Project description:Long non-coding RNAs (lncRNAs) play key roles in cell processes and are good candidates for cancer risk prediction. Few studies have investigated the association between individual genotypes and lncRNA expression. Here we integrate three separate datasets with information on lncRNA expression only, both lncRNA expression and genotype, and genotype information only, to identify circulating lncRNAs associated with the risk of gallbladder cancer (GBC), using robust linear and logistic regression techniques. In the first dataset, we preselect lncRNAs based on expression changes along the sequence “gallstones → dysplasia → GBC”. In the second dataset, we validate associations between genetic variants and serum expression levels of the preselected lncRNAs (cis-lncRNA-eQTLs) and build lncRNA-expression prediction models. In the third dataset, we predict serum lncRNA expression based on individual genotypes, and assess the association between genotype-based expression and GBC risk. AC084082.3 and LINC00662 showed increasing expression levels (p value = 0.009), while C22orf34 expression decreased in the sequence from gallstones to GBC (p value = 0.04). We identified and validated two cis-LINC00662-eQTLs (r2= 0.26) and three cis-C22orf34-eQTLs (r2 = 0.24). Only LINC00662 showed a genotyped-based serum expression associated with GBC risk (OR=1.25 per log2 expression unit, 95%CI 1.04-1.52, p value = 0.02).
Project description:In this study, we make used of mRNA-seq and its ability to reliably quantify isoforms, integrating this data with ribosome profiling and LC-MS/MS, to assign ribosome footprints and peptides at the isoform level. We leverage the principle that most cell types, and even tissues, predominantly express a single principal isoform to set isoform-level mRNA-seq quantifications as priors to guide and improve allocation of footprints or peptides to isoforms. Through tightly integrated mRNAseq, ribosome footprinting and/or LC-MS/MS proteomics we demonstrate that a principal isoform can be identified in over 80% of gene products in homogenous HEK293 cell culture and over 70% of proteins detected in complex human brain tissue. Defining isoforms in experiments with matched RNA-seq and translatomic/proteomic data increases the functional relevance of such datasets and will further broaden our understanding of multi-level control of gene expression. In this PRIDE submission you will find the raw files for the HEK293 cell proteomics. Files for the human brain proteomics can be found at PXD005445. We have also uploaded a zip file that contains the input files for our HEK293 cell analysis, and the isoform level output files – there is a separate folder within the zip files for these. The data used to create the manuscript figures is in the Rdata file. Code for assigning peptides and footprints to isoforms can be found on Github here: https://github.com/rkitchen/EMpire
Project description:We have got a yellow shell variety of Pinctada fucata martensii after years of artificial breeding. To identify differentially expressed genes between yellow shell and normal black shell pearl oysters, we performed label-free proteomic analyses by LC-MS using mantle edge tissues.
Project description:To establish the role of Slug in CRC, we created a genetic CRC model for Slug expression. As parental cells, we selected HT-29 cells that display a pronounced epithelial phe-notype. HT-29 cells were transfected with Slug, and two stable Slug-expressing clones. (Slug1, Slug2) were isolated. As transfection control, we used HT-29 cells transfected with empty vector (control). To characterize the influence of Slug on gene ex-pression, transcriptome analysis was performed for the four HT-29 cell lines as well as for the corresponding tumor xenografts. Global expression profiling showed that Slug-overexpressing cells and tumors were clustered together while the parental and control cells and tumors formed a separate cluster. Next, a two-step analysis was carried out. First, a subtractive analysis was carried out comparing the gene profiles of Slug-expressing cells and tumors with the corresponding parental/control samples. Genes were considered to be significantly upregulated by Slug if the fold change (FC) was greater than +2 and downregulated if the fold change was less than −2 with p-values (false dis-covery rates) less than 0.01
Project description:We characterized the epigenetic landscape of human colorectal cancer (CRC). To this extent, we performed gene expression profiling using high throughput sequencing (RNA-seq) and genome wide binding/occupancy profiling (ChIP-seq) for histone modifications correlated to transcriptional activity, enhancers, elongation and repression (H3K4me3, H3K4me1, H3K27Ac, H3K36me3, H3K27me3) in patient-derived organoids (PDOs), and in normal and tumoral primary colon tissues. We also generated ChIP-seq data for transcription factors YAP/TAZ in human CRC PDOs.
Project description:We characterized the epigenetic landscape of human colorectal cancer (CRC). To this extent, we performed gene expression profiling using high throughput sequencing (RNA-seq) and genome wide binding/occupancy profiling (ChIP-seq) for histone modifications correlated to transcriptional activity, enhancers, elongation and repression (H3K4me3, H3K4me1, H3K27Ac, H3K36me3, H3K27me3) in patient-derived organoids (PDOs), and in normal and tumoral primary colon tissues. We also generated ChIP-seq data for transcription factors YAP/TAZ in human CRC PDOs.
Project description:Olfactory ensheathing cells are one of the few central nervous system regenerative cells discovered so far. It is characterized by its lifelong nerve regeneration function, and it can also release a variety of neurotrophic factors and neural adhesion molecules. It is considered to be the glial cell with the strongest myelination ability. Olfactory ensheathing cells and Schwann cells have phenotypes in common, they can promote axon regeneration(R. Doucette, 1995). Olfactory ensheathing cells have the characteristics of Schwann cells and astrocytes, but the overall performance tends to be the former, which has two unique characteristics. First, it exists not only in the peripheral nerves (Schwann cells), but also in the central nervous system (astroglia); second, the olfactory mucosa has the ability to regenerate life-long, including human olfactory ensheathing cells(J. C. Bartolomei and C. A. Greer, 2000). Regeneration is a process in which olfactory ensheathing cells participate in efficient regulation, although the specific mechanism is not yet clear. Olfactory ensheathing cells are different from astrocytes and Schwann cells, but at the same time have the characteristics of these two cells(S. C. Barnett, 2004), like Schwann cells help axon growth, but more than Schwann cells It can make axons grow long distances, that is, it has stronger migration(A. Ramon-Cueto et al., 1998); there are also astrocytes that have a nutritional effect on the survival of neurons and the growth of axons, but olfactory ensheathing cells can also wrap neurons forms myelin sheath to support the growth of nerve processes(R. Devon and R. Doucette, 1992; J. Gu et al., 2019). There are two characteristics that make olfactory ensheathing cells the best choice for the treatment of neurological diseases(S. C. Chiu et al., 2009; J. Kim et al., 2018; M. Abdel-Rahman et al., 2018). Olfactory ensheathing cells are gradually used to treat spinal cord injuries and have shown amazing effects(J. C. Bartolomei and C. A. Greer, 2000; K. J. Liu et al., 2010; R. Yao et al., 2018). Olfactory ensheathing cells that have been used in research are usually derived from the olfactory bulb(E. H. Franssen et al., 2007), but it is easier to obtain olfactory ensheathing cells from the olfactory mucosa in clinical practice(M. Ryszard et al., 2006), so the difference between the olfactory ensheathing cells from the olfactory bulb and the olfactory mucosa There are more and more studies(B. M. U. et al., 2007), and previous studies have shown that they not only have many similar functions, but also have many differences(M. W. Richter et al., 2005; L. Wang et al., 2014; K. E. Smith et al., 2020). Because olfactory ensheathing cells derived from the olfactory bulb are not easy to obtain, olfactory ensheathing cells derived from the olfactory mucosa have become the focus of attention. Although we know that olfactory ensheathing cells from two sources have nerve repair functions, it is not clear why the two different sources of olfactory ensheathing cells have different therapeutic effects. Nicolas G. once studied that the genetic difference between the two cells and found that there are many genes related to wound repair and nerve regeneration(G. Nicolas et al., 2010). We have reason to guess that olfactory ensheathing cells from these two sources will also have a large difference in protein level. Our research group wants to use the current mature transcriptome and proteomic sequencing technologies to explore the difference between olfactory ensheathing cells from the olfactory bulb and olfactory mucosa, and explain why the two sources of olfactory ensheathing cells shows different therapeutic effects, hope to provide a new theoretical basis for future clinical treatment.
Project description:In this study we have deleted four metabolic genes (HIS3, LEU2, URA3 and MET15) in their sixteen possible combinations. These strains are following: knockout of HIS3, LEU2, URA3, MET15; knockout of HIS3, LEU2, MET15; knockout of HIS3, URA3, MET15; knockout of LEU2, URA3, MET15; knockout of HIS3, LEU2, URA3; knockout of HIS3, MET15; knockout of LEU2, MET15; knockout of URA3, MET15; knockout of HIS3, LEU2; knockout of HIS3, URA3; knockout of LEU2, URA3; knockout of MET15, knockout of HIS3; knockout of LEU2; knockout of URA3 and prototrophic strain. We grew the 16 strains in synthetic complete media (SC), and sampled for transcriptomincs in triplicates at mid-exponential phase (OD value of 0.8).
Project description:We report flg22 regulate the accumulation of AGO1-bound small RNA in arabidopsis. We find that a number of miRNAs are up- or down-regulated by flg22, a well-studied PAMP. Examination of AGO1-bound small RNAs with or without flg22 treatment.
Project description:Colon cancer patient-derived xenograft (PDX) models were processed to single cells and sorted by FACS (BD FACS Aria II) for ALDH activity (Aldefluor assay) and DAPI. ALDH Negative and ALDH Positive cells from each PDX model were collected and lysed in RLT buffer and processed for RNA using the RNeasy Mini Plus RNA extraction kit (Qiagen). Samples were processed using Illumina’s TrueSeq RNA protocol and sequenced on an Illumina HiSeq 2500 machine as 2x125nt paired-end reads. Reads were mapped to the human reference genome (assembly hg19) using the STAR aligner (version 2.4.2a). Total read counts per gene were computed using the program “featureCounts” (version 1.4.6-p2) in the “subread” package, with the gene annotation taken from Gencode (version 19).