Many studies have demonstrated that divergence levels generated by different mutation types vary and covary across the human genome. To improve our still-incomplete understanding of the mechanistic basis of this phenomenon, we analyze several mutation types simultaneously, anchoring their variation to specific regions of the genome. Using hidden Markov models on insertion, deletion, nucleotide substitution, and microsatellite divergence estimates inferred from human-orangutan alignments of neutrally evolving genomic sequences, we segment the human genome into regions corresponding to different divergence states-each uniquely characterized by specific combinations of divergence levels. We then parsed the mutagenic contributions of various biochemical processes associating divergence states with a broad range of genomic landscape features. We find that high divergence states inhabit guanine-and cytosine (GC)-rich, highly recombining subtelomeric regions; low divergence states cover inner parts of autosomes; chromosome X forms its own state with lowest divergence; and a state of elevated microsatellite mutability is interspersed across the genome. These general trends are mirrored in human diversity data from the 1000 Genomes Project, and departures from them highlight the evolutionary history of primate chromosomes. We also find that genes and noncoding functional marks [annotations from the Encyclopedia of DNA Elements (ENCODE)] are concentrated in high divergence states. Our results provide a powerful tool for biomedical data analysis: segmentations can be used to screen personal genome variants-including those associated with cancer and other diseases-and to improve computational predictions of noncoding functional elements. W hole-genome sequencing studies have demonstrated that divergence estimates for several mutation types (e.g., nucleotide substitutions, insertions, and deletions) vary substantially across the human genome. This phenomenon has been studied at various genomic scales and evolutionary distances (reviewed in ref. 1), and-whereas initially of interest solely to evolutionary biologists-is now entering the purview of main biomedical research. Specifically, human population (e.g., ref.2) and cancer (3, 4) genome resequencing projects have revealed that incidences of single nucleotide polymorphisms (SNPs), insertions and deletions (indels), and copy number variants (CNVs) vary across the genome. Divergence estimates for different mutation types also covary across the genome (5, 6)-e.g., substitution rates increase in regions with high indel rates (7)-suggesting that regional variation is an important and general characteristic of mutations.Variation in divergence is often linked to genomic landscape features such as base composition, replication timing, and recombination rates (1). For instance, nucleotide substitution rates are elevated in late-replicating regions because of an accumulation of single-stranded DNA susceptible to endogenous damage (8) and are affected by chromatin structure (9) and ...