Aim M IAM E/Env aim s to define a set of guidelines for the capture and exchange of microarray data, common to most environm entalgenom ic experim ents. Motivation Environm ental genom ics is a diverse, heterogeneous discipline, often involving multi-factorial experiments that can have an alm ostinfinite num ber ofexperim entalparameters. Data of this nature is inherently more complex than that generated by other disciplines. The NaturalEnvironm entResearch Council [1] (NERC) has m ade a com m itm ent to m aking M IAM E com pliance a de-facto standard w ithin the Environm entalGenom ics Science Program m e. M IAM E/Env – Background MIAME/Env defines a set of common categories typically used in conjunction to describe an environm entalgenom ics experim ent: W ild / Laboratory O rganism s N atural/ Controlled Environm ent Com m unities / Populations / Individuals Pre-conditioning / Conditioning For exam ple, three frequently occuring types of experim ental design are defined below : Field Trials – Experim ents in w hich a w ild organism /biosource is taken directly from the natural environment, samples and extracts are prepared and the hybridisations then perform ed. Conditioned field trials – Experiments in which a wild organism /biosource is taken from the naturalenvironm ent and conditioned in the lab under specified animal husbandry conditions (preconditioning) and w here “treatm ents” (conditioning) m ay be performed pre- or post-sample/extract preparation Lab experim ents – Experim ents in which an organism /biosource is lab reared or obtained from a standard provider and where “treatments” (conditioning) are usually perform ed pre-orpost-sam ple/extractpreparation. M IAM E/Env – O verview M IAM E/Env is based on the M IAM E/Tox [2] draft proposed by the EM BL-EBI, NIEHS NationalCenterfor Toxicogenom ics (NCT) and ILSI-H ESI. As w ith M IAM E [3] and M IAM E/Tox,M IAM E/Env has tw o m ajorsections: A rray design description. This section remains virtually identicalto the M IAM E and M IAM E/Tox docum ents. Experim ent description. The m ajor changes to this section are detailed below . Note: The focus of examples presented here is on those from environmental genomics. However, they are not intended to be fully com prehensive. Authors are encouraged to refer to the M GED ontology for a m ore exhaustive listw hen providing specific instances. Experim entdescription This section is com m on to allhybridizations perform ed in the environm ental genomic experiment, such as the goal, brief description, experimental factors tested. Authors,laboratory,contact Type ofthe experim ent.For instance: o challenged vs.unchallenged o geographicallocation com parison o fitness o competition o lab vs.field com parison o strain/line or ecotype com parison Experim entalfactors,Forinstance: o Species,strain,ecotype o M orphology,behaviour,fitness o Housing,feeding regim e,native location o Treatm ent,dose,vehicle Biologicalm aterials used,extractpreparation and labelling B iosource properties This section is especially im portant for experim ents such as field studies w here an organism is taken directly from the “w ild” for experim entation. In this case as much detail as possible should be provided in the sample source location and environm entalhistory sections: O rganism (NCBI taxonom y, if know n. W here the identity of the organism is unknown or a m ixed population is under study a unique identifierplus description should be provided.) Sam ple source provider Sam ple source location (If the biologicalm aterialis taken from the “wild”, a GPS coordinate and associated time stamp, to indicate w here and w hen the organism w as harvested, should be provided. For som e sam ples a m ore detailed topography m ay also be necessary) Environmental history, if know n. Inform ation on the environmental history of the biosource prior to sample m anipulation. Potentially, including growth conditions and any pertinentenvironm entalparam eters. Descriptors relevant to the particular sam ple (if know n). For instance: o sex o age o w eights o m orphology (size,colouretc) o organism behaviouralcharacteristics o fitness o development stage (of the organism or the host organism ) o anim al/plantstrain,line orecotype o genetic variation (e.g., gene knockout, transgenic variation) o individual genetic characteristics (e.g., disease alleles, polym orphism s) o disease state ornorm al o an individual identifier (for interrelation of the biological m aterials in the experim ent) Sample m anipulations: laboratory protocols and relevant param eters. Pre-conditioning This section attempts to capture the animal husbandry or cell culture conditions thatare com m on to allsam ples w ithin the experim ent. For field studies this m ay be irrelevantorsparsely populated. O rganism husbandry and housing details or cell culture conditions.Forexam ple: o Housing details o Feeding/cleaning regim e o Grow th conditions o Pre-Conditioning period (i.e.length oftim e) Conditioning (Eitherfield orlab based). M IAM E/Env classifies any change to the anim alhusbandry regim e detailed above as a treatm ent or conditioning. W here conditioning is perform ed in uncontrolled “field” environm ents, details of the environm entalparam eters found atthe conditioning site should be recorded in a sim ilar fashion to the environm entalhistory captured in biosource properties (section 2.1) Exposure to chem icalstressors.For exam ple: o Complex mixtures. Such as: Environmental Air / W ater Sam ples. o Compound / Small molecule. Including information on: Treatm ent com pound nam e, Type of com pound, CASRN, dose (and unit). Exposure to physicalstressors.For exam ple: o Electrom agnetic radiation. Including information on: Type,W avelength,Duration,Intensity. o Pressure (including depth orheight) o Heat / Cold – shock. Including inform ation on: Duration, Tem perature. Exposure to biologicalstressors.Forexam ple: o Parasitic infection o Introduction ofcom peting organism /s Perturbation.Forexam ple,changes to: o Housing and oranim alhusbandry o O rganism density o Circadian-rhythm icity o Tidal-cycle Sample Processing Separation technique: O f tissues or cells from a heterogeneous sample. Or of a specific organism sub-sam ple from a m ixed population.For exam ple: o For tissues and cells: trim ming, m icrodissection, FACS, other(including description/protocol) o For populations: size exclusion, centrifugation, manual separation (including description/protocol) M ethod ofsacrifice.Including inform ation on: o Date,time M aking use ofM IAM E/Env The NERC – Environm entalGenom ics Them atic Program m e Data Centre [4] (EGTDC) is committed to delivering a combination of open-source and com m ercialbioinform atics packages to EG aw ardees. It does this through B io-Linux,an integrated,bioinform atics-centred,com putersystem . PEDRo Available as a stand-alone package or as part of the Bio-Linux system, PEDRo [6] is an application that produces data entry form s for a data m odel specified in a particularstyle ofXM L-Schem a. An XM L based M IAM E/Env m odel is currently under developmentfor use w ith PED Ro. Makes full use of PED R O ’s ability to integrate w ith m ultiple ontology services,such as the M G ED ontology [5] . Som e ofthe benefits ofusing PEDRo are: Itis an XM L editor thatchanges its data entry form s in response to changes in a data m odel. Domain independence; PEDRo doesn't care if your model is aboutim m unology,proteom ics,botany or yourrecord collection. The application is FREE and open-source in accordance w ith a generous license. References [1] NERC – http://www .nerc.ac.uk [2] MIAME/Tox – http://w ww .m ged.org/M IAM E1.1-DenverDraft.doc [3] MIAME – http://w ww.m ged.org/W orkgroups/MIAME/m iam e_1.1.htm l [4] EDTDC – http://envgen.nox.ac.uk [5] MGED Society:O ntology – http://w w w .m ged.org/ontology [6] PEDRo – http://pedro.m an.ac.uk MIAME/Env MIAME/Env Minimum Information About a Microarray Experiment – MIAME for Environmental Minimum Information About a Microarray Experiment – MIAME for Environmental Genomics Genomics Norman Morrison, Luke Hakes, Andy Brass, Andrew Cossins, Dawn Field, Kevin Garwood, Andy Hayes, Matthew Hegarty, Peter Kille, Karim Nashar, Helen Parkinson, Susanna Sansonne, Robert Stevens, Bela Tiwari, Mike Waters, Joe Wood, Jason Snape. All members of the MIAME/Env Working Group – See: http://envgen.nox.ac.uk Bio-Linux. Bio-Linux. By By providing both providing both standard standard favourite and favourite and cutting edge cutting edge bioinformatics bioinformatics tools on a Linux- tools on a Linux- based system, it based system, it combines the combines the benefits of being benefits of being powerful, powerful, configurable, and configurable, and easily easily updateable, with updateable, with the ease of use the ease of use and potential for and potential for software software integration integration required for the required for the handling and handling and analysis of analysis of biological data biological data being produced by being produced by EG-funded labs EG-funded labs PEDRo. PEDRo. Making Making use of PEDRos use of PEDRos ability to ability to integrate with integrate with multiple ontology multiple ontology services. services. Here the Here the experiment type experiment type field can be seen field can be seen anchored to the anchored to the appropriate appropriate section in the section in the MGED ontology. MGED ontology. For further information and to keep up to date with current developments, please visit the MIAME/Env For further information and to keep up to date with current developments, please visit the MIAME/Env website: http://envgen.nox.ac.uk website: http://envgen.nox.ac.uk