Mark T. W. Ebbert

DNA reference alignment benchmarks based on tertiary structure of encoded proteins

MOTIVATION Multiple sequence alignments (MSAs) are at the heart of bioinformatics analysis. Recently, a number of multiple protein sequence alignment benchmarks (i.e. BAliBASE, OXBench, PREFAB and SMART) have been released to evaluate new and existing MSA applications. These databases have been well received by researchers and help to quantitatively evaluate MSA programs on protein sequences. Unfortunately, analogous DNA benchmarks are not available, making evaluation of MSA programs difficult for DNA sequences. RESULTS This work presents the first known multiple DNA sequence alignment benchmarks that are (1) comprised of protein-coding portions of DNA (2) based on biological features such as the tertiary structure of encoded proteins. These reference DNA databases contain a total of 3545 alignments, comprising of 68 581 sequences. Two versions of the database are available: mdsa_100s and mdsa_all. The mdsa_100s version contains the alignments of the data sets that TBLASTN found 100% sequence identity for each sequence. The mdsa_all version includes all hits with an E-value score above the threshold of 0.001. A primary use of these databases is to benchmark the performance of MSA applications on DNA data sets. The first such case study is included in the Supplementary Material.

Genetics of Alzheimer’s Disease

Alzheimers disease is the most common form of dementia and is the only top 10 cause of death in the United States that lacks disease-altering treatments. It is a complex disorder with environmental and genetic components. There are two major types of Alzheimers disease, early onset and the more common late onset. The genetics of early-onset Alzheimers disease are largely understood with variants in three different genes leading to disease. In contrast, while several common alleles associated with late-onset Alzheimers disease, including APOE, have been identified using association studies, the genetics of late-onset Alzheimers disease are not fully understood. Here we review the known genetics of early- and late-onset Alzheimers disease.

Population-based analysis of Alzheimer's disease risk alleles implicates genetic interactions.

BACKGROUND Reported odds ratios and population attributable fractions (PAF) for late-onset Alzheimers disease (LOAD) risk loci (BIN1, ABCA7, CR1, MS4A4E, CD2AP, PICALM, MS4A6A, CD33, and CLU) come from clinically ascertained samples. Little is known about the combined PAF for these LOAD risk alleles and the utility of these combined markers for case-control prediction. Here we evaluate these loci in a large population-based sample to estimate PAF and explore the effects of additive and nonadditive interactions on LOAD status prediction performance. METHODS 2419 samples from the Cache County Memory Study were genotyped for APOE and nine LOAD risk loci from AlzGene.org. We used logistic regression and receiver operator characteristic analysis to assess the LOAD status prediction performance of these loci using additive and nonadditive models and compared odds ratios and PAFs between AlzGene.org and Cache County. RESULTS Odds ratios were comparable between Cache County and AlzGene.org when identical single nucleotide polymorphisms were genotyped. PAFs from AlzGene.org ranged from 2.25% to 37%; those from Cache County ranged from .05% to 20%. Including non-APOE alleles significantly improved LOAD status prediction performance (area under the curve = .80) over APOE alone (area under the curve = .78) when not constrained to an additive relationship (p < .03). We identified potential allelic interactions (p values uncorrected): CD33-MS4A4E (synergy factor = 5.31; p < .003) and CLU-MS4A4E (synergy factor = 3.81; p < .016). CONCLUSIONS Although nonadditive interactions between loci significantly improve diagnostic ability, the improvement does not reach the desired sensitivity or specificity for clinical use. Nevertheless, these results suggest that understanding gene-gene interactions may be important in resolving Alzheimers disease etiology.

Evolutionary Pressure on Mitochondrial Cytochrome b Is Consistent with a Role of CytbI7T Affecting Longevity during Caloric Restriction

Background Metabolism of energy nutrients by the mitochondrial electron transport chain (ETC) is implicated in the aging process. Polymorphisms in core ETC proteins may have an effect on longevity. Here we investigate the cytochrome b (cytb) polymorphism at amino acid 7 (cytbI7T) that distinguishes human mitochondrial haplogroup H from haplogroup U. Principal Findings We compared longevity of individuals in these two haplogroups during historical extremes of caloric intake. Haplogroup H exhibits significantly increased longevity during historical caloric restriction compared to haplogroup U (p = 0.02) while during caloric abundance they are not different. The historical effects of natural selection on the cytb protein were estimated with the software TreeSAAP using a phylogenetic reconstruction for 107 mammal taxa from all major mammalian lineages using 13 complete protein-coding mitochondrial gene sequences. With this framework, we compared the biochemical shifts produced by cytbI7T with historical evolutionary pressure on and near this polymorphic site throughout mammalian evolution to characterize the role cytbI7T had on the ETC during times of restricted caloric intake. Significance Our results suggest the relationship between caloric restriction and increased longevity in human mitochondrial haplogroup H is determined by cytbI7T which likely enhances the ability of water to replenish the Qi binding site and decreases the time ubisemiquinone is at the Qo site, resulting in a decrease in the average production rate of radical oxygen species (ROS).

Repetitive element transcripts are elevated in the brain of C9orf72 ALS/FTLD patients

Abstract Significant transcriptome alterations are detected in the brain of patients with amyotrophic lateral sclerosis (ALS), including carriers of the C9orf72 repeat expansion and C9orf72-negative sporadic cases. Recently, the expression of repetitive element transcripts has been associated with toxicity and, while increased repetitive element expression has been observed in several neurodegenerative diseases, little is known about their contribution to ALS. To assess whether aberrant expression of repetitive element sequences are observed in ALS, we analysed RNA sequencing data from C9orf72-positive and sporadic ALS cases, as well as healthy controls. Transcripts from multiple classes and subclasses of repetitive elements (LINEs, endogenous retroviruses, DNA transposons, simple repeats, etc.) were significantly increased in the frontal cortex of C9orf72 ALS patients. A large collection of patient samples, representing both C9orf72 positive and negative ALS, ALS/FTLD, and FTLD cases, was used to validate the levels of several repetitive element transcripts. These analyses confirmed that repetitive element expression was significantly increased in C9orf72-positive compared to C9orf72-negative or control cases. While previous studies suggest an important link between TDP-43 and repetitive element biology, our data indicate that TDP-43 pathology alone is insufficient to account for the observed changes in repetitive elements in ALS/FTLD. Instead, we found that repetitive element expression positively correlated with RNA polymerase II activity in postmortem brain, and pharmacologic modulation of RNA polymerase II activity altered repetitive element expression in vitro. We conclude that increased RNA polymerase II activity in ALS/FTLD may lead to increased repetitive element transcript expression, a novel pathological feature of ALS/FTLD.

Interaction between variants in CLU and MS4A4E modulates Alzheimer's disease risk

Ebbert et al. reported gene‐gene interactions between rs11136000‐rs670139 (CLU‐MS4A4E) and rs3865444‐rs670139 (CD33‐MS4A4E). We evaluate these interactions in the largest data set for an epistasis study.

Bridging the gap between statistical and biological epistasis in Alzheimer's disease.

Alzheimers disease affects millions of people worldwide and incidence is expected to rise as the population ages, but no effective therapies exist despite decades of research and more than 20 known disease markers. Research has shown that Alzheimers diseases missing heritability remains extensive with an estimated 25% of phenotypic variance unexplained by known variants. The missing heritability may be explained by missing variants or by epistasis. Researchers often focus on individual loci rather than epistatic interactions, which is likely an oversimplification of the underlying biology since most phenotypes are affected by multiple genes. Focusing research efforts on epistasis will be critical to resolving Alzheimers disease etiology, and a major key to identifying and properly interpreting key epistatic interactions will be bridging the gap between statistical and biological epistasis. This review covers the current state of epistasis research in Alzheimers disease and how researchers can bridge the gap between statistical and biological epistasis to help resolve Alzheimers disease etiology.

Variant Tool Chest: an improved tool to analyze and manipulate variant call format (VCF) files

BackgroundSince the advent of next-generation sequencing many previously untestable hypotheses have been realized. Next-generation sequencing has been used for a wide range of studies in diverse fields such as population and medical genetics, phylogenetics, microbiology, and others. However, this novel technology has created unanticipated challenges such as the large numbers of genetic variants. Each caucasian genome has more than four million single nucleotide variants, insertions and deletions, copy number variants, and structural variants. Several formats have been suggested for storing these variants; however, the variant call format (VCF) has become the community standard.ResultsWe developed new software called the Variant Tool Chest (VTC) to provide much needed tools to work with VCF files. VTC provides a variety of tools for manipulating, comparing, and analyzing VCF files beyond the functionality of existing tools. In addition, VTC was written to be easily extended with new tools.ConclusionsVariant Tool Chest brings new and important functionality that complements and integrates well with existing software. VTC is available at https://github.com/mebbert/VariantToolChest

Application of a new informatics tool for contamination screening in the HIV sequencing laboratory.

BACKGROUND Current HIV-1 sequencing-based methods for detecting drug resistance-associated mutations are open and susceptible to contamination. Informatic identification of clinical sequences that are nearly identical to one another may indicate specimen-to-specimen contamination or another laboratory-associated issue. OBJECTIVES To design an informatic tool to rapidly identify potential contamination in the clinical laboratory using sequence analysis and to establish reference ranges for sequence variation in the HIV-1 protease and reverse transcriptase regions among a U.S. patient population. STUDY DESIGN We developed an open-source tool named HIV Contamination Detection (HIVCD). HIVCD was utilized to make pairwise comparisons of nearly 8000 partial HIV-1 pol gene sequences from patients across the United States and to calculate percent identities (PIDs) for each pair. ROC analysis and standard deviations of PID data were used to determine reference ranges for between-patient and within-patient comparisons and to guide selection of a threshold for identifying abnormally high PID between two unrelated sequences. RESULTS The PID reference range for between-patient comparisons ranged from 83.8 to 95.7% while within-patient comparisons ranged from 96 to 100%. Interestingly, 48% of between-patient sequence pairs with a PID>96.5 were geographically related. The selected threshold for abnormally high PIDs was 96 (AUC=0.993, sensitivity=0.980, specificity=0.999). During routine use, HIVCD identified a specimen mix-up and the source of contamination of a negative control. CONCLUSIONS In our experience, HIVCD is easily incorporated into laboratory workflow, useful for identifying potential laboratory errors, and contributes to quality testing. This type of analysis should be incorporated into routine laboratory practice.

Poly(GR) impairs protein translation and stress granule dynamics in C9orf72 -associated frontotemporal dementia and amyotrophic lateral sclerosis

The major genetic cause of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) is a C9orf72 G4C2 repeat expansion1,2. Proposed mechanisms by which the expansion causes c9FTD/ALS include toxicity from repeat-containing RNA and from dipeptide repeat proteins translated from these transcripts. To investigate the contribution of poly(GR) dipeptide repeat proteins to c9FTD/ALS pathogenesis in a mammalian in vivo model, we generated mice that expressed GFP–(GR)100 in the brain. GFP–(GR)100 mice developed age-dependent neurodegeneration, brain atrophy, and motor and memory deficits through the accumulation of diffuse, cytoplasmic poly(GR). Poly(GR) co-localized with ribosomal subunits and the translation initiation factor eIF3η in GFP–(GR)100 mice and, of importance, in c9FTD/ALS patients. Combined with the differential expression of ribosome-associated genes in GFP–(GR)100 mice, these findings demonstrate poly(GR)-mediated ribosomal distress. Indeed, poly(GR) inhibited canonical and non-canonical protein translation in HEK293T cells, and also induced the formation of stress granules and delayed their disassembly. These data suggest that poly(GR) contributes to c9FTD/ALS by impairing protein translation and stress granule dynamics, consequently causing chronic cellular stress and preventing cells from mounting an effective stress response. Decreasing poly(GR) and/or interrupting interactions between poly(GR) and ribosomal and stress granule-associated proteins may thus represent potential therapeutic strategies to restore homeostasis.ALS/FTD-related C9orf72 dipeptide-repeat proteins inhibit protein translation and impair stress granule dynamics, and they cause motor and cognitive deficits in mice.