ancestors with close relatives. A minimum evolution general method for continuous character analysis in a phylogenetic perspective is presented that allows for reconstruction of ancestral character states and for measuring along branch evolution. RESULTS: A software package for reconstruction of continuous character traits, like relative gene expression levels or alternative splice site usage data is presented and is available for download at . This program was applied to a primate gene expression dataset to detect transcription factor binding sites that have undergone substitution, potentially having driven lineage-specific differences in gene expression. CONCLUSION: Systematic analysis of lineage-specific evolution is becoming the cornerstone of comparative genomics. New methods, like phyrex, extend the capabilities of comparative genomics by tracing the evolution of additional biomolecular processes

A Detailed History of Intron-rich Eukaryotic Ancestors Inferred from a Global Survey of 100 Complete Genomes

Protein-coding genes in eukaryotes are interrupted by introns, but intron densities widely differ between eukaryotic lineages. Vertebrates, some invertebrates and green plants have intron-rich genes, with 6–7 introns per kilobase of coding sequence, whereas most of the other eukaryotes have intron-poor genes. We reconstructed the history of intron gain and loss using a probabilistic Markov model (Markov Chain Monte Carlo, MCMC) on 245 orthologous genes from 99 genomes representing the three of the five supergroups of eukaryotes for which multiple genome sequences are available. Intron-rich ancestors are confidently reconstructed for each major group, with 53 to 74% of the human intron density inferred with 95% confidence for the Last Eukaryotic Common Ancestor (LECA). The results of the MCMC reconstruction are compared with the reconstructions obtained using Maximum Likelihood (ML) and Dollo parsimony methods. An excellent agreement between the MCMC and ML inferences is demonstrated whereas Dollo parsimony introduces a noticeable bias in the estimations, typically yielding lower ancestral intron densities than MCMC and ML. Evolution of eukaryotic genes was dominated by intron loss, with substantial gain only at the bases of several major branches including plants and animals. The highest intron density, 120 to 130% of the human value, is inferred for the last common ancestor of animals. The reconstruction shows that the entire line of descent from LECA to mammals was intron-rich, a state conducive to the evolution of alternative splicing

The U1A/U2B /SNF Family of RNA Binding Proteins: Evolution of RNA Binding Specificity and Contributions of Heterotropic Linkage to snRNP Protein Partitioning

The U1A/U2B /SNF is a family of RNA binding proteins that is a highly conserved throughout eukaryotes. These proteins are found in the U1 and/or U2 splicing snRNPs (small nuclear ribonucleoprotein particles). In humans, U1A and U2B specifically bind to the U1 and U2 snRNAs, respectively. The Drosophila genome codes for SNF, an essential protein that localizes to both the U1 and U2 snRNP. While a specific splicing functions for these proteins have not been determined, their conserved snRNP localization suggests an important splicing-related function. The difference in protein number and partitioning between Drosophila and humans suggested that these proteins may use different RNA binding mechanisms to function in their cellular contexts. This work begins by exploring some of the differences amongst human U1A, U2B , and Drosophila SNF. The thermodynamics of the RNA-protein interactions also reveal substantial differences in the RNA binding mechanisms of these proteins. Further studies investigate the evolution of this protein family in metazoans. Reconstructing the protein phylogeny permitted resurrection of ancestral proteins. This led to the discovery that the last common ancestor of humans and Drosophila had a single U1A/U2B /SNF family homolog. This protein had RNA binding properties that most closely resemble those of Drosophila SNF. Evolution of protein motions and RNA binding specificity toward the defining characteristics of modern vertebrate proteins is also examined. Finally, linkage effects between protein-protein and protein-RNA interactions are analyzed. U2A\u27; is a U2 snRNP-specific protein that binds to U2B ; in humans and SNF in Drosophila. In Drosophila, large, positive linkage was only seen between U2A\u27-SNF and SNF-U2 snRNA binding. The RNA dependence of enhancement for SNF binding to U2A\u27 can explain the observed protein partitioning of U2A\u27 in vivo. For the more complicated human system, which contains two SNF homologs, substantial contributions to protein partitioning come from differences in both intrinsic RNA-protein binding affinities and differences in protein-U2A\u27 binding affinities. RNA dependence of the linkage parameter also contributes to protein partitioning. The binding parameters can explain U2A\u27 protein partitioning, and the presence of U2A\u27 reinforces U1A and U2B partitioning to their respective snRNAs. These linkage studies have important implications for the assembly of RiboNucleoprotein Particles, macromolecular complexes that are fundamental to many cellular activities

Choosing and Using Introns in Molecular Phylogenetics

Introns are now commonly used in molecular phylogenetics in an attempt to recover gene trees that are concordant with species trees, but there are a range of genomic, logistical and analytical considerations that are infrequently discussed in empirical studies that utilize intron data. This review outlines expedient approaches for locus selection, overcoming paralogy problems, recombination detection methods and the identification and incorporation of LVHs in molecular systematics. A range of parsimony and Bayesian analytical approaches are also described in order to highlight the methods that can currently be employed to align sequences and treat indels in subsequent analyses. By covering the main points associated with the generation and analysis of intron data, this review aims to provide a comprehensive introduction to using introns (or any non-coding nuclear data partition) in contemporary phylogenetics

Relative Timing of Intron Gain and a New Marker for Phylogenetic Analyses

Despite decades of effort by molecular systematists, the trees of life of eukaryotic organisms still remain partly unresolved or in conflict with each other. An ever increasing number of fully-sequenced genomes of various eukaryotes allows to consider gene and species phylogenies at genome-scale. However, such phylogenomics-based approaches also revealed that more taxa and more and more gene sequences are not the ultimate solution to fully resolve these conflicts, and that there is a need for sequence-independent phylogenetic meta-characters that are derived from genome sequences. Spliceosomal introns are characteristic features of eukaryotic nuclear genomes. The relatively rare changes of spliceosomal intron positions have already been used as genome-level markers, both for the estimation of intron evolution and phylogenies, however with variable success. In this thesis, a specific subset of these changes is introduced and established as a novel phylogenetic marker, termed near intron pair (NIP). These characters are inferred from homologous genes that contain mutually-exclusive intron presences at pairs of coding sequence (CDS) positions in close proximity. The idea that NIPs are powerful characters is based on the assumption that both very small exons and multiple intron gains at the same position are rare. To obtain sufficient numbers of NIP character data from genomic and alignment data sets in a consistent and flexible way, the implementation of a computational pipeline was a main goal of this work. Starting from orthologous (or more general: homologous) gene datasets comprising genomic sequences and corresponding CDS transcript annotations, the multiple alignment generation is an integral part of this pipeline. The alignment can be calculated at the amino acid level utilizing external tools (e.g. transAlign) and results in a codon alignment via back-translation. Guided by the multiple alignment, the positionally homologous intron positions should become apparent when mapped individually for each transcript. The pipeline proceeds at this stage to output portions of the intron-annotated alignment that contain at least one candidate of a NIP character. In a subsequent pipeline script, these collected so-called NIP region files are finally converted to binary state characters representing valid NIPs in dependence of quality filter constraints concerning, e.g., the amino acid alignment conservation around intron loci and splice sites, to name a few. The computational pipeline tools provide the researcher to elaborate on NIP character matrices that can be used for tree inference, e.g., using the maximum parsimony approach. In a first NIP-based application, the phylogenetic position of major orders of holometabolic insects (more specifically: the Coleoptera-Hymenoptera-Mecopterida trifurcation) was evaluated in a cladistic sense. As already suggested during a study on the eIF2gamma gene based on two NIP cases (Krauss et al. 2005), the genome-scale evaluation supported Hymenoptera as sister group to an assemblage of Coleoptera and Mecopterida, in agreement with other studies, but contradicting the previously established view. As part of the genome paper describing a new species of twisted-wing parasites (Strepsiptera), the NIP method was employed to help to resolve the phylogenetic position of them within (holometabolic) insects. Together with analyses of sequence patterns and a further meta-character, it revealed twisted-wing parasites as being the closest relatives of the mega-diverse beetles. NIP-based reconstructions of the metazoan tree covering a broad selection of representative animal species also identified some weaknesses of the NIP approach that may suffer e.g. from alignment/ortholog prediction artifacts (depending on the depth of range of taxa) and systematic biases (long branch attraction artifacts, due to unequal evolutionary rates of intron gain/loss and the use of the maximum parsimony method). In a further study, the identification of NIPs within the recently diverged genus Drosophila could be utilized to characterize recent intron gain events that apparently involved several cases of intron sliding and tandem exon duplication, albeit the mechanisms of gain for the majority of cases could not be elucidated. Finally, the NIP marker could be established as a novel phylogenetic marker, in particular dedicated to complementarily explore the wealth of genome data for phylogenetic purposes and to address open questions of intron evolution

Strategies for Reliable Exploitation of Evolutionary Concepts in High Throughput Biology

The recent availability of the complete genome sequences of a large number of model organisms, together with the immense amount of data being produced by the new high-throughput technologies, means that we can now begin comparative analyses to understand the mechanisms involved in the evolution of the genome and their consequences in the study of biological systems. Phylogenetic approaches provide a unique conceptual framework for performing comparative analyses of all this data, for propagating information between different systems and for predicting or inferring new knowledge. As a result, phylogeny-based inference systems are now playing an increasingly important role in most areas of high throughput genomics, including studies of promoters (phylogenetic footprinting), interactomes (based on the presence and degree of conservation of interacting proteins), and in comparisons of transcriptomes or proteomes (phylogenetic proximity and co-regulation/co-expression). Here we review the recent developments aimed at making automatic, reliable phylogeny-based inference feasible in large-scale projects. We also discuss how evolutionary concepts and phylogeny-based inference strategies are now being exploited in order to understand the evolution and function of biological systems. Such advances will be fundamental for the success of the emerging disciplines of systems biology and synthetic biology, and will have wide-reaching effects in applied fields such as biotechnology, medicine and pharmacology

A Data Mining Approach for Detecting Evolutionary Divergence in Transcriptomic Data

It has become common to produce genome sequences for organisms of scientific or popular interest. Although these genome projects provide insight into the gene and protein complements of a species including their evolutionary relationships, it remains challenging to determine gene regulatory behavior from genome sequence alone. It has also become common to produce “expression atlas” transcriptomic data sets. These atlases employ high-throughput transcript assays to survey an assortment of tissues, developmental states, and responses to stimuli that each may individually elicit or inhibit the transcription of genes. Although genomic and transcriptomic data sets are both routinely collected, they are seldom analyzed in tandem. Here I present a novel approach to combining these complementary data with a software package called BranchOut. BranchOut uses genomic information to construct gene family phylogenies, and then attempts to map gene expression activity onto this phylogeny to allow estimation of ancestral expression states. This allows the identification of specific innovations due to gene duplications that resulted in fundamental diversification in the roles of otherwise closely related genes. As a proof of concept, the BranchOut technique is first applied to a tangible small-scale example in Apis mellifera. Subsequently, the power of BranchOut to analyze complete genomes is shown for two mammalian genomes, Sus scrofa and Bos taurus. The transcriptomic data sets for these two mammals employ microarray and RNAseq platforms, respectively, for expression analysis, demonstrating BranchOut’s applicability to both future and historic expression atlases. Potential refinements to the approach are also discussed

Testis-specific glyceraldehyde-3-phosphate dehydrogenase: origin and evolution

<p>Abstract</p> <p>Background</p> <p>Glyceraldehyde-3-phosphate dehydrogenase (GAPD) catalyses one of the glycolytic reactions and is also involved in a number of non-glycolytic processes, such as endocytosis, DNA excision repair, and induction of apoptosis. Mammals are known to possess two homologous GAPD isoenzymes: GAPD-1, a well-studied protein found in all somatic cells, and GAPD-2, which is expressed solely in testis. GAPD-2 supplies energy required for the movement of spermatozoa and is tightly bound to the sperm tail cytoskeleton by the additional N-terminal proline-rich domain absent in GAPD-1. In this study we investigate the evolutionary history of GAPD and gain some insights into specialization of GAPD-2 as a testis-specific protein.</p> <p>Results</p> <p>A dataset of GAPD sequences was assembled from public databases and used for phylogeny reconstruction by means of the Bayesian method. Since resolution in some clades of the obtained tree was too low, syntenic analysis was carried out to define the evolutionary history of GAPD more precisely. The performed selection tests showed that selective pressure varies across lineages and isoenzymes, as well as across different regions of the same sequences.</p> <p>Conclusions</p> <p>The obtained results suggest that GAPD-1 and GAPD-2 emerged after duplication during the early evolution of chordates. GAPD-2 was subsequently lost by most lineages except lizards, mammals, as well as cartilaginous and bony fishes. In reptilians and mammals, GAPD-2 specialized to a testis-specific protein and acquired the novel N-terminal proline-rich domain anchoring the protein in the sperm tail cytoskeleton. This domain is likely to have originated by exonization of a microsatellite genomic region. Recognition of the proline-rich domain by cytoskeletal proteins seems to be unspecific. Besides testis, GAPD-2 of lizards was also found in some regenerating tissues, but it lacks the proline-rich domain due to tissue-specific alternative splicing.</p