Purpose Gene identification in small families segregating autosomal dominant sensorineural hearing loss presents a significant challenge. To address this challenge, we have developed a machine learning based software tool, AudioGene v2.0, to prioritize candidate genes for mutation screening based on audioprofiling. Methods We analyzed audiometric data from a cohort of American families with high frequency autosomal dominant sensorineural hearing loss. Those families predicted to have a DFNA2 audioprofile by AudioGene v2.0 were screened for mutations in the KCNQ4 gene. Results Two novel missense mutations and a stop mutation were detected in three American families predicted to have DFNA2-related deafness for a positive predictive value of 6.3%. The false negative rate was 0%. The missense mutations were located in the channel pore region and the stop mutation was in transmembrane domain S5. The latter is the first DFNA2-causing stop mutation reported in KCNQ4. Conclusions Our data suggest: (1) that the N-terminal end of the P-loop is crucial in maintaining the integrity of the KCNQ4 channel pore; and, (2) that AudioGene audioprofile analysis can effectively prioritize genes for mutation screening in small families segregating high frequency autosomal dominant sensorineural hearing loss. AudioGene software will be made freely available to clinicians and researchers once it has been fullly validated.

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A molecular understanding of porcine reproduction is of biological interest and economic importance. Our Midwest Consortium has produced cDNA libraries containing the majority of genes expressed in major female reproductive tissues, and we have deposited into public databases 21,499 expressed sequence tag (EST) gene sequences from the 3' end of clones from these libraries. These sequences represent 10,574 different genes, based on sequence comparison among these data, and comparison with existing porcine ESTs and genes indicate as many as 4652 of these EST clusters are novel. In silico analysis identified sequences that are expressed in specific pig tissues or organs and confirmed the broad expression in pig for many genes ubiquitously expressed in human tissues. Furthermore, we have developed computer software to identify sequence similarity of these pig genes with their human counterparts, and to extract the mapping information of these human homologues from genome databases. We demonstrate the utility of this software for comparative mapping by localizing 61 genes on the porcine physical map for Chromosomes (Chrs) 5, 10, and 14.

As part of the trans-National Institutes of Health (NIH) Mouse Brain Molecular Anatomy Project (BMAP), and in close coordination with the NIH Mammalian Gene Collection Program (MGC), we initiated a large-scale project to clone, identify, and sequence the complete open reading frame (ORF) of transcripts expressed in the developing mouse nervous system. Here we report the analysis of the ORF sequence of 1274 cDNAs, obtained from 47 full-length-enriched cDNA libraries, constructed by using a novel approach, herein described. cDNA libraries were derived from size-fractionated cytoplasmic mRNA isolated from brain and eye tissues obtained at several embryonic stages and postnatal days. Altogether, including the full-ORF MGC sequences derived from these libraries by the MGC sequencing team, NIH_BMAP full-ORF sequences correspond to ∼20% of all transcripts currently represented in mouse MGC. We show that NIH_BMAP clones comprise 68% of mouse MGC cDNAs ≥5 kb, and 54% of those ≥4 kb, as of March 15, 2004. Importantly, we identified transcripts, among the 1274 full-ORF sequences, that are exclusively or predominantly expressed in brain and eye tissues, many of which encode yet uncharacterized proteins.