Biology subjects

Graham, J.

Publications and source records attributed to Graham, J..

28 records · Page 2Linked to original sources

bioRxiv2020

High-frequency stimulation of ventral CA1 neurons reduces amygdala activity and inhibits fear

The hippocampus can be divided into distinct segments that make unique contributions to learning and memory. The dorsal hippocampus supports cognitive processes like spatial learning and navigation while the ventral hippocampus regulates emotional behaviors related to fear, anxiety and reward. In the current study, we determined how pyramidal cells in ventral CA1 respond to spatial cues and aversive stimulation during a context fear conditioning task. We also examined the effects of high and low frequency stimulation of these neurons on defensive behaviors. Similar to previous work in the dorsal hippocampus, we found that cells in ventral CA1 expressed high-levels of c-Fos in response to a novel spatial environment. Surprisingly, however, the number of activated neurons did not increase when the environment was subsequently paired with footshock. This was true even in the subpopulation of ventral CA1 pyramidal cells that send direct projections to the amygdala. When these cells were stimulated at high-frequencies (20-Hz), we observed feedforward inhibition of basal amygdala neurons and impaired expression of context fear. In contrast, low-frequency stimulation (4-Hz) did not inhibit principal cells in the amygdala and produced a slight increase in fear generalization. Similar results have been reported in dorsal CA1. Therefore, despite the clear differences between the dorsal and ventral hippocampus, CA1 neurons in each segment appear to make similar contributions to context fear conditioning.

neuroscience↗

bioRxiv2020

Ultra-deep sequencing differentiates patterns of skin clonogenic mutations associated with sun-exposure status

Non-melanoma skin cancer is the most common human malignancy and is primarily caused by exposure to ultraviolet (UV) radiation. The earliest detectable precursor of UV-mediated skin cancer is the growth of cell groups harboring clonal mutation (CM) in clinically normal appearing skin. Systematic evaluation of CMs is crucial to understand early photo-carcinogenesis. Previous studies confirmed the presence of CMs in sun-exposed skin. However, the relationship between UV-exposure and the accumulation of CMs, and the correlation of CMs with skin cancer risk remain poorly understood. To elucidate the exact molecular and clinical effects of long-term UV-exposure on skin, we performed targeted ultra-deep sequencing in 450 individual-matched sun-exposed (SE) and non-sun-exposed (NE) epidermal punch biopsies obtained from clinically normal skin from 13 donors. A total of 638 CMs were identified, including 298 UV-signature mutations (USMs). The numbers of USMs per sample were three times higher in the SE samples and were associated with significantly higher variant allele frequencies (VAFs), compared with the NE samples. We identified genomic regions in TP53, NOTCH1 and GRM3 where mutation burden was significantly associated with UV-exposure. Six mutations were almost exclusively present in SE epidermis and accounted for 42% of the overall difference between SE and NE mutation burden. We defined Cumulative Relative Clonal Area (CRCA), a single metric of UV-damage calculated by the overall relative percentage of the sampled skin area affected by CMs. The CRCA was dramatically elevated by a median of 11.2 fold in SE compared to NE samples. In an extended cohort of SE normal skin samples from patients with a high- or low-burden of cutaneous squamous cell carcinoma (cSCC), the SE samples in high-cSCC patients contained significantly more USMs than SE samples in low-cSCC patients, with the difference mostly conferred by mutations from low-frequency clones (defined by VAF≤1%) but not expanded clones (VAF>1%). Our studies of differential mutational features in normal skin between paired SE/NE body sites and high/low-cSCC patients provide novel insights into the carcinogenic effect of UV exposure, and suggest CMs might be used to develop novel biomarkers for predicting cancer risk.Significance statement In UV radiation exposed skin, mutations fuel clonal cell growth. We established a sequencing-based method to objectively assess the mutational differences between sun-exposed (SE) and non-sun-exposed (NE) areas of normal human skin. Striking differences, in both the numbers of mutations and variant allele frequencies, were found between SE and NE areas. Furthermore, we identified specific genomic regions where mutation burden is significantly associated with UV-exposure status. These findings revealed previously unknown mutational patterns associated with UV-exposure, providing important insights into UV radiation’s early carcinogenic effects. Additionally, in an extended cohort, we identified preliminary association between normal skin mutation burden and cancer risk. These findings pave the road for future development of quantitative measurement of subclinical UV damage and skin cancer risk.Competing Interest StatementThe authors have declared no competing interest.Common AbbreviationsUVUltravioletCMClonogenic mutationNMSCNonmelanoma skin cancerSESun-exposedNENon-sun-exposedUSMUV-signature mutationNUSMNon-UV-signature mutationCRCACumulative Relative Clonal AreacSCCCutaneous squamous cell carcinomaAKActinic keratosisSNVSingle nucleotide variant Indels – Insertions/deletionsDNVDinucleotide variantCSNVCluster of single nucleotide variantMACMulti-Nucleotide Variant Annotation CorrectorVAFVariant allele frequencyView Full Text

cancer biology↗

bioRxiv2019

perfectphyloR: An R package for reconstructing perfect phylogenies

BackgroundA perfect phylogeny is a rooted binary tree that recursively partitions sequences. The nested partitions of a perfect phylogeny provide insight into the pattern of ancestry of genetic sequence data. For example, sequences may cluster together in a partition indicating that they arise from a common ancestral haplotype. ResultsWe present an R package perfectphyloR to reconstruct the local perfect phylogenies underlying a sample of binary sequences. The package enables users to associate the reconstructed partitions with a user-defined partition. We describe and demonstrate the major functionality of the package. ConclusionThe perfectphyloR package should be of use to researchers seeking insight into the ancestral structure of their sequence data. The reconstructed partitions have many applications, including the mapping of trait-influencing variants.

genetics↗

bioRxiv2019

Co-reviewing and ghostwriting by early career researchers in the peer review of manuscripts

The goal of this study is to shed light on the involvement of early career researchers (ECRs) during peer review of manuscripts for publication in journals. In particular, we sought to better understand how commonly ECRs contribute ideas and/or text to peer review reports when they are not the invited reviewer (\"co-review\"), and how commonly ECRs do not receive named credit to the journal editorial staff for these scholarly efforts (\"ghostwrite\"). First, we evaluated 1,952 publications in the peer-reviewed literature generated by exhaustive search terms that combined synonyms of \"early career researcher\" and \"peer review\" and found no previous studies about ECRs ghostwriting peer review reports. We then surveyed 498 researchers about their experiences with, and opinions about, co-reviewing and ghostwriting as ECRs. Three quarters of those surveyed have co-reviewed and most find it to be a beneficial (95% agree) and ethical (73% agree) form of training in peer review. Co-reviewing is the second most commonly reported form of training in peer review besides receiving reviews on ones own papers. Half of survey respondents have ghostwritten a peer review report, despite the 4/5ths majority opinion that ghostwriting is unethical. Survey respondents report that the three major barriers to including co-reviewer names on peer review reports are: a lack of communication between PIs and ECRs; a false belief that co-authorship is for manuscripts but not peer review reports; and prohibitive journal policies that are out of alignment with current practice and opinions about best practice. We therefore propose recommendations for changing this status quo, to discourage unethical ghostwriting of peer review reports and encourage quality co-reviewing experiences as normal training in peer review.

scientific communication and education↗

bioRxiv2019

Diverse commensal E. coli clones and plasmids disseminate antimicrobial resistance genes in domestic animals and children in a semi-rural community in Ecuador

The increased prevalence of antimicrobial resistance (AMR) among Enterobacteriaceae has had major clinical and economic impacts in human medicine. Many of the multi-drug resistant (MDR) Enterobacteriaceae found in humans are community-acquired and linked to food animals (i.e. livestock raised for meat and dairy products). In this study, we examined whether numerically dominant, commensal Escherichia coli strains from humans (n=63 isolates) and domestic animals (n=174 isolates) in the same community and with matching phenotypic AMR patterns, were clonally related or shared the same plasmids. We identified 25 multi-drug resistant isolates (i.e. resistant to 3 or more antimicrobial classes) that shared identical phenotypic resistance patterns. We then investigated the diversity of E. coli clones, AMR genes and plasmids carrying the AMR genes using conjugation, replicon typing and whole genome sequencing. None of the MDR E. coli isolates (from children and domestic animals) analyzed were clonal. While the majority of isolates shared the same antimicrobial resistance genes and replicons, DNA sequencing indicated that these genes and replicons were found on different plasmid structures. Our findings suggest that nonclonal resistance gene dissemination is common in this community and that diverse plasmids carrying AMR genes presents a significant challenge for understanding the movement of AMR in a community.\n\nIMPORTANCEEven though Escherichia coli strains may share nearly identical AMR profiles, AMR genes, and overlap in space and time, the diversity of clones and plasmids challenges to research that aims to identify sources of AMR. Horizontal gene transfer appears to play a much larger role than clonal expansion in the spread of AMR in the community.

microbiology↗

bioRxiv2019

SimRVSequences: an R package to simulate genetic sequence data for pedigrees

1SummaryFamily-based studies have several advantages over case-control studies for finding causal rare variants for a disease; these include increased power, smaller sample size requirements, and improved detection of sequencing errors. However, collecting suitable families and compiling their data is time-consuming and expensive. To evaluate methodology to identify causal rare variants in family-based studies, one can use simulated data. For this purpose we present the R package SimRVSequences. Users supply a sample of pedigrees and single-nucleotide variant data from a sample of unrelated individuals representing the pedigree founders. Users may also model genetic heterogeneity among families. For ease of use, SimRVSequences offers methods to import and format single-nucleotide variant data and pedigrees from existing software.\n\nAvailability and ImplementationSimRVSequences is available as a library for R[≥] 3.5.0 on the comprehensive R archive network.

genetics↗

bioRxiv2018

Insights from Comparison of the Renal and Skin Single Cell Transcriptomes in Lupus Nephritis

Lupus nephritis (LN) occurs in up to 50% of patients with systemic lupus erythematosus (SLE), and is a major contributor to mortality and morbidity. LN presents as a highly heterogeneous disease both in histopathology and response to therapy. The molecular and cellular processes leading to renal damage and to the heterogeneity of the disease are not well understood. To elucidate the processes underpinning the heterogeneity of LN, we applied singlecell RNA-sequencing (scRNA-seq) to renal biopsies from LN patients. Skin biopsies were evaluated as a source of biomarkers for monitoring kidney disease. Type-I interferon (IFN) response signatures were identified in tubular cells and keratinocytes, differentiating LN patients from healthy controls. Non-responders associated with higher IFN signatures in both tissue compartments. Moreover, non-response was also associated with a fibrotic signature in the tubular cells. Receptor-ligand interaction analysis indicated that the fibrotic process is likely mediated by FGF receptors with the initiating signal originating from infiltrating leukocytes. Differential expression analysis of tubular cells between proliferative and membranous LN pointed to several fibrosis-relevant pathways, which may offer insight into their histological differences. In summary, scRNA-seq was applied to LN to deconstruct its heterogeneity and provide novel targets for personalized approaches to therapy.

immunology↗

bioRxiv2017

Simulating Pedigrees Ascertained for Multiple Disease-Affected Relatives

Background: Studies that ascertain families containing multiple relatives affected by disease can be useful for identification of causal, rare variants from next-generation sequencing data.\n\nResults: We present the R package SimRVPedigree, which allows researchers to simulate pedigrees ascertained on the basis of multiple, affected relatives. By incorporating the ascertainment process in the simulation, SimRVPedigree allows researchers to better understand the within-family patterns of relationship amongst affected individuals and ages of disease onset.\n\nConclusions: Through simulation, we show that affected members of a family segregating a rare disease variant tend to be more numerous and cluster in relationships more closely than those for sporadic disease. We also show that the family ascertainment process can lead to apparent anticipation in the age of onset. Finally, we use simulation to gain insight into the limit on the proportion of ascertained families segregating a causal variant. SimRVPedigree should be useful to investigators seeking insight into the family-based study design through simulation.

genetics↗

bioRxiv2017

Using gene genealogies to localize rare variants associated with complex traits in diploid populations

Background and AimsMany methods can detect trait association with causal variants in candidate genomic regions; however, a comparison of their ability to localize causal variants is lacking. We extend a previous study of the detection abilities of these methods to a comparison of their localization abilities.\n\nMethodsThrough coalescent simulation, we compare several popular association methods. Cases and controls are sampled from a diploid population to mimic human studies. As benchmarks for comparison, we include two methods that cluster phenotypes on the true genealogical trees, a naive Mantel test considered previously in haploid populations and an extension that takes into account whether case haplotypes carry a causal variant. We first work through a simulated dataset to illustrate the methods. We then perform a simulation study to score the localization and detection properties.\n\nResultsIn our simulations, the association signal was localized least precisely by the naive Mantel test and most precisely by its extension. Most other approaches had intermediate performance similar to the single-variant Fishers-exact test.\n\nConclusionsOur results confirm earlier findings in haploid populations about potential gains in performance from genealogy-based approaches. They also highlight differences between haploid and diploid populations when localizing and detecting causal variants.

genetics↗

bioRxiv2016

Multivariate association between single-nucleotide polymorphisms in Alzgene linkage regions and structural changes in the brain: discovery, refinement and validation

Both genetic variants and brain region abnormalities are recognized to play a role in cognitive decline. We explore the association between singlenucleotide polymorphisms (SNPs) in linkage regions for Alzheimers disease and rates of decline in brain structure using data from the Alzheimers Disease Neuroimaging Initiative (ADNI).\n\nIn an initial discovery stage, we assessed the presence of linear association between the minor allele counts of 75,845 SNPs in the Alzgene linkage regions and predicted rates of change in structural MRI measurements for 56 brain regions using an RV test. In a second, refinement stage, we reduced the number of SNPs using a bootstrap-enhanced sparse canonical correlation analysis (SCCA) with a fixed tuning parameter. Each SNP was assigned an importance measure proportional to the number of times it was estimated to have a nonzero coefficient in repeated re-sampling from the ADNI-1 sample. We created refined lists of SNPs based on importance probabilities greater than 50% and 90%, respectively. In a third, validation stage, we assessed the multivariate association between these refined lists of SNPs and the rates of structural change in the independent ADNI-2 study dataset.\n\nThere was strong statistical evidence for linear association between the SNPs in the Alzgene linkage regions and the 56 imaging phenotypes in both the ADNI-1 and ADNI-2 samples (p < 0.0001). The bootstrap-enhanced SCCA identified 1,694 priority SNPs with importance probabilities > 50% and 22 SNPs with importance probabilities > 90%. The 1,694 prioritized SNPs in the ADNI-1 data were associated with imaging phenotypes in the ADNI-2 data (p = 0.0021).\n\nThis manuscript presents an analysis that addresses challenges in current imaging genetics studies such as biased sampling designs and highdimensional data with low-signal. Genes corresponding to priority SNPs having the highest contribution in the validation data have previously been implicated or hypothesized to be implicated in AD, including GCLC, IDE, and STAMBP1andFAS. We hypothesize that the effect sizes of the 1,694 SNPs in the priority set are likely small, but further investigation within this set may advance understanding of the missing heritability in late-onset Alzheimers disease. Multivariate analysis; Linkage regions; Imaging genetics; Endophenotypes; Inverse probability weighting; Variable importance probabilities

neuroscience↗