Htt is a repressor of Abl activity required for APP-induced axonal growth.

Huntington's disease is a progressive autosomal dominant neurodegenerative disorder caused by the expansion of a polyglutamine tract at the N-terminus of a large cytoplasmic protein. The Drosophila huntingtin (htt) gene is widely expressed during all developmental stages from embryos to adults. However, Drosophila htt mutant individuals are viable with no obvious developmental defects. We asked if such defects could be detected in htt mutants in a background that had been genetically sensitized to reveal cryptic developmental functions. Amyloid precursor protein (APP) is linked to Alzheimer's disease. Appl is the Drosophila APP ortholog and Appl signaling modulates axon outgrowth in the mushroom bodies (MBs), the learning and memory center in the fly, in part by recruiting Abl tyrosine kinase. Here, we find that htt mutations suppress axon outgrowth defects of αß neurons in Appl mutant MB by derepressing the activity of Abl. We show that Abl is required in MB αß neurons for their axon outgrowth. Importantly, both Abl overexpression and lack of expression produce similar phenotypes in the MBs, indicating the necessity of tightly regulating Abl activity. We find that Htt behaves genetically as a repressor of Abl activity, and consistent with this, in vivo FRET-based measurements reveal a significant increase in Abl kinase activity in the MBs when Htt levels are reduced. Thus, Appl and Htt have essential but opposing roles in MB development, promoting and suppressing Abl kinase activity, respectively, to maintain the appropriate intermediate level necessary for axon growth.

Rare and common variants associated with alcohol consumption identify a conserved molecular network.

BACKGROUND: Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, genetic studies of alcohol consumption that use rare variants are still in their early stages. No prior studies of alcohol consumption have examined whether common and rare variants implicate the same genes and molecular networks, leaving open the possibility that the two approaches might identify distinct biology. METHODS: To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N = 666,978) and whole exome sequencing data (Genebass, N = 393,099) to identify a set of common and rare variants for alcohol consumption. We used gene-based analysis to implicate genes from common and rare variant analyses, which we then propagated onto a shared molecular network using a network colocalization procedure. RESULTS: Gene-based analysis of each dataset implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified in only the rare variant analysis, but have been associated with other neuropsychiatric traits. Network colocalization revealed significant network overlap between the genes identified via common and rare variants. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. Seventy-one of the genes in the shared network were previously implicated in neuropsychiatric or substance use disorders but not alcohol-related behaviors (e.g. EXOC2, EPM2A, and CACNG4). Differential gene expression analysis showed enrichment in the liver and several brain regions. CONCLUSIONS: Genes implicated by network colocalization identify shared biology relevant to alcohol consumption, which also underlie neuropsychiatric traits and substance use disorders that are comorbid with alcohol use, providing a more holistic understanding of two disparate sources of genetic information.

Rare and Common Variants Associated with Alcohol Consumption Identify a Conserved Molecular Network.

Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, rare variants have only begun to be studied for their role in alcohol consumption. No studies have examined whether common and rare variants implicate the same genes and molecular networks. To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N=666,978) and whole exome sequencing data (Genebass, N=393,099) to identify a set of common and rare variants for alcohol consumption. Gene-based analysis of each dataset have implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified only by rare variant analysis, but have been associated with related psychiatric traits. We then used a network colocalization procedure to propagate the common and rare gene sets onto a shared molecular network, revealing significant overlap. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. 74 of the genes in the network were previously implicated in comorbid psychiatric or substance use disorders, but had not previously been identified for alcohol-related behaviors, including EXOC2, EPM2A, CACNB3, and CACNG4. Differential gene expression analysis showed enrichment in the liver and several brain regions supporting the role of network genes in alcohol consumption. Thus, genes implicated by common and rare variants identify shared functions relevant to alcohol consumption, which also underlie psychiatric traits and substance use disorders that are comorbid with alcohol use.

Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

Multi-ancestry meta-analysis of tobacco use disorder prioritizes novel candidate risk genes and reveals associations with numerous health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviors, and although strides have been made using genome-wide association studies (GWAS) to identify risk variants, the majority of variants identified have been for nicotine consumption, rather than TUD. We leveraged five biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records, EHR) in 898,680 individuals (739,895 European, 114,420 African American, 44,365 Latin American). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviors in children, and hundreds of medical outcomes, including HIV infection, heart disease, and pain. This work furthers our biological understanding of TUD and establishes EHR as a source of phenotypic information for studying the genetics of TUD.

Genome-wide association studies of human and rat BMI converge on synapse, epigenome, and hormone signaling networks.

A vexing observation in genome-wide association studies (GWASs) is that parallel analyses in different species may not identify orthologous genes. Here, we demonstrate that cross-species translation of GWASs can be greatly improved by an analysis of co-localization within molecular networks. Using body mass index (BMI) as an example, we show that the genes associated with BMI in humans lack significant agreement with those identified in rats. However, the networks interconnecting these genes show substantial overlap, highlighting common mechanisms including synaptic signaling, epigenetic modification, and hormonal regulation. Genetic perturbations within these networks cause abnormal BMI phenotypes in mice, too, supporting their broad conservation across mammals. Other mechanisms appear species specific, including carbohydrate biosynthesis (humans) and glycerolipid metabolism (rodents). Finally, network co-localization also identifies cross-species convergence for height/body length. This study advances a general paradigm for determining whether and how phenotypes measured in model species recapitulate human biology.

Small-Molecule Control of Super-Mendelian Inheritance in Gene Drives.

Synthetic CRISPR-based gene-drive systems have tremendous potential in public health and agriculture, such as for fighting vector-borne diseases or suppressing crop pest populations. These elements can rapidly spread in a population by breaching the inheritance limit of 50% dictated by Mendel's law of gene segregation, making them a promising tool for population engineering. However, current technologies lack control over their propagation capacity, and there are important concerns about potential unchecked spreading. Here, we describe a gene-drive system in Drosophila that generates an analog inheritance output that can be tightly and conditionally controlled to between 50% and 100%. This technology uses a modified SpCas9 that responds to a synthetic, orally available small molecule, fine-tuning the inheritance probability. This system opens a new avenue to feasibility studies for spatial and temporal control of gene drives using small molecules.

Chemogenetic System Demonstrates That Cas9 Longevity Impacts Genome Editing Outcomes.

Prolonged Cas9 activity can hinder genome engineering as it causes off-target effects, genotoxicity, heterogeneous genome-editing outcomes, immunogenicity, and mosaicism in embryonic editing-issues which could be addressed by controlling the longevity of Cas9. Though some temporal controls of Cas9 activity have been developed, only cumbersome systems exist for modifying the lifetime. Here, we have developed a chemogenetic system that brings Cas9 in proximity to a ubiquitin ligase, enabling rapid ubiquitination and degradation of Cas9 by the proteasome. Despite the large size of Cas9, we were able to demonstrate efficient degradation in cells from multiple species. Furthermore, by controlling the Cas9 lifetime, we were able to bias the DNA repair pathways and the genotypic outcome for both templated and nontemplated genome editing. Finally, we were able to dosably control the Cas9 activity and specificity to ameliorate the off-target effects. The ability of this system to change the Cas9 lifetime and, therefore, bias repair pathways and specificity in the desired direction allows precision control of the genome editing outcome.