Nucleosomes, linker DNA, and linker histone form a unique structural motif that directs the higher-order folding and compaction of chromatin

The compaction level of arrays of nucleosomes may be understood in terms of the balance between the self-repulsion of DNA (principally linker DNA) and countering factors including the ionic strength and composition of the medium, the highly basic N termini of the core histones, and linker histones. However, the structural principles that come into play during the transition from a loose chain of nucleosomes to a compact 30-nm chromatin fiber have been difficult to establish, and the arrangement of nucleosomes and linker DNA in condensed chromatin fibers has never been fully resolved. Based on images of the solution conformation of native chromatin and fully defined chromatin arrays obtained by electron cryomicroscopy, we report a linker histone-dependent architectural motif beyond the level of the nucleosome core particle that takes the form of a stem-like organization of the entering and exiting linker DNA segments. DNA completes ≈1.7 turns on the histone octamer in the presence and absence of linker histone. When linker histone is present, the two linker DNA segments become juxtaposed ≈8 nm from the nucleosome center and remain apposed for 3–5 nm before diverging. We propose that this stem motif directs the arrangement of nucleosomes and linker DNA within the chromatin fiber, establishing a unique three-dimensional zigzag folding pattern that is conserved during compaction. Such an arrangement with peripherally arranged nucleosomes and internal linker DNA segments is fully consistent with observations in intact nuclei and also allows dramatic changes in compaction level to occur without a concomitant change in topology.

The asymptotic distribution of canonical correlations and vectors in higher-order cointegrated models

The study of the large-sample distribution of the canonical correlations and variates in cointegrated models is extended from the first-order autoregression model to autoregression of any (finite) order. The cointegrated process considered here is nonstationary in some dimensions and stationary in some other directions, but the first difference (the “error-correction form”) is stationary. The asymptotic distribution of the canonical correlations between the first differences and the predictor variables as well as the corresponding canonical variables is obtained under the assumption that the process is Gaussian. The method of analysis is similar to that used for the first-order process.