Steps to Create FASTQ of CCS Overlapping Control SSR - CCS ROI v4

Virulence and pathogenicity of bacterial pathogens are related to their adaptability to changing environments. Bacterial adaptation includes the ability to rapidly and reversibly reprogram gene expression in response to environmental cues. One process enabling adaptation is based on minor changes in genome sequence, as small as a few base pairs, within segments of genome called simple sequence repeats (SSR) that are made up of multiple copies of a short sequence (from one to several nucleotides), repeated in series. SSR are found in eukaryotes (Toth 2000) as well as prokaryotes (Moxon 2006), and variation in them occurs at frequencies up to a million-fold higher than the average bacterial mutation rate by a process of slip-stranded mispairing (SSM) by DNA polymerase during replication (Moxon 2006). Previous characterizations of SSR in bacteria have suffered from inability to distinguish artifacts generated during sequence processes from true biological signal. Here we report a method for bacterial SSR analysis that solves this problem and indicates that bacteria, rather than changing their genome in response to environment, instead consist of populations that already contain a variety of states and that adaptation results from the outgrowth of these preexisting variants. We demonstrate that a laboratory culture of Histophilus somni, prepared from a single, presumably clonal colony, actually consists of a population of distinct sequence phase and read length variant profiles at individual SSR loci. Thus, specific SSR regions in Histophilus somni are not static structures well-represented by a single consensus sequence, but rather dynamic structures with length variation differences in multiples of complete repeat units (RUs), having characteristic SSM profiles. Our method may be applied to study the potentially species-specific interactions of polymerases and regulatory biomolecules with variations in hypermutable RU sequence, RU sequence phase, RU length, and total SSR length at individual loci. In this protocol we validate the computaitonal approaches presented here by sequenciing chemically synthesized oligos and annealed to a form duplexes. These oligos are slightly shorter version of the AAGC SSR found in CP018802.1.