eCLIP Library Prep Kit

Most biological samples are amenable to eCLIP (cell lines, tissues and model organisms), with optimization required depending on endogenous RNase levels and other biological properties. Please contact us if you have a particular sample type of interest.

Antibody to immunoprecipitate the RNA binding protein of interest

Each eCLIP experiment uses an antibody to immunoprecipitate the RNA binding protein of interest from a biological sample.

Pre-validated antibodies are available for 150 RNA binding proteins

-Alternatively, we recommend antibody validation be performed prior to eCLIP using the eCLIP immunoprecipitation validation kit or anti-tag antibodies

UV Cross-linking

Biosamples should be UV cross-linked according to protocols available for:

– Suspension Cells

– Adherent Cells

– Tissues

Contact us for UV crosslinking protocols for Model Organisms

The quantity of starting material required for an eCLIP experiment depends significantly on the abundance of the protein you are studying. We would recommend however, starting with 200ug of RNA that has been quantified using our “RNA Fragmentation” guide at the protocol

We have in-house pre-validated antibodies for FLAG, V5, HA and MYC.

We recommend running at least duplicates for publication purposes, however triplicates always produce more reliable data.

Eclipse Bio’s kit is based on the single-end eCLIP variant described in:
Van Nostrand EL, Nguyen TB, et al. Robust, Cost-Effective Profiling of RNA Binding Protein Targets with Single-end Enhanced Crosslinking and Immunoprecipitation (seCLIP). Methods Mol Biol. 2017;1648:177-200. PMID: 28766298.

Libraries generated using the eCLIP-seq method are typically sequenced using standard SE50 or SE75 conditions on the Illumina HiSeq, NovaSeq, or NextSeq platforms. eCLIP-seq libraries are compatible with paired-end sequencing if desired by the user, however due to the small size of typical eCLIP RNA fragments (~200bp), most fragments are fully sequenced in standard single-end formats.

Eclipse Bio’s target is 25 million reads per eCLIP-seq dataset.
How deeply to sequence an eCLIP-seq dataset is a challenging balance between cost and sufficient read depth to detect true binding events. In an effort to experimentally address this question, an analysis of eCLIP-seq datasets for 150 RNA binding proteins suggested that for 90% of datasets, saturation of peak information occurred at or below 8.5 million reads (See Supplementary Fig. 11 of Van Nostrand EL, et al. A Large-Scale Binding and Functional Map of Human RNA Binding Proteins. Nature (Accepted, in press) However, we have found that targeting 25 million reads provides better coverage for abundant, broadly binding RNA binding proteins (such as HNRNPs) while still allowing pooling of ~14 eCLIP libraries per standard Illumina HiSeq 4000 lane.

We recommend using NEBNext HT (cat # E7600S) index primers for larger projects. Use 5ul of both the forward and reverse primer (10uM each) then scale the total master mix volume up to 50ul (5ul Forward primer, 5ul Reverse primer, 15ul cDNA and 25ul Primer Mix).

RNA adapter: 5Phos/rArGrArUrCrGrGrArArGrArGrCrArCrArCrGrUrCrUrG/3SpC3/

ssDNA adapter: 5Phos/NNNNNNNNNNAGATCGGAAGAGCGTCGTGT/3SpC3/

Index primer sequences: Illumina dual index primers (provided)
505: AGGCGAAG
506: TAATCTTA
507: CAGGACGT
508: GTACTGAC
705: TTCTGAAT
706: ACGAATTC
707: AGCTTCAG
708: GCGCATTA

The Data Analysis includes:

• Fastq files of raw sequencing reads
• Adapter trimmed fastq files of reads with UMI and adapter sequences removed
• Bam files containing PCR-deduplicated read alignments to the genome
• Bigwig files which can be uploaded to a genome browser to view read density of sample
• Bed file of input-normalized peaks containing the location of each peak in the genome, along with the log2 fold change vs. input and p-value
• Bed file of PureCLIP crosslink sites
• HTML reports with figures related to PureCLIP crosslink sites

The Data Analysis includes:

• Fastq files of raw sequencing reads
• Adapter trimmed fastq files of reads with UMI and adapter sequences removed
• Bam files containing PCR-deduplicated read alignments to the genome
• Bigwig files which can be uploaded to a genome browser to view read density of sample
• Bed file of input-normalized peaks containing the location of each peak in the genome, along with the log2 fold change vs. input and p-value
• HTML reports with figures related to significantly enriched peaks

Sample HTML Data Analysis Report

Standard analysis of eCLIP requires read adapter trimming, mapping to the appropriate genome, peak identification, and comparison against a paired input, knockout, or other suitable control sample (Figure 9). An example eCLIP analysis pipeline has been described by the ENCODE consortium here.

If you want to analyze your own data visit the Yeo lab pipeline on Github: github.com/YeoLab/eclip