Large-scale single-pass sequencing of cDNAs prepared from specific plant species or tissues has evolved as an inexpensive and efficient gene-discovery tool that can be used to identify novel cDNAs encoding enzymes of specific plant metabolic pathways. Collections of expressed sequence tags from metabolically active tissues can provide quantitative estimates of gene expression levels and thus are being exploited to unravel plant metabolic and regulatory networks.
Addresses
*Department of Botany and Plant Pathology, Michigan State University, East Lansing, Michigan 48823, USA; e-mail: ohlrogge@pilot.msu.edu
†Department of Biochemistry, Michigan State University, East Lansing,
Michigan 48823, USA; e-mail: benning@pilot.msu.edu
Current Opinion in Plant Biology2000, 3:224–228 1369-5266/00/$ — see front matter
© 2000 Elsevier Science Ltd. All rights reserved.
Abbreviations
DXPS 1-deoxy-D-xylulose-5-phosphate synthase
EST expressed sequence tag
Introduction
Dramatic improvements in DNA-sequencing technology have paved the way for the use of large-scale single-pass cDNA sequencing — which has given rise to large expressed sequence tag (EST) collections — to address many biological questions. As of December 1999, GenBank (National Center for Biotechnology Information, URL http://www.ncbi.nlm.nih.gov/) contained approximately 250,000 plant entries in its dbEST database (see [1]; URL http://www.ncbi.nlm.nih.gov/)with the greatest numbers of entries for tomato (51,932), rice (47,449) and Arabidopsis (45,757) [2–4]. One of the first uses of EST collections was in identifying genes involved in specific plant metabolic pathways. Plants synthesize more than 100,000 different compounds, many with high nutritional value, or with med-ical or industrial applications. These valuable compounds are frequently found in exotic species rather than in the crop or model plants whose genomes have been most widely researched. Because it is desirable to introduce valuable genes into a crop plant by genetic engineering, efficient methods of isolating these genes within such exotic species are needed. In the past, it was necessary to isolate the target enzymes from exotic tissues to obtain the molecular infor-mation necessary for the cloning of the encoding gene — an often challenging, time-consuming and sometimes unsuc-cessful endeavor. More recently, large-scale sequencing of cDNAs prepared from tissues with specific metabolic activ-ities has provided a cost-effective and rapid alternative route toward the isolation of several genes (e.g. [5,6•]).
The establishment of high-throughput DNA-sequencing centers in many locations has greatly reduced both the
cost and time involved in obtaining large EST data sets. A single sequencer with 96 capillaries can now produce at least 400 sequences a day, each of 600 base pairs (bp), costing less than $10 per sequence. A researcher can therefore obtain 5000 sequences from a cDNA library within a few weeks and at a cost that is substantially lower than the personnel costs associated with many other forms of gene isolation/discovery. Additional bene-fits of EST approaches are that they require very few assumptions about the target gene and provide broad additional data that may be useful in the future. For example, searching for clones of genes that encode an enzyme involved in the production of a valuable natural product may succeed, but it may subsequently become apparent that other enzymes are needed to accompany it. The EST data set may already contain the information needed to quickly obtain such ‘accessory’ clones, thus eliminating the need for further clone-isolation projects. Later, the same data set may prove extremely valuable to researchers working on other pathways who may then be able to obtain their favorite cDNA by directly accessing the respective EST cDNA set.
How many sequences are needed for gene discovery? If the cDNA library is produced from a tissue source in which the desired products are abundant, then it can be expect-ed that the enzymes neexpect-edexpect-ed to produce such a product will also be relatively abundant (>0.1% of total protein), as will be the cDNA clones corresponding to the relevant mRNA. If the abundance of an enzyme is 0.1% of the total protein and its mRNA is at a similar level, then, in theory, sequencing 3000 clones will provide a greater than 95% chance of discovering this enzyme. In several cases, clones for novel enzymes have been discovered after less than 1000 clones were sequenced (as described below).
Particularly successful examples of EST-based gene dis-covery include the isolation of genes encoding enzymes that are involved in the biosynthesis of unusual fatty acids [7,8•]. This success stems from the fact that the structures
of fatty-acid-modifying enzymes, such as fatty acid desat-urases and related enzymes, follow a general blueprint. When enzyme function cannot be deduced from sequence annotation because no molecular background information is available, the EST strategy has clear limitations. Nevertheless, even in this case, cDNA sequencing may eventually lead to success by targeting abundant classes of ESTs of unknown function derived from metabolically specialized tissues for further analysis. In this review, we will discuss several recent examples of the identification of genes encoding specific plant enzymes using the EST approach. We will also discuss attempts to exploit large-scale EST data sets to provide transcriptional profiles and to unravel regulatory metabolic networks.
Unraveling plant metabolism by EST analysis
EST sequencing as a gene discovery tool
Fatty-acid modification
The first application of large-scale sequencing of cDNAs derived from a plant tissue and having specialized metabol-ic activity was the isolation of the cDNA encoding the enzyme responsible for ricinoleic acid biosynthesis [5]. Because of the historic significance and to illustrate the principles of the approach, we will discuss this example in detail. Ricinoleic acid (i.e. 12-hydroxyoleic acid) has many industrial applications. It is highly abundant (90% of total fatty acids) in castor seeds but absent from most other plants. Although the activity of castor hydroxylase, the cru-cial enzyme involved in ricinoleic acid biosynthesis, could be studied in microsomal fractions isolated from developing seeds, this enzyme is labile and a successful biochemical purification seemed intractable. Nevertheless, multiple lines of biochemical evidence suggested that the reaction mechanism of this hydroxylase should be similar to that of membrane-bound desaturases [9]. Equipped with this knowledge, Van de Loo et al.[5] reasoned that the hydrox-ylase involved in ricinoleic acid biosynthesis should contain a pair of histidine-rich motifs, which are characteristic of membrane-bound desaturases. In addition, the gene encoding the hydroxylase should be expressed in seeds but not leaves (which lack ricinoleic acid), and its mRNA abun-dance in developing seeds should be similar to the known abundance of mRNAs encoding other fatty acid desaturas-es. Accordingly, a cDNA library was constructed from mRNA isolated from developing castor-bean endosperm [10]. Clones were randomly picked, arrayed and enriched for seed-specific mRNAs by probing the arrays with first-strand cDNA derived from leaf mRNA. Further enrichment was achieved by eliminating highly abundant clones by hybridizing the arrays with storage protein encod-ing probes. In addition, usencod-ing an immunoblottencod-ing procedure, clones reacting with antiserum against micro-somes from developing castor-bean endosperm were selected for sequencing. Among 468 clones from this enriched set, two showed similarity to a clone encoding the membrane-bound desaturase from Arabidopsis. Following expression of the full-length cDNA in tobacco, ricinoleic acid was produced, thereby confirming that a cDNA encod-ing the hydroxylase had been identified [5].
More recently, a similar EST approach has been successfully applied to identify fatty-acid conjugases for the first time [6•]. This new type of fatty-acid modifying enzyme is
involved in the lipid-linked biosynthesis of fatty acids with conjugated double bonds, such as the 18-carbon fatty acids α-eleostearic acid and α-parinaric acid. These fatty acids are the main constituents of tung oil and are ideally suited as drying agents in paints and varnishes. The developing seeds of certain plant species, such as Momordica charantia and Impatiens balsamina, contain high concentrations of these fatty acids, whereas the leaves of the same species are devoid of them. The mechanism for the introduction of conjugated double bonds into fatty acids was unknown, but either desat-urase- or lipoxygenase-like reactions had been proposed.
Thus, Cahoon et al.[6•] prepared cDNA libraries from
devel-oping seeds of M. charantia and I. balsamina and obtained 5′-sequences from approximately 3000 randomly picked clones from each library. In this case, no enrichment proce-dures were used. In the M. charantia and I. balsamina EST sets, 3 and 12 copies, respectively, of cDNAs encoding pro-teins with similarity to oleoyl-phosphatidylcholine-type microsomal desaturases were detected, and the proteins were designated MomoFadX and ImpFadX, respectively. Expression of full-length cDNAs in yeast and somatic trans-formation of soybean embryos with the respective constructs confirmed the conjugase activity of both MomoFadX and ImpFadX; this work also demonstrated that their cDNAs can be used to engineer fatty acids with conjugated double bonds in crop plants. Furthermore, the cloning of these fatty acid conjugase encoding cDNAs provides the first step towards the elucidation of the mechanism that introduces conjugated double bonds into fatty acids.
Isoprenoid biosynthesis
Although developing seeds are often quite specialized with regard to their biosynthetic capabilities, metabolic specializa-tion may have reached its pinnacle in the oil glands of peppermint. The cells of these glands devote almost all of their biosynthetic capacity toward synthesis of isoprenoid products such as menthol. A key accomplishment leading to the successful application of ESTs to this system was the iso-lation of the oil glands and preparation of sufficient mRNA for cDNA library construction [11]. Single-pass sequencing of 150 randomly picked cDNA clones from a peppermint oil gland cDNA library can hardly be deemed ‘large-scale’, but it was sufficient to allow the discovery of cDNAs encoding two novel proteins that are involved in isoprenoid biosynthe-sis. In fact, 8–10% of the cDNAs in the library appear to encode enzymes that are involved in isoprenoid biosynthesis [12], including (E)-β-farnesene synthase [11] and 1-deoxy-D-xylulose-5-phosphate synthase (DXPS) [13••].
The first enzyme identified, (E)-β-farnesene synthase [11], catalyzes the conversion of farnesyl diphosphate to (E)-β-farnesene, an acyclic sesquiterpene olefin that is present in many plants and is a chemical signal in some plant–insect interactions. The rationale for using the EST approach was based on three main factors: the presence of (E)-β-farnesene (3.4% of the sesquiterpenes) in pepper-mint oil; initial experiments that showed that terpenoid biosynthetic enzymes such as monoterpene cyclase and limonen synthase are highly abundant in the peppermint oil gland; and the availability of molecular information on other plant sesquiterpene synthases. Expression of the candidate cDNA in Escherichia colifollowed by analysis of the recombinant protein confirmed the nature of the encoded novel sesquiterpene synthase.
The second enzyme identified, DXPS [13••], catalyzes the
two encoding a protein with high sequence similarity to CLA1 fromArabidopsis [15]. The molecular function of CLA1 is unknown, but the phenotype of the cla1 mutant is consis-tent with a deficiency in isoprenoid biosynthesis. Expression of a full-length cDNA corresponding to the two ESTs from the peppermint oil gland library in E. coli and analysis of the recombinant protein led to the discovery of DXPS-encoding cDNAs [13••]. This achievement may represent a crucial step
towards the genetic engineering of isoprenoids in plants.
Cell-wall biosynthesis
Plant cell walls consist of intricately interwoven, highly complex polymers, and our insights into their biosynthesis are still sketchy. For example, success in identifying genes encoding plant cellulose synthase, which is responsible for the biosynthesis of the world’s most abundant biopolymer, cellulose, remained elusive until Pear et al. [16] sequenced 250 randomly picked cDNAs from developing cotton fibers. They were able to identify two cDNAs encoding proteins with similarity to known bacterial cellulose syn-thases and to show that the expression of the respective genes, celA1 and celA2, is strongly induced in developing cotton fibers at the onset of secondary cell-wall biosynthe-sis. Although no in vitroassay for cellulose produced by the recombinant cellulase synthase could be established, the binding of the substrate UDP–glucose was observed. Taken together, these results suggest that the two cDNAs encode cellulose synthases. Most recently, it has been shown that antibodies against these proteins react with the rosette terminal complex [17•], a cell-wall-associated
struc-ture that is visible by electron microscopy and that is believed to represent the cell-wall cellulose-synthase com-plex. This long-awaited breakthrough in cell-wall research is not the end of the story because a large number of cel-lulose-synthase-like ESTs are present in different plant EST data-sets and their function is not yet known [18].
Secondary cell walls are the main structural elements of wood, and two large-scale sequencing projects have recently been targeted at identifying of genes involved in gym-nosperm [19] and angiosperm [20] wood formation. In the first study [19], 1097 ESTs from four cDNA libraries were combined into one data set. The four libraries were derived from bent loblolly pine trees, specifically compression wood (i.e. the reaction wood formed on the underside of a leaning tree), normal wood, and two reciprocally substracted libraries derived from the former two. Approximately 10% of the ESTs encoded proteins with similarity to those known to be involved in complex-carbohydrate biosyntheses or lignin biosynthesis, or cell-wall-associated proteins, suggesting that this data set is enriched in ESTs encoding proteins that are involved in cell-wall biosynthesis. Nevertheless, because the data set was derived from four different libraries, two of which were were enriched in cDNAs specific to normal or compression wood, it will be difficult to make meaningful comparisons with other data sets with regard to transcript abundance. The second wood project [20] involved two poplar species and two different libraries: a more general,
cambial-region-specific library from one species that was expected to yield ESTs involved in xylem and phloem for-mation, and a more specific cDNA library from the developing xylem of the other species. A total number of 5692 ESTs was obtained, of which 4% were found to be relat-ed to wood formation. It was observrelat-ed that ESTs encoding proteins involved in xylem formation were twice as common in the 883 ESTs derived from the developing xylem library as in the general cambium-specific library. Interestingly, the gymnosperm [19] and angiosperm [20] data sets had similar composition with regard to the frequency of ESTs encoding proteins involved in wood formation and those encoding pro-teins of unknown function. Nevertheless, in order to interpret properly the comparison between gymnosperm and angiosperm data sets, a truly interesting experiment, the data sets would have to be acquired in similar ways with regard to library preparation and clone enrichment.
Transcriptional profiling and metabolic networks
In addition to providing an efficient method for gene discov-ery, EST data sets can also provide information on gene expression [21•,22••]. This aspect of EST analysis is basedon the rationale that if gene X is highly expressed, (leading to high mRNAX levels), then cDNAs corresponding to mRNAXwill be abundant in a cDNA library made from the tissue in which gene X is expressed. After random sequenc-ing of a large number of clones from the cDNA library, simply counting the number of ESTs that correspond to the mRNA for gene X will provide an estimate of the abundance of mRNAXin the original population. Furthermore, subject to the limitations discussed below, the number of EST sequences corresponding to mRNAX divided by the total number of ESTs in the data set provides an absolute esti-mate of mRNAX abundance. Such ‘electronic or digital’ Northerns have both advantages and limitations in compari-son to conventional Northern analysis or microarray analysis.
Conventional Northern-blot analysis is almost always per-formed with only one or a few genes, and the experimental objective is usually to compare expression of the same gene under different conditions or in different tissues. Although obtaining quantitative data on absolute mRNA expression levels is possible by careful comparison to standards, such analysis is almost never conducted. In principle, microarray analysis makes it possible to analyze simultaneously the expression levels of thousands of genes. Nevertheless, the technique is similar to Northern-blot analysis with regard to its quantitative aspects. In most microarray techniques, because of a number of technical limitations, the absolute intensity of the fluorescence signal on a spot may not reflect absolute mRNA levels. Microarray techniques can therefore provide reliable data when comparing the ratio of expression of the same mRNA under different conditions, but compar-ing the relative expression of different genes is problematic.
have an added advantage of making it possible to compare the mRNA expression of different genes quantitatively. A few limitations to this principle must be kept in mind. First, in a few cases, mRNA secondary structure may cause reverse transcriptase to ineffectively produce cDNA and therefore the copy number of such cDNAs will under-rep-resent the mRNA species from which they are derived. Second, the statistics of sampling small numbers from a large population must be considered. Audic and Claverie [23] addressed this statistical issue and established a rigor-ous significance test for identifying differentially expressed genes by comparing relative abundance of ESTs. Third, the usefulness of EST data sets to estimate gene expression levels will sometimes be compromised if the data originate from non-normalized cDNA libraries. Unfortunately, for the purposes of digital Northerns, the investigator wanting to use EST sequencing as a tool for gene discovery will frequently try to normalize or subtract a cDNA library to enhance the representation of the sought-after gene. Such procedures may or may not limit the usefulness of the data set for comparison of gene expression levels. For example, removing only the abun-dant storage-protein genes from a seed library should not alter the relative EST numbers of the vast majority of enzymes or other less abundant mRNA.
Almost all of the plant EST data in dbEST are derived from non-normalized cDNA libraries, making this large data set useful for digital-Northern analysis. A number of ArabidopsiscDNA sequences that represent re-sequencing of clones previously selected as ‘unique’ have, however, recently been deposited in GenBank. Future use of dbEST for digital Northerns in Arabidopsis will need to accommodate this new set of data. Using the digital-Northern analysis approach, Mekhedov et al. [22••] have
recently analyzed the abundance of ESTs corresponding to 62 proteins that are involved in plant lipid biosynthesis. Their results are available via the internet at http://www.bpp.msu.edu/lgc/index.html. This analysis provided the first semi-quantitative comparison of the mRNA levels of a large number of enzymes in a plant metabolic pathway. In general, analyses of the data sets from Arabidopsisand rice revealed similar patterns of EST abundance, thereby providing support for the validity of the digital-Northern approach. Furthermore, the abun-dance of ESTs for specific reactions correlated well with our understanding of the enzymology and flux characteris-tics of the pathway. For example, desaturases, which have low catalytic efficiency, were found to be more abundant than thioesterases or acyltransferases, which are extremely efficient enzymes with high turnover rates. In a few cases, however, the number of ESTs did not match expectations, and these examples may provide initial clues regarding the regulation of these enzymes. For instance, ESTs for the FatB acyl–ACP thioesterase occurred 21 times compared to
seven times for FatA acyl–ACP thioesterase, although flux
through the FatA reaction is several-times greater than through the FatB reaction.
We have also recently examined an EST data set derived from developing Arabidopsis seeds (JA Whiteet al., unpub-lished data). More than 10,000 ESTs were partially sequenced from a library from which cDNAs for storage pro-teins had been largely subtracted. Approximately 40% of the ESTs do not correspond to those previously deposited in dbEST; this new data set has therefore revealed a substan-tially different set of transcripts to those present in other tissues. Consistent with the major storage of oil in Arabidopsis seeds, the abundance of ESTs representing lipid-biosynthet-ic enzymes was two to five times higher than in the non-seed Arabidopsis EST data sets. When combined with microarray data, the EST data have revealed several hundred previous-ly uncharacterized genes whose expression is highprevious-ly specific to seeds. Included in this subset are a number of transcrip-tion factors, kinases and other proteins that are probably involved in regulation of seed metabolism. Thus, this process has identified ‘candidate’ genes that may control the specific metabolism of oilseeds and that now can be exam-ined further in transgenic plant experiments.
Conclusions
The dramatic reduction in the cost of high-throughput DNA sequencing now makes this technology affordable for almost all researchers. In most cases, the ability to generate thousands of DNA sequences provides investigators not only with low-cost identification of a target gene, but also with a wealth of information about gene expression and metabolism in the plant tissue and species from which the data were derived. Expansion of large-scale sequencing to a diverse range of non-crop species will help biologists to access the vast biodiversity represented by more than 300,000 plant species. When such sequence data are deposited in the public domain, other researchers with dif-ferent interests or perspectives may be able to ‘mine’ new insights from them. Deriving maximum information from such data sets also requires new bioinformatics tools that are only now being developed. Software is needed that can allow comparisons of large sequence data sets to identify common themes in gene expression, in addition to those patterns that are species- or tissue-specific. It is likely that unexpected dividends will accrue as our ability to organize these new large data sets evolves.
Update
Schmitt et al. [24] have recently described a four-step pro-cedure for systematic mining of whole EST libraries for differentially expressed genes. Using about four million human ESTs, they eliminated redundant entries from the EST libraries before building contigs of maximal length upon the remaining ESTs. Putative genes were compared against a database comprising ESTs from 16 different tis-sues (both normal and tumour affected) to determine whether or not they are differentially expressed (i.e. a dig-ital-Northern approach was used).
ESTs in establishing expression profiles. T his review pro-vides a brief summary of recent data implicating genes that may be involved in apoptosis in the cardiovascular system.
Machine learning techniques that can predict secretory proteins from protein, genomic and EST sequences have also been described recently [26].
Acknowledgements
Work in the authors’ laboratories is supported by grants from the National Science Foundation (DCB90-05290 and MCB 9807943), the Consortium for Plant Biotechnology Research (CPBR), and the Department of Energy (DE-FG02-87ER12729 and DE-FG02-98ER20305). We acknowledge the Michigan Agricultural Experiment Station for its support of this research.
References and recommended reading
Papers of particular interest, published within the annual period of review, have been highlighted as:
• of special interest
••of outstanding interest
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