Biology subjects

Zhou, T.

Publications and source records attributed to Zhou, T..

221 records · Page 13Linked to original sources

bioRxiv2018

Evolution analysis and expression divergence of the chitinase gene family against Leptosphaeria maculans and Sclerotinia sclerotiorum infection in Brassica napus

AbstractBlackleg and sclerotinia stem rot caused by Leptosphaeria maculans and Sclerotinia sclerotiorum respectively are two major diseases in rapeseed worldwide, which cause serious yield losses. Chitinases are pathogenesis-related proteins and play important roles in host resistance to various pathogens and abiotic stress responses. However, a systematic investigation of the chitinase gene family and its expression profile against L. maculans and S. sclerotiorum infection in rapeseed remains elusive. The recent release of assembled genome sequence of rapeseed allowed us to perform a genome-wide identification of the chitinase gene family. In this study, 68 chitinase genes were identified in Brassica napus genome. These genes were divided into five different classes and distributed among 15 chromosomes. Evolutionary analysis indicated that the expansion of the chitinase gene family was mainly attributed to segmental and tandem duplication. Moreover, the expression profiling of the chitinase gene family was investigated using RNA sequencing (RNA-Seq) and the results revealed that some chitinase genes were both induced while the other members exhibit distinct expression in response to L. maculans and S. sclerotiorum infection. This study presents a comprehensive survey of the chitinase gene family in B. napus and provides valuable information for further understanding the functions of the chitinase gene family.

plant biology↗

bioRxiv2018

Topographer Reveals Stochastic Dynamics of Cell Fate Decisions from Single-Cell RNA-Seq Data

Cell fate decisions play a pivotal role in development but technologies for dissecting them are limited. We developed a multifunction new method, Topographer to construct a quantitative Waddingtons landscape of single-cell transcriptomic data. This method is able to identify complex cell-state transition trajectories and to estimate complex cell-type dynamics characterized by fate and transition probabilities. It also infers both marker gene networks and their dynamic changes as well as dynamic characteristics of transcriptional bursting along the cell-state transition trajectories. Applying this method to single-cell RNA-seq data on the differentiation of primary human myoblasts, we not only identified three known cell types but also estimated both their fate probabilities and transition probabilities among them. We found that the percent of genes expressed in a bursty manner is significantly higher at (or near) the branch point ([~]97%) than before or after branch (below 80%), and that both gene-gene and cell-cell correlation degrees are apparently lower near the branch point than away from the branching. Topographer allows revealing of cell fate mechanisms in a coherent way at three scales: cell lineage (macroscopic), gene network (mesoscopic) and gene expression (microscopic).

systems biology↗

bioRxiv2017

Deep learning reveals many more inter-protein residue-residue contacts than direct coupling analysis

Intra-protein residue-level contact prediction has drawn a lot of attentions in recent years and made very good progress, but much fewer methods are dedicated to inter-protein contact prediction, which are important for understanding how proteins interact at structure and residue level. Direct coupling analysis (DCA) is popular for intra-protein contact prediction, but extending it to inter-protein contact prediction is challenging since it requires too many interlogs (i.e., interacting homologs) to be effective, which cannot be easily fulfilled especially for a putative interacting protein pair in eukaryotes. We show that deep learning, even trained by only intra-protein contact maps, works much better than DCA for inter-protein contact prediction. We also show that a phylogeny-based method can generate a better multiple sequence alignment for eukaryotes than existing genome-based methods and thus, lead to better inter-protein contact prediction. Our method shall be useful for protein docking, protein interaction prediction and protein interaction network construction.

bioinformatics↗

bioRxiv2017

Allopatric divergence, local adaptation, and multiple Quaternary refugia in a long-lived tree (Quercus spinosa) from subtropical China

O_LIThe complex geography and climatic changes occurring in subtropical China during the Tertiary and Quaternary might have provided substantial opportunities for allopatric speciation. To gain further insight into these processes, we reconstruct the evolutionary history of Quercus spinosa, a common evergreen tree species mainly distributed in this area.\nC_LIO_LIForty-six populations were genotyped using four chloroplast DNA regions and 12 nuclear microsatellite loci to assess genetic structure and diversity, which was supplemented by divergence time and diversification rate analyses, environmental factor analysis, and ecological niche modeling of the species distributions in the past and at present.\nC_LIO_LIThe genetic data consistently identified two lineages: the western Eastern Himalaya-Hengduan Mountains lineage and the eastern Central-Eastern China lineage, mostly maintained by populations environmental adaptation. These lineages diverged through climate/orogeny-induced vicariance during the Neogene and remained separated thereafter. Genetic data strongly supported the multiple refugia (per se, interglacial refugia) or refugia within refugia hypotheses to explain Q. spinosa phylogeography in subtropical China.\nC_LIO_LIQ. spinosa population structure highlighted the importance of complex geography and climatic changes occurring in subtropical China during the Neogene in providing substantial opportunities for allopatric divergence.\nC_LI

evolutionary biology↗

bioRxiv2016

Prototyping a valinomycin biosynthesis pathway within a cell-free transcription-translation (TX-TL) system

1Many natural metabolites have antibacterial, antiviral, or anticancer effects and can be developed into new drugs. However, working with the microorganisms that produce these products can be challenging since they are not as well characterized as a model organism like Escherichia coli. In this paper, we investigate the potential for a cell-free transcription-translation (TX-TL) system to provide a rapid prototyping platform for characterizing new genetic pathways. We use the valinomycin biosynthesis pathway as a test case, and we show successful heterologous expression of the heterodimeric valinomycin synthetase (VlmSyn, Vlm1: 374 kDa and Vlm2: 284 kDa) from Strep-tomyces tsusimaensis within the TX-TL system. Using LC-MS analysis, we find that valinomycin is produced at low but detectable levels, even when only one out of the three basic precursors is fed into the system. Our work represents another step towards applying cell-free biosynthesis to the discovery and characterization of new natural products.

synthetic biology↗