Despite intense investigation, human replication origins and termini remain elusive. Existing data have shown strong discrepancies. Here we sequenced highly purified Okazaki fragments from two cell types and, for the first time, quantitated replication fork directionality and delineated initiation and termination zones genome-wide. Replication initiates stochastically, primarily within non-transcribed, broad (up to 150 kb) zones that often abut transcribed genes, and terminates dispersively between them. Replication fork progression is significantly co-oriented with the transcription. Initiation and termination zones are frequently contiguous, sometimes separated by regions of unidirectional replication. Initiation zones are enriched in open chromatin and enhancer marks, even when not flanked by genes, and often border ‘topologically associating domains' (TADs). Initiation zones are enriched in origin recognition complex (ORC)-binding sites and better align to origins previously mapped using bubble-trap than λ-exonuclease. This novel panorama of replication reveals how chromatin and transcription modulate the initiation process to create cell-type-specific replication programs.

In the context of the renewed interest of peptides as therapeutics, it is important to have an on-line resource for 3D structure prediction of peptides with well-defined structures in aqueous solution. We present an updated version of PEP-FOLD allowing the treatment of both linear and disulphide bonded cyclic peptides with 9–36 amino acids. The server makes possible to define disulphide bonds and any residue–residue proximity under the guidance of the biologists. Using a benchmark of 34 cyclic peptides with one, two and three disulphide bonds, the best PEP-FOLD models deviate by an average RMS of 2.75 Å from the full NMR structures. Using a benchmark of 37 linear peptides, PEP-FOLD locates lowest-energy conformations deviating by 3 Å RMS from the NMR rigid cores. The evolution of PEP-FOLD comes as a new on-line service to supersede the previous server. The server is available at: http://bioserv.rpbs.univ-paris-diderot.fr/PEP-FOLD.