Alignment of time course gene expression data and the classification of developmentally driven genes with hidden Markov models

BACKGROUND: We consider data from a time course microarray experiment that was conducted on grapevines over the development cycle of the grape berries at two different vineyards in South Australia. Although the underlying biological process of berry development is the same at both vineyards, there are differences in the timing of the development due to local conditions. We aim to align the data from the two vineyards to enable an integrated analysis of the gene expression and use the alignment of the expression profiles to classify likely developmental function. RESULTS: We present a novel alignment method based on hidden Markov models (HMMs) and use the method to align the motivating grapevine data. We show that our alignment method is robust against subsets of profiles that are not suitable for alignment, investigate alignment diagnostics under the model and demonstrate the classification of developmentally driven genes. CONCLUSIONS: The classification of developmentally driven genes both validates that the alignment we obtain is meaningful and also gives new evidence that can be used to identify the role of genes with unknown function. Using our alignment methodology, we find at least 1279 grapevine probe sets with no current annotated function that are likely to be controlled in a developmental manner.Sean Robinson, Garique Glonek, Inge Koch, Mark Thomas, and Christopher Davie

The Actinome of Dictyostelium discoideum in Comparison to Actins and Actin-Related Proteins from Other Organisms

Actin belongs to the most abundant proteins in eukaryotic cells which harbor usually many conventional actin isoforms as well as actin-related proteins (Arps). To get an overview over the sometimes confusing multitude of actins and Arps, we analyzed the Dictyostelium discoideum actinome in detail and compared it with the genomes from other model organisms. The D. discoideum actinome comprises 41 actins and actin-related proteins. The genome contains 17 actin genes which most likely arose from consecutive gene duplications, are all active, in some cases developmentally regulated and coding for identical proteins (Act8-group). According to published data, the actin fraction in a D. discoideum cell consists of more than 95% of these Act8-type proteins. The other 16 actin isoforms contain a conventional actin motif profile as well but differ in their protein sequences. Seven actin genes are potential pseudogenes. A homology search of the human genome using the most typical D. discoideum actin (Act8) as query sequence finds the major actin isoforms such as cytoplasmic beta-actin as best hit. This suggests that the Act8-group represents a nearly perfect actin throughout evolution. Interestingly, limited data from D. fasciculatum, a more ancient member among the social amoebae, show different relationships between conventional actins. The Act8-type isoform is most conserved throughout evolution. Modeling of the putative structures suggests that the majority of the actin-related proteins is functionally unrelated to canonical actin. The data suggest that the other actin variants are not necessary for the cytoskeleton itself but rather regulators of its dynamical features or subunits in larger protein complexes

Functional dissection of a gene expression oscillator in C. elegans

Gene expression oscillations control diverse biological processes. One such example of gene expression oscillations, are those found for thousands of genes during C. elegans larval development. However, it remains unclear whether and how gene expression oscillations regulate development processes in C. elegans. In this work, I aimed to study the molecular architecture and the system properties of the C. elegans oscillator to provide insight into potential developmental functions and reveal features that are unique, as well as those that are shared among oscillators. Here, performing temporally highly resolved mRNA-sequencing across all larval stages (L1-L4) of C. elegans development, we identified 3,739 genes, whose transcripts revealed high-amplitude oscillations (>2-fold from peak to trough), peaking once every larval stage with stable amplitudes, but variable periods. Oscillations appeared tightly coupled to the molts, but were absent from freshly hatched larvae, developmentally arrested dauer larvae and adults. Quantitative characterization of transitions between oscillatory and stable states of the oscillator showed that the stable states are similar to a particular phase of the oscillator, which coincided with molt exit. Given that these transitions are sensitive to food, we postulate that feeding might impact the state of the oscillator. These features appear rather unique, and hence a better understanding may help to reveal general principles of gene expression oscillators. Our RNAPII ChIP-seq revealed rhythmic occupancy of RNAPII at the promoters of oscillating genes, suggesting that mRNA transcript oscillations arise from rhythmic transcription. Given that oscillations are coupled to the repetitive molts and that the molecular mechanisms that regulate molting are unknown, we aimed to find transcription factors important for molting and oscillations. Hence, we screened 92 transcription factors that oscillate on the mRNA level for their role in molting and identified grh-1, myrf1, blmp-1, bed-3, nhr-23, nhr-25 and ztf-6. We showed that oscillatory activity of GRH-1 is required for timely completion of the molt, to prevent cuticle rupturing, and for oscillatory expression of structural components of the cuticle and ‘ECM regulators’, among others, including grh-1 itself. Hence, we propose GRH-1 as a putative component of the (sub-)oscillator that regulates molting. We showed that loss of BLMP-1 increased the duration of molts, affected cuticle integrity, and changed the oscillatory dynamics of a subset of genes in diverse ways. We postulate that BLMP-1 acts as factor that couples gene expression oscillations, and potentially sub-oscillators or repetitive developmental processes. In conclusion, this work provides insight into the function of the oscillator, and its system properties. Moreover, we identified relevant factors, which we propose as a starting point to unravel the molecular wiring of the C. elegans oscillator and its functional relevance

Dynamic microRNA activity identifies therapeutic targets in trastuzumab‐resistant HER2+ breast cancer

MicroRNAs (miRNAs) are implicated in numerous physiologic and pathologic processes, such as the development of resistance to chemotherapy. Determining the role of miRNAs in these processes is often accomplished through measuring miRNA abundance by polymerase chain reaction, sequencing, or microarrays. We have developed a system for the large‐scale monitoring of dynamic miRNA activity and have applied this system to identify the contribution miRNA activity to the development of trastuzumab resistance in a cell model of HER2+ breast cancer. MiRNA activity measurements identified significantly different activity levels between BT474 cells (HER2+ breast cancer) and BT474R cells (HER2+ breast cancer cells selected for resistance to trastuzumab). We created a library of 32 miRNA reporter constructs, which were delivered by lentiviral transduction into cells, and miRNA activity was quantified by bioluminescence imaging. Upon treatment with the bioimmune therapy, trastuzumab, the activity of 11 miRNAs were significantly altered in parental BT474 cells, and 20 miRNAs had significantly altered activity in the therapy‐resistant BT474R cell line. A combination of statistical, network and classification analysis was applied to the dynamic data, which identified miR‐21 as a controlling factor in trastuzumab response. Our data suggested downregulation of miR‐21 activity was associated with resistance, which was confirmed in an additional HER2+ breast cancer cell line, SKBR3. Collectively, the dynamic miRNA activity measurements and analysis provided a system to identify new potential therapeutic targets in treatment‐resistant cancers.MicroRNAs (miRNAs) are often dysrgulated in cancer and can give rise to drug resistance. Identifying the mechanisms for resistance may lead to new This work used an array of miRNA activity reporters to identify miR‐21 as a mediator of trastuzumab resistance in breast cancer.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146392/1/bit26791.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146392/2/bit26791_am.pd

Statistics and Evolution of Functional Genomic Sequence

In this thesis, three separate problems of genomics are addressed, utilizing methods related to the field of statistical mechanics. The goal of the project discussed in the first chapter is the elucidation of post-transcriptional gene regulation imposed by microRNAs, a recently discovered class of tiny non-coding RNAs. A probabilistic algorithm for the computational identification of genes regulated by microRNAs is introduced, which was developed based on experimental data and statistical analysis of whole genome data. In particular, the application of this algorithm to multiple-alignments of groups of related species allows for the specific and sensitive detection of genes targeted by microRNAs on a genome-wide level. Examination of clade-specific predictions and cross-clade comparison yields deeper insights into microRNA biology and first clues about long-term evolution of microRNA regulation, which are discussed in detail. Modeling evolutionary dynamics of microsatellites, an abundant class of repetitive sequence in eukaryotic genomes, was the objective of the second project and is discussed in chapter two. Inspired by the putative functionality of some of these elements and the difficulty of constructing correct sequence alignments that reflect the evolutionary relationships between microsatellites, a neutral model for microsatellite evolution is developed and tested in the fruit fly Drosophila melanogaster by comparing evolutionary rates predicted by the model to independent measurements of these rates from multiple alignments of three closely relates Drosophila species. The model is applied separately to genomic sequence categories of different functional annotations in order to assess the varying influence of selective constraint among these categories. In the last chapter, a general population genetic model is introduced that allows for the determination of transcription factor binding site stability as a function of selection strength, mutation rate and effective population size at arbitrary values of these parameters. The analytical solution of this model indicates the probability of a binding site to be functional. The model is used to compute the population fraction of functional binding sites at fixed selection pressure across a variety of different taxa. The results lead to the conclusion that a decreasing effective population size, such as observed at the evolutionary transition from prokaryotes to eukaryotes, could result in loss of binding site stability. An extension to our model serves us to assess the compensatory effect of the emergence of multiple binding sites for the same transcription factor in order to maintain the existing regulatory relationship

Alternative splicing: regulation, function and evolution

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Bioquímica. Fecha de lectura: 13-01-2021Introns populate eukaryotic genes to a variable extent across species, being widespread in vertebrates and mammals. While the evolutionary advantages, if any, of introns, remain unclear, their expansion has provided the opportunity to splice genes in more than a single way, allowing the production of diferent mRNAs from a single gene through Alternative splicing (AS). AS patterns change during the development of complex organisms and diverge across diferent tissues and experimental conditions. These highly reproducible changes evidences the existence of a regulatory network that ensures repeatable responses to certain stimuli and suggest that, at least some of them, play a role in the overall physiological response or adaptation. Not surprisingly, perturbation of some elements of this network is often associated with pathological conditions. However, not only we are far from a complete characterization of the molecular mechanisms that drive AS changes in most pathologies like those afecting the heart, but the computational tools that are currently used to study these regulatory networks are limiting our ability to extract all the information that is hidden in the data. It has been long hypothesized that AS contributes to a great expansion of the proteome and facilitates the evolution of new functions from pre-existing ones without gene duplication. While there are very well known examples of how AS enables the production of diferent functional proteins or mRNAs, the proportion of AS isoforms that are actually functional remains large unknown. Indeed, recent studies from diferent perspectives, including both transcriptomic, proteomics and sequence evolutionary analysis suggest that this percentage may be rather small and that much of the observed transcriptomic diversity is driven by non-functional noise in the splicing process. In this thesis, we have studied global AS patterns through computational analysis of large RNA-seq datasets to characterize the causes and consequences of AS changes from diferent perspectives. First, we have analyzed how AS global patterns change during heart development and disease using data from a variety of mouse models. We found that AS changes modulate diferent biological processes than gene expression ones and are associated to isoform speci c protein-protein interactions. Disease patterns partially recapitulate developmental patterns probably through the upregulation of PTBP1, which is suficient to induce pathological changes in the heart. Second, in an attempt to improve computational tools for identi cation of regulatory elements, we have developed dSreg. This tool leverages the power of bayesian inference and hierarchical models to pool information across the whole transcriptome to infer, not only the changes in the activities of the underlying regulatory elements, but also the changes in inclusion rates, outperforming competing methods and tools made for both purposes separately. Finally, we have studied the evolutionary process driving AS divergence during mammalian evolution using models of phenotypic evolution in a phylogenetic framework. We found that AS patterns have evolved under weak stabilizing selection that allows widespread variability in AS patterns across species, with only about 5% of the genes probably encoding AS isoforms with dif erent functions. Rates of neutral evolution are high, preventing the identi cation of adaptive changes at this long evolutionary scale. In summary, this thesis provides new computational tools and knowledge about the evolution and regulation of AS in diferent biological conditions and helps to better understand its relevance from diferent persepectives

Genomic and functional characterization of G protein-coupled receptors in the human pathogen Schistosoma mansoni and the model planarian Schmidtea mediterranea

G protein-coupled receptors (GPCRs) constitute the largest known superfamily of integral membrane proteins, and represent a particularly lucrative set of chemotherapeutic targets. These seven transmembrane receptors play a central role in eukaryotic signal transduction and physiology, mediating cellular responses to a diverse range of extracellular stimuli. The phylum Platyhelminthes is of considerable medical and biological importance, housing prominent human pathogens as well as established model organisms in the realm of developmental and stem cell biology. There exists ample motivation to elucidate the structural and functional properties of GPCRs in this phylum. The availability of whole genome sequence data for the human blood fluke Schistosoma mansoni and the model planarian Schmidtea mediterranea paves the way for the first genome-wide analyses of platyhelminth GPCRs. Extensive efforts were made to delineate the receptor complements of these organisms. Further work primarily focuses on validation of a novel method for elucidating receptor function in the native cell membrane environment. Together, these genomic and functional data improve our understanding of basic platyhelminth receptor biology and shed light on a promising set of anthelmintic drug targets. Application of a transmembrane-focused it in silico protocol led to the discovery of 116 S. mansoni and 333 S. mediterranea GPCRs, followed by extensive curation of underlying gene models. Phylogenetic analysis of the resulting dataset confirmed the presence of the primary metazoan GRAFS families and revealed novel lineage-specific receptor groupings, including a large platyhelminth-specific Rhodopsin-like subfamily (PROF1) and a planarian-specific Adhesion-like family (PARF1). Support vector machines (SVMs) were trained and used for ligand-based classification of full-length Rhodopsin GPCRs, complementing phylogenetic and homology-based classification. PROF1 receptors were further revealed as neuronally-expressed endoGPCRs via whole mount in situ hybridization. In light of the unreliable nature of heterologous approaches to GPCR deorphanization, a novel loss-of-function assay was developed for ascertaining the ligand and G protein coupling properties of GPCRs in their native cell membrane environment. RNA interference (RNAi) was used in conjunction with a cAMP radioimmunoassay (RIA) to monitor second messenger modulation in response to the translational suppression of individual receptors. This strategy was applied to the deorphanization of both neuropeptide and aminergic GPCRs, allowing for the determination of Gαs and Gαi/o-mediated signaling. Loss-of-function phenotypic assays were performed in parallel. While these results establish the potential of this approach, future work can lead to further optimizations and the eventual adaptation of this protocol to higher-throughput platforms