Systematic expression profiling of the mouse transcriptome using RIKEN cDNA microarrays

LncRNA and mRNA expression profiles in brown adipose tissue of obesity-prone and obesity-resistant mice

Obesity-prone or obesity-resistant phenotypes can exist in individuals who consume the same diet type. Brown adipose tissue functions to dissipate energy in response to cold exposure or overfeeding. Long noncoding RNAs play important roles in a wide range of biological processes. However, systematic examination of lncRNAs in phenotypically divergent mice has not yet been reported. Here, the lncRNA expression profiles in BAT of HFD-induced C57BL/6J mice were investigated by high-throughput RNA sequencing. Genes that play roles in thermogenesis and related pathways were identified. We found lncRNA (Gm44502) may play a thermogenic role in obesity resistance by interacting with six mRNAs. Our results also indicated that seven differentially expressed lncRNAs (4930528G23Rik, Gm39490, Gm5627, Gm15551, Gm16083, Gm36860, Gm42002) may play roles in reducing heat production in obesity susceptibility by interacting with seven differentially expressed mRNAs. The screened lncRNAs may participate in the pathogenesis of weight regulation and provide insight into obesity therapy.

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First lncRNA profiles in BAT of OR and OP mice via bioinformatic analysis

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Gm44502 may play a thermogenic role by interacting with 6 mRNAs

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7 DElncRNAs may reduce thermogenesis by interacting with 7 DEmRNAs

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Validation of expression changes of candidate genes in BAT by in vivo or in vitro

Genome-wide discovery and characterization of long noncoding RNAs in patients with multiple myeloma

Background

Long noncoding RNAs (lncRNAs) are involved in a wide range of biological processes in tumorigenesis. However, the role of lncRNA expression in the biology, prognosis, and molecular classification of human multiple myeloma (MM) remains unclear, especially the biological functions of the vast majority of lncRNAs. Recently, lncRNAs have been identified in neoplastic hematologic disorders. Evidence has accumulated on the molecular mechanisms of action of lncRNAs, providing insight into their functional roles in tumorigenesis. This study aimed to characterize potential lncRNAs in patients with MM.

Methods

In this study, the whole-transcriptome strand-specific RNA sequencing of samples from three newly diagnosed patients with MM was performed. The whole transcriptome, including lncRNAs, microRNAs, and mRNAs, was analyzed. Using these data, MM lncRNAs were systematically analyzed, and the lncRNAs involved in the occurrence of MM were identified.

Results

The results revealed that MM lncRNAs had distinctive characteristics different from those of other malignant tumors. Further, the functions of a set of lncRNAs preferentially expressed in MM were verified, and several lncRNAs were identified as competing endogenous RNAs. More importantly, the aberrant expression of certain lncRNAs, including maternally expressed gene3, colon cancer–associated transcript1, and coiled-coil domain-containing 26, as well as some novel lncRNAs involved in the occurrence of MM was established. Further, lncRNAs were related to some microRNAs, regulated each other, and participated in MM development.

Conclusions

Genome-wide screening and functional analysis enabled the identification of a set of lncRNAs involved in the occurrence of MM. The interaction exists among microRNAs and lncRNAs.

The therapeutic role of long non-coding RNAs in human diseases: A focus on the recent insights into autophagy

Long non-coding RNA (lncRNA) is a class of non-coding RNA with ≥200 nucleotides in length which are involved as critical regulators in various cellular processes. LncRNAs contribute to the development and progression of many human diseases. Autophagy is a key catabolic process which helps to maintain the cellular homeostasis through the decay of damaged or unwanted proteins and dysfunctional cytoplasmic organelles. The impairment of the autophagy process has been described in numerous diseases. The autophagy possess can have either a protective or a detrimental role in cells depending on its activation status and other cellular conditions. LncRNAs have been shown to have an important function in the regulation of important biological processes such as autophagy. The relationship between lncRNAs and autophagy has been shown to be involved in the progression and possibly in the prevention of many diseases. In this review, recent findings on the regulatory roles of lncRNAs in the cell autophagy pathway, as well as their relevance to different diseases such as cardiovascular disease, cerebral ischemic stroke and cancer are highlighted.

Long Non-Coding RNAs in Metabolic Organs and Energy Homeostasis

Single cell organisms can surprisingly exceed the number of human protein-coding genes, which are thus not at the origin of the complexity of an organism. In contrast, the relative amount of non-protein-coding sequences increases consistently with organismal complexity. Moreover, the mammalian transcriptome predominantly comprises non-(protein)-coding RNAs (ncRNA), of which the long ncRNAs (lncRNAs) constitute the most abundant part. lncRNAs are highly species- and tissue-specific with very versatile modes of action in accordance with their binding to a large spectrum of molecules and their diverse localization. lncRNAs are transcriptional regulators adding an additional regulatory layer in biological processes and pathophysiological conditions. Here, we review lncRNAs affecting metabolic organs with a focus on the liver, pancreas, skeletal muscle, cardiac muscle, brain, and adipose organ. In addition, we will discuss the impact of lncRNAs on metabolic diseases such as obesity and diabetes. In contrast to the substantial number of lncRNA loci in the human genome, the functionally characterized lncRNAs are just the tip of the iceberg. So far, our knowledge concerning lncRNAs in energy homeostasis is still in its infancy, meaning that the rest of the iceberg is a treasure chest yet to be discovered.

RefEx, a reference gene expression dataset as a web tool for the functional analysis of genes

Gene expression data are exponentially accumulating; thus, the functional annotation of such sequence data from metadata is urgently required. However, life scientists have difficulty utilizing the available data due to its sheer magnitude and complicated access. We have developed a web tool for browsing reference gene expression pattern of mammalian tissues and cell lines measured using different methods, which should facilitate the reuse of the precious data archived in several public databases. The web tool is called Reference Expression dataset (RefEx), and RefEx allows users to search by the gene name, various types of IDs, chromosomal regions in genetic maps, gene family based on InterPro, gene expression patterns, or biological categories based on Gene Ontology. RefEx also provides information about genes with tissue-specific expression, and the relative gene expression values are shown as choropleth maps on 3D human body images from BodyParts3D. Combined with the newly incorporated Functional Annotation of Mammals (FANTOM) dataset, RefEx provides insight regarding the functional interpretation of unfamiliar genes. RefEx is publicly available at http://refex.dbcls.jp/.

Long non-coding RNAs: Mechanism of action and functional utility

Recent RNA sequencing studies have revealed that most of the human genome is transcribed, but very little of the total transcriptomes has the ability to encode proteins. Long non-coding RNAs (lncRNAs) are non-coding transcripts longer than 200 nucleotides. Members of the non-coding genome include microRNA (miRNA), small regulatory RNAs and other short RNAs. Most of long non-coding RNA (lncRNAs) are poorly annotated. Recent recognition about lncRNAs highlights their effects in many biological and pathological processes. LncRNAs are dysfunctional in a variety of human diseases varying from cancerous to non-cancerous diseases. Characterization of these lncRNA genes and their modes of action may allow their use for diagnosis, monitoring of progression and targeted therapies in various diseases. In this review, we summarize the functional perspectives as well as the mechanism of action of lncRNAs.

Long noncoding RNAs in regulating adipogenesis: new RNAs shed lights on obesity

Long noncoding RNAs (lncRNAs) are an emerging class of regulators involved in a myriad of biological processes. Recent studies have revealed that many lncRNAs play pivotal roles in regulating adipocyte development. Due to the prevalence of obesity and the serious effects of adiposity on human health and society development, it is necessary to summarize functions and recent advances of lncRNAs in adipogenesis. In this review, we highlight functional lncRNAs contributed to the regulation of adipogenesis, discussing their potential use as therapeutic targets to combat human obesity.

Constructing lncRNA functional similarity network based on lncRNA-disease associations and disease semantic similarity

Increasing evidence has indicated that plenty of lncRNAs play important roles in many critical biological processes. Developing powerful computational models to construct lncRNA functional similarity network based on heterogeneous biological datasets is one of the most important and popular topics in the fields of both lncRNAs and complex diseases. Functional similarity network consturction could benefit the model development for both lncRNA function inference and lncRNA-disease association identification. However, little effort has been attempted to analysis and calculate lncRNA functional similarity on a large scale. In this study, based on the assumption that functionally similar lncRNAs tend to be associated with similar diseases, we developed two novel lncRNA functional similarity calculation models (LNCSIM). LNCSIM was evaluated by introducing similarity scores into the model of Laplacian Regularized Least Squares for LncRNA–Disease Association (LRLSLDA) for lncRNA-disease association prediction. As a result, new predictive models improved the performance of LRLSLDA in the leave-one-out cross validation of various known lncRNA-disease associations datasets. Furthermore, some of the predictive results for colorectal cancer and lung cancer were verified by independent biological experimental studies. It is anticipated that LNCSIM could be a useful and important biological tool for human disease diagnosis, treatment, and prevention.

A systems genetics study of swine illustrates mechanisms underlying human phenotypic traits

Background

The pig, which shares greater similarities with human than with mouse, is important for agriculture and for studying human diseases. However, similarities in the genetic architecture and molecular regulations underlying phenotypic variations in humans and swine have not been systematically assessed.

Results

We systematically surveyed ~500 F2 pigs genetically and phenotypically. By comparing candidates for anemia traits identified in swine genome-wide SNP association and human genome-wide association studies (GWAS), we showed that both sets of candidates are related to the biological process “cellular lipid metabolism” in liver. Human height is a complex heritable trait; by integrating genome-wide SNP data and human adipose Bayesian causal network, which closely represents bone transcriptional regulations, we identified PLAG1 as a causal gene for limb bone length. This finding is consistent with GWAS findings for human height and supports the common genetic architecture between swine and humans. By leveraging a human protein-protein interaction network, we identified two putative candidate causal genes TGFB3 and DAB2IP and the known regulators MESP1 and MESP2 as responsible for the variation in rib number and identified the potential underlying molecular mechanisms. In mice, knockout of Tgfb3 and Tgfb2 together decreases rib number.

Conclusion

Our findings show that integrative network analyses reveal causal regulators underlying the genetic association of complex traits in swine and that these causal regulators have similar effects in humans. Thus, swine are a potentially good animal model for studying some complex human traits that are not under intense selection.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1240-y) contains supplementary material, which is available to authorized users.

Identification of large intergenic non-coding RNAs in bovine muscle using next-generation transcriptomic sequencing

Background

The advent of large-scale gene expression technologies has helped to reveal in eukaryotic cells, the existence of thousands of non-coding transcripts, whose function and significance remain mostly poorly understood. Among these non-coding transcripts, long non-coding RNAs (lncRNAs) are the least well-studied but are emerging as key regulators of diverse cellular processes. In the present study, we performed a survey in bovine Longissimus thoraci of lincRNAs (long intergenic non-coding RNAs not overlapping protein-coding transcripts). To our knowledge, this represents the first such study in bovine muscle.

Results

To identify lincRNAs, we used paired-end RNA sequencing (RNA-Seq) to explore the transcriptomes of Longissimus thoraci from nine Limousin bull calves. Approximately 14–45 million paired-end reads were obtained per library. A total of 30,548 different transcripts were identified. Using a computational pipeline, we defined a stringent set of 584 different lincRNAs with 418 lincRNAs found in all nine muscle samples. Bovine lincRNAs share characteristics seen in their mammalian counterparts: relatively short transcript and gene lengths, low exon number and significantly lower expression, compared to protein-encoding genes. As for the first time, our study identified lincRNAs from nine different samples from the same tissue, it is possible to analyse the inter-individual variability of the gene expression level of the identified lincRNAs. Interestingly, there was a significant difference when we compared the expression variation of the 418 lincRNAs with the 10,775 known selected protein-encoding genes found in all muscle samples. In addition, we found 2,083 pairs of lincRNA/protein-encoding genes showing a highly significant correlated expression. Fourteen lincRNAs were selected and 13 were validated by RT-PCR. Some of the lincRNAs expressed in muscle are located within quantitative trait loci for meat quality traits.

Conclusions

Our study provides a glimpse into the lincRNA content of bovine muscle and will facilitate future experimental studies to unravel the function of these molecules. It may prove useful to elucidate their effect on mechanisms underlying the genetic variability of meat quality traits. This catalog will complement the list of lincRNAs already discovered in cattle and therefore will help to better annotate the bovine genome.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-499) contains supplementary material, which is available to authorized users.

X chromosome control of meiotic chromosome synapsis in mouse inter-subspecific hybrids

Hybrid sterility (HS) belongs to reproductive isolation barriers that safeguard the integrity of species in statu nascendi. Although hybrid sterility occurs almost universally among animal and plant species, most of our current knowledge comes from the classical genetic studies on Drosophila interspecific crosses or introgressions. With the house mouse subspecies Mus m. musculus and Mus m. domesticus as a model, new research tools have become available for studies of the molecular mechanisms and genetic networks underlying HS. Here we used QTL analysis and intersubspecific chromosome substitution strains to identify a 4.7 Mb critical region on Chromosome X (Chr X) harboring the Hstx2 HS locus, which causes asymmetrical spermatogenic arrest in reciprocal intersubspecific F1 hybrids. Subsequently, we mapped autosomal loci on Chrs 3, 9 and 13 that can abolish this asymmetry. Combination of immunofluorescent visualization of the proteins of synaptonemal complexes with whole-chromosome DNA FISH on pachytene spreads revealed that heterosubspecific, unlike consubspecific, homologous chromosomes are predisposed to asynapsis in F1 hybrid male and female meiosis. The asynapsis is under the trans- control of Hstx2 and Hst1/Prdm9 hybrid sterility genes in pachynemas of male but not female hybrids. The finding concurred with the fertility of intersubpecific F1 hybrid females homozygous for the Hstx2^Mmm allele and resolved the apparent conflict with the dominance theory of Haldane's rule. We propose that meiotic asynapsis in intersubspecific hybrids is a consequence of cis-acting mismatch between homologous chromosomes modulated by the trans-acting Hstx2 and Prdm9 hybrid male sterility genes.

Genomes of newly emerging species restrict their gene exchange with related taxa in order to secure integrity. Hybrid sterility is one of the reproductive isolation mechanisms restricting gene flow between closely related, sexually reproducing organisms. We showed that hybrid sterility between two closely related mouse subspecies is executed by a failure of meiotic synapsis of orthologous chromosomes in F1 hybrid males. The asynapsis of orthologous chromosomes occurred in meiosis of male and female hybrids, though only males were sterile due to trans-acting male-specific hybrid sterility genes. We located one of the two major hybrid sterility genes to a 4.7 Mb interval on Chromosome X, showed that it controls male sterility by modulating the extent of meiotic asynapsis and using the inter-subspecific chromosome substitution strains we refuted the simple interpretation of dominance theory of Haldane's rule. A new working hypothesis posits male sterility of mouse inter-subsubspecific F1 hybrids as a consequence of meiotic chromosome asynapsis caused by the cis-acting mismatch between orthologous chromosomes modulated by the trans-acting hybrid male sterility genes.

Novel human lncRNA-disease association inference based on lncRNA expression profiles

MOTIVATION

More and more evidences have indicated that long-non-coding RNAs (lncRNAs) play critical roles in many important biological processes. Therefore, mutations and dysregulations of these lncRNAs would contribute to the development of various complex diseases. Developing powerful computational models for potential disease-related lncRNAs identification would benefit biomarker identification and drug discovery for human disease diagnosis, treatment, prognosis and prevention.

RESULTS

In this article, we proposed the assumption that similar diseases tend to be associated with functionally similar lncRNAs. Then, we further developed the method of Laplacian Regularized Least Squares for LncRNA-Disease Association (LRLSLDA) in the semisupervised learning framework. Although known disease-lncRNA associations in the database are rare, LRLSLDA still obtained an AUC of 0.7760 in the leave-one-out cross validation, significantly improving the performance of previous methods. We also illustrated the performance of LRLSLDA is not sensitive (even robust) to the parameters selection and it can obtain a reliable performance in all the test classes. Plenty of potential disease-lncRNA associations were publicly released and some of them have been confirmed by recent results in biological experiments. It is anticipated that LRLSLDA could be an effective and important biological tool for biomedical research.

AVAILABILITY

The code of LRLSLDA is freely available at http://asdcd.amss.ac.cn/Software/Details/2.

DIANA-LncBase: experimentally verified and computationally predicted microRNA targets on long non-coding RNAs

Recently, the attention of the research community has been focused on long non-coding RNAs (lncRNAs) and their physiological/pathological implications. As the number of experiments increase in a rapid rate and transcriptional units are better annotated, databases indexing lncRNA properties and function gradually become essential tools to this process. Aim of DIANA-LncBase (www.microrna.gr/LncBase) is to reinforce researchers’ attempts and unravel microRNA (miRNA)–lncRNA putative functional interactions. This study provides, for the first time, a comprehensive annotation of miRNA targets on lncRNAs. DIANA-LncBase hosts transcriptome-wide experimentally verified and computationally predicted miRNA recognition elements (MREs) on human and mouse lncRNAs. The analysis performed includes an integration of most of the available lncRNA resources, relevant high-throughput HITS-CLIP and PAR-CLIP experimental data as well as state-of-the-art in silico target predictions. The experimentally supported entries available in DIANA-LncBase correspond to >5000 interactions, while the computationally predicted interactions exceed 10 million. DIANA-LncBase hosts detailed information for each miRNA–lncRNA pair, such as external links, graphic plots of transcripts’ genomic location, representation of the binding sites, lncRNA tissue expression as well as MREs conservation and prediction scores.

Identification of novel markers of mouse fetal ovary development

In contrast to the developing testis, molecular pathways driving fetal ovarian development have been difficult to characterise. To date no single master regulator of ovarian development has been identified that would be considered the female equivalent of Sry. Using a genomic approach we identified a number of novel protein-coding as well as non-coding genes that were detectable at higher levels in the ovary compared to testis during early mouse gonad development. We were able to cluster these ovarian genes into different temporal expression categories. Of note, Lrrc34 and AK015184 were detected in XX but not XY germ cells before the onset of sex-specific germ cell differentiation marked by entry into meiosis in an ovary and mitotic arrest in a testis. We also defined distinct spatial expression domains of somatic cell genes in the developing ovary. Our data expands the set of markers of early mouse ovary differentiation and identifies a classification of early ovarian genes, thus providing additional avenues with which to dissect this process.

Long non-coding RNA expression profiles predict clinical phenotypes in glioma

Glioma is the commonest form of primary brain tumor in adults with varying malignancy grades and histological subtypes. Long non-coding RNAs (lncRNAs) are a novel class of non-protein-coding transcripts that have been shown to play important roles in cancer development. To discover novel tumor-related lncRNAs and determine their associations with glioma subtypes, we first applied a lncRNA classification pipeline to identify 1970 lncRNAs that were represented on Affymetrix HG-U133 Plus 2.0 array. We then analyzed the lncRNA expression patterns in a set of previously published glioma gene expression profiles of 268 clinical specimens, and identified sets of lncRNAs that were unique to different histological subtypes (astrocytic versus oligodendroglial tumors) and malignancy grades. These lncRNAs signatures were then subject to validation in another non-overlapping, independent data set that contained 157 glioma samples. This is the first reported study that correlates lncRNA expression profiles with malignancy grade and histological differentiation in human gliomas. Our findings indicate the potential roles of lncRNAs in the biogenesis, development and differentiation of gliomas, and provide an important platform for future studies.

NONCODE v3.0: integrative annotation of long noncoding RNAs

Facilitated by the rapid progress of high-throughput sequencing technology, a large number of long noncoding RNAs (lncRNAs) have been identified in mammalian transcriptomes over the past few years. LncRNAs have been shown to play key roles in various biological processes such as imprinting control, circuitry controlling pluripotency and differentiation, immune responses and chromosome dynamics. Notably, a growing number of lncRNAs have been implicated in disease etiology. With the increasing number of published lncRNA studies, the experimental data on lncRNAs (e.g. expression profiles, molecular features and biological functions) have accumulated rapidly. In order to enable a systematic compilation and integration of this information, we have updated the NONCODE database (http://www.noncode.org) to version 3.0 to include the first integrated collection of expression and functional lncRNA data obtained from re-annotated microarray studies in a single database. NONCODE has a user-friendly interface with a variety of search or browse options, a local Genome Browser for visualization and a BLAST server for sequence-alignment search. In addition, NONCODE provides a platform for the ongoing collation of ncRNAs reported in the literature. All data in NONCODE are open to users, and can be downloaded through the website or obtained through the SOAP API and DAS services.

The functional role of long non-coding RNA in human carcinomas

Long non-coding RNAs (lncRNAs) are emerging as new players in the cancer paradigm demonstrating potential roles in both oncogenic and tumor suppressive pathways. These novel genes are frequently aberrantly expressed in a variety of human cancers, however the biological functions of the vast majority remain unknown. Recently, evidence has begun to accumulate describing the molecular mechanisms by which these RNA species function, providing insight into the functional roles they may play in tumorigenesis. In this review, we highlight the emerging functional role of lncRNAs in human cancer.

Large-scale prediction of long non-coding RNA functions in a coding-non-coding gene co-expression network

Although accumulating evidence has provided insight into the various functions of long-non-coding RNAs (lncRNAs), the exact functions of the majority of such transcripts are still unknown. Here, we report the first computational annotation of lncRNA functions based on public microarray expression profiles. A coding–non-coding gene co-expression (CNC) network was constructed from re-annotated Affymetrix Mouse Genome Array data. Probable functions for altogether 340 lncRNAs were predicted based on topological or other network characteristics, such as module sharing, association with network hubs and combinations of co-expression and genomic adjacency. The functions annotated to the lncRNAs mainly involve organ or tissue development (e.g. neuron, eye and muscle development), cellular transport (e.g. neuronal transport and sodium ion, acid or lipid transport) or metabolic processes (e.g. involving macromolecules, phosphocreatine and tyrosine).

Expression of G protein-coupled receptors and related proteins in HEK293, AtT20, BV2, and N18 cell lines as revealed by microarray analysis

BACKGROUND

G protein coupled receptors (GPCRs) are one of the most widely studied gene superfamilies. Thousands of GPCR research studies have utilized heterologous expression systems such as human embryonic kidney cells (HEK293). Though often treated as 'blank slates', these cell lines nevertheless endogenously express GPCRs and related signaling proteins. The outcome of a given GPCR study can be profoundly influenced by this largely unknown complement of receptors and/or signaling proteins. Little easily accessible information exists that describes the expression profiles of the GPCRs in cell lines. What is accessible is often limited in scope - of the hundreds of GPCRs and related proteins, one is unlikely to find information on expression of more than a dozen proteins in a given cell line. Microarray technology has allowed rapid analysis of mRNA levels of thousands of candidate genes, but though often publicly available, the results can be difficult to efficiently access or even to interpret.

RESULTS

To bridge this gap, we have used microarrays to measure the mRNA levels of a comprehensive profile of non-chemosensory GPCRs and over a hundred GPCR signaling related gene products in four cell lines frequently used for GPCR research: HEK293, AtT20, BV2, and N18.

CONCLUSIONS

This study provides researchers an easily accessible mRNA profile of the endogenous signaling repertoire that these four cell lines possess. This will assist in choosing the most appropriate cell line for studying GPCRs and related signaling proteins. It also provides a better understanding of the potential interactions between GPCRs and those signaling proteins.

Hippocampal gene profiling: toward a systems biology of the hippocampus

Transcriptomics and proteomics approaches give a unique perspective for understanding brain and hippocampal functions but also pose unique challenges because of the singular complexity of the nervous system. The proliferation of genome-wide expression studies during the last decade has provided important insight into the molecular underpinnings of brain anatomy, neural plasticity, and neurological diseases. Microarray technology has dominated transcriptomics research, but this situation is rapidly changing with the recent technological advances in high-throughput sequencing. The full potential of transcriptomics in the neurosciences will be achieved as a result of its integration with other "-omics" disciplines as well as the development of novel analytical bioinformatics and systems biology tools for meta-analysis. Here, we review some of the most relevant advances in the gene profiling of the hippocampus, its relationship with proteomics approaches, and the promising perspectives for the future.

Comparative analysis of the testis and ovary transcriptomes in zebrafish by combining experimental and computational tools

Studies on the zebrafish model have contributed to our understanding of several important developmental processes, especially those that can be easily studied in the embryo. However, our knowledge on late events such as gonad differentiation in the zebrafish is still limited. Here we provide an analysis on the gene sets expressed in the adult zebrafish testis and ovary in an attempt to identify genes with potential role in (zebra)fish gonad development and function. We produced 10,533 expressed sequence tags (ESTs) from zebrafish testis or ovary and downloaded an additional 23,642 gonad-derived sequences from the zebrafish EST database. We clustered these sequences together with over 13,000 kidney-derived zebrafish ESTs to study partial transcriptomes for these three organs. We searched for genes with gonad-specific expression by screening macroarrays containing at least 2600 unique cDNA inserts with testis-, ovary- and kidney-derived cDNA probes. Clones hybridizing to only one of the two gonad probes were selected, and subsequently screened with computational tools to identify 72 genes with potentially testis-specific and 97 genes with potentially ovary-specific expression, respectively. PCR-amplification confirmed gonad-specificity for 21 of the 45 clones tested (all without known function). Our study, which involves over 47,000 EST sequences and specialized cDNA arrays, is the first analysis of adult organ transcriptomes of zebrafish at such a scale. The study of genes expressed in adult zebrafish testis and ovary will provide useful information on regulation of gene expression in teleost gonads and might also contribute to our understanding of the development and differentiation of reproductive organs in vertebrates.

Characterization of mouse synaptic vesicle-2-associated protein (Msvop) specifically expressed in the mouse central nervous system

In this study, we identified and characterized a mouse brain-enriched unigene (msvop) after performing digital differential display. Msvop was the mouse ortholog of Xenopus synaptic vesicle-2-associated protein (svop), the molecular characteristics of which were unknown. The 3125-bp full-length cDNA encoded a 548-aa protein of approximately 60 kDa. A strong promoter element was found in the -200 to -100 bp region in both NG108-15 and HEK293 cells. RT-PCR and in situ hybridization analysis confirmed that msvop was strictly expressed in the mouse central nervous system. In adult brains, msvop was highly expressed in the hippocampus and cerebellum. When the gene was transfected into HEK293 cells in a GFP fusion vector, the protein was specifically localized in the cytosol. These results indicate that msvop is a central nervous system-specific gene and could be utilized for elucidating gene regulation in neuronal cells.

Computational search for over-represented 8-mers within the 5'-regulatory regions of 634 mouse testis-specific genes

Accumulation of microarray data has enabled the computational analysis of gene expressions in various tissues. Although the genes showing testis-specific expression are most abundant among the genes exhibiting tissue-specific expression, no systematic study has been conducted for over-represented motifs within their regulatory regions. We have identified 117 over-represented 8-mers that appeared 2648 times within the regulatory regions of 634 testis-specific genes. Of these, 64 over-represented 8-mers were significantly more frequent in the regulatory regions of testis-specific genes than in those of non-testis-specific genes. In this group of 8-mers, 4 8-mers differed from the canonical cAMP response element (CRE) 8-mer by 1 letter, but the canonical CRE was not included in this group. We consider that CRE-like 8-mers participate in the regulatory expression of testis-specific genes to a greater extent than the canonical CRE 8-mer.

A complex genetic basis to X-linked hybrid male sterility between two species of house mice

The X chromosome plays a central role in the evolution of reproductive isolation, but few studies have examined the genetic basis of X-linked incompatibilities during the early stages of speciation. We report the results of a large experiment focused on the reciprocal introgression of the X chromosome between two species of house mice, Mus musculus and M. domesticus. Introgression of the M. musculus X chromosome into a wild-derived M. domesticus genetic background produced male-limited sterility, qualitatively consistent with previous experiments using classic inbred strains to represent M. domesticus. The genetic basis of sterility involved a minimum of four X-linked factors. The phenotypic effects of major sterility QTL were largely additive and resulted in complete sterility when combined. No sterility factors were uncovered on the M. domesticus X chromosome. Overall, these results revealed a complex and asymmetric genetic basis to X-linked hybrid male sterility during the early stages of speciation in mice. Combined with data from previous studies, we identify one relatively narrow interval on the M. musculus X chromosome involved in hybrid male sterility. Only a handful of spermatogenic genes are within this region, including one of the most rapidly evolving genes on the mouse X chromosome.

Research resource: nuclear hormone receptor expression in the endocrine pancreas

The endocrine pancreas comprises the islets of Langerhans, tiny clusters of cells that contribute only about 2% to the total pancreas mass. However, this little endocrine organ plays a critical role in maintaining glucose homeostasis by the regulated secretion of insulin (by beta-cells) and glucagon (by alpha-cells). The rapid increase in the incidence of diabetes worldwide has spurred renewed interest in islet cell biology. Some of the most widely prescribed oral drugs for treating type 2 diabetes include agents that bind and activate the nuclear hormone receptor, peroxisome proliferator-activated receptor-gamma. As a first step in addressing potential roles of peroxisome proliferator-activated receptor-gamma and other nuclear hormone receptors (NHRs) in the biology of the endocrine pancreas, we have used quantitative real-time PCR to profile the expression of all 49 members of the mouse NHR superfamily in primary islets, and cell lines that represent alpha-cells (alphaTC1) and beta-cells (betaTC6 and MIN6). In summary, 19 NHR members were highly expressed in both alpha- and beta-cell lines, 13 receptors showed predominant expression (at least an 8-fold difference) in alpha- vs. beta-cell lines, and 10 NHRs were not expressed in the endocrine pancreas. In addition we evaluated the relative expression of these transcription factors during hyperglycemia and found that 16 NHRs showed significantly altered mRNA levels in mouse islets. A similar survey was conducted in primary human islets to reveal several significant differences in NHR expression between mouse and man. These data identify potential therapeutic targets in the endocrine pancreas for the treatment of diabetes mellitus.

MicroRNA-encoding long non-coding RNAs

BACKGROUND

Recent analysis of the mouse transcriptional data has revealed the existence of approximately 34,000 messenger-like non-coding RNAs (ml-ncRNAs). Whereas the functional properties of these ml-ncRNAs are beginning to be unravelled, no functional information is available for the large majority of these transcripts.

RESULTS

A few ml-ncRNA have been shown to have genomic loci that overlap with microRNA loci, leading us to suspect that a fraction of ml-ncRNA may encode microRNAs. We therefore developed an algorithm (PriMir) for specifically detecting potential microRNA-encoding transcripts in the entire set of 34,030 mouse full-length ml-ncRNAs. In combination with mouse-rat sequence conservation, this algorithm detected 97 (80 of them were novel) strong miRNA-encoding candidates, and for 52 of these we obtained experimental evidence for the existence of their corresponding mature microRNA by microarray and stem-loop RT-PCR. Sequence analysis of the microRNA-encoding RNAs revealed an internal motif, whose presence correlates strongly (R2 = 0.9, P-value = 2.2 x 10(-16)) with the occurrence of stem-loops with characteristics of known pre-miRNAs, indicating the presence of a larger number microRNA-encoding RNAs (from 300 up to 800) in the ml-ncRNAs population.

CONCLUSION

Our work highlights a unique group of ml-ncRNAs and offers clues to their functions.

Characterization of a novel mouse brain gene (mbu-1) identified by digital differential display

Using in silico approaches, we cloned a novel mouse gene (mbu-1) that was strictly expressed in the central nervous system. mbu-1 was first identified as an EST after carrying out digital differential display for unigene libraries from various mouse tissues. The full-length cDNA sequence was obtained by extending the ends of EST by RACE. The cDNA sequence was 2611 bp long and contained an ORF of 597 AA. A positive cis-acting region was found in the neuroblastomaxglioma hybrid, NG108-15, and in human embryonic kidney HEK293 cell lines. RT-PCR and in situ hybridization analysis showed that the mbu-1 gene was only expressed in the brain and spinal cord during the embryonic stages, and throughout all regions of the adult brain, showing higher levels in the hippocampus and hypothalamus.

JUICE: a data management system that facilitates the analysis of large volumes of information in an EST project workflow

Background

Expressed sequence tag (EST) analyses provide a rapid and economical means to identify candidate genes that may be involved in a particular biological process. These ESTs are useful in many Functional Genomics studies. However, the large quantity and complexity of the data generated during an EST sequencing project can make the analysis of this information a daunting task.

Results

In an attempt to make this task friendlier, we have developed JUICE, an open source data management system (Apache + PHP + MySQL on Linux), which enables the user to easily upload, organize, visualize and search the different types of data generated in an EST project pipeline. In contrast to other systems, the JUICE data management system allows a branched pipeline to be established, modified and expanded, during the course of an EST project.

The web interfaces and tools in JUICE enable the users to visualize the information in a graphical, user-friendly manner. The user may browse or search for sequences and/or sequence information within all the branches of the pipeline. The user can search using terms associated with the sequence name, annotation or other characteristics stored in JUICE and associated with sequences or sequence groups. Groups of sequences can be created by the user, stored in a clipboard and/or downloaded for further analyses.

Different user profiles restrict the access of each user depending upon their role in the project. The user may have access exclusively to visualize sequence information, access to annotate sequences and sequence information, or administrative access.

Conclusion

JUICE is an open source data management system that has been developed to aid users in organizing and analyzing the large amount of data generated in an EST Project workflow. JUICE has been used in one of the first functional genomics projects in Chile, entitled "Functional Genomics in nectarines: Platform to potentiate the competitiveness of Chile in fruit exportation". However, due to its ability to organize and visualize data from external pipelines, JUICE is a flexible data management system that should be useful for other EST/Genome projects. The JUICE data management system is released under the Open Source GNU Lesser General Public License (LGPL). JUICE may be downloaded from or .

Cell type-specific analyses for identifying prostate cancer biomarkers

Cancers of the prostate contribute substantial morbidity and mortality to the male population. The correlation of prostate cancer incidence with aging suggests that the disease burden associated with prostate carcinoma will increase dramatically over the next several decades. Despite the large number of fatalities directly linked to prostate cancer, most men harboring the disease will die of other causes. This fact poses substantial dilemmas for screening programs designed to diagnose cancers at an early stage, as the optimal approach also would provide guidance as to which cancers could or should be observed, versus those malignancies that require curative therapy, and whether localized treatments are sufficient or if additional systemic interventions are indicated. To address these issues, substantial resources have been focused on the identification of biomarkers capable of specifically and sensitively diagnosing prostate cancers and providing prognostic information. However, the discovery and use of biomarkers must contend with the complexity and heterogeneity of body fluids and tissues. This review describes approaches that use cell type-specific analysis methods to identify cancer-associated features with the potential of distinguishing individuals with cancer of the prostate.

A noncoding RNA is a potential marker of cell fate during mammary gland development

PINC is a large, alternatively spliced, developmentally regulated, noncoding RNA expressed in the regressed terminal ductal lobular unit-like structures of the parous mammary gland. Previous studies have shown that this population of cells possesses not only progenitor-like qualities (the ability to proliferate and repopulate a mammary gland) and the ability to survive developmentally programmed cell death but also the inhibition of carcinogen-induced proliferation. Here we report that PINC expression is temporally and spatially regulated in response to developmental stimuli in vivo and that PINC RNA is localized to distinct foci in either the nucleus or the cytoplasm in a cell-cycle-specific manner. Loss-of-function experiments suggest that PINC performs dual roles in cell survival and regulation of cell-cycle progression, suggesting that PINC may contribute to the developmentally mediated changes previously observed in the terminal ductal lobular unit-like structures of the parous gland. This is one of the first reports describing the functional properties of a large, developmentally regulated, mammalian, noncoding RNA.

A mouse atlas of gene expression: large-scale digital gene-expression profiles from precisely defined developing C57BL/6J mouse tissues and cells

We analyzed 8.55 million LongSAGE tags generated from 72 libraries. Each LongSAGE library was prepared from a different mouse tissue. Analysis of the data revealed extensive overlap with existing gene data sets and evidence for the existence of approximately 24,000 previously undescribed genomic loci. The visual cortex, pancreas, mammary gland, preimplantation embryo, and placenta contain the largest number of differentially expressed transcripts, 25% of which are previously undescribed loci.

Experimental validation of the regulated expression of large numbers of non-coding RNAs from the mouse genome

Recent large-scale analyses of mainly full-length cDNA libraries generated from a variety of mouse tissues indicated that almost half of all representative cloned sequences did not contain an apparent protein-coding sequence, and were putatively derived from non-protein-coding RNA (ncRNA) genes. However, many of these clones were singletons and the majority were unspliced, raising the possibility that they may be derived from genomic DNA or unprocessed pre-mRNA contamination during library construction, or alternatively represent nonspecific "transcriptional noise." Here we show, using reverse transcriptase-dependent PCR, microarray, and Northern blot analyses, that many of these clones were derived from genuine transcripts of unknown function whose expression appears to be regulated. The ncRNA transcripts have larger exons and fewer introns than protein-coding transcripts. Analysis of the genomic landscape around these sequences indicates that some cDNA clones were produced not from terminal poly(A) tracts but internal priming sites within longer transcripts, only a minority of which is encompassed by known genes. A significant proportion of these transcripts exhibit tissue-specific expression patterns, as well as dynamic changes in their expression in macrophages following lipopolysaccharide stimulation. Taken together, the data provide strong support for the conclusion that ncRNAs are an important, regulated component of the mammalian transcriptome.

SayaMatcher: Genome scale organization and systematic analysis of nuclear receptor response elements

The availability of genome sequences enables us to make experiments in silico to find biological features encoded in the genome. In order to study gene expression regulation network by nuclear receptors that function as ligand-activated transcription, nuclear receptor response elements (NREs) in genomes were computationally explored by integration of computational prediction and experimental data. Dealing with expansion of available genome sequences and continuous update of these genomic sequences, the computation needed for these searches is organized to form a 'pipeline', called SayaMatcher. The information of genomic position for those NREs is served using the Distributed Annotation System (DAS) to be shown in Ensembl genome browser. Utilizing the SayaMatcher system, binding activity in vivo was studied for androgen response elements in human.

Gene expression profiling of jejunal Peyer’s patches in juvenile and adult pigs

Peyer's patches are organized lymphoid tissues of the small intestine that play a critical role in disease resistance and oral tolerance. Peyer's patches in the jejunum contain lymphocytes, dendritic cells, macrophages, villous epithelium, and specialized follicle-associated epithelium. Little is known about the mechanisms and processes by which cells of the Peyer's patches discriminate food nutrients and commensal microflora from pathogenic microbiota. We hypothesize that the jejunal Peyer's patches express genes that mediate and regulate its essential functions. Expression patterns of approximately 2600 cDNAs from a porcine Peyer's patch subtracted library were examined by microarray profiling. Individual mRNAs of interest were further examined by quantitative RT-PCR. Innate immunity-associated genes, including complement 3 and lysozyme, and the genes for epithelial chloride channel and trappin 1 were highly expressed by jejunal Peyer's patch in both juvenile and adult pigs. The growth- and apoptosis-associated genes CIDE-B, GW112, and PSP/Reg I (pancreatic stone protein or regenerating gene) were differentially expressed in juvenile pig Peyer's patches. Many sequences which were highly expressed in jejunal Peyer's patches have previously been described with functions in epithelial cells. Animal-to-animal variation in basal jejunal Peyer's patch gene expression was considerable and reflects the dynamic physiological environment of the gut in addition to genetic, epigenetic, and microbiological variation in the small intestine.

A systematic search for new mammalian noncoding RNAs indicates little conserved intergenic transcription

Background

Systematic identification and functional characterization of novel types of noncoding (nc)RNA in genomes is more difficult than it is for protein coding mRNAs, since ncRNAs typically do not possess sequence features such as splicing or translation signals, or long open reading frames. Recent "tiling" microarray studies have reported that a surprisingly larger proportion of mammalian genomes is transcribed than was previously anticipated. However, these non-genic transcripts often appear to be low in abundance, and their functional significance is not known.

Results

To systematically search for functional ncRNAs, we designed microarrays to detect 3,478 intergenic and intronic sequences that are conserved between the human, mouse, and rat genomes, and that score highly by other criteria that characterize ncRNAs. We probed these arrays with total RNA isolated from 16 wild-type mouse tissues. Among 55 candidates for highly-expressed novel ncRNAs tested by northern blotting, eight were confirmed as small, highly-and ubiquitously-expressed RNAs in mouse. Of the eight, five were also detected in rat tissues, but none were detected at appreciable levels in human tissues or cultured cells.

Conclusion

Since the sequence and expression of most known coding transcripts and functional ncRNAs is conserved between human and mouse, the lack of northern-detectable expression in human cells and tissues of the novel mouse and rat ncRNAs that we identified suggests that they are not functional or possibly have rodent-specific functions. Our results confirm that relatively little of the intergenic sequence conserved between human, mouse and rat is transcribed at high levels in mammalian tissues, possibly suggesting a limited role for transcribed intergenic and intronic sequences as independent functional elements.

The study of metabolic pathways in tumors based on the transcriptome

DNA microarray technology revolutionized gene-expression analysis in molecular biology to observe patterns of gene expression in genomic scale. We review the biological aspects of genome-wide gene-expression activity in tumors specially focusing on the analysis of enzyme coding genes. First, the methods for analyzing gene-expression data for the study of metabolome in silico are discussed showing SV40T antigen expressing liver tumor data as an example. Next, an application for tumor metabolome analysis utilizing a reference set of gene-expression profiles is shown.

Transcriptional Maps of 10 Human Chromosomes at 5-Nucleotide Resolution

Sites of transcription of polyadenylated and nonpolyadenylated RNAs for 10 human chromosomes were mapped at 5-base pair resolution in eight cell lines. Unannotated, nonpolyadenylated transcripts comprise the major proportion of the transcriptional output of the human genome. Of all transcribed sequences, 19.4, 43.7, and 36.9% were observed to be polyadenylated, nonpolyadenylated, and bimorphic, respectively. Half of all transcribed sequences are found only in the nucleus and for the most part are unannotated. Overall, the transcribed portions of the human genome are predominantly composed of interlaced networks of both poly A+ and poly A- annotated transcripts and unannotated transcripts of unknown function. This organization has important implications for interpreting genotype-phenotype associations, regulation of gene expression, and the definition of a gene.

Assessment of a systematic expression profiling approach in ENU-induced mouse mutant lines

Comparative genomewide expression profiling is a powerful tool in the effort to annotate the mouse genome with biological function. The systematic analysis of RNA expression data of mouse lines from the Munich ENU mutagenesis screen might support the understanding of the molecular biology of such mutants and provide new insights into mammalian gene function. In a direct comparison of DNA microarray experiments of individual versus pooled RNA samples of organs from ENU-induced mouse mutants, we provide evidence that individual RNA samples may outperform pools in some aspects. Genes with high biological variability in their expression levels (noisy genes) are identified as false positives in pooled samples. Evidence suggests that highly stringent housing conditions and standardized procedures for the isolation of organs significantly reduce biological variability in gene expression profiling experiments. Data on wild-type individuals demonstrate the positive effect of controlling variables such as social status, food intake before organ sampling, and stress with regard to reproducibility of gene expression patterns. Analyses of several organs from various ENU-induced mutant lines in general show low numbers of differentially expressed genes. We demonstrate the feasibility to detect transcriptionally affected organs employing RNA expression profiling as a tool for molecular phenotyping.

Development of a spot reliability evaluation score for DNA microarrays

We developed a reliability index named SRED (Spot Reliability Evaluation Score for DNA microarrays) that represents the probability that the calibrated gene expression level from a DNA microarray would be less than a factor of 2 different from that of quantitative real-time polymerase chain reaction assays whose dynamic quantification range is treated statistically to be similar to that of the DNA microarray. To define the SRED score, two parameters, the reproducibility of measurement value and the relative expression value were selected from nine candidate parameters. The SRED score supplies the probability that the expression level in each spot of a microarray is less than a certain-fold different compared to other expression profiling data, such as QRT-PCR. This score was applied to approximately 1,500,000 points of the expression profile in the RIKEN Expression Array Database.

Global gene expression profiling and cluster analysis in Xenopus laevis

We have undertaken a large-scale microarray gene expression analysis using cDNAs corresponding to 21,000 Xenopus laevis ESTs. mRNAs from 37 samples, including embryos and adult organs, were profiled. Cluster analysis of embryos of different stages was carried out and revealed expected affinities between gastrulae and neurulae, as well as between advanced neurulae and tadpoles, while egg and feeding larvae were clearly separated. Cluster analysis of adult organs showed some unexpected tissue-relatedness, e.g. kidney is more related to endodermal than to mesodermal tissues and the brain is separated from other neuroectodermal derivatives. Cluster analysis of genes revealed major phases of co-ordinate gene expression between egg and adult stages. During the maternal-early embryonic phase, genes maintaining a rapidly dividing cell state are predominantly expressed (cell cycle regulators, chromatin proteins). Genes involved in protein biosynthesis are progressively induced from mid-embryogenesis onwards. The larval-adult phase is characterised by expression of genes involved in metabolism and terminal differentiation. Thirteen potential synexpression groups were identified, which encompass components of diverse molecular processes or supra-molecular structures, including chromatin, RNA processing and nucleolar function, cell cycle, respiratory chain/Krebs cycle, protein biosynthesis, endoplasmic reticulum, vesicle transport, synaptic vesicle, microtubule, intermediate filament, epithelial proteins and collagen. Data filtering identified genes with potential stage-, region- and organ-specific expression. The dataset was assembled in the iChip microarray database, , which allows user-defined queries. The study provides insights into the higher order of vertebrate gene expression, identifies synexpression groups and marker genes, and makes predictions for the biological role of numerous uncharacterized genes.

Robustness of metabolic map reconstruction

With the ever increasing amount of genomic data available, the interest for generating biochemical pathways has grown tremendously. So far, mainly complete genomes have been used to reconstruct the biochemical pathways and their associated interactions. However, a large number of low coverage genomes, as well as other sources of partial genomic data, are currently available for many organisms. In order to be able to use incomplete data for metabolic reconstruction, the inherent properties of this procedure need to be investigated. In this short note, we describe the robustness and predictive power of metabolic reconstructions using partial information from Schizosaccharomyces pombe. We also discuss the implications of the results on reference genome projects as well as other large-scale sequencing data.

Ontogeny of transcription profiles during mouse early craniofacial development

Using the CD-1 mouse conceptus, we investigated gene expression changes found in vivo from gestational day 8 (GD) through GD9 at 6 h intervals, and then at 24 h intervals through GD11. Data sets were analyzed for patterns in transcriptional expression over a time course as well as to compare the GD9 in vivo mouse conceptus with conceptuses cultured for 24 h from GD8 in whole embryo culture (WEC). Our results show that during development from GD8 to GD11, a series of metabolic pathways related to carbohydrate metabolism and energy production, as well as the signal transduction pathways of the MAPK cascade and Wnt signaling were changing. Previous results have shown that WEC successfully sustains morphological development comparable to that in vivo for at least 24 h. We report here that, in the absence of morphological malformations following 24 h WEC, 329 genes were differentially expressed between in vivo and in vitro developing conceptuses.

Co-regulation of mouse genes predicts function

Large-scale microarray analyses reveal that transcriptional co-regulation patterns can be remarkably helpful in predicting the function of novel mouse genes.

The functional landscape of mouse gene expression

BACKGROUND

Large-scale quantitative analysis of transcriptional co-expression has been used to dissect regulatory networks and to predict the functions of new genes discovered by genome sequencing in model organisms such as yeast. Although the idea that tissue-specific expression is indicative of gene function in mammals is widely accepted, it has not been objectively tested nor compared with the related but distinct strategy of correlating gene co-expression as a means to predict gene function.

RESULTS

We generated microarray expression data for nearly 40,000 known and predicted mRNAs in 55 mouse tissues, using custom-built oligonucleotide arrays. We show that quantitative transcriptional co-expression is a powerful predictor of gene function. Hundreds of functional categories, as defined by Gene Ontology 'Biological Processes', are associated with characteristic expression patterns across all tissues, including categories that bear no overt relationship to the tissue of origin. In contrast, simple tissue-specific restriction of expression is a poor predictor of which genes are in which functional categories. As an example, the highly conserved mouse gene PWP1 is widely expressed across different tissues but is co-expressed with many RNA-processing genes; we show that the uncharacterized yeast homolog of PWP1 is required for rRNA biogenesis.

CONCLUSIONS

We conclude that 'functional genomics' strategies based on quantitative transcriptional co-expression will be as fruitful in mammals as they have been in simpler organisms, and that transcriptional control of mammalian physiology is more modular than is generally appreciated. Our data and analyses provide a public resource for mammalian functional genomics.

A General Survey of Thymocyte Differentiation by Transcriptional Analysis of Knockout Mouse Models

The thymus is the primary site of T cell lymphopoiesis. To undergo proper differentiation, developing T cells follow a well-ordered genetic program that strictly depends on the heterogeneous and highly specialized thymic microenvironment. In this study, we used microarray technology to extensively describe transcriptional events regulating alphabeta T cell fate. To get an integrated view of these processes, both whole thymi from genetically engineered mice together with purified thymocytes were analyzed. Using mice exhibiting various transcriptional perturbations and developmental blockades, we performed a transcriptional microdissection of the organ. Multiple signatures covering both cortical and medullary stroma as well as various thymocyte maturation intermediates were clearly defined. Beyond the definition of histological and functional signatures (proliferation, rearrangement), we provide the first evidence that such an approach may also highlight the complex cross-talk events that occur between maturing T cells and stroma. Our data constitute a useful integrated resource describing the main gene networks set up during thymocyte development and a first step toward a more systematic transcriptional analysis of genetically modified mice.

Optical projection tomography

Optical projection tomography is a new approach for three-dimensional (3-D) imaging of small biological specimens. It fills an imaging gap between MRI and confocal microscopy, being most suited to specimens that are from 1 to 10 mm across. The tomographic principles of optical projection tomography (OPT) are explained, its most important applications in biomedical research explored, and comparisons drawn of its pros and cons compared to a number of alternative imaging technologies.

Identification of mammalian microRNA host genes and transcription units

To derive a global perspective on the transcription of microRNAs (miRNAs) in mammals, we annotated the genomic position and context of this class of noncoding RNAs (ncRNAs) in the human and mouse genomes. Of the 232 known mammalian miRNAs, we found that 161 overlap with 123 defined transcription units (TUs). We identified miRNAs within introns of 90 protein-coding genes with a broad spectrum of molecular functions, and in both introns and exons of 66 mRNA-like noncoding RNAs (mlncRNAs). In addition, novel families of miRNAs based on host gene identity were identified. The transcription patterns of all miRNA host genes were curated from a variety of sources illustrating spatial, temporal, and physiological regulation of miRNA expression. These findings strongly suggest that miRNAs are transcribed in parallel with their host transcripts, and that the two different transcription classes of miRNAs ('exonic' and 'intronic') identified here may require slightly different mechanisms of biogenesis.