Molecular (cyto-) genetics Femke de Vries Clinical Laboratory Geneticist
Aim Find genetic variation responsible for a specific disease in a patient
What do I need? • Clear phenotypical description, family history • Blood, saliva, (or tissue of interest), DNA of patient and family • The proper technique to detect the expected variation • Compare your findings with unaffected controls • Choose the proper technique to confirm your initial findings • Determine the effect of the variation on RNA or protein • Link the disturbed protein function or expression to the disease
What do I need? • Clear phenotypical description, family history • Blood, saliva, (or tissue of interest), DNA of patient and family • The proper technique to detect the expected variation • Compare your findings with unaffected controls • Choose the proper technique to confirm your initial findings • Determine the effect of the variation on RNA or protein • Link the disturbed protein function or expression to the disease
phenotypical description, family history Sarah B. Pierce et al. PNAS 2011;108:18313-18317 Kaiser et al. Hum Mol Genet. 2014 Jun 1; 23(11): 2888–2900.
What do I need? • Clear phenotypical description, family history • Blood, saliva, (or tissue of interest), DNA of patient and family • The proper technique to detect the expected variation • Compare your findings with unaffected controls • The proper technique to confirm your initial findings • Determine the effect of the variation on RNA or protein • Link the disturbed protein function or expression to the disease
Targeted vs Genome-wide Genome- Targeted wide screen approach Confirmation Confirmation experiment experiment
Whole genome analysis; resolution! karyotyping WGS 22q11 Arrays Hybridization scanner
Chromosome level: karyotyping
DNA segment level: CNV-profiling
Nucleotide sequence level: WGS
Targeted analysis; previous knowledge Gene panels or WES Fluorescent in situ Sanger sequencing hybridisatie (FISH) Probe 21 22q11 MLPA qPCR or MAQ-assay +2q -15q
A. de Klein NIHES 2013 What do I want to detect? Adapted from Speicher & Carter: The new cytogenetics: blurring the boundaries with molecular biology
Types of genomic variation Structural rearrangements, inversions, duplications and deletions At least 5 Mb in length Segmental duplications & Copy Number Variation 50 bp in length, usually more than 1kb Microsatellite, minisatellite & satellite DNA Tandemly repeated sequences, repetitive DNA 100bp to hundreds of kb Small Insertions and Deletions (InDel) Up to ~50 bp in length Single Nucleotide Variants (SNV) Substitution of single nucleotides
Karyotyping Numerical, translocations, inversions, duplications and deletions (> 5Mb)
Types of genomic variation Structural rearrangements, inversions, duplications and deletions At least 5 Mb in length Segmental duplications & Copy Number Variation 50 bp in length, usually more than 1kb Microsatellite, minisatelite & satelite DNA Tandemly repeated sequences, repetitive DNA 100bp to hundreds of kb Small Insertions and Deletions (InDel) Up to ~50 bp in length Single Nucleotide Variants (SNV) Substitution of single nucleotides
Copy Number Variations Copy Number Loss /homozygous loss Copy Number Gain Garland Science chapter 4: principles of genetic variation . Most CNVs do not have clinical significance ! Santhosh Girirajan et al.; Human Copy Number Variation and Complex Genetic Disease
CGH-array and SNP-array CNV information CNV and allelic information Addapted from: E. Karampetsou et al.; Microarray Technology for the Diagnosis of Fetal Chromosomal Aberrations: Which Platform Should We Use?
Arrays : SNP arrays: B-allele frequency BAF Illumina 610Q array/Genome studio software Log2 ra rat io BBB B 100% B BB BBA BAF AF ~ 50% B AB BAA AAA A 0% B AA
Submicroscopic deletions/duplications David Miller et al. Consensus Statement: Chromosomal Microarray Is a First-Tier Clinical Diagnostic Test for Individuals with Developmental Disabilities or Congenital Anomalies
CNV-profiling Causality • Technical • In unaffected interpretation parents • In-house control • Validate with • In affected cohort second technique individuals • Public databases • Literature True CNV Inheritance
WGS or WES analysis Technical Variants filtered if present more than artefacts X times in in-house cohort Keep variants only if quality parameters are moderate or good QC Filter if present in more than 3%-0.1% Population of chromosomes (public control databases) frequency
Exome-seq analysis Inheritance • Functional consequence of • In-house control • In unaffected variant cohort parents • Relationship with • Public databases • In affected diseasecandidate individuals Unaffected Candidate controls variants
Preliminary analysis: Gene panel
What do I need? • Clear phenotypical description, family history • Blood, saliva, (or tissue of interest), DNA of patient and family • The proper technique to detect the expected variation • Compare your findings with unaffected controls • The proper technique to confirm your initial findings • Determine the effect of the variation on RNA or protein • Link the disturbed protein function or expression to the disease
A. de Klein NIHES 2013 FISH Di-George syndrome Classic cytogenetic techniques Chromosome banding 22 FISH (fluorescent insitu hybridisation) 22 With FISH: - prior knowledge essential - small probes (40-200 kb) Deletion 22q11 FISH to detect known disease related deletions
Confirmation of variation
Copy number gain Patient with intellectual disability and minor congenital anomalies Targeted array parents: no gain “de novo”
Family tree no gain no gain ? ? 3q gain
FISH index
FISH mother Mechanism of inheritance
Mechanism of inheritance meiosis Balanced carrier N dup del bal ins
Family tree balanced normal 3q gain 3q gain insertion 3q 3q gain normal normal
De novo Copy Number Loss
Multiplex Amplicon Quantification 5 amplicons in region of interest, 6 amplicons in other genomic locations Multiplex: separation on amplicon length. CN state based on fluorescent intensity; normalisation on 4 controls
WGS/WES validate variants with Sanger-seq Father Mother Patient de novo C/T
CNV can unmask a gene mutation Homozygous c.854 G>T in SCARF1 Recessive disorder; van den Ende-Gupta syndrome Bedeschi et al.; Unmasking of a Recessive SCARF2 Mutation by a 22q11.12 de novo Deletion in a Patient with Van den Ende-Gupta Syndrome
Take home messages Single basepair changes are not the only genomic variation Our genomes are highly variable; even large deletions or duplications can occur; these can be disease causing or can also be harmless There are many techniques; choose the one best fitting your question Use a genome wide technique to detect unknown variation Use a second –targeted- technique to validate your results
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