Cielo
Hernandez
Sponsor: Fumika Hamada, Ph.D. Neuro Physio & Behavior Human body temperatures fluctuate throughout the day, playing a role in overall homeostatic regulation. This body temperature rhythm (BTR) is controlled by circadian clocks. We previously demonstrated that Drosophila (fruit flies) show similar BTR and regulatory mechanisms to mammals. The purpose of our research is to determine how BTR impacts longevity and which genes are involved in its regulation. We conducted a lifespan assay under several different temperature cycles and found that the wild-type flies housed in the incubator mimicking BTR (increase during the day and decrease during the night) lived longer than those in incubators with an inverse BTR (decrease during the day and increase during the night) or at a constant 25°C. Next, we performed lifespan experiments on insulin-like peptide 6 (ilp6) mutants and circadian clock mutants (tim01) to assess the importance of these genes on the lifespan of Drosophila. We discovered that tim01 mutants showed similar life spans to the wild-type flies while all of the ilp6 mutants lost their BTR- dependent longevity. These results suggest that BTR has an important role in longevity and that insulin signals help regulate BTR-dependent longevity, while circadian clocks may not. Using Weighted Gene Correlation Network Analysis for Cross-comparison of Circadian Rhythmic Transcriptomes
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Cielo Hernandez
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Weighted Gene Correlation Network Analysis (WGCNA) is a systems biology approach designed for generating networks from RNAseq gene expression data and uses midweight correlation statistics to build modules of co-expressing genes. These modules define gene-gene interactions and can be used to determine gene regulatory networks based on co-expression. Each module is represented by module eigengenes which can then be used to correlate with a variety of traits associated with the experimental design. In this project, we are using WGCNA to build gene networks based on circadian RNAseq transcriptome data sets and trait measurements associated with each study. Although WGCNA has been used in the circadian biology field to identify co-expressing genes, we have taken the approach a step further using WGCNA to compare across different circadian rhythm transcriptome data sets to identify convergent pathways. Using both the consensus module and module preservation approaches, we can identify which groups of genes and pathways are cycling similarly or differently across different datasets. This could be useful for various applications for identifying rhythmic biological processes across tissue types, sexes, species, and models. Furthermore, this approach can also be applied to other data types including epigenomic, proteomic, and metabolomic in addition to transcriptomic data. Latina Mathematics Undergraduates at UC Davis: Their Academic Success Factors and Their Identity Ana Hernandez
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UC Davis / MED: Medical Microbiology & Imm / 2024
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Cielo Hernandez