Biology subjects

Li, N.

Publications and source records attributed to Li, N..

293 records · Page 17Linked to original sources

bioRxiv2017

ZmCOL3, a CCT-domain containing gene affects maize adaptation as a repressor and upstream of ZmCCT

Flowering time is a vital trait to control the adaptation of flowering plants to different environments. CCT-domain containing genes are considered to play an important role in plants flowering. Among 53 maize CCT family genes, 28 of them were located in the flowering time QTL regions and 16 genes were significant associated with flowering time based on candidate gene-based association mapping analysis. Furthermore, a CCT gene named as ZmCOL3 was validated to be a flowering repressor upstream of ZmCCT which is one of the key genes regulating maize flowering. The overexpressed ZmCOL3 could delay flowering time about 4 days whether in long day or short day conditions. The absent of one cytosine in 3UTR and the present of 551bp fragment in promoter regions are likely the causal polymorphisms which may contribute to the maize adaptation from tropical to temperate regions. ZmCOL3 could transactivate ZmCCT transcription or interfere circadian clock to inhibit flowering which was integrated in the modified model of maize photoperiod pathway.\n\nHighlightMaize CCT genes influence flowering time in different latitude environments and one of them named ZmCOL3 is a flowering time repressor which could transactivate ZmCCT transcription to delay flowering.

genetics↗

bioRxiv2017

Interactive Visual Analysis of Mass Cytometry Data by Hierarchical Stochastic Neighbor Embedding Reveals Rare Cell Types

Mass cytometry allows high-resolution dissection of the cellular composition of the immune system. However, the high-dimensionality, large size, and non-linear structure of the data poses considerable challenges for data analysis. In particular, dimensionality reduction-based techniques like t-SNE offer single-cell resolution but are limited in the number of cells that can be analysed. Here we introduce Hierarchical Stochastic Neighbor Embedding (HSNE) for the analysis of mass cytometry datasets. HSNE constructs a hierarchy of non-linear similarities that can be interactively explored with a stepwise increase in detail up to the single-cell level. We applied HSNE to a study on gastrointestinal disorders and three other available mass cytometry datasets. We found that HSNE efficiently replicates previous observations and identifies rare cell populations that were previously missed due to downsampling. Thus, HSNE removes the scalability limit of conventional t-SNE analysis, a feature that makes it highly suitable for the analysis of massive high-dimensional datasets.

bioinformatics↗

bioRxiv2017

Optimization of Alginante- poly-L-lysine Microencapsules Strength by Box-Behnken Model for CHO Culture in Stirred Tank Bioreactor

Summary statementBox-Behnken model is an efficient method to optimized process conditions of microencapsules strength for long-term cell culture, promotes CHO cells viability and protein production in a stirred tank bioreactor.\n\nABSTRACTCell microencapsulation technology has been proved to be a valuable technology in the fields of large-scale cell culture. It is important to accurately construct the microcapsule membranes with desired properties including a certain thickness suitable for cell growth, and maximum strength for the stability of microencapsules. As single factor experiments are time-consuming to obtain the desired membrane preparation conditions, Box-Behnken model was used to investigate the interactions among reaction conditions, predict the optimized reaction conditions for given purpose, that was membrane with maximum strength and desired thickness for microencapsulated cell culture. Significant values of R2 in this study indicated the model theoretical values are very close to the measured values. Based on the desired membrane thickness, the process of maximum strength was optimized, and the prediction agreement of measured value and model theoretical value was 91.11%. The optimized microencapsules with maximum strength and 15 m membrane thickness promote CHO cells viability and protein production in stirred tank bioreactor. The result shows that Box-Behnken model is an efficient method to optimized process conditions of microencapsules strength for long-term cell culture.

bioengineering↗

bioRxiv2016

ECL 2.0: Exhaustively Identifying Cross-Linked Peptides with a Linear Computational Complexity

Chemical cross-linking coupled with mass spectrometry is a powerful tool to study protein-protein interactions and protein conformations. Two linked peptides are ionized and fragmented to produce a tandem mass spectrum. In such an experiment, a tandem mass spectrum contains ions from two peptides. The peptide identification problem becomes a peptide-peptide pair identification problem. Currently, most existing tools dont search all possible pairs due to the quadratic time complexity. Consequently, a significant percentage of linked peptides are missed. In our earlier work, we developed a tool named ECL to search all pairs of peptides exhaustively. While ECL does not miss any linked peptides, it is very slow due to the quadratic computational complexity, especially when the database is large. Furthermore, ECL uses a score function without statistical calibration, while researchers1,2 have demonstrated that using a statistical calibrated score function can achieve a higher sensitivity than using an uncalibrated one.\n\nHere, we propose an advanced version of ECL, named ECL 2.0. It achieves a linear time and space complexity by taking advantage of the additive property of a score function. It can analyze a typical data set containing tens of thousands of spectra using a large-scale database containing thousands of proteins in a few hours. Comparison with other five state-of-the-art tools shows that ECL 2.0 is much faster than pLink, StavroX, ProteinProspector, and ECL. Kojak is the only one tool that is faster than ECL 2.0. But Kojak does not exhaustively search all possible peptide pairs. We also adopt an e-value estimation method to calibrate the original score. Comparison shows that ECL 2.0 has the highest sensitivity among the state-of-the-art tools. The experiment using a large-scale in vivo cross-linking data set demonstrates that ECL 2.0 is the only tool that can find PSMs passing the false discovery rate threshold. The result illustrates that exhaustive search and well calibrated score function are useful to find PSMs from a huge search space.

bioinformatics↗

bioRxiv2016

normR: Regime enrichment calling for ChIP-seq data

ChIP-seq probes genome-wide localization of DNA-associated proteins. To mitigate technical biases ChIP-seq read densities are normalized to read densities obtained by a control. Our statistical framework \"normR\" achieves a sensitive normalization by accounting for the effect of putative protein-bound regions on the overall read statistics. Here, we demonstrate normRs suitability in three studies: (i) calling enrichment for high (H3K4me3) and low (H3K36me3) signal-to-ratio data; (ii) identifying two previously undescribed H3K27me3 and H3K9me3 heterochromatic regimes of broad and peak enrichment; and (iii) calling differential H3K4me3 or H3K27me3-enrichment between HepG2 hepatocarcinoma cells and primary human Hepatocytes. normR is readily available on http://bioconductor.org/packages/normr

bioinformatics↗