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W Lathe

Publications and source records attributed to W Lathe.

5 recordsLinked to original sources

Prediction of deleterious human alleles.

Single nucleotide polymorphisms (SNPs) constitute the bulk of human genetic variation, occurring with an average density of approximately 1/1000 nucleotides of a genotype. SNPs are either neutral allelic variants or are under selection of various strengths, and the impact of SNPs on fitness remains unknown. Identification of SNPs affecting human phenotype, especially leading to risks of complex disorders, is one of the key problems of medical genetics. SNPs in protein-coding regions that cause amino acid variants (non-synonymous cSNPs) are most likely to affect phenotypes. We have developed a straightforward and reliable method based on physical and comparative considerations that estimates the impact of an amino acid replacement on the three-dimensional structure and function of the protein. We estimate that approximately 20% of common human non-synonymous SNPs damage the protein. The average minor allele frequency of such SNPs in our data set was two times lower than that of benign non-synonymous SNPs. The average human genotype carries approximately 10(3) damaging non-synonymous SNPs that together cause a substantial reduction in fitness.

Alleles↗

Integration of genome data and protein structures: prediction of protein folds, protein interactions and "molecular phenotypes" of single nucleotide polymorphisms.

With the massive amount of sequence and structural data being produced, new avenues emerge for exploiting the information therein for applications in several fields. Fold distributions can be mapped onto entire genomes to learn about the nature of the protein universe and many of the interactions between proteins can now be predicted solely on the basis of the genomic context of their genes. Furthermore, by utilising the new incoming data on single nucleotide polymorphisms by mapping them onto three-dimensional structures of proteins, problems concerning population, medical and evolutionary genetics can be addressed.

Apolipoproteins E↗

Exploitation of gene context.

Recently, a number of techniques have been proposed that use completely sequenced genomes for the function prediction of individual proteins encoded therein. They use the fusion of genes, their conserved location in operons or merely their co-occurrence in genomes to predict the existence of functional interactions between the proteins they encode. This type of information complements functional features that are predicted by classical homology-based search techniques.

Animals↗

Predicting protein function by genomic context: quantitative evaluation and qualitative inferences.

Various new methods have been proposed to predict functional interactions between proteins based on the genomic context of their genes. The types of genomic context that they use are Type I: the fusion of genes; Type II: the conservation of gene-order or co-occurrence of genes in potential operons; and Type III: the co-occurrence of genes across genomes (phylogenetic profiles). Here we compare these types for their coverage, their correlations with various types of functional interaction, and their overlap with homology-based function assignment. We apply the methods to Mycoplasma genitalium, the standard benchmarking genome in computational and experimental genomics. Quantitatively, conservation of gene order is the technique with the highest coverage, applying to 37% of the genes. By combining gene order conservation with gene fusion (6%), the co-occurrence of genes in operons in absence of gene order conservation (8%), and the co-occurrence of genes across genomes (11%), significant context information can be obtained for 50% of the genes (the categories overlap). Qualitatively, we observe that the functional interactions between genes are stronger as the requirements for physical neighborhood on the genome are more stringent, while the fraction of potential false positives decreases. Moreover, only in cases in which gene order is conserved in a substantial fraction of the genomes, in this case six out of twenty-five, does a single type of functional interaction (physical interaction) clearly dominate (>80%). In other cases, complementary function information from homology searches, which is available for most of the genes with significant genomic context, is essential to predict the type of interaction. Using a combination of genomic context and homology searches, new functional features can be predicted for 10% of M. genitalium genes.

Bacterial Proteins↗