Unlocking the Complexity of Mitochondrial DNA: A Key to Understanding Neurodegenerative Disease Caused by Injury

Neurodegenerative disorders that are triggered by injury typically have variable and unpredictable outcomes due to the complex and multifactorial cascade of events following the injury and during recovery. Hence, several factors beyond the initial injury likely contribute to the disease progression and pathology, and among these are genetic factors. Genetics is a recognized factor in determining the outcome of common neurodegenerative diseases. The role of mitochondrial genetics and function in traditional neurodegenerative diseases, such as Alzheimer’s and Parkinson’s diseases, is well-established. Much less is known about mitochondrial genetics, however, regarding neurodegenerative diseases that result from injuries such as traumatic brain injury and ischaemic stroke. We discuss the potential role of mitochondrial DNA genetics in the progression and outcome of injury-related neurodegenerative diseases. We present a guide for understanding mitochondrial genetic variation, along with the nuances of quantifying mitochondrial DNA variation. Evidence supporting a role for mitochondrial DNA as a risk factor for neurodegenerative disease is also reviewed and examined. Further research into the impact of mitochondrial DNA on neurodegenerative disease resulting from injury will likely offer key insights into the genetic factors that determine the outcome of these diseases together with potential targets for treatment.

Prognostic Immunophenotyping Clusters of Clear Cell Renal Cell Carcinoma Defined by the Unique Tumor Immune Microenvironment

Background: The tumor microenvironment affects the occurrence and development of cancers, including clear cell renal cell carcinoma (ccRCC). However, how the immune contexture interacts with the cancer phenotype remains unclear.Methods: We identified and evaluated immunophenotyping clusters in ccRCC using machine-learning algorithms. Analyses for functional enrichment, DNA variation, immune cell distribution, association with independent clinicopathological features, and predictive responses for immune checkpoint therapies were performed and validated.Results: Three immunophenotyping clusters with gradual levels of immune infiltration were identified. The intermediate and high immune infiltration clusters (Clusters B and C) were associated with a worse prognosis for ccRCC patients. Tumors in the immune-hot Clusters B and C showed pro-tumorigenic immune infiltration, and these patients showed significantly worse survival compared with patients in the immune-cold Cluster A in the training and testing cohorts (n = 422). In addition to distinct immune cell infiltrations of immunophenotyping, we detected significant differences in DNA variation among clusters, suggesting a high degree of genetic heterogeneity. Furthermore, expressions of multiple immune checkpoint molecules were significantly increased. Clusters B and C predicted favorable outcomes in 64 ccRCC patients receiving immune checkpoint therapies from the FUSCC cohort. In 360 ccRCC patients from the FUSCC validation cohort, Clusters B and C significantly predicted worse prognosis compared with Cluster A. After immunophenotyping of ccRCC was confirmed, significantly increased tertiary lymphatic structures, aggressive phenotype, elevated glycolysis and PD-L1 expression, higher abundance of CD8+ T cells, and TCRn cell infiltration were found in the immune-hot Clusters B and C.Conclusion: This study described immunophenotyping clusters that improved the prognostic accuracy of the immune contexture in the ccRCC microenvironment. Our discovery of the novel independent prognostic indicators in ccRCC highlights the relationship between tumor phenotype and immune microenvironment.

ODGI: understanding pangenome graphs

Motivation: Pangenome graphs provide a complete representation of the mutual alignment of collections of genomes. These models offer the opportunity to study the entire genomic diversity of a population, including structurally complex regions. Nevertheless, analyzing hundreds of gigabase-scale genomes using pangenome graphs is difficult as it is not well-supported by existing tools. Hence, fast and versatile software is required to ask advanced questions to such data in an efficient way. Results: We wrote ODGI, a novel suite of tools that implements scalable algorithms and has an efficient in-memory representation of DNA variation graphs. ODGI includes tools for detecting complex regions, extracting loci, removing artifacts, exploratory analysis, manipulation, validation, and visualization. Its fast parallel execution facilitates routine pangenomic tasks, as well as pipelines that can quickly answer complex biological questions of gigabase-scale pangenome graphs. Availability: ODGI is published as free software under the MIT open source license. Source code can be downloaded from https://github.com/pangenome/odgi and documentation is available at https://odgi.readthedocs.io. ODGI can be installed via Bioconda https: //bioconda.github.io/recipes/odgi/README.html or GNU Guix https://github.com/ ekg/guix-genomics/blob/master/odgi.scm.

Genomic characterization between strains selected for death-feigning duration for avoiding attack of a beetle

Predator avoidance is an important behavior that affects the degree of adaptation of organisms. We compared the DNA variation of one of the predator-avoidance behaviors, the recently extensively studied "death-feigning behavior”, between the long strain bred for feigning death for a long time and the short strain bred for feigning death for a short time. To clarify how the difference in DNA sequences between the long and short strains corresponds to the physiological characteristics of the death-feigning duration at the transcriptome level, we performed comprehensive and comparative analyses of gene variants in Tribolium castaneum strains using DNA-resequencing. The duration of death feigning involves many gene pathways, including caffeine metabolism, tyrosine metabolism, tryptophan metabolism, metabolism of xenobiotics by cytochrome P450, longevity regulating pathways, and circadian rhythm. Artificial selection based on the duration of death feigning results in the preservation of variants of genes in these pathways in the long strain. This study suggests that many metabolic pathways and related genes may be involved in the decision-making process of anti-predator animal behavior by forming a network in addition to the tyrosine metabolic system, including dopamine, revealed in previous studies.

Conclusion

This volume on human migration has a biocultural and environmental emphasis. The chapters are arranged into five topical sections, including a theoretical overview of migration from recent African origins to Asia, Siberia, and the Americas; reconstruction of migration patterns based on ancient DNA; variation in regional movements of peoples from Africa, Siberia, the Americas, and the Caribbean; insights into patterns of migration as revealed by sociocultural observations and the use of qualitative and quantitative approaches in North Africa and Central and South America; and the spread of disease accompanying migrations. The diseases discussed are tuberculosis in Euro-Asia and arboviral infections at the United States–Mexican border....

Efficient Gene Editing Through an Intronic Selection Marker in Cells

Background Gene editing technology has provided researchers with the ability to modify genome sequences in almost all eukaryotes. Gene-edited cell lines are being used with increasing frequency in both bench research and targeted therapy. Despite the great importance and universality of gene editing, however, precision and efficiency are hard to achieve with the prevailing editing strategies, such as homology-directed DNA repair (HDR) and the use of base editors (BEs). Results & Discussion Our group has developed a novel gene editing technology to indicate DNA variation with an independent selection marker using an HDR strategy, which we named Gene Editing through an Intronic Selection marker (GEIS). GEIS uses a simple process to avoid nonhomologous end joining (NHEJ)-mediated false-positive effects and achieves editing efficiency as high as 91% without disturbing endogenous gene splicing and expression. We re-examined the correlation of the conversion tract and editing efficiency, and our data suggest that GEIS has the potential to edit approximately 99% of gene editing targets in human and mouse cells. The results of further comprehensive analysis suggest that the strategy may be useful for introducing multiple DNA variations in cells.

Whole-genome sequencing analysis of clozapine-induced myocarditis

One of the concerns limiting the use of clozapine in schizophrenia treatment is the risk of rare but potentially fatal myocarditis. Our previous genome-wide association study and human leucocyte antigen analyses identified putative loci associated with clozapine-induced myocarditis. However, the contribution of DNA variation in cytochrome P450 genes, copy number variants and rare deleterious variants have not been investigated. We explored these unexplored classes of DNA variation using whole-genome sequencing data from 25 cases with clozapine-induced myocarditis and 25 demographically-matched clozapine-tolerant control subjects. We identified 15 genes based on rare variant gene-burden analysis (MLLT6, CADPS, TACC2, L3MBTL4, NPY, SLC25A21, PARVB, GPR179, ACAD9, NOL8, C5orf33, FAM127A, AFDN, SLC6A11, PXDN) nominally associated (p<0.05) with clozapine-induced myocarditis. Of these genes, 13 were expressed in human myocardial tissue. Although independent replication of these findings is required, our study provides preliminary insights into the potential role of rare genetic variants in susceptibility to clozapine-induced myocarditis.

Mitochondrial DNA variation across 56,434 individuals in gnomAD

Databases of allele frequency are extremely helpful for evaluating clinical variants of unknown significance; however, until now, genetic databases such as the Genome Aggregation Database (gnomAD) have ignored the mitochondrial genome (mtDNA). Here we present a pipeline to call mtDNA variants that addresses three technical challenges: (i) detecting homoplasmic and heteroplasmic variants, present respectively in all or a fraction of mtDNA molecules, (ii) circular mtDNA genome, and (iii) misalignment of nuclear sequences of mitochondrial origin (NUMTs). We observed that mtDNA copy number per cell varied across gnomAD cohorts and influenced the fraction of NUMT-derived false-positive variant calls, which can account for the majority of putative heteroplasmies. To avoid false positives, we excluded samples prone to NUMT misalignment (few mtDNA copies per cell), cell line artifacts (many mtDNA copies per cell), or with contamination and we reported variants with heteroplasmy greater than 10%. We applied this pipeline to 56,434 whole genome sequences in the gnomAD v3.1 database that includes individuals of European (58%), African (25%), Latino (10%), and Asian (5%) ancestry. Our gnomAD v3.1 release contains population frequencies for 10,850 unique mtDNA variants at more than half of all mtDNA bases. Importantly, we report frequencies within each nuclear ancestral population and mitochondrial haplogroup. Homoplasmic variants account for most variant calls (98%) and unique variants (85%). We observed that 1/250 individuals carry a pathogenic mtDNA variant with heteroplasmy above 10%. These mitochondrial population allele frequencies are publicly available at gnomad.broadinstitute.org and will aid in diagnostic interpretation and research studies.

Mitochondrial DNA Variation in Peruvian Honey Bee (Apis mellifera L.) Populations Using the tRNAleu-cox2 Intergenic Region

Mitochondrial DNA variations of Peruvian honey bee populations were surveyed by using the tRNAleu-cox2 intergenic region. Only two studies have characterized these populations, indicating the presence of Africanized honey bee colonies in different regions of Peru and varied levels of Africanization, but the current status of its genetic diversity is unknown. A total of 512 honey bee colonies were sampled from three regions to characterize them. Our results revealed the presence of European and African haplotypes: the African haplotypes identified belong to sub-lineage AI (13) and sub-lineage AIII (03), and the European haplotypes to lineages C (06) and M (02). Of 24 haplotypes identified, 15 new sequences are reported here (11 sub-lineage AI, 2 sub-lineage AIII, and 2 lineage M). Peruvian honey bee populations presented a higher proportion from African than European haplotypes. High proportions of African haplotype were reported for Piura and Junín, unlike Lima, which showed more European haplotypes from lineage C. Few colonies belonging to lineage M would represent accidental purchase or traces of the introduction into Peru in the 19th century.

Review of eating disorders and oxytocin receptor polymorphisms

Background and aims Oxytocin, a nine amino acid peptide synthesised in the hypothalamus, has been widely recognised for its role in anxiolysis, bonding, sociality, and appetite. It binds to the oxytocin receptor (OXTR)—a G-protein coupled receptor—that is stimulated by the actions of oestrogen both peripherally and centrally. Studies have implicated OXTR genotypes in conferring either a risk or protective effect in autism, schizophrenia, and eating disorders (ED). There are numerous DNA variations of this receptor, with the most common DNA variation being in the form of the single nucleotide polymorphisms (SNPs). Two OXTR SNPs have been most studied in relation to ED: rs53576 and rs2254298. Each SNP has the same allelic variant that produces genotypes AA, AG, and GG. In this critical review we will evaluate the putative role of rs53576 and rs2254298 SNPs in ED. Additionally, this narrative review will consider the role of gene-environment interactions in the development of ED pathology. Findings The OXTR SNPs rs53576 and rs2254298 show independent associations between the A allele and restrictive eating behaviours. Conversely, the G allele of the OXTR rs53576 SNP is associated with binging behaviours, findings that were also evident in neuroanatomy. One study found the A allele of both OXTR SNPs to confer risk for more severe ED symptomatology while the G allele conferred some protective effect. An interaction between poor maternal care and rs2254298 AG/AA genotype conferred increased risk for binge eating and purging in women. Conclusions Individual OXTR SNP are unlikely in themselves to explain complex eating disorders but may affect the expression of and/or effectiveness of the OXTR. A growing body of G x E work is indicating that rs53576G homozygosity becomes disadvantageous for later mental health under early adverse conditions but further research to extend these findings to eating pathology is needed. The GWAS approach would benefit this area of knowledge.