RESULTS: We show that loss of Hmgn1 or Hmgn2 in pluripotent embryonal carcinoma cells leads to increased levels of spontaneous neuronal differentiation. This is accompanied by the loss of pluripotency markers Nanog and Ssea1, and increased expression of the pro-neural transcription factors Neurog1 and Ascl1. Neural stem cells derived from these Hmgn-knockout lines also show increased spontaneous neuronal differentiation and Neurog1 expression. The loss of HMGN2 leads to a global reduction in H3K9 acetylation, and disrupts the profile of H3K4me3, H3K9ac, H3K27ac and H3K122ac at the Nanog and Oct4 loci. At endodermal/mesodermal genes, Hmgn2-knockout cells show a switch from a bivalent to a repressive chromatin configuration. However, at neuronal lineage genes whose expression is increased, no epigenetic changes are observed and their bivalent states are retained following the loss of HMGN2.
CONCLUSIONS: We conclude that HMGN1 and HMGN2 maintain the identity of pluripotent embryonal carcinoma cells by optimising the pluripotency transcription factor network and protecting the cells from precocious differentiation. Our evidence suggests that HMGN2 regulates active and bivalent genes by promoting an epigenetic landscape of active histone modifications at promoters and enhancers.
RESULTS: We propose a succinct representation of the distance matrices which tremendously reduces the space requirement. We give a complete solution, called SuperRec, for the inference of chromosomal structures from Hi-C data, through iterative solving the large-scale weighted multidimensional scaling problem.
CONCLUSIONS: SuperRec runs faster than earlier systems without compromising on result accuracy. The SuperRec package can be obtained from http://www.cs.cityu.edu.hk/~shuaicli/SuperRec .