Michael Buckley - SEALS - Whole Exome Sequencing in the Clinic

Exome Sequencing in the Clinic

Michael Buckley

Clinical Director, S.E.A.L.S. Genetics Laboratory

Randwick Hospitals Campus, Sydney

School of Medical Sciences, UNSW

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SEALS Genetics



SEALS Genetics

A Quick Orientation



SEALS Genetics

• Humans have 46 chromosomes, 22 autosomal pairs and 1 sex chr pair

• Everyone has ~6,000,000,000 base pairs of DNA in each nucleated cell

• Genome = condensation of the words ‘Gene and Chromosome’

A Quick Orientation

Transcribed and protein-coding regions

• There is good evidence for 20,687 protein coding genes and a further 11,224 pseudogenes

• On average, each gene produces 4 alternately spliced mRNA transcripts



SEALS Genetics




• Protein coding genes span 33.45% of the genome from outermost start to stop codons; 39.54% from promotor to poly(A)

• But protein coding and non-coding exons cover 2.94% of genome; purely protein coding exons account for 1.22% for protein coding exons



SEALS Genetics




• Protein coding genes span 33.45% from outermost start to stop codons; 39.54% from promotor to poly(A)

• Both protein coding and non-coding exons cover 2.94% of genome; purely protein coding exons account for 1.22% for protein coding exons

• 70,292 with promotor-like features that turn gene expression on and off

• There are 399,124 regions with enhancer-like features which help regulate expression levels



SEALS Genetics



SEALS Genetics

Genome Methylome

DNA methylation

• Methylation of cytosine (especially at CpG dinucleotides) involved in (epigenetic) regulation of gene expression

• 96% of CpGs exhibited differential methylation in at least one cell type or tissue

• Levels of DNA methylation correlated with chromatin accessibility

• Gene promotor methylation is generally associated with repression

• Reproducible cytosine methylation seen outside CpG dinucleotides; may have important roles in human biology



SEALS Genetics



SEALS Genetics

Genome

Transcriptome

Methylome

Transcription

• 80.4% of genome “participates in at least one biochemical RNA- and/or chromatin-associated event in at least one cell type”

• 95% of genome lies within 8kb of a DNA-protein interaction

• 99% is within 1kb of at least one of the biochemical event

Most of the Genome is Functional



SEALS Genetics



SEALS Genetics

Genome

Transcriptome

Methylome

Small RNAome Proteome

Transcription

Translation



SEALS Genetics

Genome

Transcriptome

Methylome


Inherited &

essentially

same in all

nuclei

Transcription

Translation



SEALS Genetics

Genome

Transcriptome

Methylome


Inherited & essentially same in all nuclei

Cell/tissue specific

Transcription

Translation

The Exome

• The exome is the part of the genome formed by exons, the sequences which when transcribed remain within the mature RNA after introns are removed by RNA splicing

• There are ~180-200,000 coding exons in the human genome

• Represents approximately 30 Mb of the total 6.4Gb diploid human genome (~1.1% of the total)



SEALS Genetics

The Exome




• But they encode the vast majority of information relevant to protein structures



SEALS Genetics

The Exome




• But they encode the vast majority of information relevant to protein structures

• Because most high penetrance (i.e. Mendelian or nearly so) variation is mediated by non-synonymous, frameshifting and canonical splice variation, exomes are ideal for studying the relationship of such variation to health and disease



SEALS Genetics



SEALS Genetics

Exon 2 Exon 3 Exon 4

Intron 2 5’UTR

Promoter

3’UTR

STOP START

Intron 1

Conservation

Exon 1

Beta-Globin Gene Structure



SEALS Genetics


Intron 2 5’UTR

Promoter

3’UTR

STOP START

Intron 1

Conservation

The standard exome only includes these few Protein-encoding elements

Exon 1



SEALS Genetics


Intron 2

Promoter

STOP START

Intron 1

Conservation

Exon 1

The other coding and non-coding regions of importance are

generally not included

5’UTR 3’UTR

WES: pluses

• Therefore analysing exomes compared with genomes involves a huge reduction in complexity

• A reduction in complexity equates to a very significant reduction in sequencing costs compared with whole genome sequencing (~15% the cost)

• It takes a much shorter time to generate the data - you can generate 1,000 exomes in the time it takes to do 67 whole genomes

• The computing time for exomes is about 1/15th that for a whole genome



SEALS Genetics

WES: pluses • Therefore analysing exomes compared with genomes involves a

huge reduction in complexity

• A reduction in complexity equates to a very significant reduction in sequencing costs compared with whole genome sequencing (~15% the cost)

• It takes a much shorter time to generate the data - you can generate 1,000 exomes in the time it takes to do 67 whole genomes

• The computing time for exomes is about 1/15th that for a whole genome

• Provides a focus on just the regions where clinical molecular geneticists provide the best interpretation, therefore the medico-legal issues are somewhat reduced

• It has been called the ‘sweet spot’ in genomics where a lot can be achieved for moderate cost



SEALS Genetics

WES: minuses

• Doesn’t address variants in non-coding regions or even non-coding exons

• It doesn’t look at regions involved in transcriptional regulation

• It has limited ability at present to resolve copy number variants by looking at read depth

• It has virtually no useful role at present in looking at balanced structural alterations such as large inversions or translocations.

• Can’t detect UPD

• With short reads, Fragile X and other trinucleotide repeats are not able to be characterised

Are the pluses sufficient to out-weigh the minuses for a diagnostic lab?



SEALS Genetics

Applications of WES

• There are two predominant applications of WES - gene discovery in the research context - mutation identification for patient diagnosis

Mendelian gene discovery:

• 497 publications reporting 457 new disease genes since November 2009

• The rate of gene discovery is increasing and is approaching 1 new Mendelian disease gene per day


SEALS Genetics



SEALS Genetics

WES is Accelerating Mendelian Gene Discovery

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10

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80

90

Number of Mendelian Disease Genes Published per Quarter

Number

Power (Number)



SEALS Genetics

Gene identification is becoming routine

0

10

20

30

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Number

Mean IF

Power (Mean IF)

Success of Exome Seq for Gene Discovery

• Reviewed 24 Mendelian disorders studied in Nijmegen.

• Research based patient cohorts who had a syndromic diagnosis

• Frequently multiple families were available for analysis from different ethnic populations. - 6/10 dominant disorders were identified - 8/14 recessive disorders identified

• Overall 58% success in research studies for gene identification purposes.


SEALS Genetics


Factors Influencing Success in Gene Discovery

• That the condition is truly a genetic disorder and its mode of inheritance is predictable (e.g. de novo dominant v. recessive)

• Careful and correct clinical/laboratory phenotyping is ESSENTIAL

• Have sufficient numbers of affected and unaffected individuals available from several families

• Pre-existing linkage or homozygosity mapping information is useful

• The gene is targeted by the exome selection kit


SEALS Genetics


Performance of WES for Diagnosis?

• Gilissen et al 2012 modelled the sensitivity of WES for known disease causing variants.

• Evaluated the sequence coverage of 50 exomes for 37,424 non-synonymous variants in Human Gene Mutation Database that don’t overlap with known SNPs - 2,128 (5.7%) were not covered by any reads - 30,239 (81%) had >10 reads

• Suggests that WES mutation sensitivities may top out at about 80%, and therefore WES is best considered as a good screening test

• Improvements in depth of sequencing are needed.


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Performance of WES for Targeted Diagnosis


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• Eleven published studies using the whole exome sequencing approach to target a defined set of genes (>5 unrelated probands, unknown case mutation status)




SEALS Genetics

• Eleven published studies using the whole exome sequencing approach to target a set of genes. (>5 unrelated probands, unknown case mutation status)

PMID Disorder Heterogeneity Cohort Known Novel Known K&N Mitochondria

PMID: 22499348 Mitochondrial complex I deficiency 10 7 70% 70%

PMID: 23596069 Suspected mitochondrial disorders. >1000 84 5 26 6% 37%

PMID: 22277967 mitochondrial oxidative phosphorylation disease >1000 42 23 13 55% 86%

Neurosensory disorders

PMID: 23226338 Autosomal recessive nonsyndromic hearing loss. 39 20 12 60% 60%

PMID: 23661368 Leber congenital amaurosis. 19 41 15 37% 37%

Complex Neurological Disorders

PMID: 23169490 Meckel-Gruber syndrome in Arabs 10 18 12 3 67% 83%

PMID: 23352163 Multipex families with autism. 70 163 9 11 6% 12%

Others

PMID: 23035047 Neonates in NICU 450 9 3 66% 66%

PMID: 22662265 Pre-screened MODY. 111 9 3 5 33% 89%

PMID: 22492991 Prescreened Congenital disorders of glycosylation I 76 9 1 2 11% 33%

PMID: 23054246 Prescreened Familial Hypercholesterolaemia. 3 48 20 7 42% 56%

PMID: 23409019 non-BRCA1/BRCA2 familial breast cancer 20 7 1 14% 14%

Sensitivity Genes




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Sensitivity Genes

• Eleven published studies using the whole exome sequencing approach to target a set of genes. (Minimum of 6 unrelated probands)

• Average sensitivity of mutation detection was 39% for known genes, rising to 54% for known plus novel genes (medians 42% and 60% respectively)

PMID Disorder Heterogeneity Cohort Known Novel Known K&N Mitochondria

PMID: 22499348 Mitochondrial complex I deficiency 10 7 70% 70%

PMID: 23596069 Suspected mitochondrial disorders. >1000 84 5 26 6% 37%

PMID: 22277967 mitochondrial oxidative phosphorylation disease >1000 42 23 13 55% 86%

Neurosensory disorders

PMID: 23226338 Autosomal recessive nonsyndromic hearing loss. 39 20 12 60% 60%

PMID: 23661368 Leber congenital amaurosis. 19 41 15 37% 37%

Complex Neurological Disorders

PMID: 23169490 Meckel-Gruber syndrome in Arabs 10 18 12 3 67% 83%

PMID: 23352163 Multipex families with autism. 70 163 9 11 6% 12%

Others

PMID: 22662265 Pre-screened MODY. 111 9 3 5 33% 89%

PMID: 22492991 Prescreened Congenital disorders of glycosylation I 76 9 1 2 11% 33%

PMID: 23054246 Prescreened Familial Hypercholesterolaemia. 3 48 20 7 42% 56%

PMID: 23409019 non-BRCA1/BRCA2 familial breast cancer 20 7 1 14% 14%

Targeted Exome Sequencing

• Exome Seq now has two forms, Targeted and Whole exome sequencing

• Illumina markets a clinical exome product (TruSight Exome) which targets the 2761 genes in HGMD databases with known clinical effect on the date of design.

• Little published data but appears a good solution for common disease genes

• Lacks targets in some clinically significant genes - Erf Variable suture craniosynostosis - TCF12 Multisuture craniosynostosis - SLC29A3 Histiocytosis/Lymphadenopathy + syndrome



SEALS Genetics

.

Reverse Phenotyping


SEALS Genetics

Reverse Phenotyping

PMID: 22378277 FSHD2 to LGMD2A Leidenroth A, et al. Eur J Hum Genet. 2012 Sep;20(9):999-1003

PMID: 22730194 Charcot-Marie-Tooth disease. Choi BO, et al. Hum Mutat. 2012 Nov;33(11):1610-5

PMID: 22823409 ASPM in apparent X-linked microcephalic intellectual deficit. Ariani F et al. Clin Genet. 2013 Mar;83(3):288-90

PMID: 22901280 atypical episodic muscle weakness. Hanchard NA, et al. Clin Genet. 2013 May;83(5):457-61

PMID: 23468869 rett syndrome exome sequencing. Grillo E, et al. PLoS One. 2013;8(2):e56599

PMID: 23483706 ATL1 Blurs Autosomal Dominant Inheritance of Spastic Paraplegia. Varga RE, et al. Hum Mutat. 2013 Jun;34(6):860-3

PMID: 23610050 Bartsocas-Papas syndrome. Gripp KW, et al. Am J Med Genet A. 2013 May;161A(5):1058-63

PMID: 23652424 PROP1 Deficiency: Clinical Impact of WES Wassner AJ, et al. Horm Res Paediatr. 2013 May 3

PMID: 23664929 X-linked adrenoleukodystrophy mimicking recessive hereditary spastic paraplegia. Zhan ZX, et al. Eur J Med Genet. 2013 May 9

PMID: 23700088 A Novel OPA3 Mutation Revealed by Exome Sequencing Arif B, et al. JAMA Neurol. 2013 Jun 1;70(6):783-7

• WES has a role in correcting phenotypic classification, so called reverse phenotyping .


Reverse Phenotyping


SEALS Genetics

Reverse Phenotyping

PMID: 22378277 FSHD2 to LGMD2A Leidenroth A, et al. Eur J Hum Genet. 2012 Sep;20(9):999-1003

PMID: 22730194 Charcot-Marie-Tooth disease. Choi BO, et al. Hum Mutat. 2012 Nov;33(11):1610-5

PMID: 22823409 ASPM in apparent X-linked microcephalic intellectual deficit. Ariani F et al. Clin Genet. 2013 Mar;83(3):288-90

PMID: 22901280 atypical episodic muscle weakness. Hanchard NA, et al. Clin Genet. 2013 May;83(5):457-61

PMID: 23468869 rett syndrome exome sequencing. Grillo E, et al. PLoS One. 2013;8(2):e56599

PMID: 23483706 ATL1 Blurs Autosomal Dominant Inheritance of Spastic Paraplegia. Varga RE, et al. Hum Mutat. 2013 Jun;34(6):860-3

PMID: 23610050 Bartsocas-Papas syndrome. Gripp KW, et al. Am J Med Genet A. 2013 May;161A(5):1058-63

PMID: 23652424 PROP1 Deficiency: Clinical Impact of WES Wassner AJ, et al. Horm Res Paediatr. 2013 May 3

PMID: 23664929 X-linked adrenoleukodystrophy mimicking recessive hereditary spastic paraplegia. Zhan ZX, et al. Eur J Med Genet. 2013 May 9

PMID: 23700088 A Novel OPA3 Mutation Revealed by Exome Sequencing Arif B, et al. JAMA Neurol. 2013 Jun 1;70(6):783-7

• WES has a role in correcting phenotypic classification, so called reverse phenotyping .

• Raises the possibility of whether an unbiased exome approach may yield more correct patient diagnoses than clinical genetics.


Performance of WES in the Diagnosis of Unknown/Complex Disorders


SEALS Genetics

Najmabadi et al Dixon-Salazar et Need et al

Nature Sept 2011

Sci Trans Med June 2012

J Med Genet June 2012

136 ID probands from consanguineous families

118 ID probands from consanguineous families

12 parent-child unselected trios

Studied homozygous regions

Studied homozygous regions

Studied de novo mutations

26 of 136 (19%) diagnoses 32 of 118 (27%) diagnoses

6 of 12 (50%) diagnoses

2 possible further diagnoses


Performance of WES for Diagnosis • Baylor College of Medicine experience:

- BCM recently published results of 250 exomes predominantly children with neurological disorders,

- 62 of 250 (25%) had a genetic cause of their disorder identified by WES

- In 4% the diagnosis was revised base don the exome findings

- About 3% end up with better management

- Only 1% get a treatment and major benefit


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4% total personal benefit


Performance of WES for Diagnosis • Baylor College of Medicine experience:

- BCM recently published results of 250 exomes predominatly children with neurological disorders,

- 62 of 250 (25%) had a genetic cause of their disorder identified by WES

- In 4% the diagnosis was revised base don the exome findings

- About 3% end up with better management

- Only 1% get a treatment and major benefit

• Not every exome sequencing study will work, but is vast improvement over previous experience.

• Baylor College of Medicine currently charges $US7,000 - 9,000 for a family exome study, so approximately $200,000 per case showing management improvement


SEALS Genetics


Familial Trios for de novo mutations


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de Ligt et al Rauch et al Yang et al

N Eng J Med Oct 2012

Lancet Nov 2012

N Eng J Med Oct 2013

100 parent-child trios with MR

45 cases parent-child trios

33 AD cases 9 XL cases

Targeted de novo mutations

Targeted de novo mutations

Targeted de novo and inherited disorders

12 de novo mutations in genes known to cause MR

16 de novo mutations in genes known to cause MR

83% AD were de novo 40% XL were de novo

Total 16 of 100 (16%) ‘de novo’ diagnoses

6 /45 in novel genes (48%) ‘de novo’ diagnoses


Research/Diagnosis Boundaries in WES

• In the early years of genomics practice in diagnostic labs it is to be expected that frequently a project that starts out as pure diagnosis will merge into a research project depending on whether or not a pathogenic mutation in a known gene is discovered.


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• Eurogentest best practice committee considered this situation and has suggested the following boundaries:


SEALS Genetics




• Eurogentest best practice committee considered this situation and has suggested the following boundaries:

- Diagnostic clinical molecular genetics reporting is considered to be based on reporting existing EVIDENCE of causality between a detected variant and a disease state.


SEALS Genetics




• Eurogentest best practice committee considered this situation and has suggested the following boundaries


- Research genetics is based on a HYPOTHESIS of an association between a variant and a phenotype, condition or disorder.


SEALS Genetics




• Eurogentest best practice committee considered this situation and has suggested the following boundaries


- Research genetics is based on a HYPOTHESIS of an association between a variant and a phenotype, condition or disorder.

• Diagnostic reporting therefore stops where there is no prior evidence, but a diagnostic report may include a recommendation for further research between an observation and a disease state.


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New Concept - Diagnostic Yield

• Eurogentest best practice meeting Feb 2013 endorsed the following concepts as performance characteristics to evaluate WES diagnostic testing.

- diagnostic yield: the number of patients who receive a molecular confirmation of a given clinical diagnosis. It is the likelihood that a test, which can include multiple genes, will provide the information needed to establish a genetic diagnosis


SEALS Genetics


NGS Diagnostic Yield



- In order to justify changing a test from Sanger based to NGS based sequencing it should result in a diagnostic yield that at least matches sequential gene testing using Sanger sequencing.


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- In order to justify changing a test from Sanger based to NGS based sequencing it should result in a diagnostic yield that at least matches sequential gene testing using Sanger sequencing.

- NGS based analysis of a large gene set or exome/genome will not cover all targeted bases as well as Sanger sequencing but will result in more diagnoses, particularly in diseases with extreme locus heterogeneity such as deafness, intellectual disability, thoracic aneurysms and many more


SEALS Genetics



SEALS Genetics

Current Investigation of

non syndromic ID

Cytogenetics ~10-15%

Chromosomal Microarray ~ 5 -15%

Fragile X ~1%

Metabolic/specific genetic tests ~5%

Overall 20-30% diagnostic sensitivity




SEALS Genetics

Current Investigation of

non syndromic ID

Cytogenetics ~10-15%

Chromosomal Microarray ~ 5 -15%

Fragile X ~1%

Metabolic/specific genetic tests ~5%

Genomic Diagnosis of nsID

Chromosomal Microarray ~15-30%

Overall 20-30% diagnostic sensitivity

Fragile X ~1%

NGS Trios ~19-50%

Overall >50-60% diagnostic sensitivity



NGS Core Disease List

• To guarantee uniform and transparent molecular testing between clinical genetic laboratories it is recommended each lab defines and maintain a ‘core disease gene’ list for genetic diseases.


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- Genes on this list are considered to be ‘disease essential’ as defined by a team of medical and genetic experts.


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- Mutation frequencies detected within these ‘core disease genes’ are significant for that particular disorder and warrant a sequencing quality that matches current practice (i.e. high sensitivity and specificity).


SEALS Genetics





- Mutation frequencies detected within these ‘core disease genes’ are significant for that particular disorder and warrant a sequencing quality that matches current practice (i.e. high sensitivity and specificity).

- It is required that all genes mentioned on this list are tested at high quality and that this specific quality requirement is clearly indicated in the final report.


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An example of a NGS Core Disease List


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Core Genes

BRCA1

BRCA2

Offer NGS, with Sanger pick-up of any region not

covered to diagnostic standard as well as MLPA




SEALS Genetics

Core Genes

BRCA1

BRCA2

Non-Core Genes

ATM

TP53

CHEK2

PTEN

CDH1

PALB2

Offer NGS, with Sanger pick-up of any region not

covered to diagnostic standard as well as MLPA

Offer NGS and exon chromosomal microarray but

with only a guarantee to sequence each gene to

a screening standard


The Ideal Pipeline

• Ideally we would like a diagnostic pipeline which could identify all classes of mutation associated with human genetic disease

• It would need to be capable of: - the detection of all DNA sequence mutations - exon resolution copy number mutation detection through bioinformatic processing of read-stack data - balanced structural mutation detection by length defined mate pairs - identifying non-human DNA inserted into a gene, by de novo assembly - ability to detect UPD by analysis of minor allele frequency usage - characterising changes in methylation patterns by sequencing captured methylated DNA - detecting changes in levels of expression



SEALS Genetics

Whole Genome Sequencing • The solution that would best fit these needs will clearly be whole

genome sequencing

• It would need to be capable of: - the detection of DNA sequence mutations , 5-10-% better exon coverage than exome approaches - exon resolution copy number mutation detection bioinformatic processing of read-stack data - balanced structural mutation detection by direct detection or via length defined mate pairs - identifying non-human DNA inserted into a gene, by de novo assembly - ability to detect UPD by analysis of minor allele frequency usage - characterising changes in methylation patterns by recognising methylated bases directly or by sequencing directly captured methylated DNA



SEALS Genetics

Health & Medicine

Michael Buckley - SEALS - Whole Exome Sequencing in the Clinic