Johnny Cruz Corchado and Katie Weihbrecht Present their Research on 9-12-16
Predictive Models of Recombination Rate Variation across the Drosophila melanogaster Genome
Andrew B. Adrian1,†, Johnny Cruz Corchado2,† and Josep M. Comeron1,2,*
In all eukaryotic species examined, meiotic recombination, and crossovers in particular, occur non‐randomly along chromosomes. The cause for this non-random distribution remains poorly understood but some specific DNA sequence motifs have been shown to be enriched near crossover hotspots in a number of species. We present analyses using machine learning algorithms to investigate whether DNA motif distribution across the genome can be used to predict crossover variation in Drosophila melanogaster, a species without hotspots. Our study exposes a combinatorial non-linear influence of motif presence able to account for a significant fraction of the genome-wide variation in crossover rates at all genomic scales investigated, from 20% at 5-kb to almost 70% at 2,500-kb scale. The models are particularly predictive for regions with the highest and lowest crossover rates and remain highly informative after removing sub-telomeric and -centromeric regions known to have strongly reduced crossover rates. Transcriptional activity during early meiosis and differences in motif use between autosomes and the X chromosome add to the predictive power of the models. Moreover, we show that population-specific differences in crossover rates can be partly explained by differences in motif presence. Our results suggest that crossover distribution in Drosophila is influenced by both meiosis-specific chromatin dynamics and very local constitutive open chromatin associated with DNA motifs that prevent nucleosome stabilization. These findings provide new information on the genetic factors influencing variation in recombination rates and a baseline to study epigenetic mechanisms responsible for plastic recombination as response to different biotic and abiotic conditions and stresses.
NPHP10 affects AIMP2 localization and alters its downstream target, p53
Bardet-Biedl Syndrome (BBS) is an autosomal recessive, pleiotropic disorder, with 21 genes currently identified as causative. One of these genes is serologically defined colon cancer antigen 8 (NPHP10 [MIM 613524]), a nephronophthisis-related ciliopathy gene (NPHP10 or BBS16). Patients with mutations in this gene exhibit retinal and renal abnormalities, obesity, and learning disabilities. Currently, little is known about the molecular functions of NPHP10 and how loss of NPHP10 function leads to the observed phenotypes. Our previous work identified strong interactors of NPHP10, consisting mainly of components of the multi-aminoacyl tRNA synthetase complex (MSC). More specifically, 8 out of 9 aminoacyl tRNA synthetases (ARS) as well as aminoacyl-tRNA-synthetase-complex interacting multifunctional protein 2 (AIMP2) interact with NPHP10. We also determined that among the MSC components, NPHP10 directly interacts with AIMP2. AIMP2 has a known non-canonical role in the apoptotic pathway via p53 activation. In response to DNA damage, a subset of AIMP2 localizes to the nucleus and binds to and prevents the ubiquitination of p53. This leads to an upregulation of apoptosis in response to DNA damage. Recently, we developed two NPHP10 knockout IMCD3 cell lines using CRISPR-mediated technology. Using these cell lines, we examined the effect of NPHP10 loss on AIMP2 localization in these cells. Immunofluorescence microscopy and cell fractionation with immunoblotting show that loss of NPHP10 leads to increased AIMP2 in the nucleus of cells. Additionally, we showed that overall p53 levels increased in knock-out cells. Further work focuses on how these changes affect downstream elements of p53 utilizing a luciferase reporter assay.