Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer.

In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/TNS3, P = 4.35 × 10-8). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PANDoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 × 10-14), rs2941471 at 8q21.11 (HNF4G, P = 6.60 × 10-10), rs4795218 at 17q12 (HNF1B, P = 1.32 × 10-8), and rs1517037 at 18q21.32 (GRP, P = 3.28 × 10-8). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene

Gal3

In this zip folder are the gal3 images used to generate the data in the paper, in Zeiss lsm format. They are sorted into folders and subfolders by genotype, and named according to the date taken. The Zeiss lsm format has other metadata (voxel size, image size, etc) associated with it. The files were analyzed using Matlab code available on the Reeveslab website

Data from: Analyzing negative feedback using a synthetic gene network expressed in the Drosophila melanogaster embryo

Background: A complex network of gene interactions controls gene regulation throughout development and the life of the organisms. Insights can be made into these processes by studying the functional interactions (or “motifs”) which make up these networks. Results: We sought to understand the functionality of one of these network motifs, negative feedback, in a multi-cellular system. This was accomplished using a synthetic network expressed in the Drosophila melanogaster embryo using the yeast proteins Gal4 (a transcriptional activator) and Gal80 (an inhibitor of Gal4 activity). This network is able to produce an attenuation or shuttling phenotype depending on the Gal80/Gal4 ratio. This shuttling behavior was validated by expressing Gal3, which inhibits Gal80, to produce a localized increase in free Gal4 and therefore signaling. Mathematical modeling was used to demonstrate the capacity for negative feedback to produce these varying outputs. Conclusions: The capacity of a network motif to exhibit different phenotypes due to minor changes to the network in multi-cellular systems was shown. This work demonstrates the importance of studying network motifs in multi-cellular systems

Gal4x2

In this zip folder are the gal4x2 images used to generate the data in the paper, in Zeiss lsm format. They are sorted into folders and subfolders by genotype, and named according to the date taken. The Zeiss lsm format has other metadata (voxel size, image size, etc) associated with it. The files were analyzed using Matlab code available on the Reeveslab website

Additional file 1: of Analyzing negative feedback using a synthetic gene network expressed in the Drosophila melanogaster embryo

Supplemental figures and model equations. (DOCX 12250 kb

Gal4x4

In this zip folder are the gal4x4 images used to generate the data in the paper, in Zeiss lsm format. They are sorted into folders and subfolders by genotype, and named according to the date taken. The Zeiss lsm format has other metadata (voxel size, image size, etc) associated with it. The files were analyzed using Matlab code available on the Reeveslab website

Tunable self-cleaving ribozymes for modulating gene expression in eukaryotic systems.

Advancements in the field of synthetic biology have been possible due to the development of genetic tools that are able to regulate gene expression. However, the current toolbox of gene regulatory tools for eukaryotic systems have been outpaced by those developed for simple, single-celled systems. Here, we engineered a set of gene regulatory tools by combining self-cleaving ribozymes with various upstream competing sequences that were designed to disrupt ribozyme self-cleavage. As a proof-of-concept, we were able to modulate GFP expression in mammalian cells, and then showed the feasibility of these tools in Drosophila embryos. For each system, the fold-reduction of gene expression was influenced by the location of the self-cleaving ribozyme/upstream competing sequence (i.e. 5' vs. 3' untranslated region) and the competing sequence used. Together, this work provides a set of genetic tools that can be used to tune gene expression across various eukaryotic systems