Chromatin conformation analysis of primary patient tissue using a low input Hi-C method

• Published in: Nature communications Vol. 9; no. 1; pp. 4938 - 13
• Main Authors: Díaz, Noelia, Kruse, Kai, Erdmann, Tabea, Staiger, Annette M., Ott, German, Lenz, Georg, Vaquerizas, Juan M.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 29.11.2018; Nature Publishing Group; Nature Portfolio
• Subjects: 14/32; 38/23; 45/100; 45/23; 631/1647/2210/2211; 631/1647/514/2254; 631/337/100/101; 64/60; 692/4028/67/69; B-cell lymphoma; Bcl-6 protein; Chromatin; Conformation; Disease control; Gene expression; Gene mapping; Genomes; Heavy chains; Humanities and Social Sciences; Immunoglobulins; Lymphocytes B; Lymphoma; Methods; multidisciplinary; Pathogenesis; Principal components analysis; Reproducibility; Science; Science (multidisciplinary); Stem cells; Translocation
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-018-06961-0

Chromatin conformation constitutes a fundamental level of eukaryotic genome regulation. However, our ability to examine its biological function and role in disease is limited by the large amounts of starting material required to perform current experimental approaches. Here, we present Low-C, a Hi-C method for low amounts of input material. By systematically comparing Hi-C libraries made with decreasing amounts of starting material we show that Low-C is highly reproducible and robust to experimental noise. To demonstrate the suitability of Low-C to analyse rare cell populations, we produce Low-C maps from primary B-cells of a diffuse large B-cell lymphoma patient. We detect a common reciprocal translocation t(3;14)(q27;q32) affecting the BCL6 and IGH loci and abundant local structural variation between the patient and healthy B-cells. The ability to study chromatin conformation in primary tissue will be fundamental to fully understand the molecular pathogenesis of diseases and to eventually guide personalised therapeutic strategies. Chromatin conformation studies are limited by the large amounts of starting material required to perform current protocols. Here the authors present Low-C, a Hi-C method for low amounts of input material and produce Low-C maps from primary B-cells of a diffuse large B-cell lymphoma patient, demonstrating the suitability of Low-C to analyse rare cell populations.