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Enhancers activate transcription in a distance-, orientation-, and position-independent manner, which makes them difficult to be identified. Self-transcribing active regulatory region sequencing (STARR-seq) measures the enhancer activity of millions of DNA fragments in parallel. Here we used STARR-seq to generate a quantitative global map of rice enhancers. Most enhancers were mapped within genes, especially at the 5' untranslated regions (5'UTR) and in coding sequences. Enhancers were also frequently mapped proximal to silent and lowly-expressed genes in transposable element (TE)-rich regions. Analysis of the epigenetic features of enhancers at their endogenous loci revealed that most enhancers do not co-localize with DNase I hypersensitive sites (DHSs) and lack the enhancer mark of histone modification H3K4me1. Clustering analysis of enhancers according to their epigenetic marks revealed that about 40% of identified enhancers carried one or more epigenetic marks. Repressive H3K27me3 was frequently enriched with positive marks, H3K4me3 and/or H3K27ac, which together label enhancers. Intergenic enhancers were also predicted based on the location of DHS regions relative to genes, which overlap poorly with STARR-seq enhancers. In summary, we quantitatively identified enhancers by functional analysis in the genome of rice, an important model plant. This work provides a valuable resource for further mechanistic studies in different biological contexts.
Pubmed ID: 31201999
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Original SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.
View all literature mentionsA powerful toolset for genome arithmetic allowing one to address common genomics tasks such as finding feature overlaps and computing coverage. Bedtools allows one to intersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g., intersect two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line.
View all literature mentionsA web-based tool and database for the gene ontology analysis. Its focus is on agricultural species and is user-friendly. The agriGO is designed to provide deep support to agricultural community in the realm of ontology analysis. Compared to other available GO analysis tools, unique advantages and features of agriGO are: # The agriGO especially focuses on agricultural species. It supports 45 species and 292 datatypes currently. And agriGO is designed as an user-friendly web server. # New tools including PAGE (Parametric Analysis of Gene set Enrichment), BLAST4ID (Transfer IDs by BLAST) and SEACOMPARE (Cross comparison of SEA) were developed. The arrival of these tools provides users with possibilities for data mining and systematic result exploration and will allow better data analysis and interpretation. # The exploratory capability and result visualization are enhanced. Results are provided in different formats: HTML tables, tabulated text files, hierarchical tree graphs, and flash bar graphs. # In agriGO, PAGE and SEACOMPARE can be used to carry out cross-comparisons of results derived from different data sets, which is very important when studying multiple groups of experiments, such as in time-course research. Platform: Online tool
View all literature mentionsPython based tools to process, visualize and analyse high-throughput sequencing data, such as ChIP-seq, RNA-seq or MNase-seq. Implemented within Galaxy framework. Used to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches.
View all literature mentionsSoftware R package for comprehensive visualization of genomic signal associations. Visualizes enrichment of genomic signals on specific target regions. Used to visualize e.g. how histone marks are enriched to specific sites.
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