Improve Gene Models Research Articles

Improved Reference Genome Annotation of Brassica rapa by Pacific Biosciences RNA Sequencing.

The species Brassica rapa includes several important vegetable crops. The draft reference genome of B. rapa ssp. pekinensis was completed in 2011, and it has since been updated twice. The pangenome with structural variations of 18 B. rapa accessions was published in 2021. Although extensive genomic analysis has been conducted on B. rapa, a comprehensive genome annotation including gene structure, alternative splicing (AS) events, and non-coding genes is still lacking. Therefore, we used the Pacific Biosciences (PacBio) single-molecular long-read technology to improve gene models and produced the annotated genome version 3.5. In total, we obtained 753,041 full-length non-chimeric (FLNC) reads and collapsed these into 92,810 non-redundant consensus isoforms, capturing 48% of the genes annotated in the B. rapa reference genome annotation v3.1. Based on the isoform data, we identified 830 novel protein-coding genes that were missed in previous genome annotations, defined the untranslated regions (UTRs) of 20,340 annotated genes and corrected 886 wrongly spliced genes. We also identified 28,564 AS events and 1,480 long non-coding RNAs (lncRNAs). We produced a relatively complete and high-quality reference transcriptome for B. rapa that can facilitate further functional genomic research.

Single-cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis.

Single-cell RNA sequencing is a powerful technique that continues to expand across various biological applications. However, incomplete 3′-UTR annotations can impede single-cell analysis resulting in genes that are partially or completely uncounted. Performing single-cell RNA sequencing with incomplete 3′-UTR annotations can hinder the identification of cell identities and gene expression patterns and lead to erroneous biological inferences. We demonstrate that performing single-cell isoform sequencing in tandem with single-cell RNA sequencing can rapidly improve 3′-UTR annotations. Using threespine stickleback fish (Gasterosteus aculeatus), we show that gene models resulting from a minimal embryonic single-cell isoform sequencing dataset retained 26.1% greater single-cell RNA sequencing reads than gene models from Ensembl alone. Furthermore, pooling our single-cell sequencing isoforms with a previously published adult bulk Iso-Seq dataset from stickleback, and merging the annotation with the Ensembl gene models, resulted in a marginal improvement (+0.8%) over the single-cell isoform sequencing only dataset. In addition, isoforms identified by single-cell isoform sequencing included thousands of new splicing variants. The improved gene models obtained using single-cell isoform sequencing led to successful identification of cell types and increased the reads identified of many genes in our single-cell RNA sequencing stickleback dataset. Our work illuminates single-cell isoform sequencing as a cost-effective and efficient mechanism to rapidly annotate genomes for single-cell RNA sequencing.

Allele mining in diverse accessions of tropical grasses to improve forage quality and reduce environmental impact.

The C4Urochloa species (syn. Brachiaria) and Megathyrsus maximus (syn. Panicum maximum) are used as pasture for cattle across vast areas in tropical agriculture systems in Africa and South America. A key target for variety improvement is forage quality: enhanced digestibility could decrease the amount of land required per unit production, and enhanced lipid content could decrease methane emissions from cattle. For these traits, loss-of-function (LOF) alleles in known gene targets are predicted to improve them, making a reverse genetics approach of allele mining feasible. We therefore set out to look for such alleles in diverse accessions of Urochloa species and Megathyrsus maximus from the genebank collection held at the CIAT. We studied allelic diversity of 20 target genes (11 for digestibility, nine for lipid content) in 104 accessions selected to represent genetic diversity and ploidy levels of U. brizantha, U. decumbens, U. humidicola, U. ruziziensis and M. maximum. We used RNA sequencing and then bait capture DNA sequencing to improve gene models in a U. ruziziensis reference genome to assign polymorphisms with high confidence. We found 953 non-synonymous polymorphisms across all genes and accessions; within these, we identified seven putative LOF alleles with high confidence, including those in the non-redundant SDP1 and BAHD01 genes present in diploid and tetraploid accessions. These LOF alleles could respectively confer increased lipid content and digestibility if incorporated into a breeding programme. We demonstrated a novel, effective approach to allele discovery in diverse accessions using a draft reference genome from a single species. We used this to find gene variants in a collection of tropical grasses that could help reduce the environmental impact of cattle production.

Long-read RNA sequencing of human and animal filarial parasites improves gene models and discovers operons.

Filarial parasitic nematodes (Filarioidea) cause substantial disease burden to humans and animals around the world. Recently there has been a coordinated global effort to generate, annotate, and curate genomic data from nematode species of medical and veterinary importance. This has resulted in two chromosome-level assemblies (Brugia malayi and Onchocerca volvulus) and 11 additional draft genomes from Filarioidea. These reference assemblies facilitate comparative genomics to explore basic helminth biology and prioritize new drug and vaccine targets. While the continual improvement of genome contiguity and completeness advances these goals, experimental functional annotation of genes is often hindered by poor gene models. Short-read RNA sequencing data and expressed sequence tags, in cooperation with ab initio prediction algorithms, are employed for gene prediction, but these can result in missing clade-specific genes, fragmented models, imperfect mapping of gene ends, and lack of isoform resolution. Long-read RNA sequencing can overcome these drawbacks and greatly improve gene model quality. Here, we present Iso-Seq data for B. malayi and Dirofilaria immitis, etiological agents of lymphatic filariasis and canine heartworm disease, respectively. These data cover approximately half of the known coding genomes and substantially improve gene models by extending untranslated regions, cataloging novel splice junctions from novel isoforms, and correcting mispredicted junctions. Furthermore, we validated computationally predicted operons, manually curated new operons, and merged fragmented gene models. We carried out analyses of poly(A) tails in both species, leading to the identification of non-canonical poly(A) signals. Finally, we prioritized and assessed known and putative anthelmintic targets, correcting or validating gene models for molecular cloning and target-based anthelmintic screening efforts. Overall, these data significantly improve the catalog of gene models for two important parasites, and they demonstrate how long-read RNA sequencing should be prioritized for ongoing improvement of parasitic nematode genome assemblies.

BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq

BackgroundThe time required to analyse RNA-seq data varies considerably, due to discrete steps for computational assembly, quantification of gene expression and splicing analysis. Recent fast non-alignment tools such as Kallisto and Salmon overcome these problems, but these tools require a high quality, comprehensive reference transcripts dataset (RTD), which are rarely available in plants.ResultsA high-quality, non-redundant barley gene RTD and database (Barley Reference Transcripts – BaRTv1.0) has been generated. BaRTv1.0, was constructed from a range of tissues, cultivars and abiotic treatments and transcripts assembled and aligned to the barley cv. Morex reference genome (Mascher et al. Nature; 544: 427–433, 2017). Full-length cDNAs from the barley variety Haruna nijo (Matsumoto et al. Plant Physiol; 156: 20–28, 2011) determined transcript coverage, and high-resolution RT-PCR validated alternatively spliced (AS) transcripts of 86 genes in five different organs and tissue. These methods were used as benchmarks to select an optimal barley RTD. BaRTv1.0-Quantification of Alternatively Spliced Isoforms (QUASI) was also made to overcome inaccurate quantification due to variation in 5′ and 3′ UTR ends of transcripts. BaRTv1.0-QUASI was used for accurate transcript quantification of RNA-seq data of five barley organs/tissues. This analysis identified 20,972 significant differentially expressed genes, 2791 differentially alternatively spliced genes and 2768 transcripts with differential transcript usage.ConclusionA high confidence barley reference transcript dataset consisting of 60,444 genes with 177,240 transcripts has been generated. Compared to current barley transcripts, BaRTv1.0 transcripts are generally longer, have less fragmentation and improved gene models that are well supported by splice junction reads. Precise transcript quantification using BaRTv1.0 allows routine analysis of gene expression and AS.

Improved annotation of the insect vector of citrus greening disease: biocuration by a diverse genomics community.

The Asian citrus psyllid (Diaphorina citri Kuwayama) is the insect vector of the bacterium Candidatus Liberibacter asiaticus (CLas), the pathogen associated with citrus Huanglongbing (HLB, citrus greening). HLB threatens citrus production worldwide. Suppression or reduction of the insect vector using chemical insecticides has been the primary method to inhibit the spread of citrus greening disease. Accurate structural and functional annotation of the Asian citrus psyllid genome, as well as a clear understanding of the interactions between the insect and CLas, are required for development of new molecular-based HLB control methods. A draft assembly of the D. citri genome has been generated and annotated with automated pipelines. However, knowledge transfer from well-curated reference genomes such as that of Drosophila melanogaster to newly sequenced ones is challenging due to the complexity and diversity of insect genomes. To identify and improve gene models as potential targets for pest control, we manually curated several gene families with a focus on genes that have key functional roles in D. citri biology and CLas interactions. This community effort produced 530 manually curated gene models across developmental, physiological, RNAi regulatory, and immunity-related pathways. As previously shown in the pea aphid, RNAi machinery genes putatively involved in the microRNA pathway have been specifically duplicated. A comprehensive transcriptome enabled us to identify a number of gene families that are either missing or misassembled in the draft genome. In order to develop biocuration as a training experience, we included undergraduate and graduate students from multiple institutions, as well as experienced annotators from the insect genomics research community. The resulting gene set (OGS v1.0) combines both automatically predicted and manually curated gene models. All data are available on https://citrusgreening.org/.

An improved assembly and annotation of the melon (Cucumis melo L.) reference genome

We report an improved assembly (v3.6.1) of the melon (Cucumis melo L.) genome and a new genome annotation (v4.0). The optical mapping approach allowed correcting the order and the orientation of 21 previous scaffolds and permitted to correctly define the gap-size extension along the 12 pseudomolecules. A new comprehensive annotation was also built in order to update the previous annotation v3.5.1, released more than six years ago. Using an integrative annotation pipeline, based on exhaustive RNA-Seq collections and ad-hoc transposable element annotation, we identified 29,980 protein-coding loci. Compared to the previous version, the v4.0 annotation improved gene models in terms of completeness of gene structure, UTR regions definition, intron-exon junctions and reduction of fragmented genes. More than 8,000 new genes were identified, one third of them being well supported by RNA-Seq data. To make all the new resources easily exploitable and completely available for the scientific community, a redesigned Melonomics genomic platform was released at http://melonomics.net. The resources produced in this work considerably increase the reliability of the melon genome assembly and resolution of the gene models paving the way for further studies in melon and related species.

OMGene: mutual improvement of gene models through optimisation of evolutionary conservation

BackgroundThe accurate determination of the genomic coordinates for a given gene – its gene model – is of vital importance to the utility of its annotation, and the accuracy of bioinformatic analyses derived from it. Currently-available methods of computational gene prediction, while on the whole successful, frequently disagree on the model for a given predicted gene, with some or all of the variant gene models often failing to match the biologically observed structure. Many prediction methods can be bolstered by using experimental data such as RNA-seq. However, these resources are not always available, and rarely give a comprehensive portrait of an organism’s transcriptome due to temporal and tissue-specific expression profiles.ResultsOrthology between genes provides evolutionary evidence to guide the construction of gene models. OMGene (Optimise My Gene) aims to improve gene model accuracy in the absence of experimental data by optimising the consistency of multiple sequence alignments of orthologous genes from multiple species. Using RNA-seq data sets from plants, mammals, and fungi, considering intron/exon junction representation and exon coverage, and assessing the intra-orthogroup consistency of subcellular localisation predictions, we demonstrate the utility of OMGene for improving gene models in annotated genomes.ConclusionsWe show that significant improvements in the accuracy of gene model annotations can be made, both in established and in de novo annotated genomes, by leveraging information from multiple species.

A modified GC-specific MAKER gene annotation method reveals improved and novel gene predictions of high and low GC content in Oryza sativa

BackgroundAccurate structural annotation depends on well-trained gene prediction programs. Training data for gene prediction programs are often chosen randomly from a subset of high-quality genes that ideally represent the variation found within a genome. One aspect of gene variation is GC content, which differs across species and is bimodal in grass genomes. When gene prediction programs are trained on a subset of grass genes with random GC content, they are effectively being trained on two classes of genes at once, and this can be expected to result in poor results when genes are predicted in new genome sequences.ResultsWe find that gene prediction programs trained on grass genes with random GC content do not completely predict all grass genes with extreme GC content. We show that gene prediction programs that are trained with grass genes with high or low GC content can make both better and unique gene predictions compared to gene prediction programs that are trained on genes with random GC content. By separately training gene prediction programs with genes from multiple GC ranges and using the programs within the MAKER genome annotation pipeline, we were able to improve the annotation of the Oryza sativa genome compared to using the standard MAKER annotation protocol. Gene structure was improved in over 13% of genes, and 651 novel genes were predicted by the GC-specific MAKER protocol.ConclusionsWe present a new GC-specific MAKER annotation protocol to predict new and improved gene models and assess the biological significance of this method in Oryza sativa. We expect that this protocol will also be beneficial for gene prediction in any organism with bimodal or other unusual gene GC content.

Serine protease-related proteins in the malaria mosquito, Anopheles gambiae

Insect serine proteases (SPs) and serine protease homologs (SPHs) participate in digestion, defense, development, and other physiological processes. In mosquitoes, some clip-domain SPs and SPHs (i.e. CLIPs) have been investigated for possible roles in antiparasitic responses. In a recent test aimed at improving quality of gene models in the Anopheles gambiae genome using RNA-seq data, we observed various discrepancies between gene models in AgamP4.5 and corresponding sequences selected from those modeled by Cufflinks, Trinity and Bridger. Here we report a comparative analysis of the 337 SP-related proteins in A. gambiae by examining their domain structures, sequence diversity, chromosomal locations, and expression patterns. One hundred and ten CLIPs contain 1 to 5 clip domains in addition to their protease domains (PDs) or non-catalytic, protease-like domains (PLDs). They are divided into five subgroups: CLIPAs (22) are clip1−5-PLD; CLIPBs (29), CLIPCs (12) and CLIPDs (14) are mainly clip-PD; most CLIPEs (33) have a domain structure of PD/PLD-PLD-clip-PLD0−1. While expression of the CLIP genes in group-1 is generally low and detected in various tissue- and stage-specific RNA-seq libraries, some putative GPs/GPHs (i.e. single domain gut SPs/SPHs) in group-2 are highly expressed in midgut, whole larva or whole adult libraries. In comparison, 46 SPs, 26 SPHs, and 37 multi-domain SPs/SPHs (i.e. PD/PLD-PLD≥1) in group-3 do not seem to be specifically expressed in digestive tract. There are 16 SPs and 2 SPH containing other types of putative regulatory domains (e.g. LDLa, CUB, Gd). Of the 337 SP and SPH genes, 159 were sorted into 46 groups (2–8 members/group) based on similar phylogenetic tree position, chromosomal location, and expression profile. This information and analysis, including improved gene models and protein sequences, constitute a solid foundation for functional analysis of the SP-related proteins in A. gambiae.

Improved annotation of the insect vector of citrus greening disease: biocuration by a diverse genomics community.

The Asian citrus psyllid (Diaphorina citri Kuwayama) is the insect vector of the bacterium Candidatus Liberibacter asiaticus (CLas), the pathogen associated with citrus Huanglongbing (HLB, citrus greening). HLB threatens citrus production worldwide. Suppression or reduction of the insect vector using chemical insecticides has been the primary method to inhibit the spread of citrus greening disease. Accurate structural and functional annotation of the Asian citrus psyllid genome, as well as a clear understanding of the interactions between the insect and CLas, are required for development of new molecular-based HLB control methods. A draft assembly of the D. citri genome has been generated and annotated with automated pipelines. However, knowledge transfer from well-curated reference genomes such as that of Drosophila melanogaster to newly sequenced ones is challenging due to the complexity and diversity of insect genomes. To identify and improve gene models as potential targets for pest control, we manually curated several gene families with a focus on genes that have key functional roles in D. citri biology and CLas interactions. This community effort produced 530 manually curated gene models across developmental, physiological, RNAi regulatory and immunity-related pathways. As previously shown in the pea aphid, RNAi machinery genes putatively involved in the microRNA pathway have been specifically duplicated. A comprehensive transcriptome enabled us to identify a number of gene families that are either missing or misassembled in the draft genome. In order to develop biocuration as a training experience, we included undergraduate and graduate students from multiple institutions, as well as experienced annotators from the insect genomics research community. The resulting gene set (OGS v1.0) combines both automatically predicted and manually curated gene models.

Multifaceted biological insights from a draft genome sequence of the tobacco hornworm moth, Manduca sexta

Manduca sexta, known as the tobacco hornworm or Carolina sphinx moth, is a lepidopteran insect that is used extensively as a model system for research in insect biochemistry, physiology, neurobiology, development, and immunity. One important benefit of this species as an experimental model is its extremely large size, reaching more than 10 g in the larval stage. M. sexta larvae feed on solanaceous plants and thus must tolerate a substantial challenge from plant allelochemicals, including nicotine. We report the sequence and annotation of the M. sexta genome, and a survey of gene expression in various tissues and developmental stages. The Msex_1.0 genome assembly resulted in a total genome size of 419.4 Mbp. Repetitive sequences accounted for 25.8% of the assembled genome. The official gene set is comprised of 15,451 protein-coding genes, of which 2498 were manually curated. Extensive RNA-seq data from many tissues and developmental stages were used to improve gene models and for insights into gene expression patterns. Genome wide synteny analysis indicated a high level of macrosynteny in the Lepidoptera. Annotation and analyses were carried out for gene families involved in a wide spectrum of biological processes, including apoptosis, vacuole sorting, growth and development, structures of exoskeleton, egg shells, and muscle, vision, chemosensation, ion channels, signal transduction, neuropeptide signaling, neurotransmitter synthesis and transport, nicotine tolerance, lipid metabolism, and immunity. This genome sequence, annotation, and analysis provide an important new resource from a well-studied model insect species and will facilitate further biochemical and mechanistic experimental studies of many biological systems in insects.

A gapless genome sequence of the fungus Botrytis cinerea

Following earlier incomplete and fragmented versions of a genome sequence for the grey mould Botrytis cinerea, a gapless, near-finished genome sequence for B. cinerea strain B05.10 is reported. The assembly comprised 18 chromosomes and was confirmed by an optical map and a genetic map based on approximately 75 000 single nucleotide polymorphism (SNP) markers. All chromosomes contained fully assembled centromeric regions, and 10 chromosomes had telomeres on both ends. The genetic map consisted of 4153 cM and a comparison of the genetic distances with the physical distances identified 40 recombination hotspots. The linkage map also identified two mutations, located in the previously described genes Bos1 and BcsdhB, that conferred resistance to the fungicides boscalid and iprodione. The genome was predicted to encode 11 701 proteins. RNAseq data from >20 different samples were used to validate and improve gene models. Manual curation of chromosome 1 revealed interesting features, such as the occurrence of a dicistronic transcript and fully overlapping genes in opposite orientations, as well as many spliced antisense transcripts. Manual curation also revealed that the untranslated regions (UTRs) of genes can be complex and long, with many UTRs exceeding lengths of 1 kb and possessing multiple introns. Community annotation is in progress.

Integration of RNA-seq and proteomics data with genomics for improved genome annotation in Apicomplexan parasites.

While high quality genomic sequence data is available for many pathogenic organisms, the corresponding gene annotations are often plagued with inaccuracies that can hinder research that utilizes such genomic data. Experimental validation of gene models is clearly crucial in improving such gene annotations; the field of proteogenomics is an emerging area of research wherein proteomic data is applied to testing and improving genetic models. Krishna et al. [Proteomics 2015, 15, 2618-2628] investigated whether incorporation of RNA-seq data into proteogenomics analyses can contribute significantly to validation studies of genome annotation, in two important parasitic organisms Toxoplasma gondii and Neospora caninum. They applied a systematic approach to combine new and previously published proteomics data from T. gondii and N. caninum with transcriptomics data, leading to substantially improved gene models for these organisms. This study illustrates the importance of incorporating experimental data from both proteomics and RNA-seq studies into routine genome annotation protocols.

New gene models and alternative splicing in the maize pathogen Colletotrichum graminicola revealed by RNA-Seq analysis.

BackgroundAn annotated genomic sequence of the corn anthracnose fungus Colletotrichum graminicola has been published previously, but correct identification of gene models by means of automated gene annotation remains a challenge. RNA-Seq offers the potential for substantially improved gene annotations and for the identification of posttranscriptional RNA modifications, such as alternative splicing and RNA editing.ResultsBased on the nucleotide sequence information of transcripts, we identified 819 novel transcriptionally active regions (nTARs) and revised 906 incorrectly predicted gene models, including revisions of exon-intron structure, gene orientation and sequencing errors. Among the nTARs, 146 share significant similarity with proteins that have been identified in other species suggesting that they are hitherto unidentified genes in C. graminicola. Moreover, 5′- and 3′-UTR sequences of 4378 genes have been retrieved and alternatively spliced variants of 69 genes have been identified. Comparative analysis of RNA-Seq data and the genome sequence did not provide evidence for RNA editing in C. graminicola.ConclusionsWe successfully employed deep sequencing RNA-Seq data in combination with an elaborate bioinformatics strategy in order to identify novel genes, incorrect gene models and mechanisms of transcript processing in the corn anthracnose fungus C. graminicola. Sequence data of the revised genome annotation including several hundreds of novel transcripts, improved gene models and candidate genes for alternative splicing have been made accessible in a comprehensive database. Our results significantly contribute to both routine laboratory experiments and large-scale genomics or transcriptomic studies in C. graminicola.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-842) contains supplementary material, which is available to authorized users.

A proteogenomic update to Yersinia: enhancing genome annotation

BackgroundModern biomedical research depends on a complete and accurate proteome. With the widespread adoption of new sequencing technologies, genome sequences are generated at a near exponential rate, diminishing the time and effort that can be invested in genome annotation. The resulting gene set contains numerous errors in even the most basic form of annotation: the primary structure of the proteins.ResultsThe application of experimental proteomics data to genome annotation, called proteogenomics, can quickly and efficiently discover misannotations, yielding a more accurate and complete genome annotation. We present a comprehensive proteogenomic analysis of the plague bacterium, Yersinia pestis KIM. We discover non-annotated genes, correct protein boundaries, remove spuriously annotated ORFs, and make major advances towards accurate identification of signal peptides. Finally, we apply our data to 21 other Yersinia genomes, correcting and enhancing their annotations.ConclusionsIn total, 141 gene models were altered and have been updated in RefSeq and Genbank, which can be accessed seamlessly through any NCBI tool (e.g. blast) or downloaded directly. Along with the improved gene models we discover new, more accurate means of identifying signal peptides in proteomics data.

A full-length cDNA resource for the pea aphid, Acyrthosiphon pisum.

Large collections of full-length cDNAs are important resources for genome annotation and functional genomics. We report the creation of a collection of 50 599 full-length cDNA clones from the pea aphid, Acyrthosiphon pisum. Sequencing from 5' and 3' ends of the clones generated 97 828 high-quality expressed sequence tags, representing approximately 9000 genes. These sequences were imported to AphidBase and are shown to play crucial roles in both automatic gene prediction and manual annotation. Our detailed analyses demonstrated that the full-length cDNAs can further improve gene models and can even identify novel genes that are not included in the current version of the official gene set. This full-length cDNA collection can be utilized for a wide variety of functional studies, serving as a community resource for the study of the functional genomics of the pea aphid.

Phylogeny and expression of carbonic anhydrase-related proteins

BackgroundCarbonic anhydrases (CAs) are found in many organisms, in which they contribute to several important biological processes. The vertebrate α-CA family consists of 16 subfamilies, three of which (VIII, X and XI) consist of acatalytic proteins. These are named carbonic anhydrase related proteins (CARPs), and their inactivity is due to absence of one or more Zn-binding histidine residues. In this study, we analyzed and evaluated the distribution of genes encoding CARPs in different organisms using bioinformatic methods, and studied their expression in mouse tissues using immunohistochemistry and real-time quantitative PCR.ResultsWe collected 84 sequences, of which 22 came from novel or improved gene models which we created from genome data. The distribution of CARP VIII covers vertebrates and deuterostomes, and CARP X appears to be universal in the animal kingdom. CA10-like genes have had a separate history of duplications in the tetrapod and fish lineages. Our phylogenetic analysis showed that duplication of CA10 into CA11 has occurred only in tetrapods (found in mammals, frogs, and lizards), whereas an independent duplication of CA10 was found in fishes. We suggest the name CA10b for the second fish isoform. Immunohistochemical analysis showed a high expression level of CARP VIII in the mouse cerebellum, cerebrum, and also moderate expression in the lung, liver, salivary gland, and stomach. These results also demonstrated low expression in the colon, kidney, and Langerhans islets. CARP X was moderately expressed in the cerebral capillaries and the lung and very weakly in the stomach and heart. Positive signals for CARP XI were observed in the cerebellum, cerebrum, liver, stomach, small intestine, colon, kidney, and testis. In addition, the results of real-time quantitative PCR confirmed a wide distribution for the Car8 and Car11 mRNAs, whereas the expression of the Car10 mRNA was restricted to the frontal cortex, parietal cortex, cerebellum, midbrain, and eye.ConclusionsCARP sequences have been strongly conserved between different species, and all three CARPs show high expression in the mouse brain and CARP VIII is also expressed in several other tissues. These findings suggest an important functional role for these proteins in mammals.

Caenorhabditis elegans cisRED: a catalogue of conserved genomic elements

The availability of completely sequenced genomes from eight species of nematodes has provided an opportunity to identify novel cis-regulatory elements in the promoter regions of Caenorhabditis elegans transcripts using comparative genomics. We determined orthologues for C. elegans transcripts in C. briggsae, C. remanei, C. brenneri, C. japonica, Pristionchus pacificus, Brugia malayi and Trichinella spiralis using the WABA alignment algorithm. We pooled the upstream region of each transcript in C. elegans with the upstream regions of its orthologues and identified conserved DNA sequence elements by de novo motif discovery. In total, we discovered 158 017 novel conserved motifs upstream of 3847 C. elegans transcripts for which three or more orthologues were available, and identified 82% of 44 experimentally proven regulatory elements from ORegAnno. We annotated 26% of the motifs as similar to known binding sequences of transcription factors from ORegAnno, TRANSFAC and JASPAR. This is the first catalogue of annotated conserved upstream elements for nematodes and can be used to find putative regulatory elements, improve gene models, discover novel RNA genes, and understand the evolution of transcription factors and their binding sites in phylum Nematoda. The annotated motifs provide novel binding site candidates for both characterized transcription factors and orthologues of characterized mammalian transcription factors.

Analysis of CATMA transcriptome data identifies hundreds of novel functional genes and improves gene models in the Arabidopsis genome

BackgroundSince the finishing of the sequencing of the Arabidopsis thaliana genome, the Arabidopsis community and the annotator centers have been working on the improvement of gene annotation at the structural and functional levels. In this context, we have used the large CATMA resource on the Arabidopsis transcriptome to search for genes missed by different annotation processes. Probes on the CATMA microarrays are specific gene sequence tags (GSTs) based on the CDS models predicted by the Eugene software. Among the 24 576 CATMA v2 GSTs, 677 are in regions considered as intergenic by the TAIR annotation. We analyzed the cognate transcriptome data in the CATMA resource and carried out data-mining to characterize novel genes and improve gene models.ResultsThe statistical analysis of the results of more than 500 hybridized samples distributed among 12 organs provides an experimental validation for 465 novel genes. The hybridization evidence was confirmed by RT-PCR approaches for 88% of the 465 novel genes. Comparisons with the current annotation show that these novel genes often encode small proteins, with an average size of 137 aa. Our approach has also led to the improvement of pre-existing gene models through both the extension of 16 CDS and the identification of 13 gene models erroneously constituted of two merged CDS.ConclusionThis work is a noticeable step forward in the improvement of the Arabidopsis genome annotation. We increased the number of Arabidopsis validated genes by 465 novel transcribed genes to which we associated several functional annotations such as expression profiles, sequence conservation in plants, cognate transcripts and protein motifs.