Biology subjects

Xu, Y.

Publications and source records attributed to Xu, Y..

983 records · Page 55Linked to original sources

bioRxiv2017

Functional Modeling of Plant Growth Dynamics

Recent advances in automated plant phenotyping have enabled the collection time series measurements from the same plants of a wide range of traits over different developmental time scales. The availability of time series phenotypic datasets has increased interest in statistical approaches for comparing patterns of change between different plant genotypes and different treatment conditions. Two widely used methods of modeling growth over time are point-wise analysis of variance (ANOVA) and parametric sigmoidal curve fitting. Point-wise ANOVA yields discontinuous growth curves, which do not reflect the true dynamics of growth patterns in plants. In contrast, fitting a parametric model to a time series of observations does capture the trend of growth, however these models require assumptions regarding the true pattern of plant growth. Depending on the species, treatment regime, and subset of the plant lifecycle sampled this assumptions will not always hold true. Here we introduce a different approach - functional ANOVA - which yields continuous growth curves without requiring assumptions regarding patterns of plant growth. We compare and validate this approach using data from an experiment measuring growth of two maize (Zea mays ssp. mays) genotypes under two water availability treatments over a 21-day period. Functional ANOVA enables a nonparametric estimation of the dynamics of changes in plant traits over time without assumptions regarding curve shape. In addition to estimating smooth curves of trait values over time, functional ANOVA also estimates the the derivatives of these curves - e.g. growth rates - simultaneously. Using two different subsampling strategies, we demonstrate that this functional ANOVA method enables the comparison of growth curves between plants phenotyped on non-overlapping days with little reduction in estimation accuracy. This means functional ANOVA based approaches can allow larger numbers of samples and biological replicates to be scored in a single experiment given fixed amounts of phenotyping infrastructure and personnel.

plant biology↗

bioRxiv2017

Deep learning of the splicing (epi)genetic code reveals a novel candidate mechanism linking histone modifications to ESC fate decision

Alternative splicing (AS) is a genetically and epigenetically regulated pre-mRNA processing to increase transcriptome and proteome diversity. Comprehensively decoding these regulatory mechanisms holds promise in getting deeper insights into a variety of biological contexts involving in AS, such as development and diseases. We assembled splicing (epi)genetic code, DeepCode, for human embryonic stem cell (hESC) differentiation by integrating heterogeneous features of genomic sequences, 16 histone modifications with a multi-label deep neural network. With the advantages of epigenetic features, DeepCode significantly improves the performance in predicting the splicing patterns and their changes during hESC differentiation. Meanwhile, DeepCode reveals the superiority of epigenomic features and their dominant roles in decoding AS patterns, highlighting the necessity of including the epigenetic properties when assembling a more comprehensive splicing code. Moreover, DeepCode allows the robust predictions across cell lineages and datasets. Especially, we identified a putative H3K36me3-regulated AS event leading to a nonsense-mediated mRNA decay of BARD1. Reduced BARD1 expression results in the attenuation of ATM/ATR signalling activities and further the hESC differentiation. These results suggest a novel candidate mechanism linking histone modifications to hESC fate decision. In addition, when trained in different contexts, DeepCode can be expanded to a variety of biological and biomedical fields.

bioinformatics↗

bioRxiv2017

Integrated transcriptome and epigenome analyses identify alternative splicing as a novel candidate linking histone modifications to embryonic stem cell fate decision

BackgroundUnderstanding the embryonic stem cell (ESC) fate decision between self-renewal and proper differentiation is important for developmental biology and regenerative medicine. Attention has focused on mechanisms involving histone modifications, alternative pre-mRNA splicing, and cell-cycle progression. However, their intricate interrelations and joint contributions to ESC fate decision remain unclear.\n\nResultsWe analyze the transcriptomes and epigenomes of human ESC and five types of differentiated cells. We identify thousands of alternatively spliced exons and reveal their development and lineage-dependent characterizations. Several histone modifications show dynamic changes in alternatively spliced exons and three are strongly associated with 52.8% of alternative splicing events upon hESC differentiation. The histone modification-associated alternatively spliced genes predominantly function in G2/M phases and ATM/ATR-mediated DNA damage response pathway for cell differentiation, whereas other alternatively spliced genes are enriched in the G1 phase and pathways for self-renewal. These results imply a potential epigenetic mechanism by which some histone modifications contribute to ESC fate decision through the regulation of alternative splicing in specific pathways and cell-cycle genes. Supported by experimental validations and extended dataset from Roadmap/ENCODE projects, we exemplify this mechanism by a cell cycle-related transcription factor, PBX1, which regulates the pluripotency regulatory network by binding to NANOG. We suggest that the isoform switch from PBX1a to PBX1b links H3K36me3 to hESC fate determination through the PSIP1/SRSF1 adaptor, which results in the exon skipping of PBX1.\n\nConclusionWe reveal the mechanism by which alternative splicing links histone modifications to stem cell fate decision.

bioinformatics↗

bioRxiv2017

Cryo-electron tomography reveals that dynactin recruits a team of dyneins for processive motility

A key player in the intracellular trafficking network is cytoplasmic dynein, a protein complex that transports molecular cargo along microtubule tracks. It has been shown that vertebrate dyneins movement becomes strikingly enhanced upon interacting with a cofactor named dynactin and one of several cargo-adapters, such as BicaudalD2. However, the mechanisms responsible for this increase in transport efficiency are not well understood, largely due to a lack of structural information. We used cryo-electron tomography to visualize the first 3-dimensional structure of the intact dynein-dynactin complex bound to microtubules. Our structure reveals that the dynactin-cargo-adapter complex recruits and binds to two dimeric cytoplasmic dyneins. Interestingly, the dynein motor organization closely resembles that of axonemal dynein, suggesting that cytoplasmic dynein and axonemal dyneins may utilize similar mechanisms to coordinate multiple motors. We propose that grouping dyneins onto a single dynactin scaffold promotes collective force production as well as unidirectional processive motility. These findings provide a structural platform that facilitates a deeper biochemical and biophysical understanding of dynein regulation and cellular transport.

cell biology↗

bioRxiv2017

A high-throughput analysis method of microdroplet PCR coupled with fluorescence spectrophotometry

Here we report a novel microdroplet PCR method combined with fluorescence spectrophotometry (MPFS), which allows for qualitative, quantitative and high -throughput detection of multiple DNA targets. In this study, each pair of primers was labeled with a specific fluorophore. Through microdroplet PCR, a target DNA was amplified and labeled with the same fluorophore. After products purification, the DNA products tagged with different fluorophores could be analyzed qualitatively by the fluorescent intensity determination. The relative fluorensence unit was also measured to construct the standard curve and to achieve quantitative analysis. In a reaction, the co -amplified products with different fluorophores could be simultaneously analyzed to achieve high -throughput detection. We used four kinds of GM maize as a model to confirm this theory. The qualitative results revealed high specificity and sensitivity of 0.5% (w / w). The quantitative results revealed that the limit of detection was 103copies and with good repeatability. Moreover, reproducibility assay were further performed using four foodborne pathogenic bacteria. Consequently, the same qualitative, quantitative and high-throughput results were confirmed as the four GM maize.

biochemistry↗

bioRxiv2017

Estrogen represses Tgfbr1 and Bmpr1a expression via estrogen receptor beta in MC3T3-E1 cells

MC3T3-E1 is a clonal pre-osteoblastic cell line derived from newborn mouse calvaria, which is commonly used in osteoblast studies. To investigate the effects of estrogen on osteoblasts, we treated MC3T3-E1 cells with various concentrations of estrogen and assessed their proliferation. Next, we performed RNA deep sequencing to investigate the effects on estrogen target genes. Bmpr1a and Tgfbr1, important participants in the TGF-beta signaling pathway, were down-regulated in our deep sequencing results. Bioinformatics analysis revealed that estrogen receptor response elements (EREs) were present in the Bmpr1a and Tgfbr1 promoters. Culturing the cells with the estrogen receptor (ER) alpha or beta antagonists 1,3-bis(4-hydroxyphenyl)-4-methyl-5-[4-(2-piperidinylethoxy)phenol]-1H-pyrazole dihydrochloride (MPP) or 4-[2-phenyl-5,7-bis(trifluoromethyl) pyrazolo[1,5-alpha]pyrimidin-3-yl] phenol (PTHPP), respectively, demonstrated that ER beta is involved in the estrogen-mediated repression of Tgfbr1 and Bmpr1a.The chromatin immunoprecipitation (ChIP) results were consistent with the conclusion that E2 increased the binding of ER beta at the EREs located in the Tgfbr1 and Bmpr1a promoters. Our research provides new insight into the role of estrogen in bone metabolisms.

biochemistry↗

bioRxiv2017

Conventional and hyperspectral time-series imagingof maize lines widely used in field trials

Maize (Zea mays ssp. mays) is one of three crops, along with rice and wheat, responsible for more than 1/2 of all calories consumed around the world. Increasing the yield and stress tolerance of these crops is essential to meet the growing need for food. The cost and speed of plant phenotyping is currently the largest constraint on plant breeding efforts. Datasets linking new types of high throughput phenotyping data collected from plants to the performance of the same genotypes under agronomic conditions across a wide range of environments are essential for developing new statistical approaches and computer vision based tools. A set of maize inbreds - primarily recently off patent lines - were phenotyped using a high throughput platform at University of Nebraska-Lincoln. These lines have been previously subjected to high density genotyping, and scored for a core set of 13 phenotypes in field trials across 13 North American states in two years by the Genomes to Fields consortium. A total of 485 GB of image data including RGB, hyperspectral, fluorescence and thermal infrared photos has been released. Correlations between image-based measurements and manual measurements demonstrated the feasibility of quantifying variation in plant architecture using image data. However, naive approaches to measuring traits such as biomass can introduce nonrandom measurement errors confounded with genotype variation. Analysis of hyperspectral image data demonstrated unique signatures from stem tissue. Integrating heritable phenotypes from high-throughput phenotyping data with field data from different environments can reveal previously unknown factors influencing yield plasticity.

plant biology↗

bioRxiv2017

Comprehensive Molecular Characterization of Mitochondrial Genomes in Human Cancers

Mitochondria are essential cellular organelles that play critical roles in cancer development. Through International Cancer Genome Consortium, we performed a multidimensional characterization of mitochondrial genomes using the whole-genome sequencing data of ~2,700 patients across 37 cancer types and related RNA-sequencing data. Our analysis presents the most definitive mutational landscape of mitochondrial genomes including a novel hypermutated case. We observe similar mutational signatures across cancer types, suggesting powerful endogenous mutational processes in mitochondria. Truncating mutations are remarkably enriched in kidney, colorectal and thyroid cancers and associated with the activation of critical signaling pathways. We find frequent somatic nuclear transfers of mitochondrial DNA (especially in skin and lung cancers), some of which disrupt therapeutic target genes (e.g., ERBB2). The mitochondrial DNA copy number shows great variations within and across cancers and correlates with clinical variables. Co-expression analysis highlights the function of mitochondrial genes in oxidative phosphorylation, DNA repair, and cell cycle; and reveals their connections with clinically actionable genes. Our study, including an open-access data portal, lays a foundation for understanding the interplays between the cancer mitochondrial and nuclear genomes and translating mitochondrial biology into clinical applications.

genomics↗

bioRxiv2017

The structural basis for regulation of the nucleo-cytoplasmic distribution of Bag6 by TRC35

The metazoan protein BCL2-associated athanogene cochaperone 6 (Bag6) forms a hetero-trimeric complex with ubiquitin-like 4A (Ubl4A) and transmembrane domain recognition complex 35 (TRC35). This Bag6 complex is involved in tail-anchored protein targeting and various protein quality control pathways in the cytosol as well as regulating transcription and histone methylation in the nucleus. Here we present a crystal structure of Bag6 and its cytoplasmic retention factor TRC35, revealing that TRC35 is remarkably conserved throughout opisthokont lineage except at the C-terminal Bag6-binding groove, which evolved to accommodate a novel metazoan factor Bag6. Remarkably, while TRC35 and its fungal homolog guided entry of tail-anchored protein 4 (Get4) utilize a conserved hydrophobic patch to bind their respective C-terminal binding partners Bag6 and Get5, Bag6 wraps around TRC35 on the opposite face relative to the Get4-5 interface. We further demonstrate that the residues involved in TRC35 binding are not only critical for occluding the Bag6 nuclear localization sequence from karyopherin binding to retain Bag6 in the cytosol, but also for preventing TRC35 from succumbing to RNF126-mediated ubiquitylation and degradation. The results provide a mechanism for regulation of Bag6 nuclear localization and the functional integrity of the Bag6 complex in the cytosol.

biochemistry↗

bioRxiv2017

Karyotype stability and unbiased fractionation in the paleo-allotetraploid Cucurbita genomes

The Cucurbita genus contains several economically important species in the Cucurbitaceae family. Interspecific hybrids between C. maxima and C. moschata are widely used as rootstocks for other cucurbit crops. We report high-quality genome sequences of C. maxima and C. moschata and provide evidence supporting an allotetraploidization event in Cucurbita. We are able to partition the genome into two homoeologous subgenomes based on different genetic distances to melon, cucumber and watermelon in the Benincaseae tribe. We estimate that the two diploid progenitors successively diverged from Benincaseae around 31 and 26 million years ago (Mya), and the allotetraploidization happened earlier than 3 Mya, when C. maxima and C. moschata diverged. The subgenomes have largely maintained the chromosome structures of their diploid progenitors. Such long-term karyotype stability after polyploidization is uncommon in plant polyploids. The two subgenomes have retained similar numbers of genes, and neither subgenome is globally dominant in gene expression. Allele-specific expression analysis in the C. maxima x C. moschata interspecific F1 hybrid and the two parents indicates the predominance of trans-regulatory effects underlying expression divergence of the parents, and detects transgressive gene expression changes in the hybrid correlated with heterosis in important agronomic traits. Our study provides insights into plant genome evolution and valuable resources for genetic improvement of cucurbit crops.

genomics↗

bioRxiv2017

Mapping Human Hematopoietic Hierarchy At Single Cell Resolution By Microwell-seq

The classical hematopoietic hierarchy, which is mainly built with fluorescence-activated cell sorting (FACS) technology, proves to be inaccurate in recent studies. Single cell RNA-seq (scRNA-seq) analysis provides a solution to overcome the limit of FACS-based cell type definition system for the dissection of complex cellular hierarchy. However, large-scale scRNA-seq is constrained by the throughput and cost of traditional methods. Here, we developed Microwell-seq, a high-throughput and low-cost scRNA-seq platform using extremely simple devices. Using Microwell-seq, we constructed a single-cell resolution transcriptome atlas of human hematopoietic differentiation hierarchy by profiling more than 50,000 single cells throughout adult human hematopoietic system. We found that adult human hematopoietic stem and progenitor cell (HSPC) compartment is dominated by progenitors primed with lineage specific regulators. Our analysis revealed differentiation pathways for each cell types, through which HSPCs directly progress to lineage biased progenitors before differentiation. We propose a revised adult human hematopoietic hierarchy independent of oligopotent progenitors. Our study also demonstrates the broad applicability of Microwell-seq technology.

cell biology↗