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Condition‐dependent genetic interactions can reveal functional relationships between genes that are not evident under standard culture conditions. State‐of‐the‐art yeast genetic interaction mapping, which relies on robotic manipulation of arrays of double‐mutant strains, does not scale readily to multi‐condition studies. Here, we describe barcode fusion genetics to map genetic interactions (BFG‐GI), by which double‐mutant strains generated via en masse “party” mating can also be monitored en masse for growth to detect genetic interactions. By using site‐specific recombination to fuse two DNA barcodes, each representing a specific gene deletion, BFG‐GI enables multiplexed quantitative tracking of double mutants via next‐generation sequencing. We applied BFG‐GI to a matrix of DNA repair genes under nine different conditions, including methyl methanesulfonate (MMS), 4‐nitroquinoline 1‐oxide (4NQO), bleomycin, zeocin, and three other DNA‐damaging environments. BFG‐GI recapitulated known genetic interactions and yielded new condition‐dependent genetic interactions. We validated and further explored a subnetwork of condition‐dependent genetic interactions involving MAG1 , SLX4, and genes encoding the Shu complex, and inferred that loss of the Shu complex leads to an increase in the activation of the checkpoint protein kinase Rad53. Synopsis A new method, Barcode Fusion Genetics to Map Genetic Interactions (BFG‐GI) allows generating double mutants and measuring condition‐dependent genetic interactions en masse . Application of BFG‐GI to DNA repair genes reveals a new function for the Shu complex. BFG‐GI involves generating double‐mutant‐specific fused barcodes, enabling to measure the abundance of double mutants en masse by next generation sequencing. Once a double mutant BFG‐GI pool has been generated genetic interactions can be tested in new growth conditions. BFG‐GI is applied to 26 genes related to DNA damage repair in nine different conditions, including seven DNA‐damaging agents. A novel relationship is reported between the Shu complex and the checkpoint protein kinase Rad53. Graphical Abstract A new method, Barcode Fusion Genetics to Map Genetic Interactions (BFG‐GI) allows generating double mutants and measuring condition‐dependent genetic interactions en masse . Application of BFG‐GI to DNA repair genes reveals a new function for the Shu complex.

The genetic background of an organism can influence the overall effects of new genetic variants. Some mutations can amplify a deleterious phenotype, whereas others can suppress it. Starting with a literature survey and expanding into a genomewide assay, van Leeuwen et al. generated a large-scale suppression network in yeast. The data set reveals a set of general properties that can be used to predict suppression interactions. Furthermore, the study provides a template for extending suppression studies to other genes or to more complex organisms. Science , this issue p. 599 A large-scale study in yeast reveals how defects associated with a mutation in one gene can be compensated for by a second mutation in a suppressor gene. Genetic suppression occurs when the phenotypic defects caused by a mutation in a particular gene are rescued by a mutation in a second gene. To explore the principles of genetic suppression, we examined both literature-curated and unbiased experimental data, involving systematic genetic mapping and whole-genome sequencing, to generate a large-scale suppression network among yeast genes. Most suppression pairs identified novel relationships among functionally related genes, providing new insights into the functional wiring diagram of the cell. In addition to suppressor mutations, we identified frequent secondary mutations,in a subset of genes, that likely cause a delay in the onset of stationary phase, which appears to promote their enrichment within a propagating population. These findings allow us to formulate and quantify general mechanisms of genetic suppression.

GABA and GABA type A receptor (GABAAR) are expressed in pancreatic β-cells and comprise an autocrine signaling system. How the GABA-GABAAR system is regulated is unknown. In this study, I investigated insulin's effect on this system in the INS-1 β-cell line. I found that GABA evoked current (IGABA) in INS-1 cells, resulting in membrane depolarization. Perforated-patch recordings showed that pre-treatment of insulin or zinc-free insulin suppressed IGABA in INS-1 cells (p < 0.01). Radioimmunossay showed that GABA (30 μM) increased C-peptide secretion from INS-1 cells, which was blocked by GABAAR antagonist picrotoxin, indicating that GABA increased insulin secretion through activation of GABAAR. However, insulin significantly reduced the stimulatory effect of GABA on C-peptide secretion (p < 0.05). These data suggest that GABA released from β-cells positively regulates insulin secretion via GABAAR activation, and that insulin negatively regulates the β-cell secretory pathway likely via inhibiting the GABA-GABA AR system in β-cells.

Condition-dependent genetic interactions can reveal functional relationships between genes that are not evident under standard culture conditions. State-of-the-art yeast genetic interaction mapping, which relies on robotic manipulation of arrays of double mutant strains, does not scale readily to multi-condition studies. Here we describe Barcode Fusion Genetics to map Genetic Interactions (BFG-GI), by which double mutant strains generated via en masse party mating can also be monitored en masse for growth and genetic interactions. By using site-specific recombination to fuse two DNA barcodes, each representing a specific gene deletion, BFG-GI enables multiplexed quantitative tracking of double mutants via next-generation sequencing. We applied BFG-GI to a matrix of DNA repair genes under nine different conditions, including methyl methanesulfonate (MMS), 4-nitroquinoline 1-oxide (4NQO), bleomycin, zeocin, and three other DNA-damaging environments. BFG-GI recapitulated known genetic interactions and yielded new condition-dependent genetic interactions. We validated and further explored a subnetwork of condition-dependent genetic interactions involving MAG1, SLX4, and genes encoding the Shu complex, and inferred that loss of the Shu complex leads to a decrease in the activation or activity of the checkpoint protein kinase Rad53. Footnotes * Manuscript has been accepted for publication in Molecular Systems Biology. This is the accepted version. In response to reviewers we completely revisited our analysis methodology, which had an impact on the resulting genetic interaction map (primarily increasing the number of positive interactions, and correspondence to a previous dataset). We have also carried out more experiments related to Rad53 and the Shu complex. Main findings remained unchanged.

As in India especially, the Punjab state sero-prevalence and distribution of ehrlichiosis in relation to clinico-hematobiochemical response remains largely unexplored. Thus, this study was designed to determine the prevalence of vector (tick)-borne tropical canine pancytopenia caused by through enzyme labeled ImmunoComb (IC) assay in dogs from in and around Ludhiana, Punjab. Correlation of prevalence was made with various clinico-hematobiochemical parameters. Seroprevalence study was carried out using IC test kit (Biogal, Galed Labs). The study was conducted in 84 dogs presented to the Small Animal Clinics, Teaching Veterinary Clinical Complex, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab. Out of 84 suspected dogs for ehrlichiosis, based on peripheral thin blood smear examination 12 (14.28%) cases were positive for the morulae of and 73 (86.90%) dogs were found positive to antibodies through IC canine antibody test kit, respectively. Among the different age groups 1-3 years of aged group showed highest prevalence (41.09%), followed by the 3-6 years age group (32.87%), infection levels were lower in the <1 year of age group dogs (13.69%) and more than 6 years age group dogs (12.32%). The highest prevalence was seen in Labrador retriever. This study indicates that season plays a very important role in the prevalence of ehrlichiosis. The most common findings observed were anemia, leukocytosis, neutropenia, lymphopenia, thrombocytopenia, eosinophilia followed by hyperbilirubinemia, increased levels of aspartate aminotransferase, alanine aminotransferase and alkaline phosphatase, hypoalbuminemia, hyperglobulinaemia, decrease in albumin and globulin ratio, increase in blood urea nitrogen and creatinine. Serological techniques like IC are more useful for detecting chronic and subclinical infections and are ideally suited to epidemiological investigations.