Biology subjects

Xing, D.

Publications and source records attributed to Xing, D..

23 records · Page 2Linked to original sources

bioRxiv2020

Analytical models for β-diversity and the power-law scaling of β-deviation

O_LI{beta}-diversity is a primary biodiversity pattern for inferring community assembly. A randomized null model that generates a standardized {beta}-deviation has been widely used for this purpose. However, the null model has been much debated and its application is limited to abundance data. C_LIO_LIHere we derive analytical models for {beta}-diversity to address the debate, clarify the interpretation, and extend the application to occurrence data. C_LIO_LIThe analytical analyses show unambiguously that the standardized {beta}-deviation is a quantification of the effect size of non-random spatial distribution of species on {beta}-diversity for a given species abundance distribution. It robustly scales with sampling effort following a power law with exponent of 0.5. This scaling relationship offers a simple method for comparing {beta}-diversity of communities of different sizes. C_LIO_LIAssuming logseries distribution for the metacommunity species abundance distribution, our model allows for calculation of the standardized {beta}-deviation using occurrence data plus a datum on the total abundance. C_LIO_LIOur theoretical model justifies and generalizes the use of the {beta} null model for inferring community assembly rules. C_LI

ecology↗

bioRxiv2020

Genomic Architecture of Cells in Tissues (GeACT): Study of Human Mid-gestation Fetus

By circumventing cellular heterogeneity, single cell omics have now been widely utilized for cell typing in human tissues, culminating with the undertaking of human cell atlas aimed at characterizing all human cell types. However, more important are the probing of gene regulatory networks, underlying chromatin architecture and critical transcription factors for each cell type. Here we report the Genomic Architecture of Cells in Tissues (GeACT), a comprehensive genomic data base that collectively address the above needs with the goal of understanding the functional genome in action. GeACT was made possible by our novel single-cell RNA-seq (MALBAC-DT) and ATAC-seq (METATAC) methods of high detectability and precision. We exemplified GeACT by first studying representative organs in human mid-gestation fetus. In particular, correlated gene modules (CGMs) are observed and found to be cell-type-dependent. We linked gene expression profiles to the underlying chromatin states, and found the key transcription factors for representative CGMs. HighlightsO_LIGenomic Architecture of Cells in Tissues (GeACT) data for human mid-gestation fetus C_LIO_LIDetermining correlated gene modules (CGMs) in different cell types by MALBAC-DT C_LIO_LIMeasuring chromatin open regions in single cells with high detectability by METATAC C_LIO_LIIntegrating transcriptomics and chromatin accessibility to reveal key TFs for a CGM C_LI

genomics↗

bioRxiv2020

Transformation of single-cell three-dimensional genome structure during postnatal development of the mammalian brain

Both transcription and 3D organization of the mammalian genome play critical roles in neurodevelopment and its disorders. However, 3D genome structures of single brain cells have not been solved; little is known about the dynamics of single-cell transcriptome and 3D genome after birth. Here we generate a transcriptome atlas of 3,517 cells and a 3D genome atlas of 3,646 cells from the developing mouse cortex and hippocampus, using our high-resolution MALBAC-DT and Dip-C methods. In adults, 3D genome "structure types" delineate all major cell types, with high correlation between A/B compartments and gene expression. During development, both transcriptome and 3D genome are extensively transformed in the first postnatal month. In neurons, 3D genome is rewired across multiple scales, correlated with gene expression modules and independent of sensory experience. Finally, we examine allele-specific structure of imprinted genes, revealing local and chromosome-wide differences. These findings uncover a previously unknown dimension of neurodevelopment. HIGHLIGHTSO_LITranscriptomes and 3D genome structures of single brain cells (both neurons and glia) in the developing mouse forebrain C_LIO_LICell type identity encoded in the 3D wiring of the mammalian genome ("structure types") C_LIO_LIMajor transformation of both transcriptome and 3D genome during the first month of life, independent of sensory experience C_LIO_LIAllele-specific 3D structure at 7 imprinted gene loci, including one that spans a whole chromosome C_LI

neuroscience↗

bioRxiv2019

An evaluation model for aboveground biomass Based on Hyperspectral Data from field and TM8 in Khorchin grassland, China

Biomass is an important indicator for monitoring vegetation degradation and productivity. This study tests the applicability of Hyperspectral Remote-Sensing in situ measurements for high-precision estimation aboveground biomass (AGB) on regional scales of Khorchin grassland landscape in Inner Mongolia, China. Field experiments were carried out which collected hyperspectral data with a portable visible/NIR hyperspectral spectrometer (SOC 710), and collected aboveground net primary productivity (ANPP). Ground spectral models were then developed to estimate ANPP from the normalized difference vegetation index (NDVI), which was measured in the field following the same method as that of the Thematic Mapper(TM) from the Landsat 8 land imager (TM_NDVI). Regression analysis was used to assess the relationship between ANPP and NDVI based on coefficients of determination (R2) and error analysis. The estimation of ANPP had unique optimal regression models. By comparing the different spectral inversion models, we selected an exponential model associating ANPP with NDVI (ANPP = 12.523*e3.370*(0.462*TM_NDVI+0.413), standard error = 24.74 g m-2, R2 = 0.636, P < 0.001). This study suggests that the model can be used to monitor the condition and estimate the productivity of grassland at regional scales. The results still show a high potential to map grassland degradation proxies on the ground hyperspectral model. Thus, this study presents biomass hyperspectral inversion technology to remotely detect and monitor grassland degradation and productivity at high precision.

ecology↗

bioRxiv2019

Functional clusters of neurons in layer 6 of macaque V1

AbstracLayer 6 appears to perform a very important role in the function of macaque primary visual cortex, V1, but not enough is understood about the functional characteristics of neurons in the layer 6 population. It is unclear to what extent the population is homogeneous with respect to their visual properties or if one can identify distinct sub-populations. Here we performed a cluster analysis based on measurements of the responses of single neurons in layer 6 of primary visual cortex to achromatic grating stimuli that varied in orientation, direction of motion, spatial and temporal frequency, and contrast. The visual stimuli were presented in a stimulus window that was also varied in size. Using the responses to parametric variation in these stimulus variables we extracted a number of tuning response measures and used them in the cluster analysis. Six main clusters emerged along with some smaller clusters. Additionally we asked whether parameter distributions from each of the clusters were statistically different. There were clear separations of parameters between some of the clusters, particularly for f1/f0 ratio, direction selectivity, and temporal frequency bandwidth but other dimensions also showed differences between clusters. Our data suggest that in layer 6, across the spatial extent of a single cortical hypercolumn, there are multiple parallel circuits that provide information about different aspects of the visual stimulus.

neuroscience↗