1,580 research outputs found

    The Regulation of Alternative Pre-mRNA Splicing in Photoreceptor Cells.

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    Alternative pre-mRNA splicing provides an important mechanism for generating the diverse array of proteins required to generate complex tissue and cell types from a limited genome. Therefore, the proper regulation of alternative splicing is vital to shape cellular identity and function. As consequence, defects in alternative splicing are associated with disease phenotypes that can range from systemic syndromes to the dysfunction of single cell types. For example, heterozygous mutations in ubiquitously expressed components of the spliceosome lead to photoreceptor specific cell death. This suggests that the topography of alternative splicing in photoreceptors cells may be unique, a notion which is supported by reports of photoreceptor specific splicing events. However, the mechanisms mediating photoreceptor specific splicing, and the reason why photoreceptors are uniquely sensitive to perturbations in the splicing machinery, remain unknown. In this work, I characterize the alternative splicing program of photoreceptor cells using exon 2A of the BBS8 gene as a model. The photoreceptor specific exon 2A was recently discovered through a mutation in the 3ā€™ splice site that was linked with non-syndromic retinitis pigmentosa (RP). Skipping of this exon in photoreceptor cells was thought to limit the phenotype of the mutation to RP, rather than the systemic disease Bardet-Biedl syndrome (BBS). I show that the IVS1-2A\u3eG mutation in BBS8 leads to missplicing of exon 2A, producing a shift in the reading frame predicted to eliminate the BBS8 protein specifically in photoreceptor cells. I also show that in the absence of splicing elements within the exon, the splicing of exon 2A is directed entirely by sequences located within the adjacent introns. To gain a more expansive view of the photoreceptor splicing program, I utilize mouse models to isolate the gene expression and alternative splicing profile of photoreceptor cells by RNA sequencing. Bioinformatics analysis indicates that while photoreceptors share a general splicing pattern with other neurons, they exhibit a distinct program that affects a broad set of genes. Cell type specific splicing in photoreceptors appears to be regulated by a combinatorial mechanism which involves activation by the Musashi proteins in the absence of many typical neuronal splicing regulators. This program controls a subset of exons, including BBS8 exon 2A, which are spliced in a ā€œswitch-likeā€ manner to produce photoreceptor specific protein isoforms. These splicing events share a temporal inclusion pattern which precedes the development of the light sensing outer segment. Remarkably, multiple switch-like exons are located within genes that are necessary for the biogenesis and maintenance of primary cilia. This suggests that alternative splicing may modulate protein function to allow for development and maintenance of the unique structure of photoreceptor cells. This work provides a foundation on which to characterize the regulation of alternative splicing in photoreceptor cells, and identifies multiple splicing events which may impact the function of the photoreceptor outer segment

    Using Evolutionary Conserved Modules in Gene Networks as a Strategy to Leverage High Throughput Gene Expression Queries

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    Background: Large-scale gene expression studies have not yielded the expected insight into genetic networks that control complex processes. These anticipated discoveries have been limited not by technology, but by a lack of effective strategies to investigate the data in a manageable and meaningful way. Previous work suggests that using a pre-determined seednetwork of gene relationships to query large-scale expression datasets is an effective way to generate candidate genes for further study and network expansion or enrichment. Based on the evolutionary conservation of gene relationships, we test the hypothesis that a seed network derived from studies of retinal cell determination in the fly, Drosophila melanogaster, will be an effective way to identify novel candidate genes for their role in mouse retinal development. Methodology/Principal Findings: Our results demonstrate that a number of gene relationships regulating retinal cell differentiation in the fly are identifiable as pairwise correlations between genes from developing mouse retina. In addition, we demonstrate that our extracted seed-network of correlated mouse genes is an effective tool for querying datasets and provides a context to generate hypotheses. Our query identified 46 genes correlated with our extracted seed-network members. Approximately 54% of these candidates had been previously linked to the developing brain and 33% had been previously linked to the developing retina. Five of six candidate genes investigated further were validated by experiments examining spatial and temporal protein expression in the developing retina. Conclusions/Significance: We present an effective strategy for pursuing a systems biology approach that utilizes an evolutionary comparative framework between two model organisms, fly and mouse. Future implementation of this strategy will be useful to determine the extent of network conservation, not just gene conservation, between species and will facilitate the use of prior biological knowledge to develop rational systems-based hypotheses

    Evolution of Interactomes

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    Protein-protein interactions are part of all biological processes and are responsible for directing the development and maintenance of all systems in a species. Identifying such interactions provides insight into molecular processes in addition to their importance in understanding disease. Identifying protein-protein interactions experimentally is expensive, both in terms of cost and effort, and can generate erroneous results. Thus computational methods are key in reducing the scope of experimental assays, providing predictions for subsequent verification. Herein I present a new computational tool for the prediction of protein-protein interactions which, looking at sequence data alone, can identify putative interacting proteins as a result of their coordinated evolution. This new approach builds on previous molecular evolutionary methods and combines evolutionary information from individual proteins. As a proof of concept, the new approach was tested on the well-studied interaction networks of the visual and auditory systems. From this analysis, several protein clusters were identified warranting further experimental investigation. Furthermore, this effort also identified areas for future refinement of the software tool

    In Silico Estimation of the Abundance and Phylogenetic Significance of the Composite Oct4-Sox2 Binding Motifs within a Wide Range of Species

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    High-throughput sequencing technologies have greatly accelerated the progress of genomics, transcriptomics, and metagenomics. Currently, a large amount of genomic data from various organisms is being generated, the volume of which is increasing every year. Therefore, the development of methods that allow the rapid search and analysis of DNA sequences is urgent. Here, we present a novel motif-based high-throughput sequence scoring method that generates genome information. We found and identified Utf1-like, Fgf4-like, and Hoxb1-like motifs, which are cis-regulatory elements for the pluripotency transcription factors Sox2 and Oct4 within the genomes of different eukaryotic organisms. The genome-wide analysis of these motifs was performed to understand the impact of their diversification on mammalian genome evolution. Utf1-like, Fgf4-like, and Hoxb1-like motif diversity was evaluated across genomes from multiple species.Peer reviewe

    Neurodevelopmental Consequences of Prenatal Alcohol Exposure: Behavioural and Transcriptomic Alterations in a Mouse Model

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    Fetal Alcohol Spectrum Disorder (FASD) is an umbrella term referring to a range of physical, behavioural, and cognitive deficits resulting from prenatal alcohol exposure. The resulting abnormalities are heterogeneous and often attributed to timing and dosage of alcohol exposure. However, the specific effects of developmental timing are not well-known. This research used C57BL/6J (B6) as an animal model for early (human trimester one) and mid-gestation (human trimester two) alcohol exposure. Pregnant B6 mice were injected with 2.5 g/kg ethanol on gestational day (GD) 8 and 11 (trimester one equivalent), or on GD 14 and 16 (trimester two equivalent). Resulting pups were followed from birth to adulthood using FASD-relevant behavioural tests. At postnatal day (PD) 70, whole brain tissues were extracted. A third group of dams were injected on GD 16 (short-term). Two hours post injection, fetal brains were removed. Brains were used for genome-wide expression analysis, including microRNAs. Downstream analyses were completed using software packages and online databases. All ethanol-treated pups showed motor skill delays, increased activity, and spatial learning deficits. Gene expression analysis resulted in altered expression of 48 short-term genes between ethanol and control mice treated during the second trimester. Fifty-five and 68 genes were differentially-expressed in the long-term analyses of mice treated during trimester one and two, respectively. Genes involved in immune system response were disrupted across all treatments. Disrupted short-term processes included cytoskeleton development and immunological functions. Processes altered in long-term exposures included stress signaling, DNA stability, and cellular proliferation. MicroRNA analyses returned eight and 20 differentially-expressed miRNAs in trimesters one and two, respectively. Target filtering of trimester one microRNAs and mRNAs resulted in inverse relationships between miR-532-5p and Atf1, Itpripl2, and Stxbp6. Trimester two target filtering resulted in miR-302c targeting Ccdc6. Gene expression and microRNA results demonstrate the stage-specific genes and processes altered during neurodevelopment upon ethanol exposure. Certain cellular processes are disrupted no matter the timing of ethanol exposure. Given that microRNAs are fine-tuners of gene expression, they may play an important role in the maintenance of FASD. Furthermore, transcriptomic changes in the brain may explain the observed behavioural effects of prenatal ethanol exposure

    SPERMATOGENESIS MOLECULAR EVOLUTION IN MURINE RODENTS

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    Reproductive traits are fascinating from an evolutionary perspective because they are necessary for individuals to produce offspring and increase their evolutionary fitness. Given the essentiality of reproduction to fitness, genes involved in reproduction may be expected to be highly conserved. However, some genes involved in reproduction evolve very rapidly, including many spermatogenesis genes. This rapid evolution may result from intense sexual selection acting on reproductive traits, particularly in species where females mate multiply thus creating the potential for sperm competition. In addition to sexual selection, other evolutionary forces may shape rapid spermatogenesis evolution, including genomic conflict and relaxed pleiotropic constraint due to the high specificity of genes involved in spermatogenesis. It is unclear how these forces may interact, their relative importance in spermatogenesis molecular evolution, and how the intensity of these forces changes across spermatogenesis developmental stages. Rapid spermatogenesis evolution is thought to have important downstream consequences, including rapid phenotypic evolution of male reproductive traits and reproductive barriers that contribute to speciation. However, direct connections between molecular evolution, phenotypic evolution, and speciation have rarely been made for male reproductive traits. Thus, my dissertation seeks to understand what are the causes and consequences of rapid spermatogenesis molecular evolution? House mice (Mus musculus) and closely related species are an ideal system in which to address this question because they experience sperm competition, form natural hybrid zones and produce sterile hybrid males, readily breed and hybridize in the laboratory, and have extensive genomic resources available. Furthermore, house mice are part of the massive Murinae subfamily of rodents, which comprise over 10% of all mammal species and show remarkable variation in reproductive traits, including sperm morphology. Spermatogenesis is a complex developmental process, so understanding variation in the intensity of different evolutionary forces across spermatogenesis stages is critical to understanding spermatogenesis evolution. Fluorescenceactivated cell sorting is one way to generate enriched cell populations representing different spermatogenesis stages. In this dissertation, I use gene expression data from sorted cell populations in house mice, as well as genomic and phenotypic data from mice and other murine rodents to study mammalian spermatogenesis evolution. In Chapter 1, I use data from enriched cell populations representing two different spermatogenesis stages and four different species of mice to investigate the relative rates of molecular evolution across spermatogenesis and the types of mutations underlying gene expression evolution in different spermatogenesis stages. I show that lineage-specificity of genes expressed, gene expression level divergence, and protein sequence divergence all increase during the late stages of spermatogenesis. I also show that protein coding divergence, but not gene expression divergence, is higher on the X chromosome than the autosomes across spermatogenesis cell types. Lastly, I use published data from F1 mouse crosses to do allelespecific expression analyses and show that the types of regulatory mutations underlieing expression divergence are strikingly different between early and late spermatogenesis. This study provides insight into mammalian spermatogenesis molecular evolution and shows the importance of developmental context in molecular evolutionary studies. In Chapter 2, I perform two genetic experiments involving advanced-generation hybrid mouse crosses to explore hybrid incompatibilities on the sex chromosomes and their effects on hybrid male spermatogenesis expression and reproductive phenotypes. My results refute the hypothesis that genomic conflict between the sex chromosomes contributes to sex chromosome overexpression during late spermatogenesis in sterile mouse hybrids. However, they do show that incompatibilities between the X and Y chromosomes, between the Y chromosome and autosomes, or both likely contribute to male hybrid sterility in house mice. These findings advance our understanding of genetic incompatibilities contributing to male hybrid sterility, a common barrier to reproduction between species. In Chapter 3, I expand my research on spermatogenesis evolution to the Murinae subfamily, using exome capture and phenotype data to investigate the role of sexual selection in sperm morphological evolution and test for positive selection acting on male reproductive genes. My analyses indicate that relative testes mass is evolving indepently of phylogeny, and therefore may be evolving in response to sperm competition. Most Murinae sperm have a hook on the sperm head, and I show that hook length and angle are correlated with relative testes mass suggesting that these traits may also be selected on by sperm competition. Lastly, I find that genes expressed in rapidly evolving male reproductive tissues and spermatogenesis cell types, specifically seminal vesicles and postmeiotic spermatids, tend to experience more positive selection than other male reproductive genes, so their rapid evolution is likely due in part to positive selection. These findings contribute to our understanding of the underlieing causes of the rapid evolution of reproduction at both the phenotypic and molecular levels. In addition to these three chapters, I contributed to several related projects that address the overarching questions of my dissertation: a review on sex chromosome evolution in mammals in the context of spermatogenesis (Larson, et al. 2018), two methodological papers on quantifying sperm morphology (Skinner, et al. 2019a; Skinner, et al. 2019b), a peer-reviewed research article on disrupted X chromosome expression at different spermatogenesis stages in sterile house mouse hybrids (Larson, et al. 2021), and a study on X chromosome evolution in dwarf hamsters (Moore, et al. 2022). Collectively, my dissertation and related projects contribute to our understanding of reproduction and molecular evolution in mammals

    Integrated view and comparative analysis of baseline protein expression in mouse and rat tissues

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    The increasingly large amount of proteomics data in the public domain enables, among other applications, the combined analyses of datasets to create comparative protein expression maps covering different organisms and different biological conditions. Here we have reanalysed public proteomics datasets from mouse and rat tissues (14 and 9 datasets, respectively), to assess baseline protein abundance. Overall, the aggregated dataset contained 23 individual datasets, including a total of 211 samples coming from 34 different tissues across 14 organs, comprising 9 mouse and 3 rat strains, respectively. In all cases, we studied the distribution of canonical proteins between the different organs. The number of canonical proteins per dataset ranged from 273 (tendon) and 9,715 (liver) in mouse, and from 101 (tendon) and 6,130 (kidney) in rat. Then, we studied how protein abundances compared across different datasets and organs for both species. As a key point we carried out a comparative analysis of protein expression between mouse, rat and human tissues. We observed a high level of correlation of protein expression among orthologs between all three species in brain, kidney, heart and liver samples, whereas the correlation of protein expression was generally slightly lower between organs within the same species. Protein expression results have been integrated into the resource Expression Atlas for widespread dissemination

    Computational, Integrative, and Comparative Methods for the Elucidation of Genetic Coexpression Networks

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    Gene expression microarray data can be used for the assembly of genetic coexpression network graphs. Using mRNA samples obtained from recombinant inbred Mus musculus strains, it is possible to integrate allelic variation with molecular and higher-order phenotypes. The depth of quantitative genetic analysis of microarray data can be vastly enhanced utilizing this mouse resource in combination with powerful computational algorithms, platforms, and data repositories. The resulting network graphs transect many levels of biological scale. This approach is illustrated with the extraction of cliques of putatively coregulated genes and their annotation using gene ontology analysis and cis-regulatory element discovery. The causal basis for coregulation is detected through the use of quantitative trait locus mapping

    In Silico

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