A novel methodology named terminal continuation (TC) RNA amplification has been developed to amplify RNA from minute amounts of starting material. Utility of the TC RNA amplification method is demonstrated with two new modifications including obviating the need for second strand synthesis, and purifying the amplification template using column filtration prior to in vitro transcription (IVT). Using four low concentrations of RNA extracted from mouse brain , one round TC RNA amplification was compared to one round amplified antisense RNA (aRNA) in conjunction with column filtration and drop dialysis purification. The TC RNA amplification without second strand synthesis performed extremely well on custom-designed cDNA array platforms, and column filtration was found to provide higher positive detection of individual clones when hybridization signal intensity was subtracted from corresponding negative control hybridization signal levels. Results indicate that TC RNA amplification without second strand synthesis, in conjunction with column filtration, is an excellent method for RNA amplification from extremely small amounts of input RNA from mouse brain and postmortem human brain, and is compatible with microaspiration strategies and subsequent microarray analysis. A disadvantage of conventional microarray technology is a requirement for significant amounts of high quality input sources of RNA for sensitivity and reproducibility. The quantity of RNA harvested from a single cell, estimated to be approximately 0.1–1.0 picograms, is not enough to employ standard RNA extraction procedures . Therefoon (IVT) –6, althoon (IVT) , 8 as weon (IVT) , 10 procA well known linear amplification method, amplified antisense RNA (aRNA) amplification , 3, 5, eA variety of strategies have been developed to improve RNA amplification efficiency , 11–13. A modification of the TC RNA amplification procedure is presented that allows for robust RNA amplification without the need for second strand synthesis using mouse brain tissue . FurtherUtilizing one round TC RNA amplification without second strand synthesis and aRNA amplification, signal intensity of 576 cDNAs corresponding to genes of interest for our research program was compared and contrasted on a custom-designed array platform with a gradient from 1 ng to 50 ng of input RNA from mouse brain. In addition, two different purification methods  were evaluated in conjunction with the aforementioned RNA amplification procedures.A comparison of the RNA amplification methods indicates that the TC RNA amplification procedure without second strand synthesis generated robust hybridization signal intensity that did not differ significantly from the TC RNA amplification with second strand synthesis. A histogram  indicateIn contrast, aRNA amplification on the identical mouse brain samples yielded a significantly lower total hybridization signal intensity result than either TC RNA amplification protocol (p < 0.0001). Moreover, the TC RNA amplification procedure produced an exponentially higher hybridization signal intensity for each individual cDNAs/ESTs examined when compared to the aRNA method starting from mouse brain RNA extracts of 1 ng, 10 ng, 25 ng, and 50 ng. Representative identical portions of membrane arrays are presented for aRNA with 1 ng , 10 ng , 25 ng , and 50 Similar results were generated comparing aRNA with the TC RNA amplification method using the column purification method . Specifi8 – 3.5 × 108) compared to the column filtration method (5 × 107 – 8 × 107). Interestingly, hybridization signal intensity increased with decreasing amounts of input RNA for the drop dialysis method  and related tissue microdissection technologies. Both of these RNA amplification methods use a linear amplification procedure based on generating a cDNA hybrid with a bacteriophage transcription promoter, which is subsequently used for IVT. However, the aRNA amplification method utilizes a T7 promoter linked to a poly d(T) primer, whereas the TC RNA amplification procedure has the ability to generate sense and antisense amplified RNA by enabling the T7 promoter sequence to be attached to either the 5’ or 3’ primers used in the amplification scheme .TC RNA amplification and aRNA have been used in combination with microaspiration and/or LCM and subsequent microarray analysis by several independent research groups to examine gene expression levels within specific brain regions and cell types, including hippocampal and basal forebrain cholinergic neurons at the single cell level on a variety of microarray platforms ranging from moderate density custom-designed arrays to commercial high density oligonucleotide arrays , 22–29. Two types of cDNA purification methods were also investigated to determine whether either was more advantageous within the amplification schemes. Utilizing column filtration did not produce the highest raw hybridization signal intensity values. However, when integrating array signal with corresponding negative control background hybridization, a stringent method that the authors urge strongly to be used universally , this meThe animal protocols have been approved by the Institutional Animal Care and Use Committee (IACUC) of the Nathan Kline Institute/NYU School of Medicine and were in full accordance with NIH guidelines. Wild-type C57BL/6 mice (6–10 months old) were euthanized by cervical dislocation and the brain was removed, frozen on dry ice, and stored at –80 °C. Approximately 50–100 mg of cortical tissue was utilized for RNA extraction. Trizol  was added at 10X (w/v) and tissue was homogenized manually. RNA was then extracted with chloroform and precipitated utilizing isopropanol and resuspended in 18.2 mega Ohm RNase-free water . RNA purity and concentration was analyzed utilizing the total RNA Nano procedure with the Agilent 2100 bioanalyzer .2, and 10 U RNase H (Invitrogen) in a final volume of 100 μL. RNase H digestion step at 37 °C, 30 minutes; denaturation step 95 °C, 3 minutes; primer re-annealing step 60 °C, 5 minutes. Samples were purified either by column filtration  or by drop dialysis. These purification methods were selected because they consist of a filter filtration system, rather than a conventional gel filtration. Specifically, employing a gel filtration matrix tends to give a low yield for cDNA purification, making RNA amplification quite difficult and hard to reproduce. For column filtration, column reservoirs were filled with 300 μL of 18.2 mega Ohm RNase-free water and the cDNA reaction was then added to the reservoir. The columns were then spun at 1000 × g for 15 minutes. To recover the cDNA, 20 μL of 18.2 mega Ohm RNase-free water was added to the columns, and the columns were inverted into clean microfuge tubes and spun at 1,000 × g for 2 minutes. The volume of the samples was measured and adjusted to 19 μL by speed vacuum and resuspension in 18.2 mega Ohm RNase-free water. For drop dialysis, phenol:chloroform extracted and ethanol precipitated cDNAs were resuspended and drop dialyzed on 25 um filter membranes (Millipore) against 50 ml 18.2 mega Ohm RNase-free water for 2 hours [The TC RNA amplification methodology was developed in this laboratory . Present 2 hours . Samples4, 100 μM DTT, 15 mM dNTPs, 0.5 U T4 DNA ligase (Invitrogen), 10 U DNA polymerase I , and 10 U RNase H. Samples were incubated at 16 °C for 2 hours, and completed by adding 10 U of T4 DNA polymerase (Promega) for 5 minutes. Reactions were stopped by the addition of 50 mM EDTA. Samples were purified by column filtration or drop dialysis as described for TC RNA amplification.The aRNA amplification protocol utilized herein was modified from the Eberwine protocol and utilized by our group prior to the development of the TC RNA amplification procedure , 36. Bri33P incorporation in 40 mM Tris (pH 7.5), 6 mM MgCl2, 10 mM NaCl, 2 mM spermidine, 10 mM DTT, 2.5 mM ATP, GTP and CTP, 100 uM of cold UTP, 20 U of SuperRNase Inhibitor, 2 KU of T7 RNA polymerase , and 120 uCi of 33P -UTP  [Hybridization probes were synthesized either from TC RNA amplification or aRNA products by IVT using ton, MA) . The reaArray platforms consisted of 1 μg of linearized cDNA purified from plasmid preparations adhered to high-density nitrocellulose . Each cDNA and/or expressed sequence-tagged cDNA (EST) was verified by sequence analysis and restriction digestion. cDNA clones and ESTs from mouse, rat, and human were employed. Approximately 576 cDNAs/ESTs were utilized on the current array platform. Arrays were prehybridized (2 hours) and hybridized 14–16 hours) in a solution consisting of 6X SSPE, 5X Denhardt's solution, 50% formamide, 0.1% sodium dodecyl sulfate (SDS), and denatured salmon sperm DNA (200 μg/mL) at 42 °C in a rotisserie oven [–16 hoursqPCR was performed in triplicate on the same microdissected frozen tissue samples subjected to the RNA amplification procedures. Samples were assayed on a real-time PCR cycler . Mouse TaqMan hydrolysis probes designed against the AMPA glutamate receptor subunit 1 (GRIA1) (Mn00514377_m1), beta actin , and glyceraldehyde-3 phosphate dehydrogenase  were utilized (Applied Biosystems). Standard curves and cycle threshold (Ct) were generated using standards obtained from total mouse brain RNA. The ddCT method was employed to determine relative gene level differences. A total of 3–4 independent samples per RNA concentration were assayed in triplicate. Negative controls were used for each assay, and consisted of the reaction mixture without input RNA.As we move forward with the use of high-throughput functional genomics approaches in biomedical sciences, the ability to manipulate minute starting amounts of RNA has become a critical parameter. The TC RNA amplification method employed herein can be utilized not only for examining different cell types within brain, but for assessing differential gene expression within virtually any cell type utilizing any tissue or cell culture paradigm under normative and pathological conditions. The lack of a requirement for second strand synthesis in the TC RNA amplification procedure is significant, as fewer steps in the procedure is economical, and a decreased likelihood of yield loss is desirable, especially for small and/or precious samples.


STAR protein binding element. C. elegans GLD-1 and mouse Quaking (Qk-1) are two representative STAR proteins that bind similar consensus hexamers, which differ only in the preferred nucleotide identities at certain positions. Earlier reports also identified partial consensus elements located upstream or downstream of a canonical consensus hexamer in target RNAs, although the relative contribution of these sequences to the overall binding energy remains less well understood. Additionally, a recently identified STAR protein called STAR-2 from C. elegans is thought to bind target RNA consensus sites similar to that of GLD-1 and Qk-1.STAR/GSG proteins regulate gene expression in metazoans by binding consensus sites in the 5' or 3' UTRs of target mRNA transcripts. Owing to the high degree of homology across the STAR domain, most STAR proteins recognize similar RNA consensus sequences. Previously, the consensus for a number of well-characterized STAR proteins was defined as a hexameric sequence, referred to as the SBE, for Here, a combination of fluorescence-polarization and gel mobility shift assays was used to demonstrate that STAR-2 binds to a similar RNA consensus as GLD-1 and Qk-1. These assays were also used to further delineate the contributions of each hexamer consensus nucleotide to high-affinity binding by GLD-1, Qk-1 and STAR-2 in a variety of RNA contexts. In addition, the effects of inserting additional full or partial consensus elements upstream or downstream of a canonical hexamer in target RNAs were also measured to better define the sequence elements and RNA architecture recognized by different STAR proteins.in vivo.The results presented here indicate that a single hexameric consensus is sufficient for high-affinity RNA binding by STAR proteins, and that upstream or downstream partial consensus elements may alter binding affinities depending on the sequence and spacing. The general requirements determined for high-affinity RNA binding by STAR proteins will help facilitate the identification of novel regulatory targets  Signal Transduction and Activation of RNA/GRP33, Sam68, GLD-1 (STAR/GSG) family. STAR protein-RNA interactions are important for translational silencing of genes necessary for germline fate in hermaphrodite C. elegans worms by the regulatory STAR protein GLD-1 . Pa. Pa12]. in vitro selection, the Qk-1 binding site was expanded to include a "half-site" positioned upstream or downstream of a consensus hexamer that further defined the STAR binding consensus as a bipartite element [Previously, Ryder et al. described the GLD-1 and Qk-1 high-affinity binding sites as consensus hexamer sequences ,19. In a element . In thatTo address this issue, the consensus core and "half-site" elements were both altered using more conservative mutations, and these MBP RNA variant sequences were tested for binding to Qk-1-STAR in a gel mobility shift assay Figure . The wilUCGGUG-3' or when the 3' "half-site" is altered from 5'-AAAUAAC-3' to 5-AGUGGAA-3'  in this assay while virtually no binding was observed to the 3' mutant (MBP:2-3'm1) in accordance with previous results [As previously noted, Qk-1-STAR does not bind MBP RNA when the 5' consensus site is changed from 5'-CACUAAC-3' to 5'-C' Figure  relative results .UCUCUC-3' (MBP:2-5'm2) results in nearly 5-fold tighter binding (Kd = 100 nM) when compared to MBP:2-5'm1. Similarly, Qk-1-STAR binds tightly to MBP:2-3'm2 and the two distinct complexes seen in the gel have measured Kd values of 69 nM and 199 nM for the first and second shifts, respectively. These values are nearly identical to that for wild-type MBP:2 RNA and neither of these mutant RNAs contain the stable secondary structures in mfold predictions as seen for MBP:2-5'm1 or MBP:2-3'm1. In addition, by simply adding multiple guanosine residues to the 5' end of the TGE in order to facilitate in vitro transcription using T7 polymerase, GLD-1 binding was essentially abolished, presumably due to formation of stable secondary structures in the RNA (data not shown). Taken together, these results suggest that MBP:2 RNA contains two independent consensus binding sites and that only one is necessary for Qk-1 to bind with high-affinity. In addition, Qk-1 is indifferent to the positioning of the consensus site as it bound the full-length MBP RNA with roughly the same affinity when either the 5' or 3' consensus sites were mutated.These results seemingly contradict the idea of a hexanucleotide consensus as the primary specificity determinant for Qk-1 binding. Both MBP:2-5'm1 and MBP:2-3'm1 have valid hexanucleotide elements, but it seemed possible that introduction of multiple G residues in an A/U rich RNA sequence might result in the formation of secondary structures that inadvertently sequester the hexanucleotide element. Indeed, RNA secondary structure predictions using mfold ,24 suggein vitro, and this difference may be due in large part to the extra binding energy attained from recognition of additional RNA elements by the second protomer.One poorly understood aspect of this system is the mode that homodimeric STAR proteins employ when binding target RNA sites, since structural models are based largely on the solution structure of monomeric human SF-1 in complex with Branch Point Sequence (BPS) RNA . SF-1 latra-2 mRNA 3'-UTR contains two 28-nt TGE repeats each with a single consensus hexamer, plus an additional hexamer encompassing part of the conserved 5'-CUCA-3' in the linker separating the two TGEs. Neither of the two TGE truncations lacking a consensus element (1-18 and 56-67) compete well with the fluorescently-labeled 28-nt TGE for GLD-1-STAR binding. When compared to self-competition with the 28-nt TGE, 1-18 and 56-67 bind 42 and 32-fold weaker, respectively, underscoring the necessity of a hexamer consensus for high-affinity binding.Competition fluorescence-polarization was used to address this issue by measuring the affinity of GLD-1-STAR for various TGE RNAs, truncated so as to contain zero, one or two consensus hexamers Figure . The traiapp = 4.6 ± 0.8 nM), binding this RNA nearly 2.5-fold tighter than the TGE 28-mer.GLD-1-STAR binds the TGE half-site RNA (labeled 14-25) containing one consensus hexamer roughly 9-fold weaker than the TGE. This is consistent with the previously measured values for this RNA by both Fp and EMSA ,19. WeakAs a homodimer, both protomers should be equally competent for binding a consensus element in the context of a dual hexamer RNA. However, it remained unclear whether enhanced binding occurs only when the consensus sites are spaced within a certain permissible range. To this end, a library of RNA constructs was developed that placed either one or two canonical hexamers at different locations within a poly-uridine background and were tested for binding to GLD-1-STAR by competition fluorescence-polarization Figure . The 28-iapp of 110.3 ± 22 nM or 83.5 ± 6 nM, respectively, which is similar to that observed for the half-site 12-mer (14-25) containing a single hexamer and also consistent with the affinity of GLD-1-STAR for TGE RNA with mutations in the upstream UA element [iapp = 12.2 ± 2 nM). Binding affinity is 2-fold weaker than TGE RNA when the hexamers are directly adjacent to each other  or with a 2-nt spacer . A spacing of six to twelve nucleotides between hexamers was optimal for tight binding with Kiapp values of 4.8 ± 0.8 nM and 4.8 ± 0.4 nM for a 6-nt and 12-nt spacing, respectively.Addition of one 5'-UACUCA-3' hexamer in the poly-U background at either the 5' or 3' end resulted in a KAAUUU-3'; A6C7, 5'-UACUUU-3') was the most preferred, with a Kiapp of 35.8 ± 5 nM and 38.0 ± 16 nM, respectively, but both are still nearly 8-fold reduced compared to the addition of a consensus hexamer (Kiapp = 4.8 ± 0.8 nM). Interestingly, RNA with the C9A10 substitution (5'-UUUUCA-3') does not bind tighter than 5'-UUUUUU-3' (Kiapp = 85.1 ± 22 nM versus Kiapp = 83.5 ± 6 nM) even though this substitution places half of a 5'-UACUCA-3' consensus upstream of the full hexamer. Of the other sequences tried, C7A10 (5'-UUCUUA-3') and A6C9 (5'-UAUUCU-3') compete with a Kiapp of 51.8 ± 18 and 116.2 ± 16 nM, respectively, indicating that these sequences do not enhance GLD-1 dimer binding when only a single consensus element is present.In the same 28-nt poly-U RNA background discussed above, various dinucleotide sequences were then inserted upstream of a single consensus hexamer and the contributions of these smaller sequence motifs to GLD-1 binding affinity were evaluated by competition fluorescence-polarization Figure . None ofC. elegans worms, GLD-1 binds to TGE RNA and regulates tra-2 translation, while in mice, Qk-1 binds MBP RNA and ensures the proper sub-cellular localization and expression of myelin. Both GLD-1 and Qk-1 bind tightly to a similar hexameric consensus element within their respective RNA targets but require different sequences for optimal binding  fusions and purified as described previously [E. coli cells transformed with pMal-c2x-STAR-2 plasmid were grown in LB media to an OD600 of 0.6 whereby STAR-2 overexpression was induced by addition of 1 mM IPTG for 3 hours. Harvested cell pellets were resuspended and lysed by sonication followed by initial purification on an amylose resin (NEB) column. Pooled fractions containing STAR-2 were further purified by ion-exchange chromatography, first on a HiTrap Q column (Amersham Biosciences) followed by a HiTrap SP column. Pure STAR-2 protein was dialyzed against 4 L of storage buffer  and stored at 4°C for use in binding experiments.The STAR domains from GLD-1 and Qk-1 were overexpressed in eviously ,19. Plas32P-ATP (Perkin Elmer) and T4 polynucleotide kinase (NEB) for 1 hour at 37°C.All RNA constructs were chemically synthesized (Dharmacon). Lyophilized RNA pellets were resuspended in deprotection buffer and incubated at 60°C for 30 minutes. Deprotected RNAs were thoroughly dried in a SpeedVac, resuspended in deionized water and stored according to the manufacturer's protocol. 5'-Fluorescein-labeled RNA constructs used in Fp binding experiments were treated as above except all steps were conducted in the dark. RNAs used in gel mobility shift experiments were 5' radiolabeled by incubation with γ-Complex formation between the various STAR proteins and RNA was monitored by both fluorescence-polarization and EMSA. For direct titration experiments, individual STAR proteins at a range of concentrations were titrated into a constant concentration of labeled RNA (1 nM fluorescein-labeled RNA for Fp or 100-300 pM radiolabeled RNA for EMSA) in reaction buffer  and the reactions equilibrated at room temperature for 3 hours. Prior to equilibration with protein, labeled RNA was heated at 65°C for 2 minutes and allowed to cool to room temperature to remove any residual secondary structure.d values for each RNA were calculated by fitting the binding data to a modified version of the Hill equation as described previously [Fp samples were equilibrated in a total volume of 100 μL in 96 well plates (Grenier) and every plate successively measured 10 times in a Packard Fusion plate reader to obtain the average polarization and standard deviation values for each protein concentration. Samples for gel mobility shifts were equilibrated in 20 μL total volume. 5 μL of each sample was loaded on a pre-run 6% native gel  after addition of loading dye  and the gel run at 600 V for 30 minutes at 4°C. Gels were dried and exposed to a phosphorimager screen overnight. ImageQuant software (Molecular Dynamics) was used to quantify the fraction of labeled RNA in complex with protein. Keviously ,25.50 values for each competitor RNA were determined by a fit of the data to the following equation using IGOR (Wavemetrics):Competition Fp experiments employed the identical conditions as the direct titration experiments described above except that various concentrations of competitor RNA were titrated into a reaction mixture where a constant concentration of STAR protein had been added. Protein concentrations were chosen such that 70-90% of the labeled RNA would be in a bound complex. Polarization values were measured after plates had incubated at room temperature for 3 hours. ICiapp) were fit to a solved quadratic expression of the equation originally described by Lin and Riggs [where f equals fraction bound or polarization value, C is the concentration of unlabeled competitor RNA, m is the maximum signal and b is the base signal. Apparent binding dissociation constants for competitor RNAs (Knd Riggs ,27.d and Kc are the concentrations of fluorescent RNA, protein, competitor RNA, and the dissociation constants for the wild type and competitor RNAs, respectively.R, P, C, KAC, JW and KLB performed the experiments and analyzed the data. AC, KLB and JRW conceived the experiments and AC wrote the manuscript. All authors read and approved the final manuscript.


Along with the low concentrations of RNA present within lichen tissues, the process of creating a cDNA library is technically challenging.The reindeer lichen is the product of a mutualistic relationship between a fungus and an algae. Lichen demonstrate a remarkable capacity to tolerate dehydration. This tolerance is driven by a variety of biochemical processes and the accumulation of specific secondary metabolites that may be of relevance to the pharmaceutical, biotechnology and agriculture industries. These protective metabolites hinder An evaluation of existing commercial and published protocols for RNA extraction from plant or fungal tissues has been performed and experimental conditions have been optimised to balance the need for the highest quality total ribonucleotides and the constraints of budget, time and human resources.We present a protocol that balances inexpensive RNA extraction methods with commercial RNA clean-up kits to yield sufficient RNA for cDNA library construction. Evaluation of the protocol and the construction of, and sampling from, a cDNA library is used to demonstrate the suitability of the RNA extraction method for expressed sequence tag production. Lichen are formed as a product of the symbiotic relationship between a fungus and its photosynthetic partner, which can be either an algae or a cyanobacterium . The funApproximately one-fifth of fungal species form obligate symbiotic associations with green algae or cyanobacteria. This increases to about 46% for the ascomycete fungi and thus the processes of lichenisation are critical to the understanding of both ascomycete relationships and the evolution of mechanisms for the control and maintenance of plant-fungal interactions. An estimated 100 species of algae from 40 genera are reported to form lichen symbioses .The molecular nature of the symbiosis is still under discussion; some researchers observe a controlled parasitism of the photobiont by the mycobiont , while oRegardless of the nature of the relationship, lichens inhabit some of the harshest climates on earth, and have demonstrated a capacity to at least survive the more challenging extremes of space . Lichen The availability of methods for the purification of high quality ribonucleic acids (RNA) is essential for studies aimed at constructing cDNA libraries or performing array-based hybridisations where microgram quantities of concentrated and chemically pure mRNA may be required. RNA isolation in lichen is complicated by the abundance of protective secondary metabolites and polysaccharides, chemicals known to interfere with RNA isolation protocols that lower both the yield and quality of the extracted total RNA . In addiCladonia rangiferina. We have evaluated and optimised a process for RNA isolation from the secondary metabolite rich tissues of Cladonia rangiferina that balance the needs of sample purity for downstream library construction, cost and labour requirements.It is the aim of our research to develop genomic resources for the fructicose lichen, Cladonia rangiferina were collected from the island of Kuusisto in Kaarina, Finland. The lichen was cleaned and stored desiccated at -20°C as this has been found to be the best way to store lichen samples [Clumps of  samples . Prior tRNA extraction was performed according to the manufacturer's instructions . The amount of starting tissue used was 100 mg of lichen tissue.An extraction procedure was modified from the manufacturer's instructions by adding an additional chloroform extraction step after the first chloroform extraction and replacing the isopropanol precipitation with ethanol precipitation at -80°C for 2 hours. Different lichen tissue/TRIzol reagent ratios were evaluated with 1 g of lichen tissue in a 15 ml volume of TRIzol reagent being optimal.The extraction protocol was modified from  by replaThe CTAB protocol was modified from Gooding, et al , who had260/280 and A260/230 ratios given by NanoDrop. Quality was also inspected visually following gel electrophoresis of denatured RNAs.The extracted total RNA samples were stored at -80°C and concentrations were measured spectrophotometrically in Tris-EDTA buffer solution using the NanoDrop instrument . The purity of the total RNA was assessed using the A® Gigapack® III Gold Cloning (#200450) cDNA library synthesis kit  according to manufacturer's instructions. Size fractionation was achieved using gel electrophoresis. Gel slices corresponding of between 500-1000 bp and 1000-3000 bp in size were excised and gel purified cDNA was cloned into a phage library. cDNA library clones were sequenced on an ABI PRISM 3130xl Genetic Analyzer capillary DNA sequencer following a BigDye v3.1  labelling reaction.mRNA was isolated from the total RNA with Nucleo-Trap mRNA kit . A phage cDNA library was constructed from the mRNA using the ZAP-cDNACladonia sequences to the NCBI non-redundant protein sequence database [Computational analysis of the raw sequence data was performed using the openSputnik sequence analysis platform . BLASTX database . BLASTX database  mappingsWe evaluated a panel of four robust methods  that yielded varying quantities of total RNA. The CTAB method was supplemented with a further RNA purification with a commercial RNA cleaning kit to yield a fifth method. The yield and purity of the extracted total RNA from these five RNA isolation procedures is presented in table The Sigma Spectrum plant total RNA kit produces high-quality total RNA with a good yield and a hands-on time of 30-45 minutes. The biggest drawback of the method is the limited amount of starting tissue (100 mg) that can be used per column. To obtain the needed 1000 μg of total RNA for the subsequent mRNA isolation for cDNA library construction, over 30 g of lichen tissue is required. This represents at least 300 extractions, which renders the method both time-consuming and prohibitively expensive.260/230 ratios are low and indicate the presence of polysaccharides and/or secondary metabolites. Modifying the TRIzol procedure by adding a second chloroform extraction step and replacing the isopropanol precipitation with ethanol precipitation slightly improved the A260/280 ratio while the yield remained similar. LiCl precipitation step was omitted from CTAB method and replaced with ethanol precipitation in Dong & Dunstan method as this step radically reduced the RNA yield. When the RNA extracted using the TRIzol reagent or Dong & Dunstan method was further purified with RNeasy clean-up kit, superior A260/280 and A260/230 ratios were obtained. When resolved by gel electrophoresis, the RNA extracted with TRIzol reagent appeared to be of better quality than that extracted according to Dong & Dunstan method (results not shown). TRIzol reagent is expensive, thus the projected volumes required would support the application of a more cost effective RNA extraction protocol as the Dong & Dunstan method appears to yield RNA of insufficient quality.With TRIzol reagent and Dong & Dunstan method the yield is superior to the other methods, but the purity of the extracted total RNA is insufficient. The A260/280 and A260/230 ratios were suitable. Expensive chemicals are not required for the CTAB method, it can easily be scaled up if needed, with a hands-on time of around 4 hours for six samples. Total RNA extracted using the CTAB method contained considerable genomic DNA contamination. After purification with the RNeasy clean-up kit, which includes a DNase I treatment, the DNA contamination was no longer visible following denaturing gel electrophoresis , with the majority of sequences falling in the range of 200 to 500 bp. BLASTX [GH717691 - GH717859.A total of 1024 μg of total RNA from six CTAB+RNeasy RNA isolations were pooled, and the pooled ribonucleotides were used for construction of a phage cDNA library. Library titres of 2.4 × 10. BLASTX  analysis. BLASTX  EST clusCladonia rangiferina.Little research has been performed on lichen at the molecular biological level and the available molecular resources for lichen species are focused towards taxonomic systematics and on the evolution of lichens. We have compared and optimised five different methods for extracting total RNA from 260/280 and A260/230 ratios >2.The secondary metabolites present in lichen tissues interfere with conventional RNA extraction procedures and in the subsequent first strand cDNA synthesis. Using the mRNA from a standard RNA isolation/mRNA purification in cDNA library construction has resulted in disappointing titre counts (results not shown). It is essential, and ultimately cost-effective, to combine a conventional RNA isolation method with a commercial RNA clean-up kit to produce sufficiently clean RNA. Conventional methods allow for the amount of starting tissue to be scaled up as needed, such that impure total RNA can be extracted in large quantities. The conventional procedure best suited for lichen RNA isolation appears to be the CTAB method. The remaining polysaccharides and secondary metabolites are effectively removed in the following clean-up step, resulting in high quality total RNA with AThe overall yield from the optimised CTAB method with subsequent sample clean-up is less than 10 μg of total RNA per gram of starting tissue. This is much lower than the amount of RNA extracted from other model organisms, or the measured yields from the other methods  extraction buffer  with 2% β-mercaptoethanol3. Extract twice with phenol-chloroform (1:1)4. Add equal volume of NTES buffer  and chloroform (1:1) to the supernatant5. Precipitate RNA with ethanol and dissolve in waterClean RNA using QIAgen RNeasy columns according to manufacturer's instructionsCladonia rangiferina unigene sequences with a BLASTX match. The collated results from the Cladonia rangiferina unigene sequences having BLASTX matches against protein sequences in the NCBI NonRedundant protein sequence database exceeding the arbitrary expectation value of 1e-10. For each sequence is shown the NCBI accession and species of origin for the best matching sequence and the number of distinct plant, and fungal species  matched. This can be used to identify tentative fungal and plant-specific sequences. The sequences flagged with a '*' appear fungal specific, while sequences flagged with the '†' have plant or algal sequence matches and no fungal matches, but may also match sequences of animal, protist or bacterial origin.Click here for file


Peripheral blood is an accessible and informative source of transcriptomal information for many human disease and pharmacogenomic studies. While there can be significant advantages to analyzing RNA isolated from whole blood, particularly in clinical studies, the preparation of samples for microarray analysis is complicated by the need to minimize artifacts associated with highly abundant globin RNA transcripts. The impact of globin RNA transcripts on expression profiling data can potentially be reduced by using RNA preparation and labeling methods that remove or block globin RNA during the microarray assay. We compared four different methods for preparing microarray hybridization targets from human whole blood collected in PAXGene tubes. Three of the methods utilized the Affymetrix one-cycle cDNA synthesis/in vitro transcription protocol but varied treatment of input RNA as follows: i. no treatment; ii. treatment with GLOBINclear; or iii. treatment with globin PNA oligos. In the fourth method cDNA targets were prepared with the Ovation amplification and labeling system.We find that microarray targets generated with labeling methods that reduce globin mRNA levels or minimize the impact of globin transcripts during hybridization detect more transcripts in the microarray assay compared with the standard Affymetrix method. Comparison of microarray results with quantitative PCR analysis of a panel of genes from the NF-kappa B pathway shows good correlation of transcript measurements produced with all four target preparation methods, although method-specific differences in overall correlation were observed. The impact of freezing blood collected in PAXGene tubes on data reproducibility was also examined. Expression profiles show little or no difference when RNA is extracted from either fresh or frozen blood samples.RNA preparation and labeling methods designed to reduce the impact of globin mRNA transcripts can significantly improve the sensitivity of the DNA microarray expression profiling assay for whole blood samples. While blockage of globin transcripts during first strand cDNA synthesis with globin PNAs resulted in the best overall performance in this study, we conclude that selection of a protocol for expression profiling studies in blood should depend on several factors, including implementation requirements of the method and study design. RNA isolated from either freshly collected or frozen blood samples stored in PAXGene tubes can be used without altering gene expression profiles. Gene expression profiling of RNA extracted from peripheral blood is an informative method used to identify biomarkers, examine disease states, and investigate immune responses. However, the relatively high proportion of globin messenger RNA present in total RNA extracted from whole blood can reduce the efficacy of the microarray assay by interfering with the detection of less abundant gene transcripts -3. FurthCommon laboratory practice often includes fractionation of whole blood components prior to RNA extraction. The process allows for the removal of the red blood cells from whole blood isolations and facilitates the study of more homogeneous cell populations. Depending on the fractionation method selected, partial or complete removal of reticulocytes, the primary source of globin RNA, may be achieved. Despite the obstacle posed by globin RNA contamination, however, there are compelling reasons to study gene expression from whole blood rather than from subpopulations such as neutrophils. First, to capture expression profiles that accurately reflect the transcriptome at time of blood collection and to minimize sample handling artifacts, it is preferable to avoid additional processing steps as some degree of cell activation is inevitable during cell fractionation. Second, even when fractionation steps are performed, α and β globin mRNA transcripts are often the most abundant transcripts present in total RNA extracted from leukocyte-enriched populations  and the Several commercially available methods for reducing the impact of globin RNA transcripts in the microarray expression assay have been developed. One approach involves the removal of α and β globin RNAs from total RNA by selective hybridization and magnetic bead separation  prior toEach method has been demonstrated to produce array data in which an increased number of non-globin gene transcripts are detected ,10, and RNA isolated directly from whole blood and processed using standard target preparation methods produces gene expression profiles with increased noise and reduced sensitivity compared with total RNA isolated after various leukocyte isolation protocols. However, the advantages of profiling gene expression from whole blood are compelling: 1) cell fractionation steps that may artifactually alter gene expression patterns are avoided; 2) easy and rapid isolation of RNA from whole blood facilitates clinical studies; 3) even rare subpopulations of cells such as dendritic cells or eosinophils remain included in the transcriptome; and 4) costs are vastly reduced. To increase assay sensitivity and reproducibility when profiling RNA extracted from whole blood, it is necessary to employ a method to reduce the impact of highly abundant globin mRNAs on target hybridization with the microarray. In this study, four methods for RNA preparation and labeling were examined to determine which protocol produced the most sensitive and reproducible results when blood RNA isolated from PAXGene tubes was used as input. In addition, since the option to freeze a whole blood sample allows samples to be collected over time and at different study sites prior to processing, the effects of freezing blood samples were examined by comparing data generated from both fresh and frozen specimens. Freezing blood samples after collection has the advantage of allowing batching of samples for RNA extraction and simplifying the blood collection protocol for multicenter studies.Blood samples were collected from healthy, human donors in PAXGene tubes; RNA was isolated either on day of collection or after freezing and storage. Four different methods of microarray target preparation for whole blood RNA samples were examined Figure . Three oThe quality of total RNA prepared from fresh and frozen PAXGene tubes and from GLOBINclear-treated RNA was assessed using standard UV spectrophotometry and by examining electropherogram images generated with the Agilent Bioanalyzer. Input RNA was of high quality for both fresh and frozen samples  with a slight reduction in average quality metrics for GLOBINclear-treated samples (average RIN score 8.6 and 8.5). Reductions in RIN scores after GLOBINclear treatment of whole blood RNA were also observed by Liu et al. . Each amUsing recommended RNA inputs for each method, average cRNA target yield ranged from 20 μg to 102 μg. The average yield with Method 1 (no depletion_Affymetrix) using RNA from either fresh or frozen PAXGene tubes is typical of yields obtained in our laboratory with this method. We speculate that the high yields for Method 2 (Globin PNAs_Affymetrix) relative to the other Affymetrix one-cycle target labeling methods are, at least partially, the result of the higher input RNA amount (5 μg) required by the Method 2 protocol. The GLOBINclear-treated RNA produced the lowest cRNA yields with the Affymetrix one-cycle labeling protocol, as has been observed previously with this method [Targets produced with each labeling method were hybridized with the GeneChip Human Focus array. Target amounts and array processing steps were performed according to the manufacturers' recommendations for the labeling method and the array format. Overall performance in the array assay was examined in three ways: 1) individual array performance metrics (generated with MAS 5.0); 2) data visualization for assessment of data distribution and variation; and 3) correlation of detected transcripts among targets generated with each method.Array performance metrics Table  indicateExamination of probe cell intensity distributions prior to normalization shows that overall signal distribution patterns Figure  varied wSample-to-sample variation was also examined by measuring similarity among expression profiles from different donor samples processed with the same target preparation method. A high within-method correlation (average r = 0.98) was measured for Methods 1 , 2 (Globin PNAs_Affymetrix) and 4 (no depletion_NuGEN). Method 3 (GLOBINclear_Affymetrix) again showed somewhat poorer performance (average r = 0.96).We assessed the extent of globin transcript depletion in the microarray assay with each labeling method by examining α- and β-globin mRNA signal intensities normalized to actin mRNA signal. All of the globin mRNA depletion methods resulted in decreased α- and β-globin mRNA transcript measurements relative to Method 1 (no depletion_Affymetrix) targets. Method 2 (Globin PNAs_Affymetrix) generated targets that showed the greatest reduction in globin mRNAs Figure . InteresExpression levels of a panel of 84 genes from the NF-κB pathway plus 5 housekeeping genes were measured by quantitative RT-PCR using total RNA from two of the individuals profiled in the microarray component of this study. The NF-κB pathway was chosen because of biological interest to study authors and high overlap of panel genes with genes represented on the Human Focus array. RNA prepared from both frozen and unfrozen PaxGene tubes was analyzed for each donor. All of the genes measured in the RT-PCR assay were scored as present in the microarray profiles produced with targets from one or more of the methods examined in this study.Comparison of the RT-PCR data with array profiles for 75 matched genes demonstrated that Method 2 (Globin PNAs_Affymetrix) produced expression data that most closely correlates with the RT-PCR results, with an average Pearson correlation of 0.77 , Method 3 (GLOBINclear_Affymetrix) and Method 4 (no depletion_NuGEN) is illustrated in the Venn diagram in Figure Overall, the vast majority of gene transcripts detected with each method were also detected by the other three methods. The highest expression concordance was observed between Methods 1 (no depletion_Affymetrix) and 2 (Globin PNAs_Affymetrix). The Globin PNAs_Affymetrix method and the no depletion_NuGEN method each detect a significant number of gene transcripts  not detected by any of the other methods tested in this study. Four of the transcripts detected with only one labeling method (3 in no depletion_NuGEN and 1 one in Globin PNAs_Affymetrix) correspond to genes whose transcription was confirmed in the quantitative RT-PCR analysis. This observation suggests that both the no depletion_NuGEN and the Globin PNAs_Affymetrix method produce microarray data that accurately measures gene expression not detected by the other methods.Microarry performance of RNA extracted from blood collected in PAXGene tubes immediately following a 2 hr room temperature incubation or after a 2 hr incubation and freezing at -80°C was compared. Correlation between array data from fresh and frozen PAXGene preparations from each donor was high across all samples prepared with Methods 1 (no depletion_Affymetrix), 2 (Globin PNAs_Affymetrix) or 4 (no depletion_NuGEN), with the exception of donor A using Method 1, where one of the microarray assays underperformed Table . Method Our results indicate that freezing blood collected in PAXGene tubes prior to RNA extraction has little impact on the RNA profiles measured in the microarray assay. This observation is consistent with the report of Ovstebo et al in whichGiven the overall similarity in fresh and frozen sample pairs as measured in both the microarray and RT-PCR analyses, we elected to use the fresh/frozen pairs for each donor to examine array assay reproducibility among the different assay methods. Method 2 (Globin PNAs_Affymetrix) showed the highest reproducibility in paired donor samples (average r = 0.99). Reproducibility was also high with Methods 1 (no depletion_Affymetrix) and 4 (no depletion_NuGEN) (average r = 0.98), but slightly reduced with Method 3 (GLOBINclear_Affymetrix) (average r = 0.97).Removing globin transcripts from cRNA hybridization targets prepared from whole blood samples results in increased sensitivity in microarray expression profiles. Sensitivity is also increased when cDNA hybridization targets prepared from undepleted RNA are used instead of cRNA targets. All of the methods tested in this study generate highly reproducible data, except when total RNA is pre-treated to remove globin transcripts (GLOBINclear_Affymetrix method). Comparison of microarray gene level signals with real-time PCR data suggests that the Globin PNAs_Affymetrix method produces the most accurate microarray results, although, all methods produce data that correlate well with the RT-PCR measurements. Performance results for each method are summarized in Table Before selecting a protocol for use in an expression profiling study of whole blood, however, several factors must be considered.This method required relatively low RNA amounts and did not require any additional processing steps. Overall, correlation to real-time PCR data was second only to the Globin PNAs_Affymetrix method (Method 2).It has been well reported that performing microarray profiling of RNA extracted from whole blood using this method without modification results in less sensitive data with high levels of sample-to-sample variability ,4,5,11. Sensitivity was highest with this method. Additionally, this method also produced the lowest relative α- and β-globin intensities when the signal was normalized to a housekeeping control gene, further confirming the effectiveness of the reduction. Among all protocols tested in this study, the globin PNAs method demonstrated the highest reproducibility when correlation values were measured between donor replicates. Finally, microarray RNA expression values produced with the PNA method showed the highest correlation to RT-PCR measurements of a selected gene panel in the same RNA samples compared to all other methods.While targets prepared following the PNA method produced the best overall results in the microarray assay, before selecting this protocol to profile expression patterns of whole blood, it is important to note that, among the protocols examined in this paper, the PNA method is one of the more time-consuming and requires the highest amount of total RNA. Although recent studies in our laboratory show that the PNA method can be successfully applied with RNA inputs as low as 2 μg (unpublished data), the relatively high RNA amounts required by this method could be a confounding factor if the amount of RNA available for expression profiling is low. Furthermore, the PNA sequences supported by Affymetrix for use in this protocol are designed to bind to human α- and β-globin transcripts. Consequently if blood RNA extracted from non-human species is to be analyzed, it would be necessary to design and optimize peptide nucleic acid sequences for the species of interest. Also note that PNA sequences recommended by Affymetrix are no longer sold by Applied Biosystems. The product is now available through Panagene .The third method examined in this study uses a magnetic-bead based hybridization system to extract globin RNA from whole blood total RNA prior to amplification. Beads can be purchased to bind to species-specific globin transcripts (human and rodent), allowing for increased flexibility. Sensitivity is almost as high as that achieved with the PNA method. Globin probe set intensities, compared to the housekeeping controls, were reduced but not to the level observed when using the PNA method.Reproducibility of GLOBINclear targets is lowest of the methods examined. Furthermore, we noted an increase in the ratio of 3' versus 5' housekeeping control probe set intensity, suggesting a slight decrease in the quality of the target prepared using this method. This trend can likely be explained by the increased sample handling required to process the RNA during the bead hybridization and magnetic purification steps. Input requirements are also relatively high for this method, again presenting challenges when sample amounts are limiting. In addition, comparison of microarray expression values generated with this method showed the lowest correlation with the RT-PCR results on the NF-κB pathway genes.Among the four protocols tested, this labeling protocol requires the lowest amount of total RNA (5–100 ng) and does not have a separate globin RNA reduction step. Instead, the hybridization kinetics of the cDNA target appear to be less affected than cRNA targets by the abundant globin RNA present in whole blood extractions. The α- and β-globin RNA intensity measurements in these targets, compared to a housekeeping control, ranked second to the PNA method indicating a reduction in globin transcript signal compared to the standard labeling method with no globin RNA depletion. In addition, because a separate species-specific globin reduction step is not required, the Ovation method is the most flexible cross-species protocol of the alternative methods tested.Microarray expression values generated with this method do not correlate as well with RT-PCR measurements as the Globin PNAs or standard Affymetrix method. In addition, detection sensitivity of targets prepared following the NuGEN Ovation Biotin RNA Amplification and Labeling System v1 protocol is the lowest of the alternative methods tested. However, since we completed this study, NuGEN has released a modified protocol (NuGEN Ovation Whole Blood Labeling System with FLv2) specifically aimed at minimizing the impact of globin transcripts when expression profiling RNA extracted from whole blood. Results from a blood profiling study that used targets generated with the Whole Blood Ovation System show significantly increased transcript detection rates compared to version 1 of this kit . It is likely that the Ovation Whole Blood FLv2 system retains the high reproducibility and implementation advantages of the version 1 system while producing microarray data with detection sensitivity similar to the globin PNAs method. In a study of small sample protocols for microarray analysis using non-blood tissues, another aspect of sensitivity, detection of differential expression between samples, was shown to be highest with the Ovation method compared to other small sample protocols and the standard Affymetrix one-cycle labeling method .Our results and observations can be summarized in five main points: (1) protocols designed to minimize the impact of globin transcripts can significantly improve the performance of whole blood-extracted RNA in an expression profiling microarray study; (2) methods to reduce globin RNA prior to target synthesis may require amounts of RNA that are not feasible in some studies; (3) for nonhuman studies, the requirement for species-specific oligonucleotides in globin RNA depletion protocols may limit use; (4) target preparation protocols can be a major source of variability; (5) if precautions are taken to properly stabilize extracted blood, the impact of freezing specimens prior to RNA extraction is minimal.Unfractionated whole blood collection and RNA isolation were performed using the PAXgene Blood RNA Isolation System . PaxGene tubes contain a proprietary reagent to reduce intracellular RNA degradation and minimize induction of gene expression . With thAmplifications and labeling were performed for each donor using one of the following four methods with RNA extracted from fresh and frozen blood samples: Method 1 – Affymetrix one-cycle cDNA synthesis/Affymetrix in vitro-transcription (IVT) on whole blood RNA (no depletion_Affymetrix); Method 2 – Affymetrix one-cycle cDNA/Affymetrix IVT with globin peptide nucleic acids (PNAs) inclusion during cDNA synthesis (Globin PNAs_Affymetrix); and Method 3-RNA pre-treated with Ambion GLOBINclear beads to reduce globin transcripts prior to labeling with the Affymetrix one-cycle cDNA synthesis/Affymetrix IVT (GLOBINclear_ Affymetrix). In the fourth method tested, cDNA target was synthesized from whole blood RNA using the NuGEN Ovation Biotin RNA Amplification and Labeling System v1 (no depletion_NuGEN). Total RNA input amounts were based on manufacturer's recommendations for each method. with minor modification. Using 1 μg of total RNA as input, messenger RNA was amplified and labeled in two steps. In the first step, mRNA was converted to double-stranded cDNA and purified by phenol-chloroform-isoamyl alcohol extraction and ethanol precipitation. In the second step, amplified and biotinylated cRNA (the target) was produced by in vitro transcription (IVT). Unincorporated nucleotides were removed using the RNeasy Mini kit (Qiagen) followed by an ethanol precipitation of the labeled target.Method 1 employed the standard laboratory method for amplification and labeling of total RNA. Target synthesis was performed following the Affymetrix GeneChip Expression Analysis Technical Manual, rev. 5 . Globin reduction PNA master mix was prepared by adding equal amounts of the globin PNA stocks. Five μg of total RNA were incubated with oligo-dT primer and 1 μl PNA master mix for 10 minutes at 70°C prior to first strand cDNA synthesis; all subsequent steps for target amplification and labeling were as described for Method 1.The standard Affymetrix amplification and labeling was performed with the following modification: four peptide nucleic acid (PNA) oligonucleotides  designed to anneal to human α- and β-globin mRNA were added to the total RNA preparations immediately prior to initiation of the target synthesis step in order to bind globin mRNA and block cDNA synthesis. The PNA oligonucleotide stocks were prepared on day of use at concentrations recommended by Affymetrix Globin mRNA depletion was performed in three steps using the GLOBINclear Kit . First, species-specific biotinylated oligonucleotides complementary to human α- and β-globin mRNA were hybridized with total RNA (5 μg). Second, magnetic streptavidin-coated beads were added to bind the biotinylated-oligonucleotide:globin RNA complexes. Finally, a magnet was used to remove beads with the selectively bound α- and β-globin transcripts. After globin mRNA depletion, RNA quantity was determined by UV absorbance and RNA integrity was assessed using RNA Nano LabChips as described above. RNA recovery following GLOBINclear treatment ranged from 2–5 μg. Target labeling and amplification steps were then performed as described for Method 1.Ovation v1 labeling and amplification reagents were obtained from NuGEN Technologies, Inc  and biotinylated cDNA targets were prepared according to manufacturer's instructions. Double-stranded cDNA was synthesized from 30 ng total RNA, followed by a linear isothermal amplification (SPIA Amplification™) to produce single-stranded cDNA (target). A proprietary fragmentation and direct labeling process attached biotin to the amplified target. Target purifications were performed using DNA Clean and Concentrator – 25  and the DyeEx 2.0 Spin Kit (Qiagen).Targets labeled with Affymetrix one-cycle cDNA synthesis/Affymetrix IVT  were chemically fragmented as per Affymetrix's recommendations and combined with Affymetrix biotinylated hybridization controls  in hybridization buffer. Hybridizations were performed for 16 hours at 45°C after addition of 6.5 μg of target to the GeneChip Human Genome Focus array (Affymetrix), containing 8700 probe sets. Post-hybridization array processing was performed according to manufacturer's recommendations. The distribution of fluorescent material on the processed array was determined using the Affymetrix 3000 GeneArray laser scanner with the 7G upgrade. Image inspection was performed manually immediately following each scan.For targets labeled with NuGEN Ovation system (Method 4), the hybridization and processing outlined above was performed with the following modification: following NuGEN's recommendations, 1.3 μg of cDNA target were mixed with Affymetrix hybridization controls in hybridization buffer and hybridized with the Human Genome Focus array for 18 hours at 45°C.The array image scan was processed with Affymetrix Microarray Suite, version 5.0, (MAS 5.0) software. GeneChip expression Arrays contain control probe sets for both spiked and endogenous RNA transcripts . Following absolute analysis of the array pattern with MAS, six values were examined to assess overall assay performance: background, noise, average Signal, % Present, ratio of Signal values for probe sets representing the 5' and 3' ends of actin and GAPDH transcripts, and total Signal for probe sets for BioB, BioC, BioD and CreX. Assays demonstrating poor or marginal performance were flagged.2 PCR Array First Strand Kit  following the manufacturer's instructions. The product was combined with SuperArray PCR SYBR Green master mix and pipetted into all wells of a 96-well RT2Profiler™ PCR Array for the human NF-κB pathway (SuperArray APHS-025A) per the manufacturer's instructions. After 10 min at 95°C to activate the HotStart DNA polymerase, the samples were subjected to 40 cycles of 15 seconds 95°C, 35 seconds at 55°C during which time the SYBR Green fluorescence was recorded, and 30 seconds at 72°C with a Chromo4 thermocycler . Cycle threshold (Ct) values were obtained for each sample and were normalized for each plate by subtracting the mean Ct value for five housekeeping genes  to yield ΔCt values.Quantitative RT-PCR was performed on RNA from donors C and D. cDNA was prepared from selected RNA samples (1 μg each) with a RTFor comparison of RT-PCR results with the microarray data, 75 genes from the SuperArray NF-κB pathway panel were matched to probe sets on the Affymetrix Human Genome Focus array.Low-level analysis  of microarray data was performed with both Microarray Suite 5.0 (MAS 5.0) ,18 and RExploratory data analysis was performed on probe cell intensities and summarized probe set signal values. Box plots of signal distributions were generated with Expression Console (Affymetrix). Scatter plots and correlation measurements were performed using Statistica 6.0 . Venn diagrams were generated using VENNY, an interactive tool for comparing lists with Venn diagrams cDNA: complementary deoxyribonucleic acid; Ct: cycle threshold; CTP: cytidine triphosphate; DNA: deoxyribonucleic acid; GAPDH: glyceraldehydes-3-phosphate dehydrogenase; IVT: in vitro-transcription; MAS 5.0: Microarray Suite version 5.0; mRNA: messenger RNA; NF-κB: nuclear factor-kappa B; NK: natural killer; OHSU: Oregon Health and Science University; PCR: polymerase chain reaction; PNA: peptide nucleic acid; r: correlation coefficient; RIN: RNA integrity number; RMA: robust multi-array average; RNA: ribonucleic acid; RT-PCR: reverse transcriptase-polymerase chain reaction; UV: ultraviolet.KV performed the microarray assays and assisted with experimental design, data analysis and preparation of the manuscript; RS assisted with protocol development and microarray assays; AC assisted with protocol development and performed RNA isolations and globin RNA depletion; TJ performed data analysis; SP participated in the design of the study, data analysis and manuscript preparation; DC performed data analysis and participated in critical review of the manuscript; JS and JR participated in the design of the study and critical review of results and the manuscript; CAH conceived of the study, guided its design and coordination, performed data analysis and drafted the manuscript. All authors read and approved the final manuscript.


There is extensive variation in gene expression among individuals within and between populations. Accurate measures of the variation in mRNA expression using microarrays can be confounded by technical variation, which includes variation in RNA isolation procedures, day of hybridization and methods used to amplify and dye label RNA for hybridization.In this manuscript we analyze the relationship between the amount of mRNA and the fluorescent signal from the microarray hybridizations demonstrating that for a wide-range of mRNA concentrations the fluorescent signal is a linear function of the amount of mRNA. Additionally, the separate isolation, labeling or hybridization of RNA does not add significant amounts of variation in microarray measures of gene expression. However, single or double rounds of amplification for labeling do have small but significant affects on 10% of genes, but this source of technical variation is easy to avoid. To examine both technical and stochastic biological variation, mRNA expression was measured from the same five individuals over a six-week time course.There were few, if any, meaningful differences in gene expression among time points. Thus, microarray measures using standard laboratory procedures can be precise and quantitative and are not subject to significant random biological noise. Microarrays simultaneously quantify several hundred to thousands of genes on a single glass slide and their use has greatly expanded the breadth of quantified gene expression Fundulus heteroclitus variation among individuals in mRNA expression is extensive: >60% of genes have significant differences in expression among individuals within a population For the teleost fish Accurate microarray quantification is best realized when there is a linear relationship between fluorescence and RNA concentration. This linear relationship fails when the dynamic range of microarrays are exceeded. For any microarray, there are two parameters that define its dynamic range: the range of fluorescence that can be measured and the range of RNA concentrations that can bind to a specific array feature. These two components of the dynamic range reflect the two types of saturation that can occur on a microarray: photomultiplier tube (PMT) saturation and biological saturation. A linear relationship between fluorescence and RNA concentration can only occur if the cDNA on the microarray captures proportional amounts of RNA and if the PMT is not saturated.16-1 or 65,535 and thus any fluorescent photons captured at this value of 65,535 are not discernable The PMT measures the number of photons from the fluorescently labeled RNA that are excited by the lasers. PMT saturation is a result of the photomultiplier tube becoming oversaturated due to an overabundance of converted electrons by the analog to digital (A/D) converter. The A/D converter can only convert the PMT signal into a value less than or equal to 2F. heteroclitus 384 cDNA metabolic microarray.Biological saturation occurs when the amount of mRNA that can hybridize to the DNA on a microarray reaches a maximum binding capacity of the printed DNA. If biological saturation is reached, then the amount of a mRNA will be underestimated and differences among arrays or experiments can not be appropriately determined. To avoid biological saturation, the amount of target RNA must be present in quantities less than the amount that the cDNA on the microarray slide can bind. To determine the range and linear response of increasing amounts of mRNA, we hybridized a 500-fold concentration range of labeled RNA from cardiac tissue to the in vivo by using the T7 RNA polymerase to incorporate amino allyls followed by covalent binding of fluorescent molecules to the incorporated amino allyls Sources of technical variation, other than PMT and biological saturation, come from methods used to fluorescently label the mRNA, the day on which the RNA is processed and varying amounts of available tissue The day and process used to isolate mRNA are two additional sources of technical variation. Variation in the preparation of mRNA could alter its quality affecting how well the RNA amplifies, is fluorescently labeled, and the signal observed on the microarray. The day on which a tissue is sampled is not strictly technical but can introduce a second type of variation: biological variation. That is, isolating tissues on different days could introduce technical variation because of the precision of dissection and the quality of tissue or RNA preparation. However, because tissues are sampled on different days, the organisms may be biologically different . To examine technical variation due only to RNA isolation, a single blood sample was divided into four, RNA was separately isolated from each sample and, gene expression was quantified. Biological variation was examined in a separate experiment where five fish were bled every two weeks for a total of six weeks in order to collect four separate samples from each individual. Gene expression was quantified for these four temporally separate samples.Fundulus array are both accurate and precise.These experiments indicate that for a wide range of experimental conditions, microarray experiments using the Fundulus heteroclitus were caught from wild populations in Wiscasset, Maine, USA  by minnow trap. Fish were transported to the Rosenstiel School of Marine and Atmospheric Science at the University of Miami and acclimated to 20°C and 15ppt for approximately 6 months.Fundulus heteroclitus (N = 20) were anesthetized with MS222 (0.1 g·l−1) and given tags with subdermal latex markers. Whole blood samples from each fish were taken every two weeks by caudal puncture using a 50 µl Hamilton syringe rinsed with heparinzed saline (50 i.u. ·ml−1). Samples were immediately frozen in liquid N2 and stored at −80°C. Only individuals that had all four serial samples taken (N = 5) were used in the present study.in vitro transcription)in vitro transcription of aRNA, an amino allyl UTP (aaUTP) is incorporated into the elongating strand. aaUTP incorporation allows for the coupling of Cy3 or Cy5 dyes (GE biosciences) onto aRNA for microarray hybridization.Total RNA was isolated using 4.5 M guanidinium thiocyanate, 2% N-lauroylsarcosine, 50 mM EDTA, 25 mM Tris-HCl, 0.1 M β-Mercaptoethanol and 2% Antifoam A. The extracted RNA was further purified using a Qiagen RNeasy Mini kit in accordance with the manufacturer's protocols. The quantity and quality of the RNA was determined using a spectrophotometer  and a bioanalyzer (Agilent 2100). RNA was then converted into amino allyl labeled RNA (aRNA) using the Ambion Amino Allyl MessageAmp II aRNA Amplification kit. This method converts poly-A RNA into cDNA with a T7 RNA polymerase binding site; T7 is then used to synthesize new strands of RNA (2), and covered with a cover slip. Slides were placed in an airtight chamber humidified with paper soaked in 5× SSPE and incubated 24–48 hours at 42°C.Dye labeled aRNA aliquots for each hybridization  were vacuum dried together and resuspended in 15 µl hybridization buffer . Hybridization buffer consisted of 5× SSPE, 1% SDS, 50% formamide, 1 mg/ml polyA, 1 mg/ml sheared herring sperm carrier DNA, and 1 mg/ml BSA. Slides were washed in sodium borohydride solution in order to reduce autofluorescence. Following rinsing, slides were boiled for 2 minutes and spin-dried in a centrifuge at 800 rpm for 3 minutes. Samples (15 µl) were heated to 90°C for 2 minutes, quick cooled to 42°C, applied to the slide . Controls include DNA spots labeled with Cy5 (positive control for position and gridding) and Ctenophore cDNA as negative controls.mRNA expression was measured using microarrays where each array had four spatially separated replicates per gene. The 384 tabolism . The annMicroarrays were created by printing cDNAs amplified with amine-linked primers onto 3-D Link Activated slides  at the University of Miami's microarray facility. All printed cDNAs were re-sequenced from the same source used for printing. The microarray slides were scanned using ScanArray Express. The raw TIFF-image data was quantified using Imagene (v5).All experiments used a loop design for hybridization of dye labeled aRNA To test for the relationship between fluorescence and the quantity of RNA, five concentrations of fluorescently labeled RNA were used: 1.2 to 700 pmol of Cy3 or Cy5 labeled mRNA where pmol are for the amount of incorporated dye . A 15 µlFor a gene to be included in an analysis, the average signal among all arrays and dyes had to exceed background but not exceed 95% of PMT saturation . Background signal was determined as the amount of fluorescence in negative control array elements. Not all genes met these criteria and therefore were not included in the analysis.ijkl = μ+Ai+Dj+k+Rl+εijkl where μ is the sample mean, Ai is the effect of the ith array (i = 1–18), Dj is the effect of the jth dye (Cy3 or Cy5), Tk is the effect of the number of rounds of amplification , Rl is the effect of the day on which samples were prepared (l = 3), and epsilon is stochastic effects. The number of rounds of amplification (single or double) and channel variables were treated as fixed effects and array, and day on which samples were prepared were treated as random effects. Statistical analyses of replicate blood samples or repetitive measures of the same five individuals were applied to a separate ANOVA for each individual. The ANOVA model for this comparison was as follows: ymnp = μ+Am+Dn+Tp+εmnp where μ is the sample mean, Am is the effect of the mth array (m = 1–4 for both replicate and repetitive samples), Dn is the effect of the nth dye (Cy3 or Cy5), Tp is the treatment effect and epsilon is stochastic effects. Sample, representative of either one of four temporal samples from an individual or one of four replicate blood samples, and channel were treated as fixed effects. Array was treated as a random effect. Significant differences were evaluated with a p-value cut-off of 0.01.To adjust for systematic variation, gene expression values were first sum normalized, log2 transformed, and then loess normalized using Microarray Data Analysis System Software (MIDAS) F. heteroclitus cDNA microarrays Ctenophore cDNA with no similarity to vertebrate genes).The concentration of fluorescently labeled RNA (0.09 to 47 µM of Cy dye) represents 0.1×, 1×, 5×, 10×, 50× the concentration of RNA typically used on 2>95% and 78 genes had a nearly perfect R2  revealed a non-linear relationship that can be explained by an apparent saturation at the 50× concentration of RNA . In this experiment fewer genes met our criteria of above background and below saturation due to sample RNA being divided for separate labeling using either single and double rounds of amplification. An ANOVA was performed to measure differences between single and double rounds of amino allyl labeled RNA amplification. Twelve of the 110 genes (11%) used in this analysis were significantly different between single and double rounds of amplification at p<0.01. The majority of genes (59%) had a higher fluorescence signal when only one round of amplification was performed.To determine how RNA preparation affects variation, cardiac RNA from three individuals were combined, and then evenly divided and amino allyl and dye labeled on three separate days using single and double rounds of amplification . Only 110 genes met our criteria for inclusion because many genes were below the low cut-off  nuclei are transcriptionally active versus 0.05  have R2 values greater than 0.95 for these four concentrations. The genes most affected by biological saturation do not have a high fluorescence; if anything, they are less than the average . The two possible explanations for biological saturation with low fluorescence are that the synthesis of amino allyl labeled RNA for these genes is strongly truncated or that there is less DNA printed on the array for these genes. Truncation of amino allyl labeling would produce many more short probes with few labels per probe. Thus, to produce a similar fluorescence many more molecules would be necessary and these would saturate the DNA on the array. These problems can be avoided by using moderate amounts of probe (<10 pmol/ul). We typically avoid this problem by using 0.7 to 2 pmol/ul. Using concentrations of RNA up to 50× (47 pmol/ul) is feasible, but our data suggest that at this high of a concentration some genes will biologically saturate the cDNA on the array and therefore should be avoided.There is a linear increase in fluorescence with increasing mRNA for 98.5% of genes between 0.1× to 10× concentrations (0.09 pmol/ul to 9.3 pmol/ul) and 95% of genes between 0.1× to 50× (0.09 pmol/ul to 47 pmol/ul). The linear relationship between RNA and fluorescence is quite strong for RNA concentrations of 0.1× to 10× having average Rversus double labeling is not large, it may be unacceptably high. Thus, we would suggest that for any one experiment that a researcher uses only single or double labeling procedures but not both within an individual experiment. Approximately half (59%) of genes with a significant difference between single and double labeling were greater for single labeling. The greater fluorescence for single labeling than that for double labeling would occur if cDNA or RNA synthesis was truncated with each round of labeling. Truncation would occur if the synthesis of cDNA or RNA were incomplete forming shorter nucleotide sequences with less fluorescence per RNA.If RNA samples are amino allyl labeled using one round of T7-RNA synthesis versus the expected three false positives). If a Bonferroni correction was applied none of these genes would be significant. Therefore, technical errors do not necessarily contribute significant amounts of variation. Similar conclusions were made about microarray results among laboratories: many different laboratories yielded similar results using different varieties of platforms We used blood to test the effect of different RNA isolations, amino allyl labeling and hybridizations. The first experiment used a single blood isolation that was divided into four equal samples. There are few differences in expression, 2.4% at a p-value of 0.01 , gene expression could vary significantly for unknown biological reasons. Yet, for the five individuals there are few, if any, meaningful differences in gene expression (only one individual had more than the expected number of false positives, The microarrays used here have array elements for essential metabolic genes  and are Microarrays are a useful technology for observing differences in gene expression and data extracted from microarrays can be reliably reproduced. With reasonable care, any experiment involving microarrays is capable of obtaining biological data that is not masked by technical variation thereby providing a true representation of the transcriptome under a particular set of conditions. However, caution is required before making conclusions about the biological nature of the data until the sources of technical variation are understood.


Experimental in vitro and animal data support an important role for matrix metalloproteinases (MMPs) in cancer invasion and metastasis via proteolytic degradation of the extracellular matrix (ECM). Our previous data have shown that MMP-9 mRNA is localized to the interface between liver metastasis and normal liver tissue, indicating that MMP-9 may play an important role in liver metastasis formation. In the present study, we analysed the cellular enzymatic expression of MMP-9 in 18 human colorectal cancer (CRC) liver metastasis specimens by enzyme-linked immunosorbent assay (ELISA) and zymography. ELISA analysis reveals that the latent form of MMP-9 is present in both liver metastasis and paired adjacent normal liver tissue. The mean level of the latent form of MMP-9 is 580+/-270 ng per mg total tissue protein (mean+/-s.e.) in liver metastasis vs 220+/-90 in normal liver tissue. However, this difference is not significantly different (P = 0.26). Using gelatin zymography, the 92-kDa band representative of the latent form is present in both liver metastasis and normal liver tissue. However, the 82 kDa band, representative of the active form of MMP-9, was seen only in liver metastasis. This was confirmed by Western blot analysis. Our observation of the unique presence of the active form of MMP-9 within liver metastasis suggests that proMMP-9 activation may be a pivotal event during CRC liver metastasis formation.


Coral reefs are hotspots of biodiversity, yet processes of diversification in these ecosystems are poorly understood. The environmental heterogeneity of coral reef environments could be an important contributor to diversification, however, evidence supporting ecological speciation in corals is sparse. Here, we present data from a widespread coral species that reveals a strong association of host and symbiont lineages with specific habitats, consistent with distinct, sympatric gene pools that are maintained through ecologically-based selection.Seriatopora hystrix, were sampled from three adjacent reef habitats (spanning a ∼30 m depth range) at three locations on the Great Barrier Reef (n = 336). The populations were assessed for genetic structure using a combination of mitochondrial (putative control region) and nuclear (three microsatellites) markers for the coral host, and the ITS2 region of the ribosomal DNA for the algal symbionts (Symbiodinium). Our results show concordant genetic partitioning of both the coral host and its symbionts across the different habitats, independent of sampling location.Populations of a common brooding coral, S. hystrix.This study demonstrates that coral populations and their associated symbionts can be highly structured across habitats on a single reef. Coral populations from adjacent habitats were found to be genetically isolated from each other, whereas genetic similarity was maintained across similar habitat types at different locations. The most parsimonious explanation for the observed genetic partitioning across habitats is that adaptation to the local environment has caused ecological divergence of distinct genetic groups within  Littorina saxatilis comprising genetically distinct ecotypes (with different shell morphologies), which are partitioned over a gradient of tidal height HalichoeresChondrilla, Favia fragumThe tropical marine realm harbors an incredible array of species, with coral reef ecosystems being the iconic epitome of this diversity. Classically, this diversity has been explained through allopatric models of speciation, in which reproductive isolation arises through the physical separation of populations Ecological diversification can arise through various sources of divergent selection , and Ayre et al. Seriatopora hystrix within reefs could be explained by distributions among five shallow reef habitats .Numerous observations indicate that ecological diversification may be important in coral evolution. Firstly, there are many examples where closely related, sympatric species occupy only part of the available habitat, i.e. they occupy a distinct environmental niche Symbiodinium) of scleractinian corals. Various coral species harbor distinct depth-specific symbiont types across their distribution range  and the results were consistent across all investigated loci. In contrast, little to no genetic divergence was found between similar habitats of Yonge Reef and Day Reef, positioned at the edge of the continental shelf on the GBR, and Lizard Island, located mid-shelf . All colonies from the ‘Upper Slope’ habitat at Yonge Reef and Day Reef shared a single host mtDNA haplotype, ‘HostU’ (n = 96), that differed from the ‘Back Reef’ haplotype ‘HostB’ by 4 substitutions. The ‘Deep Slope’ habitat harbored three additional mtDNA haplotypes: ‘HostD1’ (n = 62), ‘HostD2’ (n = 22) and ‘HostD3’ (n = 3); as well as a few ‘HostU’ genotypes (n = 9). The genotypic community structure was significantly different  between habitat types , but not reef locations. Under the AMOVA framework, 83%  of molecular variance was explained by habitat, and only 2% by location .Analyses of the putative control region of the coral mtDNA indicated strong genetic partitioning between the three different habitat types. In contrast, there was no differentiation among the same habitat types at different locations . The mtDSeriatopora caliendrum (Genbank EF633600) and Pocillopora damicornis (Genbank NC009797) as outgroups, supported the monophyly of S. hystrix with high bootstrap support , individual haplotypes corresponded with habitat type and associated symbiont rather than location, even on a broader geographical scale.Phylogenetic analyses  of the putative control region, using  support . The S. Analyses of three nuclear (microsatellite) loci corroborated the differentiation suggested by the mtDNA and revealed a similar pattern of habitat partitioning. A total of 172 unique multilocus genotypes were observed among 200 analyzed samples. Of these multilocus genotypes, 17 were shared between 2 individuals, 4 between 3 individuals, and 1 between 4 individuals. With the exception of one individual, these potential clone mates always occurred within the same habitat and location, and may have resulted from fragmentation.a priori population designations. Analyses were done with and without clonal multilocus genotypes, and rendered near identical patterns of clustering and log probability distributions. The highest log probability was found for K = 4 , as did all the individuals from the ‘Upper Slope’ habitat with mtDNA genotype ‘HostU’. Individuals sampled in the ‘Deep Slope’ habitat with a ‘HostU’ haplotype (n = 6) were assigned to the same group as the ‘Upper Slope’ individuals with the ‘HostU’ genotype (with one exception). All remaining ‘Deep Slope’ samples clustered in two groups corresponding to the haplotypes ‘HostD1’ and ‘HostD2’. The two individuals with a ‘HostD3’ genotype clustered together with ‘HostD2’ individuals . A slightly lower log probability was found for K = 3 .Genetic clustering was first assessed using STRUCTURE v2.2 or K = 3 , which r‘Deep Slope’ habitats were reduced to individuals with a ‘HostD1’ genotype. This was done as STRUCTURE results indicated that the other haplotypes in this habitat  belong to different genetic clusters , as opposed to 5% between locations . Pairwise FST values of populations  corroborated this strong differentiation between habitats (FST = 0.179–0.300), rather than among habitats at different locations , however this genetic structuring was still less than any of the across-habitat pairwise differences (FST = 0.201–0.275). Finally, the subclusters of the ‘Deep Slope’ habitat at Yonge Reef with ‘HostD1’ and ‘HostD2’ haplotypes respectively, were also genetically distinct (FST = 0.179). Linkage disequilibrium (LD) was not detected for any of the loci or population pairwise comparisons. Significant deviation from Hardy-Weinberg equilibrium (HWE) was detected only in the ‘Upper Slope’ habitat at Yonge Reef for the locus Sh2-006, whereas all three loci were in HWE in the remaining populations (IS = 0.0063–0.0793), again with exception of the ‘Upper Slope’ habitat at Yonge Reef  during further analysis under the AMOVA framework, the clusters . Clone mulations . EstimatS. hystrix colonies sampled (Symbiodinium C3n-t Symbiodinium types (except C120) contained 2-3 co-dominant ITS2 sequences within a single profile  or deep habitats (‘Deep Slope’). Approximately 95% of the colonies collected from the shallow habitats (‘Back Reef’ and ‘Upper Slope’) harbored Symbiodinium C120 irrespective of location , with a few ‘Back Reef’ habitat colonies at Day Reef harboring Symbiodinium C120a and C1m-aa (5 and 7 colonies respectively). In contrast, the majority (74%) of colonies from the ‘Deep Slope’ at Yonge Reef and Day Reef hosted Symbiodinium C3n-t (n = 69). The remaining 26% of ‘Deep Slope’ colonies harbored Symbiodinium C3-ff (n = 16) or Symbiodinium C120 (n = 9). Symbiont diversity proved significantly different  between habitats , but not locations. Pairwise comparisons between the various habitat types (One-Way ANOSIM) confirm that the ‘Deep Slope’ habitat is significantly different from ‘Back Reef’  and ‘Upper Slope’ habitat , but that the difference between ‘Back Reef’ and ‘Upper Slope’ is not significant.Specific symbiont types were found in association with Symbiodinium types C120, C120a, and C1m-aa were more closely related to each other than to the ‘deep types’ C3n-t and C3-ff. The shallow Symbiodinium types appeared to have evolved from the ancestral type C1 while the deep Symbiodinium types C3n-t and C3-ff are diverged from C3  Phylogenetic analysis indicated that the shallow Symbiodinium ITS2 types over the host mtDNA data  and C3n-t (27%). Similarly, most colonies with haplotype ‘HostB’ harbored Symbiodinium C120 (92%), but C120a (3%) and C1m-aa (5%) were also observed in low numbers. There was a significant difference (One-way ANOSIM) between the types of Symbiodinium associated with each mtDNA haplotype  as well as the types of mtDNA haplotypes each Symbiodinium type associated with . A further indication of the strong association between host mtDNA and symbiont ITS2 genotypes were the individuals with the shallow water ‘HostU’ haplotype that were found in the deep environment and always contained Symbiodinium C120, common among shallow water colonies.The overlay of the DNA data  showed aDNA data . All S. S. hystrix and its associated Symbiodinium form genetically isolated clusters across distinct reef habitats . There was also strong genetic differentiation across habitats based on microsatellites under the AMOVA framework. Replication of these striking genetic patterns across two distinct reef locations (∼20 km apart) is consistent with local adaptation to distinct habitats followed by non-random mating, as the genetic structure was observed in putative neutral loci. Detectable genetic structure based on linkage disequilibria among microsatellite loci can develop over relatively short timescales, however partitioning based on mitochondrial loci should reflect longer (evolutionary) timescales. As such, the observed partitioning likely reflects long-standing adaptations to the unique environmental conditions of each habitat, such as strong wave action (e.g. ‘Upper Slope’), extreme temperature fluctuations (e.g. ‘Back Reef’) or low-light conditions and cold-water influxes (e.g. ‘Deep Slope’). However, given that various abiotic factors covary between habitats, it is impossible at this time to assess the likely contribution of specific environmental variables to the observed genetic partitioning. Although diversity generally declines with depth in coral species Symbiodinium types The three habitats sampled in this study  ST values ranging from 0.009–0.026 for reefs up to ∼80 km apart. Additionally, genetic similarity was observed between the Ribbon Reefs and a population at Lizard Island (FST = 0.065–0.090). These results are concordant with the genetic similarity observed in this study between Yonge Reef and Day Reef (within habitats) using a subset of the microsatellite loci used by van Oppen et al. ST = 0.012–0.060) and between Yonge Reef, Day Reef and Lizard Island (within habitats) for the mtDNA locus. Thus, despite the highly localized recruitment of S. hystrixEven though populations of S. hystrix. In their allozyme study they reported that a proportion of the within reef variability was explained by variation among five shallow habitat types (FHR = 0.05) on the central GBR. A later study by Sherman HR = 0.009), but did find different levels of inbreeding between habitats . In contrast to most previous studies [44 and references therein], allele frequencies in all other populations approached expectations under HWE. Although local mating would lead to inbreeding, it would not create the replicated associations (at two different reefs) of genotypes and habitats that we observed. By sampling within distinct habitats we seem to have avoided any sign of a Wahlund effect in our data, which may have affected previous studies if distinct ecotypes were present in sample locations. The exception in our study is the ‘Deep Slope’ habitat that does contain multiple distinct genetic groups  may reflect latitudinal variation in surface irradiance and light attenuation (with lower irradiance levels recorded on the southern GBR The observed partitioning of habitats  matches habitats  and coul‘Upper Slope’ and ‘Back Reef’ host mtDNA genotypes (‘HostU’ and ‘HostB’) were found in symbiosis with two closely related shallow symbionts types, C120 and C120a, as well as the rare ‘Back Reef’ symbiont C1m-aa. The two common host genotypes associated with the ‘Deep Slope’ habitat occurred with Symbiodinium types C3n-t and C3-ff  also contained the shallow symbiont C120 instead of any of the deep symbionts  across habitats, but not geographic locations. Similarly, Duran and Rützler Chondrilla) across mangrove and reef habitats, but not geographically distant locations. On a more local scale, Carlon and Budd Favia fragum morpho-types across three sites (up to ∼2 km apart) in the Bocas del Toro region (Panama), consistent with a ‘divergence with gene flow’ model S. hystrix across environmentally distinct habitats, but not between the same habitats at different locations  In the coral reef environment, ecological speciation has been suggested in a few instances, where the general expectation of genetic partitioning according to habitat rather than biogeographical barriers was met. For example, Rocha et al. S. hystrix in the ‘Back Reef’ and especially the ‘Upper Slope’ habitats seemed to have thicker branches (perhaps related to the greater extent of wave action in these habitats) in comparison to ‘Deep Slope’ individuals. Additionally, colonies in the ‘Upper Slope’ habitat were more compacted with shorter and more frequently dividing branches. Previous work by Flot et al. Seriatopora spp.  and specifically report distinct genetic lineages within S. hystrix. Although the taxonomic status of the observed mtDNA lineages will need to be resolved in future molecular and morphological studies , or cryptic species Morphological features were not characterized, but gross morphology was observed to vary between habitats, similar to descriptions of ecotypes described by Veron and Pichot S. hystrixEven though genetic variability between habitats has been previously demonstrated The strong association of host and symbiont genotypes with particular reef environments presents a compelling case for ecological speciation, corroborating previous evidence Collection of the corals was in accordance with the Queensland Animal Care and Protection Act 2001 and the necessary permits were supplied by the Great Barrier Reef Marine Park Authority .S. hystrix colonies were collected (n = 336) on SCUBA from three different habitats: the ‘Back Reef’ (2 m depth ±1 m), ‘Upper Slope’  and ‘Deep Slope’ (27 m depth ±2 m) at two reef locations, Yonge Reef  and Day Reef (14°28′28.4″S/145°32′19.1″E) along the continental shelf edge of the GBR and from a ‘Back Reef’ habitat (2 m) at Lizard Island . The three reef locations are at an approximate distance of 19–25 km from each other  of ch other .‘Back Reef’ habitat (∼2 m) is a shallow water body with strong temperature fluctuations during slack tides when there is little exchange with surrounding waters. The ‘Upper Slope’ (∼6 m) while not experiencing the same temperature fluctuations, faces the Coral Sea and experiences strong wave action from the incoming waves that break onto the reef (Done 1982) as it is located just below the reef crest. The ‘Deep Slope’ (∼27 m) on the other hand, has low irradiance levels compared to the shallow habitats and during summer, experiences slightly lower average temperatures (monthly average during February 2008 was ∼1°C lower) due to influxes of deep, sub-thermocline water . Based on light attenuation data of the adjacent Ribbon Reefs, the proportion of surface irradiance available in the ‘Deep Slope’ habitat is also expected to be up to 10 times lower than in the shallower habitats . Thus, despite their proximity , these habitats offer very distinct environmental conditions to both the coral host and their associated photosymbionts.The S. hystrix based on characters described by Veron Corals were identified as 5′-GTC TGC TCA CAT TAA TTT AT-3′ and SerCtl-R1: 5′-AGA GAT CGA ACT AAG AGT CG-3′. Primers were designed from the published Seriatopora mitogenome (Genbank Accession Number NC010244). PCR amplifications were performed with 0.1–1.0 µl of DNA, 2 µl 10x PCR buffer (Invitrogen), 1.0 µl 50 mM MgCl2, 1 µl 10 mM dNTPs, 1 µl 10 mM SerCtl-F1, 1 µl 10 mM SerCtl-R1, 0.10 µl of Platinum Taq DNA Polymerase (Invitrogen) and dH20 water to a total volume of 20 µl per reaction. The cycling protocol was: 1×94°C (10 min); 30×; 1×72°C (8 min). PCR reactions were purified (using ethanol and ammonium acetate) and sequenced using both forward and reverse, or just the reverse primer . All chromatograms were checked manually and the resulting sequences aligned with Seriatopora caliendrum (Genbank No EF633600) and Pocillopora damicornis (Genbank No EF526302.1), which were subsequently used as outgroups. Modeltest 6 generations, a sample frequency of 100 generations and a “burn-in” of 2500 trees. The individual contributions of habitat and location on genotypic variability were assessed under the AMOVA framework using GenALEx V6 A fragment of the putative control region . Amplification was carried out by PCR incorporating a universal fluorescently labeled M13 primer following Schuelke a priori information about populations  between habitats at the various locations were also calculated. Tests for statistical significance were based on 9,999 random permutations, followed by sequential Bonferroni correction. Linkage disequilibrium and significant deviations from HWE were evaluated using GENEPOP (web version 3.4) Three polymorphic microsatellite loci  with Symbiodinium-specific primers Taq DNA Polymerase (Invitrogen) and dH20 water to a total volume of 20 µl per reaction following LaJeunesse http://www.ncbi.nlm.nih.gov/BLAST/). Maximum parsimony (MP) analysis was run in PAUP* 4.0b10 The internal transcribed spacer (ITS2) region of the rDNA for Symbiodinium types (ITS) were also evaluated using a One-Way ANOSIM. All multivariate statistics were done using the software package PRIMER (v6) Dependence of genetic population structure on habitat and location was assessed for the host (mtDNA) and symbiont (ITS2) in a nested analysis of similarity (Two-way ANOSIM) using Bray-Curtis distance. Pairwise comparisons for each habitat were then performed in a One-Way ANOSIM to test for differences between individual habitats. Associations between host genotypes (mtDNA) and Figure S1Symbiodinium ITS2 rDNA showing the 5 distinct Symbiodinium types found in S. hystrix: C120, C120a, C3n-t, C3-ff, C1m-aa. Characteristic sequences used to identify each symbiont type are shown adjacent to bands in the gel image (note that C3 and C3n co-migrate to the same position).Denaturing gradient gel electrophoresis of (1.71 MB TIF)Click here for additional data file.Table S1Log probabilities L(K) and L' (K) for the likely number of genetic clusters in the microsatellite dataset, using STRUCTURE.(0.05 MB DOC)Click here for additional data file.Table S2Seriatopora hystrix collected from three habitats at two locations (7 populations). The last population consists of the individuals from the ‘Deep Slope’ habitat at Yonge Reef with a ‘HostD2’ mtDNA genotype.Descriptive statistics for three microsatellite loci for (0.07 MB DOC)Click here for additional data file.