Biology subjects

Nelson, E. D.

Publications and source records attributed to Nelson, E. D..

7 recordsLinked to original sources

bioRxiv2024

An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus

The hippocampus contains many unique cell types, which serve the structures specialized functions, including learning, memory and cognition. These cells have distinct spatial organization, morphology, physiology, and connectivity, highlighting the importance of transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus in ten adult neurotypical donors to define molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization (NMF) and label transfer, we integrated these data by defining gene expression patterns within the snRNA-seq data and inferring their expression in the SRT data. We identified NMF patterns that captured transcriptional variation across neuronal cell types and indicated that the response of excitatory and inhibitory postsynaptic specializations were prioritized in different SRT spatial domains. We used the NMF and label transfer approach to leverage existing rodent datasets, identifying patterns of activity-dependent transcription and subpopulations of dentate gyrus granule cells in our SRT dataset that may be predisposed to participate in learning and memory ensembles. Finally, we characterized the spatial organization of NMF patterns corresponding to non-cornu ammonis pyramidal neurons and identified snRNA-seq clusters mapping to distinct regions of the retrohippocampus, to three subiculum layers, and to a population of presubiculum neurons. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.

neuroscience↗

bioRxiv2024

Transcriptomic analysis of the human habenula in schizophrenia

Pathophysiology of many neuropsychiatric disorders, including schizophrenia (SCZD), is linked to habenula (Hb) function. While pharmacotherapies and deep brain stimulation targeting the Hb are emerging as promising therapeutic treatments, little is known about the cell type-specific transcriptomic organization of the human Hb or how it is altered in SCZD. Here we define the molecular neuroanatomy of the human Hb and identify transcriptomic changes in individuals with SCZD compared to neurotypical controls. Utilizing Hb-enriched postmortem human brain tissue, we performed single nucleus RNA-sequencing (snRNA-seq; n=7 neurotypical donors) and identified 17 molecularly defined Hb cell types across 16,437 nuclei, including 3 medial and 7 lateral Hb populations, several of which were conserved between rodents and humans. Single molecule fluorescent in situ hybridization (smFISH; n=3 neurotypical donors) validated snRNA-seq Hb cell types and mapped their spatial locations. Bulk RNA-sequencing and cell type deconvolution in Hb-enriched tissue from 35 individuals with SCZD and 33 neurotypical controls yielded 45 SCZD-associated differentially expressed genes (DEGs, FDR < 0.05), with 32 (71%) unique to Hb-enriched tissue. eQTL analysis identified 717 independent SNP-gene pairs (FDR < 0.05), where either the SNP is a SCZD risk variant (16 pairs) or the gene is a SCZD DEG (7 pairs). eQTL and SCZD risk colocalization analysis identified 16 colocalized genes. These results identify topographically organized cell types with distinct molecular signatures in the human Hb and demonstrate unique genetic changes associated with SCZD, thereby providing novel molecular insights into the role of Hb in neuropsychiatric disorders. One Sentence SummaryTranscriptomic analysis of the human habenula and identification of molecular changes associated with schizophrenia risk and illness state.

neuroscience↗

bioRxiv2024

Neutral speciation in realistic populations

de Aguiar et al. have shown that basic patterns of species diversity found in nature can be described by a neutral model of speciation in which species emerge simply as a consequence of local mating, and mate preference for genetic similarity. Their results have been cited as support for the neutral theory of biodiversity. However, because the mutation rates considered in their work are much larger than those experienced by living organisms, there is still some question as to whether speciation will occur in this type of model under realistic conditions. Here, I develop a variant of the neutral model that includes a realistic mechanism for organism dispersal. I explore speciation in the model for a class of mobile organisms (butterflies), and I find that speciation does occur under conditions consistent with butterfly populations, albeit on narrow landscapes. The model also appears to exhibit scaling behavior - specifically, if the model is "scaled up" by increasing the area of the landscape while holding its length to width ratio and population density constant, the number of species tends to an asymptotic value. The results suggest that it is possible to infer speciation patterns in large populations by simulating much smaller, computationally tractable populations.

ecology↗

bioRxiv2022

Activity-regulated gene expression across cell types of the mouse hippocampus

Activity-regulated gene (ARG) expression patterns in the hippocampus (HPC) regulate synaptic plasticity, learning, and memory, and are linked to both risk and treatment response for many neuropsychiatric disorders. The HPC contains discrete classes of neurons with specialized functions, but cell type-specific activity-regulated transcriptional programs are not well characterized. Here, we used single-nucleus RNA-sequencing (snRNA-seq) in a mouse model of acute electroconvulsive seizures (ECS) to identify cell type-specific molecular signatures associated with induced activity in HPC neurons. We used unsupervised clustering and a priori marker genes to computationally annotate 15,990 high-quality HPC neuronal nuclei from N=4 mice across all major HPC subregions and neuron types. Activity-induced transcriptomic responses were divergent across neuron populations, with dentate granule cells being particularly responsive to activity. Differential expression analysis identified both upregulated and downregulated cell type-specific gene sets in neurons following ECS. Within these gene sets, we identified enrichment of pathways associated with varying biological processes such as synapse organization, cellular signaling, and transcriptional regulation. Finally, we used matrix factorization to reveal continuous gene expression patterns differentially associated with cell type, ECS, and biological processes. This work provides a rich resource for interrogating activity-regulated transcriptional responses in HPC neurons at single-nuclei resolution in the context of ECS, which can provide biological insight into the roles of defined neuronal subtypes in HPC function.

neuroscience↗

bioRxiv2020

The relationship between gene flow and population difference during secondary contact between butterfly sister species

Comparisons of genomes from recently diverged butterfly populations along a suture zone in central Texas have revealed high levels of divergence on the Z chromosome relative to autosomes, as measured by fixation index, Fst. The pattern of divergence appears to result from accumulation of incompatible alleles, obstructing introgression on the Z chromosome in hybrids. However, it is unknown whether this mechanism is sufficient to explain the data. Here, we simulate the effects of hybrid incompatibility on interbreeding butterfly populations using a model in which populations accumulate cross-incompatible alleles in allopatry prior to contact. We compute statistics for introgression and population divergence during contact between model butterfly populations and compare them to statistics obtained for 15 pairs of butterfly species interbreeding along the Texas suture zone. For populations that have evolved sufficiently in allopatry, the model exhibits high levels of divergence on the Z chromosome relative to autosomes in populations inter-breeding on time scales comparable to periods of interglacial contact between butterfly populations in central Texas. Levels of divergence on the Z chromosome increase when interacting groups of genes are closely linked, consistent with interacting clusters of functionally related genes in butterfly genomes. Results for various periods in allopatry are in qualitative agreement with the pattern of data for butterflies, supporting a picture of speciation in which populations are subjected to cycles of divergence in glacial isolation, and partial fusion during interglacial contact.

biophysics↗

bioRxiv2019

How often do Protein Genes Navigate Valleys of Low Fitness?

In order escape from local fitness peaks, a population must navigate across valleys of low fitness. How these transitions occur, and what role they play in adaptation, have been subjects of active interest in evolutionary genetics for almost a century. However, to our knowledge, this problem has never been addressed directly, by considering the evolution of a gene, or group of genes, as a whole, including the complex effects of fitness interactions among multiple loci. Here, we use a precise model of protein fitness to compute the probability P(s, {Delta}t) that an allele, randomly sampled from a population at time t, has crossed a fitness valley of depth s during an interval [t - {Delta}t, t] in the immediate past. We study populations of model genes evolving under equilibrium conditions consistent with those in mammalian mitochondria. From this data, we estimate that genes encoding small protein motifs navigate fitness valleys of depth 2Ns {gtrsim} 30 with probability P {gtrsim} 0.1 on a time scale of human evolution, where N is the (mitochondrial) effective population size. The results are consistent with recent findings for Watson-Crick switching in mammalian mitochondrial tRNA molecules.

genetics↗

bioRxiv2018

Inference of epistatic effects in a key mitochondrial protein

We use Potts model inference to predict pair epistatic effects in a key mitochondrial protein - cytochrome c oxidase subunit 2 - for ray-finned fishes. We examine the effect of phylogenetic correlations on our predictions using a simple exact fitness model, and we find that, although epistatic effects are under-predicted, they maintain a roughly linear relationship to their true (model) values. After accounting for these corrections, epistatic effects in the protein are still relatively weak, leading to fitness valleys of depth 2Ns ~ -5 in compensatory double mutants. Positive epistasis is more pronounced than negative epistasis, and the strongest positive effects capture nearly all sites subject to positive selection in fishes, similar to virus proteins evolving under selection pressure in the context of drug therapy.

evolutionary biology↗