Application of Sequencing Technology and Bioinformatics to Phytomedicine
16
©Eagle Genomics Ltd PAG-ICPN | San Diego 15 th January 2013 Application of sequencing technology and bioinformatics to phytomedicine William Spooner, CTO and Founder, Eagle Genomics ©Eagle Genomics Ltd
-
Upload
eagle-genomics-ltd -
Category
Documents
-
view
554 -
download
0
description
Phytomedicine is well-suited to being studied using the next generation DNA sequencing technologies (NGS) that have revolutionised molecular biology over the past 5 years. This is true both from the angle of lead discovery/optimisation, and also target discovery/mode of action. Starting with the search for lead candidates, bioactive molecules from plants are effectively proteins/metabolites, and, given a reference sequence, can be traced back to their genomic origins. Significantly, phytomedicinal traits can be selected for like any other plant phenotype. There are already phytomedicinal plants such as Cannabis with sequenced genomes that are being investigated in this way, and there are tens if not hundreds of species whose genomes would be similarly useful. The study of phytopharmacology is similar in many respects to that of 'standard' pharmacology, and is tractable via the same genomic techniques. A notable exception to this concerns the synergistic interactions that can be pronounced in plant extracts, meaning that a single isolated ingredient will not always reproduce efficacy of the plant extract. Although the biological explanation of synergistic effects is far from clear, unbiased whole genome assays typified by NGS provide a promising approach to their study.
Transcript of Application of Sequencing Technology and Bioinformatics to Phytomedicine
©Eagle Genomics Ltd
PAG-ICPN | San Diego 15th January 2013
Application of sequencing technology and bioinformatics to phytomedicine
William Spooner, CTO and Founder, Eagle Genomics
©Eagle Genomics Ltd
©Eagle Genomics Ltd Molecular Psychiatry advance online publication 30 August 2011; doi:10.1038/mp.2011.101
Genes
Image: Sartr http://sartr.deviantart.com/gallery/?offset=96#/d1u0z75 CC BY-NC-ND 3.0
Ph
en
oty
pe A
ssocia
tion
Genome
©Eagle Genomics Ltd
Genomics in research productivity
Reactome axon guidance pathway – highlighting NRCAM interactions
Synergy in phytopharmacology
2 + 2 = more
©Eagle Genomics Ltd
Genomics in pharmacology
Stratified Medicine
Right drug
Right patient
Right time
Pharmacogenomics
Genotypic
Transcriptomic
Epigenetic
©
Ph
enoty
pic
ass
oci
ati
on
Valid
ate
d b
iom
ark
er
Clin
ical ass
ay
©Eagle Genomics Ltd PAG-IPCN | San Diego 615th January 2013
Genomics in plant breedingGermplasm/Pedigree
Phenotype/Genotype association
Phenotype Genotype
Genotyping
Phenotyping
Assays
Breeding
Phytomedical traits
Image By: G. Nicolella http://luirig.altervista.org/cpm/albums/bot-002/normal_medicago-truncatula3637.jpg CC BY SA
©Eagle Genomics Ltd PAG-IPCN | San Diego
Association mapping workflow – DNA-SeqBiomarker discovery from DNA-Seq• End-to-end workflow• Species without a
reference genome.
15th January 2013 8
DNA-Seq (samples)
Reference genome
Build phylogenies
Assemble genome
Associate traits (GWAS)
Reference genome
Variants
Annotated variants
Biomarkers
INPUTS OUTPUTS
End Intermediate Data
ActivityInput Data/output report
Predict genesPublic EST/Protein
Call variants (alignment)
Annotate genes
Annotate variants
StartKEY
Output from one activity that forms input for a subsequent activity
Reference
Gene models
Orthologs/paralogsGene models
Ref genes (other species)
Annotated genes (e.g. GO)Orthologs/paralogs
Sample metadata
Variants
Annotated genes
DNA-Seq (samples)
Ref annot. (other species)
Reference genome
Annotated variants
Association
Ensembl as a GCMS
Comparative Genomics
Regulatory Genomics
Variation
Assembly/GenesData Integration
Data Reporting
Data Analysis
Data Integration
Data Querying
Data QC
API
DAS
Data management platform
httpd
UCSC Data Hub
Aquilegia coerulea
Sequenced phytomedicinal plants
Cannabis sativa
Theobroma cacao Ricinus communis
Image By: Actv [CC] Image By: Eric Lyons
Image By: Kai Yan, Joseph Wong [CC] Image By: Howard F. Schwartzs [CC]
©Eagle Genomics Ltd PAG-IPCN | San Diego
Association mapping workflow - RNA-SeqBiomarker discovery from DNA-Seq• End-to-end workflow• Species with or without
reference transcriptome
15th January 2013 11
INPUTS OUTPUTS
End Intermediate Data
ActivityInput Data/output reportStartKEY
Output from one activity that forms input for a subsequent activity
Reference
Association
RNA-Seq (samples)
Transcript assemblies
Transcript assemblies
Variants
BiomarkersSample metadata
RNA-Seq (samples)
Variants
Assemble transcriptome
Associate traits (GWAS)
Call variants(alignment)
PAG-IPCN | San Diego
15th January 2013 12
SNPs associated with Glucosinolate content in Rapeseed
High-density genetic maps
QTL Mapping
Harper et. al. Nature Biotechnology 30, 798–802 (2012)Trick et. al. Plant Biotechnol J., 7, 334-46 (2009)
PAG-IPCN | San Diego 1315th January 2013
Atropa belladonna
Camptotheca acuminata
Cannabis sativa
Catharanthus roseus
Digitalis purpurea
Dioscorea villosa
Echinacea purpurea
Ginkgo biloba
Hoodia gordonii
Hypericum perforatum
Panax quinquefoli
us
Rauvolfia serpentina
Rosmarinus officinalis
©Eagle Genomics Ltd PAG-IPCN | San Diego 14
Sequencing and bioinformatics have ready applications to phytomedicine R&D.
• Human: Improve understanding mode of action of bioactive plant compounds.
• Plant: Mapping of phytomedicinally-important traits for use in breeding.– DNA-Seq vs. reference genome is gold standard.– RNA-Seq with or without reference transcriptome is still useful.
• Future:– Increasing standardisation of NGS workflows.– Increasing quality of software platforms.– Growing number of public genome and transcriptome reference
resources.
15th January 2013
©Eagle Genomics Ltd
14/01/2013 15
[email protected] +44 (0)1223 654481www.eaglegenomics.com
facebook.com/eaglegenomics blog.eaglegenomics.com@wspoonr@eaglegen
©Eagle Genomics Ltd
