Genomic strategies to identify mammalian regulatory sequences

Initial sequencing and comparative analysis of the mouse genome

The sequence of the mouse genome is a key informational tool for understanding the contents of the human genome and a key experimental tool for biomedical research. Here, we report the results of an international collaboration to produce a high-quality draft sequence of the mouse genome. We also present an initial comparative analysis of the mouse and human genomes, describing some of the insights that can be gleaned from the two sequences. We discuss topics including the analysis of the evolutionary forces shaping the size, structure and sequence of the genomes; the conservation of large-scale synteny across most of the genomes; the much lower extent of sequence orthology covering less than half of the genomes; the proportions of the genomes under selection; the number of protein-coding genes; the expansion of gene families related to reproduction and immunity; the evolution of proteins; and the identification of intraspecies polymorphism.

What can cardiovascular gene transfer learn from genomics: and vice versa?

The field of gene transfer has developed in an era of expanding biomedical knowledge. The potential for gene transfer to treat cardiovascular disease is great, yet identified and unidentified barriers remain. Gene transfer and its ultimate application, gene therapy, require extensive details of not only the mechanism of disease but the biological implications of the vectors used to deliver the therapeutic genes as well. Many of these details are becoming available via the study of genomics. Genomics, the study of complete genetic sequences, holds the potential for enabling and amplifying the therapeutic hopes for gene transfer. Identification of new therapeutic genes, new regulatory sequences, and establishing the patterns of gene expression from tissues exposed to vectors and transgenes will rapidly advance the application of gene transfer. Finally, there are historical and ongoing lessons learned from the development of gene transfer that may be applicable to the challenging field of genomics and may enable its future success.

Exploring genetic regulatory networks in metazoan development: methods and models

One of the foremost challenges of 21st century biological research will be to decipher the complex genetic regulatory networks responsible for embryonic development. The recent explosion of whole genome sequence data and of genome-wide transcriptional profiling methods, such as microarrays, coupled with the development of sophisticated computational tools for exploiting and analyzing genomic data, provide a significant starting point for regulatory network analysis. In this article we review some of the main methodological issues surrounding genome annotation, transcriptional profiling, and computational prediction of cis-regulatory elements and discuss how the power of model genetic organisms can be used to experimentally verify and extend the results of genomic research.

Deterministic mutation rate variation in the human genome

Several studies of substitution rate variation have indicated that the local mutation rate varies over the mammalian genome. In the present study, we show significant variation in substitution rates within the noncoding part of the human genome using 4.7 Mb of human-chimpanzee pairwise comparisons. Moreover, we find a significant positive covariation of lineage-specific chimpanzee and human local substitution rates, and very similar mean substitution rates down the two lineages. The substitution rate variation is probably not caused by selection or biased gene conversion, and so we conclude that mutation rates vary deterministically across the noncoding nonrepetitive regions of the human genome. We also show that noncoding substitution rates are significantly affected by G+C base composition, partly because the base composition is not at equilibrium.

Computational prediction of eukaryotic protein-coding genes

The human genome sequence is the book of our life. Buried in this large volume are our genes, which are scattered as small DNA fragments throughout the genome and comprise a small percentage of the total text. Finding these indistinct 'needles' in a vast genomic 'haystack' can be extremely challenging. In response to this challenge, computational prediction approaches have proliferated in recent years that predict the location and structure of genes. Here, I discuss these approaches and explain why they have become essential for the analyses of newly sequenced genomes.

Parallel construction of orthologous sequence-ready clone contig maps in multiple species

Comparison is a fundamental tool for analyzing DNA sequence. Interspecies sequence comparison is particularly powerful for inferring genome function and is based on the simple premise that conserved sequences are likely to be important. Thus, the comparison of a genomic sequence with its orthologous counterpart from another species is increasingly becoming an integral component of genome analysis. In ideal situations, such comparisons are performed with orthologous sequences from multiple species. To facilitate multispecies comparative sequence analysis, a robust and scalable strategy for simultaneously constructing sequence-ready bacterial artificial chromosome (BAC) contig maps from targeted genomic regions has been developed. Central to this approach is the generation and utilization of "universal" oligonucleotide-based hybridization probes ("overgo" probes), which are designed from sequences that are highly conserved between distantly related species. Large collections of these probes are used en masse to screen BAC libraries from multiple species in parallel, with the isolated clones assembled into physical contig maps. To validate the effectiveness of this strategy, efforts were focused on the construction of BAC-based physical maps from multiple mammalian species (chimpanzee, baboon, cat, dog, cow, and pig). Using available human and mouse genomic sequence and a newly developed computer program to design the requisite probes, sequence-ready maps were constructed in all species for a series of targeted regions totaling approximately 16 Mb in the human genome. The described approach can be used to facilitate the multispecies comparative sequencing of targeted genomic regions and can be adapted for constructing BAC contig maps in other vertebrates.

A computerized database-scan to identify c-MYC targets

The c-MYC oncogene plays a pivotal role in the malignant transformation of various types of human cancer. It is also a key regulator of cellular proliferation, embryonic differentiation and apoptosis. c-MYC encodes a transcription factor that activates target genes in a sequence specific manner through heterodimerization with the ubiquitously expressed factor MAX. Identifying c-MYC target genes is therefore crucial for elucidating the molecular pathways that are downstream of MYC. Most of the c-MYC targets isolated to date as well as targets of other transcription factors have been identified by differential expression or the candidate gene approach. In this paper, we outline a computer-based scan that allows us to create a pool of putative target genes for a transcription factor. The scan is based on a set of criteria including sequence specificity of the c-MYC transcription factor, sequence location and evolutionary conservation of these regulatory elements. Using this procedure, we have identified 12 putative targets for c-MYC. Expression analyses, DNA binding assays and chimeric promoter-reporter experiments suggest that two genes, NM23-H2 and N-RAS, may indeed be direct targets for c-MYC activation. This type of computer-based scan may have a general use to identify targets for other transcription factors.

Hormonal genomics

The availability of the human genomic sequence is changing the way in which biological questions are addressed. Based on the prediction of genes from nucleotide sequences, homologies among their encoded amino acids can be analyzed and used to place them in distinct families. This serves as a first step in building hypotheses for testing the structural and functional properties of previously uncharacterized paralogous genes. As genomic information from more organisms becomes available, these hypotheses can be refined through comparative genomics and phylogenetic studies. Instead of the traditional single-gene approach in endocrine research, we are beginning to gain an understanding of entire mammalian genomes, thus providing the basis to reveal subfamilies and pathways for genes involved in ligand signaling. The present review provides selective examples of postgenomic approaches in the analysis of novel genes involved in hormonal signaling and their chromosomal locations, polymorphisms, splicing variants, differential expression, and physiological function. In the postgenomic era, scientists will be able to move from a gene-by-gene approach to a reconstructionistic one by reading the encyclopedia of life from a global perspective. Eventually, a community-based approach will yield new insights into the complexity of intercellular communications, thereby offering us an understanding of hormonal physiology and pathophysiology.

Comparative sequence analysis of the X-inactivation center region in mouse, human, and bovine

We have sequenced to high levels of accuracy 714-kb and 233-kb regions of the mouse and bovine X-inactivation centers (Xic), respectively, centered on the Xist gene. This has provided the basis for a fully annotated comparative analysis of the mouse Xic with the 2.3-Mb orthologous region in human and has allowed a three-way species comparison of the core central region, including the Xist gene. These comparisons have revealed conserved genes, both coding and noncoding, conserved CpG islands and, more surprisingly, conserved pseudogenes. The distribution of repeated elements, especially LINE repeats, in the mouse Xic region when compared to the rest of the genome does not support the hypothesis of a role for these repeat elements in the spreading of X inactivation. Interestingly, an asymmetric distribution of LINE elements on the two DNA strands was observed in the three species, not only within introns but also in intergenic regions. This feature is suggestive of important transcriptional activity within these intergenic regions. In silico prediction followed by experimental analysis has allowed four new genes, Cnbp2, Ftx, Jpx, and Ppnx, to be identified and novel, widespread, complex, and apparently noncoding transcriptional activity to be characterized in a region 5' of Xist that was recently shown to attract histone modification early after the onset of X inactivation.

Identification of a novel cis-regulatory element involved in the heat shock response in Caenorhabditis elegans using microarray gene expression and computational methods

We report here the identification of a previously unknown transcription regulatory element for heat shock (HS) genes in Caenorhabditis elegans. We monitored the expression pattern of 11,917 genes from C. elegans to determine the genes that were up-regulated on HS. Twenty eight genes were observed to be consistently up-regulated in several different repetitions of the experiments. We analyzed the upstream regions of these genes using computational DNA pattern recognition methods. Two potential cis-regulatory motifs were identified in this way. One of these motifs (TTCTAGAA) was the DNA binding motif for the heat shock factor (HSF), whereas the other (GGGTGTC) was previously unreported in the literature. We determined the significance of these motifs for the HS genes using different statistical tests and parameters. Comparative sequence analysis of orthologous HS genes from C. elegans and Caenorhabditis briggsae indicated that the identified DNA regulatory motifs are conserved across related species. The role of the identified DNA sites in regulation of HS genes was tested by in vitro mutagenesis of a green fluorescent protein (GFP) reporter transgene driven by the C. elegans hsp-16-2 promoter. DNA sites corresponding to both motifs are shown to play a significant role in up-regulation of the hsp-16-2 gene on HS. This is one of the rare instances in which a novel regulatory element, identified using computational methods, is shown to be biologically active. The contributions of individual sites toward induction of transcription on HS are nonadditive, which indicates interaction and cross-talk between the sites, possibly through the transcription factors (TFs) binding to these sites.

Comparative genomics approaches to study organism similarities and differences

Comparative genomics is a large-scale, holistic approach that compares two or more genomes to discover the similarities and differences between the genomes and to study the biology of the individual genomes. Comparative studies can be performed at different levels of the genomes to obtain multiple perspectives about the organisms. We discuss in detail the type of analyses that offer significant biological insights in the comparisons of (1) genome structure including overall genome statistics, repeats, genome rearrangement at both DNA and gene level, synteny, and breakpoints; (2) coding regions including gene content, protein content, orthologs, and paralogs; and (3) noncoding regions including the prediction of regulatory elements. We also briefly review the currently available computational tools in comparative genomics such as algorithms for genome-scale sequence alignment, gene identification, and nonhomology-based function prediction.

The muscular dystrophies

The muscular dystrophies are inherited myogenic disorders characterised by progressive muscle wasting and weakness of variable distribution and severity. They can be subdivided into several groups, including congenital forms, in accordance with the distribution of predominant muscle weakness: Duchenne and Becker; Emery-Dreifuss; distal; facioscapulohumeral; oculopharyngeal; and limb-girdle which is the most heterogeneous group. In several dystrophies the heart can be seriously affected, sometimes in the absence of clinically significant weakness. The genes and their protein products that cause most of these disorders have now been identified. This information is essential to establish an accurate diagnosis and for reliable genetic counselling and prenatal diagnosis. There is, as yet, no way of greatly affecting the long-term course of any of these diseases. However, advances in gene manipulation and stem-cell therapy suggest cautious optimism for finding an effective treatment in the not-too-distant future.

Vertebrate genome sequencing: building a backbone for comparative genomics

The human genome sequence provides a reference point from which we can compare ourselves with other organisms. Interspecies comparison is a powerful tool for inferring function from genomic sequence and could ultimately lead to the discovery of what makes humans unique. To date, most comparative sequencing has focused on pair-wise comparisons between human and a limited number of other vertebrates, such as mouse. Targeted approaches now exist for mapping and sequencing vertebrate bacterial artificial chromosomes (BACs) from numerous species, allowing rapid and detailed molecular and phylogenetic investigation of multi-megabase loci. Such targeted sequencing is complementary to current whole-genome sequencing projects, and would benefit greatly from the creation of BAC libraries from a diverse range of vertebrates.

The mouse: genetics meets behaviour

Genetic studies in the mouse are important in the elucidation of molecular pathways that underlie behaviour. The advantages of the mouse for behavioural studies include an extensive array of genetic technologies and an elaborate behavioural repertoire that can be used to create models of human disease. This review discusses the relative advantages of forward and reverse genetic approaches to studying the genetic basis of behaviour in the mouse, and the complexities that behavioural studies need to address, such as phenotypic variability, genetic background effects and pleiotropy.

Exploiting transcription factor binding site clustering to identify cis-regulatory modules involved in pattern formation in the Drosophila genome

A major challenge in interpreting genome sequences is understanding how the genome encodes the information that specifies when and where a gene will be expressed. The first step in this process is the identification of regions of the genome that contain regulatory information. In higher eukaryotes, this cis-regulatory information is organized into modular units [cis-regulatory modules (CRMs)] of a few hundred base pairs. A common feature of these cis-regulatory modules is the presence of multiple binding sites for multiple transcription factors. Here, we evaluate the extent to which the tendency for transcription factor binding sites to be clustered can be used as the basis for the computational identification of cis-regulatory modules. By using published DNA binding specificity data for five transcription factors active in the early Drosophila embryo, we identified genomic regions containing unusually high concentrations of predicted binding sites for these factors. A significant fraction of these binding site clusters overlap known CRMs that are regulated by these factors. In addition, many of the remaining clusters are adjacent to genes expressed in a pattern characteristic of genes regulated by these factors. We tested one of the newly identified clusters, mapping upstream of the gap gene giant (gt), and show that it acts as an enhancer that recapitulates the posterior expression pattern of gt.

Functional genomics approaches to understanding brain disorders

The completed draft of the human genome sequence has facilitated a revolution in neuroscience research. This sequence information and the development of new technologies used to analyze gene expression on a genomic scale provides a new and powerful means to investigate brain disorders of unknown etiology and to isolate novel drug targets for these disorders. The term functional genomics broadly describes a set of technologies and strategies directed at the problem of determining the function of genes, and understanding how the genome works together to generate whole patterns of biological function. The most powerful of these functional genomics approaches, expression profiling or DNA microarrays, can be used to analyze the expression of thousands of genes simultaneously. The results to date from the application of DNA microarray methods to postmortem diseased human brain tissue, animal models and cell culture models of brain disorders provide an exciting glimpse into the future of this field.

Generation and comparative analysis of approximately 3.3 Mb of mouse genomic sequence orthologous to the region of human chromosome 7q11.23 implicated in Williams syndrome

Williams syndrome is a complex developmental disorder that results from the heterozygous deletion of a approximately 1.6-Mb segment of human chromosome 7q11.23. These deletions are mediated by large (approximately 300 kb) duplicated blocks of DNA of near-identical sequence. Previously, we showed that the orthologous region of the mouse genome is devoid of such duplicated segments. Here, we extend our studies to include the generation of approximately 3.3 Mb of genomic sequence from the mouse Williams syndrome region, of which just over 1.4 Mb is finished to high accuracy. Comparative analyses of the mouse and human sequences within and immediately flanking the interval commonly deleted in Williams syndrome have facilitated the identification of nine previously unreported genes, provided detailed sequence-based information regarding 30 genes residing in the region, and revealed a number of potentially interesting conserved noncoding sequences. Finally, to facilitate comparative sequence analysis, we implemented several enhancements to the program, including the addition of links from annotated features within a generated percent-identity plot to specific records in public databases. Taken together, the results reported here provide an important comparative sequence resource that should catalyze additional studies of Williams syndrome, including those that aim to characterize genes within the commonly deleted interval and to develop mouse models of the disorder.

Association between divergence and interspersed repeats in mammalian noncoding genomic DNA

The amount of noncoding genomic DNA sequence that aligns between human and mouse varies substantially in different regions of their genomes, and the amount of repetitive DNA also varies. In this report, we show that divergence in noncoding nonrepetitive DNA is strongly correlated with the amount of repetitive DNA in a region. We investigated aligned DNA in four large genomic regions with finished human sequence and almost or completely finished mouse sequence. These regions, totaling 5.89 Mb of DNA, are on different chromosomes and vary in their base composition. An analysis based on sliding windows of 10 kb shows that the fraction of aligned noncoding nonrepetitive DNA and the fraction of repetitive DNA are negatively correlated, both at the level of an entire region and locally within it. This conclusion is strongly supported by a randomization study, in which repetitive elements are removed and randomly relocated along the sequences. Thus, regions of noncoding genomic DNA that accumulated fewer point mutations since the primate-rodent divergence also suffered fewer retrotransposition events. These results indicate that some regions of the genome are more "flexible" over the time scale of mammalian evolution, being able to accommodate many point mutations and insertions, whereas other regions are more "rigid" and accumulate fewer changes. Stronger conservation is generally interpreted as indicating more extensive or more important function. The evidence presented here of correlated variation in the rates of different evolutionary processes across noncoding DNA must be considered in assessing such conservation for evidence of selection.

Regulatory sequence analysis: application to the interpretation of gene expression

Microarray technologies for measuring mRNA abundances in cells allow monitoring of gene expression levels for tens of thousands of genes in parallel. By measuring expression responses across hundreds of different conditions or timepoints a relatively detailed gene expression map starts to emerge. Using cluster analysis techniques, it is possible to identify genes that are consistently coexpressed under several different conditions or treatments. These sets of coexpressed genes can then be compared to existing knowledge about biochemical or signalling pathways, the function of unknown genes can be hypothesised by comparing them to other genes with characterised function, or from trends in expression profiles in general - why cell needs to transcribe or silence the genes during particular treatment. The regulation of genes on the DNA level is largely guided by particular sequence features, the transcription factor binding sites, and other signals encaptured in DNA. By analyzing the regulatory regions of the DNA of the genes consistently coexpressed, we can discover the potential signals hidden in DNA by computational analysis methods. The prerequisite for this kind of analysis is the existence of genomic DNA sequence, knowledge about gene locations, and experimental gene expression measurements for a variety of conditions. This article surveys some of the analysis methods and studies for such a computational discovery approach for yeast Saccharomyces cerevisiae.

Computational identification of noncoding RNAs in E. coli by comparative genomics

Some genes produce noncoding transcripts that function directly as structural, regulatory, or even catalytic RNAs [1, 2]. Unlike protein-coding genes, which can be detected as open reading frames with distinctive statistical biases, noncoding RNA (ncRNA) gene sequences have no obvious inherent statistical biases [3]. Thus, genome sequence analyses reveal novel protein-coding genes, but any novel ncRNA genes remain invisible. Here, we describe a computational comparative genomic screen for ncRNA genes. The key idea is to distinguish conserved RNA secondary structures from a background of other conserved sequences using probabilistic models of expected mutational patterns in pairwise sequence alignments. We report the first whole-genome screen for ncRNA genes done with this method, in which we applied it to the "intergenic" spacers of Escherichia coli using comparative sequence data from four related bacteria. Starting from >23,000 conserved interspecies pairwise alignments, the screen predicted 275 candidate structural RNA loci. A sample of 49 candidate loci was assayed experimentally. At least 11 loci expressed small, apparently noncoding RNA transcripts of unknown function. Our computational approach may be used to discover structural ncRNA genes in any genome for which appropriate comparative genome sequence data are available.

Deletion of a coordinate regulator of type 2 cytokine expression in mice

Mechanisms that underlie the patterning of cytokine expression in T helper (T(H)) cell subsets remain incompletely defined. An evolutionarily conserved approximately 400-bp noncoding sequence in the intergenic region between the genes Il4 and Il13, designated conserved noncoding sequence 1 (CNS-1), was deleted in mice. The capacity to develop T(H)2 cells was compromised in vitro and in vivo in the absence of CNS-1. Despite the profound effect in T cells, mast cells from CNS-1(-/-) mice maintained their capacity to produce interleukin 4. A T cell-specific element critical for the optimal expression of type 2 cytokines may represent the evolution of a regulatory sequence exploited by adaptive immunity.

Genome annotation: from sequence to biology

The genome sequence of an organism is an information resource unlike any that biologists have previously had access to. But the value of the genome is only as good as its annotation. It is the annotation that bridges the gap from the sequence to the biology of the organism. The aim of high-quality annotation is to identify the key features of the genome - in particular, the genes and their products. The tools and resources for annotation are developing rapidly, and the scientific community is becoming increasingly reliant on this information for all aspects of biological research.