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Thomas Wiehe

Publications and source records attributed to Thomas Wiehe.

5 recordsLinked to original sources

Comparative genomics: methods and applications.

Interpreting the functional content of a given genomic sequence is one of the central challenges of biology today. Perhaps the most promising approach to this problem is based on the comparative method of classic biology in the modern guise of sequence comparison. For instance, protein-coding regions tend to be conserved between species. Hence, a simple method for distinguishing a functional exon from the chance absence of stop codons is to investigate its homologue from closely related species. Predicting regulatory elements is even more difficult than exon prediction, but again, comparisons pinpointing conserved sequence motifs upstream of translation start sites are helping to unravel gene regulatory networks. In addition to interspecific studies, intraspecific sequence comparison yields insights into the evolutionary forces that have acted on a species in the past. Of particular interest here is the identification of selection events such as selective sweeps. Both intra- and interspecific sequence comparisons are based on a variety of computational methods, including alignment, phylogenetic reconstruction, and coalescent theory. This article surveys the biology and the central computational ideas applied in recent comparative genomics projects. We argue that the most fruitful method of understanding the functional content of genomes is to study them in the context of related genomic sequences. In particular, such a study may reveal selection, a fundamental pointer to biological relevance.

Animals↗

gff2aplot: Plotting sequence comparisons.

SUMMARY: gff2aplot is a program to visualize the alignment of two sequences together with their annotations. Input for the program consists of single or multiple files in GFF-format which specify the alignment coordinates and annotation features of both sequences. Output is in PostScript format of any size. The features to be displayed are highly customizable to meet user specific needs. The program serves to generate print-quality images for comparative genome sequence analysis. AVAILABILITY: gff2aplot is freely available under the GNU software licence and can be downloaded from the address specified below. SUPPLEMENTARY INFORMATION: http://genome.imim.es/software/gfftools/GFF2APLOT.html

Animals↗

Comparative gene prediction in human and mouse.

The completion of the sequencing of the mouse genome promises to help predict human genes with greater accuracy. While current ab initio gene prediction programs are remarkably sensitive (i.e., they predict at least a fragment of most genes), their specificity is often low, predicting a large number of false-positive genes in the human genome. Sequence conservation at the protein level with the mouse genome can help eliminate some of those false positives. Here we describe SGP2, a gene prediction program that combines ab initio gene prediction with TBLASTX searches between two genome sequences to provide both sensitive and specific gene predictions. The accuracy of SGP2 when used to predict genes by comparing the human and mouse genomes is assessed on a number of data sets, including single-gene data sets, the highly curated human chromosome 22 predictions, and entire genome predictions from ENSEMBL. Results indicate that SGP2 outperforms purely ab initio gene prediction methods. Results also indicate that SGP2 works about as well with 3x shotgun data as it does with fully assembled genomes. SGP2 provides a high enough specificity that its predictions can be experimentally verified at a reasonable cost. SGP2 was used to generate a complete set of gene predictions on both the human and mouse by comparing the genomes of these two species. Our results suggest that another few thousand human and mouse genes currently not in ENSEMBL are worth verifying experimentally.

Animals↗

Calculating the SNP-effective sample size from an alignment.

MOTIVATION: The number of Single Nucleotide Polymorphisms (SNPs) detectable in an alignment is a function of the length and the number of the aligned sequences. The latter is called sample size. However, a typical alignment, for instance obtained as a BLAST-search result of a query sequence against an EST database, does not evenly cover the query sequence. Therefore, it is usually not clear what the actual sample size is. RESULTS: We present a method to calculate the effective sample size, called n(eff), for a given BLAST alignment. This method takes into account that multiple coverage contributes only logarithmically to the SNP yield of a given sequence stretch. We show that the effective sample size n(eff) is usually much smaller than would be expected for a given amount of coverage and illustrate this with two typical examples.

Algorithms↗

Recombination and gene conversion in a 170-kb genomic region of Arabidopsis thaliana.

Arabidopsis thaliana is a highly selfing plant that nevertheless appears to undergo substantial recombination. To reconcile its selfing habit with the observations of recombination, we have sampled the genetic diversity of A. thaliana at 14 loci of approximately 500 bp each, spread across 170 kb of genomic sequence centered on a QTL for resistance to herbivory. A total of 170 of the 6321 nucleotides surveyed were polymorphic, with 169 being biallelic. The mean silent genetic diversity (pi(s)) varied between 0.001 and 0.03. Pairwise linkage disequilibria between the polymorphisms were negatively correlated with distance, although this effect vanished when only pairs of polymorphisms with four haplotypes were included in the analysis. The absence of a consistent negative correlation between distance and linkage disequilibrium indicated that gene conversion might have played an important role in distributing genetic diversity throughout the region. We tested this by coalescent simulations and estimate that up to 90% of recombination is due to gene conversion.

Arabidopsis↗