Integrative and Comparative Biology Advance Access originally published online on June 3, 2006
Integrative and Comparative Biology 2006 46(6):919-930; doi:10.1093/icb/icl007
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Construction and characterization of EST libraries from the porcelain crab, Petrolisthes cinctipes
* Romberg Tiburon Center, San Francisco State University, 3152 Paradise Drive, Tiburon, CA 94920 USA
Department of Zoology, University of Hawaii at Manoa, Honolulu HI 96822, USA
Joint Genome Institute, DOE, 2800 Mitchell Drive, Bldg 400-467, Walnut Creek CA 94598, USA
Correspondence: 1E-mail: stillmaj{at}sfsu.edu
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The thermal phenotype of an organism (heat and cold tolerance, thermal range, and thermal plasticity) is an essential feature of how the organism performs across thermal environments and in response to thermal stress. Porcelain crabs are of interest in addressing questions of thermal phenotype because of their high species diversity and the large variation in thermal phenotype among species, as well as the biogeographic patterning of these crabs along environmental stress gradients. We are studying the cellular bases of thermal phenotype and physiological responses to environmental stress using a functional genomics cDNA microarray approach. To do this, we have isolated total RNA from a range of tissues from 1 species of porcelain crab (Petrolisthes cinctipes) exposed to a suite of thermal conditions, and have used this RNA to construct a 13 824-clone EST library. Here, we describe construction, EST sequencing, assembly and clustering, and results of BLASTx homology search for our initial 13 824-clone library. From 12 060 usable ESTs, 6717 consensus sequences were identified, and roughly 50% of these have homology to known proteins. At present, an additional 50 000–75 000-clone library of P. cinctipes ESTs is being generated, with the aim of developing a library with near-complete coverage of the transcriptome. The libraries and sequence information that will be generated as a result of this project should be of value for crustacean biologists working across a broad range of scientific disciplines (for example, physiology, developmental biology, biological rhythms, ecology, fisheries biology), as well as in studies of molecular evolution and phylogeography.
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Genomics-based investigative approaches have assumed a major role in advances across a wide range of disciplines, from the biomedical field to ecology, evolution, and comparative physiology (Alizadeh and others 2000
; Feder and Mitchell-Olds 2003; Gracey and Cossins 2003; Hofmann and others 2005). Sequencing genomes from model organisms such as Caenorhabaditis elegans and Drosophila melanogaster set the stage for rapid progress in characterizing gene function and regulation (C. elegans Sequencing Consortium 1998; Adams and others 2000). It is not, however, the general case that these model organisms are necessarily the select study systems for the comparative physiologist (Gracey and Cossins 2003).
The marine environment provides an interesting setting for addressing ecological and comparative physiological questions such as how ecosystems or organisms and their distributional limits might be affected by global environmental change (Stillman 2003; Hofmann and others 2005). At present, full genome sequence information for marine organisms like Fugu rubripes (Japanese pufferfish) (Aparicio and others 2002) and Ciona intestinalis (sea squirt) (Dehal and others 2002) are available. Additionally, many laboratories have opted to construct expressed sequence tag (EST) libraries from marine study systems for use in addressing problems spanning ecotoxicology (for example, mussels [Vernier and others 2003] and copepods as bioindicators of pollution [Lee and others 2005]), immunology (disease resistance in shrimp [Supungul and others 2002], immune response in oysters [Gueguen and others 2003]), muscle physiology (for example, muscle growth in scallops [Roberts and Goetz 2003]), and pharmacology (for example, cone snail conotoxins [Pi and others 2006]). The range of organisms being studied at the gene expression level provides fruitful grounds for comparative work as well.
Recently, a hub for EST information and microarray data specific to marine organisms was developed by the Marine Genomics project (McKillen and others 2005). Databases for over 19 marine species are accessible or underway (http://www.marinegenomics.org) and include those for 7 crustaceans Callinectes sapidus (Blue crab, 1742 ESTs), Homarus americanus (American Atlantic lobster, 5043 ESTs), Litopenaeus setiferus (White shrimp, 1041 ESTs), Litopenaeus stylirostris (Blue shrimp, 227 ESTs), Litopenaeus vannamei (White shrimp, 13 704 ESTs), Palaemonetes pugio (Daggerblade grass shrimp, 8821 ESTs), and Calanus finmarchicus (North Atlantic copepod, 309 ESTs) (McKillen and others 2005).
Here, we present our efforts for developing an EST database for the porcelain crab, Petrolisthes cinctipes, for use in comparative functional genomic analyses of mechanistic bases of thermal adaptation as well as patterns of thermal stress responses across ecological gradients. Development of this porcelain crab genomics resource allows us to take advantage of the great biological and ecological diversity of the porcelain crabs, and builds on a wealth of data on comparative thermal physiology for these organisms. Porcelain crabs of the genus Petrolisthes (Decapoda: Anomura: Porcellanidae) comprise over 100 species spanning a wide latitudinal range and includes species inhabiting discrete vertical zones within geographical ranges including the North Temperate, Northern Gulf of California, Tropical, and South Temperate regions of the Eastern Pacific coast (Haig 1960; Stillman 2002). A phylogeny of porcelain crabs from the Eastern Pacific has been conducted allowing for comparative analyses to be made in an evolutionary context (Stillman and Reeb 2001). P. cinctipes has been an effective model for research in thermal physiology (Stillman 2002, 2003). This species inhabits the mid to upper intertidal zone in the northeastern Pacific and experiences temperatures as high as 31°C and as low as –1°C during low tide emersion in the summer and winter, respectively (Stillman 2002, 2004). We have constructed from P. cinctipes a cDNA library for use in studying the mechanisms, at the gene expression level (using microarray analyses), that underlie organismal thermal phenotypes.
Here, we present the methodology used, and results of our intial library construction, sequencing, and annotation. Then, we describe our present efforts, in conjunction with the Joint Genome Institute (JGI), to expand the P. cinctipes EST library to cover as much of the transcriptome as possible.
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Specimen collection and handling
Our cDNA libraries were constructed from specimens of 1 species of porcelain crab (P. cinctipes) that was subjected to a wide array of experimental conditions before sacrifice. In our experiments, we collected crabs from across latitudinal and seasonal gradients and exposed these animals to acute heat and cold shocks, generally to
30 and 0°C, respectively. We also acclimated crabs to a wide range of thermal conditions that elicit changes in whole organism thermal phenotype, and exposed these animals to acute heat and cold shocks. Acclimation temperatures ranged from 8 to 25°C, and acclimation duration ranged from 2 days to 2 months. From hundreds of individual crabs used across 2 years of experiments, we preserved RNA by snap-freezing whole crabs by freeze-clamp, or by dissecting fresh tissues into 1 ml Trizol reagent (Invitrogen) and then storing frozen until RNA extraction. RNA degradation was not generally observed in Trizol preserved samples.
RNA extraction
Total RNA was extracted by either powdering tissue under liquid N2 and then thawing the powder in Trizol (whole crabs), or by homogenizing dissected tissues (heart, gill, nerve axons from walking legs (including both sensory and motor neurons), hepatopancreas, and claw muscle tissues) in 1 ml Trizol using a powered rotor-stator homogenizer. Homogenates were allowed to sit at room temperature for 15 min to ensure dissociation of nucleoprotein complexes, and centrifuged to remove cellular debris. Supernatants (up to 1 ml volume) were removed to fresh microcentrifuge tubes, mixed with 200 µl chloroform by vortex for 30 s, and centrifuged for 15 min at 16 000 g. The aqueous (top) layer was removed, mixed with 250 µl isopropanol and 250 µl high salt precipitation solution (0.8 M Na citrate, 1.2 M NaCl), and incubated at –20°C overnight. Precipitated RNA was pelleted by centrifugation at 16 000 g for 45 min at 4°C. Pellets were washed in 60% EtOH and resuspended in 1 mM Na citrate, pH 6.4. RNA concentration and purity were determined spectrophotometrically. Generally, A260/A280 ratios were 
1.9, and concentrations ranged from 1 to 1000 ng/µl, depending on tissue type and starting tissue quantity. Following quantification of total RNA, we mixed equal amounts of RNA from each tissue type of each individual together to make 7 pooled RNA samples: 2 from heart (from different sets of RNA extracts), and 1 each from gill, nerve, hepatopancreas, muscle, and whole crabs.
cDNA library construction
From each of the 7 pooled RNA samples, we constructed a cDNA library using the BD Clontech SMART cDNA library construction kit. First strand synthesis of cDNA, long-distance PCR (LD-PCR) for synthesis of full-length ds cDNA, and SfiI digestion were conducted according to BD Clontech Protocol#PT3000-1, version#PR15738 except for the following: (1) PCR cleanup using Qiagen's QIAquick PCR Purification Kit (QIAquick Spin Handbook, 7/2002) replaced the proteinase K digestion step and (2) 1% xylene cyanol dye was not added immediately after SfiI digestion. LD-PCR was generally stopped at 14–16 cycles, 2 cycles before saturation of PCR product amplification (as analyzed by agarose gel electrophoresis). Following SfiI digestion, samples were ethanol precipitated (2 volumes 100% ethanol, 1/10 volume 3 M Na acetate pH 5.2), resuspended in 25 µl Qiagen buffer EB (10 mM Tris–HCl, 1 mM EDTA, pH 8.0), and run out on a 0.75% agarose gel. cDNAs ranging from 500 to 5000 bp (most PCR products were 0.5–2 kb) were extracted using Qiagen's QIAquick Gel Extraction Kit (QIAquick Spin Handbook 7/2002). Purified cDNAs were directionally cloned into the SfiI sites of either pTriplEx vector (Clontech, GenBank Accession #U39779), or a modified pTrueBlue vector, pTB (Genomics One TBP0527, a gift from Dr Andrew Gracey) in a ligation reaction using 0.5 µl T4 DNA ligase, 0.5 µl T4 DNA ligase buffer (New England BioLabs M0202S), 15–40 ng cDNA, and 0.5 µl empty vector in 5 µl at 16°C overnight. The ligation reaction was precipitated with 200 µl isobutanol, placed on ice for 2 h, washed with 70% ethanol, and resuspended in 5 µl water.
Transformation of 1 µl of the ligation reaction into ElectroMAX DH10B Escherichia coli competent cells (Invitrogen, Cat No. 18290-015) was accomplished by electroporation. Following 1 h growth in SOC medium at 37°C, cells were plated on selective blue–white screening LB-agar medium with X-gal, IPTG, and carbenicillin overnight at 37°C. Individual colonies were handpicked with sterile wooden toothpicks into wells of Nunc 384-well plates each containing 50 µl of selective LB with ampicillin. A total of 36 384-well plates (13 824 total colonies) were picked, and this number was divided by library as in Table 1.
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Characterization of cDNA libraries
PCR analysis of cloned cDNAs
PCR was used to amplify cDNAs from each colony using vector specific primers to confirm that a single EST was cloned and for purposes of microarray printing. Primers used for pTriplEx were: 5'-CTCGGGAAGCGCGCCATTGTGTTGGT (forward) and 5'-ATACGTCTCACTATAGGGCGAATTGGCC (reverse), and for pTB were: 5'-ACAGGAGCAAAAACCATGGTCG (forward) and 5'-CGGGCTCTAGATCCGGAGT (reverse). Overnight bacterial cultures were used to seed 30 µl PCRs in 384-well PCR plates using an MJ-research DNA engine thermal cycler. PCR conditions were 94°C for 5 min, followed by 40 cycles of 92°C for 15 s, 54°C for 30 s, and 71.5°C for 1 min, with an additional 7 min at 71.5°C at the end of the program for any incomplete PCR products to be finished. The 13 824 PCR products were analyzed by 1% agarose gel electrophoresis (Fig. 1).
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Sequencing of cloned cDNAs
Each cloned EST was sequenced by the JGI 2006 Community Sequencing Program (CSP). Sequences were generated from overnight cultures using rolling circle amplification with TempliPhi and sequenced on an ABI3730xl following standard JGI internal protocols (http://www.jgi.doe.gov/sequencing/protocols/prots_production.html). Every clone was sequenced from both the 3' and 5'-ends using 1 of the appropriate PCR primers (above). Some clones were sequenced more than once. Raw sequence traces automatically enter the JGI EST Pipeline, as described in the following 3 paragraphs.
The JGI EST Pipeline begins with the cleanup of DNA sequences derived from the 5'and 3'-end reads from a library of cDNA clones. The Phred software (Ewing and Green 1998; Ewing and others 1998) is used to call the bases and generate quality scores. Vector, linker, adapter, poly-A/T, and other artifact sequences are removed using the Cross_match software (Ewing and Green 1998; Ewing and others 1998), as well as a short pattern-finder developed internally at JGI. Low quality regions of the read are identified using JGI software that masks regions with a combined quality score of <15. The longest high quality region of each read is used as the EST. ESTs <150 bp, or containing common contaminants (for example, rRNA, mitochondrial DNA, E. coli, common vectors, and sequencing standards) are also removed from the dataset.
EST clustering is performed ab initio, based on alignments between each pair of ESTs. Pairwise EST alignments are generated using the Malign software (J. Chapman and others, unpublished), a modified version of the Smith–Waterman algorithm (Smith and Waterman 1981), which was developed at the JGI for use in whole-genome shotgun assembly. ESTs sharing an alignment of at least 98% identity, and 150 bp overlap are assigned to the same cluster. All alignments generated by Malign are restricted such that they will always extend to within a few bases of the ends of both ESTs. These are relatively strict clustering cutoffs, and are intended to avoid placing divergent members of gene families in the same cluster. However, these clustering cutoffs could also have the effect of separating splice variants into different clusters. Optionally, ESTs that do not share alignments can be assigned to the same cluster, if they are derived from the same cDNA clone.
For each cluster of EST sequences, cluster consensus sequences are generated by running the Phrap software (Ewing and Green 1998; Ewing and others 1998) on the ESTs comprising each cluster. This matches well with the directed sequencing assumptions underlying the Phrap algorithm, as each cluster comprises a clean "tiling path", which can be easily assembled. Additional improvements were made to the Phrap assemblies by using the "forcelevel 4" option, which decreases the chances of generating multiple consensi for a single cluster, where the consensi differ only by sequencing errors (P. Brokstein, personal observation). Protein homology for each consensus sequence was determined using BLASTx to search against 3 different databases: GenBank non-redundant (nr), Swiss-Prot, and the Gene Ontology (GO) database. BLASTx was run using NCBI Blast 2.2.6. In order to ensure consistency of BLASTx e-value between BLASTx runs on databases of varying size, the –Y parameter was set to 1.75e12. Data used for nr and Swiss-Prot BLAST were downloaded from GenBank on September 27, 2005, and the GO representative sequence file (go_200510-seqdb.fasta) was downloaded from ftp://ftp.geneontology.org/pub/go/godatabase/archive/full/latest. Classification of GO terms (Fig. 2) was done using basic MS Excel search functions.
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Insert size characterization
Overall, the smallest PCR products were
250 bp, the largest were 2000 bp, and the average size was 1000 bp (Fig. 1). Approximately 13 271 (96%) of the clones yielded a single PCR product, 300 of the 13 824 clones did not produce a PCR product, and 235 produced multiple PCR products.
Sequence analysis
From these clones picked from the 7 libraries that were constructed (Table 1), a total of 35 232 sequencing reactions were performed and run on the ABI sequencer. Following quality control assessment, 22 463 sequences of high quality, representing 12 062 clones, were obtained (Fig. 1). For 1762 clones, sequence quality was either poor (for example, failed sequencing reactions, or the 235 cases where no or multiple PCR bands were observed) (Fig. 1), or represented empty vector or a cloned bacterial gene. There was no further processing of sequence data from these clones.
The 22 463 high quality sequences were found to represent 6717 consensus sequences. Thus 48.6% (6717/13 824) of the cDNA library represented unique cDNAs. This was moderately comparable with EST libraries for other crustaceans including the intertidal harpacticoid copepod Tigriopus japonicus (262/686 = 38.2% non-overlapping ESTs) and the green shore crab Carcinus maenas (1928/5362 = 36.0% unique cDNAs from a normalized cDNA library), and was middle range when compared with EST libraries for the waterflea Daphnia pulex (12 600/71 000 = 17.7% unique genes in a unidirectional cDNA library) and the American lobster H. americanus (3773/4604 = 82.0% unique cDNAs from a normalized cDNA library) (Lee and others 2005; Colbourne and others 2005; Towle 2005).
The 6717 consensus sequences fell into 5078 different clusters (Table 2). There were 4024 clusters that were only represented by a single clone (singlets), and there were 2 clusters that represented the most redundant transcripts, 1 with 473 clones and the other with 2137 clones (Table 2). The largest cluster contained 194 different consensus sequences, representing 102 different cDNAs.
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Sequence similarity of consensus sequences or cluster sequences using a translated query (BLASTx) resulted in the greatest percentage of matches from the nr database (Table 3) and the lowest percentage of matches from the Swiss-Prot database (Table 3). BLASTx hits were considered a strong match if the expect score was <1e–4, a weak match if 1e–1
expect 1e–1 and no match if expect > 1e–1. In general, 23–30% of the consensus sequences or clusters had strong matches, 20–22% had weak matches, and 50–55% did not match any known sequence (Table 3).
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Of the strong matches, different transcripts were predominant in the different tissue libraries (Table 4). Anti-lipopolysaccharide factor (anti-LPS) was most abundant in heart and whole crab libraries. Anti-LPS is an anticoagulating agent and would be expected to be highly expressed in the heart; its predominance in the whole crab library might be explained by expression in hemocytes. Genes for mitochondrial proteins were most abundant in the nerve library, which likely reflects high nerve ATP generation, and the fact that most of the nerve tissue used was axon and not cell bodies. Proteases were most common in the hepatopancreas library, which was anticipated because of this tissue's digestive role. Cuticle protein was an abundant transcript in the gill library, and reflects the large cuticular surface of this tissue. Lastly, as anticipated, muscle proteins were most abundant in the claw muscle library (Table 4).
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A large number of transcripts occurred in only 1 or 2 of the tissue libraries (Appendix Table A1), although we should not necessarily attempt to confer function from this fact as our library is far from comprehensive for each tissue. Many transcripts that were observed in specific tissues have interesting biological function and warrant further discussion. For example, in heart libraries an EST encoding the iron-binding protein transferrin was cloned (Appendix Table A1). Further analysis, however, is required to determine whether this EST represents transferrin or 1 of the mRNAs that encode the large proteinase inhibitor, pacifastin (Liang and others 1997
). Examination of the 2 largest clusters (Table 2) reveals that the clustering algorithm has grouped many different genes together. The 102 different cDNAs from the largest cluster (above, Table 2) included 4 separate cDNAs each for 2 proteins (anti-LPS and trypsin) and 2 separate cDNAs each for 3 proteins (tropomyosin, cytochrome b, cytochrome oxidase subunit I); the remaining 88 cDNAs in the largest cluster represented different proteins. The second largest cluster (above, Table 2) contained 44 different consensus sequences that encoded a total of 10 different proteins, including 4 cDNAs for arginine kinase, 3 cDNAs for alpha actin, and 2 cDNAs for beta actin. In both of these large clusters, there was also a number of consensus sequences that did not match any known proteins. This result is probably reflective of the challenges of developing clustering algorithms that work every time; these challenges are being actively pursued at JGI, and refinements to clustering algorithms are forthcoming.
GO terms for each cluster were categorized by cellular compartment (Fig. 2A) and molecular function (Fig. 2B). Information for biological process was not available for most of the clusters, and thus these data are not shown here. Some clusters had GO terms for more than 1 cellular compartment or more than 1 molecular function.
Construction of the second EST library for P. cinctipes will be performed at the JGI using RNA derived from crabs exposed to a wide array of stressors, thermal conditions, developmental states, and physiological states (Table 5). For this library, we have omitted most of the hepatopancreas tissues because of the very high redundancy of trypsin in this tissue (Table 4). Stressors include temperature, chemicals, heavy metals, high and low salinity (osmotic stressors), and hypoxia. Thermal conditions include warm and cold acclimation, as well as acclimation to warm–cold fluctuating temperatures, and crabs acclimatized to the species' range of natural habitat conditions. By sampling larval and freshly molted crabs, we captured transcripts unique to processes occurring in those stages. Total RNA has been pooled from all of the tissue samples indicated in Table 5, and will be used by JGI to develop and sequence a library of 50 000–75 000 clones. At the completion of that project, we hope to have captured as much of the P. cinctipes transcriptome as possible. The final analyzed set of ESTs will be submitted to GenBank dbEST, and a "unique" gene set will be generated for use in printing cDNA microarrays to be used for functional genomics analyses.
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This work was supported by NSF-IOB 0533920 to J.H.S., NSF graduate research fellowship to K.S.T. DNA sequencing was performed as a part of a 2006 Community Sequencing Project, under the auspices of the US Department of Energy's Office of Science, Biological, and Environmental Research Program, and by the University of California, Lawrence Livermore National Laboratory under Contract No. W-7405-Eng-48, Lawrence Berkeley National Laboratory under Contract No. DE-AC02-05CH11231 and Los Alamos National Laboratory under Contract No. W-7405-ENG-36.
Conflict of interest: None declared.
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Footnotes |
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From the symposium "Genomic and Proteomic Approaches in Crustacean Biology" presented at the annual meeting of the Society for Integrative and Comparative Biology, January 4–8, 2006, at Orlando, Florida.
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