Social insects are ecologically dominant because of their specialized, cooperative castes. Reproductive queens lay eggs, while workers take part in brood rearing, nest defense, and foraging. These cooperative castes are a prime example of phenotypic plasticity, whereby a single genetic code gives rise to variation in form and function based on environmental differences. Thus, social insects are well suited for studying mechanisms which give rise to and maintain phenotypic plasticity. At the molecular level, phenotypic plasticity coincides with the differential expression of genes. This dissertation examines the molecular evolution of genes with differential expression between discrete phenotypic or environmental contexts, represented chiefly by female queen and worker castes in social insects. The studies included herein examine evolution at three important levels of biological information: (i) gene expression, (ii) modifications to DNA in the form of methylation, and (iii) protein-coding sequence. From these analyses, a common theme has emerged: genes with differential expression among castes frequently exhibit signatures of relaxed selective constraint relative to ubiquitously expressed genes. Thus, genes associated with phenotypic plasticity paradoxically exhibit modest importance to overall fitness but exceptional evolutionary potential, as illustrated by the success of the social insects.

Species evolution can often be adequately described with a phylogenetic tree. Interestingly, this is the case also for the evolution of homologous genes; a gene in an ancestral species may – through gene duplication, gene loss, lateral gene transfer (LGT), and speciation events – give rise to a gene family distributed across contemporaneous species. However, molecular sequence evolution and genetic recombination make the history – the gene tree – non-trivial to reconstruct from present-day sequences. This history is of biological interest, e.g., for inferring potential functional equivalences of extant gene pairs. In this thesis, we present biologically sound probabilistic models for gene family evolution guided by species evolution – effectively yielding a gene-species tree reconciliation. Using Bayesian Markov-chain Monte Carlo (MCMC) inference techniques, we show that by taking advantage of the information provided by the species tree, our methods achieve more reliable gene tree estimates than traditional species tree-uninformed approaches. Specifically, we describe a comprehensive model that accounts for gene duplication, gene loss, a relaxed molecular clock, and sequence evolution, and we show that the method performs admirably on synthetic and biological data. Further-more, we present two expansions of the inference procedure, enabling it to pro-vide (i) refined gene tree estimates with timed duplications, and (ii) probabilistic orthology estimates – i.e., that the origin of a pair of extant genes is a speciation. Finally, we present a substantial development of the model to account also for LGT. A sophisticated algorithmic framework of dynamic programming and numerical methods for differential equations is used to resolve the computational hurdles that LGT brings about. We apply the method on two bacterial datasets where LGT is believed to be prominent, in order to estimate genome-wide LGT and duplication rates. We further show that traditional methods – in which gene trees are reconstructed and reconciled with the species tree in separate stages – are prone to yield inferior gene tree estimates that will overestimate the number of LGT events. / Arters evolution kan i många fall beskrivas med ett träd, vilket redan Darwins anteckningsböcker från HMS Beagle vittnar om. Detta gäller också homologa gener; en gen i en ancestral art kan – genom genduplikationer, genförluster, lateral gentransfer (LGT) och artbildningar – ge upphov till en genfamilj spridd över samtida arter. Att från sekvenser från nu levande arter rekonstruera genfamiljens framväxt – genträdet – är icke-trivialt på grund av genetisk rekombination och sekvensevolution. Genträdet är emellertid av biologiskt intresse, i synnerhet för att det möjliggör antaganden om funktionellt släktskap mellan nutida genpar. Denna avhandling behandlar biologiskt välgrundade sannolikhetsmodeller för genfamiljsevolution. Dessa modeller tar hjälp av artevolutionens starka inverkan på genfamiljens historia, och ger väsentligen upphov till en förlikning av genträd och artträd. Genom Bayesiansk inferens baserad på Markov-chain Monte Carlo (MCMC) visar vi att våra metoder presterar bättre genträdsskattningar än traditionella ansatser som inte tar artträdet i beaktning. Mer specifikt beskriver vi en modell som omfattar genduplikationer, genförluster, en relaxerad molekylär klocka, samt sekvensevolution, och visar att metoden ger högkvalitativa skattningar på både syntetiska och biologiska data. Vidare presenterar vi två utvidgningar av detta ramverk som möjliggör (i) genträdsskattningar med tidpunkter för duplikationer, samt (ii) probabilistiska ortologiskattningar – d.v.s. att två nutida gener härstammar från en artbildning. Slutligen presenterar vi en modell som inkluderar LGT utöver ovan nämnda mekanismer. De beräkningsmässiga svårigheter som LGT ger upphov till löses med ett intrikat ramverk av dynamisk programmering och numeriska metoder för differentialekvationer. Vi tillämpar metoden för att skatta LGT- och duplikationsraten hos två bakteriella dataset där LGT förmodas ha spelat en central roll. Vi visar också att traditionella metoder – där genträd skattas och förlikas med artträdet i separata steg – tenderar att ge sämre genträdsskattningar, och därmed överskatta antalet LGT-händelser. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 5: Manuscript.</p>

Comparative sequence analyses were performed with members of the Solanaceae and the Brassicaceae. These studies investigated genomic organization, determined levels of microcolinearity, identified orthologous genes and investigated the molecular basis of trait differences. The first analysis was performed by comparison of tomato (Solanum lycopersicum) genomic sequence (119 kb) containing the JOINTLESS1 (J1) locus with orthologous sequences from two potato species, a diploid, Solanum bulbocastanum (800-900 Mb, 2N=2X=24), and a hexaploid, Solanum demissum (2,700 Mb, 2N=6X=72). Gene colinearity was well maintained across all three regions. Twelve orthologous open reading frames were identified in identical order and orientation and included three putative J1 orthologs with 93-96% amino acid sequence identity in both potato species. Although these regions were highly conserved, several local disruptions were detected and included small-scale expansion/contraction regions with intergenic sequences, non-colinear genes and transposable elements. Three putative Solanaceous-specific genes were also identified in this analysis. The second analysis was performed by comparison of a Thellungiella halophila (T. halophila) genomic sequence (193 kb) containing the SALT OVERLY SENSITIVE1 (SOS1) locus with the orthologous sequence (146 kb) in Arabidopsis thaliana (Arabidopsis). T. halophila is a halophytic relative of Arabidopsis thaliana that exhibits extreme salt tolerance. Twenty-five genes, including the putative T. halophila SOS1 (ThSOS1), showed a high degree of colinearity with Arabidopsis genes in the corresponding region. Although the two sequences were significantly colinear, several local rearrangements were detected which were caused by tandem duplications and inversions. Three major expansion/contraction regions in T. halophila contained five LTR retrotransposons which contributed to genomic size variation in this region. ThSOS1 shares similar gene structure and sequence with Arabidopsis SOS1 (AtSOS1), including 11 transmembrane domains and a cyclic nucleotide-binding domain. Three Simple Sequence Repeats (SSRs) were detected within a 540 bp region upstream of the putative translational start site in ThSOS1. The (CTT)n repeat is present in different copy numbers in ThSOS1 (18 repeats) and AtSOS1 (3 repeats). When present in the 5' UTRs of some Arabidopsis genes, (CTT)n serves as a putative salicylic acid responsive element. These SSRs may serve as cis-acting elements affecting differential mRNA accumulation of SOS1 in the two species.

All cellular processes depend on the coordinate expression of genes and their interactions. Regulatory sequences encoded in the genome stipulate the necessary instructions interpreted by sequence-specific transcription factors (TFs) to control the spatial-temporal output of gene expression. Detection of cis-regulatory signals is challenging, owing to the lack of distinguishing features such as open reading frames and an overwhelming excess of spurious to functional TF binding site matching sequences embedded within the vast non-coding regions of vertebrate genomes. From an evolutionary standpoint, functional alterations in cis-regulatory architecture are thought to be important in diversifying morphology and physiology in the evolution of vertebrates, which share a similar body plan and complement of genes. Correspondingly, recent studies have highlighted the plasticity of cis-regulatory architecture organization over evolutionary time, finding associations with examples of both diverged and conserved patterns of gene expression. These observations underscore the gap in our collective knowledge with respect to the rules by which TFs recognize and bind their targets in vivo, as well as how this process evolves in vertebrates, and serve as a motivating basis for this thesis work. To begin, I probed the extent of conservation and divergence of sequence and expression profiles across tissues of diverse vertebrate species, identifying thousands of candidate genes with conserved expression by microarray analysis. However, corresponding conservation of non-exonic and potentially regulatory sequence was lacking, suggestive of binding site turnover over evolutionary time. Next, I analyzed the sequence specificity of a wide array of mouse and yeast TFs, finding great diversity and complexity in their binding preferences, with many factors recognizing multiple distinct motifs. Furthermore, comparative analysis of orthologous TFs suggest well conserved binding specificities. I also demonstrate the likely biological relevance of sequences highly preferred by these TFs by revealing distinctive signatures in their distribution and organization within putative regulatory regions in each genome. Lastly, I have begun to explore the organization of cis-regulatory sequences active in vertebrate tissues by high-throughput sequencing of open chromatin. Together, these data help illuminate the organization and evolution of vertebrate regulatory architectures, providing a useful toolkit for the testing of new models and hypotheses.

Comparative analysis of genomic data investigates the relationship of genome structure and function across different biological species to shed light on their similarities and differences. In this dissertation, we study two important problems in comparative genomics, namely comparative sequence analysis and comparative network analysis. In the comparative sequence analysis, we study the multiple sequence alignment of protein and DNA sequences as well as the structural alignment of multiple RNA sequences. For closely related sequences, multiple sequence alignment can be efficiently performed through progressive techniques. However, for divergent sequences it is very challenging to predict an accurate alignment. Here, we introduce PicXAA, an efficient non-progressive technique for multiple protein and DNA sequence alignment. We also further extend PicXAA to PicXAA-R for structural alignment of RNA sequences. PicXAA and PicXAA-R greedily build up the alignment from sequence regions with high local similarity, thereby yielding an accurate global alignment that effectively captures local similarities among sequences. As another important research area in comparative genomics, we also investigate the comparative network analysis problem. Translation of increasing number of large-scale biological networks into meaningful biological insights requires efficient computational techniques. One such example is network querying, which aims to identify subnetwork regions in a large target network that are similar to a given query network. Here, we introduce an efficient algorithm for querying large-scale biological networks, called RESQUE. RESQUE adopts a semi-Markov random walk model to probabilistically estimate the correspondence scores between nodes that belong to different networks. The target network is iteratively reduced based on the estimated correspondence scores until the best matching subnetwork emerges. The proposed network querying scheme is computationally efficient, can handle any network query with an arbitrary topology, and yields accurate querying results. We also extend the idea used in RESQUE to develop an efficient algorithm for alignment of multiple large-scale biological networks, called SMETANA. SMETANA outperforms state-of- the-art network alignment techniques, in terms of both computational efficiency and alignment accuracy. The accomplished studies have enabled us to provide a coherent framework for probabilistic approach to comparative analysis of biological sequences and networks. Such a probabilistic framework helps us employ rigorous mathematical schemes to find accurate and efficient solutions to these problems.

Deciphering the functionality encoded in the genome constitutes an essential first step to understanding the context through which mutations can cause human disease. In this dissertation, I present multiple studies based on the use or development of comparative genomics techniques to elucidate function (or lack of function) from the genomes of humans and other animal species. Collectively, these studies focus on two biological entities encoded in the human genome: genes related to human disease susceptibility and those that encode microRNAs - small RNAs that have important gene-regulatory roles in normal biological function and in human disease. Extending this work, I investigated the evolution of these biological entities within animals to shed light on how their underlying functions arose and how they can be modeled in non-human species. Additionally, I present a new tool that uses large-scale clinical genomic data to identify human mutations that may affect microRNA regulatory functions, thereby providing a method by which state-of-the-art genomic technologies can be fully utilized in the search for new disease mechanisms and potential drug targets. The scientific contributions made in this dissertation utilize current data sets generated using high-throughput sequencing technologies. For example, recent whole-genome sequencing studies of the most distant animal lineages have effectively restructured the animal tree of life as we understand it. The first two chapters utilize data from this new high-confidence animal phylogeny - in addition to data generated in the course of my work - to demonstrate that (1) certain classes of human disease have uncommonly large proportions of genes that evolved with the earliest animals and/or vertebrates, and (2) that canonical microRNA functionality - absent in at least two of the early branching animal lineages - likely evolved after the first animals. In the third chapter, I expand upon recent research in predicting microRNA target sites, describing a novel tool for predicting clinically significant microRNA target site variants and demonstrating its applicability to the analysis of clinical genomic data. Thus, the studies detailed in this dissertation represent significant advances in our understanding of the functions of disease genes and microRNAs from both an evolutionary and a clinical perspective.

Made available in DSpace on 2014-06-11T19:26:06Z (GMT). No. of bitstreams: 0 Previous issue date: 2012-03-13Bitstream added on 2014-06-13T20:33:37Z : No. of bitstreams: 1 bizari_dc_me_jabo.pdf: 336489 bytes, checksum: 0801c01531c7ce877e08321205d11d07 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / No presente estudo, cinco novos genes codificantes de proteínas foram selecionados para o mapeamento do cromossomo 6 bubalino (BBU6). Os novos genes (muc1, ppp1r7, psmd4, tshb e gtf2b) foram testados com a tecnologia de PCR resultando em produtos de PCR adequados ao mapeamento utilizando-se um painel de células somáticas híbridas irradiadas, denominado BBURH5000. Os resultados obtidos mostraram uma freqüência de retenção (FR) do produto de PCR de cada gene nas diferentes linhagens do painel com variação de 13,3% (gtf2b) a 26,6% (psmd4). A análise comparativa entre os mapas RH do BBU6 e a sequência do cromossomo 3 bovino permitiu indicar a localização dos novos genes no cromossomo 6 bubalino / In this study, five new protein coding genes were select for mapping buffalo chromosome 6. The new genes (muc1, ppp1r7, psmd4, tshb and gtf2b) were tested using PCR technology resulting in PCR products suitable for mapping using a radiation hybrid panel (BBURH5000). The retention frequency of the PCR products in each hybrid cell line of the panel showed the percentage from 13,3% (gtf2b) to 26,6% (psmd4). Comparative analysis between the buffalo chromosome 6 RH map and the sequence from bovine chromosome 3 allowed to assign the location of the new genes on buffalo chromosome 6

O advento do sequenciamento de nova geração (NGS - Next Generation Sequencing) nos últimos anos proporcionou um aumento expressivo no número de projetos genômicos. De maneira simplificada, as máquinas sequenciadoras geram como resultado fragmentos de DNA que são utilizados por programas montadores de genoma. Esses programas tentam juntar os fragmentos de DNA de modo a obter a representação completa da sequência genômica (por exemplo um cromossomo) da espécie sendo sequenciada. Em alguns casos o processo de montagem pode ser executado com maior facilidade para organismos com genomas de tamanhos pequenos (por exemplo bactérias com genoma em torno de 5Mpb), através de pipelines que automatizam a maior parte da tarefa. Um cenário mais complicado surge quando a espécie possui genoma com grande comprimento (acima de 1Gpb) e elementos repetidos, como no caso de alguns eucariotos. Nesses casos o resultado da montagem é geralmente composto por milhares de fragmentos (chamados de contigs), uma ordem de magnitude muito superior ao número de cromossomos estimado para um organismo (comumente da ordem de dois dígitos), dando origem a uma montagem altamente fragmentada. Uma atividade comum nesses projetos é a comparação da montagem com a de outro genoma como forma de validação e também para identificação de regiões conservadas entre os organismos. Embora o problema de alinhamento par-a-par de genomas grandes seja bem contornado por abordagens existentes, o alinhamento múltiplo (AM) de genomas grandes em estado fragmentado ainda é uma tarefa de difícil resolução, por demandar alto custo computacional e grande quantidade de tempo. Este trabalho consiste em uma metologia para fazer alinhamento múltiplo de genomas grandes de eucariotos com montagens altamente fragmentadas. Nossa implementação, baseada em alinhamento estrela, se mostrou capaz de fazer AM de grupos de montagens com diversos níveis de fragmentação. O maior deles, um conjunto de 5 genomas de répteis, levou 14 horas de processamento para fornecer um mapa de regiões conservadas entre as espécies. O algoritmo foi implementado em um software que batizamos de FROG (FRagment Overlap multiple Genome alignment), de código aberto e disponível sob licença GPLv3. / The advent of Next Generation Sequencing (NGS) in recent years has led to an expressive increase in the number of genomic projects. In a simplified way, sequencing machines generate DNA fragments that are used by genome assembler software. These programs try to merge the DNA fragments to obtain the complete representation of the genomic sequence (for example a chromosome) of the species being sequenced. In some cases the assembling process can be performed more easily for organisms with small-sized genomes (e.g. bacteria with a genome length of approximately 5Mpb) through pipelines that automate most of the task. A trickier scenario arises when the species has a very large genome (above 1Gbp) and complex elements, as in the case of some eukaryotes. In those cases the result of the assembly is usually composed of thousands of fragments (called contigs), an order of magnitude much higher than the number of chromosomes estimated for an organism (usually in the order two digits), giving rise to a highly fragmented assembly. A common activity in these projects is the comparison of the assembly with that of another genome as a form of validation and also to identify common elements between organisms. Although the problem of pairwise alignment of large genomes is well circumvented by existing approaches, multiple alignment of large genomes with highly fragmented assemblies remains a difficult task due to its time and computational requirements. This work consists of a methodology for doing multiple alignment of large eukaryotic genomes with highly fragmented assemblies, a problem that few solutions are able to cope with. Our star alignment-based implementation, was able to accomplish a MSA of groups of assemblies with different levels of fragmentation. The largest of them, a set of 5 reptilian genomes where the B. jararaca assembly (800,000 contigs, N50 of 3.1Kbp) was used as anchor, took 14 hours of execution time to provide a map of conserved regions among the participating species. The algorithm was implemented in a software named FROG (FRagment Overlap multiple Genome alignment), available under the General Public License v3 (GPLv3) terms.

This dissertation consists of three manuscripts for publication: Appendix A presents a genomic comparison of Aspergillus flavus isolates with different morphologies, and Appendices B and C present the identification and systematics of an emerging snake pathogen, Ophidiomyces ophiodiicola. The comparative genomics project of A. flavus tests the hypothesis that isolates with different morphologies within the species are adapted to different niches. Our results reveal differences in genome structure and protein content that are implicated in niche adaptation to the soil and phyllosphere. The systematics project of O. ophiodiicola was initiated to resolve the frequent misidentification of emerging reptilian diseases that is occuring in the literature. One of these emerging pathogens, O. ophiodiicola, was incorrectly described in the genus Chrysosporium due to its resemblance in spore morphology; therefore, the taxonomy of the genus was revised. We hope the review will aid in accurate identification and tracking of emerging reptilian diseases to better understand their epidemiology.

Long intergenic non-coding RNAs (lincRNAs) are an abundant and functionally diverse class of eukaryotic transcripts. Reported lincRNA repertoires in mammals vary, but are commonly in the thousands to tens of thousands of transcripts, covering similar to 90% of the genome. In addition to elucidating function, there is particular interest in understanding the origin and evolution of lincRNAs. Aside from mammals, lincRNA populations have been sparsely sampled, precluding evolutionary analyses focused on their emergence and persistence. Here we present Evolinc, a two-module pipeline designed to facilitate lincRNA discovery and characterize aspects of lincRNA evolution. The first module (Evolinc-I) is a lincRNA identification workflow that also facilitates downstream differential expression analysis and genome browser visualization of identified lincRNAs. The second module (Evolinc-II) is a genomic and transcriptomic comparative analysis workflow that determines the phylogenetic depth to which a lincRNA locus is conserved within a user-defined group of related species. Here we validate lincRNA catalogs generated with Evolinc-I against previously annotated Arabidopsis and human lincRNA data. Evolinc-I recapitulated earlier findings and uncovered an additional 70 Arabidopsis and 43 human lincRNAs. We demonstrate the usefulness of Evolinc-II by examining the evolutionary histories of a public dataset of 5,361 Arabidopsis lincRNAs. We used Evolinc-II to winnow this dataset to 40 lincRNAs conserved across species in Brassicaceae. Finally, we show how Evolinc-II can be used to recover the evolutionary history of a known lincRNA, the human telomerase RNA (TERC). These latter analyses revealed unexpected duplication events as well as the loss and subsequent acquisition of a novel TERC locus in the lineage leading to mice and rats. The Evolinc pipeline is currently integrated in CyVerse's Discovery Environment and is free for use by researchers.