Additional file 6: Table S4. of High-density P300 enhancers control cell state transitions

Cell-specific SE-associated lncRNAs in T helper cells.(XLSX 58 kb

Additional file 5: Table S3. of High-density P300 enhancers control cell state transitions

Cell-specific SE-associated genes in T helper cells.(XLSX 74 kb

Additional file 7: Table S5. of High-density P300 enhancers control cell state transitions

Table S5: Cell-specific SE-associated miRNAs in T helper cells.(XLSX 35 kb

Additional file 8: Figure S3. of High-density P300 enhancers control cell state transitions

A. A genome browser screenshot depicts a mouse SE which overlaps the Ccr7 gene and lncRNAs (or eRNAs) that are enriched in Th17 cells. Expression of these lncRNAs in Th17 cells depend on Stat3 or Batf, and these two transcription factors bind extensively throughout this locus and co-localize with P300. This locus also contains sequence homology to two human Th17 cell-specific SEs [4], mapped by synteny. Data are from [25]. (DOC 100 kb

Additional file 3: Table S2. of High-density P300 enhancers control cell state transitions

A summary of datasets used in this study.(XLSX 14 kb

Additional file 2: Table S1. of High-density P300 enhancers control cell state transitions

Publicly available datasets used to curate SE catalogs.(XLSX 51 kb

Nanostring expression assay for positionally conserved lncRNAs

This dataset contains expression data for positionally conserved lncRNAs measure using the Nanostring assay. Sheet A: Annotation of probes used in the assay. B: List of samples tested in the assay. C: Normalised expression of tested human and mouse pcRNAs and associated coding genes.<div><br></div><div><b>Methods</b></div><div>We designed probes to detect 50 pairs of pcRNAs and corresponding coding genes in human and mouse. The probes were designed according to the Nanostring guidelines and to maximize their specificity and included 9 house-keeping genes for normalization (ALAS1, B2M, CLTC, GAPDH, GUSB, HPRT, PGK1, TDB, TUBB). The raw count data were first normalized by Nanostring Technologies with the nSolver software using a two-step protocol. First, data were normalized to internal positive controls, then to the geometric mean of house-keeping genes. The normalised data was then imported into R for further analysis.<b><br></b></div

Where's Wally? Finding RNA modifications with ONT direct-RNA Sequencing

RNA molecules undergo a vast array of post-transcriptional modifications (PTMs). Transcriptome-wide PTM mapping methods such as RNA-immunoprecipitation and chemoselective alteration have revolutionised the field, however they are laborious and there are concerns about their lack of reproducibility. To evaluate the ability of ONT direct RNA sequencing to detect PTMs, we developed a protocol to concatenate <em>in vitro</em> synthesised RNA blocks containing a single modified nucleotide (m⁶A or m⁶2A) surrounded by all possible sequence contexts. We analysed our direct RNA-Seq data by integrating signal intensity, dwell time and local sequence context. Our descriptive statistical analysis revealed that the presence of m⁶A and m⁶2A induces a distinctive change in the signal for the majority of the k-mers. We are now working on extending our PTM catalogue and are actively developing a deep learning based PTM detection package

Additional file 2: of Genomic positional conservation identifies topological anchor point RNAs linked to developmental loci

Supplementary information. (PDF 324 kb

Additional file 6: of Genomic positional conservation identifies topological anchor point RNAs linked to developmental loci

Table S4. GO enrichment protein coding genes associated with pcRNAs in each possible orientation. (XLSX 54 kb