Biology subjects

Smith, M. L.

Publications and source records attributed to Smith, M. L..

52 records · Page 3Linked to original sources

bioRxiv2021

Deep oncopanel sequencing reveals fixation time- and within block position-dependent quality degradation in FFPE processed samples

Clinical laboratories routinely use formalin-fixed paraffin-embedded (FFPE) tissue or cell block cytology samples in oncology panel sequencing to identify mutations that can predict patient response to targeted therapy. To understand the technical error due to FFPE processing, a robustly characterized normal cell line was used to create FFPE samples with four different pre-tissue processing formalin fixation times. A total of 96 FFPE sections were then distributed to different laboratories for targeted sequencing analysis by four oncopanels, and variants resulting from technical error were identified. Tissue sections that failed more frequently showed low cellularity, lower than recommended library preparation DNA input, or target sequencing depth. Importantly, sections from block surfaces were more likely to show FFPE-specific errors, akin to "edge effects" seen in histology, and the depth of formalin damage was related to fixation time. To assure reliable results, we recommend avoiding the block surface portion and restricting mutation detection to genomic regions of high confidence.

cancer biology↗

bioRxiv2021

The frequency and topology of pseudoorthologs

Phylogenetics has long relied on the use of orthologs, or genes related through speciation events, to infer species relationships. However, identifying orthologs is difficult because gene duplication can obscure relationships among genes. Researchers have been particularly concerned with the insidious effects of pseudoorthologs--duplicated genes that are mistaken for orthologs because they are present in a single copy in each sampled species. Because gene tree topologies of pseudoorthologs may differ from the species tree topology, they have often been invoked as the cause of counterintuitive results in phylogenetics. Despite these perceived problems, no previous work has calculated the probabilities of pseudoortholog topologies, or has been able to circumscribe the regions of parameter space in which pseudoorthologs are most likely to occur. Here, we introduce a model for calculating the probabilities and branch lengths of orthologs and pseudoorthologs, including concordant and discordant pseudoortholog topologies, on a rooted three-taxon species tree. We show that the probability of orthologs is high relative to the probability of pseudoorthologs across reasonable regions of parameter space. Furthermore, the probabilities of the two discordant topologies are equal and never exceed that of the concordant topology, generally being much lower. We describe the species tree topologies most prone to generating pseudoorthologs, finding that they are likely to present problems to phylogenetic inference irrespective of the presence of pseudoorthologs. Overall, our results suggest that pseudoorthologs are less of a problem for phylogenetics than currently believed, which should allow researchers to greatly increase the number of genes used in phylogenetic inference. Significance StatementPhylogenetics has long relied on the use of orthologs, or genes related through speciation events, to infer species relationships. However, filtering datasets to include only orthologs is both difficult and restrictive, drastically limiting the amount of data available for phylogenetic inference. Here, we introduce a model to study the probability and topologies of pseudoorthologs--duplicated genes that are mistaken for orthologs because they are present in a single copy in each sampled species. We show that pseudoorthologs are rare and that, even when they are present, they should not mislead phylogenetic inference. Our results suggest that strict filtering to remove pseudoorthologs unnecessarily limits the amount of data used in phylogenetic inference.

evolutionary biology↗

bioRxiv2021

Unbiased profiling of CRISPR RNA-guided transposition products by long-read sequencing

Bacterial transposons propagate through either non-replicative (cut-and-paste) or replicative (copy-and-paste) pathways, depending on how the mobile element is excised from its donor source. In the well-characterized E. coli transposon Tn7, a heteromeric TnsA-TnsB transposase directs cut-and-paste transposition by cleaving both strands at each transposon end during the excision step. Whether a similar pathway is involved for RNA-guided transposons, in which CRISPR-Cas systems confer DNA target specificity, has not been determined. Here, we apply long-read, population-based whole-genome sequencing (WGS) to unambiguously resolve transposition products for two evolutionarily distinct transposon types that employ either Cascade or Cas12k for RNA-guided DNA integration. Our results show that RNA-guided transposon systems lacking functional TnsA primarily undergo copy-and-paste transposition, generating cointegrate products that comprise duplicated transposon copies and insertion of the vector backbone. Finally, we report natural and engineered transposon variants encoding a TnsAB fusion protein, revealing a novel strategy for achieving RNA-guided transposition with fewer molecular components.

molecular biology↗

bioRxiv2020

Social networks predict the life and death of honey bees

In complex societies, individuals roles are reflected by interactions with other conspecifics. Honey bees (Apis mellifera) generally change tasks as they age, but developmental trajectories of individuals can vary drastically due to physiological and environmental factors. We introduce a succinct descriptor of an individuals social network that can be obtained without interfering with the colony. This network age accurately predicts task allocation, survival, activity patterns, and future behavior. We analyze developmental trajectories of multiple cohorts of individuals in a natural setting and identify distinct developmental pathways and critical life changes. Our findings suggest a high stability in task allocation on an individual level. We show that our method is versatile and can extract different properties from social networks, opening up a broad range of future studies. Our approach highlights the relationship of social interactions and individual traits, and provides a scalable technique for understanding how complex social systems function.

animal behavior and cognition↗

bioRxiv2020

A novel framework for characterizing genomic haplotype diversity in the human immunoglobulin heavy chain locus

An incomplete ascertainment of genetic variation within the highly polymorphic immunoglobulin heavy chain locus (IGH) has hindered our ability to define genetic factors that influence antibody and B cell mediated processes. To date, methods for locus-wide genotyping of all IGH variant types do not exist. Here, we combine targeted long-read sequencing with a novel bioinformatics tool, IGenotyper, to fully characterize genetic variation within IGH in a haplotype-specific manner. We apply this approach to eight human samples, including a haploid cell line and two mother-father-child trios, and demonstrate the ability to generate high-quality assemblies (>98% complete and >99% accurate), genotypes, and gene annotations, including 2 novel structural variants and 16 novel gene alleles. We show that multiplexing allows for scaling of the approach without impacting data quality, and that our genotype call sets are more accurate than short-read (>35% increase in true positives and >97% decrease in false-positives) and array/imputation-based datasets. This framework establishes a foundation for leveraging IG genomic data to study population-level variation in the antibody response.

genomics↗

bioRxiv2019

Brain Regional Gene Expression Network Analysis Identifies Unique Interactions Between Chronic Ethanol Exposure and Consumption

Progressive increases in ethanol consumption is a hallmark of alcohol use disorder (AUD). Persistent changes in brain gene expression are hypothesized to underlie the altered neural signaling producing abusive consumption in AUD. To identify brain regional gene expression networks contributing to progressive ethanol consumption, we performed microarray and scale-free network analysis of expression responses in a C57BL/6J mouse model utilizing chronic intermittent ethanol by vapor chamber (CIE) in combination with limited access oral ethanol consumption. This model has previously been shown to produce long-lasting increased ethanol consumption, particularly when combining oral ethanol access with repeated cycles of intermittent vapor exposure. The interaction of CIE and oral consumption was studied by expression profiling and network analysis in medial prefrontal cortex, nucleus accumbens, hippocampus, bed nucleus of the stria terminalis, and central nucleus of the amygdala. Brain region expression networks were analyzed for ethanol-responsive gene expression, correlation with ethanol consumption and functional content using extensive bioinformatics studies. In all brain-regions studied the largest number of changes in gene expression were seen when comparing ethanol naive mice to those exposed to CIE and drinking. In the prefrontal cortex, however, unique patterns of gene expression were seen compared to other brain-regions. Network analysis identified modules of co-expressed genes in all brain regions. The prefrontal cortex and nucleus accumbens showed the greatest number of modules with significant correlation to drinking behavior. Across brain-regions, however, many modules with strong correlations to drinking, both baseline intake and amount consumed after CIE, showed functional enrichment for synaptic transmission and synaptic plasticity.

genomics↗

bioRxiv2019

Germline murine immunoglobulin IGHV genes in wild-derived and classical inbred strains: a comparison

The genomes of classical inbred mouse strains include genes derived from all three major subspecies of the house mouse, Mus musculus. We recently posited that genetic diversity in the immunoglobulin heavy chain (IGH) gene loci of C57BL/6 and BALB/c mice reflect differences in subspecies origin. To investigate this hypothesis, we conducted high-throughput sequencing of IGH gene rearrangements to document IGH variable (IGHV), joining (IGHJ), and diversity (IGHD) genes in four inbred wild-derived mouse strains (CAST/EiJ, LEWES/EiJ, MSM/MsJ, and PWD/PhJ), and a single disease model strain (NOD/ShiLtJ), collectively representing genetic backgrounds of several major mouse subspecies. A total of 341 germline IGHV sequences were inferred in the wild-derived strains, including 247 not curated in the International Immunogenetics Information System. In contrast, 83/84 inferred NOD IGHV genes had previously been observed in C57BL/6 mice. Variability among the strains examined was observed for only a single IGHJ gene, involving a description of a novel allele. In contrast, unexpected variation was found in the IGHD gene loci, with four previously unreported IGHD gene sequences being documented. Very few IGHV sequences of C57BL/6 and BALB/c mice were shared with strains representing major subspecies, suggesting that their IGH loci may be complex mosaics of genes of disparate origins. This suggests a similar level of diversity is likely present in the IGH loci of other classical inbred strains. This must now be documented if we are to properly understand inter-strain variation in models of antibody-mediated disease.

immunology↗

bioRxiv2019

ORF Capture-Seq: a versatile method for targeted identification of full-length isoforms

Most human protein-coding genes are expressed as multiple isoforms. This in turn greatly expands the functional repertoire of the encoded proteome. While at least one reliable open reading frame (ORF) model has been assigned for every gene, the majority of alternative isoforms remains uncharacterized experimentally. This is primarily due to: i) vast differences of overall levels between different isoforms expressed from common genes, and ii) the difficulty of obtaining contiguous full-length ORF sequences. Here, we present ORF Capture-Seq (OCS), a flexible and cost-effective method that addresses both challenges for targeted full-length isoform sequencing applications using collections of cloned ORFs as probes. As proof-of-concept, we show that an OCS pipeline focused on genes coding for transcription factors increases isoform detection by an order of magnitude, compared to unenriched sample. In short, OCS enables rapid discovery of isoforms from custom-selected genes and will allow mapping of the full set of human isoforms at reasonable cost.

genomics↗

bioRxiv2019

Developmental changes in the processing of faces as revealed by EEG decoding

Rapidly and accurately processing information from faces is a critical human function that is known to improve with developmental age. Understanding the underlying drivers of this improvement remains a contentious question, with debate continuing as to the presence of early vs. late maturation of face-processing mechanisms. Recent behavioural evidence suggests an important hallmark of expert face processing - the face inversion effect - is present in very young children, yet neural support for this remains unclear. To address this, we conducted a detailed investigation of the neural dynamics of face-selective processing in children spanning a range of ages (6 - 11 years) and adults. Uniquely, we applied multivariate pattern analysis (MVPA) to the electroencephalogram signal (EEG) to test for the presence of a distinct neural profile associated with canonical upright faces when compared both to other objects (houses) and to inverted faces. Results revealed robust discrimination profiles, at the individual level, of differentiated neural activity associated with broad face categorization and further with its expert processing, as indexed by the face inversion effect, from the youngest ages tested. This result is consistent with an early functional maturation of broad face processing mechanisms. Yet, clear quantitative differences between the response profile of children and adults is suggestive of age-related refinement of this system with developing face and general expertise. Standard ERP analysis also provides some support for qualitative differences in the neural response to inverted faces in children in contrast to adults. This neural profile is in line with recent behavioural studies that have reported impressively expert early face abilities during childhood, while also providing novel evidence of the ongoing neural specialisation between child and adulthood.

neuroscience↗

bioRxiv2018

Decoding dynamic implicit and explicit representations of facial expressions of emotion from EEG

Faces transmit a wealth of important social signals. While previous studies have elucidated the network of cortical regions important for perception of facial expression, and the associated temporal components such as the P100, N170 and EPN, it is still unclear how task constraints may shape the representation of facial expression (or other face categories) in these networks. In the present experiment, we investigate the neural information available across time about two important face categories (expression and identity) when those categories are either perceived under explicit (e.g. decoding emotion when task is on emotion) or implicit task contexts (e.g. decoding emotion when task is on identity). Decoding of both face categories, across both task contexts, peaked in a 100-200ms time-window post-stimulus (across posterior electrodes). Peak decoding of expression, however, was not affected by task context whereas peak decoding of identity was significantly reduced under implicit processing conditions. In addition, errors in EEG decoding correlated with errors in behavioral categorization under explicit processing for both expression and identity, but only with implicit decoding of expression. Despite these differences, decoding time-courses and the spatial pattern of informative electrodes differed consistently for both tasks across explicit Vs implicit face processing. Finally our results show that information about both face identity and facial expression is available around the N170 time-window on lateral occipito-temporal sites. Taken together, these results reveal differences and commonalities in the processing of face categories under explicit Vs implicit task contexts and suggest that facial expressions are processed to a richer degree even under implicit processing conditions, consistent with prior work indicating the relative automaticity by which emotion is processed. Our work further demonstrates the utility in applying multivariate decoding analyses to EEG for revealing the dynamics of face perception.

neuroscience↗

bioRxiv2018

The humungous fungus of Michigan three decades on

In the late 1980s, a genetic individual of the fungus Armillaria gallica that extended over at least 37 hectares of forest floor and encompassed hundreds of tree root systems was discovered on the Upper Peninsula of Michigan. Based on observed growth rates, the individual was estimated to be at least 1500 years old with a mass of more than 105 kg. Nearly three decades on, we returned to the site of individual for new sampling. We report here that the same genetic individual of A. gallica is still alive on its original site, but we estimated that it is older and larger than originally estimated, at least 2,500 years and 4 x 105 kg, respectively. We also show that mutation has occurred within the somatic cells of the individual, reflecting its historical pattern of growth from a single point. The overall rate of mutation, however, was extremely low. The large individual of A. gallica has been remarkably resistant to genomic change as it has persisted in place.

evolutionary biology↗

bioRxiv2018

Tensional homeostasis in multicellular clusters: effects of geometry and traction force dynamics

The ability of cells to maintain a constant level of their cytoskeletal tension in response to external and internal disturbances is referred to as tensional homeostasis. It is essential for the normal physiological function of cells and tissues, and for protection against disease progression, including atherosclerosis and cancer. It has been shown recently that some cell types, such as endothelial cells, can maintain tensional homeostasis only when they form multicellular clusters, whereas other cell types, such as fibroblasts, do not require clustering for tensional homeostasis. For example, measurements of cell-extracellular matrix traction forces have shown that temporal fluctuations of the traction field in clusters of endothelial cells become progressively attenuated with increasing number of cells in the cluster, whereas in fibroblasts cell clustering does not influence traction field variability. Mechanisms that are responsible for these observations are largely unknown. In this study, a theoretical analysis and mathematical modeling have been applied to analyze experimental data obtained previously from traction microscopy measurements in order to investigate possible physical mechanisms that influence temporal variability of the traction field in multicellular forms. The focus of the analysis is on the contribution of dynamics and distribution of focal adhesion traction forces in conjunction with geometrical shape and size of multicellular clusters. Results of the analysis revealed that cluster size, magnitude and temporal fluctuations of focal adhesion traction forces have a major influence on traction field variability, whereas the influence of cluster shape appears to be minor.

biophysics↗

bioRxiv2018

Disentangling the process of speciation using machine learning

Historically, investigations into the processes driving speciation have largely been isolated from systematic investigations into species limits. Recent advances in sequencing technology have led to a rapid increase in the availability of genomic data, and this, in turn, has led to the introduction of many novel methods for species delimitation. However, these methods have been limited to divergence-only scenarios and have not attempted to evaluate complex modes of speciation, such as those that include gene flow during early stages of divergence (sympatric speciation) or population size changes (founder effect speciation). To address this shortcoming, we introduce delimitR, an approach that enables biologists to infer species boundaries and evaluate the demographic processes that may have led to speciation. delimitR uses the binned multidimensional Site Frequency Spectrum and a machine-learning algorithm (Random Forests) to compare speciation models. We use simulations to evaluate the accuracy of delimitR. When comparing models that include lineage divergence and gene flow for three populations, error rates are near zero with recent divergence times (<100,000 generations) and a modest number of Single Nucleotide Polymorphisms (SNPs; 1,500). When applied to a more complex model set (including divergence, gene flow, and population size changes), error rates are moderate (~0.15 with 10,000 SNPs), and misclassifications are generally between highly similar models. We also evaluate the utility of delimitR using three previously published datasets and find results that corroborate previous findings. Our analyses indicate that delimitR can serve as an important conceptual bridge uniting various investigations into the process of speciation.

evolutionary biology↗

bioRxiv2017

Amplification-free, CRISPR-Cas9 Targeted Enrichment and SMRT Sequencing of Repeat-Expansion Disease Causative Genomic Regions

Targeted sequencing has proven to be an economical means of obtaining sequence information for one or more defined regions of a larger genome. However, most target enrichment methods require amplification. Some genomic regions, such as those with extreme GC content and repetitive sequences, are recalcitrant to faithful amplification. Yet, many human genetic disorders are caused by repeat expansions, including difficult to sequence tandem repeats.\n\nWe have developed a novel, amplification-free enrichment technique that employs the CRISPR-Cas9 system for specific targeting multiple genomic loci. This method, in conjunction with long reads generated through Single Molecule, Real-Time (SMRT) sequencing and unbiased coverage, enables enrichment and sequencing of complex genomic regions that cannot be investigated with other technologies. Using human genomic DNA samples, we demonstrate successful targeting of causative loci for Huntingtons disease (HTT; CAG repeat), Fragile X syndrome (FMR1; CGG repeat), amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (C9orf72; GGGGCC repeat), and spinocerebellar ataxia type 10 (SCA10) (ATXN10; variable ATTCT repeat). The method, amenable to multiplexing across multiple genomic loci, uses an amplification-free approach that facilitates the isolation of hundreds of individual on-target molecules in a single SMRT Cell and accurate sequencing through long repeat stretches, regardless of extreme GC percent or sequence complexity content. Our novel targeted sequencing method opens new doors to genomic analyses independent of PCR amplification that will facilitate the study of repeat expansion disorders.

genomics↗

bioRxiv2017

beachmat: a Bioconductor C++ API for accessing single-cell genomics data from a variety of R matrix types

Recent advances in single-cell RNA sequencing have dramatically increased the number of cells that can be profiled in a single experiment. This provides unparalleled resolution to study cellular heterogeneity within biological processes such as differentiation. However, the explosion of data that are generated from such experiments poses a challenge to the existing computational infrastructure for statistical data analysis. In particular, large matrices holding expression values for each gene in each cell require sparse or file-backed representations for manipulation with the popular R programming language. Here, we describe a C++ interface named beachmat, which enables agnostic data access from various matrix representations. This allows package developers to write efficient C++ code that is interoperable with simple, sparse and HDF5-backed matrices, amongst others. We perform simulations to examine the performance of beachmat on each matrix representation, and we demonstrate how beachmat can be incorporated into the code of other packages to drive analyses of a very large single-cell data set.

bioinformatics↗

bioRxiv2017

Telomerecat: A Ploidy-Agnostic Method For Estimating Telomere Length From Whole Genome Sequencing Data

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, technical replicates, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype.

bioinformatics↗