 CHANGE!! MGL Users Group meetings will now be on the 1 st Monday of each month 3:00-4:00 Room Note the change of time and room

 Notes on ChIP-seq library preparation and initial handling MGL Users Group 1/21/15

Library Preparation  What is the desired resolution of the experiment?  Is it desired to be able to identify a specific recognition motif?  Do we want to resolve binding to bp resolution?  Do we just need general areas?  Target resolution will influence both sample preparation and initial library construction.  It may also influence a decision to do either paired-end or single-end sequencing.  Paired end will result in more reliable mapping, generally, by disambiguation of highly similar sequences with another proximal read.  It can also potentially resolve the ‘ends’ and sizes of protected fragments

HiSeq / SOLiD reads are short  Unless the ChIP targets have a small footprint, even paired end reads may not span a full pulldown target in some cases.  Only ends will be read, with intervening sequence ‘invisible’ to overall read density.  In the case of digested nucleosome fragments, for example, it may be possible to have more than one tandem ligand/target on a single resulting fragment.  Again, if resolution is key, it’s often desirable to ensure efficient cleavage/digestion of DNA prior to pulldown.  Additional steps may be added to size-select for fragments matching most closely in size to the expected single-ligand protected fragment.

Always run an Input control  ChIP-seq identifies regions of enrichment in the IP pool which may be affected by relative abundance of those in the input.  To control for artificial enrichment, the input control serves as a normalization for apparent peaks of enriched signal in the IP.

Additional treatments pre- library construction  Large pulldown fragments were subjected to additional Covaris shearing prior to library construction. Input Immuno-precipitated Mono-nucleosomes ~151 nt Poly-nucleosomes ~1,000-8,000 nt  >1kb necessitate mate-pair library construction otherwise.

Final library sizes were similar  After Covaris shearing, construction of standard fragment libraries proceeded as normal. Input Immuno-precipitated Library ~285 nt Library ~285 nt

The common workflow for ChIPseq following sequencing Bardet, et al. Nature Protocols (2012)

Data Alignment  Alignment strategies may differ, particularly if redundant or highly similar sequences are expected.  Alignment modes:  Unique alignment – Only uniquely best alignments are used  Random assignment – If equal best alignments are found, randomly assign the read to one of them  Multiple assignment – If equal best alignments are found, assign the same read to all of them  Depending on the aligner used, often a random/multi aligned read will be reported as mapping quality of 0.  Visualization tools may mask mapping quality below a certain threshold

Peak identification & Mining Software  Peak calling/comparisons  HOMER, MACS, ODIN, R (DBChIP, others), MAnorm  Peak annotation  HOMER, Bedtools, GREAT, Cistrome, R (ChIPpeakAnno)  Vizualization  IGV, UCSC Genome Browser, NGS-Plot, R (base & other packages)  Motif Identification  Interpro (known), Pfam (known), MEME (discovery/known)  Enrichment Analysis  DAVID, gProfiler, BiNGO, AmiGO, R (GOstats, others)