Transcriptome Profiling of Human Cardiac

Tissues in Hypoplastic Left Heart SyndromeKarl D. Stamm, MS

Donna K. Mahnke, MS; Mary A. Goetsch, MS; D. Woodrow Benson, MD, PhD; Xing Li, PhD; Aoy Tomita-Mitchell, PhD; Timothy J. Nelson, MD, PhD; James S. Tweddell, MD; Michael E. Mitchell, MDSeptember 2013 Research UpdateSeptember 2013 Research Update

Overview• Medical Research• Trouble with humans• Rare diseases are common in a large enough population

• Next-Generation Sequencing Tech• Illumina HiSeq methodology• Differential expression

• Further Mining• Principle components analyses• Gene profiles and the self-organizing-map

Trouble with Humans• Small sample sizes• Low statistical power• High interpersonal variability• Ethnic backgrounds imply metabolic differences

• Phenocopy• Multiple distinct diseases showing identical presentation• Confounds clustering or association studies• Ruins Case/Control study power

• PHI – Private/Protected Health Information• Data security is paramount• Cross-disciplinary collaborations are limited• DNA is theoretically but not practically identifiable

Congenital Heart Defect Incidence• Down Syndrome 1:700 live births• 50-60% have some structural heart defect

• 22qD Syndrome 1:4000 live births• 75-90% have some structural heart defect

• ‘Healthy’ 99:100 live births• 0.8% have some structural heart defect

Proportion Explained:

C.H.D. in particularHypoplastic Left Heart Syndrome

All sequencing costs for this study provided by

1 in 40 CHD cases are HLHS2.5 : 10000 of all births•Complex developmental disorder•100% fatal before the invention of the Norwood Procedure 1981•No multigenerational pedigrees•Spontaneous mutation: immune to detection by genetic linkage

Generate Reads – Illumina Tech

10 to 500 million short reads are generated in pairs, 2x50 to 2x100 bp each.http://seqanswers.com/forums/showthread.php?t=21

Align Reads to Reference

• Which one? • NCBI #37.3 has 3.1 billion bases across 190 contiguous scaffolds• UCSC hg19 has 3.2 billion bases across 163 contiguous scaffolds• Haploid reference contains disease alleles and chimeric sequence

like an A+B+O blood type.

Image of patches modifying the CHR17 reference from 2011 according to Ensemblhttp://www.ensembl.info/blog/2011/05/20/accessing-non-reference-sequences-in-human/

Millions of Variants• The 1000 Genomes project found 38 million SNPs, 1.4 million

short insertions or deletions, and more than 14 thousand larger deletions

• The NHLBI Exome Sequencing Project targeted 22MBases across 2,440 individuals and found 563,700 variants, 82% of which were novel. They averaged 200 novel, coding mutations per person.

• We find about 150-300 thousand SNVs in an exome, 10% of which are nonsynonymous

• SAMTOOLS is the software of choice for variant calling relative to your reference genome.

• CCG/Proline -> CTG/Leucine • HOPX is a gene known to regulate heart development!

• Very common mutation

RNA-Seq vs. Whole Genome

1. Extract and purify mRNA by polyadenylation

2. Convert spliced mRNA to DNA fragments

3. Run standard genome sequencing on the product

4. Result: Expression level dependent sequence coverage

Image found athttp://www.pacificu.edu/optometry/ce/courses/20591/armdpg3.cfm

RNA-Seq Reconstructs Transcripts

From the CuffLinks paper, Trapnell et al.http://www.nature.com/nbt/journal/v28/n5/abs/nbt.1621.htmlNature Biotechnology Volume: 28, Pages: 511–515 Year published: (2010)

IGV – aligned reads viewer

CoverageBED

BEDTOOLS : a flexible suite of utilities for comparing genomic features. http://code.google.com/p/bedtools/

Simple arbitrary feature read depth counting.-Count by gene, exon, whatever

Example of bad alignment

Variance and mean linked by local regression - for robust parameter estimation.

• Negative Binomial

• Models count as ‘binomial successes until a set number of failures’ which better fits the RNA-Seq fragment generation (limited reagent)

• Allows/captures the ‘overdispersion’ seen in RNA-Seq experiments.

Scale the totals for compatible means

Mean-Variance Connection

Detection in Low Values

Per-gene mean by difference ratio

DESeq• Starting from 18,000 Rsids minus 1200 NA• 1000 entries p<0.05

Theme

• Big lists• Noisy data• Complex correlation• Heterogeneous background

Precious Tissue Samples

• Collecting tissue during surgery is an extra burden placed on overloaded surgical teams.

• Samples must be processed carefully to avoid degradation of sensitive molecules.

• Many steps and costs prior to gene sequencing.

• Collaborators have provided 35 patients’ atrial septal tissues.

• Still no ethical source of healthy control.

• Hope to see separation between red/notred or solid/notsolid points• Lack of discrimination in major variation dimensions • Implying uncontrolled heterogeneity dominates

Therefore, more difference person to person than between subtypes

Top25 Consistent Genes

• Anyone know what it means when Adducin2 and HomeoboxA4 are overexpressed? Is it significant that a dehydrogenase is under-expressed?

Group Profiles at Selected Dimensions

Self-Organizing Map

• Kohonen 1990 • Halfway between neural networks and k-means (horrible oversimplification)

• Enforced grid layout and local neighborhood similarity• Data points (here 25-dimensional vectors) lay out in natural organization

Stochastic - Iteration

Pairwise Similarity• Co-clustering frequency determines sample similarity• Sub-clusters are identified organically

Results• Lists of genes differential across conditions• Many conditions, uncertain homogeneity• List cutoff subjective• No healthy control group

• We can mine these lists for pathways or biological processes• Resulting in more lists of more complex results

Transcriptome Project Future Work• A few more samples are coming… Can we build a classifier?• Predict non-measured variables? Signatures of immune

response point towards treatment targets.• Predict compensatory effects? Samples are taken just days

after birth, but 8 months after the heart started beating.

• How else we could look at this rich, unique dataset?

Thanks for listening