Functional genomics of cattle through integration of multi-omics data
Ontology highlight
ABSTRACT: The cattle industry is the largest of the agricultural commodities in the United States and generated over $101 billion in farm cash receipts during 2016; 28% of all US farm cash receipts. Although the sequence of the bovine reference genome has been publicly available since 2009, annotation of functional genome elements is largely incomplete, resulting in limitations for exploiting the genome to phenome relationship. This project generate high-quality detailed transcript and miRNA status datasets from a comprehensive set of bovine tissues, developmental stages, and cells through a set of rationally selected assays.
Project description:CASPASE-3 (CASP3) is well known for its proteolytic function that mediates multiple key cell death-initiated processes and other related cellular processes. However, the possibility that CASP3 may also possess important additional non-catalytic functions in mammalian cells has remained largely unexplored. We now report the results of CASP3 knockdown, rescue, proteomic analysis and flow cytometry experiments initially in normal and malignant human mammary cells and later shown to extent to all other human cell types tested. The results reveal a new role of the CASP3 prodomain in regulating the cell cycle progression, survival, proliferation, and protein aggregate accumulation in all cells tested. The generality of these findings suggests that the ancestral pro-survival role of CASP3 in yeast persisted throughout evolution via a conservation of its prodomain, predating its later acquisition of an inherent catalytic property and subsequently preserved cell death control functions.
Project description:In vitro neural stem cell models are widely used to model a wide range of neuropsychiatric conditions. However, how well such models correspond to in vivo brain has not been evaluated in an unbiased, comprehensive manner. We used transcriptomic analyses to compare in vitro systems to developing human fetal brain and observed strong conservation of in vivo gene expression and network architecture in differentiating primary human neural progenitor cells (phNPCs). Conserved modules are enriched in genes associated with ASD, supporting the utility of phNPCs for studying neuropsychiatric disease. We also developed and validated a machine learning approach called CoNTExT that identifies the developmental maturity and regional identity of in vitro models. We observed strong differences between in vitro models, including hiPSC-derived neural progenitors from multiple laboratories. This work provides a framework for evaluating in vitro systems and supports their value in studying the molecular mechanisms of human neurodevelopmental disease. In this GEO submission, we upload data from 5 lines of phNPCs as well as hiPSCs cultured in two different laboratories all at multiple differentiation time points. phNPCs: For each of 5 lines generated from 3 donors (15-16 PCW), two independent differentiation experiments each containing two replicates were performed and harvested at four time points (1, 4, 8, 12 wks PD; ~16 samples per line; 77 total samples). We confirmed RNA integrity by RIN score with the Agilent 2100 Bioanalyzer (mean +/- sd: 9.16 +/- 0.78). iPSC: Two hiPSC datasets were RNA profiled as part of this study. hiPSCs grown in the Kosik lab was derived from two independent, non-isogenic IPS lines: one derived from a patient carrying a mutant Tau variant G55R and one reference control. For each of these lines, two samples were harvested at each of 0, 1, 4, and 8 weeks PD (total n=16 samples). hiPSCs grown in the Gage lab were from six samples derived from 3 control lines at each of two time points (0 and 4 wk PD, total n=12 samples). Samples were randomized to microarray chip by all biological variables of interest (donor, line, passage, replicate number, differentiation week, plate date, and RIN) to control for potential batch effects.
Project description:Epithelial-mesenchymal transition (EMT) involves profound changes in cell morphology, driven by transcriptional and epigenetic reprogramming. However, it emerges that translation and the ribosome composition play also key role in establishing physio-pathological phenotypes. Using genome-wide analyses, we report significant rearrangement of the translational landscape and machinery during EMT. Specifically, a mesenchymal cell line overexpressing the EMT transcription factor ZEB1 shows alterations in translational reprogramming and fidelity. Considering the change in translational activity of ZEB1-overexpressing mesenchymal cells, including in fidelity activity, we sought for changes in ribosome composition. We thus performed a riboproteome approach, i.e., mass spectrometry (MS)-based quantitative proteomic analysis of purified cytoplasmic ribosomes to highlight any change in relative amount of individual ribosomal proteins between wild-type and ZEB1-overexpressing human mammary epithelial cells.
Project description:Androgen-stimulated growth of the molecular apocrine breast cancer is mediated by an androgen receptor (AR)-regulated transcriptional program. Through profiling the genomic licalizations of AR and its co-regulators FOXA1 and TCF7L2 in MDA-MB-453 breast cancer cells, we revealed the molecular details of the AR-centered regulatory network. We further identified that c-MYC is a key downstream target co-regulated by AR, FOXA1 and TCF7L2, and reinforces the transctiopnal activation of androgen-responsive genes in this subtype of breast cancers. MDA-MB-453 breast cancer cells were transfected with control of MYC siRNA for 48 h, followed by treatment with 10nM DHT or vehicle for 6 h. The cells were subjected to mRNA purification and library praparation for RNA-seq on Illumina HiSeq2000 platform.
Project description:"The main goal of the project is to develop a new generation of bioinformatics resources for the integrative analysis of multiple types of omics data. These resources include both novel statistical methodologies as well as user-friendly software implementations. STATegra methods address many aspects of the omics data integration problem such as the design of multiomics experiments, integrative transcriptional and regulatory networks, integrative variable selection, data fusion, integration of public domain data, and integrative pathway analysis. To support method development STATegra uses a model biological system, namely the differentiation process of mouse pre-B-cells. The STATegra consortium generated data focused on a critical step in the differentiation of B lymphocytes, which are key components of the adaptive immune system. Transcription factors of the Ikaros family are central to the normal differentiation of B cell progenitors and their expression increases in response to developmental stage-specific signals to terminate the proliferation of B cell progenitors and to initiate their differentiation. In particular, a novel biological system that models the transition from the pre-BI stage to the pre-BII subsequent stage, where B cell progenitors undergo growth arrest and differentiation, was used. The approach involves a pre-B cell line, B3 , and an inducible version of the Ikaros transcription factor, Ikaros-ERt2. Ikaros factors act to down-regulate genes that drive proliferation and to simultaneously up-regulate the expression of genes that promote the differentiation of B cell progenitors. Hence, in the B3 system, before induction of Ikaros, cells proliferate and their gene expression pattern is similar to proliferating B cell progenitors in vivo. Following Ikaros induction, B3 cells undergo gene expression changes that resemble those that occur in vivo during the transition from cycling to resting pre-B cells, followed by a marked reduction in cellular proliferation and by G1 arrest. On this system the consortium has created a high-quality data collection consisting of a replicated time course using seven different omics platforms: RNA-seq, miRNA-seq, ChIP-seq, DNase-seq, Methyl-seq, proteomics and metabolomics, which is used to assess and to validate STATegra methods."
Project description:High yielding dairy cattle undergo a state of NEB (negative energy balance) during the post-partum period when energy demand for lactation and maintenance exceeds energy intake. During this period in order to counteract NEB the liver under goes extensive metabolic and physiological change resulting in alteration in hepatic genes and miRNAs expression. We used Affymetrix Multispecies miRNA-2_0 Array with miRBase version 15 coverage to assess the liver miRNA expression in SNEB (severe NEB) and MNEB (mild NEB) Holstein Friesian cattle during the post-partum period. A NEB model of Holstein Friesian was established such that 12 post-partum cattle were randomly assigned to MNEB and SNEB groups depending on different feeding and milking regimes
Project description:Intestinal epithelial cells (IECs) were isolated from the colon of Villin-CreERT2, Rnf20-flox and Rnf40-flox mice two weeks upon the Tamoxifen-induced, intestinal knockout of Rnf20 and Rnf40. ChIP-seq for H3K4me3 was performed using snap-frozen IECs.
Project description:Multiple-condition experiment was desinged to be any number of conditions in an experiment without replicate observations for microarray and used to identify genes differentially expressed between different pairs of conditions (treatments).<br> In this study we used breast cancer stable cell lines for overexpressing and silencing annexin A1 (ANXA1), which belongs to a family of -dependent phospholipid binding proteins and are preferentially located on the cytosolic face of the plasma membrane. Cell lines overexpressing ANXA1 (MDA_MB-453/cDNA) were generated by introducing retroviral vectors containing ANXA1 cDNA (pBabe/ANXA1 cDNA) into breast cancer cell line MDA-MB-453 (a low expressor of ANXA1). Breast cancer cell line BT-474, a high expressor of ANXA1, was infected with ANXA1 siRNA-plasmid viruses to knockdown ANAXAI expressor (BT-474/siRNA) where nucleotides corresponding to siRNA were synthesized and ligated into the pLNCX retroviral vector [35,36]. We also used a pLNCX/U6 empty vector to infect BT-474 and obtained an empty vector expressor. Therefore, 5 breast cancer cell lines (MDA_MB-453, MDA_MB-453/cDNA, BT-474, BT-474/siRNA, and BT-474/U6) are attributed to two genotypes: MDA_MB-453 and BT-474. MCE was performed for microarray analysis with these 5 breast cancer cell lines, that is, only one sample was drawn from each breast cancer cell line.