508 research outputs found

    FreePSI: an alignment-free approach to estimating exon-inclusion ratios without a reference transcriptome.

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    Alternative splicing plays an important role in many cellular processes of eukaryotic organisms. The exon-inclusion ratio, also known as percent spliced in, is often regarded as one of the most effective measures of alternative splicing events. The existing methods for estimating exon-inclusion ratios at the genome scale all require the existence of a reference transcriptome. In this paper, we propose an alignment-free method, FreePSI, to perform genome-wide estimation of exon-inclusion ratios from RNA-Seq data without relying on the guidance of a reference transcriptome. It uses a novel probabilistic generative model based on k-mer profiles to quantify the exon-inclusion ratios at the genome scale and an efficient expectation-maximization algorithm based on a divide-and-conquer strategy and ultrafast conjugate gradient projection descent method to solve the model. We compare FreePSI with the existing methods on simulated and real RNA-seq data in terms of both accuracy and efficiency and show that it is able to achieve very good performance even though a reference transcriptome is not provided. Our results suggest that FreePSI may have important applications in performing alternative splicing analysis for organisms that do not have quality reference transcriptomes. FreePSI is implemented in C++ and freely available to the public on GitHub

    Genome-wide identification of long intergenic non-coding RNAs of responsive to powdery mildew stress in wheat (Triticum aestivum)

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    Wheat powdery mildew caused by Blumeria graminis f. sp. tritici is one of the most serious foliar diseases of wheat, causing grain yield and quality degradation by affecting plant photosynthesis. It is an effective method to improve the disease resistance of wheat plants by molecular breeding. With the continuous development of sequencing technology, long intergenic noncoding RNAs (lincRNAs) have been discovered in many eukaryotes and act as key regulators of many cellular processes. In this study, 12 sets of RNA-seq data from wheat leaves pre- and post-pathogen infection were analyzed and 2,266 candidate lincRNAs were identified. Consistent with previous findings, lincRNA has shorter length and fewer exons than mRNA. The results of differential expression analysis showed that 486 DE-lincRNAs were selected as lincRNAs that could respond to powdery mildew stress. Since lincRNAs may be functionally related to their adjacent target genes, the target genes of these lincRNAs were predicted, and the GO and KEGG functional annotations of the predicted target genes were performed. Integrating the functions of target genes and the biological processes in which they were involved uncovered 23 lincRNAs that may promote or inhibit the occurrence of wheat powdery mildew. Co-expression patterns of lincRNAs with their adjacent mRNAs showed that some lincRNAs showed significant correlation with the expression patterns of their potential target genes. These suggested an involvement of lincRNAs in pathogen stress response, which will provide a further understanding of the pathogenic mechanism of wheat powdery mildew

    Numerical study of acoustophoretic manipulation of particles in microfluidic channels

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    The microfluidic technology based on surface acoustic waves (SAW) has been developing rapidly, as it can precisely manipulate fluid flow and particle motion at microscales. We hereby present a numerical study of the transient motion of suspended particles in a microchannel. In conventional studies, only the microchannel’s bottom surface generates SAW and only the final positions of the particles are analyzed. In our study, the microchannel is sandwiched by two identical SAW transducers at both the bottom and top surfaces while the channel’s sidewalls are made of poly-dimethylsiloxane (PDMS). Based on the perturbation theory, the suspended particles are subject to two types of forces, namely the Acoustic Radiation Force (ARF) and the Stokes Drag Force (SDF), which correspond to the first-order acoustic field and the second-order streaming field, respectively. We use the Finite Element Method (FEM) to compute the fluid responses and particle trajectories. Our numerical model is shown to be accurate by verifying against previous experimental and numerical results. We have determined the threshold particle size that divides the SDF-dominated regime and the ARF-dominated regime. By examining the time scale of the particle movement, we provide guidelines on the device design and operation

    Team Dynamics Theory: Nomological network among cohesion, team mental models, coordination, and collective efficacy

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    I put forth a theoretical framework, namely Team Dynamics Theory (TDT), to address the need for a parsimonious yet integrated, explanatory and systemic view of team dynamics. In TDT, I integrate team processes and outputs and explain their relationships within a systemic view of team dynamics. Specifically, I propose a generative nomological network linking cohesion, team mental models, coordination, collective efficacy, and team outcomes. From this nomological conceptualization, I illustrate how myriad alternative models can be derived to account for variance in different working teams, each comprised of unique members, and embedded in singular contexts. I outline TDT’s applied implications for team development, the enhancement of team functioning, and the profiling of team resilience. I conclude by discussing how TDT’s ontological and nomological propositions can be tested through various theoretical inquiries, methodological approaches, and intervention-based studies
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