Small chromosomal regions position themselves autonomously according to their chromatin class

The spatial arrangement of chromatin is linked to the regulation of nuclear processes. One striking aspect of nuclear organization is the spatial segregation of heterochromatic and euchromatic domains. The mechanisms of this chromatin segregation are still poorly understood. In this work, we investigated the link between the primary genomic sequence and chromatin domains. We analyzed the spatial intranuclear arrangement of a human artificial chromosome (HAC) in a xenospecific mouse background in comparison to an orthologous region of native mouse chromosome. The two orthologous regions include segments that can be assigned to three major chromatin classes according to their gene abundance and repeat repertoire: (1) gene-rich and SINE-rich euchromatin; (2) gene-poor and LINE/LTR-rich heterochromatin; and (3) genedepleted and satellite DNA-containing constitutive heterochromatin. We show, using fluorescence in situ hybridization (FISH) and 4C-seq technologies, that chromatin segments ranging from 0.6 to 3 Mb cluster with segments of the same chromatin class. As a consequence, the chromatin segments acquire corresponding positions in the nucleus irrespective of their chromosomal context, thereby strongly suggesting that this is their autonomous property. Interactions with the nuclear lamina, although largely retained in the HAC, reveal less autonomy. Taken together, our results suggest that building of a functional nucleus is largely a self-organizing process based on mutual recognition of chromosome segments belonging to the major chromatin classes

Partitioning DAG Computations: a Cautionary Note

The representation of a parallel computation as a directed acyclic graph can help the programmer to analyse the properties of the computation in order to optimise partitioning and scheduling. We point out that the results obtained from such "optimizations" are only as good as the underlying cost model. 1 Introduction Some parallel computations can be represented as a directed acyclic graph (DAG) in which the nodes represent operations and there is an arc from a node v to a node w if the output from the operation performed at v is needed as one of the inputs to the operation at w. Examples of DAG computation are the fast Fourier transform graph, the binary tree for arithmetic expression evaluation and the diamond for computing the longest common subsequence. Various researchers have used this representation of a computation in order to investigate the input/output complexity of a computation [Kung and Hong 1981], the effects of introducing communications as a resource in the PRAM ..