Biology subjects

Chapman, M. A.

Publications and source records attributed to Chapman, M. A..

13 recordsLinked to original sources

bioRxiv2026

Human neurodevelopmental genes housed in massive, ancient gene deserts

Mammalian genomes contain a remarkable proportion of non-coding sequence relative to protein-coding sequence, including megabase-scale gene deserts. The origin of gene deserts and their function have long been mysteries, and most studies probing these questions have focused on specific deserts linked to transcription factors, like SOX9 and MYC. Here, we describe 21 human "lonely genes" located within some of the largest deserts in the genome, making them exceptionally isolated from other genes in linear sequence space. Together, these regions comprise roughly 3.4% of the human genome. Despite minimal sequence conservation, we find that the sizes and locations of these gene deserts are conserved, and they likely originated at the root of the vertebrate tree. In contrast to the deserts near transcription factors that have been the primary focus to date, we find that most genes housed within these massive deserts, as well as genes on the edges of deserts, are cell adhesion molecules. Additionally, many of the genes associated with these deserts are dysregulated in datasets involving chromatin modifiers linked to neurodevelopmental disorders. Using DNA FISH in mouse olfactory epithelium, we find that lonely genes appose the nuclear lamina. We propose that these ancient regions may play a structural role in the nucleus, and that this structure makes the genes within them uniquely difficult to express. While specific chromatin modifiers are able to access lonely genes, this dependence creates a regulatory vulnerability in brain development.

evolutionary biology↗

bioRxiv2025

A wild genome of the underutilized legume lablab (Lablab purpureus) reveals the genetic basis of domestication

BackgroundWith global food security threatened by climate change and the growing global population, underutilized crops offer sustainable solutions for diversifying current agricultural systems. Lablab (Lablab purpureus) is a highly versatile, climate-resilient underutilized legume native to Africa and widely, but locally, cultivated in Asia with untapped potential for sustainable agriculture. However, the lack of wild genome resource prevents a comprehensive genome utilization research for this underutilized crop. This paper presents the first chromosome-scale genome of wild lablab with its complete gene annotation and provides comprehensive population genomic analyses of its evolution and domestication by resequencing a panel of wild and domesticated accessions. ResultsThe genome was assembled into a total size of 478.2 Mb with a scaffold N50 of 39.7 Mb, and 96.4% (460.8 Mb) of the scaffolds anchored to 11 pseudochromosomes, the haploid chromosome number of lablab. We demonstrated that domestication was likely in Africa with several subsequent instances of transportation into Asia. Our analyses identified selective sweeps resulting from domestication as well as pseudogenes associated with yield-related traits and stress tolerance, representing candidate genes for further validation and targets for future breeding programs. ConclusionsOur genomic resource for wild lablab delineated its domestication history and identified key genes and pseudogenes under selection, bridging the gap between its untapped wild diversity and breeding for improved stress resilience and yield in underutilized legumes. This offers genomic and genetic insights for crop improvement of lablab.

evolutionary biology↗

bioRxiv2025

Transcriptomic Profiling of scWAT Reveals Reduced Lipid-Associated Macrophage Signatures in Long-Term Endurance- and Resistance-Trained Athletes

Regular exercise training is associated with systemic and tissue-specific performance and health benefits, yet long-term molecular adaptations in subcutaneous abdominal white adipose tissue (scWAT) remain unclear. We analyzed the resting scWAT transcriptome of 89 adults (35-50 years) who were long-term (>15 years) endurance- or strength-trained, or untrained. Long-term training was linked to enrichment of ribosomal, mitochondrial, and aerobic metabolism-related pathways, while immune-related pathways were enriched in untrained individuals. A distinct sex dimorphic scWAT was identified: untrained females exhibited a more metabolically favorable, trained-like transcriptomic profile, and untrained males an untrained-like profile. In trained males, the inflammatory gene signature was lower than in untrained males. We also identified 11 genes specific to lipid-associated macrophages with lower expression in trained individuals, particularly in all endurance-trained individuals and strength-trained females. These findings highlight sex-specific, exercise-induced adaptations in scWAT relevant to metabolic health, and underscore the importance of including both sexes in scWAT research.

physiology↗

bioRxiv2023

Molecular profiling of high-level athlete skeletal muscle after acute exercise - a systems biology approach

Life-long high-level exercise training leads to improvements in physical performance and multi-tissue adaptation following changes in molecular pathways. While skeletal muscle baseline differences between exercise-trained and untrained individuals have been previously investigated, it remains unclear how acute exercise multi-omics are influenced by training history. We recruited and extensively characterized 24 individuals categorized as endurance athletes, strength athletes or control subjects. Multi-omics profiling was performed from skeletal muscle before and at three time-points after endurance or resistance exercise sessions. Timeseries multi-omics analysis revealed distinct differences in molecular processes such as fatty- and amino acid metabolism and for transcription factors such as HIF1A and the MYF-family between both exercise history and acute form of exercise. Furthermore, we found a "transcriptional specialization effect" by transcriptional narrowing and intensification. Finally, we performed multi-omics network analysis and clustering, providing a novel resource of skeletal muscle transcriptomic and metabolomic profiling in highly trained and untrained individuals.

physiology↗

bioRxiv2023

Targeting Myeloma Essential Genes using NOT Gated CAR- T Cells, a computational approach.

Sensitive cell surface proteomics studies have shown that the number of completely tumour-specific targets for adoptive cellular immunotherapy is extremely low. Even approved CAR T-cell targets appear to have expression in the central nervous system, leading to long-term neurological complications. We propose that this toxicity could be significantly improved by adoption of NOT-gates, which have been shown to limit CAR T-cell activity against healthy tissue expressing a second target that is absent on the tumour. Furthermore, the approach could also target essential, but non-specific proteins on tumour cells. The use of a NOT gate confers the specificity, whilst targeting the essential protein limits antigen escape. Here we explore the feasibility of such an approach for CAR T-cell targeting of primary myeloma. We show that none of the 45 most essential proteins are unique to the myeloma cell. However, whilst widely expressed, one of the most important proteins for myeloma cell survival, the transferrin receptor, could safely be targeted by a NOT-gate approach. Exploring co-expression patterns demonstrate 26 proteins that are not expressed on myeloma cells, but which are coexpressed with the transferrin receptor in all healthy tissues. We also describe a web app, NOTATER, which can be used by scientists with no bioinformatic capabilities to explore potential NOT-gate combinations in myeloma.

cancer biology↗

bioRxiv2023

Cell surface proteomics reveal a strategy for targeting myeloma through combinatorial targeting of TNFRSF8 and TMPRSS11E

Chimeric antigen receptor (CAR) T-cell therapy is a highly effective novel treatment in haematological malignancies that has shown promise as a therapeutic option in multiple myeloma. However, widespread adoption of CAR T-cell therapy in myeloma has been hindered by the challenge of unbiased target antigen identification and selection. As activation of CAR T-cells requires minimal antigen on the cell surface, a major risk of toxicity is destruction of healthy tissue expressing the target protein, i.e. on-target, off-tumour toxicity. Indeed, examination of the myeloma surface proteome demonstrated that there was no single target that was completely unique to myeloma cells. One approach to achieve target specificity is to require simultaneous expression of two proteins on the target cells, so-called AND-gate targeting. To identify potential AND-gate combinations for myeloma, we devised an algorithm to prioritise pairings that exhibited pan-myeloma expression and no overlapping expression in vital healthy tissue, as predicted by proteomics. Through this approach, we identified over 600 combinations. To minimise the risk of exhaustion or priming by CAR T-cells, any combination whereby one of the two antigens was expressed in T-cells was also excluded, leading to the prioritisation of 144 candidate pairings. This demonstrates the potential for AND-gating to expand the repertoire of CAR T-cell targets for myeloma. We evaluated one of these candidate pairings, TMPRSS11E and TNFRSF8, in vitro. Activation in the Jurkat cell line co-expressing a suboptimal CAR against TNFRSF8 and a chimeric costimulatory receptor (CCR) against TMPRSS11E was markedly enhanced following co-culture with a dual-target positive myeloma cell line compared with single-target positive K562, demonstrating improved discrimination between tumour and non-tumour cells.

cancer biology↗

bioRxiv2023

A machine learning approach to predict drug-induced autoimmunity using transcriptional data.

Drug-induced autoimmunity (DIA) is an idiosyncratic adverse drug reaction. Although first reported in the mid-1940s, the mechanisms underlying DIA remain unclear, and there is little understanding of why it is only associated with some drugs. Because it only occurs in a small number of patients, DIA is not normally detected until a drug has reached the market. We describe an ensemble machine learning approach using transcriptional data to predict DIA. The genes comprising the signature implicate dysregulation of cell cycling or proliferation as part of the mechanism of DIA. This approach could be adapted by pharmaceutical companies as an additional preclinical safety screen, reducing the risk of drugs with the potential to cause autoimmunity reaching the market.

pharmacology and toxicology↗

bioRxiv2023

Fate-mapping lymphocyte clones and their progenies from induced antigen-signals identifies temporospatial behaviours of T cells mediating tolerance

Tissue homeostasis is maintained by the behaviours of lymphocyte clones responding to antigenic triggers in the face of pathogen, environmental, and developmental challenges. Current methodologies for tracking the behaviour of specific lymphocytes identify clones of a defined antigen-receptor--antigen binding affinity. However, lymphocytes can receive antigenic signals from undefined or endogenous antigens, and the strength of each signal, even for the same lymphocyte, varies with accessory signalling, across tissues and across time. We present a novel fate-mapping mouse, that, by tracking lymphocyte clones and their progenies from induced antigen signals, overcomes these hurdles and provides novel insights into the maintenance of tissue homeostasis. We demonstrate the systems use by investigating the maintenance of localised T cell tolerance in tumour immunity. In a murine tumour model, our system reveals how Tregs differentiate to a reversible, tolerance inducing state within the tumour, and recirculate, while CD8+ T cells failing to recirculate, differentiate to an increasingly exhausted, tolerant state in the tumour. These contrasting T cell behaviours provide means by which immunity can tolerate a particular anatomical niche while maintaining systemic clonal protection. Our system can thus explore lymphocyte behaviours that cannot be tracked by previous methods and will therefore provide novel insights into the fundamental mechanisms underlying immunitys role in tissue homeostasis.

immunology↗

bioRxiv2022

FiNuTyper: an automated deep learning-based platform for simultaneous fiber and nucleus type analysis in human skeletal muscle

SummaryWhile manual quantification is still considered the gold standard for skeletal muscle histological analysis, it is time-consuming and prone to investigator bias. We assembled an automated image analysis pipeline, FiNuTyper (Fiber and Nucleus Typer), from recently developed deep learning-based image segmentation methods, optimized for unbiased evaluation of fresh and postmortem human skeletal muscle. We validated and utilized SERCA1 and SERCA2 as type-specific myonucleus and myofiber markers. Parameters including myonuclei per fiber, myonuclear domain, central myonuclei per fiber, and grouped myofiber ratio were determined in a fiber type-specific manner, revealing a large degree of gender- and muscle-related heterogeneity. Our platform was also tested on pathological muscle tissue (ALS) and adapted for the detection of other resident cell types (leukocytes, satellite cells, capillary endothelium). In summary, we present an automated image analysis tool for the simultaneous quantification of myofiber and myonuclear types, to characterize the composition of healthy and diseased human skeletal muscle. HighlightsO_LIA deep learning-based automated platform for skeletal muscle microscopic analysis C_LIO_LIHigh-fidelity identification and characterization of myonuclei and myofibers C_LIO_LIValidation of SERCA1 and SERCA2 as markers for myofiber and myonuclear subtypes C_LIO_LICharacterization of healthy and pathological human skeletal muscle tissue features C_LIO_LIAdaptations provided for studies on other resident cell types like satellite cells C_LI eTOC BlurbAn automated platform for unbiased analysis of skeletal muscle immunohistochemical images, focusing on type-specific myofiber-myonucleus relationships, facilitating high-throughput studies of healthy and diseased tissues.

cell biology↗

bioRxiv2022

A common genomic architecture for interacting with the external world

The radiation of mammals at the extinction of the dinosaurs produced a plethora of new forms--as diverse as bats, dolphins, and elephants--in only 10-20 million years. Behind the scenes, adaptation to new niches is accompanied by extensive innovation in large families of genes that allow animals to contact the environment, including chemosensors, xenobiotic enzymes, and immune and barrier proteins. Genes in these "outward-looking" families are allelically diverse among humans and exhibit tissue-specific and sometimes stochastic expression. Here, we show that outward-looking genes are clustered in tandem arrays, enriched in AT-biased isochores, and lack CpG islands in their promoters. Models of mammalian genome evolution have not incorporated the sharply different functions and transcriptional patterns of genes in AT-versus GC-biased regions. To examine the relationship between gene family expansion, sequence content, and functional diversification, we use population genetic data and comparative analysis. First, we find that AT bias can emerge with gene family expansion in cis. Second, human genes in AT-biased isochores or with GC-poor promoters experience relatively low rates of de novo point mutation today but are enriched for functional variants. Finally, we find that isochores containing gene clusters exhibit low rates of recombination. We hypothesize that the depletion of GC bases in outward-facing gene clusters results from tolerance of sequence variation and low recombination. In turn, high AT content exerts a profound effect on their chromatin organization and transcriptional regulation.

evolutionary biology↗

bioRxiv2022

The exocyst complex is an essential component of the mammalian constitutive secretory pathway

Secreted proteins fulfil a vast array of different functions, including adaptive immunity, cell signalling and extracellular matrix remodelling. In the trans-Golgi network, proteins destined for constitutive secretion are sorted into post-Golgi carriers which fuse with the plasma membrane to deliver their contents to the extracellular space. The molecular machinery involved is poorly understood. Here, we have used kinetic trafficking assays and transient CRISPR knock-outs to study the biosynthetic sorting route from the Golgi apparatus to the plasma membrane. Depletion of core-exocyst subunits reduces carrier fusion and causes cargo accumulation in the post-Golgi carriers. Exocyst subunits co-localise with carriers fusing at the plasma membrane and we show that the exocyst complex is recruited directly to these carriers. Abrogation of exocyst followed by kinetic trafficking assays with multiple different soluble cargoes results in cargo accumulation of all tested cargoes. Unbiased secretomics reveals a drastic reduction in the secretion of soluble proteins to the extracellular milieu after knock-out of exocyst subunits. Importantly, the knock-out of exocyst subunits in specialised secretory cell types prevents the constitutive secretion of antibodies in lymphocytes and of the hormones leptin and adiponectin in adipocytes. Together these data identify the exocyst complex as the functional tether of secretory post-Golgi carriers at the plasma membrane and an essential component of the mammalian constitutive secretory pathway.

cell biology↗

bioRxiv2022

Chromosome-scale assembly of the lablab genome - A model for inclusive orphan crop genomics

Orphan crops (also described as underutilised and neglected crops) hold the key to diversified and climate-resilient food systems. After decades of neglect, the genome sequencing of orphan crops is gathering pace, providing the foundations for their accelerated domestication and improvement. Recent attention has however turned to the gross under-representation of researchers in Africa in the genome sequencing efforts of their indigenous orphan crops. Here we report a radically inclusive approach to orphan crop genomics using the case of Lablab purpureus (L.) Sweet (syn. Dolichos lablab, or hyacinth bean) - a legume native to Africa and cultivated throughout the tropics for food and forage. Our Africa-led South-North plant genome collaboration produced a high-quality chromosomescale assembly of the lablab genome - the first chromosome-scale plant genome assembly locally sequenced in Africa. We also re-sequenced cultivated and wild accessions of lablab from Africa confirming two domestication events and examined the genetic diversity in lablab germplasm conserved in Africa. Our approach provides a valuable resource for lablab improvement and also presents a model that could be explored by other researchers sequencing indigenous crops particularly from Low and middle income countries (LMIC).

genomics↗

bioRxiv2021

Spatiotemporal dynamics of human microglia are linked with brain developmental processes across the lifespan

Microglia, the brains resident macrophages, shape neural development and wiring, and are key neuroimmune hubs in the pathological signature of neurodevelopmental disorders. In the human brain, microglial development has not been carefully examined yet, and most of our knowledge derives from rodents. We established an unprecedented collection of 97 postmortem tissues enabling quantitative, sex-matched, detailed analysis of microglial across the human lifespan. We identify the dynamics of these cells in the human telencephalon, describing novel waves in microglial density across gestation and infancy, controlled by a balance of proliferation and apoptosis, which track key neurodevelopmental milestones. These profound changes in microglia are also observed in bulk RNAseq and single-cell RNAseq datasets. This study provides unparalleled insight and detail into the spatiotemporal dynamics of microglia across the human lifespan. Our findings serve as a solid foundation for elucidating how microglia contribute to shaping neurodevelopment in humans.

neuroscience↗