Transcript slides
Probe Selection for Microarrays Considerations and Pitfalls Kay Hofmann MEMOREC Stoffel GmbH Cologne/Germany Probe selection wish list Probe selection strategy should ensure Biologically meaningful results (The truth...) Coverage, Sensitivity (... The whole truth...) Specificity (... And nothing but the truth) Annotation Reproducability Technology Probe immobilization Oligonucleotide coupling Synthesis with linker, covalent coupling to surface Oligonucleotide photolithography ds-cDNA coupling cDNA generated by PCR, nonspecific binding to surface ss-cDNA coupling PCR with one modified primer, covalent coupling, 2nd strand removal Spotting With contact (pin-based systems) Withoug contact (ink jet technology) Technology-specific requirements General Not too short (sensitivity, selectivity) Not too long (viscosity, surface properties) Not too heterogeneous (robustness) Degree of importance depends on method Single strand methods (Oligos, ss-cDNA) Orientation must be known ss-cDNA methods are not perfect ds-cDNA methods don’t care Probe selection approaches Accuracy Throughput Selected Genes Selected Gene Regions ESTs Cluster Representatives Anonymous Non-Selective Approaches Anonmymous (blind) spotting Using clones from a library without prior sequencing Only clones with interesting expression pattern are sequenced Normalization of library highly recommended Typical uses: HT-arrays of ‘exotic’ organisms or tissues Large-scale verification of DD clones EST spotting Using clones from a library after sequencing Little justification since sequence availability allow selection Spotting of cluster representatives Sequence Clustering For human / mouse / rat EST clones: public cluster libraries Unigene (NCBI) THC (TIGR) For custom sequence: clustering tools STACK_PACK (SANBI) JESAM (HGMP) PCP (Paracel, commercial) A benign clustering situation ! In the absence of 5‘-3‘ links Two clusters corresponding to one gene ! Overlap too short Three clusters corresponding to one gene ! ! Chimeric ESTs One cluster corresponding to two genes Chimeric ESTs .. continued Chimeric ESTs are quite common Chimeric ESTs are a major nuisance for array probe selection One of the fusion partners is usually a highly expressed mRNA Double-picking of chimeric ESTs can fool even cautious clustering programs. Unigene contains several chimeric clusters The annotation of chimeric clusters is erratic Chimeric ESTs can be detected by genome comparison There is one particularly bad class of chimeric sequences that will be subject of the exercises. How to select a cluster representative If possible, pick a clone with completely known sequence Avoid problematic regions Alu-repeats, B1, B2 and other SINEs LINEs Endogenous retroviruses Microsatellite repeats Avoid regions with high similarity to non-identical sequences In many clusters, orientation and position relative to ORF are unknown and cannot be selected for. Test selected clone for sequence correctness Test selected clone for chimerism Some commercial providers offer sequence verified UNIGENE cluster representatives Selection of genes If possible, use all of them Biased selection Selection by tissue Selection by topic Selection by visibility Selection by known expression properties Selection from unbiased pre-screen Use sources of expression information EST frequency Published array studies SAGE data Selection of gene regions 3‘ UTR ORF 5‘ UTR Alternative polyadenylation Alternative polyadenylation Constitutive polyA heterogeneity 3’-Fragments: reduced sensitivity no impact on expression ratio Regulated polyA heterogeneity Fragment choice influences expression ratio Multiple fragments necessary Detection of cryptic polyA signals Prediction (AATAAA) Polyadenylated ESTs SAGE tags Alternative splicing Alternative splicing Constitutive splice form heterogeneity Fragment in alternative exon: reduced sensitivity No impact on expression ratio Regulated splice form heterogeneity Fragment choice influences expression ratio Multiple fragments necessary Detection of alternative splicing events Hard/Impossible to predict EST analysis (beware of pre-mRNA) Literature Alternative promoter usage Alternative promotor usage What is the desired readout? If promoter activity matters most: multiple fragments If overall mRNA level matters most: downstream fragment Detection of alternative promoter usage Prediction difficult (possible?) EST analysis Literature UDP-Glucuronosyltransferases UGT1A8 UGT1A7 Selection of gene regions Coding region (ORF) Annotation relatively safe No problems with alternative polyA sites No repetitive elements or other funny sequences danger of close isoforms danger of alternative splicing might be missing in short RT products 3’ untranslated region Annotation less safe danger of alternative polyA sites danger of repetitive elements less likely to cross-hybridize with isoforms little danger of alternative splicing 5’ untranslated region close linkage to promoter frequently not available A checklist Pick a gene Try get a complete cDNA sequence Verify sequence architecture (e.g. cross-species comparison) Mask repetitive elements (and vector!) If possible, discard 3’-UTR beyond first polyA signal Look for alternative splice events Use remaining region of interest for similarity searches Mask regions that could cross-hybridize Use the remaining region for probe amplification or EST selection When working with ESTs, use sequence-verified clones Exercises 1) Assume that you are interested in the p53-homolog p63, also known as Ket (TrEMBL: Q9UE10) What kind of fragment(s) would you use for expression analysis? Why? 2) The cytochrome P450 family is very important for toxicological microarray analysis since most isoforms repond to different toxic compounds. Is it possible to design a cDNA fragment (minimal size 200 bp) that would be able to separate CYP2A6 and CYP2A7? What is the situation with CYP1A1 and CYP1A2? What region should be used? 3) Check whether probes for p53 (Swissprot: P53_HUMAN), p63 and p73 (P73_HUMAN) are available on the Affymetrix human 35K chip or the mouse 12K chip. Check whether there are sequence verified clones available from Research Genetics. 4) Two (hypothetical) papers using different types of microarrays report very different results for the regulation of the thyroid receptor alpha-2 (Swissprot: THA2_HUMAN). Can you think of a possible explanation? What could you do to resolve this issue? Tools for Exercises 1) Literature search with Pubmed: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed 2) Sequence search & retrieval (SwissProt, Entrez) http://www.expasy.ch/sprot/ http://www.ncbi.nlm.nih.gov:80/entrez/query.fcgi?db=Nucleotide 3) BLAST searches at SIB http://www.ch.embnet.org/software/aBLAST.html Use specific subdatabase! Mind the ‘repsim‘ filter 4) Two-way sequence alignment http://www.ch.embnet.org/software/LALIGN_form.html