Linkage studies of Usher syndrome type 1: exclusion results from the Usher syndrome consortium.

Usher Syndrome Type 1 is an autosomal recessive disease characterized by profound congenital hearing impairement and vestibular dysfunction followed by the onset of retinitis pigmentosa in childhood or early adolescence. Members of the Usher Syndrome Consortium, whose objective is to locate and isolate the genes for Usher syndrome, have pooled linkage data from 36 families with 111 affected individuals. We report the analysis of 206 blood group, protein, and DNA marker polymorphisms. No evidence of linkage heterogeneity among families was found for any of the markers studied; the negative lod scores exclude the locus for this disease from about 39% of the genome. Our results indicate the regions of the genome to which our continuing efforts should be directed.     

Localization of two genes for Usher syndrome type I to chromosome 11.

The Usher syndromes (USH) are autosomal recessive diseases characterized by congenital sensorineural hearing loss and progressive pigmentary retinopathy. While relatively rare in the general population, collectively they account for approximately 6% of the congenitally deaf population. Usher syndrome type II (USH2) has been mapped to chromosome 1q (W. J. Kimberling, M. D. Weston, C. M?ller, et al., 1990, Genomics 7: 245-249; R. A. Lewis, B. Otterud, D. Stauffer, et al., 1990, Genomics 7: 250-256), and one form of Usher syndrome type I (USH1) has been mapped to chromosome 14q (J. Kaplan, S. Gerber, D. Bonneau, J. Rozet, M. Briord, J. Dufier, A. Munnich, and J. Frezal, 1990. Cytogenet. Cell Genet. 58: 1988). These loci have been excluded as regions of USH genes in our data set, which is composed of 8 French-Acadian USH1 families and 11 British USH1 families. Both of these sets of families show linkage to loci on chromosome 11. Linkage analysis demonstrates locus heterogeneity between these sets of families, with the French-Acadian families showing linkage to D11S419 (Z = 4.20, theta = 0) and the British families showing linkage to D11S527 (Z = 6.03, theta = 0). Genetic heterogeneity of the data set was confirmed using HOMOG and the M test (log likelihood ratio > 10(5)). These results confirm the presence of two distinct USH1 loci on chromosome 11.     

Genetic variation of recent Alu insertions in human populations

The Alu family of intersperesed repeats is comprised of ovr 500,000 members which may be divided into discrete subfamilies based upon mutations held in common between members. Distinct subfamilies of Alu sequences have amplified within the human genome in recent evolutionary history. Several individual Alu family members have amplified so recently in human evolution that they are variable as to presence and absence at specific loci within different human populations. Here, we report on the distribution of six polymorphic Alu insetions in a survey of 563 individuals from 14 human population groups across several continents. Our results indicate that these polymorphic Alu insertions probably have an African origin and that there is a much smaller amount of genetic variation between European populations than that found between other populations groups. Present address: Department of Pathology, Stanley S. Scott Cancer Center, Louisiana State University Medical Center, 1901 Perdido St., New Orleans, LA 70112 Correspondence to: M.A. Batzer     

Data Quality

A methodology is presented to develop and analyze vectors of data quality attribute scores. Each data quality vector component represents the quality of the data element for a specific attribute (e.g., age of data). Several methods for aggregating the components of data quality vectors to derive one data quality indicator (DQI) that represents the total quality associated with the input data element are presented with illustrative examples. The methods are compared and it is proven that the measure of central tendency, or arithmetic average, of the data quality vector components as a percentage of the total quality range attainable is an equivalent measure for the aggregate DQI. In addition, the methodology is applied and compared to realworld LCA data pedigree matrices. Finally, a method for aggregating weighted data quality vector attributes is developed and an illustrative example is presented. This methodology provides LCA practitioners with an approach to increase the precision of input data uncertainty assessments by selecting any number of data quality attributes with which to score the LCA inventory model input data. The resultant vector of data quality attributes can then be analyzed to develop one aggregate DQI for each input data element for use in stochastic LCA modeling.