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ISMB 2010 Keynote Presentations Keynote Presenters
ISCB Overton Prize Lecture ![]() (Photo by: Glen Dohie) University of California, Berkeley
![]() ISMB2010 Blog Keynote: Steven Brenner - Ultraconserved nonsense: gene regulation by splicing & RNA surveillance Barb Bryant, Mickey Kosloff, Deepak Singh, Saravanamuttu Gnaneshan, arne, Tomasz Puton and Roland Krause liked this ![]() ![]() Whitehead Institute for Biomedical Research ![]() ISMB2010 Blog Keynote: Susan Lindquist - Protein Folding and Environmental Stress REDRAW the Relationship between Genotype and Phenotype ![]() Ted Laderas: "Inherited Environmentally acquired traits - lamarck wasn't so insane" Venkata P. Satagopam: "Protein folding - environment is very important ... showed videos" Ted Laderas: "experiments in heat shock tolerance -initial small shock allowed for survival -hsp proteins are made in massive amounts - role in protein folding" John Greene: "Hsp90 a special chaperone." Ted Laderas: "in excess in cell - acts as homeostasis buffer" John Greene: "Hsp90 a special chaperone." Dawei lin: "hsp70 helps early stage folding and works with a number of proteins, but not hsp90." Venkata P. Satagopam: "HSP 90 a special chaperone ... because very abundant, it induced by two folds, it has extra folding capability .... acts as a buffer" Venkata P. Satagopam: "Signal transduction networks & HSP90 ... Hanahan and Weinberg, cell 2000" Dawei lin: "showed signal transduction network involved by hsp90. It seems pretty spread." Dawei lin: "hsp90's function is found by an accident." Venkata P. Satagopam: "Hsp90 mutations in fruit flies leads to death of flies" Dawei lin: "some mutated fruit flies survived revealed that hidden genetic variant. Hsp90 does not destabilize development." Dawei lin: "raise fly at high temperature can reduce the amount hsp90 level, easier than did it in a genetic way" John Greene: "Hsp90 a special chaperone." Venkata P. Satagopam: "acts as a capacitor for some variation .... it also acts as a potentiator for other variation" Dawei lin: "both fly and arabidopsis experiments show that hsp90 acts a buffer for variations." Dawei lin: "hsp90 can complex with inactive hormone receptors and oncogenic kinases" Dawei lin: "hsp90 helps mutated kinase, which lost the ability to inhibit itself." Dawei lin: "same thing happened in human diseases." Dawei lin: "so hsp90 inhibitor can be used for a drug." Dawei lin: "there are a few fungi drugs available clinically" Dawei lin: "remove level hsp90 buffer level completely removed the drug resistance evolution" Dawei lin: "Raise temperature again eliminated the drug resistant development. Should the patient be put in fever stage." Dawei lin: "talked about some unpublished data" arne: "Where is the bioinformatics ?" Dawei lin: "when added hsp90 inhibitor, some traits disappeared but some showed up" Dawei lin: "ame, people who analyzed the data, :-)" Dawei lin: "it should be a huge work to make genotype to phenotype map" Dawei lin: "the polymorphism in NFS1 that required for tRNA modifications caused the phenotype charge" Dawei lin: "polymorphisms in 3' UTR of HNI1 is also affected by hsp90, but not directly instead through the proteins binding to that region." Dawei lin: "has Hsp90 left an imprint on genomes that exist today?" Dawei lin: "hsp90 affects polymorphisms throughout the genome even non-coding, in combinatorial way" Dawei lin: "it is benefit to human is the big reason to continue the research." Saravanamuttu Gnaneshan: "yeast prions - genetic element based on protein conformation" Saravanamuttu Gnaneshan: "prion also switches on with environmental stress" Dawei lin: "prion has similar behavior of hsp90. It generates new phenotypes." ![]() Max Planck Institute for Evolutionary Anthropology
![]() ISMB2010 Blog Keynote: Svante Pääbo - Analyses of Pleistocene Genomes ![]() Tomasz Puton: "This will probably be a very interesting talk. Just can't wait." arne: "Not just interesting, but most likely great. Svante is a fantastic speaker" Barb Bryant: "If you’re interested in human history, the genome is a great source of information. To reconstruct history, we compare sequences of people (and other species) living today. We use models of how DNA changes over time to understand the differences that exist today. This is an indirect way to study history, because we are reconstructing from the present what we think has happened in the past." Venkata P. Satagopam: "specimens are highly contaminated, ...." Mickey Kosloff: "mtDNA - advantage of many copies per cell" Shannon McWeeney: "original work from 1984 on egyptian mummy - http://..." arne: "Replacement (out of africa theory) vs assimilation (i.e. geneflow from modern humans)" Venkata P. Satagopam: "mtDNA is extracted from a specimen from neanderthal" arne: "Started with the original neanderthal specimen" arne: "The variation in human population origins before the split (as measured by mtDNA) of modern and neanderthals" Mickey Kosloff: "extract dna from skull, skip PCR and directly sequence" Shannon McWeeney: "only 3.5% actually from neanderthal genome" arne: "Average length 50 nucleotides" Venkata P. Satagopam: "Vindija Cave, Croatia .... 3 bones" Mickey Kosloff: "only about 3.5% of dna came from human" Shannon McWeeney: "3 billion fragments - again most from bacteria" Mickey Kosloff: "most dna is bacterial contaminants" Venkata P. Satagopam: "avg genome cover is 1.5X" Ted Laderas: "most DNA extracted is female look at Y chrom % as contaminant" arne: "Three females samples (and therefore Y chromosome contamination can be used to calculate noise). Total risk is below 1% risk of contaimination" Shannon McWeeney: "at any particular position - 1% chance contamination (broken down by source - 3 measures)" Mickey Kosloff: "consistant nucleotide chemical changes at 5' and 3' ends" Mickey Kosloff: "try to correct by alignments to human and chimpanzee genomes" Shannon McWeeney: "Details on bioinformatics and alignment issues (led by Ed Green) can be found in Science paper - http://..." Ted Laderas: "55% chance of seeing a position covered by at least 1 read" arne: "Divergence to human reference genome 12% highest among human is in San 10%" Shannon McWeeney: "typical european (French) 8% divergence to human reference compared with 12% in neanderthal" Venkata P. Satagopam: "78 amino acid substitutions ... a catalog of novel fixed features in the human genome" arne: "But this number will change" Shannon McWeeney: "novel fixed features in human genome - 78 aa substitutions (in paper) - now down to 50" arne: "Three out of six proteins with 2 changes are skin expressed" Mickey Kosloff: "next focused on SNPs" Shannon McWeeney: "detection of selective sweeps - look for snps in human, chimps, neanderthals - r egions where neanderthal looks all ancestral." Shannon McWeeney: "S vs cM plot - visual inspection for widest spread" arne: "Most extreme case in THADA, http://... Transport and diabeted related" Shannon McWeeney: "Thada is risk allele for type 2 diabetes - implications for metabolism" Shannon McWeeney: "detection of insertion in intron in Thada (not fixed in humans as initially thought in paper)" arne: "3-4% in europe has the neanderthal version (and are protected against Diabetes Type II)" Shannon McWeeney: "interesting follow-up research here - positive selection yet cost with risk allele" arne: "RUNX2: Mutations cause CCD (Cleidocranial dysplasia)" Shannon McWeeney: "annotation of others associated with autism and other diseases including CCD" Shannon McWeeney: "CCD of interest due to skull morphology phenotype" arne: "CCD: http://..." arne: "Now comes the most surprising result." Venkata P. Satagopam: "focusing on - Interbreeding with modern humans?" arne: "Work by Rasmus Nielsen http://..." arne: "Is Craig Venter a "fully modern human" ?" Shannon McWeeney: "analysis of self-identified neanderthals who write to Svante - predominantly men." Mickey Kosloff: "Comparisons to genomes of humans from different continents suggests interbreeding occured in middle east, before geographic expansion" arne: ":)" Venkata P. Satagopam: "45% men who are neandertals, 1% women are neandertals...." Mickey Kosloff: "future 10-20x coverage of genome" arne: "Future: (i) Better coverage (10-20x coverage) (ii) Functional analyses of candidate genes Exemplified by FoxP2 http://..." Venkata P. Satagopam: "next topic - functional analysis of genes - foxp2" arne: "FoxP2 is the same in human and neanderthal." Ted Laderas: "hope to identify backmutations in humans -cheaper to find these people because of low cost of sequencing" Mickey Kosloff: "easier to check phenotypes in mice" arne: "Human FoxP2 in mouse: The mouse can not speak ! Large scale phenotype study (323 phenotypic traits). -> More cautious in a novel area (stays close to the wall). No difference after 3 minutes. Second phenotype: Altered vocalization !!!" Venkata P. Satagopam: "323 phenotypic traits ... studied .." Venkata P. Satagopam: "movement more cautious in humanized mice" Venkata P. Satagopam: "next one is altered vocalization" Venkata P. Satagopam: "Enard et al Cell 2009" Mickey Kosloff: "mice with human foxp2 grew longer neurons" arne: "Other hominid forms........" arne: "Denisova individual 1 Myears (400 diffs in mtDNA)" Mickey Kosloff: "very good keynote" ISCB Senior Scientist Prize Lecture ![]() Memorial Sloan-Kettering Cancer Center
![]() ISMB2010 Blog Keynote: Chris Sander - Systems Biology of Cancer Cells arne, Mickey Kosloff, Saravanamuttu Gnaneshan, Iddo Friedberg, Venkata P. Satagopam and Roland Krause liked this ![]() Venkata P. Satagopam: "An interview with Chris Sander ... http://..." Shannon McWeeney: "Kabsch and Sander paper - over 6000 citations - http://..." Iddo Friedberg: "Note the subliminal message in the announcement slide" Shannon McWeeney: "Prediction by transparency - no computation necessary story" arne: "Awards should be shared: People working with Chris includes: Burkhard Rost, Alfonso Valencia, Liisa Holm and many more" Roland Krause: "Announcement of unpublished and new work. A good trend at this ISMB." arne: "Cancer genome atlas: TCGA" Roland Krause: "Mapping of molecular alterations (cpy number variation) to 200 glioblastoma samples. http://..." arne: "Difference between patients is huge" Roland Krause: "extract network, find relevant modules." Shannon McWeeney: "illustration of netbox algorithm" arne: "When grouping mutations into pathways up to 85% of GBM have a muation in the most important pathways, while individual genes are down to a few %" Barb Bryant: "Each oncogene may have relatively low frequency across patients; but when you group genes across pathways, a pathway may explain a large fraction of patients with a given type of cancer." Barb Bryant: ""Network pharmacology"" Mickey Kosloff: "can see a change in pathway activation between primary tumor and mets" Roland Krause: "Dominant alterations changes between cancer types and states." arne: "GBM: copy number is rare (and noisier) Ovarian: more regular and higher" Mickey Kosloff: "profiles of copy numbre variations differ between types of cancers" Barb Bryant: "Metastatic tumor samples have more copy number changes than primary tumors. Not surprising. But maybe primary samples with more copy number changes than others are more likely to metastasize? Generally, better outcome with fewer somatic copy number changes." Barb Bryant: "BRCA1 and BRCA2 mutations convey germline inherited cancer risk" Barb Bryant: "These genes act in the homologous repair pathway. Half of all patients have mutations in some homologous repair pathway gene." Mickey Kosloff: "and more generally, homologous repair genes are altered in > 50% of ovarian cancer" Barb Bryant: "Tumor suppressor genes can be inactivated in various ways: germline mutation, somatic mutation, epigenetic silencing, etc." Barb Bryant: "There are drugs under development that might work particularly well in patients with defects in this particular pathway." Barb Bryant: "Cancer genomics portal: www.cbio.mskcc.org/cancergenomics" Barb Bryant: "mutationassessor.org" Barb Bryant: "Topic shift: now, perturbation cell biology. "and belief propagation". (eh?)" arne: "Perturbation Cell Biology" Barb Bryant: "In recent past, says Chris, you make a few perturbations: overexpress or knock down a gene; inhibit with a compound, etc." Mickey Kosloff: "use network inference algorithms" Mickey Kosloff: "goal = predictive models for therapy" Mickey Kosloff: "with only 200 datapoints -> derive validated (known) pathways" arne: "Prediction of networks does not scale to larger networks" Roland Krause: "Large data generation with the number of pertubation > than proteins." Roland Krause: "Still prohibitively large number of networks even for small number of nodes." Barb Bryant: "Use statistical physics methods to tackle combinatorial explosion of possible networks." Roland Krause: "Inference using belief propagation known from statistical physics." Barb Bryant: "Ah, here is where "belief" comes in. Network inference using belief propagation. Reference Riccardo Zecchina et al. http://..." Barb Bryant: "Instead of going through all the models that are possible, you derive statistical properties across a set of good models for each of the Wij weights in the model." Barb Bryant: "This is sort of like partition functions in statistical physics" Shannon McWeeney: "evolving work on Wij (transition from Nelander et al 2008- http://..." Shannon McWeeney: "Cavity approach - optimize locally on global background iteratively cover all local cavities" Barb Bryant: "Mm, this is rather opaque to me." Barb Bryant: ""Let me give you some intuition about how this all works." Yes, I'd like that." Shannon McWeeney: "Nice results on toy experiment - constraints from 10 experiments with 5 interactions (the nodes W in factor graph)." arne: "Almost looks too good" Shannon McWeeney: "after step 1 - generation of probability distributions then step 2- decimation" Barb Bryant: "So you have a probability distribution for each Wij, which represents the interaction between element i and element j. I'm not really getting how you "update" these probability distributions in the iterative steps. I do understand that at the end you take the most "certain" (narrowest) distribution and fix its value (some Wij) at the most probable value, then update all the other Wij's given this fixation. And so on. To get your final model in a sort of greedy fashion." Barb Bryant: "And by the way, the underlying model is a simple differential equation sort of thing: change of one variable xi is a sigmoidal function of weighted (Wij) sum of all variables xj, less a decay term." Michael Jones: "thanks for the summary bb" Barb Bryant: "Mike!" Barb Bryant: "Mentions bunches of other stuff in passing. Like bioPAX: paper in press." Barb Bryant: "bioPAX is community project on pathways, ontology, and exchange format." Shannon McWeeney: ""no science without people; science for the people; ask good questions"" arne: "Biopax.org" arne: "Ask good questions !!!!!" Barb Bryant: "Question: Interacting network tend to be modular, with strongly-interacting subnetworks that interact weakly with each other. ..." Barb Bryant: "Chris: Is the modular approach really useful in confronting the data? [Is that what he said?]" Barb Bryant: "Question: can you get at causal relationships?" Barb Bryant: "Chris: yes - if the network model allows you to predict correctly the result of a particular perturbation applied to a particular node, then you can simulate using that model." Barb Bryant: "Question: with a big network, how many experiments will you need to model?" Barb Bryant: "Chris: Good question. Could use an entropy measure. Help us figure this out. Help us design the experiments. It's important because of the costs of experiment. This is going to be broadly applicable in cell biology." Shannon McWeeney: "bb - he said one should see if approach is useful by confronting with real data" Barb Bryant: "Ah, thx" Barb Bryant: "Chris gets at the difference between a model that tells a story and a model that is truly predictive." Barb Bryant: "Question: yes, but, what are the semantics of the graph? What kinds of interaction? Answer: The semantics are in the mathematics of your model." Barb Bryant: "Question: mean field approach is interesting. Compared to Monte Carlo approach, you are assuming some decoupling. Loss of posterior coupling between weights - is that an issue?" Barb Bryant: "Chris: If you look at a coupled system overall, the extent to which the algorithms work depends on correlations within the system. Long-range (in terms of network distance) correlations are problematic. There are some clever approaches to handle some of this. Mentions non-ergotic space; deal with parts of space separately or iteratively." ![]() (Photo by: Len Rubenstein) Harvard Medical School ![]() ISMB2010 Blog Keynote: David Altshuler - Genomic Variation and the Inherited Basis of Common Disease ![]() Dawei lin: "Altshuler is an expert on diabetes type II." Dawei lin: "It is said that he is also a good dancer." Ted Laderas: "Tap, ballroom, or tango?" Dawei lin: "Slide dancing" Dawei lin: "motivation is to understand genetic basis of human diseases" Venkata P. Satagopam: "Genetic basis of human diseases - important disease mechanisms and bio pathways remain unidentified" Dawei lin: "gap in knowledge of human disease biology contribute to high failure rates in drug development" arne: "Why understanding genetic mechanisms ? (1) Important mechanism remain unidentified (ii) Gaps in knowledge causes failure rate in drug development" Dawei lin: "It will be a long way to know if the two motivating hypotheses are true" Dawei lin: "one of the most research on T2D. It scaned 100k people for 10 yrs" Dawei lin: "10 years later 50% progressed to have the disease" Venkata P. Satagopam: "10years of diabetic research - the out come is - 50% of people with good lifestyle improved" Dawei lin: "lifestyle has a bigger impact than Metformin" Barb Bryant: "Diabetes study with 10-year follow-up of diabetes incidence and weight loss, "T2D". Randomized into treatments: lifestyle, metformin, placebo. Best drug makes relatively little difference in incidence; lifestyle intervention is better than drug but still doesn't help a whole lot." Mickey Kosloff: "best prevention was extensive lifestyle changes (50% -> 40% incidence)" arne: "Diabetes is not only a matter of life style" Venkata P. Satagopam: "success rate in current pharma industry is <5% of molecules entering the clinical trails" arne: "This is bad !!" Mickey Kosloff: "mentions well known number of >95% failure rate of new compounds" Dawei lin: "because there are still 40% people got the disease after the lifestyle change, it seems that people do not know the course of the disease" Venkata P. Satagopam: "a genetic approach - http://..." Dawei lin: "Genetic mapping started in 1913" Venkata P. Satagopam: "genetic map came in 1913" arne: "Morgan and Sturtevant 1913" Mickey Kosloff: "emphasizes he advocates a genetecist's approach (rather than a genomic approach)" arne: "And tells you to skip undergraduate work if you have something better to do" Venkata P. Satagopam: "key attributes of genetic mapping - unbiased by prior assumptions about pathways" Venkata P. Satagopam: "saturation mutagenesis reveals pathways" Dawei lin: "key attributes of genetic mapping: (1) unbiased by prior assumptions about pathways (2) saturation mutagenesis reveal pathways" Ted Laderas: "many mutants -> reveals coherence of pathways" Barb Bryant: "These days we have other methods that are unbiased like expression profiling, but genetic mapping has some unique characteristics relative to these (he’ll explain in a minute)." Dawei lin: "Drosophola's mutations looked initially random, years they almost all related to pathways." Ted Laderas: "bottleneck is functional determination - biochemical approaches" Dawei lin: "A lot of current knowledge can track back to genetic mapping" Venkata P. Satagopam: "Botstein and Fink Science 1988 ...." Dawei lin: "A slide based on Galzier et al, Science 2002" Venkata P. Satagopam: "genetic mapping of human single gene disorders ...over 15 years Botstein paper in 1980, first genetic map in 1985 ...." Dawei lin: "It took 10 year to find maker for Huntington disease" Barb Bryant: "Once you find a linked region from genetic mapping, it still takes a long time to find the specific gene responsible." arne: "in the 1990's the idea was that common diseases were caused by rare mutations with large effects" Roland Krause: ""Chromosome shlepping" - Eic Lander's term for the identification of a very gene in some genomic region." Dawei lin: "It is robust to find mendelian disease but to not common diseases" Ted Laderas: "another approach: population genetics - QTL approach" Dawei lin: "phenotypic variation is often continuous and may involve variation in many genes" Roland Krause: "Galton invented regression analysis to analyze the measuring of phenotypic data (heights of parents and offspring)." arne: "The biometric unit --- almost nothing was Mendelian" Ted Laderas: "Most traits are continuously variable" Barb Bryant: "Francis Galton was a cousin of Darwin. Darwin didn’t explain the source of variation. Galton focused on this; he measured the heights of parents and their offspring, and found a relationship. He invented regression analysis to draw the line. The slope of the line is related to the inheritability of the disease." Dawei lin: "It was studied by the cousin of Darwin, Francis Galton (1885)" Venkata P. Satagopam: "phenotypic variation is often continuous ... some history ... Francis Galton (1885), Ronald Fisher (1918), Hermann Muller (1920)" Barb Bryant: "This gave rise to the biometric movement – measure every living thing. Traits were related to genetic relatedness; and it wasn’t Mendelian. This led to the biometric-Mendelian debate." Dawei lin: "Ronald Fisher, was actually a geneticist, who also invented p-value and Fisher exact test" Roland Krause: "Ronald Fisher (the one with the exact test) was also a geneticist." arne: "Solved by assuming that phenotype often is an effect of several Mendelian genes." Ted Laderas: "Fisher: individual genes are mendelian, effects of genes additive" Barb Bryant: "Hermann Muller 1920 (Nobel Prize for X-ray induced mutations). PhD thesis not Mendelian trait, but truncate wing. Wasn’t Mendelian. Did genetic mapping." Dawei lin: "Hermann Muller decided to use broken wing of fruit fly to study non-Mendelian diseases" Barb Bryant: "Muller 1920 paper: 4 chromosomes in fly – 3 contain genes that influence the trait truncate wing. Muller wrote about implications for human traits, like psychological traits. Said that traits were going to be too complicated. Said you could figure out by looking at population, but not looking at Mendelian inheritance in families." Dawei lin: "Muller 1920 suggested that it needed to do study on a population." Ted Laderas: "Muller: Truncate wing - 3 genes influence effect of phenotype" Roland Krause: "Mullers thesis included the notion of surveying complex phenotypes in the population rather than families." Ted Laderas: "Muller: traits are too complex to observe in families, but can observe in population" Venkata P. Satagopam: "characterization and catalogue human seq variation is a decade of work .. i.e international HapMap project" Barb Bryant: "Another decade-long failure: the candidate gene approach. Instead, we need a genome-wide, unbiased approach." Dawei lin: "Testing candidate genes was not successful. Only 10-20 successes." Mickey Kosloff: "779 GWA published for 148 traits" Venkata P. Satagopam: "out come - 779 published GWA for 148 trails" Ted Laderas: "For common diseases, GWA was needed" Mickey Kosloff: "but "correlation does not imply causality"" Barb Bryant: "There have been 779 genome-wide association studies (or regions/genes found?) for 148 traits, with p < 5x10^-8" Venkata P. Satagopam: ""correlation does not imply causality" ...." Barb Bryant: "But correlation does not imply causality." Dawei lin: "The reasons of "Correlation does not imply causality": irreproducibility, lack of randomization, confounding, arrow of time." Barb Bryant: "If you can't randomize the experiment you can never prove causality as opposed to just being correlated to the underlying cause." Mickey Kosloff: "FF lag results in all these duplicate posts" Dawei lin: "a lot of efforts are on finding correlation between rare variation and diseases" Dawei lin: "rare variation is defined as has <5% in population" arne: "95% of variations is already present in the database" arne: "Identified 50 regions that are associated with T2D" Venkata P. Satagopam: "with in next few years ... the role of rare and less common variants will be characterized in a variety of diseases" Venkata P. Satagopam: "next topic - can we obtains new insights into the basis of disease?" Venkata P. Satagopam: "one example - sickle cell anemia" Venkata P. Satagopam: "Sankaran et al Science 2008" Venkata P. Satagopam: "Lettre et al PNAS 2008" Venkata P. Satagopam: "Uda et al PNAS 2008" Dawei lin: "Crohn's disease: 15 years, no idea what was happening. Now many genes and 3 pathways are identified to be relevant." Mickey Kosloff: "96 loci explain ~25% of cholesterol levels" Dawei lin: "Lipid GWAS found 60 loci that are previous unknown. Some of the positives are drug targets already." arne: "Global lipids consortium, forthcoming Nature paper (Nature paper is mentioned about 20 times !!!)" Ted Laderas: "is there a way to automate validation/function determination?" Venkata P. Satagopam: "prediction -- will prediction prove useful --this is depending on the clinical testing and the genetic test" Mickey Kosloff: "prediction will be useful when there's a proven intervention" Mickey Kosloff: "BRCA1/2 risk for cancer as an example" Venkata P. Satagopam: "seq tech will increase the reach of genetic methods" Ted Laderas: "mendelian fallacy - sub-populations are easily divisible in terms of risk" Roland Krause: "Prediction will only be useful if there is an intervention that you would not use without the prediction. Otherwise, you should use the intervention anyway." Mickey Kosloff: "Huntington will not be a representative example - for most diseases/people identified risk will be <<100% even with full genetic information" Mickey Kosloff: "Cautionary tale - PSA prediction results in over-treatment, hasn't been shown that people live longer because of test" Roland Krause: "Very cautious about PSA - no improvements on the mortality but many operations performed." Venkata P. Satagopam: "genetics offers a path to discover the underlying biology of human diseases ; the great value will drive from pathophysiology and treatment" ![]() Harvard Medical School and Broad Institute of Harvard and MIT
![]() ISMB2010 Blog Keynote: George Church - BI/O: Reading and Writing Genomes Samuli Eldfors, Ruchira S. Datta, Saravanamuttu Gnaneshan, Roland Krause, Mickey Kosloff and arne liked this ![]() Barb Bryant: "George Church has developed an amazing amount of technology." Dawei lin: "I am always wondering that if he gets any sleep at all." Dawei lin: "Which is the introducer?" arne: "michal linial, if I'm not wrong (which I was, need new glasses)" Shannon McWeeney: "The My First DNA sequencer reference: http://..." Dawei lin: "First challenge on computational interpretation and integration: personal genomes =stem cell epigenome + mC environments + traits." Barb Bryant: "Olga Troyanskaya" Barb Bryant: "Cost of drugs goes up linearly; cost of sequencing is dropping exponentially" Dawei lin: "40,000 fold price drop for 4 years" Dawei lin: "CGI price for genome is 00/year?" Barb Bryant: "In 2005 we abandoned a monopolistic capillary electrophoresis; instead we have a couple and now 21 different technologies for sequencing. Resulted in a jump in rate of change of sequencing capacity" arne: "He thinks that many of the sequencing companies will find a niche :)" Barb Bryant: "Cost of personal genome: 2007: M; 2009 00, for 40-fold coverage." arne: "Close to the 00 genome" Barb Bryant: "(+ 0,000 interpretation cost?) (he doesn't really think that)" Dawei lin: "Drmanac et al Science Jan 2010" arne: "Sidetrack: One friend said when he started his PhD it took 6 month to sequence a bacteria and 6-60 month to analyse it. Not it takes 6 minuted to sequence it and still 6-60 month to analyze it." Dawei lin: "limitation is several hundreds nm in scale on chip (positive charge molecules on hydrophobic background" Dawei lin: "7% human genome is missing so far because of technical challenges" Dawei lin: "trio genomics information (father, mother, child) is increasing important in genomics research" arne: "From open acess Sequences to Bio-Fab" Barb Bryant: "One of the 21 sequencing technologies is open-access. Reads and writes DNA with light." arne: "2nd-gen synthesis (0 per 15 Mbp)" Barb Bryant: "Second-generation synthesis - four different kinds of technologies." Dawei lin: "Next Gen synthesis: off chips 0 15Mbp" arne: "Tian et al 2004 Nature" Dawei lin: "The work started around 2003" arne: "personalgenomics.org" Dawei lin: "person genome 3M allele -> immunology + microbome -> trait" Barb Bryant: "Issues of personal identification from genomic data. Informed consent as one solution." Barb Bryant: "Have 16,000 volunteers for Personal Genome Project so far; 100,000 target." Barb Bryant: "Claims that ~1800 genes are highly predictive and medically actionable." Dawei lin: "They are rare but collective common at 10% level" Barb Bryant: "Example of the Madsen family with two diseases. Found causative allelles - 4 total (2 from each parent)." Dawei lin: "evidence.personalgenomics.org" Barb Bryant: "Each time we find a scary allele in a person, it could be a sequencing error; it could be a problem with the literature." Dawei lin: "found a dozen cases in the literature got allele sequence wrong" Dawei lin: "The oldest volunteer for PGP is 96.7 years old" arne: "Q: Are these genomes available ?" Barb Bryant: "Circulating tumor, pathogen, fetal, and immune cells." arne: "Microbe vs Immunome" Barb Bryant: "If you want to look for a microorganism in a body, you can either look directly for the microbe, or look for the body's reaction." Dawei lin: "immune test is to focus on response to exposure." arne: "Sequencing after vaccination - response is maximum after 7 days" Barb Bryant: "Generating human tissue from pluripotent stem cells" Dawei lin: "The Economist 20-May-2010 cover" Barb Bryant: "Genome engineering" Barb Bryant: "E.g., change the genetic code -- for resistance to pathogens, new amino acids, and something else." Barb Bryant: "You have to do this safely." Barb Bryant: "For 0M, Dupont made 27 changes to the 4.6 Mbp E. coli, to make a chemical." Barb Bryant: "Another application: bio-petroleum from microbes." Barb Bryant: "Identify enzymes that synthesize alkane. Many cyanobacteria made trace amounts; others made none. Did genome sequence "subtraction" to find which genes were in the former. Isolated & tested these genes. Overproduced them; it worked. Green chemistry." Barb Bryant: "Multiplex Automated Genome Engineering (MAGE)..." Christiaan Klijn: "Church's own genome is available: http://..." Barb Bryant: "So: subtract my genome from Church's, then overproduce those genes --> TOTAL BRILLIANCE!" Barb Bryant: "Example of freeing up a codon by changing those codons to a different one./" arne: "Is this not just the analysis. Not the sequence ? (or did I miss a link)" Christiaan Klijn: "See the 'Datasets' header -> you can get 500k Affy data as well as exome" Barb Bryant: "Metabolic engineering example. Historically, you'd get obsessed with one step in the pathway and overproduce one enzyme. But then you'd get product inhibition, or the product might be toxic." arne: "Would be nice with a map to the reference genome as well, but guess that can be done" arne: "DNA Nanostructures: (DNA origami). Proposes a combination of DNA and proteins." Barb Bryant: "DNA nanostructures help solve structures of membrane proteins." arne: "First practical application: Made a long rod that was stiffer than other DNA. Used in NMR for membrane proteins (Cooooll idea but, it has been tried with proteins before)" Dawei lin: "caDNAno is a software tool that is free available" arne: "Time for questions." ![]() Whitehead Institute for Biomedical Research
![]() ISMB2010 Blog Special Public Lecture: Dr. Robert Weinberg - Cancer Stem Cells and the Evolution of Malignancy ![]() Barb Bryant: "Shows picture of stages of cancer progression (ref Vogelstein, colon); poses the question of how metastasis occurs -- does this involve genetic or epigenetic changes?" Barb Bryant: "Tan Ince cultured two kinds of normal human mammary epithelial cells. He transformed them with oncogenes, resulting in different types of tumors." Barb Bryant: "Concludes that the nature of the normal cell of origin is a strong determinant of the phenotype of the primary tumor, and whether it metastasizes. The playing field is tilted in the beginning." Barb Bryant: "Posits tumor-generating cells." Barb Bryant: "Self-renewing stem cells produce either more stem cells or transit amplifying cells which in turn lead to post-mitotic differentiated cells. Only the self-renewing stem cell could seed a new tumor." Barb Bryant: "invasion-metastasis cascade" Barb Bryant: "How do cancer cells acquire all of these capabilities (invasion, intravasastion, transport, metastasis...) Are there addiitonal mutations required? Is it epigenetic?" Barb Bryant: "epithelial-mesenchymal transition -- cells on the perimeter of the tumor are mesenchymal. This may be due to signals from the surrounding stroma." Barb Bryant: "There are probably 1000 proteins that shift in EMT. Vaious transcription factors (TFs) induce EMTs." Mickey Kosloff: "EMT program highly complex and occurs normally during development." Barb Bryant: "It seems likely that most of the invasion-metastasis program can happen without need for additional mutations; rather use signaling from microenvironment." Barb Bryant: "P. Gupta transformed human primary melanocytes (pigmentation in the skin) with a cocktail of oncogenes. Found that in contrast to transformed epithelial cells, there was much higher likelihood of metastasis. Again, cell of origin is important in future behavior." Barb Bryant: "One TF, Slug, was found to enable melanoma metastasis. (Even though the primary tumors grew a little faster.)" Barb Bryant: "Another TF, FOXC2, when expressed in epithelial cells induces migration and invasion. A subset of breast cancers have high levels of nuclear FOXC2, and these are more aggressive breast cancers." Barb Bryant: "Speculates that different networks of EMT-inducing factors might program metastasis in different cell types./" Barb Bryant: "Stem cells identified by high CD44 and low CD24. (CD's are markers on cell surface which can be assayed fairly easily.)" Barb Bryant: "There are various ways to make cells acquire stem cell characteristics." Barb Bryant: "Mentions Kornelia Polyak. There are stem-like cells in primary human breast samples. The stem cell program in normal human mammary gland is coopted by cancer cells." Barb Bryant: "More proof that EMT creates stem cells." Barb Bryant: "Most current chemotherapies preferentially kill non-cancer-stem-cells. The remaining stem cells can repopulate the tumor and are often more resistant to therapies." Barb Bryant: "Gupta & Onder tested CSCs and non_CSCs with a bunch of drugs. There are some CSC-targeted agents (Salinomycin, Abamectin). Of 16,000 compounds only about a dozen preferentially killed CSCs as opposed to non_CSCs. Many were the other way round." Barb Bryant: "This probably won't be the "answer". Christine Chaffer noticed that there were some floating cells in 2D cultured human mammary epithelial cells. She grew these up; these look more like CSCs." Barb Bryant: "Interestingly, she found that non-CSCs could generate CSCs." Barb Bryant: "Hm, isn't this kind of pouring cold water on the excitement about CSCs as drug targets? Or maybe you have to target both CSCs and non-CSCs simultaneously." Barb Bryant: "yup" Barb Bryant: "Q: cancer biologists like to study druggable genome. But transcription factors seem most important. A: expression of TFs is controlled by cytoplasmic factors. Might want to go after those. Drugging the TF itself might be hard, but the signaling pathways might be more druggable." Barb Bryant: "Q: has it been shown that change in the two forms of cadherins match the change in CD expression, and are these correlated with morphology? A: I showed that: CD44 high cells shut down E-cadherin; they expression vimentin, and other mesenchymal markers. I don't know whether CD44 is useful for non-mammary epithelial tissues." Barb Bryant: "Q: So do normal non-SCs generate SCs? A: Yes. Same differences as in cancer." Steve Chervitz Trutane: "Spontaneous de-differentiation into SCs. Interesting phenomenon." |
Venkata P. Satagopam: "ISMB2010 just kicked off"
Venkata P. Satagopam: "Prof Søren Brunak introducing Steven Brenner, ISCB overton prize winner"
Roland Krause: "Brenner contributed to many fields in bioinformations, starting in structureal biology ober RNA to metagenomics."
Roland Krause: "A short biography, summarizing Soren Brunaks kind introduction http://..."
Shannon McWeeney: "The morphology of steves paper: http://..."
Roland Krause: "Intro: The ultraconservative (as seen from Berkely) and nonsense (as found in Through the Looking Glass"
Roland Krause: "The jabberwocky poem does have meanings and is elegantly crafted."
Roland Krause: "Generally, nonsens in biology is bad."
Venkata P. Satagopam: "Nonsense is generally bad, even in a codon"
Roland Krause: "Truncated proteins might interfere with physiological function (dominant negative). The cell removes such transcripts through nonsense-mediated decay (NMD)."
Roland Krause: "Good example for NMD: Sox10"
Roland Krause: "Mutations early in the gene leads to less severe phenotypes than later ones"
Venkata P. Satagopam: "NMD is an mRNA surveillance system"
Roland Krause: "NMD important to development of the immunesystem and cleans up other transcriptional errors."
Roland Krause: "We do not know how NMD works outside the mammals."
Roland Krause: "The mechanism involves the splicing machinery. If a stop is found wwithin 50nt upstream of the exon junction complex, it is removed.."
Venkata P. Satagopam: "50 nucleotide rule - translated normally or degraded by NMD"
Shannon McWeeney: "brilliant nytimes article title - surviving on low number of genes"
Venkata P. Satagopam: "splicing can introduce PTC - premature termination codon"
Shannon McWeeney: "AS as mechanism to introduce PTCs - can lead to unproductive splicing"
Venkata P. Satagopam: "these isoforms often have PTC"
John Greene: "Humans have fewer genes but better genes, due to AS."
Venkata P. Satagopam: "Are PTC splice forms funcitonal?"
Venkata P. Satagopam: "Many PTC mRNAs are noise"
Shannon McWeeney: "analgous mechanism to shrinter: http://..."
John Greene: "Humans have fewer genes but better genes, due to AS."
Shannon McWeeney: "Related reference: http://..."
Venkata P. Satagopam: "Alt splicing can yield isoforms differentially subjected to NMD"
Venkata P. Satagopam: "SR protein - 11 in human which are serine and arginine rich"
Roland Krause: "SR proteins have premature stop codons."
Venkata P. Satagopam: "SR genes has mRNAs with premature termination codons"
Ted Laderas: "AS of PTC isoforms is mechanism for autoregulation of proteins"
Venkata P. Satagopam: "NMD has a large effect on isoform abundance"
Shannon McWeeney: "NMD has impact on isoform abundance - example of NMD clearing the major isoform"
Shannon McWeeney: "minor isoforms are only shared 25% of time - modrek and lee 2003"
Roland Krause: "Not just anecdotal stories, splice patterns are conserved in mouse, implying functional significance."
Roland Krause: "(Unpulbished work)"
Venkata P. Satagopam: "All the SR proteins are talking to each other"
Ted Laderas: "SR proteins 'compensate' for each other via coupling via AS and NMD"
Venkata P. Satagopam: "SR genes have ultraconversed elements .. Bejerano et al 2004 Science 304: 1321"
Roland Krause: "Most ultraconserved regions are in intergenic regions, the regions in SR within genes."
Shannon McWeeney: "question of why conserved - not protein coding, no obvious significant RNA secondary structure"
Roland Krause: "No proteins are produced from these genes."
Venkata P. Satagopam: "The reason why SR sequences are highly conserved - most of the seq are not protein coding,"
Venkata P. Satagopam: "no repetitive elements"
Shannon McWeeney: "why conserved part 2 - no overrepresentation of binding / regulatory elements"
Roland Krause: "No simple explanations e.g. from miRNA binding etc."
Venkata P. Satagopam: "no similarity elsewhere in genome except retropseudogenes"
Shannon McWeeney: "analysis on origin of unproductive splicing"
Roland Krause: "No sequence similarity between the conserved elements. Seems to have been introduced mutliple times."
Venkata P. Satagopam: "mouse and human SRp55 conserved but changing"
Venkata P. Satagopam: "working on chordate SR proteins"
Venkata P. Satagopam: "here intron and exon structure is more informative"
Shannon McWeeney: "at this point - he has requested no further blogging - unpublished work"
Burkhard Rost: "no blog slides may be over"
Roland Krause: "# Looks like interesting work."
Shannon McWeeney: "wonderful talk"
Roland Krause: "Tells a (hard to blog) story about the successful treatment of collaborator with novel treatment based on genotyping."
John Greene: "Wow - what a conclusion! Fantatic talk..."
Roland Krause: "# Certainly great work. The talk was nice too, and he only bitched at other reseachers in person once, another step up."
Saravanamuttu Gnaneshan: ""Ultraconversed elements in SR genes ONLY show similarity to retropseudogenes" - what does this mean? Any takers?"