Genome-wide scan of copy number variation in late-onset Alzheimer's disease.

Alzheimer's disease is a complex and progressive neurodegenerative disease leading to loss of memory, cognitive impairment, and ultimately death. To date, six large-scale genome-wide association studies have been conducted to identify SNPs that influence disease predisposition. These studies have confirmed the well-known APOE epsilon4 risk allele, identified a novel variant that influences disease risk within the APOE epsilon4 population, found a SNP that modifies the age of disease onset, as well as reported the first sex-linked susceptibility variant. Here we report a genome-wide scan of Alzheimer's disease in a set of 331 cases and 368 controls, extending analyses for the first time to include assessments of copy number variation. In this analysis, no new SNPs show genome-wide significance. We also screened for effects of copy number variation, and while nothing was significant, a duplication in CHRNA7 appears interesting enough to warrant further investigation.

Later Life Consequences of Developmental Mitochondrial DNA Damage in C. elegans

Mitochondria are responsible for producing the vast majority of cellular ATP, and are therefore critical to organismal health [1]. They contain thir own genomes (mtDNA) which encode 13 proteins that are all subunits of the mitochondrial respiratory chain (MRC) and are essential for oxidative phosphorylation [2]. mtDNA is present in multiple copies per cell, usually between 103 and 104 , though this number is reduced during certain developmental stages [3, 4]. The health of the mitochondrial genome is also important to the health of the organism, as mutations in mtDNA lead to human diseases that collectively affect approximately 1 in 4000 people [5, 6]. mtDNA is more susceptible than nuclear DNA (nucDNA) to damage by many environmental pollutants, for reasons including the absence of Nucleotide Excision Repair (NER) in the mitochondria [7]. NER is a highly functionally conserved DNA repair pathway that removes bulky, helix distorting lesions such as those caused by ultraviolet C (UVC) radiation and also many environmental toxicants, including benzo[a]pyrene (BaP) [8]. While these lesions cannot be repaired, they are slowly removed through a process that involves mitochondrial dynamics and autophagy [9, 10]. However, when present during development in C. elegans, this damage reduces mtDNA copy number and ATP levels [11]. We hypothesize that this damage, when present during development, will result in mitochondrial dysfunction and increase the potential for adverse outcomes later in life.

To test this hypothesis, 1st larval stage (L1) C. elegans are exposed to 3 doses of 7.5J/m2 ultraviolet C radiation 24 hours apart, leading to the accumulation of mtDNA damage [9, 11]. After exposure, many mitochondrial endpoints are assessed at multiple time points later in life. mtDNA and nucDNA damage levels and genome copy numbers are measured via QPCR and real-time PCR , respectively, every 2 day for 10 days. Steady state ATP levels are measured via luciferase expressing reporter strains and traditional ATP extraction methods. Oxygen consumption is measured using a Seahorse XFe24 extra cellular flux analyzer. Gene expression changes are measured via real time PCR and targeted metabolomics via LC-MS are used to investigate changes in organic acid, amino acid and acyl-carnitine levels. Lastly, nematode developmental delay is assessed as growth, and measured via imaging and COPAS biosort.

I have found that despite being removed, UVC induced mtDNA damage during development leads to persistent deficits in energy production later in life. mtDNA copy number is permanently reduced, as are ATP levels, though oxygen consumption is increased, indicating inefficient or uncoupled respiration. Metabolomic data and mutant sensitivity indicate a role for NADPH and oxidative stress in these results, and exposed nematodes are more sensitive to the mitochondrial poison rotenone later in life. These results fit with the developmental origin of health and disease hypothesis, and show the potential for environmental exposures to have lasting effects on mitochondrial function.

Lastly, we are currently working to investigate the potential for irreparable mtDNA lesions to drive mutagenesis in mtDNA. Mutations in mtDNA lead to a wide range of diseases, yet we currently do not understand the environmental component of what causes them. In vitro evidence suggests that UVC induced thymine dimers can be mutagenic [12]. We are using duplex sequencing of C. elegans mtDNA to determine mutation rates in nematodes exposed to our serial UVC protocol. Furthermore, by including mutant strains deficient in mitochondrial fission and mitophagy, we hope to determine if deficiencies in these processes will further increase mtDNA mutation rates, as they are implicated in human diseases.

Comparative analyses of seven algorithms for copy number variant identification from single nucleotide polymorphism arrays.

Determination of copy number variants (CNVs) inferred in genome wide single nucleotide polymorphism arrays has shown increasing utility in genetic variant disease associations. Several CNV detection methods are available, but differences in CNV call thresholds and characteristics exist. We evaluated the relative performance of seven methods: circular binary segmentation, CNVFinder, cnvPartition, gain and loss of DNA, Nexus algorithms, PennCNV and QuantiSNP. Tested data included real and simulated Illumina HumHap 550 data from the Singapore cohort study of the risk factors for Myopia (SCORM) and simulated data from Affymetrix 6.0 and platform-independent distributions. The normalized singleton ratio (NSR) is proposed as a metric for parameter optimization before enacting full analysis. We used 10 SCORM samples for optimizing parameter settings for each method and then evaluated method performance at optimal parameters using 100 SCORM samples. The statistical power, false positive rates, and receiver operating characteristic (ROC) curve residuals were evaluated by simulation studies. Optimal parameters, as determined by NSR and ROC curve residuals, were consistent across datasets. QuantiSNP outperformed other methods based on ROC curve residuals over most datasets. Nexus Rank and SNPRank have low specificity and high power. Nexus Rank calls oversized CNVs. PennCNV detects one of the fewest numbers of CNVs.

The evolutionary history of ferns inferred from 25 low-copy nuclear genes.

UNLABELLED: • PREMISE OF THE STUDY: Understanding fern (monilophyte) phylogeny and its evolutionary timescale is critical for broad investigations of the evolution of land plants, and for providing the point of comparison necessary for studying the evolution of the fern sister group, seed plants. Molecular phylogenetic investigations have revolutionized our understanding of fern phylogeny, however, to date, these studies have relied almost exclusively on plastid data.• METHODS: Here we take a curated phylogenomics approach to infer the first broad fern phylogeny from multiple nuclear loci, by combining broad taxon sampling (73 ferns and 12 outgroup species) with focused character sampling (25 loci comprising 35877 bp), along with rigorous alignment, orthology inference and model selection.• KEY RESULTS: Our phylogeny corroborates some earlier inferences and provides novel insights; in particular, we find strong support for Equisetales as sister to the rest of ferns, Marattiales as sister to leptosporangiate ferns, and Dennstaedtiaceae as sister to the eupolypods. Our divergence-time analyses reveal that divergences among the extant fern orders all occurred prior to ∼200 MYA. Finally, our species-tree inferences are congruent with analyses of concatenated data, but generally with lower support. Those cases where species-tree support values are higher than expected involve relationships that have been supported by smaller plastid datasets, suggesting that deep coalescence may be reducing support from the concatenated nuclear data.• CONCLUSIONS: Our study demonstrates the utility of a curated phylogenomics approach to inferring fern phylogeny, and highlights the need to consider underlying data characteristics, along with data quantity, in phylogenetic studies.