Project description:SILAC based protein correlation profiling using size exclusion of protein complexes derived from seven Mus musculus tissues (Heart, Brain, Liver, Lung, Kidney, Skeletal Muscle, Thymus)
Project description:PURPOSE: To provide a detailed gene expression profile of the normal postnatal mouse cornea. METHODS: Serial analysis of gene expression (SAGE) was performed on postnatal day (PN)9 and adult mouse (6 week) total corneas. The expression of selected genes was analyzed by in situ hybridization. RESULTS: A total of 64,272 PN9 and 62,206 adult tags were sequenced. Mouse corneal transcriptomes are composed of at least 19,544 and 18,509 unique mRNAs, respectively. One third of the unique tags were expressed at both stages, whereas a third was identified exclusively in PN9 or adult corneas. Three hundred thirty-four PN9 and 339 adult tags were enriched more than fivefold over other published nonocular libraries. Abundant transcripts were associated with metabolic functions, redox activities, and barrier integrity. Three members of the Ly-6/uPAR family whose functions are unknown in the cornea constitute more than 1% of the total mRNA. Aquaporin 5, epithelial membrane protein and glutathione-S-transferase (GST) omega-1, and GST alpha-4 mRNAs were preferentially expressed in distinct corneal epithelial layers, providing new markers for stratification. More than 200 tags were differentially expressed, of which 25 mediate transcription. CONCLUSIONS: In addition to providing a detailed profile of expressed genes in the PN9 and mature mouse cornea, the present SAGE data demonstrate dynamic changes in gene expression after eye opening and provide new probes for exploring corneal epithelial cell stratification, development, and function and for exploring the intricate relationship between programmed and environmentally induced gene expression in the cornea. Keywords: other
Project description:To characterize the genetic basis of hybrid male sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL). Many trans eQTL cluster into eleven ‘hotspots,’ seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL - but not cis eQTL - were substantially lower when mapping was restricted to a ‘fertile’ subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. Gene expression was measured in whole testis in males aged 70(±5) days. Samples include 294 WSB/EiJ x PWD/PhJ F2s, 11 PWD/PhJ x WSB/EiJ F2s, 8 WSB/EiJ, 8 PWD/PhJ, 6 PWD/PhJ x WSB/EiJ F1s and 4 WSB/EiJ x PWD/PhJ F1s.
Project description:We collected whole genome testis expression data from hybrid zone mice. We integrated GWAS mapping of testis expression traits and low testis weight to gain insight into the genetic basis of hybrid male sterility. Gene expression was measured in whole testis from males aged 62-86 days. Samples include 190 first generation lab-bred male offspring of wild-caught mice from the Mus musculus musculus - M. m. domesticus hybrid zone.
Project description:Cellular binary fate decisions require the progeny to silence genes associated with the alternative fate. The major subsets of alpha:beta T cells have been extensively studied as a model system for fate decisions. While the transcription factor RUNX3 is required for the initiation of Cd4 silencing in CD8 T cell progenitors, it is not required to maintain the silencing of Cd4 and other helper T lineage genes. The other runt domain containing protein, RUNX1, silences Cd4 in an earlier T cell progenitor, but this silencing is reversed whereas the gene silencing after RUNX3 expression is not reverse. Therefore, we hypothesized that RUNX3 and not RUNX1 recruits other factors that maintains the silencing of helper T lineage genes in CD8 T cells. To this end, we performed a proteomics screen of RUNX1 and RUNX3 to determine candidate silencing factors.
Project description:A transcriptome study in mouse hematopoietic stem cells was performed using a sensitive SAGE method, in an attempt to detect medium and low abundant transcripts expressed in these cells. Among a total of 31,380 unique transcript, 17,326 (55%) known genes were detected, 14,054 (45%) low-copy transcripts that have no matches to currently known genes. 3,899 (23%) were alternatively spliced transcripts of the known genes and 3,754 (22%) represent anti-sense transcripts from known genes. Overall design: Mouse hematopoietic stem cells were purified from bone marrow cells using negative and positive selection with a Magnetic-Activated Cell Sorter (MACS). total RNA and mRNA were purified from the purified cells using Trizol reagent and magnetic oligo dT beads. Double strand cDNAs were synthesized using a cDNA synthesis kit and anchored oligo dT primers. After NlaIII digestion, 3’ cDNAs were isolated and amplified through 16-cycle PCR. SAGE tags were released from the 3’ cDNA after linker ligation. Ditags were formed, concatemerized and cloned into a pZERO vector. Sequencing reactions were performed with the ET sequencing terminator kit. Sequences were collected using a Megabase 1000 sequencer. SAGE tag sequences were extracted using SAGE 2000 software.
Project description:Genome wide expression profiling to determine the overlap of Affymetrix-signals with SOLID sequencing RNA was extracted using the Qiagen RNeasy kit following the manufacturers guidelines, arrays were prepared and hybridized following the Affymetrix protocol. Overall design: Mus musculus samples from small intestine and colon, to be compared to transcript data aquired with other techniques
Project description:It is known that ubiquitination is important for T cell receptor (TCR) signaling during T cell activation but the breadth of ubiquitination events triggered during TCR signaling is not completely understood. This dataset utilizes di-glycine remnant profiling combined with mass spectrometry to identify a global landscape of ubiquitination events downstream of the TCR and to quantify changes ubiquitin abundance in response to TCR stimulation. Additionally, whole cell proteomics data were generated to measure protein abundances during TCR stimulation. Mouse primary T cells were isolated, proliferated and either remained resting or stimulated with CD3/CD28 to activate downstream signaling through the TCR and co-stimulatory pathways. Di-glycine remnant profiling and whole cell proteomics was performed on rested cells and cells that had undergone CD3/CD28 TCR stimulation for 4 hours. These data were analyzed to identify the ubiquitination events during TCR activation and to quantify the change in peptide-based ubiquitin abundance and total protein abundance over the course of the 4 hour TCR stimulation. Integration of di-glycine and whole cell proteomics was used to generate protein-specific predictions of whether ubiquitination events downstream of TCR signaling lead to a decrease in associated protein abundance. The analysis of these data suggests that T cell activation leads to an increase in ubiquitination that is not associated with proteasomal or lysosomal degradation.
Project description:Comparision of Mus musculus Control and Treated samples. Overall design: Low RNA Input Fluorescent Linear Amplification Kit (Agilent, Santa Clara, CA) was used for labeling. Briefly, both first and second strand cDNA were synthesized by incubating 500ng of total RNA with 1.2ul of oligo dT-T7 Promoter Primer in nuclease-free water at 65 ◦C for 10 min followed by incubation with 4.0ul of 5× First strand buffer, 2ul of 0.1M DTT, 1 ul of 10mM dNTP mix, 1ul of 200 U/ul MMLV-RT, and 0.5ul of 40U/ul RNaseOUT, at 40 ◦C for 2 hour. Immediately following cDNA synthesis, the reaction mixture was incubated with 2.4 ul of 10 mM Cyanine-3-CTP or 2.4 ul of 10 mM Cyanine-5-CTP (Perkin-Elmer, Boston, MA), 20ul of 4X Transcription buffer, 8 ul of NTP mixture, 6 ul of 0.1M DTT, 0.5 ul of RNaseOUT, 0.6ul of Inorganic pyrophosphatase, 0.8 ul of T7 RNA polymerase, and 15.3ul of nuclease-free water at 40 ◦C for 2 hour. Qiagen’s RNeasy mini spin columns were used for purifying amplified aRNA samples. The quantity and specific activity of cRNA was determined by using NanoDrop ND-1000 UV-VIS Spectrophotometer version3.2.1. Samples with specific activity >8 were used for hybridization. 825ng of each Cyanine 3 or Cyanine 5 labeled cRNA in a volume of 41.8ul were combined with 11ul of 10x Blocking agent and 2.2ul of 25x Fragmentation buffer (Agilent), and incubated at 60deg C for 30 minutes in dark. The fragmented cRNA were mixed with 55ul of 2x Hybridization Buffer (Agilent). About 110ul of the resulting mixture was applied to the Microarray and hybridized at 65degC for 17 hours in an Agilent Microarray Hybridization Chamber (SureHyb: G2534A) with Hybridization Oven. After hybridization, slides were washed with Agilent Gene expression Wash Buffer I for 1 minute at room temperature followed by a 1 min wash with Agilent Gene expression Wash Buffer II for 37C. Slides were finally rinsed with Acetonitrile for cleaning up and drying. Microarrays were scanned on an Agilent scanner (G2565AA) at 100% laser power, 30% PMT.Data extraction was carried out with Agilent Feature Extraction software (version 9.1), and normalization was done using linear per array algorithm according to the manufacturer’s protocol. The data was analysed by GeneSpring GX . The differential expression was considered if the Log 2 mean of at least -1 for the down regulated genes and +1 for the upregulated genes. We considered only the genes that were reproducible from all replicates.