Biology subjects

Chu, C.

Publications and source records attributed to Chu, C..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

An assembly of genomic dataset sequences of the sugar beet root maggot Tetanops myopaeformis, TpSBRM_v1.0

The sugar beet root maggot (SBRM), Tetanops myopaeformis (von Roder), is a devastating pathogen of sugar beet (SB), Beta vulgaris, ssp vulgaris (B. vulgaris), an important food crop, while also being one of only two plants globally from which sugar is widely produced, and accounting for 35% of global raw sugar with an annual farm value of $3 billion in the United States alone. SBRM is the most devastating pathogen of sugar beet in North America. The limited natural resistance of B. vulgaris necessitates an understanding of the SBRM genome to facilitate generating knowledge of its basic biology, including the interaction between the pathogen and its host(s). Presented is the de novo assembled draft genome sequence of T. myopaeformis isolated from field-grown B. vulgaris in North Dakota, USA. The SBRM genome sequence will also be valuable for molecular genetic marker development to facilitate host resistance gene identification and knowledge, including SB polygalacturonase inhibiting protein (PGIP), and development of new control strategies for this pathogen. SPECIFICATIONSOrganism/cell line/tissue: Tetanops myopaeformis Sequencer or array type: PacBio Revio flow cell Data format: Raw and processed Experimental factors: DNA extracted from a wild-type strain, no treatment Experimental features: Genome sequencing Consent n/a Sample source location: Sugar beet field at Fargo, North Dakota, USA DIRECT LINK TO DEPOSITED DATABioSample accession: SAMN37733483 Temporary Submission ID: SUB13882507 BioProject ID: PRJNA1026092 Release date: 2024-09-09, or with the release of linked data, whichever is first

genomics↗

bioRxiv2023

Converging Topographic Axes of Connectivity and Genetic Architectures Scaffold Cortical Patterning

Genetic information is involved in the gradual emergence of cortical areas since the neural tube begins to form, shaping the heterogeneous functions of neural circuits in the human brain. Informed by invasive tract-tracing measurements, the cortex exhibits marked interareal variation in connectivity profiles to reveal the heterogeneity across cortical areas. However, it remains unclear about the organizing principles possibly shared by genetics and cortical wiring to manifest the spatial heterogeneity across the cortex. Instead of considering a complex one-to-one mapping between genetic coding and interareal connectivity, we hypothesized the existence of a more efficient way that the organizing principles are embedded in genetic profiles to underpin the cortical wiring space. Leveraging on the vertex-wise tractography in diffusion-weighted MRI, we derived the global connectopies to reliably index the organizing principles of interareal connectivity variation in a low-dimensional space, which specifically captured three dominant topographic patterns along the dorsoventral, rostrocaudal, and mediolateral axes of the cortex. More importantly, we demonstrated that the global connectopies converge to the gradients of vertex-by-vertex genetic correlation matrix on the phenotype of cortical morphology and the cortex-wide spatiomolecular gradients. By diving into the genetic profiles, we found the critical role of genes scaffolding the global connectopies were related to brain morphogenesis and enriched in radial glial cells before birth and excitatory neurons after birth. Taken together, our findings demonstrated the existence of a genetically determined space to encode the interareal connectivity variation, which may give new insights into the links between cortical connections and arealization.

neuroscience↗

bioRxiv2023

A Pooled Cell Painting CRISPR Screening Platform Enables de novo Inference of Gene Function by Self-supervised Deep Learning

Pooled CRISPR screening has emerged as a powerful method of mapping gene functions thanks to its scalability, affordability, and robustness against well or plate-specific confounders present in array-based screening 1-6. Most pooled CRISPR screens assay for low dimensional phenotypes (e.g. fitness, fluorescent markers). Higher-dimensional assays such as perturb-seq are available but costly and only applicable to transcriptomics readouts 7-11. Recently, pooled optical screening, which combines pooled CRISPR screening and microscopy-based assays, has been demonstrated in the studies of the NFkB pathway, essential human genes, cytoskeletal organization and antiviral response 12-15. While the pooled optical screening methodology is scalable and information-rich, the applications thus far employ hypothesis-specific assays. Here, we enable hypothesis-free reverse genetic screening for generic morphological phenotypes by re-engineering the Cell Painting 16 technique to provide compatibility with pooled optical screening. We validated this technique using well-defined morphological genesets (124 genes), compared classical image analysis and self-supervised learning methods using a mechanism-of-action (MoA) library (300 genes), and performed discovery screening with a druggable genome library (1640 genes) 17. Across these three experiments we show that the combination of rich morphological data and deep learning allows gene networks to emerge without the need for target-specific biomarkers, leading to better discovery of gene functions.

genomics↗

bioRxiv2023

A gel-coated air-liquid-interface culture system with tunable substrate stiffness matching healthy and diseased lung tissues

Since its invention in the late 1980s, the air-liquid-interface (ALI) culture system has been the standard in vitro model for studying human airway biology and pulmonary diseases. However, in a conventional ALI system, cells are cultured on a porous plastic membrane that is much stiffer than human airway tissues. Here, we develop a gel-ALI culture system by simply coating the plastic membrane with a thin layer of hydrogel with tunable stiffness matching that of healthy and fibrotic airway tissues. We determine the optimum gel thickness that does not impair the transport of nutrients and biomolecules essential to cell growth. We show that the gel-ALI system allows human bronchial epithelial cells (HBECs) to proliferate and differentiate into a pseudostratified epithelium. Further, we discover that HBECs migrate significantly faster on hydrogel substrates with stiffness matching that of fibrotic lung tissues, highlighting the importance of mechanical cues to human airway remodeling. The developed gel-ALI system provides a facile approach to studying the effects of mechanical cues on human airway biology and in modeling pulmonary diseases. New and NoteworthyIn a conventional air-liquid-interface (ALI) system, cells are cultured on a plastic membrane that is much stiffer than human airway tissues. We develop a gel-ALI system by coating the plastic membrane with a thin layer of hydrogel with tunable stiffness matching that of healthy and fibrotic airway tissues. We discover that human bronchial epithelial cells migrate significantly faster on hydrogel substrates with pathological stiffness, highlighting the importance of mechanical cues to human airway remodeling.

bioengineering↗

bioRxiv2023

Repeated Caffeine Intake Suppresses Cerebral Grey Matter Responses to Chronic Sleep Restriction in an A1 Adenosine Receptor-Dependent Manner.

Evidence has shown that both sleep loss and daily caffeine intake can induce changes in grey matter (GM). Caffeine is frequently used to combat sleepiness and impaired performance caused by insufficient sleep. It is unclear 1) whether daily use of caffeine could prevent or exacerbate the GM alterations induced by chronic sleep restriction, and 2) whether the potential impact on GM plasticity depends on individual differences in the availability of adenosine receptors, which are involved in mediating effects of caffeine on sleep and waking function. In this double-blind, randomized, controlled study, 36 healthy adults (aged 28.9 {+/-} 5.2 y/o; 15 females; habitual daily caffeine intake < 450 mg; 29 homozygous C/C allele carriers of the A2A adenosine receptor (A2AR) gene variant rs5751876 of ADORA2A) underwent a 9-day laboratory visit consisting of one adaption day, 2 baseline days (BL), 5-day sleep restriction (CSR, 5 h time-in-bed), and a recovery day (REC) after an 8-h sleep opportunity. Nineteen participants received 300 mg caffeine in coffee through the 5 days of CSR (CAFF group), while 17 matched participants received decaffeinated coffee (DECAF group). We measured the GM morphology on the 2nd BL Day, 5th CSR Day, and REC Day. Moreover, we used [18F]-CPFPX PET to quantify the baseline availability of A1 adenosine receptors (A1R) and their relation to GM plasticity. The voxel-wise multimodal whole-brain analysis on T1-weighted images controlled for variances of cerebral blood flow indicated a significant interaction between caffeine and CSR in four brain regions: 1) right temporal-occipital region, 2) right thalamus, 3) left dorsolateral, and 4) dorsomedial prefrontal region. The post-hoc analyses indicated increased GM intensity in the DECAF group in all four regions but decreased GM in the thalamus as well as dorsolateral and dorsomedial prefrontal regions in the CAFF group after sleep restriction. Furthermore, lower baseline subcortical A1R availability predicted larger reduction in the CAFF group after CSR of all brain regions except for the caffeine-associated thalamic reduction. In conclusion, our data suggest an adaptive upregulation in GM after 5-day CSR, while concomitant use of caffeine instead leads to a GM reduction. The lack of consistent association with individual A1R availability may suggest that CSR and caffeine affect GM plasticity predominantly by a different mechanism. Future studies on the role of adenosine A2A receptors (ADORA2A) in CSR-induced GM plasticity are warranted.

neuroscience↗

bioRxiv2023

Latitudinal scaling of aggregation with abundance and its consequences for coexistence in species rich forests

The search for simple principles underlying the complex spatial structure and dynamics of plant communities is a long-standing challenge in ecology1-6. In particular, the relationship between the spatial distribution of plants and species coexistence is challenging to resolve in species-rich communities7-9. Analysing the spatial patterns of tree species in 21 large forest plots, we find that rare species tend to be more spatially aggregated than common species, and a latitudinal gradient in the strength of this negative correlations that increases from tropical to temperate forests. Our analysis suggests that latitudinal gradients in animal seed dispersal10 and mycorrhizal associations11,12,13 may jointly generate this intriguing pattern. To assess the consequences of negative aggregation-abundance correlations for species coexistence, we present here a framework to incorporate the observed spatial patterns into population models8 along with an analytical solution for the local extinction risk14 of species invading from low abundances in dependence of spatial structure, demographic parameters, and immigration. For example, the stabilizing effect of the observed spatial patterns reduced the local extinction risk of species when rare almost by a factor of two. Our approach opens up new avenues for integrating observed spatial patterns into mathematical theory, and our findings demonstrate that spatial patterns, such as species aggregation and segregation, can contribute substantially to coexistence in species-rich communities. This underscores the need to understand the interactions between multiple ecological processes and spatial patterns in greater detail.

ecology↗

bioRxiv2023

Mechanism-guided quantification of LINE-1 reveals p53 regulation of both retrotransposition and transcription

Somatic activity of LINE-1 (L1) mobile elements has been implicated in cancer etiology, which may be related to the loss of p53-mediated regulation as a result of TP53 mutations. Quantifying the mechanisms of L1 regulation in cancer has been challenging. Here, we build a statistical model of L1 regulation by simultaneously quantifying L1 retrotransposition, L1 expression, and the fitness costs of mutated TP53 with precision. We first developed Total ReCall, an algorithm specifically tailored to the mechanisms of L1 reintegration, to detect L1 insertions from short-read whole-genome sequencing. Applying Total ReCall to high-quality data consisting of >750 paired tumor and normal samples from The Cancer Genome Atlas (TCGA) shows high L1 insertion heterogeneity among tumor types, with increased retrotransposition burden in lung squamous cell carcinoma, head and neck, and colon cancers. We next assessed the active RNA expression of intact L1 in >9,000 TCGA tumor samples, establishing, for the first time, a clear correlation between L1 expression and retrotransposition. Finally, we integrated the number of L1 insertions, L1 expression and a mathematical model of TP53 fitness into a multi-modal model of p53- mediated mechanisms of L1 regulation. We show that TP53 mutations enable retrotransposition both by disinhibiting L1 expression and enabling its reintegration and quantify the relative weights of this dual regulatory role. We demonstrate how mechanism-based multi-modal modeling applied at scale can statistically disentangle the complex interplay between canonical driver events in tumor evolution and retrotransposon activity.

cancer biology↗

bioRxiv2022

A novel method revealing animal evolutionary relationships based on milk Mid-infrared

Mid-infrared spectra (MIRS) can effectively reflect the chemical bonds in milk, which has been widely used in dairy herd improvement. However, the relationship between MIRS and animal evolution remains largely unclear. This study firstly found great differences in MIRS and the components of milk by analyzing MIRS information of 12 different mammal species. A five-level discriminant model of evolutionary level based on MIRS was established with a test set kappa coefficient >0.97. In addition, a regression model of genetic distance was also established to estimate the genetic distance of different animal species with a correlation coefficient of R >0.94. These results showed that this method could be used for accurate mammalian evolutionary relationship assessment. We further clarified the potential relationship between MIRS and genes, such as PPP3CA and SCD that could change MIRS by regulating specific milk components. In conclusion, we expand the application of MIRS in animal species identification and evolution research and provide new perspectives for the research on the formation mechanism of different animal milk special components.

evolutionary biology↗

bioRxiv2022

Network Occlusion Sensitivity Analysis Identifies Regional Contributions to Brain Age Prediction

Deep learning frameworks utilizing convolutional neural networks (CNNs) have frequently been used for brain age prediction and have achieved outstanding performance. Nevertheless, deep learning remains a black box as it is hard to interpret which brain parts contribute significantly to the predictions. To tackle this challenge, we first trained a lightweight, fully CNN model for brain age estimation on a large sample data set (N = 3054, age range = [8,80 years]) and tested it on an independent data set (N = 555, mean absolute error (MAE) = 4.45 years, r = 0.96). We then developed an interpretable scheme combining network occlusion sensitivity analysis (NOSA) with a fine-grained human brain atlas to uncover the learned invariance of the model. Our findings show that the dorsolateral, dorsomedial frontal cortex, anterior cingulate cortex, and thalamus had the highest contributions to age prediction across the lifespan. More interestingly, we observed that different regions showed divergent patterns in their predictions for specific age groups and that the bilateral hemispheres contributed differently to the predictions. Regions in the frontal lobe were essential predictors in both the developmental and aging stages with the thalamus remaining relatively stable and saliently correlated with other regional changes throughout the lifespan. The lateral and medial temporal brain regions gradually became involved during the aging phase. At the network level, the frontoparietal and the default mode networks show an inverted U-shape contribution from the developmental to the aging stages. The framework could identify regional contributions to the brain age prediction model, which could help increase the model interpretability when serving as an aging biomarker.

neuroscience↗

bioRxiv2022

Statistical modelling of aquatic size spectra: integrating data from multiple taxa and sampling methods

Size spectra are used to assess the status and functioning of marine and freshwater ecosystems worldwide. Its use is underpinned by theory linking the dynamics of trophic interactions to a power-law decline of abundance with body size in ecological communities. Recent papers on empirical size spectrum estimation have argued for Maximum Likelihood Estimation (MLE) of power-law probability distributions as a more accurate alternative to traditional linear regression approaches. One major limitation of currently used size spectrum estimators from MLE is that they cannot account for the use of multiple sampling protocols, nor the distortions caused by gear size selectivity, and therefore they become restricted to a relatively narrow taxonomic group and size range. Further progress in the field requires new methods that are flexible enough to combine multiple trophic groups and sampling gears into a single size spectrum estimate, while taking advantage of more accurate distributional approaches. The method we propose in this paper fills this gap by deriving the distribution of observed sizes explicitly from the underlying power-law spectrum and gear selectivity functions. It specifies likelihoods as a product of two components: (i) the probability of belonging to a given group and (ii) the probability distribution within the group. Using Bayesian estimation, we applied the method to surveys of phytoplankton, zooplankton, and fishes in lakes of Quetico Provincial Park, northwestern Ontario, using Van Dorn samplers, zooplankton nets, gillnets, and hydroacoustics. The results show that the spectra estimated from subsets of trophic groups or gears are weak predictors of more complete spectra, highlighting the importance of using more inclusive community data. The two-component partitioning of likelihoods also helped demonstrating the existence of between-group spectrum slopes that were overall steeper than within-group slopes, indicating that heterogeneity of trophic transfers across the size spectrum is an important factor structuring these ecosystems.

ecology↗

bioRxiv2022

Non-canonical Telomerase Reverse Transcriptase Controls Osteogenic Differentiation of Aortic Valve Cells Through STAT5

BackgroundCalcific aortic valve disease (CAVD) is the pathological remodeling of valve leaflets. The initial steps in valve leaflet osteogenic reprogramming are not fully understood. As telomerase reverse transcriptase (TERT) overexpression primes mesenchymal stem cells to differentiate into osteoblasts, we investigated whether TERT contributes to the osteogenic reprogramming of valve interstitial cells (VICs). MethodsHuman control and CAVD aortic valve leaflets and patient-specific hVICs were used in in vivo and in vitro calcification assays. Loss of function experiments in hVICs and cells isolated from Tert-/-and Terc-/- mice were used for mechanistic studies. Calcification was assessed in Tert+/+ and Tert-/- mice ex vivo and in vivo. In silico modeling, proximity ligation and co-immunoprecipitation assays defined novel TERT interacting partners. Chromatin immunoprecipitation and CUT&TAG sequencing defined protein-DNA interactions. ResultsTERT protein was highly expressed in calcified valve leaflets without changes in telomere length, DNA damage, or senescence markers, and these features were retained in isolated primary hVICs. TERT expression increased with osteogenic or inflammatory stimuli, and knock-down or genetic deletion of TERT prevented calcification in vitro and in vivo. Mechanistically, TERT was upregulated via NF-{kappa}B and required to initiate osteogenic reprogramming, independent of its canonical reverse transcriptase activity and the lncRNA TERC. TERT exerts non-canonical osteogenic functions via binding with Signal Transducer and Activator of Transcription 5 (STAT5). Depletion or inhibition of STAT5 prevented calcification. STAT5 was found to bind the promoter region of Runt-Related Transcription Factor 2 (RUNX2), the master regulator of osteogenic reprogramming. Lastly, we demonstrate that TERT and STAT5 are upregulated and colocalized in CAVD tissue compared to control tissue. ConclusionsTERTs non-canonical activity is required to initiate calcification. TERT is upregulated via inflammatory signaling pathways and partners with STAT5 to bind the RUNX2 gene promoter. These data identify a novel mechanism and potential therapeutic target to decrease vascular calcification. Novelty and SignificanceWhat is known? Calcific aortic valve disease (CAVD) is the most prevalent form of aortic valve pathology. CAVD strongly correlates with age and leads to heart failure and a high risk of stroke. Currently, the only therapeutic option is valve replacement, which comes with significant healthcare costs and additional risks to patients. Runt-related transcription factor 2 (RUNX2) is the master transcription factor required for osteogenic differentiation of stem cells to osteoblasts and osteogenic reprogramming of cardiovascular cells. Yet, the early events driving its activity in aortic valve cells are poorly defined. In addition to its reverse transcriptase enzymatic activity, TERT exhibits non-canonical transcriptional regulatory functions and overexpression of TERT primes mesenchymal stem cells to differentiate down the osteoblast lineage. What new information does this article contribute? TERT protein levels in calcified aortic leaflets and valve interstitial cells, and its non-canonical osteogenic activity are independent of changes in telomere length and cell senescence. Genetic loss or depletion of TERT prevented calcification in valve interstitial cells, coronary smooth muscle cells, and mesenchymal stem cells in vitro and the vasculature in vivo. Early in the osteogenic reprogramming inflammatory signaling promotes TERT to co-localize with SMARCA4 and STAT5, and this TERT-tethered STAT5 binds to the RUNX2 gene promoter, the master regulator of osteogenic transcriptional programs. STAT5 depletion and pharmacological inhibition prevent calcification of human valve interstitial cells, coronary smooth muscle cells, and mesenchymal stem cells. What are the clinical implications? We have identified TERT-STAT5 as a novel signaling axis that orchestrates the early steps in the osteogenic reprogramming of aortic valve cells. Inhibiting TERT/STAT5 interaction or their activity may be leveraged for the development of therapeutic strategies to halt or prevent calcification in the aortic valve, bioprosthetic valves, and or perhaps other cardiovascular tissues. Invasive and expensive surgical procedures are currently the only treatment option for patients with CAVD. The discovery and defining of the early events driving vascular calcification identifies novel and druggable targets for developing non-surgical therapies.

pathology↗

bioRxiv2022

Prior-guided Individualized Thalamic Parcellation based on Local Diffusion Characteristics using Deep Learning

As a gateway for projections entering and exiting the cerebral cortex, the human thalamus processes information from sensory to cognition relevant to various neuropsychiatric disorders. It is composed of dozens of nuclei, which have been difficult to identify with clinical MR sequences. However, delineating thalamic nuclei accurately at an individual level is essential for precise neuromodulation treatment. Here, we not only identified the fine-grained thalamic nuclei using local diffusion properties in vivo but also employed a deep learning strategy to achieve highly reproducible individual-level parcellation. Using High-quality diffusion MRI (dMRI), we first constructed a fine-grained group thalamus atlas based on thalamic local diffusion features. Then, the high-probability core area of the group thalamus atlas was wrapped into the native space as prior guidance for individualized thalamus construction. Finally, we trained the semi-supervised multiple classification models to accurately construct the individualized thalamus atlas with single-subject local diffusion characteristics. Compared to group atlas registration and single-subject clustering strategies, our individualized thalamus atlas combines population commonality and individual specificity and is superior in depicting the individual thalamic nuclei boundaries. Besides, our atlas provides a more conspicuous capacity to capture the individual specificity of thalamic nuclei. Through the evaluation by 3.0T\7.0T and test-retest dMRI datasets, the proposed high-probability group prior guided individualized thalamus construction pipeline is robust and repeatable in different magnetic field strengths and scanning batches. In addition, the individual parcellation of the thalamic nuclei has a good correspondence with the histological atlas and captured both higher group consistency and inter-subjects variations, which could be a valuable solution for precision clinical treatment.

neuroscience↗

bioRxiv2022

Diversity and biogeography of plant leaf bacteria along a latitudinal gradient

Plant-associated microbes are essential for promoting plant well-being, maintaining biodiversity, and supporting ecosystem function. However, little is known about the geographic distribution of plant-microbe symbioses and how they are formed and change along latitudinal gradients. Here we identified leaf bacteria for 328 plant species sampled from 10 forests along a tropical to temperate gradient in China. We analyzed the diversity and composition of plant leaf-associated bacteria and quantified the contributions of hosts, habitats, and neighborhood plants to the plant-bacterial symbiosis. We found a strong latitudinal gradient in leaf bacterial diversity and composition. Bacterial assemblages on leaves were most strongly selected by host plants, and the selection pressure increased with latitude. In contrast, at low latitudes and at large geographical scales multiple factors were found to jointly regulate bacterial community composition. Our result also showed that plant-bacteria symbiotic networks were structured by network hub bacteria taxa with high co-occurrence network centrality, and the abundance of temperate hub taxa was more influenced by host plants than that in tropical forests. For the first time, we documented a previously unrecognized latitudinal gradient in plant-bacterial symbioses that was regulated by a joint effect of multiple factors at low latitudes but mostly by host selection at high latitudes, implying that leaf microbiomes are likely to respond differently to global change along the latitudinal gradient.

ecology↗

bioRxiv2022

Genetic Variation and Disease Severity of Respiratory Syncytial Viruses

Respiratory Syncytial Virus (RSV) disease in newborns ranges from mild symptoms to severe disease requiring hospitalization. RSV is classified into two subtypes (RSVA and RSVB) based on antigenic and genetic differences. The role these genomic variations play in disease severity remains unknown. Genome sequences were obtained using next-generation RNA sequencing on archived frozen nasal swabs of young children (< 8 months-old) infected with RSV in Rochester, NY between 1977-1998. Samples were chosen from both children hospitalized with severe RSV disease (inpatient) and those presenting with mild symptoms (outpatient) during their first cold-season. Both A and B subtypes demonstrated significant differences in the phylogeny and primary-protein structure during this time period. We found a significant association between RSV phylogeny over this time period and disease severity. For both subtypes, the G-protein demonstrated the greatest amino acid substitutions, although the number of amino acid substitutions was higher in the RSVA subtype. We found a significant association between G-protein variation and disease severity for RSVA, but not RSVB. For both subtypes, variation in the M2-2 protein was significantly associated with disease severity. These results suggest that the genetic variability of RSV proteins may contribute to disease severity in humans. ImportanceEach cold-season Respiratory Syncytial Virus (RSV) infects thousands of children in the US. Some will display mild cold symptoms while others develop severe disease, sometimes resulting in lifelong lung problems or fatality. RSV initiates infection and replicates in the nasopharynx. Substitutions in the RSV genome can be found in clinically isolated nasal-swab samples of RSV infected children. Whether these genome variations contribute to severe disease is unknown. Here we found a statistically significant association between RSV phylogeny and disease severity. Furthermore, we found specific RSV proteins (G and M2-2) whose amino acid variation was statistically associated with severe disease, although which protein was associated depended on subtype. Taken together, our results suggest that RSV genotype contributed to disease severity over this time period.

microbiology↗

bioRxiv2022

Anatomical connectivity profile development constrains medial-lateral topography in the dorsal prefrontal cortex

The prefrontal cortex (PFC) is a highly variable, evolutionarily expanded brain region that is engaged in multiple cognitive processes. The subregions of the PFC mature relatively late compared with other brain regions, and the maturation times vary between these subregions. Among these, the dorsomedial and dorsolateral prefrontal cortex (dmPFC and dlPFC) share a parallel topographic pattern of functional connectivity, while participating in different types of complex behaviors. However, the developmental trajectories of the two areas remain obscure. In this study, we uncovered differences in the developmental trends of the dmPFC and dlPFC. These differences were mainly caused by structural and functional changes in the medial area of the superior frontal gyrus (SFG). The developmentally different arealization patterns were verified using multiple parcellation approaches with multimodal data, including structural magnetic resonance imaging (sMRI), diffusion MRI (dMRI), resting state functional MRI (rfMRI), and a publicly available transcriptomic dataset. Human brain gene expression data was also used to perform downstream analyses, which could inform us about the potential biological mechanisms underlying the developmentally different arealizations. Furthermore, behavioral analyses hinted at the effects of regionalization on ontogeny. In brief, this study revealed a tendency toward a medial-lateral prefrontal division and can provide a fuller understanding of the potential underlying genetic underpinnings as well as of the potential effects on developmental behavior.

neuroscience↗

bioRxiv2021

Angiotensin converting enzyme 2 (ACE2) is expressed in murine cutaneous under single-cell transcriptome resolution

Angiotensin converting enzyme 2 (Ace2) is widely distributed in human organs, which was identified as a functional receptor for severe acute respiratory syndrome (SARS) coronavirus in human beings. It was also confirmed that SARS-CoV-2 uses the same cell entry receptor, ACE2, as SARS-CoV. However, related research still not discover the expression data associated with murine skin under single cell RNA resolution. In this study, we performed single-cell RNA sequencing (scRNA-seq) on unsorted cells from mouse dorsal skin after 7 days post-wounding. 8312 sequenced cells from four skin samples met quality control metrics and were analyzed.

genomics↗

bioRxiv2021

Disentangling key species interactions in diverse and heterogeneous communities: A Bayesian sparse modeling approach

1Modeling species interactions in diverse communities traditionally requires a prohibitively large number of species-interaction coefficients, especially when considering environmental dependence of parameters. We implemented Bayesian variable selection via sparsity-inducing priors on non-linear species abundance models to determine which species-interactions should be retained and which can be represented as an average heterospecific interaction term, reducing the number of model parameters. We evaluated model performance using simulated communities, computing out-of-sample predictive accuracy and parameter recovery across different input sample sizes. We applied our method to a diverse empirical community, allowing us to disentangle the direct role of environmental gradients on species intrinsic growth rates from indirect effects via competitive interactions. We also identified a few neighboring species from the diverse community that had non-generic interactions with our focal species. This sparse modeling approach facilitates exploration of species-interactions in diverse communities while maintaining a manageable number of parameters.

ecology↗

bioRxiv2021

Uncovering the Genetic Profiles Underlying the Intrinsic Organization of the Human Cerebellum

The functional diversity of the human cerebellum is largely believed to be derived more from its extensive connections rather than being limited to its mostly invariant architecture. However, whether and how the determination of cerebellar connections in its intrinsic organization interact with microscale gene expression is still unknown. Here we decode the genetic profiles of the cerebellar functional organization by investigating the genetic substrates simultaneously linking cerebellar functional heterogeneity and its drivers, i.e., the connections. We not only identified 443 network-specific genes but also discovered that their co-expression pattern correlated strongly with intra-cerebellar functional connectivity (FC). Ninety of these genes were also linked to the FC of cortico-cerebellar cognitive-limbic networks. To further discover the biological functions of these genes, we performed a "virtual gene knock-out" by observing the change in the coupling between gene co-expression and FC and divided the genes into two subsets, i.e., a positive gene contribution indicator (GCI+) involved in cerebellar neurodevelopment and a negative gene set (GCI-) related to neurotransmission. A more interesting finding is that GCI- is significantly linked with the cerebellar connectivity-behavior association and many recognized brain diseases that are closely linked with the cerebellar functional abnormalities. Our results could collectively help to rethink the genetic substrates underlying the cerebellar functional organization and offer possible micro-macro interacted mechanistic interpretations of the cerebellum-involved high order functions and dysfunctions in neuropsychiatric disorders.

neuroscience↗