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  • Review Article
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Genomic strategies to identify mammalian regulatory sequences

Nature Reviews Genetics volume 2, pages 100–109 (2001)Cite this article

Key Points

  • Computational tools for the analysis of genomic DNA are good at identifying coding sequences, but poor at identifying regulatory sequences.

  • Comparative genomic sequence analysis is a powerful approach for identifying conserved non-coding regions. Many such conserved regions have been shown to be involved in gene regulation.

  • A second approach to identify regulatory regions is to look for sequence motifs known to bind to transcription factors. A number of databases have compiled information on these motifs.

  • A third approach is to use expression profiling to identify regulatory sequences. Co-regulated genes are identified by cluster analysis and their upstream regions are searched for common motifs. This method has been applied most successfully in yeast.

  • These approaches can be combined to yield a powerful strategy for identifying novel regulatory elements, and for decoding the non-coding portion of mammalian genomes.

Abstract

With the continuing accomplishments of the human genome project, high-throughput strategies to identify DNA sequences that are important in mammalian gene regulation are becoming increasingly feasible. In contrast to the historic, labour-intensive, wet-laboratory methods for identifying regulatory sequences, many modern approaches are heavily focused on the computational analysis of large genomic data sets. Data from inter-species genomic sequence comparisons and genome-wide expression profiling, integrated with various computational tools, are poised to contribute to the decoding of genomic sequence and to the identification of those sequences that orchestrate gene regulation. In this review, we highlight several genomic approaches that are being used to identify regulatory sequences in mammalian genomes.

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Figure 1: Classification of conserved human–mouse sequences.
Figure 2: Identifying transcription-factor-binding sites.
Figure 3: TRANSFAC and position-weighted matrices.
Figure 4: Combining expression data and sequence conservation.
Figure 5: Annotating the genome.

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Acknowledgements

This research was supported by a Programs for Genomic Applications grant awarded to E.M.R. from the NHLBI and conducted at the E.O. Lawrence Berkeley National Laboratory, University of California, sponsored by the Department of Energy, as well as an appointment to the Alexander Hollaender Distinguished Postdoctoral Fellowship Program sponsored by the US Department of Energy, Office of Biological and Environmental Research, and administered by the Oak Ridge Institute for Science and Education (L.A.P.). We thank M. Biggin, J. Bristow, I. Dubchak, C. Prangeand D. Symula for their thoughtful comments.

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Authors and Affiliations

  1. Genome Sciences Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, 94720, California, USA

    Len A. Pennacchio & Edward M. Rubin

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  1. Len A. Pennacchio
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Related links

Related links

DATABASE LINKS

LPA

GMCSF

IL4

IL13

IL5

SCL

FURTHER INFORMATION

TRANSFAC

Transcription Regulatory Region Database

COMPEL

Eukaryotic Promoter Database

VISTA

PipMaker

hepatic nuclear factor 4 (HNF4) position-weighted matrix

Glossary

DNASEI HYPERSENSITIVITY ASSAY

Identifies regions of the genome that lack nucleosome structure and are therefore readily degraded by the enzyme DNaseI. Such regions tend to be associated with transcriptional activity.

DNA FOOTPRINTING ASSAY

An assay that identifies a region of DNA that is protected from digestion by DNaseI (usually due to the binding of a protein, such as a transcription factor).

GEL SHIFT ASSAY

A gel-based assay in which proteins that bind to a DNA fragment are detected by virtue of the reduced migration of the DNA. The assay is often used to detect transcription factor binding.

CRE RECOMBINASE SYSTEM

A method in which the Cre enzyme catalyses recombination between loxP sequences. If the loxP sequences are arranged as a direct repeat, recombination will delete the DNA between the sites.

CPG ISLANDS

Sequences of at least 200 bp with greater than 50% G+C content and high CpG frequency.

FLAT FILE

A computer readable file or database in which records are not connected or 'related'. Similar to a card index.

RELATIONAL DATABASE

A storage format in which data items can be stored in separate files but linked together to form different relations. This system allows greater flexibility than a flat file format.

MLUI CELL-CYCLE BOX

An 8-bp motif (ACGCGTNA) that promotes the transcription of genes involved in DNA replication in yeast.

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Pennacchio, L., Rubin, E. Genomic strategies to identify mammalian regulatory sequences. Nat Rev Genet 2, 100–109 (2001). https://doi.org/10.1038/35052548

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