Selecting cases from nuclear families for case-control association analysis

We examine the efficiency of a number of schemes to select cases from nuclear families for case-control association analysis using the Genetic Analysis Workshop 14 simulated dataset. We show that with this simulated dataset comparing all affected siblings with unrelated controls is considerably more powerful than all of the other approaches considered. We find that the test statistic is increased by almost 3-fold compared to the next best sampling schemes of selecting all affected sibs only from families with affected parents (AF(aff)), one affected sib with most evidence of allele-sharing from each family (SF), and all affected sibs from families with evidence for linkage (AF(L)). We consider accounting for biological relatedness of samples in the association analysis to maintain the correct type I error. We also discuss the relative efficiencies of increasing the ratio of unrelated cases to controls, methods to confirm associations and issues to consider when applying our conclusions to other complex disease datasets

Classification of rheumatoid arthritis status with candidate gene and genome-wide single-nucleotide polymorphisms using random forests

Abstract Using the North American Rheumatoid Arthritis Consortium (NARAC) candidate gene and genome-wide single-nucleotide polymorphism (SNP) data sets, we applied regression methods and tree-based random forests to identify genetic associations with rheumatoid arthritis (RA) and to predict RA disease status. Several genes were consistently identified as weakly associated with RA without a significant interaction or combinatorial effect with other candidate genes. Using random forests, the tested candidate gene SNPs were not sufficient to predict RA patients and normal subjects with high accuracy. However, using the top 500 SNPs, ranked by the importance score, from the genome-wide linkage panel of 5742 SNPs, we were able to accurately predict RA patients and normal subjects with sensitivity of approximately 90% and specificity of approximately 80%, which was confirmed by five-fold cross-validation. However, in a complete training-testing framework, replication of genetic predictors was less satisfactory; thus, further evaluation of existing methodology and development of new methods are warranted.http://deepblue.lib.umich.edu/bitstream/2027.42/117372/1/12919_2007_Article_2426.pd

Evaluation and monitoring of terrestrial and aquatic insect biodiversity in forested and cleared watersheds at Camp Atterbury, Indiana.

Executive Summary Camp Atterbury is a 33,132 ha military installation near Edinburgh, Indiana. Construction of a 80 ha (4,550 ha with safety fan) Multi-Purpose Training Range (MPTR) began in 1998, and supports training for military vehicles and dismounted infantry, with a variety of stationary and moving targets. This study provides a baseline for long term monitoring and evaluation of natural communities to assess the impacts of construction of, and training in, the MPTR. We assessed both aquatic macroinvertebrate and terrestrial insect community diversity, abundance, and richness and similarity at a series of study plots using quantifiable, repeatable and replicated methods. These data provide baseline data facilitating long-term monitoring and assessment as a measure of ecosystem health, and allow evaluation of relationships between community composition and habitat metrics. Methods Eight terrestrial study sites, each comprised of a 30 m square plot, were randomly selected, with four of these placed in the cleared portions of the MPTR and four placed in adjacent upland forest. We used several sampling methods, with focus on three groups of taxa (all insect taxa, ants, and leafhoppers and kin) and compared the efficacy of both the methods and the groups as monitoring tools. Sampling methods included: 1) a Malaise trap (mesh tent-like device that captures flying insects) at each site; 2) four sweep sample transects at each site; 3) four leaf litter samples from each site, with invertebrates extracted using the Winkler method; and 4) Nine pitfall traps at each site. Samples were collect during Summer and Fall study periods, and this report gives results from the Summer sample period. Several habitat parameters were recorded, including a vegetation index, canopy cover, ground cover, and leaf litter depth. Dominant plant taxa were collected, and data loggers recorded soil and air temperature during the study. We sampled aquatic macroinvertebrates at three stream sites draining the MPTR. Invertebrates were collected in replicate samples with a dipnet and these were sorted and subsampled in the laboratory. Canopy cover and basic water chemistry data were collected, and data loggers recorded changes in terrestrial and aquatic temperature. An index of biotic integrity and taxon richness were used to evaluate the aquatic communities. Results and Discussion At least 409 taxa and 3776 specimens were collected at terrestrial sample sites during the Summer sampling period. In general, there were some differences among sites, among sampling methods, and among treatments (cleared MPTR versus forested) when we examined taxon richness and species diversity, but these differences could not always be fully resolved. While taxon richness and species diversity differed among treatments, and, in general, plots in the two treatments harbored different insect communities. Species accumulation curves and various estimators of taxon richness were used to evaluate the four sampling methods and the three groups of taxa (all taxa, ants, leafhoppers). Based on the performance of the different taxa (all, ants, leafhoppers) compared across the different methods (malaise sampling, Winkler extracted leaf litter samples, pitfall traps, and sweep samples), the single most effective taxon for monitoring was found to be the ants (Formicidae), and the single best method for monitoring was found to be pitfall trapping. We collected 818 specimens, primarily aquatic macroinvertebrates, from the three stream sites during Summer sampling. All three streams were dry during the fall sample period, and thus no aquatic macroinvertebrates were collected. Using Hilsenhoff’s (1988) family-level index of biotic integrity, water quality was classified as “good” at one site, and “fair” at the other two, although taxon richness was lowest at the site classified as good. In addition to invertebrates, numerous salamanders (Eurycea cirrigera, the Two-lined Salamander) were observed in the streams. 3 For aquatic invertebrates, we found that the small upstream portions that directly drained the MPTR only held water seasonally, and thus were not effective sites for monitoring of stream macroinvertebrates. There was insufficient separation between MPTR-influenced stream sites and control sites, and a lack of replication (few streams flowing away from the MPTR) precluded robust statistical analysis of the data we did obtain. The community of aquatic macroinvertebrates collected during this study appeared similar to the communities reported by Robinson (2004) elsewhere at Camp Atterbury in larger streams, and includes taxa typical of rocky bottom Midwestern forest streams. Fish were largely absent due to the intermittent nature of the streams. Salamanders were abundant in the streams, and because they are top predators in this seasonal habitat, they may be suitable subjects for studies of potential bioaccumulation of toxins. This study provides a snapshot of insect biodiversity at a point in time, thus providing baseline for any possible future monitoring of insect biodiversity. Sampling methods and analyses developed in this study could easily be implemented at a wide variety of other military installations to facilitate inventory and/or monitoring of insect biodiversity.Ope

Methodological development of allelic analyses using DNA pooling

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Identification of Pathogenic Variants Causes Microcephaly In Sindh Families

 Introduction: The study was designed to identify the genetic mutation in families with autosomal recessive primary microcephaly (MCPH). Methodology: The present study was cross-sectional and conducted at the Department of Biochemistry, Quaid-e-Azam University, Islamabad in 2017. The two families (A and B) with MCPH phenotype randomly selected from Hyderabad and Tando Adam districts respectively. Informed written consent was taken, physical parameters were measured and blood samples were collected from both families. DNA was extracted from whole blood and PCR was performed. The ASPM gene located on chromosome 1 is known to play a vital role in mitotic spindle fiber regulation during neurogenesis, and also is the most probable causative agent of microcephaly. Therefore targeted Sanger sequencing method for the ASPM gene was selected for variant identification in both families. Results: The Sanger sequencing result showed the novel missense variant (c.5841T/C; p. K1862E) in 18 exon of ASPM gene in Family A  and this variant predicted as damaging in mutation tester, and provean and also exhibited deleterious in Polyphen 2 and SIFT public database. Similarly in family B we found a previously reported protein pre termination variant (c.3978G/A; p.Trp1326*) (rs137852995) in exon 17 of ASPM gene. The later mutation was most predominant cause of microcephaly in KPK families. Conclusion: Therefore it is concluded that mutation in the ASPM gene is the most prominent genetic player of Microcephaly in Pakistani families. The current study aids in the genetic analysis of MCPH phenotype families in Pakistan alongwith the counseling of MCPH families

Selecting cases from nuclear families for case-control association analysis-0

<p><b>Copyright information:</b></p><p>Taken from "Selecting cases from nuclear families for case-control association analysis"</p><p></p><p>BMC Genetics 2005;6(Suppl 1):S105-S105.</p><p>Published online 30 Dec 2005</p><p>PMCID:PMC1866834.</p><p></p>tion, R) and the lower right hand triangle shows pair-wise D' values (labelled d prime). Red indicates values of r or D' close to 1, blue represents values close to 0

Classification of rheumatoid arthritis status with candidate gene and genome-wide single-nucleotide polymorphisms using random forests-1

Tus with the true RA status in the testing dataset. Each color curve represents prediction accuracy of one of the five CVs.<p><b>Copyright information:</b></p><p>Taken from "Classification of rheumatoid arthritis status with candidate gene and genome-wide single-nucleotide polymorphisms using random forests"</p><p>http://www.biomedcentral.com/1753-6561/1/S1/S62</p><p>BMC Proceedings 2007;1(Suppl 1):S62-S62.</p><p>Published online 18 Dec 2007</p><p>PMCID:PMC2367463.</p><p></p