Biology subjects

Williams, R. W.

Publications and source records attributed to Williams, R. W..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Genome-wide screen identifies host loci that modulate M. tuberculosis fitness in immunodivergent mice

Genetic differences among mammalian hosts and Mycobacterium tuberculosis (Mtb) strains determine diverse tuberculosis (TB) patient outcomes. The advent of recombinant inbred mouse panels and next-generation transposon mutagenesis and sequencing approaches has enabled dissection of complex host- pathogen interactions. To identify host and pathogen genetic determinants of Mtb pathogenesis, we infected members of the BXD family of mouse strains with a comprehensive library of Mtb transposon mutants (TnSeq). Members of the BXD family segregate for Mtb-resistant C57BL/6J (B6 or B) and Mtb-susceptible DBA/2J (D2 or D) haplotypes. The survival of each bacterial mutant was quantified within each BXD host, and we identified those bacterial genes that were differentially required for Mtb fitness across BXD genotypes. Mutants that varied in survival among the host family of strains were leveraged as reporters for "endophenotypes", each bacterial fitness profile directly probing specific components of the infection microenvironment. We conducted QTL mapping of these bacterial fitness endophenotypes and identified 140 host-pathogen quantitative trait loci (hpQTL). We identified a QTL hotspot on chromosome 6 (75.97-88.58 Mb) associated with the genetic requirement of multiple Mtb genes; Rv0127 (mak), Rv0359 (rip2), Rv0955 (perM), and Rv3849 (espR). Together, this screen reinforces the utility of bacterial mutant libraries as precise reporters of the host immunological microenvironment during infection and highlights specific host-pathogen genetic interactions for further investigation. To enable downstream follow-up for both bacterial and mammalian genetic research communities, all bacterial fitness profiles have been deposited into GeneNetwork.org and added into the comprehensive collection of TnSeq libraries in MtbTnDB.

genetics↗

bioRxiv2022

Divergent risky decision-making and impulsivity behaviors in two Lewis substrains of rats with low genetic difference

Substance use disorder (SUD) is associated with a cluster of cognitive disturbances that engender vulnerability to ongoing drug seeking and relapse. Two of these endophenotypes--risky decision-making and impulsivity--are amplified in individuals with substance use disorder and are augmented by repeated exposure to illicit drugs. Identifying genetic factors underlying variability in these traits is critical for early identification, prevention, and treatment of SUD-vulnerable individuals. Here, we compared risky decision-making and different facets of impulsivity between two fully inbred substrains of Lewis rats--LEW/NCrl and LEW/NHsd. We performed whole genome sequencing of both substrain to identify almost all relevant variants. We observed substantial differences in risky decision-making and impulsive behaviors. Relative to LEW/HHsd, the LEW/NCrl substrain accepts higher risk options in a decision-making task and higher rates of premature responses in the differential reinforcement of low rates of responding (DRL) task. These phenotypic differences were more pronounced in females than males. We defined a total of [~]9,000 polymorphisms between these substrains at 40X whole genome short-read coverage. Roughly half of variants are located within a single 1.5 Mb region of chromosome 8, but none impact protein-coding regions. In contrast, other variants are widely distributed, and of these 38 are predicted to cause protein-coding variants. In conclusion, Lewis rat substrains differ significantly in risk-taking and impulsivity and only a small number of easily mapped variants are likely to be causal. Sequencing combined with a reduced complexity cross (RCC) should enable identification of one or more variants underlying multiple complex addiction-relevant traits.

genomics↗

bioRxiv2022

Investigating mouse motor coordination using quantitative trait locus analysis to model the genetic underpinnings of developmental coordination disorder

The fundamental skills for motor coordination and motor control emerge through development, from infancy to late childhood years. Neurodevelopmental disorders such as Developmental Coordination Disorder (DCD) lead to impaired acquisition of motor skills. This study investigated motor behaviors that reflect the core symptoms of human DCD through the use of BXD recombinant inbred lines of mice that are known to have divergent phenotypes in many behavioral traits, including motor activity. We sought to correlate behavior in basic motor control tasks with the known genotypes of these reference populations of mice using quantitative trait locus (QTL) mapping. We used twelve BXD lines with an average of 16 mice per group to assess the onset of reflexes during the early neonatal stage of life and differences in motor coordination using the open field, rotarod, and gait analyses during the adolescent/young adulthood period. Results indicated significant variability between lines in as to when neonatal reflexes appeared as well as significant line differences for all measures of motor coordination. Five lines (BXD15, BXD27, BXD28, BXD75, and BXD86) struggled with sensorimotor coordination as seen in gait analysis, rotarod, and open field, similar to human presentation of DCD. We identified three significant quantitative trait loci for gait on proximal Chr 3, Chr 4 and distal Chr 6. Based on expression, function, and polymorphism within the mapped QTL intervals, 7 candidate genes (Gpr63, Spata5, Trpc3, Cntn6, Chl1, Grm7 and Ogg1) emerged. This study offers new insights into mouse motor behavior which promises to be a first murine model to explore the genetics and neural correlates of DCD.

neuroscience↗

bioRxiv2022

Developmental Coordination Disorder: What Can We Learn From Recombinant Inbred Mice Using Motor Learning Tasks and Quantitative Trait Locus Analysis

Developmental Coordination Disorder (DCD) is a motor skills disorder that affects 5-6% of all school-aged children. There is an indication that DCD has an underlying genetic component due to its high heritability. Therefore, we we have explored the use of a recombinant inbred family of mice known as the BXD panel to understand the genetic basis of complex traits (i.e., motor learning) through identification of Quantitative Trait Loci (QTLs). The overall aim of this study was to utilize the QTL approach to evaluate the genome-to-phenome correlation in BXD strains of mice in order to to better understanding the human presentation of DCD. Results in this current study indicate there is a spectrum of motor learning in the pre-selected BXD strains of mice with a spectrum between high and low learning capabilities. Five lines - BXD15, BXD27, BXD28, BXD75, and BXD86 - exhibited the most DCD-like phenotype, when compared to other BXD lines of interest. The results indicate that BXD15 and BXD75 struggled primarily with gross motor skills, BXD28 primarily had difficulties with fine motor skills, and BXD27 and BXD28 lines struggled with both fine and gross motor skills. The functional roles of significant QTL genes were assessed in relation to DCD-like behavior. Only Rab3a (Ras-related protein Rab-3A) emerged as a best candidate gene for the horizontal ladder rung task. This gene is found to be associated with brain and skeletal muscle development. This is the first study to specifically examine the genetic linkage of DCD using BXD lines of mice.

neuroscience↗

bioRxiv2022

Private and sub-family specific mutations of founder haplotypes in the BXD family reveal phenotypic consequences relevant to health and disease

The BXD family of recombinant inbred mice were developed by crossing and inbreeding progeny of C57BL/6J and DBA/2J strains. This family is the largest and most extensively phenotyped mammalian experimental genetic resource. Although used in genetics for 52 years, we do not yet have comprehensive data on DNA variants segregating in the BXDs. Using linked-read whole-genome sequencing, we sequenced 152 members of the family at about 40X coverage and quantified most variants. We identified 6.25 million polymorphism segregating at a near-optimal minor allele frequency of 0.42. We also defined two other major variants: strain-specific de novo singleton mutations and epoch-specific de novo polymorphism shared among subfamilies of BXDs. We quantified per-generation mutation rates of de novo variants and demonstrate how founder-derived, strain-specific, and epoch-specific variants can be analyzed jointly to model genome-phenome causality. This integration enables forward and reverse genetics at scale, rapid production of any of more than 10,000 diallel F1 hybrid progeny to test predictions across diverse environments or treatments. Combined with five decades of phenome data, the BXD family and F1 hybrids are a major resource for systems genetics and experimental precision medicine.

genomics↗

bioRxiv2022

Opiate responses are controlled by interactions of Oprm1 and Fgf12 loci in the murine BXD family: Correspondence to human GWAS finding

Exploring the molecular genetic cascades responsible for behavioral responses to opioids can improve our understanding of drug use initiation. We generated high-precision time-series data for 105 morphine-and naloxone-related traits across [~]700 young adult BXD mice (64 diverse strains and both sexes) for 3 hours after a single morphine injection. Variations in responses were mapped using high-precision genome sequencing-based genotypes. The initial locomotor responses to morphine mapped precisely to the {micro} opioid receptor gene (Oprm1) on chromosome (Chr) 10 with a peak linkage of 12.4 (-logP, genome-wide significance level is approximately 3.8). The B allele inherited from C57BL/6J was associated with up to 60% higher activity. This effect climaxed at 75 min but was exhausted by 160 min. A second major modulator of opioid-induced locomotion emerged after approximately 100 min. This locus, also associated with a high B allele, was located on Chr 16 with peak linkage of 10.6 (-logP) in females. This locus included only one compelling candidate, fibroblast growth factor 12 (Fgf12), a 600 Kb gene that controls sodium current kinetics at the axon hillock. A strong and transient epistatic interaction existed between the Oprm1 and Fgf12 loci during a short time window (45-75 min). The combination of a B haplotype at Oprm1 with a D haplotype from DBA/2J at Fgf12 was associated with unusually high activity. In a complementary study in heterogeneous stock rats, we demonstrated that Oprm1 and Fgf12 were co-expressed in one specific subtype of Drd1+ medium spiny neuron. A Bayesian network analysis supported an Oprm1-to-Fgf12 network that involves a MAP kinase cascade that modulates FGF12 phosphorylation and locomotor activation. OPRM1 and FGF12 networks in human GWAS data highlight enrichment of signals associated with substance use disorder. This study represents the first demonstration of a time-dependent epistatic interaction modulating drug response in mammals and the first linkage of Fgf12 to opioid-induced behavior.

genetics↗

bioRxiv2022

HiDiver: A Suite of Methods to Merge Magnetic Resonance Histology, Light Sheet Microscopy, and Complete Brain Delineations

We have developed new imaging and computational workflows to produce accurately aligned multimodal 3D images of the mouse brain that exploit high resolution magnetic resonance histology (MRH) and light sheet microscopy (LSM) with fully rendered 3D reference delineations of brain structures. The suite of methods starts with the acquisition of geometrically accurate (in-skull) brain MRIs using multi-gradient echo (MGRE) and new diffusion tensor imaging (DTI) at an isotropic spatial resolution of 15 m. Whole brain connectomes are generated using over 100 diffusion weighted images acquired with gradients at uniformly spaced angles. Track density images are generated at a super-resolution of 5 m. Brains are dissected from the cranium, cleared with SHIELD, stained by immunohistochemistry, and imaged by LSM at 1.8 m/pixel. LSM channels are registered into the reference MRH space along with the Allen Brain Atlas (ABA) Common Coordinate Framework version 3 (CCFv3). The result is a high-dimensional integrated volume with registration (HiDiver) that has a global alignment accuracy of 10-50 m. HiDiver enables 3D quantitative and global analyses of cells, circuits, connectomes, and CNS regions of interest (ROIs). Throughput is sufficiently high that HiDiver is now being used in comprehensive quantitative studies of the impact of gene variants and aging on rodent brain cytoarchitecture.

neuroscience↗

bioRxiv2021

SVJAM: Joint Analysis of Structural Variants Using Linked Read Sequencing Data

Linked-read whole genome sequencing methods, such as the 10x Chromium, attach a unique molecular barcode to each high molecular weight DNA molecule. The samples are then sequenced using short-read technology. During analysis, sequence reads sharing the same barcode are aligned to adjacent genomic locations. The pattern of barcode sharing between genomic regions allows the discovery of large structural variants (SVs) in the range of 1 Kb to a few Mb. Most SV calling methods for these data, such as LongRanger, analyze one sample at a time and often produces inconsistent results for the same genomic location across multiple samples. We developed a method, SVJAM, for joint calling of SVs, using data from 152 members of the BXD family of recombinant inbred strains of mice. Our method first collects candidate SV regions from single sample analysis, such as those produced by LongRanger. We then retrieve barcode overlapping data from all samples for each region. These data are organized as a high dimensional matrix. The dimension of this matrix is then reduced using principal component analysis. Samples projected onto a two dimensional space formed by the first two principal components forms two or three clusters based on their genotype, representing the reference, alternative, or heterozygotic alleles. We developed a novel distance measure for hierarchical clustering and rotating the axes to find the optimal clustering results. We also developed an algorithm to decide whether the pattern of sample distribution is best fitted with one, two, or three genotypes. For each sample, we calculate its membership score for each genotype. We compared results produced by SVJAM with LongRanger and few methods that rely on PacBio or Oxford Nanopore data. In a comparison of SVJAM with SV detected using long-read sequencing data for the DBA/2J strain, we found that our results recovered many SVs missed by LongRanger. We also found many SVs called by LongRanger were assigned with an incorrect SV type. Our algorithm also consistently identified heterozygotic regions.

genomics↗

bioRxiv2021

Multimodal Magnetic Resonance Histology and Light Sheet Imaging for Quantitative Neurogenetics of the Mouse

Paul Lauterbur closed his seminal paper on MRI with the statement that "zeugmatographic (imaging) techniques should find many useful applications in studies of the internal structures, states and composition of microscopic objects" [1]. Magnetic resonance microscopy was subsequently demonstrated in 1986 by three groups [2] [3] [4]. The application of MRI to the study of tissue structure, i.e. magnetic resonance histology (MRH) was suggested in 1993 [5]. MRH, while based on the same physical principals as MRI is something fundamentally different than the clinical exams which are typically limited to voxel dimensions of ~ 1 mm3. Preclinical imaging systems can acquire images with voxels ~ 1000 times smaller. The MR histology images presented here have been acquired at yet another factor of 1000 increase in spatial resolution. Figure S1 in the supplement shows a comparison of a state-of-the-art fractional anisotropy images of a C57 mouse brain in vivo @ 150 m resolution (voxel volume of 3.3 x10-3 mm3) with the atlas we have generated for this work at 15 m spatial resolution (voxel volume of 3.3 x 10-6 mm3). In previous work, we have demonstrated the utility of MR histology in neurogenetics at spatial/angular resolution of 45 m /46 angles [6]. At this spatial/angular resolution it is possible to map whole brain connectivity with high correspondence to retroviral tracers [7]. But the MRH derived connectomes can be derived in less than a day where the retroviral tracer studies require months/years [8]. The resolution index (angular samples/voxel volume) for this previous work was >500,000 [9]. Figure S2 shows a comparison between that previous work and the new atlas presented in this paper with a resolution index of 32 million. Light sheet microscopy (LSM) has undergone similar rapid evolution over the last 20 years. The invention of tissue clearing, advances in immunohistochemistry and development of selective plane illumination microscopy (SPIM) now make it possible to acquire whole mouse brain images at submicron spatial resolution with a vast array of cell specific markers [10] [11] [12] [13]. And these advantages can be realized in scan times of < 6hrs. The major limitation from these studies is the distortion in the tissue from dissection from the cranium, swelling from clearing and staining, and tissue damage from handling. We report here the merger of these two methods: O_LIMRH with the brain in the skull to provide accurate geometry, cytoarchitectural measures using scalar imaging metrics and whole brain connectivity at 15 m isotropic spatial resolution with super resolution track density images @ 5 m isotropic resolution; C_LIO_LIwhole brain multichannel LSM @ 1.8x1.8x4.0 m; C_LIO_LIa big image data infrastructure that enables label mapping from the atlas to the MR image, geometric correction to the light sheet data, label mapping to the light sheet volumes and quantitative extraction of regional cell density. These methods make it possible to generate a comprehensive collection of image derived phenotypes (IDP) of cells and circuits covering the whole mouse brain with throughput that can be scaled for quantitative neurogenetics. C_LI

neuroscience↗

bioRxiv2021

A quantitative trait variant in Gabra2 underlies increased methamphetamine stimulant sensitivity

Psychostimulant (methamphetamine, cocaine) use disorders have a genetic component that remains mostly unknown. Here, we conducted genome-wide quantitative trait locus (QTL) analysis of methamphetamine stimulant sensitivity. To facilitate gene identification, we employed a Reduced Complexity Cross between closely related C57BL/6 mouse substrains and examined maximum speed and distance traveled over 30 min following methamphetamine (2 mg/kg, i.p.). For maximum methamphetamine-induced speed following the second and third administration, we identified a single genome-wide significant QTL on chromosome 11 that peaked near the Cyfip2 locus [LOD = 3.5, 4.2; peak = 21 cM (36 Mb)]. For methamphetamine-induced distance traveled, we identified a single genome-wide significant QTL on chromosome 5 that peaked near a functional intronic indel in Gabra2 that codes for the alpha-2 subunit of the GABA-A receptor [LOD = 5.2; peak = 35 cM (67 Mb)]. Striatal cis-expression QTL mapping corroborated Gabra2 as a functional candidate gene underlying methamphetamine-induced distance traveled. CRISPR/Cas9-mediated correction of the mutant intronic deletion on the C57BL/6J background to the wild-type C57BL/6NJ allele was sufficient to reduce methamphetamine-induced locomotor activity toward the wild-type C57BL/6NJ-like level, thus validating the quantitative trait variant (QTV). These studies demonstrate the power and efficiency of Reduced Complexity Crosses in identifying causal genes and variants underlying complex traits. Functionally restoring Gabra2 expression decreased methamphetamine stimulant sensitivity and supports preclinical and human genetic studies implicating the GABA-A receptor in psychostimulant addiction-relevant traits. Importantly, our findings have major implications for investigators studying psychostimulants in the C57BL/6J strain - the gold standard strain in biomedical research.

genetics↗

bioRxiv2021

Genetic Analyses of Epigenetic Predictors that Estimate Aging, Metabolic Traits, and Lifespan

Changes in DNA methylation (DNAm) are linked to aging. Here, we profile highly conserved CpGs in 339 predominantly female mice belonging to the BXD family for which we have deep longevity and genomic data. We use a pan-mammalian microarray that provides a common platform for assaying the methylome across mammalian clades. We computed epigenetic clocks and tested associations with DNAm entropy, diet, weight, metabolic traits, and genetic variation. We describe the multifactorial variance of methylation at these CpGs, and show that high fat diet augments the age-associated changes. Entropy increases with age. The progression to disorder, particularly at CpGs that gain methylation over time, was predictive of genotype-dependent life expectancy. The longer-lived BXD strains had comparatively lower entropy at a given age. We identified two genetic loci that modulate rates of epigenetic age acceleration (EAA): one on chromosome (Chr) 11 that encompasses the Erbb2/Her2 oncogenic region, and a second on Chr19 that contains a cytochrome P450 cluster. Both loci harbor genes associated with EAA in humans including STXBP4, NKX2-3, and CUTC. Transcriptome and proteome analyses revealed associations with oxidation-reduction, metabolic, and immune response pathways. Our results highlight concordant loci for EAA in humans and mice, and demonstrate a tight coupling between the metabolic state and epigenetic aging.

genomics↗

bioRxiv2021

System genetics in the rat HXB/BXH family identifies Tti2 as a pleiotropic quantitative trait gene for adult hippocampal neurogenesis and serum glucose

Neurogenesis in the adult hippocampus contributes to learning and memory in the healthy brain but is dysregulated in metabolic and neurodegenerative diseases. The molecular relationships between neural stem cell activity, adult neurogenesis, and global metabolism are largely unknown. Here we applied unbiased systems genetic methods to quantify genetic covariation among adult neurogenesis and metabolic phenotypes in peripheral tissues of a genetically diverse family of rat strains, derived from a cross between the spontaneously hypertensive (SHR/OlaIpcv) strain and Brown Norway (BN-Lx/Cub). The HXB/BXH family is a very well established model to dissect genetic variants that modulate metabolic and cardiovascular disease and we have accumulated deep phenome and transcriptome data in a FAIR-compliant resource for systematic and integrative analyses. Here we measured rates of precursor cell proliferation, survival of new neurons, and gene expression in the hippocampus of the entire HXB/BXH family, including both parents. These data were combined with published metabolic phenotypes to detect a neurometabolic quantitative trait locus (QTL) for serum glucose and neuronal survival. We subsequently fine-mapped a key phenotype to a locus that includes the telo2-interacting protein 2 gene (Tti2)--a chaperone that modulates the activity and stability of PIKK kinases. To validate variants in or near Tti2 as a cause for differences in neurogenesis and glucose levels, we generated a targeted frameshift mutation on the SHR/OlaIpcv background. Heterozygous SHR-Tti2+/- mutants had lower rates of hippocampal neurogenesis and hallmarks of dysglycemia compared to wild-type littermates. Our findings highlight Tti2 as a causal genetic and molecular link between glucose metabolism and structural brain plasticity. In humans, more than 800 genomic variants are linked to TTI2 expression, seven of which have associations to protein and blood stem cell factor concentrations, blood pressure and frontotemporal dementia. Author summaryMetabolic and neurological disorders are often comorbid, suggesting that biological pathways which orchestrate peripheral homeostasis and the integrity of the nervous system intersect. The genetic architecture behind these relationships is still poorly described, in part because molecular processes in the human brain are very difficult to study. We thus used a rodent genetic reference population to investigate links between adult hippocampal neurogenesis-- a cellular plasticity mechanism important for learning flexibility--and metabolism. We measured adult neurogenesis in the family of 30 HXB/BXH rat recombinant inbred strains, who are characterised by stable differences in metabolism, behaviour, and gene expression levels. Because gene variants affecting distinct traits segregated into different members of the family, we discovered that previously published phenotypes correlated to adult neurogenesis due to shared genomic sequence. We found that expression levels of Tti2--a part of a specialised protein chaperone complex regulating stability of PIKK kinases--were concomitantly influencing adult neurogenesis and serum glucose levels. In human populations hundreds of genomic variants regulate TTI2 expression, potentially affecting brain function and glucose homeostasis.

neuroscience↗

bioRxiv2021

A wild-derived antimutator drives germline mutation spectrum differences in a genetically diverse murine family

Summary ParagraphAlthough germline mutation rates and spectra can vary within and between species, genetic modifiers of these traits have long eluded detection. In this study, we searched for loci that influence germline mutagenesis using a uniquely powerful resource: a panel of recombinant inbred mouse lines known as the BXD, descended from the laboratory mouse strains C57BL/6J (B) and DBA/2J (D). Each BXD lineage has been maintained by brother-sister mating in the near absence of natural selection, accumulating de novo mutations for up to 50 years on a known genetic background that is a unique linear mosaic of B and D haplotypes. We show that mice inheriting D haplotypes at a quantitative trait locus (QTL) on chromosome 4 accumulate C>A germline mutations at a 50% higher rate than those inheriting B haplotypes, primarily due to the activity of a C>A-dominated mutational signature known as SBS18. The B and D QTL haplotypes encode different alleles of the DNA repair gene Mutyh, which underlies the heritable colorectal cancer syndrome in which SBS18 was first identified. The B and D Mutyh alleles are present in wild populations of Mus musculus domesticus, providing evidence that common genetic variation modulates germline mutagenesis in a model mammalian species.

genetics↗

bioRxiv2021

Genetic modulation of initial sensitivity to Δ9-tetrahydrocannabinol (THC) among the BXD family of mice

Cannabinoid receptor 1 activation by the major psychoactive component in cannabis, {Delta}9-tetrahydrocannabinol (THC), produces motor impairments, hypothermia, and analgesia upon acute exposure. In previous work, we demonstrated significant sex and strain differences in acute responses to THC following administration of a single dose (10 mg/kg, i.p.) in C57BL/6J (B6) and DBA/2J (D2) inbred mice. To determine the extent to which these differences are heritable, we quantified acute responses to a single dose of THC (10 mg/kg, i.p.) in males and females from 20 members of the BXD family of inbred strains derived by crossing and inbreeding B6 and D2 mice. Acute THC responses (initial sensitivity) were quantified as changes from baseline for: 1. spontaneous activity in the open field (mobility), 2. body temperature (hypothermia), and 3. tail withdrawal latency to a thermal stimulus (analgesia/antinociception). Initial sensitivity to the immobilizing, hypothermic, and antinociceptive effects of THC varied substantially across the BXD family. Heritability was highest for mobility and hypothermia traits, indicating that segregating genetic variants modulate initial sensitivity to THC. We identified genomic loci and candidate genes, including Ndufs2, Scp2, Rps6kb1 or P70S6K, Pde4d, and Pten, that may control variation in THC initial sensitivity. We also detected strong correlations between initial responses to THC and legacy phenotypes related to intake or response to other drugs of abuse (cocaine, ethanol, and morphine). Our study demonstrates the feasibility of mapping genes and variants modulating THC responses in the BXDs to systematically define biological processes and liabilities associated with drug use and abuse.

genetics↗

bioRxiv2020

Whole genome sequencing of nearly isogeneic WMI and WLI inbred rats identifies genes potentially involved in depression

BackgroundThe WMI and WLI inbred rat substrains were generated from the stress-prone, and not yet fully inbred, Wistar Kyoto (WKY) strain using bi-directional selection for immobility in the forced swim test followed by over 38 generations of inbreeding. Despite the low level of genetic diversity among WKY progenitors, the WMI substrain is more vulnerable to stress relative to its WLI control substrain. Here we quantify numbers and classes of sequence variants distinguishing these substrains and test the hypothesis that they are nearly isogenic. ResultsThe WLI and WMI genomic DNA were sequenced using Illumina xTen, IonTorrent and 10X Chromium technologies to obtain a combined coverage of over 100X. We identified 4,296 high quality homozygous SNPs and indels that differ between the WMI and WLI substrains. Gene ontology analysis of these variants showed an enrichment for neurogenesis related pathways. In addition, high impact variations were detected in genes previously implicated in depression (e.g. Gnat2), depression-like behavior (e.g. Prlr, Nlrp1a), other psychiatric disease (e.g. Pou6f2, Kdm5a, Reep3, Wdfy3) or stress response (e.g. Pigr). ConclusionsThe high coverage sequencing data confirms the near isogenic nature of the two substrains, which combined with the variants detected can lead to the identification of genetic factors underlying greater susceptibility for depression, stress reactivity, and addiction.

bioinformatics↗

bioRxiv2020

RatsPub: a webservice aided by deep learning to mine PubMed for addiction-related genes

Interpreting and integrating results from omics studies typically requires a comprehensive and time consuming survey of extant literature. Here, we introduce GeneCup, an easy to use literature mining web service that searches all PubMed abstracts for user-provided gene symbols in conjunction with a set of custom keywords organized into a customized ontology, as well as results from human genome-wide association studies (GWAS). As an example, we organized over 300 keywords related to drug addiction into seven categories. The literature search is conducted by querying the NIH PubMed server using a programming interface, which is followed by retrieving abstracts from a local copy of the PubMed archive. The main results presented to the user are individual sentences containing the gene symbol, organized by the keywords they also contain. These sentences are presented through an interactive graphical interface or as tables. GWAS results are displayed using a similar method. All results are linked to the original abstract in PubMed. In addition, a convolutional neural network is employed to distinguish sentences describing systemic stress from those describing cellular stress. The automated and comprehensive search strategy provided by GeneCup facilitates the integration of new discoveries from omic studies with existing literature. GeneCup is free and open source software. The source code of GeneCup and the link to a running instance is available at https://github.com/hakangunturkun/GeneCup

bioinformatics↗

bioRxiv2020

The Molecular Landscape of the Aging Mouse Liver

Systems biology approaches often use inferred networks of gene expression and metabolite data to identify regulatory factors and pathways connected with phenotypic variance. Generally, study-specific multi-layer "Omics" datasets are used to contextualize generic molecular networks. In this regard separating upstream causal mechanisms, downstream biomarkers, and incidental correlations remains a significant challenge, yet it is essential for designing mechanistic experiments. To address this, we designed a study following a population of 2157 individuals from 89 isogenic BXD mouse strains across their lifespan to identify molecular interactions among genotype, environment, age (GxExA) and metabolic fitness. Each strain was separated into two cohorts, one fed low fat (6% cal/fat) and the other high fat (60% cal/fat) diets. Tissues were collected for 662 individuals (309 cohorts) diverging across age (7, 12, 18, and 24 months), diet, sex, and strain. Transcriptome, proteome, and metabolome data were generated for liver. Of these we identified linear relations among these molecular data with lifespan for the same genomes of mice (Roy et al. 2020), and we defined [~]1100 novel protein-coding genes associated with longevity. We knocked down the ortholog of Ctsd in C. elegans. The treatment reduced longevity both in wildtype and in mutant long-lived strains, thus validating the prediction. Next, to assess the molecular impact of GxExA on gene expression, the multi-omics data was parsed into metabolic networks where connectivity varied due to the independent variables. Differences in edge strengths connecting nodes in these molecular networks according to each variable enabled causal inference by using stability selection, with roughly 21% of novel gene-pathway connections being causally affected by diet and/or age. For instance, Chchd2 is activated by aging and drives changes in the proteasome, oxidative phosphorylation, and mitochondrial translation transcriptional networks. Together, we have developed a large multi-omics resource for studying aging in the liver, and a resource for turning standard associations into causal networks.

systems biology↗

bioRxiv2020

Computational approaches towards reducing contamination in single-cell RNA-seq data

Single cell RNA sequencing has enabled quantification of single cells and identification of different cell types and subtypes as well as cell functions in different tissues. Single cell RNA sequence analyses assume acquired RNAs correspond to cells, however, RNAs from contamination within the input data are also captured by these assays. The sequencing of background contamination as well as unwanted cells making their way to the final assay Potentially confound the correct biological interpretation of single cell transcriptomic data. Here we demonstrate two approaches to deal with background contamination as well as profiling of unwanted cells in the assays. We use three real-life datasets of whole-cell capture and nucleotide single-cell captures generated by Fluidigm and 10x technologies and show that these methods reduce the effect of contamination, strengthen clustering of cells and improves biological interpretation.

bioinformatics↗