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In JoVE (1)
Other Publications (4)
Articles by Lin Fan in JoVE
JoVE Clinical and Translational Medicine
Development of Obliterative Bronchiolitis in a Murine Model of Orthotopic Lung Transplantation
1Departments of Medicine, Microbiology and Immunology, Indiana University School of Medicine, 2Center for Immunobiology, Indiana University School of Medicine
Obliterative bronchiolitis is the key impediment to the long-term survival of lung transplant recipients and the lack of a robust preclinical model precludes examining obliterative bronchiolitis immunopathogenesis. Unlike other solid organ transplants, vascularized mouse lung transplantation has only recently been developed. Here we show our independently developed obliterative bronchiolitis model after murine orthotopic single-lung transplantation.
Other articles by Lin Fan on PubMed
Monitoring Dermal Wound Healing After Mesenchymal Stem Cell Transplantation Using Nonlinear Optical Microscopy
Nonlinear optical microscopy (NLOM) was applied for monitoring dermal wound healing after mesenchymal stem cell (MSC) transplantation. Our results showed that NLOM can reveal different regeneration processes of collagen in nontreated and MSC-treated wound dermis. Specifically, the temporal increases in the intensity of second-harmonic-generation signals can quantify kinetic properties of collagen regeneration. Orientation analysis of collagen fiber bundles can monitor the formation of new normal collagen fiber bundles, which is an indicator for evaluating the therapy response. It was also found that NLOM can track MSCs' location and recruitment. These findings suggested that NLOM is ideal for monitoring the progress of dermal wound healing.
Ab Initio Reconstruction of Cell Type-specific Transcriptomes in Mouse Reveals the Conserved Multi-exonic Structure of LincRNAs
Massively parallel cDNA sequencing (RNA-Seq) provides an unbiased way to study a transcriptome, including both coding and noncoding genes. Until now, most RNA-Seq studies have depended crucially on existing annotations and thus focused on expression levels and variation in known transcripts. Here, we present Scripture, a method to reconstruct the transcriptome of a mammalian cell using only RNA-Seq reads and the genome sequence. We applied it to mouse embryonic stem cells, neuronal precursor cells and lung fibroblasts to accurately reconstruct the full-length gene structures for most known expressed genes. We identified substantial variation in protein coding genes, including thousands of novel 5' start sites, 3' ends and internal coding exons. We then determined the gene structures of more than a thousand large intergenic noncoding RNA (lincRNA) and antisense loci. Our results open the way to direct experimental manipulation of thousands of noncoding RNAs and demonstrate the power of ab initio reconstruction to render a comprehensive picture of mammalian transcriptomes.
Metabolic Labeling of RNA Uncovers Principles of RNA Production and Degradation Dynamics in Mammalian Cells
Cellular RNA levels are determined by the interplay of RNA production, processing and degradation. However, because most studies of RNA regulation do not distinguish the separate contributions of these processes, little is known about how they are temporally integrated. Here we combine metabolic labeling of RNA at high temporal resolution with advanced RNA quantification and computational modeling to estimate RNA transcription and degradation rates during the response of mouse dendritic cells to lipopolysaccharide. We find that changes in transcription rates determine the majority of temporal changes in RNA levels, but that changes in degradation rates are important for shaping sharp 'peaked' responses. We used sequencing of the newly transcribed RNA population to estimate temporally constant RNA processing and degradation rates genome wide. Degradation rates vary significantly between genes and contribute to the observed differences in the dynamic response. Certain transcripts, including those encoding cytokines and transcription factors, mature faster. Our study provides a quantitative approach to study the integrative process of RNA regulation.
Full-length Transcriptome Assembly from RNA-Seq Data Without a Reference Genome
Massively parallel sequencing of cDNA has enabled deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here we present the Trinity method for de novo assembly of full-length transcripts and evaluate it on samples from fission yeast, mouse and whitefly, whose reference genome is not yet available. By efficiently constructing and analyzing sets of de Bruijn graphs, Trinity fully reconstructs a large fraction of transcripts, including alternatively spliced isoforms and transcripts from recently duplicated genes. Compared with other de novo transcriptome assemblers, Trinity recovers more full-length transcripts across a broad range of expression levels, with a sensitivity similar to methods that rely on genome alignments. Our approach provides a unified solution for transcriptome reconstruction in any sample, especially in the absence of a reference genome.
