Characterization of the complete mitochondrial genome of Ergasilus anchoratus Markevich, 1946 (Ergasilidae) and phylogeny of Copepoda.

The mitochondrial (mt) genome can provide data for phylogenetic analyses and evolutionary biology. Herein, we sequenced and annotated the complete mt genome of Ergasilus anchoratus. This mt genome was 13852 bp long and comprised 13 protein-coding genes (PCGs), 22 tRNAs and 2 rRNAs. All PCGs used the standard ATN start codons and complete TAA/TAG termination codons. A majority of tRNA genes exhibited standard cloverleaf secondary structures, with the exception of one tRNA that lacked the TψC arm (trnC), and three tRNAs that lacked the DHU arm (trnR, trnS1 and trnS2). Phylogenetic analyses conducted using Bayesian inference (BI) and maximum likelihood (ML) methods both supported Ergasilidae as a monophyletic family forming a sister group to Lernaea cyprinacea and Paracyclopina nana. It also supported the monophyly of orders Calanoida, Cyclopoida, and Siphonostomatoida; and the monophyly of families Harpacticidae, Ergasilidae, Diaptomidae, and Calanidae. The gene orders of E. anchoratus and Sinergasilus undulatus were identical, which represents the first instance of two identical gene orders in copepods. More mt genomes are needed to better understand the phylogenetic relationships within Copepoda in the future.

A novel scatterplot-based method to detect copy number variation (CNV).

Objective: Most methods to detect copy number variation (CNV) have high false positive rates, especially for small CNVs and in real-life samples from clinical studies. In this study, we explored a novel scatterplot-based method to detect CNVs in microarray samples. Methods: Illumina SNP microarray data from 13,254 individuals were analyzed with scatterplots and by PennCNV. The data were analyzed without the prior exclusion of low-quality samples. For CNV scatterplot visualization, the median signal intensity of all SNPs located within a CNV region was plotted against the median signal intensity of the flanking genomic region. Since CNV causes loss or gain of signal intensities, carriers of different CNV alleles pop up in clusters. Moreover, SNPs within a deletion are not heterozygous, whereas heterozygous SNPs within a duplication show typical 1:2 signal distribution between the alleles. Scatterplot-based CNV calls were compared with standard results of PennCNV analysis. All discordant calls as well as a random selection of 100 concordant calls were individually analyzed by visual inspection after noise-reduction. Results: An algorithm for the automated scatterplot visualization of CNVs was developed and used to analyze six known CNV regions. Use of scatterplots and PennCNV yielded 1019 concordant and 108 discordant CNV calls. All concordant calls were evaluated as true CNV-findings. Among the 108 discordant calls, 7 were false positive findings by the scatterplot method, 80 were PennCNV false positives, and 21 were true CNVs detected by the scatterplot method, but missed by PennCNV (i.e., false negative findings). Conclusion: CNV visualization by scatterplots allows for a reliable and rapid detection of CNVs in large studies. This novel method may thus be used both to confirm the results of genome-wide CNV detection software and to identify known CNVs in hitherto untyped samples.

Genetic Variation in LRP1 Associates with Stanford Type B Aortic Dissection Risk and Clinical Outcome.

Genetic variation in LRP1 (low-density lipoprotein receptor-related protein 1) was reported to be associated with thoracic aortic dissections and aneurysms. The aims of this study were to confirm this association in a prospective single-center patient cohort of patients with acute Stanford type B aortic dissections (STBAD) and to assess the impact of LRP1 variation on clinical outcome. The single nucleotide variation (SNV) rs11172113 within the LRP1 gene was genotyped in 113 STBAD patients and 768 healthy control subjects from the same population. The T-allele of rs11172113 was more common in STBAD patients as compared to the reference group (72.6% vs. 59.6%) and confirmed to be an independent risk factor for STBAD (p = 0.002) after sex and age adjustment in a logistic regression model analyzing diabetes, smoking and hypertension as additional risk factors. Analysis of clinical follow-up (median follow-up 2.0 years) revealed that patients with the T-allele were more likely to suffer aorta-related complications (T-allele 75.6% vs. 63.8%; p = 0.022). In this study sample of STBAD patients, variation in LRP1 was an independent risk factor for STBAD and affected clinical outcome.

Multiple Arterial Dissections and Connective Tissue Abnormalities.

BACKGROUND: Although patients with multiple arterial dissections in distinct arterial regions rarely present with known connective tissue syndromes, we hypothesized that mild connective tissue abnormalities are common findings in these patients. METHODS: From a consecutive register of 322 patients with cervical artery dissection (CeAD), we identified and analyzed 4 patients with a history of additional dissections in other vascular beds. In three patients, dermal connective tissue was examined by electron microscopy. DNA from all four patients was studied by whole-exome sequencing and copy number variation (CNV) analysis. RESULTS: The collagen fibers of dermal biopsies were pathologic in all three analyzed patients. One patient carried a CNV disrupting the COL3A1 and COL5A2 genes (vascular or hypermobility type of Ehlers-Danlos syndrome), and another patient a CNV in MYH11 (familial thoracic aortic aneurysms and dissections). The third patient carried a missense substitution in COL5A2. CONCLUSION: Three patients showed morphologic alterations of the dermal connective tissue, and two patients carried pathogenic variants in genes associated with arterial connective tissue dysfunction. The findings suggest that genetic testing should be recommended after recurrent arterial dissections, independently of apparent phenotypical signs of connective tissue disorders.