brendan loftus genomics - etsi
TRANSCRIPT
Genomics• Sequencing: the data deluge• Dynamic genome vs static genome• Increase in the diversity of uses of genomic data• Foundational technology for new science • synthetic genomics and the engineering of
biologybiology
Genome I: DNA sequencing data deluge
2006-2011
2011-2015$30K Human genome
< $1K Human genome1-10Tb storage per run
10-100Tb storage per run
$3B Human genome
1998-2007
1-10Gb storage per run
- Traditionally genomic data has been stored and acc essed through a centralized repository (NCBI)
- Researchers may have to store their own data local ly in future
-As research becomes increasingly data centric there will be a requirement for structured comparison with other av ailable data on a continuous basis.. ..
Implications of data driven/data centric genomics r esearch
continuous basis.. ..
? Closed communities of users with different access privileges ?
? Reduction in complexity of search parameters …Data cubes ?..Software agents ?
Genome related information for the general user-as consumer product ?
Once the cost of comes within easy reach of individuals they can initiate its production and it s uses thus altering many of the privacy issuesuses thus altering many of the privacy issues
When in control, more likely to share it/take part in studies (drug company/social/geneological etc)
This requires a new way to present, handle and interrogate personal genome information
ENCODE: Encyclopedia of functional elements within the human genome
1) Pervasive transcription
Genome II Qualitatively different
1) Pervasive transcription2) Fewer boundaries3) More control elements4) Genome partitioned into discreet functional territories that repress or activate transcription
Genome II: The gene: Qualitatively different
Transcriptional complexity of a gene
Gingeras T. R. Genome Res. 2007;17:682-690
©2007 by Cold Spring Harbor Laboratory Press
Genome III: Epigenetics and the Genome III: Epigenetics and the “Histone code”“Histone code”
Epigenome is Dynamic-
Influenced by environmental and social forces
Associated with increasing Associated with increasing numbers of developmental
states and diseases
A model of “Lineage Choice” from a epigenetic perspe ctive
Lineage choice involves coordinated activation and
repression of blocks of genes
Your genome cant be altered but your epigenome can
Implications of a life-long dynamic epigenome?
chemical social
Signaling pathways
Epigenome
The abstraction of the Genome as linear string of DNA is now outdated and needs to be replaced with something richer to capture some of the topology and its systems dynamics
phenotype
William Sellers (1824-1905)
Biology has as a engineered technology has few standards
To deploy Biology as a constructive technology standards will be essential
Genome IV: Synthetic Biology
It is highly likely many organisms of the future whether evolving or not will come from the design
of engineers/scientists
The process will become an essential part of the outcome
Features of Synthetic Biology
Traditional techniques in genetic engineering have underpinned modern molecular biology (PCR/Recombinant DNA/cloning)
To this now can be added-Automated construction (synthesis) of DNA-Automated construction (synthesis) of DNA
- Introduction of standards underpinning their use
- Design of more complex systems other than what exists in nature will require abstraction of some o f the complexity to allow for improved design
Genomics coupled with DNA synthesis: allows for the seamless linking of information and material
Some initiatives in Synthetic BiologyTop-down and Bottom up approaches
Creation of first free-living synthetic genome (mycoplasma (2008))
The MIT Registry of Standard Biological Parts (BioBricks)(protein generators/regulators/receivers and senders/measurement devices/reporters)
The international Genetically Engineered Machine competition
Summary
- The human Genome led to the parts list
-The capacity to measure its changes in a dynamic way presents new challenges for researchers and industry alike
-Its likely that genomic related data will be collec ted and monitored for a large number of Biological systems (e.g. humans) in the future
- We are moving from observing the Genome and trying to predict its effects on Biological systems towards learning to utilize it as a technology
FIN