Download HIV Vaccine Database and Web Works

Visit to John Hopkins
Aravinda Chakravarti and
other researchers
People and labs
• Aravinda Chakravarti - human geneticist
specializing in complex traits.
– Dan Arking much work with SNP arrays
• Andy McCallion - Gene regulation,
especially enhancers in zebrafish.
• Akhilesh Pandey - runs human protein
reference database.
• Ada Hamosh - runs curation side of
OMIM.
– Joanna Amberger - curator
• David Valle - psychiatric genetics
• David Cutler - SNP haplotyping, phasing.
Some of Arivinda’s Projects
• Likes projects that use a variety of
techniques. Likes developing methods.
• Hirschprung’s disease.
• Cardiac sudden death & QT interval.
• Hypertension
• Autism
Hirschprung’s Disease
• Lower parts of the gut, or in severe
cases all of the gut lacks innervation.
• Patients used to due from blocked gut
during infancy. Surgery now helps.
• 4x more common in males.
• 1/5000 infants affected.
• ~10% of siblings of affected are also
affected.
Genetics of Hirschprung’s
• Mutations in 6 genes significantly increase
risk for Hirschprungs.
– RET,PHOX2B,NRTN, L1CAM, GDNF, EDN3
• These genes identified since 90’s via linkage.
• Aravinda’s lab sequenced RET in many
patients.
– They estimate that coding mutations in RET cause
3% of cases. Mutations here tend to be fairly
penetrant.
– A common SNP (~25% minor allele frequency) in
a conserved noncoding region, increases
Hirschprung’s risk by 4x, especially in males.
Sudden Cardiac Death & QT
• Seemingly healthy individuals die suddenly from
heart failure (VTach/V Fib).
– ~2/3rds have some coronary artery disease but not enough
to explain death
– ~1/3rd are from people with no detectable heart disease.
• Associated with long or very short QT interval (which
can be observed in an EKG).
• Hard to get samples from sudden death victims,
since they are dead.
• Initial study focused on QT interval as a quantitative
trait.
– Lots of data and DNA samples from Framingham Heart
Study and others are available.
Genetic Analysis of QT
Intervals
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Nature Genetics article by Dan Arking et al.
Treated QT interval as a continuous trait.
Large association study using Affy 100k chip.
Took extreme 200 subjects showing most extreme
QT’s out of 4000 total subjects.
• Validated results on 4400 independent subjects.
• Used simple ANOVA stats to calculate association
at each SNP.
• NOS1AP (CAPON) varients explain 1.5% of QT
interval variation.
– 3 SNPs in conserved noncoding regions, one of which likely
explains this variation.
Genetic analysis of Sudden
Death
• Small samples of sudden death victims from
ambulances are available.
• Currently lab is doing an association study
based on the Affy 500k chip.
• At end of data gathering stage, just starting
data analysis.
– Evaluating algorithms, Abacus vs. BRLM
– There is an annoying amount of variation
between lots of Affy chips.
Hypertension
• Also a quantitative trait.
• Aravinda’s involved with many analysis
– Meta-analysis of many linkage studies
– Explaining differential effects of salt on
hypertension in various populations to
evolutionary history (salt/heat tolerant
populations more susceptable to salt-sensitive
hypertension).
– Candidate gene approaches
– Also has turned up regulatory mutants.
Aravinda’s Lab & Autism
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Focusing on autistics with language difficulties.
Using affy 500k chip
Have family information
Use chip data first in linkage study, then use
same data with transmission-disequilibrium-test
for association study within candidate regions.
• Have found some relatively common varients
that contribute to risk.
• Colleagues at UCLA have found rarer, higher
risk variants.
Aravinda’s Thinking about
Association vs. Linkage
• Ultimately need to take kinship into account in both
association and linkage studies.
• For every region in the genome, given a population,
can make a binary tree based on genetic similarity
in that region.
• In a sense are looking for regions where cases show
up on one side of tree and controls on another.
• There will be some such regions by chance
common kinship *within*that*region.
• The causative mutations should be in such a region
as well.
• A promising technique is to estimate the relatedness
overall within the population, and use that to scale
significance of associations.
Andy McClellan
• Postdoc’d in Aravinda’s lab.
• Has done functional assays of RET mutants in mouse
and zebrafish.
• Interested in transcriptional regulation in general,
especially enhancers/suppressors.
• Finding many mammalian enhancers work in
zebrafish, even in absense of overt sequence
conservation.
• Doing zebrafish versions of many things Eddy Rubin
& Len Pinnocio doing in mouse.
– Higher throughput in zebrafish, and can observe embryo
over time.
A technique Andy is
examining:
• Hypothesis - enhancers/repressors are brought into
physical proximity with promoters they regulate.
• Method:
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–
–
–
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Cross-link cells with formaldehyde
Digest DNA with restriction enzyme
Ligate with ligase
Sequences near each other in nucleus will form little circles.
Do PCR with primers from one sequence. Sequence PCR
results and see what else is there.
promoter fragment
primer
restriction &
ligation site
primer
restriction &
ligation site
enhancer fragment
Akhilesh Pandey
• Human Protein Reference
Database.
– http://www.hprd.org/
– Large scale effort curating human proteins and
protein-protein interactions out of the literature.
– Curation team was 70 at it’s peak, all PhDs in
India.
– Web works is also quite nice.
– Contains much more pathway stuff than
reactome.
– Web works are also quite nice.
Ada Hamosh & OMIM
• Pediatrician and geneticist
• Took over running OMIM from
Victor McKusick.
• Software and web development
for OMIM is at NCBI.
• Curation is mostly at John Hopkins with some
additional contractors. McKusick still does
some of the curation. Only ~7 curators.
OMIM continued
• OMIM is 100% literature based.
• Genetic varients in OMIM:
– All varients in first paper describing gene/disease link.
– Beyond this try to have most important and common
disease-causing variants.
– No shortcut to mapping variants to genome, all taken from
literature directly, which is a hodge-podge.
• Curators are skeptical of controlled vocabularies
– Prefer medical thesaurus
• http://www.nlm.nih.gov/research/umls/about_umls.html
#Metathesaurus
– Human disease phenotypes are especially a moving target
because doctors intervene! Therapies generally improve
over time.
David Valle
• Pediatrician, works with OMIM
• Discussed primarily psychiatric
genetics.
David Cutler
• Implements software for working with
Affymetrix chips, from gridding to calling.
• His Abacus algorithm has been adopted
by Affy now.
• Also works on haplotype phasing.
Suggestions for hgGenome
• Overall fewer than at King lab (reflecting
hgGenome design for association studies….)
• Support Merlin output, which gives
chromosome/centimorgans as position in a
number of different maps.
• Support Affy ID’s as well as dbSNP.
• Consider adding some optional smoothing.
Suggestion for track showing
phased SNPs and copy number.
s001
s002
s003
s004
s005
s006
s007
s008
Other suggestions
• Ways to make it easier to find candidate
genes within linkage/association peaks.
• Making it more obvious that something has
actually happened when you make a
custom track in table browser.
• Make it so that you can see OMIM ID from
graphics page.
• Make links into Human Protein Reference
Database.
xyz
• XYZ