Project description:We performed RNA-Seq experiments on 4 replicate samples from growth condition of hexoploid bread wheat (Chinese Spring) to construct a transcriptional map on meiotic conditions. Library preparation was preformed according to TruSeq RNA Sample Preparation Guide (Illumina, Part # 15008136 REV. A). Reagents were taken from the Illumina TruSeq Sample Prep Kit -Set A (Illumina, CAT # RS-930-2001). Samples were sequenced with 4 samples per lane on 2x100bp.
Project description:CTCF plays an important role in 3D genome organization by adjusting insulation at TAD boundaries, where clustered CBS (CTCF-binding site) elements are often arranged in tandem array with a complex divergent or convergent orientation. Here using cPcdh and HOXD loci as a paradigm, we look into the clustered CTCF TAD boundaries and find that, counterintuitively, outward-oriented CBS elements are crucial for inward enhancer-promoter interactions as well as for gene regulation. Specifically, by combinatorial deletions of a series of putative enhancer elements in vivo or CBS elements in vitro, in conjunction with chromosome conformation capture and RNA-seq analyses, we show that deletions of outward-oriented CBS elements weaken the strength of long-distance intraTAD promoter-enhancer interactions and enhancer activation of target genes. Our data highlight the crucial role of outward-oriented CBS elements within the clustered CTCF TAD boundaries and have interesting implications on the organization principles of clustered CTCF sites within TAD boundaries.
Project description:Data analysis is a critical part of quantitative proteomics studies in interpreting biological questions. Numerous computational tools including protein quantification, imputation, and differential expression (DE) analysis were generated in the past decade. However, searching optimized tools is still an unsolved issue. Moreover, due to the rapid development of RNA-Seq technology, a vast number of DE analysis methods are created. Applying these newly developed RNA-Seq-oriented tools to proteomics data is still a question that needs to be addressed. In order to benchmark these analysis methods, a proteomics dataset constituted the proteins derived from human, yeast, and drosophila with different ratios were generated. Based on this dataset, DE analysis tools (including array-based and RNA-Seq based), imputation algorithms, and protein quantification methods were compared and benchmarked. This study provided useful information on analyzing quantitative proteomics datasets. All the methods used in this study were integrated into Perseus which are available at https://www.maxquant.org/perseus.