Biology subjects

Martin, C. D.

Publications and source records attributed to Martin, C. D..

9 recordsLinked to original sources

bioRxiv2026

Genomic SEM reveals shared genetic architecture and expands locus discovery for locomotor activity in heterogeneous stock rats

Locomotor response to a novel environment is a heritable, addiction-relevant behavioral phenotype in rodents. We characterized its genetic basis in 9,341 male and female heterogeneous stock (HS) rats from eight studies. Locomotor activity was heritable across studies, while pairwise genetic correlations were positive but variable, indicating shared yet nonidentical genetic influences. Given nonuniform genetic architecture, we compared three complementary approaches to locus discovery that analyzed SNP effects 1) on a pooled locomotor phenotype (MEGA), 2) across studies under a fixed-effect model (METAL), or 3) on a shared genetic factor (Genomic SEM). To ensure comparability, all three locus-discovery approaches were applied to a common subset of seven studies. Together, these approaches identified 38 loci, with both convergence and method-specific discovery across analyses. Genomic SEM identified 31 loci, compared to 8 for MEGA and 13 for METAL. To interpret the loci, we integrated brain molecular QTLs, predicted coding and splice consequences, and open-field locomotor phenotypes from knockouts of orthologous mouse genes. Our results highlighted established neurobehavioral candidates spanning locomotor and reward-related biology (Negr1 and Lmo4), serotonergic signaling (Htr1b), and GABAergic signaling (Gabrg2), as well as relatively novel genes including Tcerg1l, Pcdh10, and Tmem132e. Our results illustrate how Genomic SEM can integrate genetically correlated yet heterogeneous behavioral measures and enable discovery of loci underlying their shared genetic architecture, highlighting its utility for complex-trait studies in rodents.

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

Are you talking to me? How the choice of speech register impacts listeners' hierarchical encoding of speech.

Speakers accommodate their speech to meet the needs of their listeners, producing different speech registers. One such register is Foreigner-Directed Speech (FDS), which is the way native speakers address non-native listeners, typically characterized by features such as slow speech rate and phonetic exaggeration. Here, we investigated how register impacts the cortical encoding of speech at different levels of language integration. Specifically, we tested the hypothesis that enhanced comprehension of FDS compared with Native-Directed Speech (NDS) involves more than just a slower speech rate, influencing speech processing from acoustic to semantic levels. Electroencephalography (EEG) signals were recorded from Spanish native listeners, who were learning English (L2 learners), and English native listeners (L1 listeners) as they were presented with audio-stories. Speech was presented in English in three different speech registers: FDS, NDS and a control register (Slow-NDS) which is slowed down version of NDS. We measured the cortical tracking of acoustic, phonological, and semantic information with a multivariate temporal response function analysis (TRF) on the EEG signals. We found that FDS promoted L2 learners cortical encoding at all the levels of speech and language processing considered. First, FDS led to a more pronounced encoding of the speech envelope. Second, phonological encoding was more refined when listening to FDS, with phoneme perception getting closer to that of L1 listeners. Finally, FDS also enhanced the TRF- N400, a neural signature of lexical expectations. Conversely FDS impacted acoustic but not linguistic speech encoding in L1 listeners. Taken together, these results support our hypothesis that FDS accommodates speech processing in L2 listeners beyond what can be achieved by simply speaking slowly, impacting the cortical encoding of sound and language at different abstraction levels. In turn, this study provides objective metrics that are sensitive to the impact of register on the hierarchical encoding of speech, which could be extended to other registers and cohorts.

neuroscience↗

bioRxiv2023

The impact of speaker accent on discourse processing: a frequency investigation

Previous studies show that there are differences in native and foreign speech processing (Lev-Ari, 2018) while mixed evidence has been found regarding differences between dialectal and foreign accent processing (see: Adank et al., 2009; Floccia et al. 2006 but see also: Floccia et al., 2009; Girard et al., 2008). Within this field, two theories have been proposed. The Perceptual Distance Hypothesis states that the mechanisms underlying dialectal accent processing are attenuated versions of those of foreign (Clarke & Garrett, 2004). While, the Different Processes Hypothesis argues that the mechanisms of foreign and dialectal accent processing are qualitatively different (Floccia et al, 2009). A recent study looking at single-word EEG data, suggested that there may be flexibility in processing mechanisms (Thomas et al., 2022). The present study deepens this investigation by addressing in which frequency bands native, dialectal and foreign accent processing differ when listening to extended speech. Electroencephalographic data was recorded from 30 participants who listened to dialogues of approximately six minutes spoken in native, dialectal and foreign accents. Power spectral density estimation (1-35 hz) was performed. Linear mixed models were done in frequency windows of particular relevance to discourse processing. Frequency bands associated with phoneme [gamma], syllable [theta], and prosody [delta] were considered along with those of general cognitive mechanisms [alpha and beta]. Results show power differences in the Gamma frequency range. While in higher frequency ranges foreign accent processing is differentiated from power amplitudes of native and dialectal accent processing, in low frequencies we do not see any accent-related power amplitude modulations. This suggests that there may be a difference in phoneme processing for native accent types and foreign accent, while we speculate that top-down mechanisms during discourse processing may mitigate the effects observed with short units of speech.

neuroscience↗

bioRxiv2023

Environmental enrichment promotes adaptive responding during tests of behavioral regulation in male heterogeneous stock rats

Organisms must regulate their behavior flexibly in the face of environmental challenges. Failure can lead to a host of maladaptive behavioral traits associated with a range of neuropsychiatric disorders, including attention deficit hyperactivity disorder, autism, and substance use disorders. This maladaptive dysregulation of behavior is influenced by genetic and environmental factors. For example, environmental enrichment produces beneficial neurobehavioral effects in animal models of such disorders. The present study determined the effects of environmental enrichment on a range of measures related to behavioral regulation using a large cohort of male, outbred heterogeneous stock (HS) rats as subjects to mimic the genetic variability found in the human population. Subjects were reared from late adolescence onwards either in pairs in standard housing with minimal enrichment (n=200) or in groups of 16 in a highly enriched environment consisting of a large multi-level cage filled with toys, running wheels, and shelters (n=64). Rats were subjected to a battery of tests, including: (i) locomotor response to novelty, (iI) light reinforcement, (iii) social reinforcement, (iv) reaction time, (v) a patch-depletion foraging test, (vi) Pavlovian conditioned approach, (vii) conditioned reinforcement, and (viii) cocaine conditioned cue preference. Results indicated that rats housed in the enriched environment were able to filter out irrelevant stimuli more effectively and thereby regulate their behavior more efficiently than standard-housing rats. The dramatic impact of environmental enrichment suggests that behavioral studies using standard housing conditions may not generalize to more complex environments that may be more ethologically relevant.

animal behavior and cognition↗

bioRxiv2023

Automated quantitative trait locus analysis (AutoQTL)

BackgroundQuantitative Trait Locus (QTL) analysis and Genome-Wide Association Studies (GWAS) have the power to identify variants that capture significant levels of phenotypic variance in complex traits. However, effort and time are required to select the best methods and optimize parameters and pre-processing steps. Although machine learning approaches have been shown to greatly assist in optimization and data processing, applying them to QTL analysis and GWAS is challenging due to the complexity of large, heterogenous datasets. Here, we describe proof-of-concept for an automated machine learning approach, AutoQTL, with the ability to automate many complex decisions related to analysis of complex traits and generate diverse solutions to describe relationships that exist in genetic data. ResultsUsing a dataset of 18 putative QTL from a large-scale GWAS of body mass index in the laboratory rat, Rattus norvegicus, AutoQTL captures the phenotypic variance explained under a standard additive model while also providing evidence of non-additive effects including deviations from additivity and 2-way epistatic interactions from simulated data via multiple optimal solutions. Additionally, feature importance metrics provide different insights into the inheritance models and predictive power of multiple GWAS-derived putative QTL. ConclusionsThis proof-of-concept illustrates that automated machine learning techniques can be applied to genetic data and has the potential to detect both additive and non-additive effects via various optimal solutions and feature importance metrics. In the future, we aim to expand AutoQTL to accommodate omics-level datasets with intelligent feature selection strategies.

genetics↗

bioRxiv2022

Polygenic Transcriptome Risk Scores Can Translate Genetic Results Between Species

Genome-wide association studies (GWAS) have implicated specific alleles and genes as risk factors for numerous complex traits. However, translating GWAS results into biologically and therapeutically meaningful discoveries remains extremely challenging. Most GWAS results identify noncoding regions of the genome, suggesting that differences in gene regulation are the major driver of trait variability. To better integrate GWAS results with gene regulatory polymorphisms, we previously developed PrediXcan (also known as "transcriptome-wide association studies" or TWAS), which maps SNPs to predicted gene expression using GWAS data. In this study, we developed RatXcan, a framework that extends this methodology to outbred heterogeneous stock (HS) rats. RatXcan accounts for the close familial relationships among HS rats by modeling the relatedness with a random effect that encodes the genetic relatedness. RatXcan also corrects for polygenic-driven inflation because of the equivalence between a relatedness random effect and the infinitesimal polygenic model. To develop RatXcan, we trained transcript predictors for 8,934 genes using reference genotype and expression data from five rat brain regions. We found that the cis genetic architecture of gene expression in both rats and humans was sparse and similar across brain tissues. We tested the association between predicted expression in rats and two example traits (body length and BMI) using phenotype and genotype data from 5,401 densely genotyped HS rats and identified a significant enrichment between the genes associated with rat and human body length and BMI. Thus, RatXcan represents a valuable tool for identifying the relationship between gene expression and phenotypes across species and paves the way to explore shared biological mechanisms of complex traits. Author SummaryUnderstanding how genetic variation affects phenotypic variation is critical to leveraging the wealth of genetic studies to make biologically and therapeutically useful discoveries. Since most of the genetic loci associated with complex diseases are regulatory in nature--meaning that they do not alter protein coding but rather subtly affect gene expression--transcriptome-wide association studies have been developed. However, these apply only to human data where large samples of unrelated individuals are available. For animal models, relatedness is much higher, causing higher false-positive rates. We propose a computationally efficient method to address this problem and find shared biology between humans and rats. Taken together, our development paves the way to further explore shared biological mechanisms of complex traits across species.

genomics↗

bioRxiv2022

Quantitative Isothermal Amplification on Paper Membranes using Amplification Nucleation Site Analysis

Quantitative nucleic acid amplification tests (qNAATs) are critical in treating infectious diseases, such as in HIV viral load monitoring or SARS-CoV-2 testing, in which viral load indicates viral suppression or infectivity. Quantitative PCR is the gold standard tool for qNAATs; however, there is a need to develop point-of-care (POC) qNAATs to manage infectious diseases in outpatient clinics, low- and middle-income countries, and the home. Isothermal amplification methods are an emerging tool for POC NAATs as an alternative to traditional PCR-based workflows. Previous works have focused on relating isothermal amplification bulk fluorescence signals to input copies of target nucleic acids for sample quantification with limited success. In this work, we show that recombinase polymerase amplification (RPA) reactions on paper membranes exhibit discrete fluorescent amplification nucleation sites. We demonstrate that the number of nucleation sites can be used to quantify HIV-1 DNA and RNA in less than 20 minutes. An image-analysis algorithm quantifies nucleation sites and determines the input nucleic acid copies in the range of 67-3,000 copies per reaction. We demonstrate a mobile phone-based system for image capture and onboard processing, illustrating that this method may be used at the point-of-care for qNAATs with minimal instrumentation.

molecular biology↗

bioRxiv2018

Functional connectivity reveals dissociable ventrolateral prefrontal mechanisms for the control of multilingual word retrieval

A fundamental cognitive operation involved in speech production is word retrieval from the mental lexicon, which in monolinguals is supported by dissociable ventro-lateral prefrontal cortex (vlPFC) mechanisms associated with proactive and reactive control. This functional magnetic resonance imaging (fMRI) study established whether in multilinguals word retrieval is supported by the same prefrontal mechanisms, and whether proactive modulation consists in suppression of the non-target lexicon. Healthy multilingual volunteers participated in a task that required them to name pictures alternatively in their dominant and less-dominant language. Two crucial variables were manipulated: the cue-target interval (CTI) to either engage (long CTI) or prevent proactive control processes (short CTI), and the cognate status of the pictures to-be-named (non-cognates versus cognates) to capture the presence of selective pre-activation of the target language. Results support the two-process account of vlPFC and indicate that multilinguals engage in proactive control to prepare the target language. This proactive modulation, enacted by anterior vlPFC, is achieved by boosting the activation of lexical representations of the target language. Control processes supported by mid-vlPFC and left inferior parietal lobe together, are similarly engaged in pre-and post-word retrieval, possibly exerted on phonological representations to reduce cross-language interference.\n\nSignificance Statement\n\nWord retrieval in monolingual speech production is enacted by left ventro-lateral prefrontal cortex (vlPFC) supporting controlled access to conceptual representations (proactive control), and left mid-vlPFC supporting post-retrieval lexical selection (reactive control). In this functional magnetic resonance imaging (fMRI) study we demonstrate that multilingual word retrieval is supported by similar prefrontal mechanisms. However, differently from monolinguals, multilingual speakers retrieve words by applying proactive control on lexical representations to reduce cross-language interference. Alternatively to what it has been proposed by one of the most influential models, here we show that this proactive modulation is achieved by boosting the activation of lexical representations of the target language.

neuroscience↗