User:Robert M. MacCallum/WTFGSB Reportback

Welcome Trust Functional Genomics and Systems Biology Workshop

30 November to 1 December 2009

Day one

Edison Liu

Estrogen (or is it EGF) receptor (ER) binding site analysis (ChIP and bioinf) - "Cosmic" score, correlation with RNA PolII binding and H3K4meX marks.

Some functional binding is 1Mb away from gene!! Only 9% in 5k "promoter".

Cool ChIA-PET (ChiA-seq) method to determine chromosomal loops.

Looping for efficient transcription, grouping of coregulated genes ("looped out" genes don't respond to ER)

Johan Rung

GWAS for type 2 diabetes

F Pradezynski

Y2H between various virus proteomes and human proteins.

Many human pathways interfered with, in particular the ones you'd expect (interferon reponse)

Seems to be a remarkable number of targets (100s) from such a few viral proteins.

Chris Bakal

Wounding, cell morphology, image analysis -> 100+ feature profile of cell's, morphology.

"canalised" morphology space (jumps between states)

Keith Baggerly

Reproducibility in hi-thru biology

More to come on this

Nick Luscombe

Nuclear lamins known to tether transcriptionally inactive DNA

Nucleoporins now shown to be assoc with active gene expression.

Also through ChIP some proteins bind to enable X chromosome dosage compensation.

Mark Gerstein

A review of several years' network work. Including some Venter ocean sample sequence analysis (map to pathways, correlate with environmental factors with some canonical ..... method (is this like bi-clustering?))

Day two, session one

Seth Grant

Complexity of post-synaptic molecular machinery (several thousand proteins). Conserved in invertebrates (50% of prots) and single celled (25%). Evolution of the machinery (including plasticity) preceded evolution of synapses.

Very slow evolution.

Many diseases.

Caleb Webber

CNV in mouse

What's special about pathological CNVs? (vs. benign)

Human CNVs look up mouse phenotypes (somehow!)

Enrichment!

Florian Markowetz

ES cell histone modifications

days 1 3 5 of ES development - 4 analyses

Protein MS ChIP-chip histone Rna pol II Microarrays

day 0 nanog TF downreg -> network of TFs

clustering of smoothed histone profiles (around TSS)

when mRNA upreg, small local acetylation around TSS when mRNA down, wider deacetylation around TSS.

increased correlation between H acet and gene expression through time (more at day 5 than day 1) genome-wide

predict gene expr from histone acetylation using LOTS of ML methods (in R)

Grant Belgard

brain transcriptomics

by sequencing

6 layers of neocortex

many cell types spanning several layers

paired end 50bp reads

(you get some intronic reads)

some intergenic regions detected (a few percent of reads)

layer specific genes, various layers show various GO enrichments.

John Hogenesch

Circadian clock genes through hi-thru func genomics. nice robot video.

siRNA screen (seems to be tunable to desired knockdown level)

clock pathway is robust - surprising lack of lethal knock outs

Day two, session two

Peter Hoen

(standing in for Gert-Jan van Ommen)

Duchenne muscular dystrophy

antisense therapy

Andrew Teschendorff

classification of breast cancer

Dan Geschwind

transcriptional regulation of CNS development genes by FoxP2

looked at human vs chimp regulation of genes (microarray) in a cell line.

many genes respond differently (up and down)

But why? The 2 AA diffs are not in known DNA binding domain

6 genes regulated via proximal promoter (luciferase reporter)

validated in vivo

haNCS human accelerated non coding sequences (look this up)

Horvath weighted gene co-expression network analysis. WGCNA

Recent paper showing two mitochondrial network types in neurons (synaptic and cell body)

Compare human vs chimp networks

Douglas Kell

Suit and tie alert!

networks described in unambiguous fashion, SBML, ChEBI SMILES etc for small molecules.

uptake of drugs, via transporters (proteins).

Day two, session three

Genevieve Konopka

Language genes

Can't do multi-species (human, chimp, macaque) on a human affy chip.

Next gen sequencing! Four brain regions.

"Sequencing wins"

Networks from WGCNA

Tom Freeman

Networks in immunity

focus: macrophage

mentioned proteasome (did I see that on map wrt immunity?)

graphical markup for pathways

some kind of flow simulations through them

biolayout express software - looks good (has enrichment analysis built in)

Day two, session four

Frank Holstege

yeast

1200 regulatory components, TFs, kinases, ch remodelers, RNA processing -> mutations and expression microarrays

GASSCO dye correction algorithm (two colour!)

done so far deletome

some kinases have no diff expr, is it because they are inactive in standard conditions or is it because of redundancy?

The use some synthetic genetic interaction prediction to choose pairs

find signals!

some kinases redundant with phosphatase! it's cross talk between two pathways (somehow).

different types of redundancy:

1. complete
2. quantitative (double has more effect than single(s))
3. incongruent (effects in single are not in double)

also used the data for protein complex prediction

Stefan Weimann

new targets for drug resistant breast cancer

ErbB signalling network

the drug is an ErbB2 antibody

Louis Serrano

Mycoplasma pneumoniae

689 ORFs + 44 RNAs

free living

maybe only 10-11 TFs (E. coli 100 or so)

full complement of chromatin remodelling

plan was to do loads of -omics + electron microscopy

transcriptomics: arrays 62 conditions, tiling array

detailed look at transcripts (reverse strand ncRNA, no idea of mechanism) multiple TSSs

where you have operons encoding 4 genes, you don't just see mRNA of all four, you get different levels of each gene, somehow...

same SOS response as subtilis, but without the TFs! very interesting

plenty of regulatory complexity

metabolome: KEGG didn't work out, had to do lots of manual work to build metabolic map. defined minimal medium.

know reactions are there, but 10-12 enzymes are not known

200 molecules per protein per cell

so small that you're "living in a stochastic world" - each reaction is like rolling a dice, how does it survive is an interesting question.

Day three, session one

Jurg Bahler

Pre-post splicing levels measured with RNA seq.

Splicing efficiency regulated

Co-transcriptional splicing. Look for relationship between splicing and chromatin - H3K36me3 lower in introns.

Measured transcript levels after transcription blocking compound - measure decay, however drugs have side-effects. Better to measure PolII occupancy and RNA abundance and estimate decay with a formula.