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bioRxiv2018

Evaluation of endothelial nitric oxide synthase gene expression in mice genetically heterozygous in Cx43 (Cx43 + / - mice)

Gap junctions are proteins made of connexins which are involved in the regulation of vascular function. Deletion of connexins 43 (Cx43) modifies expression of genes known to be involved in the regulation of the vasculature, differentiation and function of vascular cells. Interestingly, mutant mice lacking endothelial nitric oxide synthase (eNOS) gene have been shown to be hypertensive, suggesting that nitric oxide (NO) plays a role in the physiological control of blood pressure. It was therefore hypothesised that the endothelial deletion of Cx43 in the pulmonary vasculature induces endothelial dysfunction and causes eNOS impairment thereby reducing NO biosynthesis, thus leading to vasoconstriction and vascular remodelling which subsequently leads to the development of pulmonary arterial hypertension (PAH). This project was aimed at evaluating eNOS gene expression in mice genetically heterozygous (HET) in Cx43 (Cx43 +/- mice). This was achieved by using lung tissues from four groups of wild type (W/T) and Cx43 +/- (male and female) mice. Ribonucleic acid (RNA) was isolated from the lung tissues using RNA II isolation system and was reverse transcribed to complementary deoxyribonucleic acid (cDNA). End - point polymerase chain reaction (PCR) and real time PCR were used to measure the expression of eNOS gene. eNOS gene expression levels were found to be the same in all four groups of mice tested, with no significant difference. The result therefore suggests that eNOS gene is expressed in mice genetically heterozygous in Cx43 (Cx43 + / -).

cell biology↗

bioRxiv2018

CRISPR-interference based modulation of mobile genetic elements in bacteria

Spontaneous mutagenesis of synthetic genetic constructs by mobile genetic elements frequently results in the rapid loss of advantageous functions. Previous efforts to minimize such mutations required the exceedingly time-consuming manipulation of bacterial chromosomes and the complete removal of insertional sequences (ISes). To this aim, we developed a single plasmid-based system (pCRIS) that applies CRISPR-interference to inhibit the transposition of bacterial ISes. pCRIS expresses multiple guide RNAs to direct inactivated Cas9 (dCas9) to simultaneously silence IS1, IS3, IS5, and IS150 at up to 38 chromosomal loci in Escherichia coli, in vivo. As a result, the transposition rate of all four targeted ISes dropped to negligible levels at both chromosomal and episomal targets, increasing the half-life of exogenous protein expression. Most notably, pCRIS, while requiring only a single plasmid delivery performed within a single day, provided a reduction of IS-mobility comparable to that seen in genome-scale chromosome engineering projects. Global transcriptomics analysis revealed nevertheless only minute alterations in the expression of untargeted genes. Finally, the transposition-silencing effect of pCRIS was easily transferable across multiple E. coli strains. The plasticity and robustness of our IS-silencing system make it a promising tool to stabilize bacterial genomes for synthetic biology and industrial biotechnology applications.

synthetic biology↗

bioRxiv2018

Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning

The increasing amount of scientific literature in biological and biomedical science research has created a challenge in the continuous and reliable curation of the latest knowledge discovered, and automatic biomedical text-mining has been one of the answers to this chal-lenge. In this paper, we aim to further improve the reliability of biomedical text-mining by training the system to directly simulate the human behaviors such as querying the PubMed, selecting articles from queried results, and reading selected articles for knowledge. We take advantage of the efficiency of biomedical text-mining, the flexibility of deep reinforcement learning, and the massive amount of knowledge collected in UMLS into an integrative arti-ficial intelligent reader that can automatically identify the authentic articles and effectively acquire the knowledge conveyed in the articles. We construct a system, whose current pri-mary task is to build the genetic association database between genes and complex traits of the human. Our contributions in this paper are three-fold: 1) We propose to improve the reliability of text-mining by building a system that can directly simulate the behavior of a researcher, and we develop corresponding methods, such as Bi-directional LSTM for text mining and Deep Q-Network for organizing behaviors. 2) We demonstrate the effec-tiveness of our system with an example in constructing a genetic association database. 3) We release our implementation as a generic framework for researchers in the community to conveniently construct other databases.

bioinformatics↗

bioRxiv2018

BIN1 genetic risk factor for Alzheimer is sufficient to induce early structural tract alterations in entorhinal cortex-dentate gyrus pathway and related hippocampal multi-scale impairments

Genetic factors are known to contribute to Late Onset Alzheimers disease (LOAD) but their contribution to pathophysiology, specially to prodomic phases accessible to therapeutic approaches are far to be understood. To translate genetic risk of Alzheimers disease (AD) into mechanistic insight, we generated transgenic mouse lines that express a [~]195 kbp human BAC that includes only BIN1, a gene associated to LOAD. This model gives a modest BIN1 overexpression, dependent of the number of BAC copies. At 6 months of age, we detected impaired entorhinal cortex (EC)-hippocampal pathways with specific impairments in EC-dentate gyrus synaptic long-term potentiation, dendritic spines of granular cells and recognition episodic memory. Structural changes were quantified using MRI. Their whole-brain functional impact were analyzed using resting state fMRI with a hypoconnectivity centered on entorhinal cortex. These early phenotype defects independent of any changes in A-beta can be instrumental in the search for new AD drug targets.

neuroscience↗

bioRxiv2018

Managing the Spatial Covariance of Genetic Diversity in Niemann-Pick C1 Through Modulation of the Hsp70 Chaperone System

Genetic diversity provides a rich repository for understanding the role of proteostasis in the management of the protein fold to allow biology to evolve through variation in the population and in response to the environment. Failure in proteostasis can trigger multiple disease states affecting both human health and lifespan. Niemann-Pick C (NPC) disease is a genetic disorder mainly caused by mutations in NPC1, a multi-spanning transmembrane protein that is trafficked through the exocytic pathway to late endosomes and lysosomes (LE/Ly) to manage cholesterol homeostasis. Proteostatic defects triggered by >600 NPC1 variants found in the human population inhibit export of NPC1 protein from ER or function in downstream LE/Ly, leading to accumulation of cholesterol and rapid onset neurodegeneration in childhood for most patients. We now show that chemical allosteric inhibitors, such as JG98, targeting the cytosolic Hsp70 chaperone/co-chaperone complex improves the trafficking and stability of NPC1 variants with diverse NPC1 genotypes. By exploiting the knowledge-base of NPC1 variants found in the world-wide patient population using Variation Spatial Profiling (VSP), a Gaussian-process based machine learning (ML) approach, we show how the Hsp70 chaperone system alters the spatial covariance (SCV) tolerance of the ER and the SCV set-points for each residue of the NPC1 polypeptide chain differentially to improve trafficking efficiency and post-ER stability for variants distributed across the entire NPC1 polypeptide. The impact of JG98 is supported by the observation that silencing of Hsp70 specific nucleotide exchange factors (NEF) (BCL-anthogene (BAG) family) co-chaperones significantly improve the folding status of NPC1 variants. Together, these studies suggest that targeting the cytosolic Hsp70 system to adjust the SCV tolerance of the proteostasis network can improve recognition of the plasticity of the NPC1 fold found in the disease population for trafficking to the LE/Ly compartments.

genomics↗

bioRxiv2018

Modular modeling improves the predictions of genetic variant effects on splicing

Predicting the effects of genetic variants on splicing is highly relevant for human genetics. We describe the framework MMSplice (modular modeling of splicing) with which we built the winning model of the CAGI 2018 exon skipping prediction challenge. The MMSplice modules are neural networks scoring exon, intron, and splice sites, trained on distinct large-scale genomics datasets. These modules are combined to predict effects of variants on exon skipping, alternative donor and acceptor sites, splicing efficiency, and pathogenicity, with matched or higher performance than state-of-the-art. Our models, available in the repository Kipoi, apply to variants including indels directly from VCF files.

genomics↗

bioRxiv2018

The genetics of morphological and behavioral island traits in deer mice

Animals on islands often exhibit dramatic differences in morphology and behaviour compared to mainland individuals, a phenomenon known as the \"island syndrome\". These differences are thought to be adaptations to island environments, but the extent to which they have a genetic basis or instead represent plastic responses to environmental extremes is often unknown. Here, we revisit a classic case of island syndrome in deer mice (Peromyscus maniculatus) from British Columbia. We first show that Saturna Island mice and those from neighbouring islands are [~]35% ([~]5g) heavier than mainland mice and diverged approximately 10 thousand years ago. We then established laboratory colonies and find that Saturna Island mice are heavier both because they are longer and have disproportionately more lean mass. These trait differences are maintained in second-generation captive-born mice raised in a common environment. In addition, island-mainland hybrids reveal a maternal genetic effect on body weight. Using behavioural testing in the lab, we also find that wild-caught island mice are less aggressive than mainland mice; however, lab-raised mice born to these founders do not differ in aggression. Together, our results reveal that these mice respond differently to environmental conditions on islands - evolving both heritable changes in a morphological trait and also expressing a plastic phenotypic response in a behavioural trait.

evolutionary biology↗

bioRxiv2018

Different genetic mechanisms mediate spontaneous versus UVR-induced malignant melanoma

Genetic variation conferring resistance and susceptibility to carcinogen-induced tumorigenesis is frequently studied in mice. We have now turned this to melanoma using the collaborative cross (CC), a resource of mouse strains designed to discover genes for complex diseases. We studied melanoma-prone transgenic progeny across seventy CC genetic backgrounds. We mapped a strong quantitative trait locus for rapid onset spontaneous melanoma onset to Prkdc, a gene involved in detection and repair of DNA damage. In contrast, rapid onset UVR-induced melanoma was linked to the ribosomal subunit gene Rrp15. Ribosome biogenesis was upregulated in skin shortly after UVR exposure, Mechanistically, variation in the \"usual suspects\" by which UVR may exacerbate melanoma, defective DNA repair, melanocyte proliferation, or inflammatory cell infiltration, did not explain melanoma susceptibility or resistance across the CC. Instead, events occurring soon after exposure, such as dysregulation of ribosome function, which alters many aspects of cellular metabolism, may be important.

cancer biology↗

bioRxiv2018

Genetic distance between complex repeats

Complex nucleotide or aminoacid repeats with long units play an important role in proteins. The evolutionary analysis of these variants is challenging due to genetic diversity within repeat units as well as variability in the arrangement of different units along the repeat sequence. Here we present a new approach for the computation of genetic distances between complex repeats. This method takes into account evolutionary processes including point mutations, insertions and deletions of repeat units, as well as duplication of single units. We provide an algorithm for the computation of these distances along with the corresponding global pairwise alignment of repeats. As an example, we apply our approach to the evolution of repeat units in the highly polymorphic zinc-finger repeat domain of the PRDM9 protein across wild populations of house mice. This approach opens the way for new insights into the evolutionary history of polymorphic repeats.

bioinformatics↗

bioRxiv2018

Whole genome sequencing Mycobacterium tuberculosis directly from sputum identifies more genetic diversity than sequencing from culture

BackgroundRepeated culture reduces within-sample Mycobacterium tuberculosis genetic diversity due to selection of clones suited to growth in culture and/or random loss of lineages, but it is not known to what extent omitting the culture step altogether alters genetic diversity. We compared M. tuberculosis whole genome sequences generated from 33 paired clinical samples using two methods. In one method DNA was extracted directly from sputum then enriched with custom-designed SureSelect (Agilent) oligonucleotide baits and in the other it was extracted from mycobacterial growth indicator tube (MGIT) culture.\n\nResultsDNA directly sequenced from sputum showed significantly more within-sample diversity than that from MGIT culture (median 5.0 vs 4.5 heterozygous alleles per sample, p=0.04). Resistance associated variants present as HAs occurred in four patients, and in two cases may provide a genotypic explanation for phenotypic resistance.\n\nConclusionsCulture-free M. tuberculosis whole genome sequencing detects more within-sample diversity than a leading culture-based method and may allow detection of mycobacteria that are not actively replicating.

genomics↗

bioRxiv2018

Integrity and stability of virulence plasmids from Pseudomonas syringae are modulated by mobile genetic elements and multiple toxin-antitoxin systems

BackgroundVirulence plasmids are critically exposed to genetic decay and loss, particularly in Pseudomonas syringae strains because of their high content of mobile genetic elements and their exploitation of environmental niches outside of the plant host. The demonstrated high plasticity and adaptability of P. syringae plasmids, involving the acquisition and loss of large DNA regions, contrasts with their usual high stability and the maintenance of key virulence genes in free living conditions. The identification of plasmid stability determinants and mechanisms will help to understand their evolution and adaptability to agroecosystems as well as to develop more efficient control measures.\n\nResultsWe show that the three virulence plasmids of P. syringae pv. savastanoi NCPPB 3335 contain diverse functional stability determinants, including three toxin-antitoxin systems (TA) in both pPsv48A and pPsv48C, whereas one of the two replicons of pPsv48C can confer stable inheritance by itself. Loss of pPsv48A increased by two orders of magnitude upon functional inactivation of its TA systems. However, inactivation of the TA systems from pPsv48C did not result in its curing but led to the recovery of diverse deletion derivatives. One type consisted in the deletion of an 8.3 kb fragment, with a frequency of 3.8 {+/-} 0.3 x 10-3, by recombination between two copies of MITEPsy2. Likewise, IS801 promoted the occurrence of deletions of variable size by one-ended transposition with a frequency of 5.5 {+/-} 2.1 x 10-4, 80 % of which resulted in the loss of virulence gene idi. These deletion derivatives were stably maintained in the population by replication mediated by repJ, which is adjacent to IS801. IS801 also promoted deletions in plasmid pPsv48A, either by recombination or one-ended transposition. In all cases, functional TA systems contributed significantly to reduce the occurrence of plasmid deletions in vivo.\n\nConclusionsVirulence plasmids from P. syringae harbour a diverse array of stability determinants with a variable contribution to plasmid persistence. Additionally, multiple TA systems favour the long-term survival and integrity of virulence plasmids, as well as the maintenance of pathogenicity genes in free-living conditions. This strategy is likely widespread amongst native plasmids of P. syringae and other bacteria.

microbiology↗

bioRxiv2026

Genetic Disruption at the CIP2A Locus Modulates T Cell Responses and Attenuates Experimental Autoimmune Encephalomyelitis

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system (CNS) driven by pathogenic T cell-mediated inflammation. Fingolimod (FTY720), an approved therapy for MS, is an established activator of protein phosphatase 2A (PP2A). However the contribution of PP2A in autoimmune neuroinflammation remains incompletely understood. Here, we addressed this question using experimental autoimmune encephalomyelitis (EAE), a murine model of MS, in mice carrying a genetic disruption of the locus encoding cancerous inhibitor of protein phosphatase 2A (CIP2A), an endogenous inhibitor of PP2A. Mice with disruption of the CIP2A locus, the knock out (KO) mice, exhibited attenuated EAE severity compared with wild-type (WT) controls. Histological and flow-cytometric analyses revealed markedly reduced infiltration of mononuclear cells, including CD4 and CD4CXCR6 encephalitogenic T cells, in the CNS of diseased KO mice. Reduced numbers of these T cell populations were also observed in peripheral lymphoid organs of the Cip2a-deficient mice during EAE, while T cell abundance was comparable under steady-state conditions, suggesting impaired activation-induced expansion rather than altered homeostasis or migration. Single-cell RNA sequencing of CNS and lymph node immune cells revealed changes in cell-type abundance and gene expression. Notably, Il17a expression was reduced in CNS CD8+ T cells and showed a similar trend in {gamma}{delta} T cells. Together, our findings reveal that genetic disruption at the CIP2A locus attenuates EAE, possibly by limiting the expansion and accumulation of encephalitogenic T cell populations in CNS. These results identify the CIP2A locus as a previously unrecognized regulator of T cell-driven autoimmune neuroinflammation and provide new insights into mechanisms that restrain pathogenic T cell responses during EAE.

immunology↗

bioRxiv2026

Sensory-sleep dysfunction is a shared phenotype across genetically distinct neurodevelopmental disorder models

Sensory abnormalities and sleep disruption frequently co-occur in neurodevelopmental disorders (NDDs), but how sensory input interacts with sleep regulation in NDDs remains poorly understood. Here, we examined vibration-induced sleep (VIS), in which prolonged gentle vibration promotes sleep in Drosophila, in three genetically distinct NDD models: dNf1, dNrx1, and dFmr1. Despite markedly different baseline sleep phenotypes, all three mutants exhibited impaired VIS, identifying disrupted sensory-sleep integration as a shared phenotype across these NDD models. Behavioral responses to vibration, activity-associated CRTC signaling in Nanchung-positive (Nan+) mechanosensory neurons, and thermogenetic activation of Nan+ neurons revealed distinct underlying abnormalities across the three models, indicating that disruption at different points along the sensory-sleep axis can converge on the same behavioral phenotype. The effect of mechanosensory stimulation was also strongly shaped by homeostatic sleep drive: following sleep deprivation, vibration promoted sleep in dNf1 mutants, remained ineffective in dNrx1 mutants, and opposed recovery sleep in dFmr1 mutants. Together, these findings identify impaired sensory regulation of sleep as a point of convergence across genetically distinct NDD models and demonstrate that the expression of this shared phenotype depends on internal state.

neuroscience↗

bioRxiv2014

A 22,403 marker composite genetic linkage map for cassava (Manihot esculenta Crantz) derived from ten populations

Cassava (Manihot esculenta Crantz) is a major staple crop in Africa, Asia, and South America, and its starchy roots provide nourishment for 800 million people worldwide. Although native to South America, cassava was brought to Africa approximately 400 years ago and is now widely cultivated across sub-Saharan Africa. The widespread use of clonal planting material, however, aids the spread of disease. Breeding for disease resistance and improved yield began in the 1920s and has accelerated in the last 45 years. To assist in the rapid identification of markers for pathogen resistance and crop traits, and to accelerate breeding programs, we generated a framework map for M. esculenta Crantz derived from reduced representation sequencing (genotyping-by-sequencing [GBS]). The composite 2,412 cM map integrates ten biparental maps (comprising 3,480 meioses) and organizes 22,403 genetic markers on 18 chromosomes, in agreement with the observed karyotype. The map anchors 71.9% of the draft genome assembly and 90.7% of the predicted protein-coding genes. The resulting chromosome-anchored genome sequence provides an essential framework for identification of trait markers and causal genes as well as genomics-enhanced breeding of this important crop.

Genetics↗

bioRxiv2017

Exome chip meta-analysis elucidates the genetic architecture of rare coding variants in smoking and drinking behavior

BackgroundSmoking and alcohol use behaviors in humans have been associated with common genetic variants within multiple genomic loci. Investigation of rare variation within these loci holds promise for identifying causal variants impacting biological mechanisms in the etiology of disordered behavior. Microarrays have been designed to genotype rare nonsynonymous and putative loss of function variants. Such variants are expected to have greater deleterious consequences on gene function than other variants, and significantly contribute to disease risk.\n\nMethodsIn the present study, we analyzed [~]250,000 rare variants from 17 independent studies. Each variant was tested for association with five addiction-related phenotypes: cigarettes per day, pack years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted single variant tests of all variants, and gene-based burden tests of nonsynonymous or putative loss of function variants with minor allele frequency less than 1%.\n\nResultsMeta-analytic sample sizes ranged from 70,847 to 164,142 individuals, depending on the phenotype. Known loci tagged by common variants replicated, but there was no robust evidence for individually associated rare variants, either in gene based or single variant tests. Using a modified method-of-moment approach, we found that all low frequency coding variants, in aggregate, contributed 1.7% to 3.6% of the phenotypic variation for the five traits (p<.05).\n\nConclusionsThe findings indicate that rare coding variants contribute to phenotypic variation, but that much larger samples and/or denser genotyping of rare variants will be required to successfully identify associations with these phenotypes, whether individual variants or gene- based associations.

genetics↗

bioRxiv2014

LIMIX: genetic analysis of multiple traits

Multi-trait mixed models have emerged as a promising approach for joint analyses of multiple traits. In principle, the mixed model framework is remarkably general. However, current methods implement only a very specific range of tasks to optimize the necessary computations. Here, we present a multi-trait modeling framework that is versatile and fast: LIMIX enables to flexibly adapt mixed models for a broad range of applications with different observed and hidden covariates, and variable study designs. To highlight the novel modeling aspects of LIMIX we performed three vastly different genetic studies: joint GWAS of correlated blood lipid phenotypes, joint analysis of the expression levels of the multiple transcript-isoforms of a gene, and pathway-based modeling of molecular traits across environments. In these applications we show that LIMIX increases GWAS power and phenotype prediction accuracy, in particular when integrating stepwise multi-locus regression into multi-trait models, and when analyzing large numbers of traits. An open source implementation of LIMIX is freely available at: https://github.com/PMBio/limix.

Genetics↗

bioRxiv2014

The genetic basis of energy conservation in the sulfate-reducing bacterium Desulfovibrio alaskensis G20

Sulfate-reducing bacteria play major roles in the global carbon and sulfur cycles, but it remains unclear how reducing sulfate yields energy. To determine the genetic basis of energy conservation, we measured the fitness of thousands of pooled mutants of Desulfovibrio alaskensis G20 during growth in 12 different combinations of electron donors and acceptors. We show that ion pumping by the ferredoxin:NADH oxidoreductase Rnf is required whenever substrate-level phosphorylation is not possible. The uncharacterized complex Hdr/flox-1 (Dde_1207:13) is sometimes important alongside Rnf and may perform an electron bifurcation to generate more reduced ferredoxin from NADH to allow further ion pumping. Similarly, during the oxidation of malate or fumarate, the electron-bifurcating transhydrogenase NfnAB-2 (Dde_1250:1) is important and may generate reduced ferredoxin to allow additional ion pumping by Rnf. During formate oxidation, the periplasmic [NiFeSe] hydrogenase HysAB is required, which suggests that hydrogen forms in the periplasm, diffuses to the cytoplasm, and is used to reduce ferredoxin, thus providing a substrate for Rnf. During hydrogen utilization, the transmembrane electron transport complex Tmc is important and may move electrons from the periplasm into the cytoplasmic sulfite reduction pathway. Finally, mutants of many other putative electron carriers have no clear phenotype, which suggests that they are not important under our growth conditions.

Genetics↗

bioRxiv2014

Calling genotypes from public RNA-sequencing data enables identification of genetic variants that affect gene-expression levels

Given increasing numbers of RNA-seq samples in the public domain, we studied to what extent expression quantitative trait loci (eQTLs) and allele-specific expression (ASE) can be identified in public RNA-seq data while also deriving the genotypes from the RNA-seq reads. 4,978 human RNA-seq runs, representing many different tissues and cell-types, passed quality control. Even though this data originated from many different laboratories, samples reflecting the same cell-type clustered together, suggesting that technical biases due to different sequencing protocols were limited. We derived genotypes from the RNA-seq reads and imputed non-coding variants. In a joint analysis on 1,262 samples combined, we identified cis-eQTLs effects for 8,034 unique genes. Additionally, we observed strong ASE effects for 34 rare pathogenic variants, corroborating previously observed effects on the corresponding protein levels. Given the exponential growth of the number of publicly available RNA-seq samples, we expect this approach will become relevant for studying tissue-specific effects of rare pathogenic genetic variants.

Genetics↗