Considerations for Analyzing Targeted NGS Data

HLA

Tim Hague, CTO

Introduction Human leukocyte antigen (HLA) is the

major histocompatibility complex (MHC) in humans.

Group of genes ('superregion') on chromosome 6

Essentially encodes cell-surface antigen-presenting proteins.

Functions

HLA genes have functions in: combating infectious diseasesgraft/transplant rejectionautoimmunity cancer

Alleles Large number of alleles (and proteins). Many alleles are already known.

The number of known alleles is increasing

HLA Class IGene A B C Alleles 2013 2605 1551Proteins 1448 1988 1119 HLA Class IIGene DRA DRB* DQA1 DQB1 DPA1 DPB1 Alleles 7 1260 47 176 34 155Proteins 2 901 29 126 17 134

HLA Class II - DRB AllelesGene DRB1 DRB3 DRB4 DRB5 Alleles 1159 58 15 20Proteins 860 46 8 17

Analysis Challenges

HLA genes have specific analysis challenges regardless of the sequencing technology.

High Polymorphism

High rate of polymorphism – up to 100 times the average human mutation rate.

The HLA-DRB1 and HLA-B loci have the highest

sequence variation rate within the human genome.High degree of heterozygosity – homozygotes are

the exception in this region.

Duplications

High level of segmental duplications Lots of similar genes and lots of very similar

pseudegenes. Duplicated segments can be more similar to each other

within an individual than they are similar to the corresponding segments of the reference genome.

Complex Genetics

Particularly HLA-DRB* The DR β-chain is encoded by 4 loci, however

only no more than 3 functional loci are present in a single individual, and only a maximum of 2 per chromosome.

Mitigating Factors

It's not all bad news:Many HLA alleles are already well known – both in terms of sequence and frequencies within the population. The HLA region is fairly small so there a high degree of linkage disequilibrium, and therefore lots of known haplotypes.

Traditional Typing SSO – low resolution, high throughput,

cheap SSP – very fast results, low resolution SBT – sequence-based typing, high

resolution, usually done by Sanger sequencing.

NGS Typing

High resolution, an alternative to Sanger-based SBT

Why is it needed?

Sanger and HLA Sanger data is still the gold standard in

the genomic sequencing industry, even though it is very expensive compared to NGS.

1 in 1'000 base error rate, if forward and reverse typing are done, error rate drops to 1 in 1'000'000.

So why is it bad for HLA?

Phase Resolution

2x chromosome 6 Many loci, many alleles Lots of heterozygosity

reference sequence

A

T

Allele 1

Allele 2 A TAllele 1

Allele 2

OR???

Allele Phasing problem

T/ A

G/T

consensus sequence

The Problem with Sanger There is only one signal High degree of heterozygosity = high degree of

ambiguity Requires statistical techniques based on known

allele frequencies, plus manual intervention by trained operators

Ambiguity can only be resolved statistically, which can lead to wrong assignment for rare types

HLA typing by Sanger method

GGACSGGRASACACGGAAWGTGAAGGCCCACTCACAGACTSACCGAGYGRACCTGGGGACCCTGCGCGGCTACTACAACCAGAGCGAGGMCGGT

0

50

100

150

200

250

300

350

400

450

500

550

Number of potential alleles

NGS Advantages Can reduce ambiguity Phase resolution - two signals, but lots of

short reads Cheaper and faster than Sanger Less manual intervention required

NGS Data - Unphased

NGS Data - Phased

NGS Approaches

HLA*IMP – chip based imputation engine

Reference-based alignment, followed by a HLA call based on the variants detected during alignment

Search against database of known alleles

NGS Reference-based Fraught with difficulties Very hard to align reads to this region The variant/HLA call is only as good as the

alignment No coverage = no call

Has been attempted by Broad Institute (HLA Caller) and Roche

Alignment Efforts

RainDance provide a targeted HLA amplification kit call HLAseq.

Target: the whole MHC superregion (except for some tandem repeat regions)

Goal: align this data, before doing variant/HLA call.

Diverse variant “density” in the MHC superregion

Based on a single sample

Default BWA alignment – No coverage at an exon of HLA-DMB

Low coverage and orphaned reads at a HLA-DRB1 exon

BWA vs more permissive alignment: higher coverage = higher noise

Large targeted region without usable coverage

NGS Reference-based Not providing enough coverage everywhere

What about de novo?

De novo assembly (MIRA)

287 contigs (longest contig: 2199 bp)

Mean contig size: 268 bp

Median contig size: 209 bp

Total consensus: 77084 bp

RainDance target: ~ 3800000 bp

De novo assembly (MIRA)

NGS De Novo Alignment Not enough contigs produced, not enough coverage of

the target region.

What about a hybrid approach?

De novo assembly with “backbone”

First, alignment to backbone, then de novo assembly

Backbone: 2220 contigs from HG19 chr 6 (sum: 3554852 bps) → almost whole RainDance target

Results:

Max reads / backbone contig: 197

Max coverage: 71

De novo assembly with “backbone”

NGS Typing - Alignment Based We tried: Burrows Wheeler alignerMore sensitive, seed and extend alignerDe novo aligner'Hybrid' de novo aligner

The variant/HLA call is only as good as the alignmentThe alignments were not good enough

NGS Database Based Search against 'database' of known alleles Such as IMGT/HLA database, available from EBI

web site

Stanford, Connexio, JSI Medical, BC Cancer Agency and Omixon have all tried this approach.

DB Based Approach AdvantagesLess mapping headaches Unambiguous resultsPotential to be fast

DifficultiesNovel allele detectionHomozygous alleles

Results with Exome data

Exon level detail

Detailed results - short read pileup

Conclusions DB based approach to HLA typing is new but very

promising

NGS approaches can resolve much of the ambiguity of Sanger SBT

DB based approach can also overcome the limitations of NGS reference-based alignment

Conclusions Available DB based HLA typing tools differ in:SpeedSequencers supportedTypes of sequencing data supported (targeted,

exome, whole genome)Ease of useAmbiguity of resultsDegree of manual intervention requiredNovel allele detection capabilities