Biology Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2749
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Item ANALYTICAL APPROACHES FOR COMPLEX MULTI-BATCH -OMICS DATASETS AND THEIR APPLICATION TO NEURONAL DEVELOPMENT(2023) Alexander, Theresa Ann; Speer, Colenso M; El-Sayed, Najib M; Biology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)High-throughput sequencing methods are extremely powerful tools to quantify gene expression in bulk tissue and individual cells. Experimental designs often aim to quantify expression shifts to characterize developmental trajectories, disease states, or cellular drug responses. Experimental and genetic methods are also rapidly evolving to capture specific aspects of gene expression such as in targeting individual cell types, regulatory stages, and spatially resolved cell subcompartments. These studies frequently involve a variety of experimental conditions that require many samples to guarantee sufficient statistical power for subsequent analyses. These studies are frequently processed in multiple batches due to limitations on the number of samples that can be collected, processed, and sequenced at once. To eliminate erroneous results in subsequent analyses, it is necessary to deconvolve non-biological variation (batch effect) from biological signal. Here, we explored variational contributions in multi-batch high throughput sequencing experiments by developing new methods, evaluating heterogeneity-contributors in an axon-TRAP-RiboTag protocol case-study, and highlighting biological results from this protocol. First, we describe iDA, a novel dimensionality reduction method for high-throughput sequencing data. High-dimensional data in complex, multi-batch experiments often result in discrete clustering of samples or cells. Existing unsupervised linear dimensionality reduction methods like PCA often do not resolve discreteness simply with projections of maximum variance. We show that iDA can produce better projections for separating discrete clustering that correlates with known experimental biological and batch factors. Second, we provide a case study of special considerations for a complex, multi-batch high throughput experiment. We investigated the multi-faceted heterogenic contributions of a study using the axon-TRAP-RiboTag translatomic isolation protocol in a neuronal cell type. We show that popular batch-correction methods may reduce signal due to true biological heterogeneity in addition to technical noise. We offer metrics to help identify biological signal-driven batch-differences. Lastly, we employ our understanding of variational contributions in the intrinsically photosensitive retinal ganglion cell (ipRGC) -omics case study to explore the biological transcriptomic and translatomic coordination. Our analysis revealed ipRGCs participate in subcompartment-specific local protein translation. Genetic perturbations of photopigment-driven neuronal activity led to global tissue transcriptomic shifts in both the retina and brain targets, but the ipRGC axonal-specific translatome was unaltered.Item Diet and Stomach Microbiota of Gulf Menhaden, a key forage filter feeding fish species(2020) Hanif, Ammar Wali; Jagus, Rosemary; Marine-Estuarine-Environmental Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Menhaden represent a family of important filter feeding forage fish that serves as a trophic link between plankton and piscivorous predators in the marine environment. Dietary analysis is difficult because diet items are small and >80 % of the stomach content is amorphous material. DNA metabarcoding combines mass-amplification of short DNA sequences (barcodes) with high-throughput sequencing. This application allows the simultaneous identification of many taxa within the same environmental sample, as well as the analysis of many samples simultaneously, providing a comprehensive assessment of diet items and gut microbiota. Here we present a methodological approach using DNA metabarcoding suitable for a small filter feeding fish to identify the stomach contents of juvenile Gulf menhaden (Brevoortia patronus), collected within Apalachicola Bay, Florida. I describe the optimization of DNA extraction, comparison of two primers and sequencing protocols, estimation of menhaden DNA contamination, quality filtering of sequences, post-sequence processing and taxonomic identification of recovered sequences. I characterized the prokaryotic community using 16S universal ribosomal RNA (rRNA) gene sequencing primers in the V3-V4 hypervariable regions. Using two different sequencing protocols employing different “universal” 16S rRNA gene sequencing primers. Although no difference in overall operational taxonomic units (OTUs) was found, the two sequencing protocols gave differences in the relative abundancies of several bacterial classes. The dominant OTUs resulting from 16S rRNA gene sequencing at the phylum level were assigned to Proteobacteria, Acidobacteria, Actinobacteria and Chloroflexi and included oil eating bacteria consistent with the Gulf of Mexico location. Stomach microbiota and diet were compared in juvenile Gulf menhaden, Brevoortia patronus, caught at two locations, Two Mile Channel and St. Vincent Sound, in Apalachicola Bay, FL in May and July of 2013. The stomach microbiota of samples from both locations showed a predominance of Proteobacteria, Chloroflexi, Bacteroidetes, Acidobacteria and Actinobacteria, although significant differences in composition at the class level were seen. The stomach microbiota from fish from Two-Mile Channel showed a higher level of taxonomic richness and there was a strong association between the microbiota and sampling location, correlating with differences in salinity. Approximately 1050 diet items were identified, although significant differences in the species represented were found in samples from the two locations. Members of the Stramenopile/ Alveolate/Rhizaria (SAR) clade accounted for 66 % representation in samples from Two Mile Channel, dominated by the diatoms Cyclotella and Skeletonema, as well as the ciliate Oligotrichia. In contrast, Metazoa (zooplankton) dominated in samples from St. Vincent Sound, accounting for over 80 % of the reads. These are mainly Acartia copepods. Since ciliates are considered to be microzooplankton, this means there is just over 60 % representation of phytoplankton in samples from Two Mile Channel and over 90 % representation of zooplankton in samples from St. Vincent Sound. Overall, I demonstrate the diversity of juvenile menhaden stomach contents that supports a characterization of menhaden as environmental samplers.