Chiropteran types I and II interferon genes inferred from genome sequencing traces by a statistical gene-family assembler.

BACKGROUND: The rate of emergence of human pathogens is steadily increasing; most of these novel agents originate in wildlife. Bats, remarkably, are the natural reservoirs of many of the most pathogenic viruses in humans. There are two bat genome projects currently underway, a circumstance that promises to speed the discovery host factors important in the coevolution of bats with their viruses. These genomes, however, are not yet assembled and one of them will provide only low coverage, making the inference of most genes of immunological interest error-prone. Many more wildlife genome projects are underway and intend to provide only shallow coverage. RESULTS: We have developed a statistical method for the assembly of gene families from partial genomes. The method takes full advantage of the quality scores generated by base-calling software, incorporating them into a complete probabilistic error model, to overcome the limitation inherent in the inference of gene family members from partial sequence information. We validated the method by inferring the human IFNA genes from the genome trace archives, and used it to infer 61 type-I interferon genes, and single type-II interferon genes in the bats Pteropus vampyrus and Myotis lucifugus. We confirmed our inferences by direct cloning and sequencing of IFNA, IFNB, IFND, and IFNK in P. vampyrus, and by demonstrating transcription of some of the inferred genes by known interferon-inducing stimuli. CONCLUSION: The statistical trace assembler described here provides a reliable method for extracting information from the many available and forthcoming partial or shallow genome sequencing projects, thereby facilitating the study of a wider variety of organisms with ecological and biomedical significance to humans than would otherwise be possible.

Genetic variants in IGF-I, IGF-II, IGFBP-3, and adiponectin genes and colon cancer risk in African Americans and Whites.

PURPOSE: Evaluating genetic susceptibility may clarify effects of known environmental factors and also identify individuals at high risk. We evaluated the association of four insulin-related pathway gene polymorphisms in insulin-like growth factor-1 (IGF-I) (CA)( n ) repeat, insulin-like growth factor-2 (IGF-II) (rs680), insulin-like growth factor-binding protein-3 (IGFBP-3) (rs2854744), and adiponectin (APM1 rs1501299) with colon cancer risk, as well as relationships with circulating IGF-I, IGF-II, IGFBP-3, and C-peptide in a population-based study. METHODS: Participants were African Americans (231 cases and 306 controls) and Whites (297 cases, 530 controls). Consenting subjects provided blood specimens and lifestyle/diet information. Genotyping for all genes except IGF-I was performed by the 5'-exonuclease (Taqman) assay. The IGF-I (CA)(n) repeat was assayed by PCR and fragment analysis. Circulating proteins were measured by enzyme immunoassays. Odds ratios (ORs) and 95 % confidence intervals (CIs) were calculated by logistic regression. RESULTS: The IGF-I (CA)( 19 ) repeat was higher in White controls (50 %) than African American controls (31 %). Whites homozygous for the IGF-I (CA)(19) repeat had a nearly twofold increase in risk of colon cancer (OR = 1.77; 95 % CI = 1.15-2.73), but not African Americans (OR = 0.73, 95 % CI 0.50-1.51). We observed an inverse association between the IGF-II Apa1 A-variant and colon cancer risk (OR = 0.49, 95 % CI 0.28-0.88) in Whites only. Carrying the IGFBP-3 variant alleles was associated with lower IGFBP-3 protein levels, a difference most pronounced in Whites (p-trend <0.05). CONCLUSIONS: These results support an association between insulin pathway-related genes and elevated colon cancer risk in Whites but not in African Americans.