Eric Dugat-Bony

Eric Peyretaillade

Nicolas Parisot

Corinne Biderre-Petit

Faouzi Jaziri

David Hill

Sébastien Rimour

Pierre Peyret
email: pierre.peyret@univ-bpclermont.fr

Detecting unknown sequences with DNA microarrays: explorative probe design strategiese mi_2559 356..371

Designing environmental DNA microarrays that can be used to survey the extreme diversity of microorganisms existing in nature, represents a stimulating challenge in the field of molecular ecology. Indeed, recent efforts in metagenomics have produced a substantial amount of sequence information from various ecosystems, and will continue to accumulate large amounts of sequence data given the qualitative and quantitative improvements in the next-generation sequencing methods. It is now possible to take advantage of these data to develop comprehensive microarrays by using explorative probe design strategies. Such strategies anticipate genetic variations and thus are able to detect known and unknown sequences in environmental samples. In this review, we provide a detailed overview of the probe design strategies currently available to construct both phylogenetic and functional DNA microarrays, with emphasis on those permitting the selection of such explorative probes. Furthermore, exploration of complex environments requires particular attention on probe sensitivity and specificity criteria. Finally, these innovative probe design approaches require exploiting newly available high-density microarray formats.

Introduction

The microbial world represents the most important and diverse group of organisms living on earth [START_REF] Whitman | Prokaryotes: The unseen majority[END_REF][START_REF] Curtis | Estimating prokaryotic diversity and its limits[END_REF], comprising most of the diversity of the three domains of life defined by Woese and colleagues (1990): Archaea, Bacteria and Eucarya. Furthermore, these organisms are widely distributed across many environmental habitats, even the most extreme. Their numerous enzymatic machineries have allowed them to adapt to almost every ecological niche and take advantage of any environmental condition [START_REF] Øvreås | Population and community level approaches for analysing microbial diversity in natural environments[END_REF][START_REF] Guerrero | Life's unity and flexibility: the ecological link[END_REF]. Despite our increasing knowledge of the role of microorganisms in ecosystem functioning, our current vision of the microbial world is still incomplete and several issues remain unsolved. This is partially explained (i) by the tremendous diversity of the genes and metabolisms of the existing species but also of ecological niches and (ii) by technological limits such as our inability to culture the majority of microorganisms [START_REF] Amann | Phylogenetic identification and in situ detection of individual microbial cells without cultivation[END_REF][START_REF] Pace | A Molecular View of Microbial Diversity and the Biosphere[END_REF].

Because of this huge microbial biocomplexity, highthroughput molecular tools allowing simultaneous analyses of existing populations are greatly needed [START_REF] Torsvik | Microbial diversity and function in soil: from genes to ecosystems[END_REF][START_REF] Xu | Microbial ecology in the age of genomics and metagenomics: concepts, tools, and recent advances[END_REF]. Massive sequencing based on next-generation sequencing (NGS) technologies and microarrays are currently the most promising and complementary approaches to address these tasks [START_REF] Claesson | Comparative Analysis of Pyrosequencing and a Phylogenetic Microarray for Exploring Microbial Community Structures in the Human Distal Intestine[END_REF][START_REF] Roh | Comparing microarrays and next-generation sequencing technologies for microbial ecology research[END_REF][START_REF] Van Den Bogert | Microarray Analysis and Barcoded Pyrosequencing Provide Consistent Microbial Profiles Depending on the Source of Human Intestinal Samples[END_REF]. Using NGS, two specific strategies can be applied: metagenomics, which refers to the study of the collective genomes in a given environmental community and the 16S rDNA amplicon sequencing approach. In principle, these methods enable: (i) access to the wide diversity of microbial communities, (ii) identification of unknown microorganisms and (iii) the potential to link structure to functions [START_REF] Simon | Achievements and new knowledge unraveled by metagenomic approaches[END_REF]. Some limitations of metagenomics, however, have been demonstrated: for example, the huge difficulty of managing large amounts of sequence data, or the short sequence read length (400-500 bases maximum with 454 FLX Titanium instrument from Roche), which complicates contigs assembling, or the sequencing errors caused by NGS technologies [START_REF] Roh | Comparing microarrays and next-generation sequencing technologies for microbial ecology research[END_REF]. Furthermore, Quince and colleagues (2008) estimated that detecting 90% of the richness in some hyperdiverse environments could require tens of thousands of times the current sequencing effort, which is inconceivable. Oligonucleotide microarray technologies have, however, been widely used for gene detection and gene expression quantification, and more recently, were adapted to profiling environmental communities in a flexible and easy-to-use manner [START_REF] Zhou | Microarrays for bacterial detection and microbial community analysis[END_REF][START_REF] Wagner | Unravelling Microbial Communities with DNA-Microarrays: Challenges and Future Directions[END_REF]. These approaches can monitor the presence, or the expression, of thousands of genes, combining qualitative and quantitative aspects in only one experiment [START_REF] Tiquia | Evaluation of 50-mer oligonucleotide arrays for detecting microbial populations in environmental samples[END_REF][START_REF] Marcelino | Accurately quantifying low-abundant targets amid similar sequences by revealing hidden correlations in oligonucleotide microarray data[END_REF][START_REF] Dugat-Bony | HiSpOD: probe design for functional DNA microarrays[END_REF]. Furthermore, this technology appears well adapted to multi-sample comparison. Although several whole-genome arrays have been developed in the last few years, phylogenetic oligonucleotide arrays (POAs), targeting the 16S rRNA genes, as well as functional gene arrays (FGAs), targeting key genes encoding enzymes involved in metabolic processes, are the two major approaches to assess diversity of microbial communities in the environment [START_REF] Wagner | Unravelling Microbial Communities with DNA-Microarrays: Challenges and Future Directions[END_REF]. Currently, the most comprehensive tools developed are the high-density PhyloChip, with nearly 500 000 oligonucleotide probes to almost 9000 operational taxonomic units [START_REF] Brodie | Application of a high-density oligonucleotide microarray approach to study bacterial population dynamics during uranium reduction and reoxidation[END_REF], and the GeoChip 3.0 with ~28 000 probes covering approximately 57 000 gene variants from 292 functional gene families [START_REF] He | GeoChip 3.0 as a high-throughput tool for analyzing microbial community composition, structure and functional activity[END_REF]. Whereas microarrays were demonstrated as being sufficiently sensitive, with detection of sequences representing genomic material from 0.05% to 5% of the total environmental community [START_REF] Bodrossy | Development and validation of a diagnostic microbial microarray for methanotrophs[END_REF][START_REF] Peplies | Application and validation of DNA microarrays for the 16S rRNA-based analysis of marine bacterioplankton[END_REF][START_REF] Loy | 16S rRNA gene-based oligonucleotide microarray for environmental monitoring of the betaproteobacterial order 'Rhodocyclales[END_REF][START_REF] Gentry | Microarray Applications in Microbial Ecology Research[END_REF][START_REF] Marcelino | Accurately quantifying low-abundant targets amid similar sequences by revealing hidden correlations in oligonucleotide microarray data[END_REF][START_REF] Palmer | Rapid quantitative profiling of complex microbial populations[END_REF][START_REF] Huyghe | Novel Microarray Design Strategy To Study Complex Bacterial Communities[END_REF], these methods require a sequence a priori to determine probes and hence allow surveys only of microorganisms with available sequences in public databases [START_REF] Chandler | Taking arrays from the lab to the field: trying to make sense of the unknown[END_REF][START_REF] Wagner | Unravelling Microbial Communities with DNA-Microarrays: Challenges and Future Directions[END_REF].

The main problem that must be faced to construct oligonucleotide microarrays dedicated to microbial ecology is the probe design step. Indeed, environmental microarrays often require this step to be manually performed. Although numerous general probe design programmes are currently freely accessible for academics [for recent reviews see Lemoine and colleagues (2009)], only few may be useful for microbial ecology applications and are listed in Table 1. This review aims to show how probe design strategies can avoid the limitation of sequence availability and make possible the detection of previously uncharacterized microbial populations present in nature. We emphasize various recent methods combining the use of both degenerate and non-degenerate oligonucleotide probes to target either 16S rRNA markers, or new proteic variants. In conclusion, we highlight other procedures and limitations that must be circumvented, to improve microarray development in terms of specificity and sensitivity.

General criteria for probe design

In silico probe design is one of the most critical step for microarray experiments because the selected oligonucleotide probe set will have to combine: (i) sensitivity (e.g. probes should detect low abundance targets in complex mixtures), (ii) specificity (e.g. probes should not crosshybridize with non-target sequences) and (iii) uniformity (e.g. probes should display similar hybridization behaviour) [START_REF] Loy | Highly parallel microbial diagnostics using oligonucleotide microarrays[END_REF][START_REF] Wagner | Unravelling Microbial Communities with DNA-Microarrays: Challenges and Future Directions[END_REF].

According to Lemoine and colleagues (2009), this process requires dealing with many parameters and currently available probe design programmes differ in the choice of criteria that are considered to select the best probe set (Table 2).

Sensitivity

The sensitivity generally increases with probe length, as the binding energy for longer probe-target hybrid complexes is typically higher and hybridization kinetics are irreversible [START_REF] Hughes | Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer[END_REF][START_REF] Relogio | Optimization of oligonucleotide-based DNA microarrays[END_REF][START_REF] Letowski | Designing better probes: effect of probe size, mismatch position and number on hybridization in DNA oligonucleotide microarrays[END_REF]. For example, probes of 60 mers can detect targets with eightfold higher sensitivity than those of 25 mers [START_REF] Chou | Optimization of probe length and the number of probes per gene for optimal microarray analysis of gene expression[END_REF]. However, their threshold for differentiation is at 75-90% sequence similarity [START_REF] Kane | Assessment of the sensitivity and specificity of oligonucleotide (50mer) microarrays[END_REF][START_REF] Taroncher-Oldenburg | Oligonucleotide microarray for the study of functional gene diversity in the nitrogen cycle in the environment[END_REF][START_REF] Tiquia | Evaluation of 50-mer oligonucleotide arrays for detecting microbial populations in environmental samples[END_REF], which indicates a poor specificity [START_REF] Li | Selection of optimal oligonucleotide probes for microarrays using multiple criteria, global alignment and parameter estimation[END_REF]. In contrast, short oligonucleotide probes are more specific, allowing discrimination of single nucleotide polymorphisms under optimal conditions, but at the cost of reduced sensitivity [START_REF] Relogio | Optimization of oligonucleotide-based DNA microarrays[END_REF]. Furthermore, the formation of stable secondary self-structures like stem-loops, hairpins and probe-toprobe dimerization by the probes or their targets is another crucial factor that must be considered to minimize loss of microarray sensitivity. However, despite a good knowledge of the thermodynamic properties of nucleic acid duplex formation and dissociation in solution [START_REF] Santalucia | Improved nearest-neighbor parameters for predicting DNA duplex stability[END_REF] and the availability of several algorithms like Mfold [START_REF] Zuker | Mfold web server for nucleic acid folding and hybridization prediction[END_REF] or Hyther [START_REF] Bommarito | Thermodynamic parameters for DNA sequences with dangling ends[END_REF] for their accurate prediction, these calculations should be treated cautiously in the microarray context due to the limited knowledge on the thermodynamics of hybridization at solid-liquid interfaces [START_REF] Pozhitkov | Tests of rRNA hybridization to microarrays suggest that hybridization characteristics of oligonucleotide probes for species discrimination cannot be predicted[END_REF]2007).

Specificity

The specificity of microarray hybridization is one of the main effectors of the result quality [START_REF] Kane | Assessment of the sensitivity and specificity of oligonucleotide (50mer) microarrays[END_REF][START_REF] Evertsz | Hybridization cross-reactivity within homologous gene families on glass cDNA microarrays[END_REF][START_REF] Koltai | Specificity of DNA microarray hybridization: characterization, effectors and approaches for data correction[END_REF]. Therefore, it is crucial that oligonucleotide probes must be unique with respect to all non-target sequences. To check probe specificity, software usually use results produced by algorithms such as BLAST or suffix array method, to search for cross-hybridization against databases constructed in accordance with the microarray application. In this step, potential cross-hybridization prediction are usually based on Kane's recommendations (probe should not have a total percent identity > 75-80% with a nontarget sequence, or contiguous stretches of identity > 15 nt with a non-target sequence) [START_REF] Kane | Assessment of the sensitivity and specificity of oligonucleotide (50mer) microarrays[END_REF] or thermodynamics calculations (duplex's stability between the probe and the non-target sequence). Moreover, lowcomplexity regions such as those containing long homopolymers may also contribute to affect probe specificity and must therefore be avoided for probe design [START_REF] Wang | Selection of oligonucleotide probes for protein coding sequences[END_REF][START_REF] Leparc | Model-based probe set optimization for high-performance microarrays[END_REF].

Uniformity

Because microarray technology relies on the simultaneous hybridization of many probes under the same conditions (salt concentration, temperature, etc.), it is important to ensure that the selected probes have thermodynamic behaviours as uniform as possible [START_REF] Loy | Highly parallel microbial diagnostics using oligonucleotide microarrays[END_REF][START_REF] Wagner | Unravelling Microbial Communities with DNA-Microarrays: Challenges and Future Directions[END_REF]. The easiest way to achieve this is to select probes with homogeneous structural properties such as probe length, G + C content, melting temperature (T m) or binding capacities (DG).

Characterization of environmental species with POAs

The classical way to characterize members of complex bacterial communities relies on the small subunit ribosomal RNA gene (16S rRNA) analysis. This target is particularly well adapted to phylogenetic studies as it contains highly conserved and variable moieties permitting reliable and detailed bacterial classification. Moreover, the advent of many PCR-based approaches, as well as sequencing projects, has led to the explosion of 16S rRNA gene sequences now available in major specialized sequence repositories, such as SILVA [START_REF] Pruesse | SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB[END_REF], Greengenes [START_REF] Desantis | Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB[END_REF] and the Ribosomal Database Project (RDP) [START_REF] Cole | The Ribosomal Database Project: improved alignments and new tools for rRNA analysis[END_REF].

In order to rapidly survey prokaryotic communities present in complex environments high-throughput tools have been developed, such as POAs using the SSU rRNA biomarker [START_REF] Wilson | High-Density Microarray of Small-Subunit Ribosomal DNA Probes[END_REF][START_REF] Brodie | Application of a high-density oligonucleotide microarray approach to study bacterial population dynamics during uranium reduction and reoxidation[END_REF][START_REF] Palmer | Rapid quantitative profiling of complex microbial populations[END_REF][START_REF] Desantis | High-density universal 16S rRNA microarray analysis reveals broader diversity than typical clone library when sampling the environment[END_REF]. The main obstacle in designing a POA, however, is potential crosshybridization. In many cases, the 16S rRNA genes of the type species are too conserved to allow the design of discriminatory probes [START_REF] Bae | Homogeneous versus heterogeneous probes for microbial ecological microarrays[END_REF]. To circumvent this problem, a hierarchical design allows probing for microbial taxa at different phylogenetic levels [START_REF] Huyghe | Novel Microarray Design Strategy To Study Complex Bacterial Communities[END_REF][START_REF] Liles | A phylogenetic microarray targeting 16S rRNA genes from the bacterial division Acidobacteria reveals a lineage-specific distribution in a soil clay fraction[END_REF], providing information on the presence or absence of the branches and the twigs on the Tree of Life.

Probe design for POA

Both fully automated software and manual approaches have been developed to design POAs, taking into account the main criteria for efficient probe design, which are sensitivity and specificity. Currently, three programmes have been developed to work with structured data for retrieving and analysing sequences from dedicated databases and to operate a phylogenetic probe design targeting the 16S rRNA gene. The first programme is the Probe Design tool included in the ARB programme package [START_REF] Ludwig | ARB: a software environment for sequence data[END_REF] which is commonly used to select 10-100 mer oligonucleotides. The first step in the programme consists of the target group selection. Second, the algorithm identifies unique sequence stretches that could serve as target sites, and subsequently returns a sorted list of potential oligonucleotides. Third, the suggested probes can be matched against all sequences in the database using the Probe Match software programme. ARB also proposes different sets of predefined probes, each targeting distinct phylogenetic groups. It has been widely used to develop low-density custom-made POAs, containing up to a few hundred oligonucleotide probes. These probes usually target either restricted microorganism groups known to perform a specific metabolism [START_REF] Loy | Oligonucleotide microarray for 16S rRNA gene-based detection of all recognized lineages of sulfatereducing prokaryotes in the environment[END_REF][START_REF] Kelly | DNA microarray detection of nitrifying bacterial 16S rRNA in wastewater treatment plant samples[END_REF][START_REF] Franke-Whittle | Design and development of the ANAEROCHIP microarray for investigation of methanogenic communities[END_REF], or belonging to a specific taxon [START_REF] Castiglioni | Development of a universal microarray based on the ligation detection reaction and 16S rrna gene polymorphism to target diversity of cyanobacteria[END_REF][START_REF] Lehner | Oligonucleotide microarray for identification of Enterococcus species[END_REF][START_REF] Loy | 16S rRNA gene-based oligonucleotide microarray for environmental monitoring of the betaproteobacterial order 'Rhodocyclales[END_REF][START_REF] Kyselkova | Development of a 16S rRNA gene-based prototype microarray for the detection of selected actinomycetes genera[END_REF][START_REF] Schonmann | 16S rRNA genebased phylogenetic microarray for simultaneous identification of members of the genus Burkholderia[END_REF][START_REF] Liles | A phylogenetic microarray targeting 16S rRNA genes from the bacterial division Acidobacteria reveals a lineage-specific distribution in a soil clay fraction[END_REF], or living in a habitat/ ecosystem of particular interest [START_REF] Neufeld | Composition of microbial communities in hexachlorocyclohexane (HCH) contaminated soils from Spain revealed with a habitat-specific microarray[END_REF][START_REF] Sanguin | Rhizosphere bacterial communities associated with disease suppressiveness stages of take-all decline in wheat monoculture[END_REF]. To illustrate this purpose, Sanguin and colleagues (2009) identified multiple changes in rhizobacterial community composition associated with the decline of take-all disease of wheat caused by the soilborne fungus Gaeumannomyces graminis by using a taxonomic 16S rRNA-based microarray targeting both Bacteria, Archaea and the OP11 and OP2 candidate divisions. ARB has also been used to construct phylogenetic microarrays based on other biomarkers such as protein coding genes [START_REF] Bodrossy | Development and validation of a diagnostic microbial microarray for methanotrophs[END_REF][START_REF] Duc | Development and experimental validation of a nifH oligonucleotide microarray to study diazotrophic communities in a glacier forefield[END_REF].

The second programme is the PRIMROSE programme [START_REF] Ashelford | PRIM-ROSE: a computer program for generating and estimating the phylogenetic range of 16S rRNA oligonucleotide probes and primers in conjunction with the RDP-II database[END_REF], which uses standard or custom databases, and allows the design of degenerate probes. Initially, a multiple alignment is produced using all the different sequences representing a given taxon. Every probe is subsequently tested against all the sequences of the initial database, to characterize potential crosshybridizations and to verify good coverage of the targeted taxon. Although this tool was developed to identify both phylogenetic probes and primers, it has been mainly applied to PCR-based and FISH (fluorescent in situ hybridization) approaches [START_REF] Rusch | Order-specific 16S rRNAtargeted oligonucleotide probes for (hyper)thermophilic archaea and bacteria[END_REF][START_REF] Yu | Group-specific primer and probe sets to detect methanogenic communities using quantitative real-time polymerase chain reaction[END_REF][START_REF] Feldhaar | Nutritional upgrading for omnivorous carpenter ants by the endosymbiont Blochmannia[END_REF][START_REF] Boeckaert | Accumulation of trans C18:1 fatty acids in the rumen after dietary algal supplementation is associated with changes in the Butyrivibrio community[END_REF][START_REF] Klitgaard | Evidence of multiple Treponema phylotypes involved in bovine digital dermatitis as shown by 16S rRNA gene analysis and fluorescence in situ hybridization[END_REF][START_REF] Muhling | Improved group-specific PCR primers for denaturing gradient gel electrophoresis analysis of the genetic diversity of complex microbial communities[END_REF][START_REF] Gittel | Prokaryotic community structure and sulfate reducer activity in water from high-temperature oil reservoirs with and without nitrate treatment[END_REF][START_REF] Fraune | In an early branching metazoan, bacterial colonization of the embryo is controlled by maternal antimicrobial peptides[END_REF][START_REF] Bers | A molecular toolbox to estimate the number and diversity of Variovorax in the environment: application in soils treated with the phenylurea herbicide linuron[END_REF]. Few applications of POAs using PRIMROSE have been reported. [START_REF] Blaskovic | Oligo-chip based detection of tick-borne bacteria[END_REF] reported the development of a user-friendly chip to specifically detect tick-borne bacteria responsible of human and animal diseases.

Nevertheless, neither of these two applications is built specifically for the determination of discriminating positions within a set of very similar sequences. The third programme is ORMA (Oligonucleotide Retrieving for Molecular Applications), which represents a good alternative solution [START_REF] Severgnini | ORMA: a tool for identification of species-specific variations in 16S rRNA gene and oligonucleotides design[END_REF]. This programme designs and selects oligonucleotide probes for molecular application experiments on sets of highly similar sequences. Although it was first applied to the design of probes targeting 16S rRNA genes, this software can be used on any set of highly correlated sequences, such as new potential phylogenetic biomarkers. Using this programme, Candela and colleagues (2010) designed the HTF-Microbi.Array allowing high taxonomic level fingerprinting of the human intestinal microbial community.

In parallel, other computational approaches not implemented under fully automated software were developed to design high-density POAs (thousands of oligonucleotide probes) allowing a comprehensive screening for all known bacterial or archaeal taxa with a single microarray [START_REF] Wilson | High-Density Microarray of Small-Subunit Ribosomal DNA Probes[END_REF][START_REF] Desantis | High-density universal 16S rRNA microarray analysis reveals broader diversity than typical clone library when sampling the environment[END_REF]. These approaches rely on sophisticated algorithms for the design of a multitude of probes and for the analyses of highly complex hybridization patterns. The best example is the PhyloChip developed by Brodie and colleagues (2006), which contains 500 000 probes based on the Affymetrix GeneChip platform. This tool is able to simultaneously identify thousands of taxa present in an environmental sample and has been applied to characterize prokaryotic communities from ecosystems such as urban atmosphere [START_REF] Brodie | Urban aerosols harbor diverse and dynamic bacterial populations[END_REF], grassland soils [START_REF] Cruz-Martinez | Despite strong seasonal responses, soil microbial consortia are more resilient to long-term changes in rainfall than overlying grassland[END_REF][START_REF] Deangelis | Selective progressive response of soil microbial community to wild oat roots[END_REF], Antarctic soils [START_REF] Yergeau | Environmental microarray analyses of Antarctic soil microbial communities[END_REF], mining-impacted soils (Rastogi et al., 2010a,b), metal-contaminated river sediments [START_REF] Rastogi | Investigation of Microbial Populations in the Extremely Metal-Contaminated Coeur d'Alene River Sediments[END_REF], terrestrial volcanic glasses [START_REF] Kelly | Bacterial diversity of weathered terrestrial Icelandic volcanic glasses[END_REF], rhizosphere of potato [START_REF] Weinert | PhyloChip hybridization uncovered an enormous bacterial diversity in the rhizosphere of different potato cultivars: many common and few cultivardependent taxa[END_REF], citrus leaf [START_REF] Sagaram | Bacterial diversity analysis of Huanglongbing pathogen-infected citrus, using Phylo-Chip arrays and 16S rRNA gene clone library sequencing[END_REF], endotracheal aspirates from patients colonized by Pseudomonas aeruginosa [START_REF] Flanagan | Loss of bacterial diversity during antibiotic treatment of intubated patients colonized with Pseudomonas aeruginosa[END_REF], and pearly eyed thrasher eggs [START_REF] Shawkey | Avian incubation inhibits growth and diversification of bacterial assemblages on eggs[END_REF]. Recently, due to increased interest in microbes of human and animal gastrointestinal tracts, a number of high-density microarrays were also developed to study the composition and activity of intestinal microbiota [START_REF] Palmer | Rapid quantitative profiling of complex microbial populations[END_REF][START_REF] Paliy | High-throughput quantitative analysis of the human intestinal microbiota with a phylogenetic microarray[END_REF][START_REF] Rajilic-Stojanovic | Development and application of the human intestinal tract chip, a phylogenetic microarray: analysis of universally conserved phylotypes in the abundant microbiota of young and elderly adults[END_REF].

The main limitation of all the strategies proposed for 16S rRNA probe design is that they only ensure the survey of known microorganisms with available sequences in public databases. Unfortunately, the vast majority of microbial species is still unidentified and, therefore, is not represented by sequences in public ribosomal rRNA databases. A major challenge for the future is improvement of microarray technology to, in part, rely on new strategies for the design of explorative probes targeting sequences, which have not yet been described.

Explorative probe design strategies for POA

The 'multiple probe concept' consists of using several probes targeting an organism at similar and different phylogenetic/taxonomic levels. Designing probes using this concept significantly reduces the risk of misidentification, and often allows discrimination of bacteria down to the species level [START_REF] Ludwig | rRNA based identification and detection systems for rhizobia and other bacteria[END_REF][START_REF] Loy | Highly parallel microbial diagnostics using oligonucleotide microarrays[END_REF][START_REF] Schliep | Decoding non-unique oligonucleotide hybridization experiments of targets related by a phylogenetic tree[END_REF][START_REF] Huyghe | Novel Microarray Design Strategy To Study Complex Bacterial Communities[END_REF][START_REF] Schonmann | 16S rRNA genebased phylogenetic microarray for simultaneous identification of members of the genus Burkholderia[END_REF][START_REF] Liles | A phylogenetic microarray targeting 16S rRNA genes from the bacterial division Acidobacteria reveals a lineage-specific distribution in a soil clay fraction[END_REF]. Arrays constructed using this concept may ensure the detection of unknown taxa using probes defined from known higher phylogenetic levels. Because such probes are strictly complementary to available sequences, however, they do not harbour the explorative power to detect microorganisms with uncharacterized phylogenetic signatures.

Currently, the only software dedicated to POAs offering the possibility of designing explorative probes, is the Phyl-Array programme [START_REF] Militon | PhylArray: phylogenetic probe design algorithm for microarray[END_REF] This algorithm generates 16S rRNA probes to globally monitor known and unknown bacterial communities in complex environments. The first step in the design is the extraction of all available sequences corresponding to a given taxon from a custom 16S rRNA curated database. Second, a multiple sequence alignment is performed using the ClustalW algorithm [START_REF] Thompson | CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice[END_REF]. Third, a degenerate consensus sequence is produced taking into account sequence variability at each position, which allows the selection of degenerate probes. Finally, all combinations from each degenerate probe are checked for crosshybridization against the 16S rRNA database. Among the combinations derived from each degenerate probe, some correspond to sequences not previously included in public databases (Fig. 1). They should, therefore, allow for the exploration of the as yet undescribed fraction of environmental microbial communities. Moreover, comparative experimental evaluations indicate that probes designed with PhylArray yield a higher sensitivity and specificity than those designed with the PRIMROSE and ARB strat-egies [START_REF] Militon | PhylArray: phylogenetic probe design algorithm for microarray[END_REF]. Recently, a microarray designed with the PhylArray strategy has been employed to evaluate the bacterial diversity in two different soils [START_REF] Delmont | Accessing the soil metagenome for studies of microbial diversity[END_REF]. The authors highlighted the significant influence of several parameters like sampling depth or DNA extraction protocols on the biodiversity estimation.

Detection of functional signatures for FGA design

Assessing the metabolic potential of microorganisms in natural ecosystems is an interesting goal in microbial ecology. In fact, some authors estimate that individual environmental samples, like soil, may contain between 10 3 and 10 7 different bacterial genomes [START_REF] Curtis | Estimating prokaryotic diversity and its limits[END_REF][START_REF] Gans | Computational improvements reveal great bacterial diversity and high metal toxicity in soil[END_REF], each of them harbouring thousands of genes. In this context, high-density oligonucleotide FGAs provide the best high-throughput tools to access this tremendous genetic content [START_REF] He | Development and application of functional gene arrays for microbial community analysis[END_REF]. GeoChips, composed of 50 mer probes designed with CommOligo [START_REF] Li | Selection of optimal oligonucleotide probes for microarrays using multiple criteria, global alignment and parameter estimation[END_REF], are currently the most comprehensive FGAs. Indeed, these microarrays have evolved over several generations and now target key genes involved in most microbial functional processes such as carbon, nitrogen, phosphorus and sulfur cycles, energy metabolism, antibiotic resistance, metal resistance and organic contaminant degradation [START_REF] Rhee | Detection of genes involved in biodegradation and biotransformation in microbial communities by using 50-mer oligonucleotide microarrays[END_REF][START_REF] He | GeoChip: a comprehensive microarray for investigating biogeochemical, ecological and environmental processes[END_REF]2010;2011). However, being able to encompass the full diversity of gene family sequences encountered in nature, described in databanks or not, is still one of the most difficult challenges for the future. Most FGAs described to date only monitor sequences available in databases and, therefore, cannot appraise the unknown part of the microbial gene diversity present in complex environments. A more extensive coverage of the probe set is, therefore, crucial and designing explorative probes represents a pertinent and essential approach.

Characterization of new functional signatures from nucleic sequence alignment

Many probe design programmes are currently freely accessible for academics [for recent reviews see Lemoine and colleagues (2009)]. Most of them were developed for use on single-genome datasets, and hence, are limited to the determination of probes targeting specific gene sequences (Table 2). In contrast, few strategies offer the opportunity to design probes allowing a broad coverage of multiple sequence variants for a given gene family.

With the availability of more and more sequences corresponding to functional genes (complete genome sequencing and environmental studies from specific functional markers), new programmes have been developed in the last decade taking into account this wide diversity. Hierarchical Probe Design (HPD) was the first programme dedicated to functional oligonucleotide determination based on the concept of cluster-specific probes [START_REF] Chung | Design of long oligonucleotide probes for functional gene detection in a microbial community[END_REF]. The first step of the programme consists of the alignment and hierarchical clustering of input sequences in order to generate all possible candidate probes. The optimal probe set is subsequently determined according to probe quality criteria, including cluster coverage, specificity, GC content and hairpin energy. Although this tool is not explorative, it automatically produces probes against all nodes of the clustering tree, providing an extensive coverage of known variants from a conserved functional gene. Using this programme, Rinta-Kanto and colleagues (2011) developed a taxon-specific microarray targeting sulfur-related gene transcription in members of Roseobacter clade, using data from 13 genome sequences. This FGA consisted of 1578 probes to 431 genes and was applied to the study of diverse natural Roseobacter communities. The results revealed that dimethylsulfoniopropionate was not preferred over other organic carbon and sulfur substrates by these populations.

ProDesign, developed by [START_REF] Feng | A fast and flexible approach to oligonucleotide probe design for genomes and gene families[END_REF], uses similar clustering methods with the aim of detecting all members of a same gene family in environmental samples. But, unlike HPD, this software uses spaced seed hashing, rather than a suffix tree algorithm, in order to benefit from permitted mismatches between a probe and its targets, and ensures the re-clustering of groups for which no probe was found. This results in a significant improvement in sequence coverage. As with HPD, however, this tool does not provide probes targeting uncharacterized nucleic acid sequences. In addition, to the best of our knowledge, no application using this design strategy has been reported in literature.

Although both of these strategies allow a wider range of sequence variants to be covered, and, therefore, appear best suited to describe microbial communities from complex environments, their main drawbacks are their inability to generate explorative probes and the absence of specificity tests (i.e. searching for potential cross-hybridizations) against large databases representative of microbial diversity. Recently, an efficient functional microarray probe design algorithm, called HiSpOD (High Specific Oligo Design), was proposed to overcome this problem [START_REF] Dugat-Bony | HiSpOD: probe design for functional DNA microarrays[END_REF]. It is particularly useful for studying microbial communities in their environmental context. HiSpOD takes into account classical parameters for the design of effective probes (probe length, Tm, GC%, complexity) and combines supplemental properties not considered by previous programmes. First, it can allow for the design of degenerate probes for gene families after multiple alignments of nucleic sequences belonging to the same gene family, and the production of consensus sequences. All combinations deduced from these degenerate probes are then divided into two groups. The first corresponds to specific probes for sequences available in databanks, and the second to explorative probes, which represent potential new signatures not corresponding to any previously described microorganisms (Fig. 2A). Both the probe sets covering the most likely gene sequence variants and those covering new combinations not yet deposited in databanks are created based on multiple mutation events already identified. Second, the specificity of all selected probes is checked against a large formatted database dedicated to microbial communities, the EnvExBase (Environmental Expressed sequences data-Base) composed of all coding DNA sequences (CDSs) from Prokaryotes (PRO), Fungi (FUN) and Environmental (ENV) taxonomic divisions of the EMBL databank, in order to limit cross-hybridizations. To validate this strategy, a microarray focusing on the genes involved in chloroethene solvent biodegradation was developed as a model system and enabled the identification of active cooperation between Sulfurospirillum and Dehalococcoides populations in the decontamination of a polluted groundwater [START_REF] Dugat-Bony | HiSpOD: probe design for functional DNA microarrays[END_REF].

Use of protein sequence signatures for probe design

Unlike the strategies outlined above, a number of new strategies have been proposed to initiate probe design not from nucleic acid sequences, but from conserved peptidic regions, in order to survey all potential nucleic acid variants.

The first strategy based on this principle was described by Bontemps and colleagues (2005) and called CODEH-MOP (for COnsensus DEgenerate Hybrid Motif Oligonucleotide Probe). It comes from an adaptation of the CODEHOP (for COnsensus DEgenerate Hybrid Oligonucleotide Primer) PCR primer design strategy, originally developed to identify distantly related genes encoding proteins that belong to known families [START_REF] Rose | Consensusdegenerate hybrid oligonucleotide primers for amplification of distantly related sequences[END_REF]2003;[START_REF] Boyce | iCODEHOP: a new interactive program for designing COnsensus-DEgenerate Hybrid Oligonucleotide Primers from multiply aligned protein sequences[END_REF]. In the CODEHMOP strategy, conserved amino acid motifs are identified from multiple alignments of protein sequences. Then, all possible nucleic combinations (15-21 nucleotides) from the most highly conserved region (5-7 amino acids) of each protein motif are recreated and flanked by 5′ and 3′ fixed ends (12-15 nucleotides each), derived from the most frequent nucleotide at each position. The final probes are called 'hybrids', as they consist of a variable central core, to target a larger diversity, with some nucleic combinations not corresponding to any yet described sequences, and two fixed end sequences (available in databanks) added to increase probe length. The authors used this approach to design a prototype DNA array covering all described and undescribed nodC (nodulation gene) sequences in bacteria, and applied it to legume nodules [START_REF] Bontemps | Microarray-based detection and typing of the Rhizobium nodulation gene nodC: potential of DNA arrays to diagnose biological functions of interest[END_REF]. This strategy allowed the authors to detect new nodC sequences exhibiting less than 74% identity with known sequences.

The application of the CODEHMOP strategy is limited by the fact that it is not implemented into a fully automated programme and no probe specificity test is incorporated. Nevertheless, this approach appears to be the most comprehensive way of encompassing the larger diversity of gene sequence variants potentially found for enzymes mediating a given function. Furthermore, Terrat and colleagues (2010) developed a new software programme called Metabolic Design, which ensures in silico reconstruction of metabolic pathways, the identification of conserved motifs from protein multiple alignments and the generation of efficient explorative probes through a simple convenient graphical interface. In this case, before the probe design stage, the user reconstructs the chosen metabolic pathway in silico with all substrates and products from each metabolic step. One reference enzyme for each of these steps is selected and its protein sequence extracted from a curated database (by default, Swiss-Prot), which is then used to retrieve all homologous proteins from complete databases (Swiss-Prot and TrEMBL). After selecting the most pertinent homologous sequences, they are aligned to begin the probe design stage. The amino acids are back-translated for each molecular site identified, taking into account all genetic code redundancy, to produce a degenerate nucleic consensus sequence. All degenerate probes that meet the criteria defined by the user are retained (probe length and maximal degeneracy). All the specific possible combinations for each degenerate probe are subsequently checked for potential cross-hybridizations against a representative database (i.e. EnvExBase as in the HiSpOD programme). Finally, an output file, listing all degenerate probes selected by the user, permits the deduction of all possible combinations and organizes them into specific probes and exploratory probes (Fig. 2B). The approach was validated by studying enzymes involved in the degradation of polycyclic aromatic hydrocarbons [START_REF] Terrat | Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray development[END_REF].

Towards circumventing microarray limitations

Despite the emergence of new design strategies, such as those presented above, the determination of a highquality probe set appears to be crucial, especially in an environmental ecology context [START_REF] Liebich | Improvement of oligonucleotide probe design criteria for functional gene microarrays in environmental applications[END_REF][START_REF] Leparc | Model-based probe set optimization for high-performance microarrays[END_REF]. Although explorative potential represents a major criterion for fingerprint determination, other parameters also impact considerably on probe sensitivity and specificity, and, therefore, require particular attention [START_REF] Zhou | Microarrays for bacterial detection and microbial community analysis[END_REF][START_REF] Wagner | Unravelling Microbial Communities with DNA-Microarrays: Challenges and Future Directions[END_REF].

Optimization of probe size criterion

Generally, POAs employed for microbial community analysis contain short probes (typically 24-25 mers) [START_REF] Brodie | Application of a high-density oligonucleotide microarray approach to study bacterial population dynamics during uranium reduction and reoxidation[END_REF][START_REF] Paliy | High-throughput quantitative analysis of the human intestinal microbiota with a phylogenetic microarray[END_REF][START_REF] Rajilic-Stojanovic | Development and application of the human intestinal tract chip, a phylogenetic microarray: analysis of universally conserved phylotypes in the abundant microbiota of young and elderly adults[END_REF], whereas FGAs are built either with short (15-30 mers) [START_REF] Bodrossy | Development and validation of a diagnostic microbial microarray for methanotrophs[END_REF][START_REF] Stralis-Pavese | Optimization of diagnostic microarray for application in analysing landfill methanotroph communities under different plant covers[END_REF] or long oligonucleotides (40-70 mers) [START_REF] Kane | Assessment of the sensitivity and specificity of oligonucleotide (50mer) microarrays[END_REF][START_REF] Relogio | Optimization of oligonucleotide-based DNA microarrays[END_REF][START_REF] He | GeoChip: a comprehensive microarray for investigating biogeochemical, ecological and environmental processes[END_REF]. The main limitation of microarrays based on short oligonucleotide probes, therefore, is the need to use, in most cases, PCR-amplified targets to ensure enrichment and thereby increase sensitivity, but this also introduces an inherent PCR bias [START_REF] Suzuki | Bias caused by template annealing in the amplification of mixtures of 16S rRNA genes by PCR[END_REF][START_REF] Peplies | Application and validation of DNA microarrays for the 16S rRNA-based analysis of marine bacterioplankton[END_REF][START_REF] Vora | Nucleic acid amplification strategies for DNA microarray-based pathogen detection[END_REF].

An alternative approach to design oligonucleotide probes, which combines excellent specificity with a potentially high sensitivity, is the use of the GoArrays strategy developed by Rimour and colleagues (2005) (software available at http://g2im.u-clermont1.fr/serimour/goarrays. html). In this approach, the oligonucleotide probe consists of the concatenation of two short subsequences that are complementary to disjoined regions of the target, with an insertion of a short random linker (e.g. 3-6 mer) (Fig. 3). This strategy has been shown to improve microarray efficiency for a wide range of applications [START_REF] Rimour | GoArrays: highly dynamic and efficient microarray probe design[END_REF][START_REF] Zhou | A strategy to optimize the oligo-probes for microarray-based detection of viruses[END_REF][START_REF] Pariset | Microarrays and high-throughput transcriptomic analysis in species with incomplete availability of genomic sequences[END_REF][START_REF] Kang | Dysbiosis of fecal microbiota in Crohn's disease patients as revealed by a custom phylogenetic microarray[END_REF].

Specificity improvement using large databases

Because only a small portion of the natural microbial diversity has been identified, it is a major challenge to design appropriate probes specific to unique markers that do not cross-hybridize with similar unknown sequences [START_REF] Chandler | Taking arrays from the lab to the field: trying to make sense of the unknown[END_REF]. Most of the currently available probe design software have been developed for nonenvironmental applications and performs specificity tests only against a reduced set of sequences, such as wholegenome data or specific sets of genes [START_REF] Lemoine | An evaluation of custom microarray applications: the oligonucleotide design challenge[END_REF]. The study of microbial communities, however, requires dedicated databases that are as representative as possible of all non-target sequences potentially present in environmental samples. GenBank (Benson et al., 2011), European Nucleotide Archive (ENA) [START_REF] Leinonen | The European Nucleotide Archive[END_REF] and the DNA Data Bank of Japan (DDBJ) [START_REF] Kaminuma | DDBJ progress report[END_REF] are the most complete nucleic sequence databases publicly available to perform specificity tests. Dealing with such databases, however, is too time-consuming for probe design task, and, in this instance not really appropriate as some subsets of these databases correspond to sequences from organisms such as Metazoa, which are typically not considered in microbial ecology. Furthermore, for studies focusing on particular biomarkers, other sequence information need not to be considered.

For example, within POAs, each probe must be specific with respect to all small subunit (SSU) rRNA sequences, which may be present in the sample during hybridization. Curated and dedicated secondary databases have been already constructed [RDP [START_REF] Cole | The Ribosomal Database Project: improved alignments and new tools for rRNA analysis[END_REF]), Greengenes (DeSantis et al., 2006) and SILVA [START_REF] Pruesse | SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB[END_REF]], assembling all SSU rRNA sequences described on public databases. The differences between these databases come from the construction and update pipelines that lead to distinct sizes: SILVA (Release 104) contains 1 304 069 16S rRNA sequences, RDP (Release 10) 1 545 680 and Greengenes (03/22/2011) 855 446. These large databases, therefore, are well adapted to phylogenetic probe design. PhylArray software [START_REF] Militon | PhylArray: phylogenetic probe design algorithm for microarray[END_REF] was developed before these databases were publicly available, and, therefore, uses its own highly curated (full length and quality filtered) and automatically updated prokaryotic SSU rRNA database (122 337 sequences for the last release).

Because environmental FGAs target coding sequences (CDS), the database used for specificity tests must include all known CDSs that may be encountered in natural environments. To the best of our knowledge, EnvExBase (integrated in both HiSpOD and Metabolic Design programmes) is the first CDSs database dedicated to microbial ecology [START_REF] Terrat | Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray development[END_REF][START_REF] Dugat-Bony | HiSpOD: probe design for functional DNA microarrays[END_REF]. For its construction, all annotated transcript sequences and their associated 5′ and 3′ untranslated regions in all classes of EMBL Prokaryotes (PRO), Fungi (FUN) and Environmental (ENV) taxonomic divisions, were extracted and curated to remove badquality sequences. It represents a 9 129 323 sequence database.

The rapid growth of datasets, particularly environmental datasets, has led to an important increase in computational requirements coupled with a fundamental change in the way algorithms are conceived and designed [e.g. mpi-BLAST [START_REF] Darling | The Design, Implementation, and Evaluation of mpiBLAST[END_REF]]. Consequently, parallel computing is essential, and algorithms must be deployed on large cluster infrastructures or computing grids, if specificity tests and alignments are to be performed with reasonable data processing times [START_REF] Gardner | Parallel genomic sequence-searching on an ad-hoc grid: experiences, lessons learned, and implications[END_REF][START_REF] Thorsen | Parallel genomic sequencesearch on a massively parallel system[END_REF].

Adaptation of the microarray format to the design strategy

Explorative design strategies targeting unknown sequences involve the use of degenerate probes [START_REF] Bontemps | Microarray-based detection and typing of the Rhizobium nodulation gene nodC: potential of DNA arrays to diagnose biological functions of interest[END_REF][START_REF] Militon | PhylArray: phylogenetic probe design algorithm for microarray[END_REF][START_REF] Terrat | Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray development[END_REF][START_REF] Dugat-Bony | HiSpOD: probe design for functional DNA microarrays[END_REF]. Consequently, the selected strategy will greatly influence the choice between the two major DNA microarray types (ex situ or in situ), the platform and the density [START_REF] Dufva | Fabrication of high quality microarrays[END_REF][START_REF] Ehrenreich | DNA microarray technology for the microbiologist: an overview[END_REF][START_REF] Kawasaki | The end of the microarray Tower of Babel: will universal standards lead the way?[END_REF]. When using in situ synthesis microarrays, such as the Agilent, Affymetrix and NimbleGen platforms, all combinations resulting from a degenerate probe must be independently synthesized. This will exponentially increase the final number of probes for the array production (density). For instance, concerning the CODE-HMOP [START_REF] Bontemps | Microarray-based detection and typing of the Rhizobium nodulation gene nodC: potential of DNA arrays to diagnose biological functions of interest[END_REF] and Metabolic Design strategies [START_REF] Terrat | Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray development[END_REF], because the genetic code often involves degeneracy at the third position of each codon, a 24 mer probe (targeting a seven amino acid conserved motif) will generate at least 128 combinations (assuming a minimal degeneracy rate of two for each codon). This value will reach at least 131 072 for a 51 mer probe containing 17 degenerate positions. Conversely, ex situ platforms allow the degenerate probes (all combinations mixed together) to be spotted in the same location on the array and consequently reduce the total amount of features.

Other user choices may also affect the final number of probes per array. Replication is crucial to achieve reliable data for microarrays [START_REF] Spruill | Assessing sources of variability in microarray gene expression data[END_REF]. Multiple replicates of the same probe provide some back-up in case a feature cannot be evaluated due to technical artefacts, such as dye precipitations or dust particles. A statistical estimation has deduced that at least three replicates should be made [START_REF] Lee | Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations[END_REF]. Second, multiple probes per gene could be designed in order to increase confidence in the results [START_REF] Loy | Oligonucleotide microarray for 16S rRNA gene-based detection of all recognized lineages of sulfatereducing prokaryotes in the environment[END_REF][START_REF] Chou | Optimization of probe length and the number of probes per gene for optimal microarray analysis of gene expression[END_REF] and to mask misleading signal variations whose causes (e.g. target secondary structure, probe folding, etc.) are not yet fully understood [START_REF] Pozhitkov | Oligonucleotide microarrays: widely applied -poorly understood[END_REF]. Third, some platforms, such as Affymetrix GeneChips, determine probe pairs where each probe ('match') is accompanied by a negative control with a single differing base in the middle of the probe ('mismatch probe') in order to discriminate between real signals and those due to non-specific hybridizations [START_REF] Lipshutz | High density synthetic oligonucleotide arrays[END_REF].

To address this problem of probe number, several commercial companies have proposed two major types of high-density microarrays whose main characteristics are described in Table 3: (i) in situ synthesized microarrays, distributed by Agilent (http://www.chem.agilent.com), NimbleGen (http://www.nimblegen.com) and Affymetrix (http://www.affymetrix.com), which can attain billions of probes and be physically divided into multi-arrays per slide (up to 12) to perform simultaneous analyses of several samples on a single experiment; and (ii) spotted microarrays [e.g. Arrayit (http://www.arrayit.com)] with a current printing capacity close to 100 000 features per microarray.

Concluding remarks and future directions

Assessing the extreme microbial diversity encountered in environmental samples represents an exciting challenge that could create a better understanding of microbial community functioning. Environmental DNA microarrays, with the opportunity to survey both known and unknown microorganisms through explorative probe design, are one of the most powerful approaches for achieving this goal. Future perspectives in this domain will be to systematically integrate this innovative concept into probe design workflows, especially by offering the possibility to design degenerate probes targeting sequence clusters. Furthermore, to efficiently recognize signals due to unknown targets, it will be particularly useful to develop automatic procedures to analyse microarray data. In addition, using explorative probe design in sequence capture approaches that couple with NGS, such as those originally developed for direct selection of human genomic loci [START_REF] Albert | Direct selection of human genomic loci by microarray hybridization[END_REF], could also improve this gene characterization. Indeed, sequence capture elution products should allow the full identification and characterization of new taxa when using POAs or new protein coding genes with FGAs.

The constant increase in available sequences [START_REF] Cochrane | Petabyte-scale innovations at the European Nucleotide Archive[END_REF] means that databases for specificity tests must be regularly updated. As a result, probe datasets must be re-computed as frequently as possible in order to take into account all deposited data. Nevertheless, assessing probe specificity against large databases is a time-consuming task. To overcome this problem, two complementary strategies could be employed: (i) Creation of databases specific to each ecological compartment. Usually, specificity tests are not performed against a suitable subset of sequences mainly due to lack of databases for microbial ecology. Depending on the environment studied it would be more relevant to perform these tests against reduced databanks dedicated to specific ecosystems (soil, marine, freshwater, gut, etc.).

(ii) Parallelization of probe design algorithms. Perspectives to limit computation time are based on exploiting the computational resources available using specialized frameworks such as Message Passing Interface (MPI) or heterogeneous systems including General-purpose Processing on Graphics Processing Units (GPGPU). With the recent development of extremely fast broadband networks, it has become possible to distribute the calculations at larger and larger scales over different geographical locations [START_REF] Schadt | Computational solutions to large-scale data management and analysis[END_REF]. Cluster, grid or emerging cloud computing are all examples of shared computing resources where probe design algorithms can be deployed. Being able to improve the bioinformatics tools applied to environmental microbiology through algorithm deployment on such shared computational resources, and combining them with automatic update pipelines, are two important challenges and strategies for the future of the field of molecular ecology.

Fig. 1 .

 1 Fig. 1. PhylArray programme workflow. PhylArray programme is composed of four steps: (i) sequence extraction for each taxon, (ii) multiple sequence alignment, (iii) degenerate consensus sequence production and probe selection and (iv) specificity tests against the 16S rRNA database.

Fig. 2 .

 2 Fig. 2. Explorative probe design strategies implemented in (A) HiSpOD and (B) Metabolic Design software. The example shows probe design for the bphA1c gene encoding the Salicylate 1-hydroxylase alpha subunit involved in PAH degradation from three distinct Sphingomonas or Sphingobium species with both strategies.

Fig. 3 .

 3 Fig. 3. Representation of the GoArrays strategy. In this strategy, two short oligonucleotide probes are concatenated with a random linker. Depending on the probes' positions, the target can form two kinds of stable loops during hybridization (A and B). (For the color version of this figure, please refer to the Web version of this article.)

Table 1 .

 1 Appropriate probe design software for microbial ecology studies.

		URL
	Applications in	microbial ecology Accessibility and user interface
		Software

FGA, functional gene array; GUI, graphical user interface; L, Linux; M, MacOS; POA, phylogenetic oligonucleotide array; S, SunOS; W, Windows; WGA, whole-genome array.

Table 3 .

 3 Characteristics of the main commercially distributed high-density microarrays.

	Type of array	Technology	Probe length	Max features	Max plex
	Spotted Arrays	Robot spotting Pre-made DNA	Any	~100 000	1
	Affymetrix	Photolithography in situ	<100 mer (generally 25 mer)	~6 000 000	1
	NimbleGen	Micro-mirrors in situ	<100 mer (generally 50-75 mer)	4 200 000	12
	Agilent	Inkjet in situ	<100 mer (generally 25-60 mer)	1 000 000	8

© 2011 Society for AppliedMicrobiology and Blackwell Publishing Ltd, Environmental Microbiology, 14,[356][357][358][359][360][361][362][363][364][365][366][367][368][369][370][371]

Acknowledgments

This work was supported by the grant ID 2598 from the 'Agence De l'Environnement et de la Maîtrise de l'Energie' (ADEME, France); the Grant ANR-07-ECOT-005-05 for the programme PRECODD Evasol from 'Agence Nationale de la Recherche' (ANR, France); the Grant ANR-08-BIOENERGIES-0 for the programme BIOENERGIES AnaBio-H2 from 'Agence Nationale de la Recherche' (ANR, France); and the INSU-EC2CO programme from 'Centre National de la Recherche Scientifique' (CNRS, France). We thank David Tottey for reviewing the English version of the manuscript.

Yes ND RDP-II Database ORMA Fixed by the user No Yes No Yes No Yes No No PhylArray Fixed by the user (20-70) No No Yes


Nazzareno Diodato

Gianni Bellocchi

Gianni Tartari

How do Himalayan areas respond to global warming?

Keywords: global warming, Pyramid Automated Weather Station, teleconnection, temperature, Tibetan Plateau

We study the interdecadal-scale variability over the Himalayas/Tibetan Plateau (H/TP) to deepen the understanding of Earth's important ecosystem after the recent controversy about glaciers melting in the Himalayan Mountains. We present a new statistical reconstruction of annual temperature variability back to 1901 for the Pyramid Automated Weather Station of the Ev-K2-CNR Committee, located at the base of the Mount Everest. Our reconstruction using recorded weather station data compared with the Climate Research Unit temperature pattern data indicate that in recent decades the warming trend over the H/TP has been faster than during any equivalent period in the last century. Positive temperature anomalies (mostly observed after 1970) were found to be correlated with the Atlantic Multidecadal Oscillation and the Pacifical Decadal Oscillation indices, but unevenly correlated with the Northern Hemisphere (NH) land-surface temperature. Such decoupled response between H/TP and NH suggests the mechanisms of global warming are only marginally influencing the H/TP climate.

Introduction

The debate regarding the impact of anthropogenic climate change on Earth's remote ecosystems is complicated by the fact that historical weather records are limited in their length, especially at high altitudes where the sensitivity to global climatic change may be paramount [START_REF] Liu | Climatic warming in the Tibetan Plateau during recent decades[END_REF][START_REF] Bagla | No sign yet of Himalayan meltdown, Indian report finds[END_REF]. Furthermore, large-scale orographies such as the Himalayan and Tibetan Plateau (H/TP), can also play an important role in influencing climate -most particularly with respect to monsoon circulation [START_REF] Liu | Climatic warming in the Tibetan Plateau during recent decades[END_REF][START_REF] Yasunary | Evolution of the Asian monsoon and the coupled atmosphere-ocean system in the tropics associated with the uplift of the Tibetan Plateau -A simulation with the MRI coupled atmosphere-ocean GCM[END_REF][START_REF] Kang | Review of climate and cryospheric change in the Tibetan Plateau[END_REF], especially by acting as an obstacle to southward flow of cool, dry air [START_REF] Molnar | Orographic controls on climate and paleoclimate of Asia: thermal and mechanical roles for the Tibetan Plateau[END_REF].

Increases in positive temperature trends have been observed in southern pre-Himalayan areas since the 1970s [START_REF] Shrestha | Maximum temperature trends in the Himalaya and its vicinity: an analysis based on temperature records from Nepal for the period 1971-94[END_REF], as well as over the Tibetan Plateau (TP) in more recent decades [START_REF] Yimin | Recent progress in the impact of the Tibetan Plateau on climate in China[END_REF][START_REF] Liu | Elevation dependency of recent and future minimum surface air temperature trends in the Tibetan Plateau and its surroundings[END_REF]. This may induce a faster melting of some Himalayan glaciers depending on their own individual behaviours [START_REF] Inman | Settling the science on Himalayan glaciers[END_REF]. However, permafrost temperatures are mainly controlled by elevation and latitude (together with geothermal heat flux), and concerns are only potentially raised in relation to the possible transfert of the climate warming into permafrost temperature increases and degradation * Correspondence to: Nazzareno Diodato, Met European Research Observatory, GEWEX-CEOP Network -World Climate Research Programme, 82100 Benevento, Italy. E-mail: nazdiod@tin.it on the TP [START_REF] Wu | Permafrost temperatures and thickness on the Qinghai-Tibet Plateau[END_REF]. Important teleconnections between El Niño-Southern Oscillation (ENSO) and temperature anomalies of the Tibetan Plateau have been temporally identified by [START_REF] Yin | Temperature anomalies in central and eastern Tibetan Plateau in relation to general circulation patterns during 1951-1993[END_REF] and [START_REF] Liang | Tree-ring based summer temperature reconstruction for the source region of the Yangtze River on the Tibetan Plateau[END_REF] but, in general, temperature teleconnections are not yet well understood across Asia. This is mainly due to sparsely distributed meteorological measurement stations over such remote and mountainous areas [START_REF] Xie | Pressure and temperature feasibility of NCEP/NCAR reanalysis data at Mt. Everest[END_REF]. Today, the Himalayan area benefits from the recently installed instrumental observations [START_REF] Ueno | Stepwise onset of monsoon weather observed in the Nepal Himalaya[END_REF] The present study establishes the longest temperature and indices series ever for this highelevation area, taking advantage of both high-resolution gridded temperature data made available by the Climate Research Unit (CRU TS3) [START_REF] Brohan | Uncertainty estimates in regional and global observed temperature changes: a new dataset from 1850[END_REF]

Methods

A variety of datasets was evaluated for the purposes of temperature modelling and reconstruction (Table I). In the following sections, their use is elaborated upon in detail.

Temperature data reconstruction

Annual temperature data for Pyramid AWS before 1994 were estimated from monthly CRU TS3 dataset [START_REF] Brohan | Uncertainty estimates in regional and global observed temperature changes: a new dataset from 1850[END_REF] (1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001). From the same CRU TS3 dataset, data from 2002 to 2005 were used for validation. Monthly mean temperatures (T m , °C) at the Pyramid AWS were estimated using a linear model approximated by:

T m = a + b • T m(CRU ) (1)
where a = -3.8 (±0.11) and b = 0.75 (±0.02) are model parameters (R = 0.98), and T m(CRU ) is the monthly temperature ( °C) of CRU TS3 dataset. Least-square regression analyses were run to estimate the parameters of Equation (1). The entire process was assessed interactively using Microsoft  Office Excel 2003 with the support of Statistics Software-R modules [START_REF] Wessa | Free Statistics Software[END_REF].

Evaluation of temperature series

The estimated temperature monthly values by Equation (1) were compared against observational values.

The agreement between estimates and T m -values was evaluated using the modelling efficiency by Nash and Sutcliffe [START_REF] Nash | River flow forecasting through conceptual models part I -A discussion of principles[END_REF] as performance statistic (ranging from negative to positive unity, the latter being the optimum value; positive values indicating that the model is estimating better than the average of the observed data). For a visual inspection of the quality of results, a set of comparative scatterplots and histograms (four graphs) are also presented based on temperature simulations to evaluate how the model works. A comparison against long-term records was performed using data from Kathmandu Airport, Nepal (the nearest available station), provided for 1950-2009 by the Climate Explorer database (WMO station code 44 454, van [START_REF] Van Oldenborgh | Western Europe is warming much faster than expected[END_REF].

Climate change investigations

Continuous-time signals of climate change and trends in the reconstructed series were investigated by using a Morlet mother wavelet based on the same procedure described in [START_REF] Torrence | A practical guide to wavelet analysis[END_REF]. Wavelet transforms decompose complex information and patterns into elementary forms. They are efficient in determining the damping ratio of oscillating signals and are resistant to the noise in the signal, changing adaptively to the time and frequency resolution (e.g. [START_REF] Ding | Time-frequency analysis and wavelet transform[END_REF].

The following climate indices were also used to characterize and explain the influential role of local processes and teleconnections that influence over TP temperatures: Pacific Decadal Oscillation [START_REF] Mantua | A Pacific interdecadal climate oscillation with impacts on salmon production[END_REF], Atlantic Multidecadal Oscillation [START_REF] Goldenberg | The recent increase in Atlantic hurricane activity: causes and implications[END_REF], and Asian-Pacific Oscillation [START_REF] Zhao | An Asian-Pacific teleconnection in summer tropospheric temperature and associated Asian climate variability[END_REF].

Results and discussion

Evaluation of reconstructed temperature data

A general agreement is apparent between observed data and T m distributional estimates with both calibration, In order to verify if temperature reconstruction from monthly records was also able to capture interannual variability at the Pyramid AWS, predicted and observed annual temperatures (mean of monthly temperatures) were compared (Figure 2). The years 1994-2006 define a period of overlap with reanalysis data provided by the National Centers for Environmental Prediction (NCEP), National Oceanic and Atmospheric Administration of the United States Department of Commerce-Earth System Research Laboratory (http://www.cdc.noaa.gov).

The NCEP reanalysis represents an updated source providing relatively coarse spatial data (about 1 °× 1 °). For the period investigated, NCEP temperature fluctuations are largely approached by our reconstruction, and both series do not differ substantially from the observed profile (Figure 2, graph A).

Figure 2, graph B displays the comparison, for the testing period 1950-2009, of the predicted temperatures at Pyramid AWS and the observations taken at Kathmandu station (Nepal). The latter is placed 100 km apart and about 4000 m lower than the Pyramid station, thus, lack of correspondence between the two series is not unexpected. However, the overall trend of predicted temperatures can be considered to agree sufficiently well with the observed data series of Kathmandu. This also corresponds to the distributions of seasonal and annual temperature trends shown by [START_REF] Shrestha | Maximum temperature trends in the Himalaya and its vicinity: an analysis based on temperature records from Nepal for the period 1971-94[END_REF] for Kathmandu and high-elevation sites of the Himalayan region.

Warming trends

The Himalayan climate is characterized by a considerable significant temperature increase, referred to as a core of +0.5 °C for the period 1971-2005 in comparison to 1901-1960 (Figure 3A 1 ). Similarly, satellite tropospheric temperature data detected from 1979 and 2007 revealed small (positive) warming trends over the TP compared to the strong warming trend observed in the western Himalayan region [START_REF] Gautam | Enhanced pre-monsoon warming over the Himalayan-Gangetic region from 1979 to 2007[END_REF], although there are major physical differences between surface and tropospheric temperatures [START_REF] Parker | Temperatures high and low[END_REF].

Focusing on Mount Everest, Figure 3A 2 shows the temperature anomaly series for the Pyramid AWS statistically reconstructed back to 1901 using a linear regression between gridded (CRU TS3) and Pyramid AWS station data updated until 2009 (Figure 3B 1 ). The temperature series at this high elevation appear affected by an increasing trend with irregular steps and sudden shifts in amplitude that took place particularly during The area in white is the south-north Plateau section around the 90th meridian; overlying coloured zones represent the correlation patterns of the typical cross-section in the free atmosphere (the Plateau is placed around 600 hPa = 5000 m a.s.l.). This figure is available in colour online at wileyonlinelibrary.com/journal/joc decade, several times over the past two millennia the climate was considerably warmer in the TP, and for longer periods, than during the late 20th century [START_REF] Liu | Annual temperatures during the last 2485 years in the Mid-Eastern Tibetan Plateau inferred from tree rings[END_REF][START_REF] Feng | Regulation of Tibetan Plateau heating on variation of Indian summer monsoon in the last two millennia[END_REF]. Furthermore, no trend and no important changes are visible in agreement with the global warming paused over [START_REF] Parker | Temperatures high and low[END_REF]-2009[START_REF] Kerr | What happened to global warming? Scientists say just wait a bit[END_REF][START_REF] Camuffo | 500-year temperature reconstruction in the Mediterranean Basin by means of documentary data and instrumental observations[END_REF][START_REF] Simmons | Lowfrequency variations in surface atmospheric humidity, temperature, and precipitation: inferences from reanalyses and monthly gridded observational data sets[END_REF][START_REF] Solomon | Contributions of stratospheric water vapor to decadal changes in the rate of global warming[END_REF]. Albeit the TP is a small part of the North Hemisphere (NH), it may respond in a different way to climate forcing (also due to its complex surrounding topography), and then it is interesting to assess the degree of teleconnections between NH and TP, taking advantage of both CRU TS3 and NCDC-NH (land + ocean) temperature series and TP temperature pattern. The result highlights a moderate but long and important coupling between NH warming and TP temperature in the period 1901-1960 (Figure 4A). This outcome is supported by a previous study performed by [START_REF] Bhutiyani | Long-term trends in maximum, minimum and mean annual air temperatures across the Northwestern Himalaya during the twentieth century[END_REF] indicating, for the 20th century, similar epochs of temperature variation between global and northwestern Himalayas. Nowadays, although a coupling in the northwestern area of the TP appears clearly and with certain persistence and it can be related to global warming, at the same time, on the rest of southeastern region across the Pyramid AWS, the unvarying TP temperature with NH warming is an unexpected and hard-to-figure behaviour (Figure 4). It is the southeastern TP, in particular, that seems to resist the mechanisms of global warming after 1970 (Figure 4B). This is also revealed by a correlation pattern between the global and TP temperatures in the latitude-height cross-section (Figure 5, graphs A and B), based on the NCEP reanalysis. In particular for 1971-2009 (graph B), it is visible that while temperatures to the north of the TP and in Nepal agree to the global warming (green and yellow areas), the southern part of the TP (circle) resists this global forcing, indicating the existence of different driving forces between northern and southern plateau zones. Not entirely supported by [START_REF] Shrestha | Maximum temperature trends in the Himalaya and its vicinity: an analysis based on temperature records from Nepal for the period 1971-94[END_REF], whose study was limited to 1971-1994, our results are consistent with an updated investigation by [START_REF] Ding | Intercomparison of the time for climate abrupt change between the Tibetan Plateau and other regions in China Chin[END_REF], who found that the recent acceleration of warming in the TP has occurred later than in the north of the Yangtze River (east China), especially in winter and spring. In the recent decades, some unknown forcing working in a decoupled way, seems to have triggered the southeastern TP to depart from the NH climate. This decoupling emerging from the CRU TS3 estimates reveals the existence of spatial heterogeneity of regional forcing factors affecting current warming [START_REF] Bradley | Climate in Medieval time[END_REF].

Temperature teleconnections

Climate indices may influence the climate at regional scale, although areas in which important changes are detected can be scattered around the globe and lack consistency in time [START_REF] Sterl | On the robustness of ENSO teleconnections[END_REF]. The Atlantic Multidecadal Oscillation (AMO, defined from the patterns of sea surface temperatures), for instance, may have played an important role in influencing the TP climate, since it appears to be part of a wider phenomenon driven by variation in the surface heat flux and coherent with parallel fluctuations in the strength of the thermohaline circulation [START_REF] Burroughs | Weather cycles: real or imaginary[END_REF]. This is indicated by a positive AMO-temperature correlation pattern, prominent and more powerful in 1971-2005 than in the previous longer period 1901-1960 when some significant correlation was already apparent limited to the southeastern TP (Figure 6A,B).

With equal emphasis and extension, a confounding change in the correlation patterns was also detected between Pacific Decadal Oscillation (PDO, detected as warm or cool surface waters in the Pacific Ocean) and temperature (Figure 7A,B), and for which a high predictability was found in relation to global climate change on decadal time scales [START_REF] Mochizuki | Pacific decadal oscillation hindcasts relevant to near-term climate prediction[END_REF] as above. This was, in turn, consistent with the Asian-Pacific Oscillation (a zonal teleconnection pattern over the extratropical Asian-Pacific region) -which is associated with the out-of-phase relationship in atmospheric heating -and that shows a decadal variation according to the high index polarity registered before 1975 and to the low index polarity registered afterwards [START_REF] Zhao | An Asian-Pacific teleconnection in summer tropospheric temperature and associated Asian climate variability[END_REF]. Conforming to the warming phase 1971-2005, the AMO and PDO effectively marked the last decades, and Figures 6 and7 show that the switch of both AMO and PDO to their warm cycles from a precedent cool cycle has become firmly established.

Although [START_REF] Sheffield | Global trends and variability in soil moisture and drought characteristics, 1950-2000, from observationdriven simulations of the terrestrial hydrologic cycle[END_REF] found weak correlations between drought and climate indices over the warm period 1950-2000 with El Niño-3.4 and AMO, a significant correlation was found for TP temperature and AMO.

The northwestern TP is highly sensitive to global warming, while the southeastern part seems less prone to these changes. However, the relative importance of these regional factors is not clear, particularly because neither the response to regional forcing nor the regional forcing itself are well known for the 20th century [START_REF] Shindell | Climate response to regional radiative forcing during the twentieth century[END_REF]. It is possible that climate-environment interactions in the Tibetan area coincide with global warming at a sub-regional level, thus leading to a speculative interpretation [START_REF] Qian | Simulated impacts of land cover change on summer climate in the Tibetan Plateau[END_REF]. For instance, [START_REF] You | Climate warming and associated changes in atmospheric circulation in the eastern and central Tibetan Plateau from a homogenized dataset[END_REF] suggested that change in regional atmospheric circulation is one of the important factors contributing to the recent climate warming of the TP. Considerable changes in teleconnection strength were also detected in recent decades compared to 1901-1960. Changes in cloud amount [START_REF] Duan | Change of cloud amount and the climate warming on the Tibetan Plateau[END_REF] and land use [START_REF] Zhang | Perspectives on environmental study of response to climatic and land cover/land use change over the Qinghai-Tibetan plateau: an introduction[END_REF] can also be considered important factors contributing to the recent climate warming in the TP, although local and global greenhouse gas emissions cannot be excluded. The combined action of tropospheric and stratospheric volcanic aerosols, due to their attenuation of incoming solar radiation, may also have a cooling effect on surface air temperature (e.g. [START_REF] Balling | Decreasing diurnal temperature range: CO2 greenhouse or SO2 energy balance effect?[END_REF].

Summary and conclusions

In this study, we investigated the dynamic patterns of surface warming in the Tibetan Plateau, by correlating temperature series reconstructed in situ with large-scale (Northern Hemisphere) temperature variability. While some results seem hardly explainable, we highlight that the complex interactions between climate and temperature variability over the TP are still poorly understood and the mechanisms driving future temperature changes are not completely clarified.

The TP is located in a unique geographical zone with peculiar altitudinal characteristics and low average air temperature. Basing on our study, its climate since 1901 has changed both in time and in space indicating the non-uniform effects of global warming. Global warming started in around1850, after the end of the Little Ice Age, but its pattern could have changed character since the 1970s. The changes of air temperature in the last decades exhibit a zonational pattern not always significant. The start of a new decade (from 2010 onward) appears promising, as observed and predicted climates reveal them in a way not seen in the past 100 years. A challenge and priority for future research lies in attaining a much better understanding of what is causing the global warming. In particular, more comparative studies between different types of data sources are possible, and certainly also desirable for the reason that remote regions (such as the TP) include inhomogeneities resulting from disposal or relocation of stations and changes in the local environment. Moreover, further investigation to seasonal scales would help in the process of finding explanations for the trends and teleconnections. This will be possible as more records become available in situ, and homogenized data will be provided by the CRU TS3 on a monthly basis.

Figure 1 .

 1 Figure 1. Scatterplots between predicted (Equation (1)) and observed montly temperature data for both (A) the calibration set (1994-2001) and (B) the validation set (2002-2005); residual distribution for both the calibration dataset (A1) and the validation dataset (B1). The 1 : 1 lines are also shown in A and B. This figure is available in colour online at wileyonlinelibrary.com/journal/joc

Figure 2

 2 Figure 2. (A) Annual temperature as observed at the Pyramid AWS (black line), as produced from NCEP reanalysis (green line), and as predicted from CRU TS3 records (red line) for 1994-2005; (B) annual temperature as reconstructed (black data points) at the Pyramid AWS and as observed (gray data points) at Kathmandu WMO station (1333 m a.s.l.) for 1950-2009 (black and gray lines represent the respective 3-year running means). For predictions versus Pyramid AWS observed data (graph A): Nash-Sutcliffe index = 0.39; correlation coefficient = 0.81. For predictions versus NCEP reanalysis data (graph A): Nash-Sutcliffe index = 0.72; correlation coefficient = 0.92. For reconstructed (Pyramid AWS) versus Kathmandu observed data (3-year running means, graph B): correlation coefficient = 0.72. This figure is available in colour online at wileyonlinelibrary.com/journal/joc

Figure 4 .

 4 Figure 4. Spatial correlation (p < 0.10) between the annual temperature over the Tibetan Plateau (TP) and the Northern Hemisphere (NH) for 1901-1960 (A) and 1971-2005 (B) based on CRU TS3 (TP) and NCDC (NH) data, respectively (colour-coded map of the region as arranged by the Royal Netherlands Meteorological Institute databases and supplied by the web-GIS Climate Explorer, van Oldenborgh et al., 2009). x-axis is longitude, y-axis is latitude. This figure is available in colour online at wileyonlinelibrary.com/journal/joc

Figure 6 .

 6 Figure 6. Spatial correlation (p < 0.10) between the AMO (HadSST2) and annual temperature (CRU TS3) over the Tibetan Plateau for (A) 1901-1960 and (B) 1971-2005 (arranged by the Royal Netherlands Meteorological Institute databases and supplied by the web-GIS Climate Explorer, van Oldenborgh et al., 2009). x-axis is longitude, y-axis is latitude. This figure is available in colour online at wileyonlinelibrary.com/journal/joc

  operated by Ev-K2-CNR Committee (effective in this area since 1989, http://www.evk2cnr.org, with measured data becoming available by 1994) and, in particular, from the Pyramid Automated Weather Station (hereafter Pyramid AWS), placed at the foot of Mount Everest at 5050 m a.s.l. (86.80 °E and 27.95 °N).

  and global datasets arranged via Climate Explorer web-GIS by both the Hadley Centre for Climate Prediction and Research and the National Climatic Data Center (van Oldenborgh et al., 2009). The annual trends in reconstructed temperature time series at the Pyramid AWS since 1901 was used to document the interdecadal-scale variability patterns over TP and to study potential temperature teleconnections.

	976	N. DIODATO et al.

Table I .

 I Availability and source of temperature datasets used for model calibration and validation, reconstruction of the temperature time series, and testing (out-of-sample validation).

	Dataset	Sources	Period	Use
	Pyramid AWS	Ev-K2-CNR Committee (Ueno	1994-2001	Model calibration; Temperature time
		et al., 2008)		series reconstruction
			2002-2005	Model validation; Temperature time
				series reconstruction
		Update from Ev-K2-CNR	2006-2009	Temperature time series
		Committee (personal		reconstruction
		communication)
	CRU TS3	Climate Explorer (Brohan	1901-2005	Temperature time series
		et al., 2006; van Oldenborgh		reconstruction; Spatial correlation
		et al., 2009)
	NCEP reanalysis	NCEP NOAA-ESRL through	1994-2009	Testing of the reconstructed
		http://www.cdc.noaa.gov/cgi-		temperature series
		bin/PublicData/getpage.pl
	Kathmandu WMO station	Climate Explorer (van	1950-2009
		Oldenborgh et al., 2009)

Copyright  2011 Royal Meteorological Society

Copyright  2011 Royal Meteorological Society Int. J. Climatol. 32:975-982 (2012)

Acknowledgements

The authors are grateful to specialist colleagues Casey Saenger (Department of Geology and Geophysics at Yale University) and Carlo Casty (Risk Management and Reserves of Zürich, Switzerland) who have provided helpful comments while the research for this paper was in progress, and on draft versions of the manuscript. The authors are also grateful for the possibility offered them of using predictor data from various sources, and mainly from the Royal Netherlands Meteorological Institute (in the person of Andreas Sterl) for supplies by the Climate Explorer database. We also thank the Ev-K2-CNR Committee for the use of Pyramid AWS data and the work carried out to maintain the monitoring activity in the Everest area.