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Plants require sunlight, water, CO2, and essential nutrients to drive photosynthesis and fulfill their life cycle. The photosynthetic apparatus resides in chloroplasts and fundamentally relies on transition metals as catalysts and cofactors. Accordingly, chloroplasts are particularly rich in iron (Fe), manganese (Mn), and copper (Cu). Owing to their redox properties, those metals need to be carefully balanced within the cell. However, the regulation of transition metal homeostasis in chloroplasts is poorly understood. With the availability of the arabidopsis genome information and membrane protein databases, a wider catalogue for searching chloroplast metal transporters has considerably advanced the study of transition metal regulation. This review provides an updated overview of the chloroplast transition metal requirements and the transporters involved for efficient photosynthesis in higher plants.

Twenty years ago, the Arabidopsis thaliana genome sequence was published. This was an important moment as it was the first sequenced plant genome and explicitly brought plant science into the genomics era. At the time, this was not only an outstanding technological achievement, but it was characterized by a superb global collaboration. The Arabidopsis genome was the seed for plant genomic research. Here, we review the development of numerous resources based on the genome that have enabled discoveries across plant species, which has enhanced our understanding of how plants function and interact with their environments.

International audience; Plant long noncoding RNAs (lncRNAs) have emerged as important regulators of chromatin dynamics, impacting on transcriptional programs leading to different developmental outputs. The lncRNA AUXIN-REGULATED PROMOTER LOOP (APOLO) directly recognizes multiple independent loci across the Arabidopsis genome and modulates their three-dimensional chromatin conformation, leading to transcriptional shifts. Here, we show that APOLO recognizes the locus encoding the root hair (RH) master regulator ROOT HAIR DEFECTIVE 6 (RHD6) and controls RHD6 transcriptional activity, leading to cold-enhanced RH elongation through the consequent activation of the transcription factor gene RHD6-like RSL4. Furthermore, we demonstrate that APOLO interacts with the transcription factor WRKY42 and modulates its binding to the RHD6 promoter. WRKY42 is required for the activation of RHD6 by low temperatures and WRKY42 deregulation impairs cold-induced RH expansion. Collectively, our results indicate that a novel ribonucleoprotein complex with APOLO and WRKY42 forms a regulatory hub to activate RHD6 by shaping its epigenetic environment and integrate signals governing RH growth and development.

Heavy metal exposure is a serious environmental stress in plants. However, plants have evolved several strategies to improve their heavy metal tolerance. Heavy metal-associated proteins (HMPs) participate in heavy metal detoxification. Here, we identified 46 and 55 HMPs in rice and Arabidopsis, respectively, and named them OsHMP 1–46 and AtHMP 1–55 according to their chromosomal locations. The HMPs from both plants were divided into six clades based on the characteristics of their heavy metal-associated domains (HMA). The HMP gene structures and motifs varied greatly among the different classifications. The HMPs had high collinearity and were segmentally duplicated. A cis-element analysis revealed that the HMPs may be regulated by different transcription factors. An expression profile analysis disclosed that only eight OsHMPs were constitutive in rice tissues. Of these, the expression of OsHMP37 was far higher than that of the other seven genes while OsHMP28 was expressed exclusively in the roots. For Arabidopsis, nine AtHMPs presented with very high transcript levels in all organs. Most of the selected OsHMPs were differentially expressed in various tissues under different heavy metal stresses. Only OsHMP09, OsHMP18, and OsHMP22 showed higher expression levels in all tissues under different heavy metal stresses. In contrast, most of the selected AtHMPs had nearly constant expression levels in different tissues under various heavy metal stresses. The AtHMP20, AtHMP23, AtHMP25, AtHMP31, AtHMP35, AtHMP46 expression levels under different heavy metal stresses were higher in the leaves and roots. The foregoing discoveries elucidated HMP evolution in monocotyledonous and dicotyledonous plants and may helpful functionally characterize HMPs in the future.

In the field of the bioinformatics, during osmotic stress response genes mining processing, it is also very crucial to verify experimental data obtained in the course of complex experiments by using the computer. Aim of this paper is taking Arabidopsis thaliana as the experimental crop, designing technology roadmap, taking advantage of the skills of function and programming, then designing algorithms. After using the program to predict the transcription start point, the promoter sequence is extracted and simplified. In addition, different alignment methods are classified. Then, comparing the promoter sequence with the cis-element and using the formula for further processing. Finally, get the probability P value, which provide further help to experts and scholars on the basis of probability values to determine the correlation between the osmotic stress. The experimental data source of chromosomal sequences is received from Genbank database files, and cis-element sequence that associated with osmotic stress is collected from TRANSFAC and TRRD database. From this, the authors not only used the Arabidopsis promoter as the experimental data, but also use a variety of eukaryotic promoters include promoters GhNHX1 rice, cotton OsNHX1 promoter, as a comparison. Wherein the data obtained in the biological laboratory, which in the course of running the program, 70% have been verified. P value close to 0.8, this article will be treated as the promoter contains osmotic stress cis-elements, the expression of gene induced by osmotic stress. For thaliana, cotton and rice, programs running average time was 51s, 72s and 114s. Through the use of some commonly used bioinformatics gene mining algorithms, MEME algorithm and BioProspector algorithm for the same data have been processed, the average running time of the system is increasing with the increase of data. Running time of MEME algorithm increases from 60s to reach 198s, BioProspector algorithm increases from 45s to 150s model process used herein were 50s, 75s, 110s, 135s. At the same time, the authors can see in the three algorithms, the model algorithm used herein with respect to the first two more optimized. To ensure the accuracy rate, meanwhile has high speed and stabilization of higher.

Recent works have shed light on the long-distance interorgan signaling by which hormone-like peptides precisely regulate physiological effects in a manner similar to phytohormones. Many such peptides have already been identified in the primary model plant, Arabidopsis thaliana. In addition, Arabidopsis genome reanalysis revealed over 7000 novel candidate small coding genes, some of which are likely to be associated with hormone-like peptides. Hormone-like peptides have also been reported to play critical roles in interorgan communications during morphogenesis and stress responses. In this review, we focus on the functional roles of hormone-like peptides and small coding genes in cell-to-cell and/or long-distance communications during plant stress signaling and development and discuss the evolutionary conservation of these peptides among plants.

Methylation systems have been conserved during the divergence of plants and animals, although they are regulated by different pathways and enzymes. However, studies on the interactions of the epigenomes among evolutionarily distant organisms are lacking. To address this, we studied the epigenetic modification and gene expression of plant chromosome fragments (~30 Mb) in a human–Arabidopsis hybrid cell line. The whole-genome bisulfite sequencing results demonstrated that recombinant Arabidopsis DNA could retain its plant CG methylation levels even without functional plant methyltransferases, indicating that plant DNA methylation states can be maintained even in a different genomic background. The differential methylation analysis showed that the Arabidopsis DNA was undermethylated in the centromeric region and repetitive elements. Several Arabidopsis genes were still expressed, whereas the expression patterns were not related to the gene function. We concluded that the plant DNA did not maintain the original plant epigenomic landscapes and was under the control of the human genome. This study showed how two diverging genomes can coexist and provided insights into epigenetic modifications and their impact on the regulation of gene expressions between plant and animal genomes.

Mapping-by-sequencing is a rapid method for identifying both natural as well as induced variations in the genome. However, it requires extensive bioinformatics expertise along with the computational infrastructure to analyze the sequencing data and these requirements have limited its widespread adoption. In the current study, we develop an easy to use tool, artMAP, to discover ethyl methanesulfonate (EMS) induced mutations in the Arabidopsis genome. The artMAP pipeline consists of well-established tools including TrimGalore, BWA, BEDTools, SAMtools, and SnpEff which were integrated in a Docker container. artMAP provides a graphical user interface and can be run on a regular laptop and desktop, thereby limiting the bioinformatics expertise required. artMAP can process input sequencing files generated from single or paired-end sequencing. The results of the analysis are presented in interactive graphs which display the annotation details of each mutation. Due to its ease of use, artMAP made the identification of EMS-induced mutations in Arabidopsis possible with only a few mouse click. The source code of artMAP is available on Github (https://github.com/RihaLab/artMAP).

TGACG-BINDING FACTORs (TGAs) control the developmental or defense-related processes. In Arabidopsis thaliana, the functions of at least TGA2 and PERIANTHIA (PAN) can be repressed by interacting with CC-type glutaredoxins, which have the potential to control the redox state of target proteins. As TGA1 can be redox modulated in planta, we analyzed whether some of the 21 CC-type glutaredoxins (ROXYs) encoded in the Arabidopsis genome can influence TGA1 activity in planta and whether the redox active cysteines of TGA1 are functionally important. We show that the tga1 tga4 mutant and plants ectopically expressing ROXY8 or ROXY9 are impaired in hyponastic growth. As expression of ROXY8 and ROXY9 is activated upon transfer of plants from hyponasty-inducing low light to normal light, they might interfere with the growth-promoting function of TGA1/TGA4 to facilitate reversal of hyponastic growth. The redox-sensitive cysteines of TGA1 are not required for induction or reversal of hyponastic growth. TGA1 and TGA4 interact with ROXYs 8, 9, 18, and 19/GRX480, but ectopically expressed ROXY18 and ROXY19/GRX480 do not interfere with hyponastic growth. Our results therefore demonstrate functional specificities of individual ROXYs for distinct TGAs despite promiscuous protein-protein interactions and point to different repression mechanisms, depending on the TGA/ROXY combination.

In the 1980s, the first genes encoding plant enzymes were cloned and plant genetic transformation was born. With the new century, knockout technology was established and the Arabidopsis genome sequence was published. In the last decade, the discipline of plant genomics has expanded rapidly. These developments promised a quantum leap forward in understanding plant biology. In some areas this has undoubtedly been the case, but what about in metabolism and related physiology? This issue of Current Opinion in Plant Biology presents a spectrum of topics from subcellular to global levels. It aims to provide an update on some mainstream topics and some that are less well known. It hopefully provides not only an update, but also an opportunity to reflect on the achievements of the last 35 years and to anticipate the challenges and possibilities in the next 35 years to 2050.

Agrobacterium tumefaciens mediated T-DNA integration is a common tool for plant genome manipulation. However, there is controversy regarding whether T-DNA integration is biased towards genes or randomly distributed throughout the genome. In order to address this question, we performed high-throughput mapping of T-DNA-genome junctions obtained in the absence of selection at several time points after infection. T-DNA-genome junctions were detected as early as 6 hours post-infection. T-DNA distribution was apparently uniform throughout the chromosomes, yet local biases toward AT-rich motifs and T-DNA border sequence micro-homology were detected. Analysis of the epigenetic landscape of previously isolated sites of T-DNA integration in Kanamycin-selected transgenic plants showed an association with extremely low methylation and nucleosome occupancy. Conversely, non-selected junctions from this study showed no correlation with methylation and had chromatin marks, such as high nucleosome occupancy and high H3K27me3, that correspond to three-dimensional-interacting heterochromatin islands embedded within euchromatin. Such structures may play a role in capturing and silencing invading T-DNA., Author summary Agrobacterium tumefaciens mediated T-DNA integration is an important tool for genetic engineering in plants. This work compares the genetic and epigenetic landscapes of T-DNA-genome junctions under selective and non-selective conditions. Under selection, preferential junctions in low-nucleosome occupancy and hypomethylated regions were found. In the absence of selection, these biases disappeared and T-DNA-genome junctions were uniformly distributed with a preference for 3D-interacting heterochromatin islands embedded within euchromatin, suggesting that many integration events become transcriptionally inactive.

UNLABELLED The schema for UCSC Known Genes (knownGene.txt) has been widely adopted for use in both standard and custom downstream analysis tools/scripts. For many popular model organisms (e.g. Arabidopsis), sequence and annotation data tables (including "knownGene.txt") have not yet been made available to the public. Therefore, it is of interest to describe Tbl2KnownGene, a .tbl file parser that can process the contents of a NCBI .tbl file and produce a UCSC Known Genes annotation feature table. The algorithm is tested with chromosome datasets from Arabidopsis genome (TAIR10). The Tbl2KnownGene parser finds utility for data with other organisms having similar .tbl annotations. AVAILABILITY Perl scripts and required input files are available on the web at http://thoth.indstate.edu/~ybai2/Tbl2KnownGene/ index.html.

Mainly driven by the availability of the first Arabidopsis genome sequence in 2000 a rapid development of high throughput analytical techniques were developed and termed transcriptomics. This development was quickly followed by developing metabolite-profiling technologies, metabolomics. The ever-growing data bases made the development of new biostatistical and bioinformatics tools necessary. These ‘omics’ approaches were also applied to analyze the response of plants towards sulfate deprivation with the aim to gain a more complete, holistic view on plant metabolism and its control in response to varied nutrient supply. Early results though already providing novel results and fostering new routes of investigation were hampered by the incomplete annotation of the genes of the Arabidopsis genome. In recent years this informational gap was largely filled. Thus, we revisit here one old data set obtained at the infancy of ‘omics’ research and indicate novel conclusions possible when re-assessing these data as well as indicate new possibilities of continued analyses.

Approximately 450 glycosyltransferase (GT) sequences have been already identified in the Arabidopsis genome that organize into 40 sequence-based families, but a vast majority of these gene products remain biochemically uncharacterized open reading frames. Given the complexity of the cell wall carbohydrate network, it can be inferred that some of the biosynthetic genes have not yet been identified by classical bioinformatics approaches. With the objective to identify new plant GT genes, we designed a bioinformatic strategy that is based on the use of several remote homology detection methods that act at the 1D, 2D, and 3D level. Together, these methods led to the identification of more than 150 candidate protein sequences. Among them, 20 are considered as putative glycosyltransferases that should further be investigated since known GT signatures were clearly identified.

Eight years after publication of the Arabidopsis genome sequence and two years before completing the first phase of an international effort to characterize the function of every Arabidopsis gene, plant biologists remain unable to provide a definitive answer to the following basic question: what is the minimal gene set required for normal growth and development? The purpose of this review is to summarize different strategies employed to identify essential genes in Arabidopsis, an important component of the minimal gene set in plants, to present an overview of the datasets and specific genes identified to date, and to discuss the prospects for future saturation of this important class of genes. The long-term goal of this collaborative effort is to facilitate basic research in plant biology and complement ongoing research with other model organisms.

The problem of predicting non-long terminal repeats (LTR) like long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs) from the DNA sequence is still an open problem in bioinformatics. To elevate the quality of annotations of LINES and SINEs an automated tool "RetroPred" was developed. The pipeline allowed rapid and thorough annotation of non-LTR retrotransposons. The non-LTR retrotransposable elements were initially predicted by Pairwise Aligner for Long Sequences (PALS) and Parsimonious Inference of a Library of Elementary Repeats (PILER). Predicted non-LTR elements were automatically classified into LINEs and SINEs using ANN based on the position specific probability matrix (PSPM) generated by Multiple EM for Motif Elicitation (MEME). The ANN model revealed a superior model (accuracy = 78.79 +/- 6.86 %, Q(pred) = 74.734 +/- 17.08 %, sensitivity = 84.48 +/- 6.73 %, specificity = 77.13 +/- 13.39 %) using four-fold cross validation. As proof of principle, we have thoroughly annotated the location of LINEs and SINEs in rice and Arabidopsis genome using the tool and is proved to be very useful with good accuracy. Our tool is accessible at http://www.juit.ac.in/RepeatPred/home.html.

Background Scaffolding is a crucial step in the genome assembly process. Current methods based on large fragment paired-end reads or long reads allow an increase in continuity but often lack consistency in repetitive regions, resulting in fragmented assemblies. Here, we describe a novel tool to link assemblies to a genome map to aid complex genome reconstruction by detecting assembly errors and allowing scaffold ordering and anchoring. Results We present MaGuS (map-guided scaffolding), a modular tool that uses a draft genome assembly, a genome map, and high-throughput paired-end sequencing data to estimate the quality and to enhance the continuity of an assembly. We generated several assemblies of the Arabidopsis genome using different scaffolding programs and applied MaGuS to select the best assembly using quality metrics. Then, we used MaGuS to perform map-guided scaffolding to increase continuity by creating new scaffold links in low-covered and highly repetitive regions where other commonly used scaffolding methods lack consistency. Conclusions MaGuS is a powerful reference-free evaluator of assembly quality and a map-guided scaffolder that is freely available at https://github.com/institut-de-genomique/MaGuS. Its use can be extended to other high-throughput sequencing data (e.g., long-read data) and also to other map data (e.g., genetic maps) to improve the quality and the continuity of large and complex genome assemblies.

The development of complex eukaryotic organisms can be viewed as the selective expression of distinct fractions of the genome in different organs or tissue types in response to developmental and environmental cues. Here, we generated a genome expression atlas of 18 organ or tissue types representing the life cycle of Arabidopsis (Arabidopsis thaliana). We showed that each organ or tissue type had a defining genome expression pattern and that the degree to which organs share expression profiles is highly correlated with the biological relationship of organ types. Further, distinct fractions of the genome exhibited expression changes in response to environmental light among the three seedling organs, despite the fact that they share the same photoperception and transduction systems. A significant fraction of the genes in the Arabidopsis genome is organized into chromatin domains exhibiting coregulated expression patterns in response to developmental or environmental signals. The knowledge of organ-specific expression patterns and their response to the changing environment provides a foundation for dissecting the molecular processes underlying development.

Putative transcription factors bearing a particular DNA-binding domain called “MADS-box”, have been mainly involved in processes related to flower development. It is generally accepted that MADS-box genes may have played a central role in the evolution of plant reproductive structures. During the last years increasing evidence points to more general roles of these factors that spans to the control of the flowering time, but also to other non-reproductive processes. Moreover, sequencing of the Arabidopsis genome has led to the recognition of above hundred MADS-box genes in this model organism, most of them still uncharacterized. This opens the possibility of uncovering new roles for MADS-box genes in plant development and evolution.

The sequencing of the Arabidopsis genome revealed a multiplicity of thioredoxins (TRX), ubiquitous protein disulfide oxido-reductases. We have analyzed the TRX family in the genome of the unicellular green alga Chlamydomonas reinhardtii and identified eight different thioredoxins for which we have cloned and sequenced the corresponding cDNAs. One of these TRXs represents a new type that we named TRX y. This most probably chloroplastic TRX is highly conserved in photosynthetic organisms. The biochemical characterization of the recombinant protein shows that it exhibits a thermal stability profile and specificity toward target enzymes completely different from those of TRXs characterized so far.

Calmodulin (CaM) is an essential calcium-binding protein that binds to and activates a diverse population of downstream targets (calmodulin-binding proteins; CaMBPs) that carry out its critical signalling functions. In spite of the central importance of CaM in Ca2+-mediated signal transduction pathways in all eukaryotes, many CaMBPs remain to be identified and characterized. SDS-PAGE followed by gel overlay with recombinant, metabolically radiolabelled CaM (Calmodulin-binding Overlay Technique, CaMBOT) is a valuable method for following behavioural, developmental, forensic and physiological changes in total CaMBP populations and to identify candidate CaMBPs for further study. CaMBOT has also been adapted to isolate cDNAs encoding novel CaMBPs in various organisms. Recently, the method was used to examine the CaMBP complement encoded by the Arabidopsis genome and to identify a new family of transcription activators. To add to its diversity, CaMBOT may be useful for finding target proteins for work on phytoremediation and for the screening of pharmaceuticals and toxic agents that, directly or indirectly, affect CaM and its target proteins. This review discusses all of these topics and the role of CaMBOT in characterizing a functional unit of the proteome—proteins regulated by calmodulin.

The Arabidopsis genome encodes numerous iron-containing proteins such as iron-sulfur (Fe-S) cluster proteins and hemoproteins. These proteins generally utilize iron as a cofactor, and they perform critical roles in photosynthesis, genome stability, electron transfer, and oxidation-reduction reactions. Plants have evolved sophisticated mechanisms to maintain iron homeostasis for the assembly of functional iron-containing proteins, thereby ensuring genome stability, cell development, and plant growth. Over the past few years, our understanding of iron-containing proteins and their functions involved in genome stability has expanded enormously. In this review, I provide the current perspectives on iron homeostasis in Arabidopsis, followed by a summary of iron-containing protein functions involved in genome stability maintenance and a discussion of their possible molecular mechanisms.

Since the Arabidopsis genome was sequenced, hundreds of plant genomes have either been sequenced or are in sequencing progress. Reference genome sequences and large-scale genome sequencing technologies have initiated a new era in molecular breeding. The field of genomics is progressing rapidly and has already provided invaluable practical products for plant molecular breeding. Here, we review progress in genome sequencing technology and its application to plant breeding. We introduce various genomics tools and discuss how next-generation genome sequencing and genotyping technologies have been applied to high-throughput molecular breeding. We also describe the use of epigenome analysis to interpret phenotypic variations that cannot be explained by simple genetics based on the underlying DNA sequence alone, but rather by epigenetically-controlled mechanisms.

Folates are essential cofactors for one-carbon transfer reactions, which are central to plant metabolism. Plants synthesize folates de novo, and are key sources of dietary folate for humans. Research into plant folates therefore impacts human nutrition. Biochemical progress, the sequencing of the Arabidopsis genome, and EST databases are now painting a clear picture of the folate synthesis pathway in plants and its surprising compartmentation. Moreover, new analytical advances will help to elucidate plant folate turnover and transport, which are practically unexplored.

The Arabidopsis genome sequence has given us an inventory of the genes needed to specify a flowering plant. Plants are highly diverse in appearance and the mechanisms whereby this diversity has arisen need explanation. A fundamental question is to what extent diversity arises from remodelling of gene function or relocation of gene pathways, rather than from the gain or loss of genes. Similar types of genetic rewiring may be responsible for both intra- and inter-specific differences in developmental processes. Recent advances in the understanding of shoot, flower and leaf development provide insights to this question.

The dawn of the third millenium has witnessed an impressive leap forward in the number of approaches, techniques and materials available to tackle what has seemingly become the number one goal in plant as well as animal and human genetics: assigning functions to genes. The economic consequences, patenting included, and potential benefits ensuing from this exercise are enormous and long-lasting. As trivial and obvious as this may sound, it has become clear to most of those engaged in this exercise that the road to gene function discovery is going to be long and winding and the ride will not be a smooth one, especially for quantitative traits (Beavis, 1994; Flint and Mott, 2001). Nevertheless, map-based cloning of QTLs for agronomically valuable traits has already been reported in rice (Yano et al., 2000; Takahashi et al., 2001) and may soon become a reality also in maize (Salvi et al., this issue). This special issue presents a number of articles illustrating the type of contributions which genomics can offer to unravel the path from genes to phenotypes and vice versa in cereals and, indirectly, also in other crops. In this virtual relay, each article shows how structural and/or functional genomics can improve our capacity to uncover and deploy genetic variation useful to improve food quality and security. A number of articles in this issue were presented at a workshop held in April 2000 at the University of Bologna, Italy under the patronage of the Italian Society of Agricultural Genetics (SIGA) and sponsored by the Biotechnology and Biological Sciences Research Council (BBSRC) and the British Council (BC) in Italy and the CARISBO Foundation. The main objective of the workshop was to bring together a number of scientists in order to debate the state of the art in cereal genomics with a particular emphasis to Europe and the U.S., and to assess the technological gap existing at that time between Europe and the U.S. The grouping of the articles into five sections reflects their overall objectives. We are well aware that these articles represent only the tip of the iceberg since many other projects are underway in this fast expanding area, especially following the completion of the sequencing of the Arabidopsis genome and the recent release of part of the rice sequence. Although some genomics techniques are still in their infancy (e.g., SNP detection) or remain too expensive for routine applications (e.g., microarray analysis), the healthy status of plant genomics is witnessed by initiatives similar to this one (Chandler and Wessler, 2001) as well as by the growing number of meetings and new specialised journals devoted to genomics.

Considerable physiological and biochemical evidence suggests that plants, like animals, widely use intracellular signalling coupled to heterotrimeric G proteins. Yet, the molecular components of this machinery remained elusive until recently. We overview the work carried out during the last two decades, aimed at identification of the plant proteins involved in G protein-coupled signalling. The completion of the sequencing of the Arabidopsis genome now permits to assess whether plants possess signalling and regulatory components of this machinery corresponding to those known from animals.

Motivation: The completion of the Arabidopsis genome offers the first opportunity to analyze all of the membrane protein sequences of a plant. The majority of integral membrane proteins including transporters, channels, and pumps contain hydrophobic \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \({\alpha}\) \end{document}-helices and can be selected based on TransMembrane Spanning (TMS) domain prediction. By clustering the predicted membrane proteins based on sequence, it is possible to sort the membrane proteins into families of known function, based on experimental evidence or homology, or unknown function. This provides a way to identify target sequences for future functional analysis. Results: An automated approach was used to select potential membrane protein sequences from the set of all predicted proteins and cluster the sequences into related families. The recently completed sequence of Arabidopsis thaliana , a model plant, was analyzed. Of the 25470 predicted protein sequences 4589 (18%) were identified as containing two or more membrane spanning domains. The membrane protein sequences clustered into 628 distinct families containing 3208 sequences. Of these, 211 families (1764 sequences) either contained proteins of known function or showed homology to proteins of known function in other species. However, 417 families (1444 sequences) contained only sequences with no known function and no homology to proteins of known function. In addition, 1381 sequences did not cluster with any family and no function could be assigned to 1337 of these. Availability: Results from the analysis of all proteins of A.thaliana , source code for the programs, and links to primary data are available at the following WWW site: http://www.cbs.umn.edu/arabidopsis Contact: jward@tc.umn.edu