Gene index analysis of the human genome estimates approximately 120,000 genes

The cryptome: a subset of the proteome, comprising cryptic peptides with distinct bioactivities

There is increasing evidence that proteolytic cleavage gives rise to 'hidden' peptides with bioactivities that are often unpredicted and totally distinct to the parent protein. So far, the liberation of these cryptic peptides, or crypteins, has been shown to be prevalent in proteins associated with endocrine signalling, the extracellular matrix, the complement cascade and milk. A broad spectrum of proteases has been implicated in the generation of natural crypteins that appear to play a role in modulating diverse biological processes, such as angiogenesis, immune function and cell growth. The proteolytic liberation of crypteins with novel activities represents an important mechanism for increasing diversity of protein function and potentially offers new opportunities for protein-based therapeutics.

NMR and cDNA array analysis prior to heart failure reveals an increase of unsaturated lipids, a glutamine/glutamate ratio decrease and a specific transcriptome adaptation in obese rat heart

Obesity is a risk factor for heart failure through a set of hemodynamic and hormonal adaptations, but its contribution at the molecular level is not clearly known. Therefore, we investigated the kinetic cardiac transcriptome and metabolome in the Spontaneous Hypertensive Heart Failure (SHHF) rat. The SHHF rat is devoid of leptin signaling when homozygous for a mutation of the leptin receptor (ObR) gene. The ObR-/- SHHF rat is obese at 4 months of age and prone to heart failure after 14 months whereas its lean counterpart ObR-/+ is prone to heart failure after 16 months. We used a set of rat pangenomic high-density macroarrays to monitor left ventricle cardiac transcriptome regulation in 4- and 10-month-old, lean and obese animals. Comparative analysis of left ventricle of 4- and 10-month-old lean rat revealed 222 differentially expressed genes while 4- and 10-month-old obese rats showed 293 differentially expressed genes. (1)H NMR analysis of the metabolome of left ventricular extracts displayed a global decrease of metabolites, except for taurine, and lipid concentration. This may be attributed to gene expression regulation and likely increased extracellular mass. The glutamine to glutamate ratio was significantly lower in the obese group. The relative unsaturation of lipids increased in the obese heart; in particular, omega-3 lipid concentration was higher in the 10-month-old obese heart. Overall, several specific kinetic molecular patterns act as a prelude to heart failure in the leptin signaling deficient SHHF obese rat.

Analysis of expressed sequence tags from skeletal muscle-specific cDNA library of Chinese native Xiang pig

A Longissimus Dorsi muscle cDNA library of Xiang Pig was constructed, and 131 randomly isolated clones were sequenced in this study. The results of bioinformatics analysis showed that 131 ESTs represented 109 unique clones sequences, of which 99 showed homology to previously identified genes in humans or other mammals, 3 matched other uncharacterized expressed sequence tags (ESTs), and 7 showed no significant matches to sequences already present in DNA databases. No protein matches were found for 10 ESTs. Functional analysis of the ESTs showed that a considerable proportion of them encoded proteins involved in gene/protein expression (45.46%). Other classes included genes involved in metabolism (10.10%), cell structure/motility (10.10%), cell/organism defense (5.05%), cell signaling/communication (2.02%), and cell division (0.0%). Unclassified genes constituted the remaining 27.27%. This study reported the results of the first gene expression profile analysis of Chinese native Xiang Pig skeletal muscle cells, thereby greatly facilitating the functional study of candidate genes involved in muscle growth as well as in the improvement of meat quality in domestic pigs.

Alternative splicing in human transcriptome: Functional and structural influence on proteins

Alternative splicing is a molecular mechanism that produces multiple proteins from a single gene, and is thought to produce variety in proteins translated from a limited number of genes. Here we analyzed how alternative splicing produced variety in protein structure and function, by using human full-length cDNAs on the assumption that all of the alternatively spliced mRNAs were translated to proteins. We found that the length of alternatively spliced amino acid sequences, in most cases, fell into a size shorter than that of average protein domain. We evaluated comprehensively the presumptive three-dimensional structures of the alternatively spliced products to assess the impact of alternative splicing on gene function. We found that more than half of the products encoded proteins which were involved in signal transduction, transcription and translation, and more than half of alternatively spliced regions comprised interaction sites between proteins and their binding partners, including substrates, DNA/RNA, and other proteins. Intriguingly, 67% of the alternatively spliced isoforms showed significant alterations to regions of the protein structural core, which likely resulted in large conformational change. Based on those findings, we speculate that there are a large number of cases that alternative splicing modulates protein networks through significant alteration in protein conformation.

From 'omes to biology

Technologies that have emerged from the genome project have dramatically increased our ability to generate data on the way in which organisms respond to their environments, how they execute their programmes of development and growth, and how these are altered in the development of disease states. However, our ability to analyse these large datasets has not kept pace with our ability to generate them and consequently new strategies must be developed to address the issues associated with their analysis. One approach that we have employed quite successfully is to look at data from microarrays (or proteomics or metabolomics experiments) not as independent datasets, but rather as elements of a much larger body of biological information across various scales that must be integrated with, and interpreted within, the context of such ancillary data. Here we outline the general approach and provide three examples from published studies of the way in which we have applied this strategy.

Gene capture prediction and overlap estimation in EST sequencing from one or multiple libraries

BACKGROUND

In expressed sequence tag (EST) sequencing, we are often interested in how many genes we can capture in an EST sample of a targeted size. This information provides insights to sequencing efficiency in experimental design, as well as clues to the diversity of expressed genes in the tissue from which the library was constructed.

RESULTS

We propose a compound Poisson process model that can accurately predict the gene capture in a future EST sample based on an initial EST sample. It also allows estimation of the number of expressed genes in one cDNA library or co-expressed in two cDNA libraries. The superior performance of the new prediction method over an existing approach is established by a simulation study. Our analysis of four Arabidopsis thaliana EST sets suggests that the number of expressed genes present in four different cDNA libraries of Arabidopsis thaliana varies from 9155 (root) to 12005 (silique). An observed fraction of co-expressed genes in two different EST sets as low as 25% can correspond to an actual overlap fraction greater than 65%.

CONCLUSION

The proposed method provides a convenient tool for gene capture prediction and cDNA library property diagnosis in EST sequencing.

Alternative splicing and protein function

Background

Alternative splicing is a major mechanism of generating protein diversity in higher eukaryotes. Although at least half, and probably more, of mammalian genes are alternatively spliced, it was not clear, whether the frequency of alternative splicing is the same in different functional categories. The problem is obscured by uneven coverage of genes by ESTs and a large number of artifacts in the EST data.

Results

We have developed a method that generates possible mRNA isoforms for human genes contained in the EDAS database, taking into account the effects of nonsense-mediated decay and translation initiation rules, and a procedure for offsetting the effects of uneven EST coverage. Then we computed the number of mRNA isoforms for genes from different functional categories. Genes encoding ribosomal proteins and genes in the category "Small GTPase-mediated signal transduction" tend to have fewer isoforms than the average, whereas the genes in the category "DNA replication and chromosome cycle" have more isoforms than the average. Genes encoding proteins involved in protein-protein interactions tend to be alternatively spliced more often than genes encoding non-interacting proteins, although there is no significant difference in the number of isoforms of alternatively spliced genes.

Conclusion

Filtering for functional isoforms satisfying biological constraints and accountung for uneven EST coverage allowed us to describe differences in alternative splicing of genes from different functional categories. The observations seem to be consistent with expectations based on current biological knowledge: less isoforms for ribosomal and signal transduction proteins, and more alternative splicing of interacting and cell cycle proteins.

'The 39 steps' in gene expression profiling: critical issues and proposed best practices for microarray experiments

Gene expression microarrays have been used widely to address increasingly complex biological questions and to produce an unprecedented amount of data, but have yet to realize their full potential. The interpretation of microarray data remains a major challenge because of the complexity of the underlying biological networks. To gather meaningful expression data, it is crucial to develop standardized approaches for vigilant study design, controlled annotation of resources, careful quality control of experiments, robust statistics, and data registration and storage. This article reviews the steps needed in the design and execution of valid microarray experiments so that global gene expression data can play a major role in the pursuit of future biological discoveries that will impact drug development.

Seven novel and stable translocations associated with oncogenic gene expression in malignant melanoma

Cytogenetics has not only precipitated the discovery of several oncogenes, but has also led to the molecular classification of numerous malignancies. The correct identification of aberrations in many tumors has, however, been hindered by extensive tumor complexity and the limitations of molecular cytogenetic techniques. In this study, we have investigated five malignant melanoma (MM) cell lines from at least three different passages using high-resolution R-banding and the recently developed methods of comparative genomic hybridization and multicolor or multiplex fluorescence in situ hybridization. We subsequently detected nine consistent translocations, seven of which were novel: dic(1;11)(p10;q14), der(9)t(3;9)(p12;p11), der(4)t(9;4;7)(q33:p15-q23:q21), der(14)t(5;14)(q12;q32), der(9)t(9;22)(p21;q11), der(19)t(19;20)(p13.3;p11), der(10)t(2;12;7;10)(q31:p12-->pter:q11.2-->q31:q21), der(19)t(10;19)(q23;q13), and der(20)t(Y;20)(q11.23;q13.3). Furthermore, using the human HG-U133A GeneChip, positive expression levels of oncogenes or tumor-related genes located at the regions of chromosomal breakpoints were identified, including AKT1, BMI1, CDK6, CTNNB1, E2F1, GPNMB, GPRK7, KBRAS2, LDB2, LIMK1, MAPK1, MEL, MP1, MUC18, NRCAM, PBX3, RAB22A, RAB38, SNK, and STK4, indicating an association between chromosomal breakpoints and altered gene expression. Moreover, we also show that growth of all five cell lines can be significantly reduced by downregulating CDK6 gene expression with small interfering RNA (siRNA). Because the majority of these breakpoints have been reported previously in MM, our results support the idea of common mechanisms in this disease.

AU-rich transient response transcripts in the human genome: expressed sequence tag clustering and gene discovery approach

Transient response genes regulate critical biological responses that include cell proliferation, signal transduction events, and responses to exogenous agents such as inflammatory stimuli, microbes, and radiation. An important feature that ensures a timely response is the short half-life of the messenger RNA (mRNA), which is thought to be predominantly mediated by adenylate uridylate-rich sequence elements (AREs) in the 3' untranslated region (3' UTR). The repertoire and extent of transient response genes in the human genome are not known. We used a computational approach to delineate those genes that code for transient ARE mRNAs. We utilized a 3' UTR-specific ARE motif to retrieve and cluster 3'-end ESTs using a refined extraction protocol. With the availability of the entire human genome, we were able to utilize ARE EST clusters for further mining and computational prediction of ARE genes. The described approaches led to the finding of more than 1500 ARE genes in the human genome. In particular, "hidden" ARE mRNAs and alternative forms due to 3'UTR completeness, variant polyadenylation, and splicing were uncovered.

Evaluation of EST-data using the genome assembly

Using expressed sequence tag (EST) data for genomewide studies requires thorough understanding of the nature of the problems that are related to handling these sequences. We investigated how EST clustering performs when the genome is used as guidance as compared to pairwise sequence alignment methods. We show that clustering with the genome as a template outperforms sequence similarity methods used to create other EST clusters, such as the UniGene set, in respect to the extent ESTs originating from the same transcriptional unit are separated into disjunct clusters. Using our approach, approximately 80% of the RefSeq genes were represented by a single EST cluster and 20% comprised of two or more EST clusters. In contrast, approximately 25% of all RefSeq genes were found to be represented by a single cluster for the UniGene clustering method. The approach minimizes the risk for overestimations due to the amount of disjunct clusters originating from the same transcript. We have also investigated the quality of EST-data by aligning ESTs to the genome. The results show how many ESTs are not adequately trimmed in respect of vector sequences and low quality regions. Moreover, we identified important problems related to ESTs aligned to the genome using BLAT, such as inferring splice junctions, and explained this aspect by simulations with synthetic data. EST-clusters created with the method are available upon request from the authors.

Comparison of the current RefSeq, Ensembl and EST databases for counting genes and gene discovery

Large amounts of refined sequence material in the form of predicted, curated and annotated genes and expressed sequences tags (ESTs) have recently been added to the NCBI databases. We matched the transcript-sequences of RefSeq, Ensembl and dbEST in an attempt to provide an updated overview of how many unique human genes can be found. The results indicate that there are about 25000 unique genes in the union of RefSeq and Ensembl with 12-18% and 8-13% of the genes in each set unique to the other set, respectively. About 20% of all genes had splice variants. There are a considerable number of ESTs (2200000) that do not match the identified genes and we used an in-house pipeline to identify 22 novel genes from Genscan predictions that have considerable EST coverage. The study provides an insight into the current status of human gene catalogues and shows that considerable refinement of methods and datasets is needed to come to a conclusive gene count.

The truth about mouse, human, worms and yeast

Genome comparisons are behind the powerful new annotation methods being developed to find all human genes, as well as genes from other genomes. Genomes are now frequently being studied in pairs to provide cross-comparison datasets. This 'Noah's Ark' approach often reveals unsuspected genes and may support the deletion of false-positive predictions. Joining mouse and human as the cross-comparison dataset for the first two mammals are: two Drosophila species, D. melanogaster and D. pseudoobscura; two sea squirts, Ciona intestinalis and Ciona savignyi; four yeast (Saccharomyces) species; two nematodes, Caenorhabditis elegans and Caenorhabditis briggsae; and two pufferfish (Takefugu rubripes and Tetraodon nigroviridis). Even genomes like yeast and C. elegans, which have been known for more than five years, are now being significantly improved. Methods developed for yeast or nematodes will now be applied to mouse and human, and soon to additional mammals such as rat and dog, to identify all the mammalian protein-coding genes. Current large disparities between human Unigene predictions (127,835 genes) and gene-scanning methods (45,000 genes) still need to be resolved. This will be the challenge during the next few years.

Animal phylogenomics: multiple interspecific genome comparisons

The utility of DNA sequence information for phylogenetics and phylogeography is now well known. Rather than attempt to summarize studies addressing this well-demonstrated utility, this chapter focuses on fundamental approaches and techniques that implement the collection of DNA sequence data for comparative phylogenetic purposes in a genomic context (phylogenomics). Whole genome sequencing approaches have changed the way we think about phylogenetics and have opened the way for new perspectives on "old" phylogenetics concerns. Some of these concerns are which gene regions to use and how much sequence information is needed for robust phylogenetic inference. Whole genome sequences of a few animal model organisms have gone a long way to implement approaches to better understand these important phylogenetic concerns. This chapter also addresses how genomics has made it more important for a clear understanding of orthology of gene regions in comparative biology. Finally, genome-enabled technologies that are affecting comparative biology are also discussed.

Regulation of alternative RNA splicing by exon definition and exon sequences in viral and mammalian gene expression

Intron removal from a pre-mRNA by RNA splicing was once thought to be controlled mainly by intron splicing signals. However, viral and other eukaryotic RNA exon sequences have recently been found to regulate RNA splicing, polyadenylation, export, and nonsense-mediated RNA decay in addition to their coding function. Regulation of alternative RNA splicing by exon sequences is largely attributable to the presence of two major cis-acting elements in the regulated exons, the exonic splicing enhancer (ESE) and the suppressor or silencer (ESS). Two types of ESEs have been verified from more than 50 genes or exons: purine-rich ESEs, which are the more common, and non-purine-rich ESEs. In contrast, the sequences of ESSs identified in approximately 20 genes or exons are highly diverse and show little similarity to each other. Through interactions with cellular splicing factors, an ESE or ESS determines whether or not a regulated splice site, usually an upstream 3' splice site, will be used for RNA splicing. However, how these elements function precisely in selecting a regulated splice site is only partially understood. The balance between positive and negative regulation of splice site selection likely depends on the cis-element's identity and changes in cellular splicing factors under physiological or pathological conditions.

Libraries enriched for alternatively spliced exons reveal splicing patterns in melanocytes and melanomas

It is becoming increasingly clear that alternative splicing enables the complex development and homeostasis of higher organisms. To gain a better understanding of how splicing contributes to regulatory pathways, we have developed an alternative splicing library approach for the identification of alternatively spliced exons and their flanking regions by alternative splicing sequence enriched tags sequencing. Here, we have applied our approach to mouse melan-c melanocyte and B16-F10Y melanoma cell lines, in which 5,401 genes were found to be alternatively spliced. These genes include those encoding important regulatory factors such as cyclin D2, Ilk, MAPK12, MAPK14, RAB4, melastatin 1 and previously unidentified splicing events for 436 genes. Real-time PCR further identified cell line-specific exons for Tmc6, Abi1, Sorbs1, Ndel1 and Snx16. Thus, the ASL approach proved effective in identifying splicing events, which suggest that alternative splicing is important in melanoma development.

A comprehensive transcript index of the human genome generated using microarrays and computational approaches

BACKGROUND

Computational and microarray-based experimental approaches were used to generate a comprehensive transcript index for the human genome. Oligonucleotide probes designed from approximately 50,000 known and predicted transcript sequences from the human genome were used to survey transcription from a diverse set of 60 tissues and cell lines using ink-jet microarrays. Further, expression activity over at least six conditions was more generally assessed using genomic tiling arrays consisting of probes tiled through a repeat-masked version of the genomic sequence making up chromosomes 20 and 22.

RESULTS

The combination of microarray data with extensive genome annotations resulted in a set of 28,456 experimentally supported transcripts. This set of high-confidence transcripts represents the first experimentally driven annotation of the human genome. In addition, the results from genomic tiling suggest that a large amount of transcription exists outside of annotated regions of the genome and serves as an example of how this activity could be measured on a genome-wide scale.

CONCLUSIONS

These data represent one of the most comprehensive assessments of transcriptional activity in the human genome and provide an atlas of human gene expression over a unique set of gene predictions. Before the annotation of the human genome is considered complete, however, the previously unannotated transcriptional activity throughout the genome must be fully characterized.

Mouse-centric comparative transcriptomics of protein coding and non-coding RNAs

The largest transcriptome reported so far comprises 60,770 mouse full-length cDNA clones, and is an effective reference data set for comparative transcriptomics. The number of mouse cDNAs identified greatly exceeds the number of genes predicted from the sequenced human and mouse genomes. This is largely because of extensive alternative splicing and the presence of many non-coding RNAs (ncRNAs), which are difficult to predict from genomic sequences. Notably, ncRNAs are a major component of the transcriptomes of higher organisms, and many sense-antisense pairs have been identified. The ncRNAs function in a range of regulatory mechanisms for gene expression and other biological processes. They might also have contributed to the increased functional diversification of genomes during evolution. In this review, we discuss aspects of the transcriptome of various organisms in relation to the mouse data, in order to shed light on the regulatory mechanisms and physiological significance of these abundant RNAs.

Methods in comparative genomics: genome correspondence, gene identification and regulatory motif discovery

In Kellis et al. (2003), we reported the genome sequences of S. paradoxus, S. mikatae, and S. bayanus and compared these three yeast species to their close relative, S. cerevisiae. Genomewide comparative analysis allowed the identification of functionally important sequences, both coding and noncoding. In this companion paper we describe the mathematical and algorithmic results underpinning the analysis of these genomes. (1) We present methods for the automatic determination of genome correspondence. The algorithms enabled the automatic identification of orthologs for more than 90% of genes and intergenic regions across the four species despite the large number of duplicated genes in the yeast genome. The remaining ambiguities in the gene correspondence revealed recent gene family expansions in regions of rapid genomic change. (2) We present methods for the identification of protein-coding genes based on their patterns of nucleotide conservation across related species. We observed the pressure to conserve the reading frame of functional proteins and developed a test for gene identification with high sensitivity and specificity. We used this test to revisit the genome of S. cerevisiae, reducing the overall gene count by 500 genes (10% of previously annotated genes) and refining the gene structure of hundreds of genes. (3) We present novel methods for the systematic de novo identification of regulatory motifs. The methods do not rely on previous knowledge of gene function and in that way differ from the current literature on computational motif discovery. Based on genomewide conservation patterns of known motifs, we developed three conservation criteria that we used to discover novel motifs. We used an enumeration approach to select strongly conserved motif cores, which we extended and collapsed into a small number of candidate regulatory motifs. These include most previously known regulatory motifs as well as several noteworthy novel motifs. The majority of discovered motifs are enriched in functionally related genes, allowing us to infer a candidate function for novel motifs. Our results demonstrate the power of comparative genomics to further our understanding of any species. Our methods are validated by the extensive experimental knowledge in yeast and will be invaluable in the study of complex genomes like that of the human.

Characterization and comparative analyses of transcriptomes from the normal and neoplastic human prostate

BACKGROUND

The prostate gland is a highly specialized organ with functional attributes that serve to enhance the fertility of mammalian species. Pathological processes affecting the prostate include benign prostate hypertrophy and prostate carcinoma; diseases that account for major morbidity and mortality in middle-aged and elderly men. To facilitate studies of biological processes uniquely represented in the prostate and assess molecular alterations associated with prostate carcinoma, we sought to establish the diversity of gene expression in the normal and neoplastic prostate through the compilation and analysis of a prostate transcriptome.

METHODS

We assembled and annotated ESTs derived from prostate cDNA libraries that were either produced in our laboratory or available from public sequence repositories such as CGAP, dbEST, and Unigene. Determinations of differential gene expression between the normal prostate, other normal tissues, and neoplastic prostate tissues was performed using statistical algorithms. Confirmation of differential expression was performed by quantitative PCR and Northern analysis.

RESULTS

A total of 99,448 high-quality ESTs were assembled and annotated to produce a prostate transcriptome comprised of 24,580 distinct TUs. Comparative analyses of gene expression levels identified 61 TUs with exclusive expression in the prostate and 45 TUs with high levels of expression in the prostate relative to at least 25 other normal tissues (P > 0.99). Comparative analyses of ESTs derived from neoplastic prostate tissues identified 75 genes with dysregulated expression in cancer (P > 0.99).

CONCLUSIONS

The human prostate expresses a diverse repertoire of genes that reflect a functionally complex organ. The identification of genes with prostate-restricted or enhanced expression may provide additional insights into the biochemical processes that interact to form the developmental, signaling, and metabolic pathways of the normal and neoplastic gland.

A transcript finishing initiative for closing gaps in the human transcriptome

We report the results of a transcript finishing initiative, undertaken for the purpose of identifying and characterizing novel human transcripts, in which RT-PCR was used to bridge gaps between paired EST clusters, mapped against the genomic sequence. Each pair of EST clusters selected for experimental validation was designated a transcript finishing unit (TFU). A total of 489 TFUs were selected for validation, and an overall efficiency of 43.1% was achieved. We generated a total of 59,975 bp of transcribed sequences organized into 432 exons, contributing to the definition of the structure of 211 human transcripts. The structure of several transcripts reported here was confirmed during the course of this project, through the generation of their corresponding full-length cDNA sequences. Nevertheless, for 21% of the validated TFUs, a full-length cDNA sequence is not yet available in public databases, and the structure of 69.2% of these TFUs was not correctly predicted by computer programs. The TF strategy provides a significant contribution to the definition of the complete catalog of human genes and transcripts, because it appears to be particularly useful for identification of low abundance transcripts expressed in a restricted set of tissues as well as for the delineation of gene boundaries and alternatively spliced isoforms.

Regulation of alternative RNA splicing by exon definition and exon sequences in viral and mammalian gene expression

Intron removal from a pre-mRNA by RNA splicing was once thought to be controlled mainly by intron splicing signals. However, viral and other eukaryotic RNA exon sequences have recently been found to regulate RNA splicing, polyadenylation, export, and nonsense-mediated RNA decay in addition to their coding function. Regulation of alternative RNA splicing by exon sequences is largely attributable to the presence of two major cis-acting elements in the regulated exons, the exonic splicing enhancer (ESE) and the suppressor or silencer (ESS). Two types of ESEs have been verified from more than 50 genes or exons: purine-rich ESEs, which are the more common, and non-purine-rich ESEs. In contrast, the sequences of ESSs identified in approximately 20 genes or exons are highly diverse and show little similarity to each other. Through interactions with cellular splicing factors, an ESE or ESS determines whether or not a regulated splice site, usually an upstream 3' splice site, will be used for RNA splicing. However, how these elements function precisely in selecting a regulated splice site is only partially understood. The balance between positive and negative regulation of splice site selection likely depends on the cis-element's identity and changes in cellular splicing factors under physiological or pathological conditions.

PCR isolation and cloning of novel splice variant mRNAs from known drug target genes

Alternative splicing of pre-mRNAs is an important mechanism for the generation of vertebrate protein diversity. Unfortunately, the contribution of alternative splicing to protein diversity is currently not well understood because many full-length mRNA sequences have yet to be identified. In this report, we describe the use of RT-PCR to identify and clone 279 novel alternatively spliced mRNAs from 114 well-known drug target genes. Our findings demonstrate the existence of many novel alternatively spliced mRNA transcripts and suggest that many more genes undergo functionally significant alternative splicing than previously thought.

Gene expression profile of human chondrocyte HCS-2/8 cell line by EST sequencing analysis

Large-scale single-pass sequencing of randomly selected cDNA clones from cell type specific libraries has proven to be a powerful approach for the discovery of novel gene functions, identification of novel gene family members, and definition of gene expression profiles. HCS-2/8 chondrocyte has been used as a cell culture model to study chondrocyte differentiation. Here we performed 3350 single-pass sequencing reactions obtained from the 5' ends of cDNAs from HCS-2/8 cells. To define the expression profiles of HCS-2/8 chondrocytes, we analyzed the identity of these representative cDNA sequences using database searches (BLAST). The sequences represent 1927 unique genes with known function (i.e., unigene clusters), 38 transcripts that are similar to genes with known function, 739 expressed genes with unknown function (i.e., expressed sequence tags), and 18 cDNAs which have not previously been sequenced. Interestingly, many transcripts were expressed from chromosome 12 compared with total genes, while the fewer numbers of cDNAs were derived from genes on chromosomes 14, 18 and Y. The chondrocytic phenotype of HCS-2/8 cells is reflected by abundant expression of genes related to cell structure and motility and the 20 most frequently expressed unigenes reflect a chondrocyte-related gene expression signature. Thus, our data establish a representative set of more than 2000 genes expressed in a chondrocytic cell line. This finding provides a framework for understanding cell growth and differentiation of chondrocytes and their metabolic function in the formation and remodeling of cartilage.

The mammalian transcriptome and the function of non-coding DNA sequences

Many non-coding sequences transcribed from the mammalian genome are proving to have important regulatory roles, but the functions of the majority remain mysterious.

For decades, researchers have focused most of their attention on protein-coding genes and proteins. With the completion of the human and mouse genomes and the accumulation of data on the mammalian transcriptome, the focus now shifts to non-coding DNA sequences, RNA-coding genes and their transcripts. Many non-coding transcribed sequences are proving to have important regulatory roles, but the functions of the majority remain mysterious.

Novel RNAs identified from an in-depth analysis of the transcriptome of human chromosomes 21 and 22

In this report, we have achieved a richer view of the transcriptome for Chromosomes 21 and 22 by using high-density oligonucleotide arrays on cytosolic poly(A)(+) RNA. Conservatively, only 31.4% of the observed transcribed nucleotides correspond to well-annotated genes, whereas an additional 4.8% and 14.7% correspond to mRNAs and ESTs, respectively. Approximately 85% of the known exons were detected, and up to 21% of known genes have only a single isoform based on exon-skipping alternative expression. Overall, the expression of the well-characterized exons falls predominately into two categories, uniquely or ubiquitously expressed with an identifiable proportion of antisense transcripts. The remaining observed transcription (49.0%) was outside of any known annotation. These novel transcripts appear to be more cell-line-specific and have lower and less variation in expression than the well-characterized genes. Novel transcripts were further characterized based on their distance to annotations, transcript size, coding capacity, and identification as antisense to intronic sequences. By RT-PCR, 126 novel transcripts were independently verified, resulting in a 65% verification rate. These observations strongly support the argument for a re-evaluation of the total number of human genes and an alternative term for "gene" to encompass these growing, novel classes of RNA transcripts in the human genome.

The multiassembly problem: reconstructing multiple transcript isoforms from EST fragment mixtures

Recent evidence of abundant transcript variation (e.g., alternative splicing, alternative initiation, alternative polyadenylation) in complex genomes indicates that cataloging the complete set of transcripts from an organism is an important project. One challenge is the fact that most high-throughput experimental methods for characterizing transcripts (such as EST sequencing) give highly detailed information about short fragments of transcripts or protein products, instead of a complete characterization of a full-length form. We analyze this "multiassembly problem"-reconstructing the most likely set of full-length isoform sequences from a mixture of EST fragment data-and present a graph-based algorithm for solving it. In a variety of tests, we demonstrate that this algorithm deals appropriately with coupling of distinct alternative splicing events, increasing fragmentation of the input data and different types of transcript variation (such as alternative splicing, initiation, polyadenylation, and intron retention). To test the method's performance on pure fragment (EST) data, we removed all mRNA sequences, and found it produced no errors in 40 cases tested. Using this algorithm, we have constructed an Alternatively Spliced Proteins database (ASP) from analysis of human expressed and genomic sequences, consisting of 13,384 protein isoforms of 4422 genes, yielding an average of 3.0 protein isoforms per gene.

Census of genes expressed in porcine embryos and reproductive tissues by mining an expressed sequence tag database based on human genes

A total of 98,898 expressed sequence tags (ESTs) derived from embryos and reproductive tissues in pigs were identified in the GenBank "est_others" database. Pig embryos were collected at 11, 12, 13, 14, 15, 20, 30, and 45 days after gestation. The reproductive tissues were sampled from testis, ovary, endometrium, hypothalamus, anterior pituitary, uterus, and placenta. A gene-oriented approach was developed to annotate these porcine EST sequences to census the genes expressed from these sources. Of the 33 308 mRNA sequences from the human genes used as references (data accessed on 1 November 2002), 9410 had the porcine EST homologs expressed in embryos and 11 795 had the EST homologs expressed in reproductive tissues. The entire genome contributes at least 28.3% of its genes to embryo development and 35.4% of its genes to reproduction. Using the EST entry numbers as indicators of gene expression, we determined that the gene expression patterns differ significantly between embryos and reproductive tissues in pigs. The basic active genes were identified for each source, but most of them are not coexpressed abundantly. Few genes were expressed on the Y chromosome (P < 0.01), but they may represent counterparts of the double-dose genes that remain active in an inactivated X chromosome in females but are needed for proper development and growth. The census provides a panel of transcripts in a broad sense that can be used as targets to study the mechanisms involved in embryo development and reproduction in pigs and other mammals, including humans.

GENEANNOTATION: PREDICTION ANDTESTING

Fifty years after the publication of DNA structure, the whole human genome sequence will be officially finished. This achievement marks the beginning of the task to catalogue every human gene and identify each of their function expression patterns. Currently, researchers estimate that there are about 30,000 human genes and approximately 70% of these can be automatically predicted using a combination of ab initio and similarity-based programs. However, to experimentally investigate every gene's function, the research community requires a high-quality annotation of alternative splicing, pseudogenes, and promoter regions that can only be provided by manual intervention. Manual curation of the human genome will be a long-term project as experimental data are continually produced to confirm or refine the predictions, and new features such as noncoding RNAs and enhancers have not been fully identified. Such a highly curated human gene-set made publicly available will be a great asset for the experimental community and for future comparative genome projects.

Investigating single nucleotide polymorphism (SNP) density in the human genome and its implications for molecular evolution

We investigated the single nucleotide polymorphism (SNP) density across the human genome and in different genic categories using two SNP databases: Celera's CgsSNP, which includes SNPs identified by comparing genomic sequences, and Celera's RefSNP, which includes SNPs from a variety of sources and is biased toward disease-associated genes. Based on CgsSNP, the average numbers of SNPs per 10 kb was 8.33, 8.44, and 8.09 in the human genome, in intergenic regions, and in genic regions, respectively. In genic regions, the SNP density in intronic, exonic and adjoining untranslated regions was 8.21, 5.28, and 7.51 SNPs per 10 kb, respectively. The pattern of SNP density based on RefSNP was different from that based on CgsSNP, emphasizing its utility for genotype-phenotype association studies but not for most population genetic studies. The number of SNPs per chromosome was correlated with chromosome length, but the density of SNPs estimated by CgsSNP was not significantly correlated with the GC content of the chromosome. Based on CgsSNP, the ratio of nonsense to missense mutations (0.027), the ratio of missense to silent mutations (1.15), and the ratio of non-synonymous to synonymous mutations (1.18) was less than half of that expected in a human protein coding sequence under the neutral mutation theory, reflecting a role for natural selection, especially purifying selection.

Apparent homology of expressed genes from wood-forming tissues of loblolly pine (Pinus taeda L.) with Arabidopsis thaliana

Pinus taeda L. (loblolly pine) and Arabidopsis thaliana differ greatly in form, ecological niche, evolutionary history, and genome size. Arabidopsis is a small, herbaceous, annual dicotyledon, whereas pines are large, long-lived, coniferous forest trees. Such diverse plants might be expected to differ in a large number of functional genes. We have obtained and analyzed 59,797 expressed sequence tags (ESTs) from wood-forming tissues of loblolly pine and compared them to the gene sequences inferred from the complete sequence of the Arabidopsis genome. Approximately 50% of pine ESTs have no apparent homologs in Arabidopsis or any other angiosperm in public databases. When evaluated by using contigs containing long, high-quality sequences, we find a higher level of apparent homology between the inferred genes of these two species. For those contigs 1,100 bp or longer, approximately 90% have an apparent Arabidopsis homolog (E value < 10-10). Pines and Arabidopsis last shared a common ancestor approximately 300 million years ago. Few genes would be expected to retain high sequence similarity for this time if they did not have essential functions. These observations suggest substantial conservation of gene sequence in seed plants.

Antisense transcripts with FANTOM2 clone set and their implications for gene regulation

We have used the FANTOM2 mouse cDNA set (60,770 clones), public mRNA data, and mouse genome sequence data to identify 2481 pairs of sense-antisense transcripts and 899 further pairs of nonantisense bidirectional transcription based upon genomic mapping. The analysis greatly expands the number of known examples of sense-antisense transcript and nonantisense bidirectional transcription pairs in mammals. The FANTOM2 cDNA set appears to contain substantially large numbers of noncoding transcripts suitable for antisense transcript analysis. The average proportion of loci encoding sense-antisense transcript and nonantisense bidirectional transcription pairs on autosomes was 15.1 and 5.4%, respectively. Those on the X chromosome were 6.3 and 4.2%, respectively. Sense-antisense transcript pairs, rather than nonantisense bidirectional transcription pairs, may be less prevalent on the X chromosome, possibly due to X chromosome inactivation. Sense and antisense transcripts tended to be isolated from the same libraries, where nonantisense bidirectional transcription pairs were not apparently coregulated. The existence of large numbers of natural antisense transcripts implies that the regulation of gene expression by antisense transcripts is more common that previously recognized. The viewer showing mapping patterns of sense-antisense transcript pairs and nonantisense bidirectional transcription pairs on the genome and other related statistical data is available on our Web site.

Human-mouse gene identification by comparative evidence integration and evolutionary analysis

The identification of genes in the human genome remains a challenge, as the actual predictions appear to disagree tremendously and vary dramatically on the basis of the specific gene-finding methodology used. Because the pattern of conservation in coding regions is expected to be different from intronic or intergenic regions, a comparative computational analysis can lead, in principle, to an improved computational identification of genes in the human genome by using a reference, such as mouse genome. However, this comparative methodology critically depends on three important factors: (1) the selection of the most appropriate reference genome. In particular, it is not clear whether the mouse is at the correct evolutionary distance from the human to provide sufficiently distinctive conservation levels in different genomic regions, (2) the selection of comparative features that provide the most benefit to gene recognition, and (3) the selection of evidence integration architecture that effectively interprets the comparative features. We address the first question by a novel evolutionary analysis that allows us to explicitly correlate the performance of the gene recognition system with the evolutionary distance (time) between the two genomes. Our simulation results indicate that there is a wide range of reference genomes at different evolutionary time points that appear to deliver reasonable comparative prediction of human genes. In particular, the evolutionary time between human and mouse generally falls in the region of good performance; however, better accuracy might be achieved with a reference genome further than mouse. To address the second question, we propose several natural comparative measures of conservation for identifying exons and exon boundaries. Finally, we experiment with Bayesian networks for the integration of comparative and compositional evidence.

From biological databases to platforms for biomedical discovery

The use of high-throughput DNA sequencing and proteomic methods has led to an unprecedented increase in the amount of genomic and proteomic data. Application of computing technologies and development of computational tools to analyze and present these data has not kept pace with the accumulation of information. Here, we discuss the use of different database systems to store biological information and mention some of the key emerging computing technologies that are likely to have a key role in the future of bioinformatics.

Proteomics based on high-efficiency capillary separations

Identifying and quantifying in a high throughput manner the proteins expressed by cells, tissues or an organism provides the basis for understanding the functions of its constituents at a "systems" level. As a result, proteome analysis has increasingly become the focus of significant interest and research over the past decade. This is especially true following the recent stunning achievements in genomics analyses. However, unlike the static genome, the complexities and dynamism of the proteome present significant analytical challenges and demand highly efficient separations and detection technologies. A number of recent technological advancements have been in direct response to these challenges. Currently, strategically mated combinations of sophisticated separations techniques and advanced mass spectrometric detection represent the best approach to addressing the intricacies of the proteome. Liquid-phase separations, often within capillaries, are increasingly recognized as the best separations technique for this approach. In combination on-line with mass spectrometry, liquid-phase separations provide the improved analytical sensitivity, sample throughput, and quantitation capabilities necessitated by the multifaceted problems within proteomics analyses. This review focuses primarily on current high-efficiency capillary separations techniques, including both capillary liquid chromatography and capillary electrophoresis, applied to the analysis of complex proteomic samples. We emphasize developments at our laboratory and illustrate technical advances that attempt to review the role of separations within the broader context of a state-of-the-art integrated proteomics effort.

The transcriptional activity of human Chromosome 22

A DNA microarray representing nearly all of the unique sequences of human Chromosome 22 was constructed and used to measure global-transcriptional activity in placental poly(A)(+) RNA. We found that many of the known, related and predicted genes are expressed. More importantly, our study reveals twice as many transcribed bases as have been reported previously. Many of the newly discovered expressed fragments were verified by RNA blot analysis and a novel technique called differential hybridization mapping (DHM). Interestingly, a significant fraction of these novel fragments are expressed antisense to previously annotated introns. The coding potential of these novel expressed regions is supported by their sequence conservation in the mouse genome. This study has greatly increased our understanding of the biological information encoded on a human chromosome. To facilitate the dissemination of these results to the scientific community, we have developed a comprehensive Web resource to present the findings of this study and other features of human Chromosome 22 at http://array.mbb.yale.edu/chr22.

A complexity reduction algorithm for analysis and annotation of large genomic sequences

DNA is a universal language encrypted with biological instruction for life. In higher organisms, the genetic information is preserved predominantly in an organized exon/intron structure. When a gene is expressed, the exons are spliced together to form the transcript for protein synthesis. We have developed a complexity reduction algorithm for sequence analysis (CRASA) that enables direct alignment of cDNA sequences to the genome. This method features a progressive data structure in hierarchical orders to facilitate a fast and efficient search mechanism. CRASA implementation was tested with already annotated genomic sequences in two benchmark data sets and compared with 15 annotation programs (10 ab initio and 5 homology-based approaches) against the EST database. By the use of layered noise filters, the complexity of CRASA-matched data was reduced exponentially. The results from the benchmark tests showed that CRASA annotation excelled in both the sensitivity and specificity categories. When CRASA was applied to the analysis of human Chromosomes 21 and 22, an additional 83 potential genes were identified. With its large-scale processing capability, CRASA can be used as a robust tool for genome annotation with high accuracy by matching the EST sequences precisely to the genomic sequences.

A novel algorithm for computational identification of contaminated EST libraries

A key goal of the Human Genome Project was to understand the complete set of human proteins, the proteome. Since the genome sequence by itself is not sufficient for predicting new genes and alternative splicing events that lead to new proteins, expressed sequence tags (ESTs) are used as the primary tool for these purposes. The high prevalence of artifacts in dbEST, however, often leads to invalid predictions. Here we describe a novel method for recognizing genomic DNA contamination and other artifacts that cannot be identified using current EST cleaning techniques. Our method uses the alignment of the entire set of ESTs to the human genome to identify highly contaminated EST libraries. We discovered 53 highly contaminated libraries and a subset of 24 766 ESTs from these libraries that probably represent contamination with genomic DNA, pre-mRNA, and ESTs that span non-canonical introns. Although this is only a small fraction of the entire EST dataset, each contaminating sequence could create a spurious transcript prediction. Indeed, in the clustering and assembly tool that we used, these sequences would have caused incorrect inference of 9575 new splice variants and 6370 new genes. Conclusions based on EST analysis, including prediction of alternative splicing, should be re-evaluated in light of these results. Our method, along with the identified set of contaminated sequences, will be essential for applications that depend on large EST datasets.

A semiautomated approach to gene discovery through expressed sequence tag data mining: discovery of new human transporter genes

Identification and functional characterization of the genes in the human genome remain a major challenge. A principal source of publicly available information used for this purpose is the National Center for Biotechnology Information database of expressed sequence tags (dbEST), which contains over 4 million human ESTs. To extract the information buried in this data more effectively, we have developed a semiautomated method to mine dbEST for uncharacterized human genes. Starting with a single protein input sequence, a family of related proteins from all species is compiled. This entire family is then used to mine the human EST database for new gene candidates. Evaluation of putative new gene candidates in the context of a family of characterized proteins provides a framework for inference of the structure and function of the new genes. When applied to a test data set of 28 families within the major facilitator superfamily (MFS) of membrane transporters, our protocol found 73 previously characterized human MFS genes and 43 new MFS gene candidates. Development of this approach provided insights into the problems and pitfalls of automated data mining using public databases.

Reevaluating human gene annotation: a second-generation analysis of chromosome 22

We report a second-generation gene annotation of human chromosome 22. Using expressed sequence databases, comparative sequence analysis, and experimental verification, we have extended genes, fused previously fragmented structures, and identified new genes. The total length in exons of annotation was increased by 74% over our previously published annotation and includes 546 protein-coding genes and 234 pseudogenes. Thirty-two potential protein-coding annotations are partial copies of other genes, and may represent duplications on an evolutionary path to change or loss of function. We also identified 31 non-protein-coding transcripts, including 16 possible antisense RNAs. By extrapolation, we estimate the human genome contains 29,000-36,000 protein-coding genes, 21,300 pseudogenes, and 1500 antisense RNAs. We suggest that our revised annotation criteria provide a paradigm for future annotation of the human genome.

Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs

Only a small proportion of the mouse genome is transcribed into mature messenger RNA transcripts. There is an international collaborative effort to identify all full-length mRNA transcripts from the mouse, and to ensure that each is represented in a physical collection of clones. Here we report the manual annotation of 60,770 full-length mouse complementary DNA sequences. These are clustered into 33,409 'transcriptional units', contributing 90.1% of a newly established mouse transcriptome database. Of these transcriptional units, 4,258 are new protein-coding and 11,665 are new non-coding messages, indicating that non-coding RNA is a major component of the transcriptome. 41% of all transcriptional units showed evidence of alternative splicing. In protein-coding transcripts, 79% of splice variations altered the protein product. Whole-transcriptome analyses resulted in the identification of 2,431 sense-antisense pairs. The present work, completely supported by physical clones, provides the most comprehensive survey of a mammalian transcriptome so far, and is a valuable resource for functional genomics.

Gene expression studies using microarrays: principles, problems, and prospects

A number of mammalian genomes having been sequenced, an important next step is to catalog the expression patterns of all transcription units in health and disease by use of microarrays. Such discovery programs are crucial to our understanding of the gene networks that control developmental, physiological, and pathological processes. However, despite the excitement, the full promise of microarray technology has yet to be realized, as the superficial simplicity of the concept belies considerable problems. Microarray technology is very new; methodologies are still evolving, common standards have yet to be established, and many problems with experimental design and variability have still to be fully understood and overcome. This review will describe the time course of a microarray experiment-RNA isolation from sample, target preparation, hybridization to the microarray probe, data capture, and bioinformatic analysis. For each stage, the advantages and disadvantages of competing techniques are compared, and inherent sources of error are identified and discussed.

Comparison of whole genome assemblies of the human genome

A fundamental problem in the human genome project is uncovering the correct assembly of the human genome. Many studies, including transcriptional analysis, SNP detection and characterization, gene finding and EST clustering, use genome assemblies as templates so it is important to determine the consistency among the various whole genome assemblies. A comparison of the order and orientation of the GenBank entries used to construct the NCBI and UCSC Goldenpath assemblies was made. In addition, a sequence level comparison was performed using MULTI, an efficient database search tool developed to make whole genome comparisons possible. The resulting comparisons show significant discrepancies in the sequence as well as in the order and orientation of GenBank entries used in constructing the NCBI and UCSC assemblies.

Renal transcriptomes: segmental analysis of differential expression

BACKGROUND/AIMS

Progress accomplished by complete genomes and cDNA-sequencing projects calls for methods that fully use these resources to study gene expression patterns in characterized cell populations. However, since the number of functional genes cannot be readily inferred from the genomic sequence, it is highly desirable to make use of methods enabling to study both known and unknown genes.

METHODS

The method of serial analysis of gene expression provides short diagnostic cDNA tags without bias towards known genes. In addition, the frequency of each tag in the library conveys quantitative information on gene expression. A microassay was set-up to perform serial analysis of gene expression in minute samples such as those obtained by microdissecting nephron segments.

RESULTS

Studies carried out in the thick ascending limb of Henle's loop and the collecting duct of the mouse kidney provided expression data for several thousand genes. Known markers were found appropriately enriched, and several of the thick ascending limb or collecting duct specific transcripts had no database match.

CONCLUSIONS

The microassay for serial analysis of gene expression makes possible large-scale quantitative measurements of mRNA levels in nephron segments. The comprehensive picture generated by analyzing both known and unknown transcripts in defined cell populations should help to discover genes with dedicated functions.