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Contribution of environmental factors to genetic variation in the Pacific white-sided dolphin

Talwar et al. | Jan 23, 2024

Contribution of environmental factors to genetic variation in the Pacific white-sided dolphin
Image credit: Flavio

Here the authors sought to understand the effects of different variables that may be tied to pollution and climate change on genetic variation of Pacific white-sided dolphins, a species that is currently threatened by water pollution. Based on environmental data collected alongside a genetic distance matrix, they found that ocean currents had the most significant impact on the genetic diversity of Pacific white-sided dolphins along the Japanese coast.

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Aberrant response to dexamethasone suppression test associated with inflammatory response in MDD patients

Ulery et al. | Nov 06, 2023

Aberrant response to dexamethasone suppression test associated with inflammatory response in MDD patients

Major depressive disorder (MDD) is a prevalent mood disorder. The direct causes and biological mechanisms of depression still elude understanding, though genetic factors have been implicated. This study looked to identify the mechanism behind the aberrant response to the dexamethasone suppression test (DST) displayed by MDD patients, in which they display a lack of cortisol suppression. Analysis revealed several pro-inflammatory genes that were significant and differentially expressed between affected and non-affected groups in response to the DST. Looking at ways to decrease the inflammatory response could have implications for treatment and may explain why some people treated for depression still display symptoms or may lead researchers to different classes of drugs for treatment.

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siRNA-dependent KCNMB2 silencing inhibits lung cancer cell proliferation and promotes cell death

Jeong et al. | Nov 01, 2022

siRNA-dependent KCNMB2 silencing inhibits lung cancer cell proliferation and promotes cell death

Here, seeking to better understand the genetic associations underlying non-small cell lung cancer, the authors screened hundreds of genes, identifying that KCNMB2 upregulation was significantly correlated with poor prognoses in lung cancer patients. Based on this, they used small interfering RNA to decrease the expression of KCNMB2 in A549 lung cancer cells, finding decreased cell proliferation and increased lung cancer cell death. They suggest this could lead to a new potential target for lung cancer therapies.

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Using DNA Barcodes to Evaluate Ecosystem Health in the SWRCMS Reserve

Horton et al. | Sep 27, 2018

Using DNA Barcodes to Evaluate Ecosystem Health in the SWRCMS Reserve

Although the United States maintains millions of square kilometers of nature reserves to protect the biodiversity of the specimens living there, little is known about how confining these species within designated protected lands influences the genetic variation required for a healthy population. In this study, the authors sequenced genetic barcodes of insects from a recently established nature reserve, the Southwestern Riverside County Multi-Species Reserve (SWRCMSR), and a non-protected area, the Mt. San Jacinto College (MSJC) Menifee campus, to compare the genetic variation between the two populations. Their results demonstrated that the midge fly population from the SWRCMSR had fewer unique DNA barcode sequence changes than the MSJC population, indicating that the comparatively younger nature reserve's population had likely not yet established its own unique genetic drift changes.

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Contrasting role of ASCC3 and ALKBH3 in determining genomic alterations in Glioblastoma Multiforme

Sriram et al. | Sep 27, 2022

Contrasting role of <i>ASCC3</i> and <i>ALKBH3</i> in determining genomic alterations in Glioblastoma Multiforme

Glioblastoma Multiforme (GBM) is the most malignant brain tumor with the highest fraction of genome alterations (FGA), manifesting poor disease-free status (DFS) and overall survival (OS). We explored The Cancer Genome Atlas (TCGA) and cBioportal public dataset- Firehose legacy GBM to study DNA repair genes Activating Signal Cointegrator 1 Complex Subunit 3 (ASCC3) and Alpha-Ketoglutarate-Dependent Dioxygenase AlkB Homolog 3 (ALKBH3). To test our hypothesis that these genes have correlations with FGA and can better determine prognosis and survival, we sorted the dataset to arrive at 254 patients. Analyzing using RStudio, both ASCC3 and ALKBH3 demonstrated hypomethylation in 82.3% and 61.8% of patients, respectively. Interestingly, low mRNA expression was observed in both these genes. We further conducted correlation tests between both methylation and mRNA expression of these genes with FGA. ASCC3 was found to be negatively correlated, while ALKBH3 was found to be positively correlated, potentially indicating contrasting dysregulation of these two genes. Prognostic analysis showed the following: ASCC3 hypomethylation is significant with DFS and high ASCC3 mRNA expression to be significant with OS, demonstrating ASCC3’s potential as disease prediction marker.

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Refinement of Single Nucleotide Polymorphisms of Atopic Dermatitis related Filaggrin through R packages

Naravane et al. | Oct 12, 2022

Refinement of Single Nucleotide Polymorphisms of Atopic Dermatitis related Filaggrin through R packages

In the United States, there are currently 17.8 million affected by atopic dermatitis (AD), commonly known as eczema. It is characterized by itching and skin inflammation. AD patients are at higher risk for infections, depression, cancer, and suicide. Genetics, environment, and stress are some of the causes of the disease. With the rise of personalized medicine and the acceptance of gene-editing technologies, AD-related variations need to be identified for treatment. Genome-wide association studies (GWAS) have associated the Filaggrin (FLG) gene with AD but have not identified specific problematic single nucleotide polymorphisms (SNPs). This research aimed to refine known SNPs of FLG for gene editing technologies to establish a causal link between specific SNPs and the diseases and to target the polymorphisms. The research utilized R and its Bioconductor packages to refine data from the National Center for Biotechnology Information's (NCBI's) Variation Viewer. The algorithm filtered the dataset by coding regions and conserved domains. The algorithm also removed synonymous variations and treated non-synonymous, frameshift, and nonsense separately. The non-synonymous variations were refined and ordered by the BLOSUM62 substitution matrix. Overall, the analysis removed 96.65% of data, which was redundant or not the focus of the research and ordered the remaining relevant data by impact. The code for the project can also be repurposed as a tool for other diseases. The research can help solve GWAS's imprecise identification challenge. This research is the first step in providing the refined databases required for gene-editing treatment.

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