Effects of sheared chromatin length on ChIP-seq quality and sensitivity

CLIMB: High-dimensional association detection in large scale genomic data

Joint analyses of genomic datasets obtained in multiple different conditions are essential for understanding the biological mechanism that drives tissue-specificity and cell differentiation, but they still remain computationally challenging. To address this we introduce CLIMB (Composite LIkelihood eMpirical Bayes), a statistical methodology that learns patterns of condition-specificity present in genomic data. CLIMB provides a generic framework facilitating a host of analyses, such as clustering genomic features sharing similar condition-specific patterns and identifying which of these features are involved in cell fate commitment. We apply CLIMB to three sets of hematopoietic data, which examine CTCF ChIP-seq measured in 17 different cell populations, RNA-seq measured across constituent cell populations in three committed lineages, and DNase-seq in 38 cell populations. Our results show that CLIMB improves upon existing alternatives in statistical precision, while capturing interpretable and biologically relevant clusters in the data.

Transcription factor chromatin profiling genome-wide using uliCUT&RUN in single cells and individual blastocysts

Determining chromatin-associated protein localization across the genome has provided insight into the functions of DNA-binding proteins and their connections to disease. However, established protocols requiring large quantities of cell or tissue samples currently limit applications for clinical and biomedical research in this field. Furthermore, most technologies have been optimized to assess abundant histone protein localization, prohibiting the investigation of nonhistone protein localization in low cell numbers. We recently described a protocol to profile chromatin-associated protein localization in as low as one cell: ultra-low-input cleavage under targets and release using nuclease (uliCUT&RUN). Optimized from chromatin immunocleavage and CUT&RUN, uliCUT&RUN is a tethered enzyme-based protocol that utilizes a combination of recombinant protein, antibody recognition and stringent purification to selectively target proteins of interest and isolate the associated DNA. Performed in native conditions, uliCUT&RUN profiles protein localization to chromatin with low input and high precision. Compared with other profiling technologies, uliCUT&RUN can determine nonhistone protein chromatin occupancies in low cell numbers, permitting the investigation into the molecular functions of a range of DNA-binding proteins within rare samples. From sample preparation to sequencing library submission, the uliCUT&RUN protocol takes <2 d to perform, with the accompanying data analysis timeline dependent on experience level.