Molecular Genetics

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Now showing 1 - 3 of 3
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    Differences in race-specific outcome measures for chronic low back pain patients with relation to HTR2A variations
    (2021) Holden, Jeremy; Phillips, Nicole R.; Licciardone, John C.
    Purpose: The effects of many genes involved in the pathogenesis of chronic low back pain (CLBP) are not fully understood, especially concerning racial variation. This study aims to determine if variations of the serotonin receptor gene HTR2A, which has been implicated in psychological and pain disorders, correlate to differences in clinical outcome measures of patients with CLBP in the PRECISION Pain Research Registry. Methods: The base population includes 283 (68.4%) Caucasians and 131 (31.6%) African Americans who were genotyped for their haplotype in 2 haploblocks: A (rs6313;A/G, rs6311;T/C, rs1928040;A/G, rs9567746;A/G) and B (rs7997012;A/G, rs7330636;T/C). Race-specific Kruskal-Wallis analyses were used to determine differences in outcome measures when comparing haplotypes within haploblocks. Separate regression analyses looked at whether haplotypes that are overrepresented in one racial group versus the other had effects on the same outcomes. Results: There were differences in scores for the Roland-Morris Disability Questionnaire (RMDQ) (p=0.04), pain catastrophizing (PCS) (p=0.04), and pain self-efficacy (PSEQ) (p< 0.01) within haploblock A for African Americans. There were also differences in the RMDQ (p=0.02) and PSEQ (p< 0.01) scores within haploblock B for Caucasians. Regressions showed having at least one allele with the haplotype GC in haploblock B is associated with a lower numerical rating scale value for pain intensity after adjusting for additional variables (beta=-0.59; p=0.02). Conclusions: Haplotypes of HTR2A may have a relationship with the pain intensity, disability, and pain response of CLBP patients. Further studies would look at additional race-specific factors and their interplay with HTR2A.
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    Optimization of CRISPR-Cas9 via the synergy of MD simulation and machine learning
    (2021) Liu, Jin; Wang, Duen-Shian; Liang, Ivy
    CRISPR-Cas9, a promising gene-editing tool, sheds light on gene therapy. The normal DNA cleavage of CRISPR-Cas9 is programmed by a guide RNA (gRNA) template. However, recent studies showed that Cas9 cleavage occurs even without guidance from the gRNA in the presence of Mn2+ ions, implying the issue of off-target effect of Cas9. Here, we report a mechanism of this RNA-independent off-target cleavage (RI-cleavage) elucidated by molecular dynamic (MD) simulations. We further used machine learning algorithms developed by our lab to facilitate the design of novel Cas9 variants to reduce such RI-cleavage. In this study, we revealed the possible mechanism of RI-cleavage and further engineered Cas9 to reduce RI-cleavage via the power of machine learning. Our research serves as an excellent example showing the potential in the synergy of MD simulation and machine learning to optimize CRISPR-Cas9.
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    MitoHooker: A PCR-free enrichment strategy using RNA baits for targeted detection of mitochondrial base modifications on nanopore sequencing devices
    (2021) Hall, Courtney; Reid, Danielle; Phillips, Nicole; Planz, John
    Purpose: Aberrant methylation and increased oxidative damage throughout the mitochondrial genome (mtDNA) have been implicated in numerous diseases ranging from cancer to neurodegeneration. Current understanding, however, is obscured by the inherent limitations of traditional detection techniques. Nanopore sequencing offers the ability to simultaneously ascertain genetic variation and base modifications without chemical treatment. While numerous copies of mtDNA are present within a sample, these sequences represent a small fraction of total genetic material competing for pore access. Therefore, this project aimed to evaluate RNA baits hybridization capture for enrichment of mtDNA prior to nanopore sequencing. Methods: Heavy and light mtDNA strands in cell-free plasma extracts were individually captured using the Arbor Biosciences myBaits Expert Mito kit. Elutant from the first capture served as input for rebaiting with the opposite probe set. Following complement synthesis by Klenow fragment, double-stranded products were multiplexed and sequenced on the MinION device. Resultant basecalled reads were mapped to the human reference genome to assess on- and off-target coverage. Base modifications in the raw data were detected using a combination of available bioinformatics tools and in-house algorithms. Results: Although overall input and throughput were significantly lower than a typical whole genome sequencing run, read count and coverage data indicate that this technique allowed mtDNA to outcompete background DNA while maintaining modified bases within the native strands. Conclusion: The workflow developed herein could provide novel insights into the complete collection of mtDNA base modifications and enable identification of disease-relevant alterations in this landscape.