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Christopher B Burge

Publications and source records attributed to Christopher B Burge.

8 recordsLinked to original sources

Single nucleotide polymorphism-based validation of exonic splicing enhancers.

Because deleterious alleles arising from mutation are filtered by natural selection, mutations that create such alleles will be underrepresented in the set of common genetic variation existing in a population at any given time. Here, we describe an approach based on this idea called VERIFY (variant elimination reinforces functionality), which can be used to assess the extent of natural selection acting on an oligonucleotide motif or set of motifs predicted to have biological activity. As an application of this approach, we analyzed a set of 238 hexanucleotides previously predicted to have exonic splicing enhancer (ESE) activity in human exons using the relative enhancer and silencer classification by unanimous enrichment (RESCUE)-ESE method. Aligning the single nucleotide polymorphisms (SNPs) from the public human SNP database to the chimpanzee genome allowed inference of the direction of the mutations that created present-day SNPs. Analyzing the set of SNPs that overlap RESCUE-ESE hexamers, we conclude that nearly one-fifth of the mutations that disrupt predicted ESEs have been eliminated by natural selection (odds ratio = 0.82 +/- 0.05). This selection is strongest for the predicted ESEs that are located near splice sites. Our results demonstrate a novel approach for quantifying the extent of natural selection acting on candidate functional motifs and also suggest certain features of mutations/SNPs, such as proximity to the splice site and disruption or alteration of predicted ESEs, that should be useful in identifying variants that might cause a biological phenotype.

Alleles↗

The microRNAs of Caenorhabditis elegans.

MicroRNAs (miRNAs) are an abundant class of tiny RNAs thought to regulate the expression of protein-coding genes in plants and animals. In the present study, we describe a computational procedure to identify miRNA genes conserved in more than one genome. Applying this program, known as MiRscan, together with molecular identification and validation methods, we have identified most of the miRNA genes in the nematode Caenorhabditis elegans. The total number of validated miRNA genes stands at 88, with no more than 35 genes remaining to be detected or validated. These 88 miRNA genes represent 48 gene families; 46 of these families (comprising 86 of the 88 genes) are conserved in Caenorhabditis briggsae, and 22 families are conserved in humans. More than a third of the worm miRNAs, including newly identified members of the lin-4 and let-7 gene families, are differentially expressed during larval development, suggesting a role for these miRNAs in mediating larval developmental transitions. Most are present at very high steady-state levels-more than 1000 molecules per cell, with some exceeding 50,000 molecules per cell. Our census of the worm miRNAs and their expression patterns helps define this class of noncoding RNAs, lays the groundwork for functional studies, and provides the tools for more comprehensive analyses of miRNA genes in other species.

Animals↗

DNA sequence evolution with neighbor-dependent mutation.

We introduce a model of DNA sequence evolution which can account for biases in mutation rates that depend on the identity of the neighboring bases. An analytic solution for this class of models is developed by adopting well-known methods of nonlinear dynamics. Results are presented for the CpG-methylation-deamination process, which dominates point substitutions in vertebrates. The dinucleotide frequencies generated by the model (using empirically obtained mutation rates) match the overall pattern observed in noncoding DNA. A web-based tool has been constructed to compute single- and dinucleotide frequencies for arbitrary neighbor-dependent mutation rates. Also provided is the backward procedure to infer the mutation rates using maximum likelihood analysis given the observed single- and dinucleotide frequencies. Reasonable estimates of the mutation rates can be obtained very efficiently, using generic noncoding DNA sequences as input, after masking out long homonucleotide subsequences. Our method is much more convenient and versatile to use than the traditional method of deducing mutation rates by counting mutation events in carefully chosen sequences. More generally, our approach provides a more realistic but still tractable description of noncoding genomic DNA and may be used as a null model for various sequence analysis applications.

DNA↗

Widespread selection for local RNA secondary structure in coding regions of bacterial genes.

Redundancy of the genetic code dictates that a given protein can be encoded by a large collection of distinct mRNA species, potentially allowing mRNAs to simultaneously optimize desirable RNA structural features in addition to their protein-coding function. To determine whether natural mRNAs exhibit biases related to local RNA secondary structure, a new randomization procedure was developed, DicodonShuffle, which randomizes mRNA sequences while preserving the same encoded protein sequence, the same codon usage, and the same dinucleotide composition as the native message. Genes from 10 of 14 eubacterial species studied and one eukaryote, the yeast Saccharomyces cerevisiae, exhibited statistically significant biases in favor of local RNA structure as measured by folding free energy. Several significant associations suggest functional roles for mRNA structure, including stronger secondary structure bias in the coding regions of intron-containing yeast genes than in intronless genes, and significantly higher folding potential in polycistronic messages than in monocistronic messages in Escherichia coli. Potential secondary structure generally increased in genes from the 5' to the 3' end of E. coli operons, and secondary structure potential was conserved in homologous Salmonella typhi operons. These results are interpreted in terms of possible roles of RNA structures in RNA processing, regulation of mRNA stability, and translational control.

Computational Biology↗

A uniform system for microRNA annotation.

MicroRNAs (miRNAs) are small noncoding RNA gene products about 22 nt long that are processed by Dicer from precursors with a characteristic hairpin secondary structure. Guidelines are presented for the identification and annotation of new miRNAs from diverse organisms, particularly so that miRNAs can be reliably distinguished from other RNAs such as small interfering RNAs. We describe specific criteria for the experimental verification of miRNAs, and conventions for naming miRNAs and miRNA genes. Finally, an online clearinghouse for miRNA gene name assignments is provided by the Rfam database of RNA families.

MicroRNAs↗

Prediction of plant microRNA targets.

We predict regulatory targets for 14 Arabidopsis microRNAs (miRNAs) by identifying mRNAs with near complementarity. Complementary sites within predicted targets are conserved in rice. Of the 49 predicted targets, 34 are members of transcription factor gene families involved in developmental patterning or cell differentiation. The near-perfect complementarity between plant miRNAs and their targets suggests that many plant miRNAs act similarly to small interfering RNAs and direct mRNA cleavage. The targeting of developmental transcription factors suggests that many plant miRNAs function during cellular differentiation to clear key regulatory transcripts from daughter cell lineages.

Arabidopsis↗

Predictive identification of exonic splicing enhancers in human genes.

Specific short oligonucleotide sequences that enhance pre-mRNA splicing when present in exons, termed exonic splicing enhancers (ESEs), play important roles in constitutive and alternative splicing. A computational method, RESCUE-ESE, was developed that predicts which sequences have ESE activity by statistical analysis of exon-intron and splice site composition. When large data sets of human gene sequences were used, this method identified 10 predicted ESE motifs. Representatives of all 10 motifs were found to display enhancer activity in vivo, whereas point mutants of these sequences exhibited sharply reduced activity. The motifs identified enable prediction of the splicing phenotypes of exonic mutations in human genes.

Computational Biology↗