SNP COURSE Nov. 14, 2018 MONOGENETIC DISEASES AND APPLICATIONS OF NEXT GENERATION SEQUENCING IN HUMAN GENETICS ANNEMIEKE VERKERK j.verkerk@erasmusmc.nl http://www.nature.com/scitable/topicpage/calculation-of-complex-disease-risk-756
1985 OMIM 1966-1998 ONLINE MENDELIAN INHERITANCE IN MAN = database of human disorders, phenotype descriptions gene descriptions Around 6600 monogenetic DISEASES 6297 - phenotype descriptions, molecular basis known 3990 – genes with phenotype-causing mutation 1596 - phenotype descriptions, molecular basis unknown http://omim.org Update from November 2018
OMIM data 6000 7 years: 2270 start of exome seq 5000 4000 first working draft of human genome 10 years: 1800 3000 2000 12 years: 1000 1000 0 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 phenotype with known gene function phenotype without known gene function
TYPES OF DISEASES II “Simple” diseases “Complex” diseases monogenetic more than one gene involved one disease – one genedefect - genetic background plays a role - environment plays a role more severe phenotype mild phenotype often early onset late onset relatively rare common Mendelian inheritance complex inheritance e.g. osteogenesis imperfecta e.g. osteoporosis caused by Mutation in DNA combinations of Variations in DNA are risk factors small effect large effect
solving Mendelian Disorders LINKAGE ANALYSIS NEXT GENERATION / SEQUENCING POSITIONAL CLONING linkage analysis
LINKAGE ANALYSIS _look for the chromosomal region that is shared in all patients and segregates with the disease _works for large families _lot of meioses needed to end up with a small shared region in the patients _does not work for small families with AD rare diseases de novo cases cases with “same disease” but different genes involved - locus heterogeneity _solve with NGS techniques EXOME sequencing
Are monogenetic diseases really that simple?
AUTOSOMAL RECESSIVE homozygous variants in affected siblings compound heterozygous variants in affected siblings heterozygous variants in parents heterozygous variants in parents
De NOVO heterozygous variants in affected sibling ref. seq in parents
X - linked X-chr. heterozygous variants in carrier females X-chr. variants hemizygous in affected males
AUTOSOMAL DOMINANT heterozygous non reference variant in all affected family members
confusing ?? Mani et al, Science 315, 1278, 2007
complicating factors _phenocopies : it looks like the “same disease”, but is it? _locus heterogeneity _technical issues _incomplete penetrance _phenotype definition
PHENOCOPY IN DOMINANT INHERITANCE Example: osteoporosis is a disease in the elderly population _low bone mineral density _impaired bone quality _fractures 30% of women and 12% of men of >60 years are affected _interaction between genes and environment but is also seen as a monogenetic disorder in families
Is one of them a phenocopy? age of age of age of age of onset 74 onset 54 onset 45 onset 40 age of onset 39
PROBLEM OF LOCUS HETEROGENEITY = the disease in your group of patients is caused by more than 1 gene for exome sequencing this is a problem: _the patient population is not homogeneous _you have to search for variants in more than 1 gene _you need enough samples to find the gene mutation
KABUKI SYNDROME _ very rare 1/30.000 – 1/50.000 -- 400 cases worldwide reported _exome sequencing of 10 cases _expectation to find the same causing gene in all cases _only in 4 of the most severe cases a mutation in MLL2 was found _due to >1 gene involved and also technical issues
NON-PENETRANT MUTATION CARRIERS MODIFIERS in AD disease Retinitis Pigmentosa Mutations in PRPF31 Asymptomatic mutation carrier non-penetrant mutation Symptomatic High expression of the gene mutation carrier due to a polymorphism in Low expression of the gene due to the promoter of the absence of polymorphism in the unaffected allele promoter of the unaffected allele = mutated allele + high = mutated allele + low expression expression normal allele normal allele
PARKINSON DISEASE DIGENIC AND INCOMPLETE PENETRANCE _autosomal recessive form due to mutations in DJ-1 or PINK1 DJ-1:wt/A39S _heterozygous PINK1 mutation from mother incomplete penetrance? _heterozygous DJ-1 mutation from father
NON-PENETRANT MUTATION CARRIERS MODIFIERS in AR disease Cystic Fibrosis: Mutations in CFTR classic CF mutation CF + infertility risk in males p.R117H + TGTTTTT classic CF mutation females asymptomatic p.R117H + TTTTTTT males CF - infertility http://genetics.emory.edu/docs/Emory_Human_Genetics_Cystic_Fibrosis_PolyT_TG_Tracts.pdf http://www.cftr2.org/r117h.php
Phenotype Definition _first paper on NGS published in Nature Genetics in 2010 by Ng et al. _Miller syndrome (facial and limb abnormalities) _very rare disease, only 30 cases described in literature _gene 1: DHODH, causing Miller syndrome _gene 2: DNAH5, causing pulmonary problems
NGS DATA WHAT DO YOU GET a large file with variants +/- 25.000 variants present in 1 person
variant information genotypes 25.000 – 80.000 variants depending on the number of samples sequenced genotype file
HOW TO FIND THE RIGHT VARIANT ? MUTATION ?
HOW TO FIND THE RIGHT VARIANT / MUTATION … after exome sequencing you are left with different kind of variants 1. where in the genome -- exonic -- intronic -- intergenic -- ncRNA 2. what kind of change -- STOP gain -- STOP loss -- SYNONYMOUS SNPs -- NON-SYNONYOUS SNPs -- SPLICE SITE VARIANTS -- SMALL INSERTIONS or DELETIONS steps are needed to filter out normal variants -- keep LoF variants
annotated file
HOW TO FIND THE RIGHT VARIANT / MUATION … 3. filter according to the genetic model e.g. for a dominant disease: keep the heterozygous variants in the patients keep the homozygous reference variants in the unaffecteds 4. filter out common variants present in different databases WHICH DATABASES CAN YOU USE? -- dbSNP -- 1000 genomes -- goNL (750 genomes) -- Washington ExomeSequenceProject database (6500 exomes) -- ExAC database (>60,706 exomes) -- gnomeAD database (125,748 exomes + 15,708 genomes)
db SNP contains: _genetic variation; human + other species _SNPs (99.7%) short insertion/deletion polymorphisms (0.2%) short tandem repeats and other things (0.1%) _large submissions included by HapMap Project, 1000 Genomes Project, goNL, Wash_UV ESP _ build 151 with 113,862,023 human validated SNPs in Nov. 2018 _neutral variants as well as disease-causing clinical mutations !
washington ESP database contains: _genetic variation obtained by exome sequencing _from 6503 human samples (4300 European-Americans - 2203 African-Americans) _normal but also with heart, lung and blood disorders _ > 2,000,000 variants 50% Eur-Am 50% Afr-Am _dbSNP build 132 contains a subset of ESP build 138 contains the complete set of ESP
EXAC database Exome Aggregation Consortium combines variants form different consortia worldwide _from 92.000 exomes _65.000 available through their website recently updated to 123.136 exomes + 15.500 WGS now: The Genome Aggregation Database ( gnomAD )
gnomAD database Genome Aggregation Database combines variants form different consortia worldwide _from 125,748 exomes and 15,708 genomes individuals with severe pediatric disease as well as first-degree relatives are removed from the database
frequency in databases
HOW TO USE THE VARIANT FREQUENCY a SNP has a Minor Allele Frequency ... ATGCCGATCGCT ... 80% G allele SNP | G ... ATGCCGATCGCT ... Ancestral allele ... ATGCCGATCGCT ... ... ATGCCGATCGCT ... ... ATGCCGATCGCT ... ... ATGCCGATCGCT ... 20% A allele SNP | A ... ATGCCGATCGCT ... Minor allele ... ATGCCGATCGCT ... ... ATGCCGATCACT ... ... ATGCCGATCACT ... variation/ SNP with MAF of 0. 20 MAF of 20 %
HOW TO USE THE VARIANT FREQUENCY _population frequencies _frequency of monogenetic disorders is very low in the population example: the frequency of disease is: 1 per 10.000 births = 0,0001 = (0,01%) variants freq > 0,0001 can be discarded (to be on the safe side > 0,0005)
HOW TO FIND THE RIGHT VARIANT / MUATION … 5. synonymous variants (no change in amino-acid) can be filtered out but can they?
DIFFERENT TYPES OF SNP s IN CODING REGIONS synonymous SNP non-synonymous SNP variation on DNA level variation on DNA level no change in amino acid gives change in amino acid TTT or TTC TGG or TGC both code for Phenylalanine Tryptofane Cysteine no change in protein change in protein
Example of a functional synonymous SNP - 1 2013
Example of a functional synonymous SNP - 1 Gene: ABCA12 Mutations cause a severe form of recessive skin disease (congenital ichthyosiform erythroderma) _DNA sequencing in a family: no obvious mutation _cDNA sequencing: 163 bp homozygous deletion in the RNA sequence _SYNONYMOUS variant: c.3456G>A TCG TCA : Ser Ser Normal sequence: GTTCCTGTATTTTTCGGACTACAGCTTCT Mutated sequence: GTTCCTGTATTTTTCAGACTACAGCTTCT Creation of a novel acceptor splice site
Example of a functional synonymous SNP - 2 2011
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