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Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder that affects 6-7% of people worldwide (Wilcutt, 2012). MAOA is a gene that encodes monoamine oxidase A, an enzyme responsible for the regulation and metabolism of monoamines thought to be associated with ADHD. This study investigates a leucine to serine swap at amino acid position 32 in FAD-binding domain of the enzyme monoamine oxidase A. Results from in silico prediction tools and molecular dynamics modeling provide evidence to support pathogenicity of the L32S missense variant of monoamine oxidase A. 

Hereditary Hemorrhagic Telangiectasia (HHT) is an autosomal dominant disease that interferes with the formation of arteries. The ENG gene encodes for the protein endoglin which is used to properly develop and remodel arteries. The removal of endoglin forms telangiectasias that cause bleeding from the nose and vital organs. This study investigates the impact of one of the many variants of uncertain significance of ENG associated with HHT. The missense swap of alanine for valine at position 218 (Ala218Val) was characterized through computational metrics from in silico pathogenicity prediction tools, conservation analysis, and molecular dynamics simulation (MDS). The structural residue is highly conserved over multiple species and buried. The missense swap resulted in a difference in movement from the wild type according to MDS in a simulated aqueous environment. Therefore, it is predicted to be likely pathogenic. 

Background: Variants within factor VIII (F8) are associated with sex-linked hemophilia A and thrombosis, with gene therapy approaches being available for pathogenic variants. Many variants within F8 remain variants of uncertain significance (VUS) or are under-explored as to their connections to phenotypic outcomes. Methods: We assessed data on F8 expression while screening the UniProt, ClinVar, Geno2MP, and gnomAD databases for F8 missense variants; these collectively represent the sequencing of more than a million individuals. Results: For the two F8 isoforms coding for different protein lengths (2351 and 216 amino acids), we observed noncoding variants influencing expression which are also associated with thrombosis risk, with uncertainty as to differences in females and males. Variant analysis identified a severe stratification of potential annotation issues for missense variants in subjects of non-European ancestry, suggesting a need for further defining the genetics of diverse populations. Additionally, few heterozygous female carriers of known pathogenic variants have sufficiently confident phenotyping data, leaving researchers unable to determine subtle, less defined phenotypes. Using structure movement correlations to known pathogenic variants for the VUS, we determined seven clusters of likely pathogenic variants based on screening work. Conclusions: This work highlights the need to define missense variants, especially those for VUS and from subjects of non-European ancestry, as well as the roles of these variants in women’s physiology. 

Parkinson’s disease is the second most common neurodegenerative disease which is caused by a lack of dopamine in the brain. Parkinson 22 is a form of Parkinson’s disease caused by variations in the coiled-coil-helix-coiled-coil-helix domain containing 2 (CHCHD2) protein. This study investigates an aspartic acid-to-alanine swap on amino acid position 130 (D130A) of the CHCHD2 protein. We have employed protein modeling, conservation analysis, and molecular dynamics simulations to gain an understanding of the effects of the D130A variant on CHCHD2 protein structure and movement. 

The COVID‐19 pandemic brought to light the continued issues in access to research opportunities. Many of our undergraduate students at research‐intensive institutes lost their ability to go into labs to gain experience. However, students at most smaller colleges and universities faced these challenges to bring research opportunities to students long before the pandemic. Thus, our lower‐cost community colleges and higher education institutes with diverse students lack equity when it comes to research investments. This highlights the need for bringing research into diverse institutes using novel approaches. Over the past ten years, our team has built a strategy for integrating genomic and molecular bioinformatics tools into undergraduate opportunities. Developing bioinformatics training material, professor training opportunities, summer research opportunities, and organized large scale research projects, our team has developed a distributed research network. Our goal is to bring genomic and bioinformatic literacy to early undergraduate training to increase STEM retention while improving research equity issues. Having students work on characterizing challenging clinical variants, known as Variants of Uncertain Significance (VUS), brings novel research projects to students while filling the growing needs of clinical variant characterizations. At the core training, we focus on bringing tools to professors and instructors, lowering the initiation efforts to performing bioinformatics research. These include the optimization of protein homology modeling, molecular dynamic simulations through analysis with a few mouse clicks (or two lines of code for Linux users), 3D protein printing, deep evolutionary profiling with hundreds of species using user‐friendly tools, assessing expression from the NCBI SRA, and integrating genomic databases (GTEx, Human Protein Atlas, Geno2MP, gnomAD, Comparative Toxicogenomics Database, PharmGKB, Open Targets Genetics). Once in the hands of professors, they have implemented these tools into independent research projects for their students, coursework design such as bioinformatics classes, and research clubs. Over the past ten years, we have thus impacted hundreds of students with these tools. This can best be highlighted by the student's successes integrating the tools into publications on the NMDA receptors (PMID:34726335), CFTR database for cystic fibrosis (PMID: 32734384), NAA10 variant analysis (PMID: 33335012), multiple sclerosis genetics (PMID: 31482761), COVID‐19 immune response (PMID:34335605), the SARS‐CoV‐2 evolution/structural dynamicome (PMID: 32587094), CCR5 role in diverse phenotypes and bioethics (accepted), and SOX gene developmental biology (in review). Thus, the development of tools and strategies and the distribution of research projects can reach students and faculty at any institute, bringing equitable research opportunities to those who traditionally do not have many opportunities. 

Genomics has grown exponentially over the last decade. Common variants are associated with physiological changes through statistical strategies such as Genome-Wide Association Studies (GWAS) and quantitative trail loci (QTL). Rare variants are associated with diseases through extensive filtering tools, including population genomics and trio-based sequencing (parents and probands). However, the genomic associations require follow-up analyses to narrow causal variants, identify genes that are influenced, and to determine the physiological changes. Large quantities of data exist that can be used to connect variants to gene changes, cell types, protein pathways, clinical phenotypes, and animal models that establish physiological genomics. This data combined with bioinformatics including evolutionary analysis, structural insights, and gene regulation can yield testable hypotheses for mechanisms of genomic variants. Molecular biology, biochemistry, cell culture, CRISPR editing, and animal models can test the hypotheses to give molecular variant mechanisms. Variant characterizations can be a significant component of educating future professionals at the undergraduate, graduate, or medical training programs through teaching the basic concepts and terminology of genetics while learning independent research hypothesis design. This article goes through the computational and experimental analysis strategies of variant characterization and provides examples of these tools applied in publications. © 2022 American Physiological Society. Compr Physiol 12:3303-3336, 2022.