Biology subjects

Johnson, B. B.

Publications and source records attributed to Johnson, B. B..

7 recordsLinked to original sources

bioRxiv2025

A protocol for high-throughput microplate-based CUT&Tag

Cleavage Under Targets & Tagmentation (CUT&Tag) is a versatile method for measuring genomic occupancy of chromatin-associated proteins with high sensitivity and specificity. CUT&Tag has low sequencing requirements and is therefore suitable for highly multiplexed experiments, but methods to process samples at throughput without specialized equipment are lacking. Here we present a method for simultaneous parallel processing of 96 CUT&Tag samples in a standard microplate. Plate-CUT&Tag can be carried out in a similar time frame to benchtop CUT&Tag and yields data of comparable quality. We present data from cell culture and patient leukemia samples processed with Plate-CUT&Tag to illustrate its utility in large-scale preclinical and translational studies.

genomics↗

bioRxiv2025

Genome-wide association study of cocaine self-administration behavior in Heterogeneous Stock rats

BackgroundCocaine use disorder (CUD) is a major public health crisis with detrimental individual and societal effects. The specific genes mediating CUD remain largely unknown. MethodsWe conducted a genome-wide association study (GWAS) using outbred N/NIH Heterogeneous Stock (HS; n = 836, female = 415, male = 421) rats. We examined multiple CUD-related phenotypes that captured acquisition of self-administration, escalation of intake, and compulsive-like responding. ResultsConsistent with the existing literature, these traits were phenotypically and genetically correlated and exhibited modest heritability (h2 = 0.07 - 0.16). We identified six genome-wide significant associations. One locus on chromosome 19 was associated with the variable time between cocaine infusions (post infusion interval) and contains several carboxylesterase genes that are orthologous to the human CES1 gene; notably, carboxylesterases metabolize cocaine. Three non-synonymous coding variants in the genes Ces1c and Ces1d were in perfect linkage disequilibrium with this locus, suggesting that one or more of them might be the causal SNP. The other 5 loci also contained promising coding and expression variants, including Trak2, a gene previously associated with CUD in human GWAS and Slc10a7, Plcl1, and Satb2 which have been associated with alcohol and tobacco use disorder. ConclusionsThis is the largest genetic study of cocaine self-administration ever conducted in any species. Our results replicate previous loci associated with CUD in humans and provide several novel biological insights including the potential of pharmacological strategies targeting carboxylesterases for the treatment of CUD.

genetics↗

bioRxiv2025

Novel insights into the genetic architecture and mechanisms of host/microbiome interactions from a multi-cohort analysis of outbred laboratory rats

The intestinal microbiome influences health and disease. Its composition is affected by host genetics and environmental exposures. Understanding host genetic effects is critical but challenging in humans, due to the difficulty of detecting, mapping and interpreting them. To address this, we analysed host genetic effects in four cohorts of outbred laboratory rats exposed to distinct but controlled environments. We found that polygenic host genetic effects were consistent across environments. We identified three replicated microbiome-associated loci, one of which involved a sialyltransferase gene and Paraprevotella. We found a similar association in a human cohort, between ST6GAL1 and Paraprevotella, both of which have been linked with immune and infectious diseases. Moreover, we found evidence of indirect genetic effects on microbiome phenotypes, which substantially increased their total genetic variance. Finally, we identified a novel mechanism whereby indirect genetic effects can contribute to "missing heritability".

genetics↗

bioRxiv2024

Industrialization of three-dimensional hiPSC-cardiac microtissues for high-throughput cardiac safety and drug discovery screening

Current cardiac cell models for drug screening often face a trade-off between cellular maturity and achieving high throughput. While three-dimensional human induced pluripotent stem cell-based heart models typically exhibit more adult-like features, their application is hindered by the need for large cell numbers or complex equipment. Here, we developed cost-effective methods to scale up production of three-dimensional cardiac microtissues (cMTs) containing three cardiac cell types, and assess calcium transients and action potential metrics for high-throughput screening (HTS). Automating the procedure revealed reproducible drug responsiveness and predictive accuracy in a reference compound screen. Furthermore, an arrhythmic phenotype was reliably triggered in cMTs containing cardiomyocytes with a RYR2 mutation. A screen of FDA-approved drugs identified 17 drugs that rescued the arrhythmic phenotype. Our findings underscore the scalability of cMTs and their utility in disease modelling and HTS. The advanced "technology-readiness-level" of cMTs supports their regulatory uptake and acceptance within the pharmaceutical industry.

cell biology↗

bioRxiv2024

A Cost-effective, High-throughput, Highly Accurate Genotyping Method for Outbred Populations

Affordable sequencing and genotyping methods are essential for large scale genome-wide association studies. While genotyping microarrays and reference panels for imputation are available for human subjects, non-human model systems often lack such options. Our lab previously demonstrated an efficient and cost-effective method to genotype heterogeneous stock rats using double-digest genotyping-by-sequencing. However, low-coverage whole-genome sequencing offers an alternative method that has several advantages. Here, we describe a cost-effective, high-throughput, high-accuracy genotyping method for N/NIH heterogeneous stock rats that can use a combination of sequencing data previously generated by double-digest genotyping-by-sequencing and more recently generated by low-coverage whole-genome-sequencing data. Using double-digest genotyping-by-sequencing data from 5,745 heterogeneous stock rats (mean 0.21x coverage) and low-coverage whole-genome-sequencing data from 8,760 heterogeneous stock rats (mean 0.27x coverage), we can impute 7.32 million bi-allelic single-nucleotide polymorphisms with a concordance rate >99.76% compared to high-coverage (mean 33.26x coverage) whole-genome sequencing data for a subset of the same individuals. Our results demonstrate the feasibility of using sequencing data from double-digest genotyping-by-sequencing or low-coverage whole-genome-sequencing for accurate genotyping, and demonstrate techniques that may also be useful for other genetic studies in non-human subjects. Article SummaryHeterogeneous stock rats were derived by interbreeding eight inbred founders in 1984, and have been maintained as an outbred population for more than 100 generations. Heterogeneous stock rats offer a high degree of genetic and phenotypic diversity, and have been extensively used for genetic studies. Here, we describe a cost-effective and high-throughput genotyping method for heterogeneous stock rats. We applied the method to 15,552 heterogeneous stock rats. The resulting genotypes were highly accurate. These techniques may be useful for genetic studies in other non-human subjects.

genetics↗

bioRxiv2023

Genome-wide association study of delay discounting in Heterogenous Stock rats

Delay discounting refers to the behavioral tendency to devalue rewards as a function of their delay in receipt. Heightened delay discounting has been associated with substance use disorders, as well as multiple co-occurring psychopathologies. Genetic studies in humans and animal models have established that delay discounting is a heritable trait, but only a few specific genes have been associated with delay discounting. Here, we aimed to identify novel genetic loci associated with delay discounting through a genome-wide association study (GWAS) using Heterogenous Stock rats, a genetically diverse outbred population derived from eight inbred founder strains. We assessed delay discounting in 650 male and female rats using an adjusting amount procedure in which rats chose between smaller immediate sucrose rewards or a larger reward at variable delays. Preference switch points were calculated for each rat and both exponential and hyperbolic functions were fitted to these indifference points. Area under the curve (AUC) and the discounting parameter k of both functions were used as delay discounting measures. GWAS for AUC, exponential k, and indifference points for a short delay identified significant loci on chromosomes 20 and 14. The gene Slc35f1, which encodes a member of the solute carrier family of nucleoside sugar transporters, was the only gene within the chromosome 20 locus. That locus also contained an eQTL for Slc35f1, suggesting that heritable differences in the expression of that gene might be responsible for the association with behavior. The gene Adgrl3, which encodes a member of the latrophilin family of G-protein coupled receptors, was the only gene within the chromosome 14 locus. These findings implicate novel genes in delay discounting and highlight the need for further exploration.

genomics↗

bioRxiv2023

RATTACA: Genetic predictions in Heterogeneous Stock rats offer a new tool for genetic correlation and experimental design

Genetic correlations between traits are a common first step in studies identifying causal genetic pathways and mechanisms. Using this framework with inbred or selected lines, however, requires intensive labor investment through breeding and phenotyping, and is prone to confounding, as observed trait correlations do not necessarily reflect a causative genetic architecture shared between distinct populations. When drawn from a single outbred population, genetic trait predictions offer a viable alternative to experimental phenotyping and can be used to identify putative genetic correlations when samples with divergent trait predictions also diverge in a second measured trait. Here, we present a novel research paradigm and service called RATTACA, in which genotypes from Heterogenous Stock (HS) rats are used to predict trait values using linear mixed models. These predictions are used to select samples of individuals with high and low extreme trait values, facilitating (1) a priori sampling of desired trait values without oversampling across phenotypic space and (2) easy identification of putative genetic correlations between predicted and newly measured traits. We validated prediction models using four example phenotypes with measured trait values and found sufficient accuracy to distinguish extreme trait samples, even when using a small number of genome-wide variants (n = 50,000) for traits with modest heritability (h2 = 0.13). Given genotypes and trait measurements available through previous research in HS rats, we propose RATTACA as a service to reliably predict more than 80 behavioral and physiological traits.

genomics↗