Bioinformatics Commons^™

Spatiotemporal Transcriptome Diversity And Responses To Salinity Tolerance In The Extremophyte Schrenkiella Parvula, Chathura Wijesinghege

LSU Doctoral Dissertations

Schrenkiella parvula is an extremophyte model related to the most widely studied plant model, Arabidopsis thaliana and Brassica crops in the mustard family (Brassicaceae). It can thrive in highly saline environments where the soil is enriched in Na⁺, K⁺, Li⁺, borates, and chlorides. Understanding how this extremophyte can survive high salinity with genomic adaptations can provide insight into developing stress resilient crops in the future. Gene expression of S. parvula in response to salt has been investigated using shoot and root tissue from mature vegetative-phase plants. However, prior studies have not examined the transcript …

Understanding Potassium Toxicity Stress Responses Of The Extremophyte Schrenkiella Parvula Using Systems Biology Approaches, Pramod Pantha

LSU Doctoral Dissertations

Schrenkiella parvula is an extremophyte model closely related to Arabidopsis thaliana and Brassica crops. Its natural habitat includes shores of saline lakes in the Irano-Turanian region. It has adapted to grow in soils rich in multiple salts including Na⁺ and K⁺. I have investigated the genetic basis for high K⁺ tolerance in plants using S. parvula as a stress tolerant model compared to the premier plant model, Arabidopsis thaliana which is highly sensitive to salt stresses using physiological, ionomic, transcriptomic, and metabolomic approaches. Under high K⁺ stress, root system architecture changes significantly compared to control …

Quantifying Structure And Variation In Complex Phylogenetic Data, Genevieve Geraldine Mount

LSU Doctoral Dissertations

Identifying the source and structure of variation in nature is crucial to understanding fundamental aspects of evolution. Despite a recent plethora of genetic and morphological data, many interesting questions about the relationships between different groups remain unresolved. My dissertation evaluates three approaches for identifying and quantifying the variation within phylogenetic datasets. Characterizing variation within datasets and across analytical methods gives insight into biologically interesting characters, unusual evolutionary processes, and areas for model improvement.

Network-based community detection approaches offer a powerful tool to describe variation in phylogenetic signal across the genome (i.e., gene tree variation). In Chapter 2, I investigate the …

Metabolic Network Analysis Of Filamentous Cyanobacteria, Daniel Alexis Norena-Caro

LSU Doctoral Dissertations

Cyanobacteria were the first organisms to use oxygenic photosynthesis, converting CO₂ into useful organic chemicals. However, the chemical industry has historically relied on fossil raw materials to produce organic precursors, which has contributed to global warming. Thus, cyanobacteria have emerged as sustainable stakeholders for biotechnological production. The filamentous cyanobacterium Anabaena sp. UTEX 2576 can metabolize multiple sources of Nitrogen and was studied as a platform for biotechnological production of high-value chemicals (i.e., pigments, antioxidants, vitamins and secondary metabolites). From a Chemical engineering perspective, the biomass generation in this organism was thoroughly studied by interpreting the cell as a microbial …

High-Performance Computing Frameworks For Large-Scale Genome Assembly, Sayan Goswami

LSU Doctoral Dissertations

Genome sequencing technology has witnessed tremendous progress in terms of throughput and cost per base pair, resulting in an explosion in the size of data. Typical de Bruijn graph-based assembly tools demand a lot of processing power and memory and cannot assemble big datasets unless running on a scaled-up server with terabytes of RAMs or scaled-out cluster with several dozens of nodes. In the first part of this work, we present a distributed next-generation sequence (NGS) assembler called Lazer, that achieves both scalability and memory efficiency by using partitioned de Bruijn graphs. By enhancing the memory-to-disk swapping and reducing the …

Computational Analysis Of Papionini Evolution Using Alu Insertions, Vallmer Edward Jordan Ii

LSU Doctoral Dissertations

Alu elements are primate specific retrotransposons that have remained active throughout the course of primate evolution. As a result of this sustained mobilization. Alu elements are present in greater copy number in primate genomes than any other transposable element. An average of over one million Alu elements has been identified in every sequenced haplorrhine genome to date. These characteristics qualify Alu elements as ideal characters for studying evolutionary relationship among primates.

The increasing availability of whole genome sequencing data presents novel challenges and opportunities for comparative genomic analyses. Genomic data is now publicly available for most primate species. Such an …

Mtbindingsim: Simulate Protein Binding To Microtubules, Julia T. Philip, Charles H. Pence, Holly V. Goodson

Faculty Publications

Summary: Many protein–protein interactions are more complex than can be accounted for by 1:1 binding models. However, biochemists have few tools available to help them recognize and predict the behaviors of these more complicated systems, making it difficult to design experiments that distinguish between possible binding models. MTBindingSim provides researchers with an environment in which they can rapidly compare different models of binding for a given scenario. It is written specifically with microtubule polymers in mind, but many of its models apply equally well to any polymer or any protein–protein interaction. MTBindingSim can thus both help in training intuition about …