cd1 Mutation in Drosophila Affects Phenoxazinone Synthase Catalytic Site and Impairs Long-Term Memory

Being involved in development of Huntington’s, Parkinson’s and Alzheimer’s diseases, kynurenine pathway (KP) of tryptophan metabolism plays a significant role in modulation of neuropathology. Accumulation of a prooxidant 3-hydroxykynurenine (3-HOK) leads to oxidative stress and neuronal cell apoptosis. Drosophila mutant cardinal (cd1) with 3-HOK excess shows age-dependent neurodegeneration and short-term memory impairments, thereby presenting a model for senile dementia. Although cd gene for phenoxazinone synthase (PHS) catalyzing 3-HOK dimerization has been presumed to harbor the cd1 mutation, its molecular nature remained obscure. Using next generation sequencing, we have shown that the cd gene in cd1 carries a long deletion leading to PHS active site destruction. Contrary to the wild type Canton-S (CS), cd1 males showed defective long-term memory (LTM) in conditioned courtship suppression paradigm (CCSP) at days 5–29 after eclosion. The number of dopaminergic neurons (DAN) regulating fly locomotor activity showed an age-dependent tendency to decrease in cd1 relative to CS. Thus, in accordance with the concept “from the gene to behavior” proclaimed by S. Benzer, we have shown that the aberrant PHS sequence in cd1 provokes drastic LTM impairments and DAN alterations

Chromatin Structure and “DNA Sequence View”: The Role of Satellite DNA in Ectopic Pairing of the Drosophila X Polytene Chromosome

Chromatin 3D structure plays a crucial role in regulation of gene activity. Previous studies have envisioned spatial contact formations between chromatin domains with different epigenetic properties, protein compositions and transcription activity. This leaves specific DNA sequences that affect chromosome interactions. The Drosophila melanogaster polytene chromosomes are involved in non-allelic ectopic pairing. The mutant strain agnts3, a Drosophila model for Williams–Beuren syndrome, has an increased frequency of ectopic contacts (FEC) compared to the wild-type strain Canton-S (CS). Ectopic pairing can be mediated by some specific DNA sequences. In this study, using our Homology Segment Analysis software, we estimated the correlation between FEC and frequency of short matching DNA fragments (FMF) for all sections of the X chromosome of Drosophila CS and agnts3 strains. With fragment lengths of 50 nucleotides (nt), CS showed a specific FEC–FMF correlation for 20% of the sections involved in ectopic contacts. The correlation was unspecific in agnts3, which may indicate the alternative epigenetic mechanisms affecting FEC in the mutant strain. Most of the fragments that specifically contributed to FMF were related to 1.688 or 372-bp middle repeats. Thus, middle repetitive DNA may serve as an organizer of ectopic pairing

Prioritisation of structural variant calls in cancer genomes

Sensitivity of short read DNA-sequencing for gene fusion detection is improving, but is hampered by the significant amount of noise composed of uninteresting or false positive hits in the data. In this paper we describe a tiered prioritisation approach to extract high impact gene fusion events from existing structural variant calls. Using cell line and patient DNA sequence data we improve the annotation and interpretation of structural variant calls to best highlight likely cancer driving fusions. We also considerably improve on the automated visualisation of the high impact structural variants to highlight the effects of the variants on the resulting transcripts. The resulting framework greatly improves on readily detecting clinically actionable structural variants

Distributed under Creative Commons CC-BY 4.0 Prioritisation of structural variant calls in cancer genomes

ABSTRACT Sensitivity of short read DNA-sequencing for gene fusion detection is improving, but is hampered by the significant amount of noise composed of uninteresting or false positive hits in the data. In this paper we describe a tiered prioritisation approach to extract high impact gene fusion events from existing structural variant calls. Using cell line and patient DNA sequence data we improve the annotation and interpretation of structural variant calls to best highlight likely cancer driving fusions. We also considerably improve on the automated visualisation of the high impact structural variants to highlight the effects of the variants on the resulting transcripts. The resulting framework greatly improves on readily detecting clinically actionable structural variants