CREB1 TIP-seq data
Epigenomic profiling provides insights into the regulatory mechanisms that govern gene expression. Techniques such as ChIP-seq have been instrumental in mapping transcription factor binding sites across the genome. Recent advances have led to the development of TIP-seq, a highly sensitive method designed to increase the number of unique reads that can be obtained from single cells. TIP-seq uses a Tn5 transposase to insert T7 promotors at antibody-labelled genomic locations. An RNA polymerase then performs linear amplification at these sites to increase the signal. A chain of bioinformatics tools is required to analyse epigenetic data, and to date, these have not been fully adapted to suit the unique features of TIP-seq data. One such step is peak calling, the process of identifying regions of the genome enriched for sequence reads. Unlike ChIP-seq, the Tn5 enzyme of TIP-seq simultaneously cuts and inserts sequencing adapters near target protein binding sites. By leveraging the directionality of these inserted adapters, we show that the width of called peaks can be greatly reduced, and the peak summits can be more precisely aligned with transcription factor binding sites. This is done by using only the first mate of each read pair and centring the reads on their 5' ends. We have also identified optimal peak calling parameters, which leverage how the Tn5 transposase cuts target sites. We expect this methodological advancement to facilitate future efforts to apply and benchmark TIP-seq.
Epigenomic profiling provides insights into the regulatory mechanisms that govern gene expression. Techniques such as ChIP-seq have been instrumental in mapping transcription factor binding sites across the genome. Recent advances have led to the development of TIP-seq, a highly sensitive method designed to increase the number of unique reads that can be obtained from single cells. TIP-seq uses a Tn5 transposase to insert T7 promotors at antibody-labelled genomic locations. An RNA polymerase then performs linear amplification at these sites to increase the signal. A chain of bioinformatics tools is required to analyse epigenetic data, and to date, these have not been fully adapted to suit the unique features of TIP-seq data. One such step is peak calling, the process of identifying regions of the genome enriched for sequence reads. Unlike ChIP-seq, the Tn5 enzyme of TIP-seq simultaneously cuts and inserts sequencing adapters near target protein binding sites. By leveraging the directionality of these inserted adapters, we show that the width of called peaks can be greatly reduced, and the peak summits can be more precisely aligned with transcription factor binding sites. This is done by using only the first mate of each read pair and centring the reads on their 5' ends. We have also identified optimal peak calling parameters, which leverage how the Tn5 transposase cuts target sites. We expect this methodological advancement to facilitate future efforts to apply and benchmark TIP-seq.