Linkage disequilibrium assessment via log-linear modeling of SNP haplotype frequencies

Analyses of high-density single-nucleotide polymorphism (SNP) data, such as genetic mapping and linkage disequilibrium (LD) studies, require phase-known haplotypes to allow for the correlation between tightly linked loci. However, current SNP genotyping technology cannot determine phase, which must be inferred statistically. In this paper, we present a new Bayesian Markov chain Monte Carlo (MCMC) algorithm for population haplotype frequency estimation, particulary in the context of LD assessment. The novel feature of the method is the incorporation of a log-linear prior model for population haplotype frequencies. We present simulations to suggest that 1) the log-linear prior model is more appropriate than the standard coalescent process in the presence of recombination (>0.02cM between adjacent loci), and 2) there is substantial inflation in measures of LD obtained by a "two-stage" approach to the analysis by treating the "best" haplotype configuration as correct, without regard to uncertainty in the recombination process. Genet Epidemiol 25:106-114, 2003. (C) 2003 Wiley-Liss, Inc.

Measuring gametic disequilibrium from multilocus data

We describe a Bayesian approach to analyzing multilocus genotype or haplotype data to assess departures from gametic (linkage) equilibrium. Our approach employs a Markov chain Monte Carlo (MCMC) algorithm to approximate the posterior probability distributions of disequilibrium parameters. The distributions are computed exactly in some simple settings. Among other advantages, posterior distributions can be presented visually, which allows the uncertainties in parameter estimates to be readily assessed. In addition, background knowledge can be incorporated, where available, to improve the precision of inferences. The method is illustrated by application to previously published datasets; implications for multilocus forensic match probabilities and for simple association-based gene mapping are also discussed.

Energy at work: a measurement validation and linkage to unit effectiveness

We introduce the notion that the energy of individuals can manifest as a higher-level, collective construct. To this end, we conducted four independent studies to investigate the viability and importance of the collective energy construct as assessed by a new survey instrument—the productive energy measure (PEM). Study 1 (n = 2208) included exploratory and confirmatory factor analyses to explore the underlying factor structure of PEM. Study 2 (n = 660) cross-validated the same factor structure in an independent sample. In study 3, we administered the PEM to more than 5000 employees from 145 departments located in five countries. Results from measurement invariance, statistical aggregation, convergent, and discriminant-validity assessments offered additional support for the construct validity of PEM. In terms of predictive and incremental validity, the PEM was positively associated with three collective attitudes—units' commitment to goals, the organization, and overall satisfaction. In study 4, we explored the relationship between the productive energy of firms and their overall performance. Using data from 92 firms (n = 5939employees), we found a positive relationship between the PEM (aggregated to the firm level) and the performance of those firms. Copyright © 2011 John Wiley & Sons, Ltd.

A genetic linkage map of an apple rootstock progeny anchored to the Malus genome sequence

An apple rootstock progeny raised from the cross between the very dwarfing ‘M.27’ and the more vigorous ‘M.116’ (‘M.M.106’ × ‘M.27’) was used for the construction of a linkage map comprising a total of 324 loci: 252 previously mapped SSRs, 71 newly characterised or previously unmapped SSR loci (including 36 amplified by 33 out of the 35 novel markers reported here), and the self-incompatibility locus. The map spanned the 17 linkage groups (LG) expected for apple covering a genetic distance of 1,229.5 cM, an estimated 91% of the Malus genome. Linkage groups were well populated and, although marker density ranged from 2.3 to 6.2 cM/SSR, just 15 gaps of more than 15 cM were observed. Moreover, only 17.5% of markers displayed segregation distortion and, unsurprisingly in a semi-compatible backcross, distortion was particularly pronounced surrounding the self-incompatibility locus (S) at the bottom of LG17. DNA sequences of 273 SSR markers and the S locus, representing a total of 314 loci in this investigation, were used to anchor to the ‘Golden Delicious’ genome sequence. More than 260 of these loci were located on the expected pseudo-chromosome on the ‘Golden Delicious’ genome or on its homeologous pseudo-chromosome. In total, 282.4 Mbp of sequence from 142 genome sequence scaffolds of the Malus genome were anchored to the ‘M.27’ × ‘M.116’ map, providing an interface between the marker data and the underlying genome sequence. This will be exploited for the identification of genes responsible for traits of agronomic importance such as dwarfing and water use efficiency.

Development of a dense SNP-based linkage map of an apple rootstock progeny using the Malus Infinium whole genome genotyping array

Background A whole-genome genotyping array has previously been developed for Malus using SNP data from 28 Malus genotypes. This array offers the prospect of high throughput genotyping and linkage map development for any given Malus progeny. To test the applicability of the array for mapping in diverse Malus genotypes, we applied the array to the construction of a SNPbased linkage map of an apple rootstock progeny. Results Of the 7,867 Malus SNP markers on the array, 1,823 (23.2 %) were heterozygous in one of the two parents of the progeny, 1,007 (12.8 %) were heterozygous in both parental genotypes, whilst just 2.8 % of the 921 Pyrus SNPs were heterozygous. A linkage map spanning 1,282.2 cM was produced comprising 2,272 SNP markers, 306 SSR markers and the S-locus. The length of the M432 linkage map was increased by 52.7 cM with the addition of the SNP markers, whilst marker density increased from 3.8 cM/marker to 0.5 cM/marker. Just three regions in excess of 10 cM remain where no markers were mapped. We compared the positions of the mapped SNP markers on the M432 map with their predicted positions on the ‘Golden Delicious’ genome sequence. A total of 311 markers (13.7 % of all mapped markers) mapped to positions that conflicted with their predicted positions on the ‘Golden Delicious’ pseudo-chromosomes, indicating the presence of paralogous genomic regions or misassignments of genome sequence contigs during the assembly and anchoring of the genome sequence. Conclusions We incorporated data for the 2,272 SNP markers onto the map of the M432 progeny and have presented the most complete and saturated map of the full 17 linkage groups of M. pumila to date. The data were generated rapidly in a high-throughput semi-automated pipeline, permitting significant savings in time and cost over linkage map construction using microsatellites. The application of the array will permit linkage maps to be developed for QTL analyses in a cost-effective manner, and the identification of SNPs that have been assigned erroneous positions on the ‘Golden Delicious’ reference sequence will assist in the continued improvement of the genome sequence assembly for that variety.

Analysis of protein sequence and interaction data for candidate disease gene prediction

Linkage analysis is a successful procedure to associate diseases with specific genomic regions. These regions are often large, containing hundreds of genes, which make experimental methods employed to identify the disease gene arduous and expensive. We present two methods to prioritize candidates for further experimental study: Common Pathway Scanning (CPS) and Common Module Profiling (CMP). CPS is based on the assumption that common phenotypes are associated with dysfunction in proteins that participate in the same complex or pathway. CPS applies network data derived from protein–protein interaction (PPI) and pathway databases to identify relationships between genes. CMP identifies likely candidates using a domain-dependent sequence similarity approach, based on the hypothesis that disruption of genes of similar function will lead to the same phenotype. Both algorithms use two forms of input data: known disease genes or multiple disease loci. When using known disease genes as input, our combined methods have a sensitivity of 0.52 and a specificity of 0.97 and reduce the candidate list by 13-fold. Using multiple loci, our methods successfully identify disease genes for all benchmark diseases with a sensitivity of 0.84 and a specificity of 0.63. Our combined approach prioritizes good candidates and will accelerate the disease gene discovery process.

Validation of de-identified record linkage to ascertain hospital admissions in a cohort study

Background Cohort studies can provide valuable evidence of cause and effect relationships but are subject to loss of participants over time, limiting the validity of findings. Computerised record linkage offers a passive and ongoing method of obtaining health outcomes from existing routinely collected data sources. However, the quality of record linkage is reliant upon the availability and accuracy of common identifying variables. We sought to develop and validate a method for linking a cohort study to a state-wide hospital admissions dataset with limited availability of unique identifying variables.

Methods A sample of 2000 participants from a cohort study (n = 41 514) was linked to a state-wide hospitalisations dataset in Victoria, Australia using the national health insurance (Medicare) number and demographic data as identifying variables. Availability of the health insurance number was limited in both datasets; therefore linkage was undertaken both with and without use of this number and agreement tested between both algorithms. Sensitivity was calculated for a sub-sample of 101 participants with a hospital admission confirmed by medical record review.

Results Of the 2000 study participants, 85% were found to have a record in the hospitalisations dataset when the national health insurance number and sex were used as linkage variables and 92% when demographic details only were used. When agreement between the two methods was tested the disagreement fraction was 9%, mainly due to "false positive" links when demographic details only were used. A final algorithm that used multiple combinations of identifying variables resulted in a match proportion of 87%. Sensitivity of this final linkage was 95%.

Conclusions High quality record linkage of cohort data with a hospitalisations dataset that has limited identifiers can be achieved using combinations of a national health insurance number and demographic data as identifying variables.

Using clinical trial data and linked administrative health data to reduce the risk of adverse events associated with the uptake of newly released drugs by older Australians: a model process

BACKGROUND: The study was undertaken to evaluate the contribution of a process which uses clinical trial data plus linked de-identified administrative health data to forecast potential risk of adverse events associated with the use of newly released drugs by older Australian patients. METHODS: The study uses publicly available data from the clinical trials of a newly released drug to ascertain which patient age groups, gender, comorbidities and co-medications were excluded in the trials. It then uses linked de-identified hospital morbidity and medications dispensing data to investigate the comorbidities and co-medications of patients who suffer from the target morbidity of the new drug and who are the likely target population for the drug. The clinical trial information and the linked morbidity and medication data are compared to assess which patient groups could potentially be at risk of an adverse event associated with use of the new drug. RESULTS: Applying the model in a retrospective real-world scenario identified that the majority of the sample group of Australian patients aged 65 years and over with the target morbidity of the newly released COX-2-selective NSAID rofecoxib also suffered from a major morbidity excluded in the trials of that drug, indicating a substantial potential risk of adverse events amongst those patients. This risk was borne out in post-release morbidity and mortality associated with use of that drug. CONCLUSIONS: Clinical trial data and linked administrative health data can together support a prospective assessment of patient groups who could be at risk of an adverse event if they are prescribed a newly released drug in the context of their age, gender, comorbidities and/or co-medications. Communication of this independent risk information to prescribers has the potential to reduce adverse events in the period after the release of the new drug, which is when the risk is greatest.Note: The terms 'adverse drug reaction' and 'adverse drug event' have come to be used interchangeably in the current literature. For consistency, the authors have chosen to use the wider term 'adverse drug event' (ADE).

Monitoring and evaluating surgical care: defining perioperative mortality rate and standardising data collection

BACKGROUND: Case volume per 100 000 population and perioperative mortality rate (POMR) are key indicators to monitor and strengthen surgical services. However, comparisons of POMR have been restricted by absence of standardised approaches to when it is measured, the ideal denominator, need for risk adjustment, and whether data are available. We aimed to address these issues and recommend a minimum dataset by analysing four large mixed surgical datasets, two from well-resourced settings with sophisticated electronic patient information systems and two from resource-limited settings where clinicians maintain locally developed databases. METHODS: We obtained data from the New Zealand (NZ) National Minimum Dataset, the Geelong Hospital patient management system in Australia, and purpose-built surgical databases in Pietermaritzburg, South Africa (PMZ) and Port Moresby, Papua New Guinea (PNG). Information was sought on inclusion and exclusion criteria, coding criteria, and completeness of patient identifiers, admission, procedure, discharge and death dates, operation details, urgency of admission, and American Society of Anesthesiologists (ASA) score. Date-related errors were defined as missing dates and impossible discrepancies. For every site, we then calculated the POMR, the effect of admission episodes or procedures as denominator, and the difference between in-hospital POMR and 30-day POMR. To determine the need for risk adjustment, we used univariate and multivariate logistic regression to assess the effect on relative POMR for each site of age, admission urgency, ASA score, and procedure type. FINDINGS: 1 365 773 patient admissions involving 1 514 242 procedures were included, among which 8655 deaths were recorded within 30 days. Database inclusion and exclusion criteria differed substantially. NZ and Geelong records had less than 0·1% date-related errors and greater than 99·9% completeness. PMZ databases had 99·9% or greater completeness of all data except date-related items (94·0%). PNG had 99·9% or greater completeness for date of birth or age and admission date and operative procedure, but 80-83% completeness of patient identifiers and date related items. Coding of procedures was not standardised, and only NZ recorded ASA status and complete post-discharge mortality. In-hospital POMR range was 0·38% in NZ to 3·44% in PMZ, and in NZ it underestimated 30-day POMR by roughly a third. The difference in POMR by procedures instead of admission episodes as denominator ranged from 10% to 70%. Age older than 65 years and emergency admission had large independent effects on POMR, but relatively little effect in multivariate analysis on the relative odds of in-hospital death at each site. INTERPRETATION: Hospitals can collect and provide data for case volume and POMR without sophisticated electronic information systems. POMR should initially be defined by in-hospital mortality because post-discharge deaths are not usually recorded, and with procedures as denominator because details allowing linkage of several operations within one patient's admission are not always present. Although age and admission urgency are independently associated with POMR, and ASA and case mix were not included, risk adjustment might not be essential because the relative odds between sites persisted. Standardisation of inclusion criteria and definitions is needed, as is attention to accuracy and completeness of dates of procedures, discharge and death. A one-page, paper-based form, or alternatively a simple electronic data collection form, containing a minimum dataset commenced in the operating theatre could facilitate this process. FUNDING: None.

Multidimensional cluster stability analysis from a Brazilian Bradyrhizobium sp RFLP/PCR data set

The taxonomy of the N(2)-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined, mainly due to conflicting results obtained by the analysis of the phenotypic and genotypic properties. This paper presents an application of a method aiming at the identification of possible new clusters within a Brazilian collection of 119 Bradryrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability was studied as a function of the number of restriction enzymes used in the RFLP-PCR analysis of three ribosomal regions with three restriction enzymes per region. The method proposed here uses Clustering algorithms with distances calculated by average-linkage clustering. Introducing perturbations using sub-sampling techniques makes the stability analysis. The method showed efficacy in the grouping of the species B. japonicum and B. elkanii. Furthermore, two new clusters were clearly defined, indicating possible new species, and sub-clusters within each detected cluster. (C) 2008 Elsevier B.V. All rights reserved.

A microsatellite-based, gene-rich linkage map for the AA genome of Arachis (Fabaceae)

Cultivated peanut (Arachis hypogaea) is an important crop, widely grown in tropical and subtropical regions of the world. It is highly susceptible to several biotic and abiotic stresses to which wild species are resistant. As a first step towards the introgression of these resistance genes into cultivated peanut, a linkage map based on microsatellite markers was constructed, using an F-2 population obtained from a cross between two diploid wild species with AA genome (A. duranensis and A. stenosperma). A total of 271 new microsatellite markers were developed in the present study from SSR-enriched genomic libraries, expressed sequence tags (ESTs), and by data-mining sequences available in GenBank. of these, 66 were polymorphic for cultivated peanut. The 271 new markers plus another 162 published for peanut were screened against both progenitors and 204 of these (47.1%) were polymorphic, with 170 codominant and 34 dominant markers. The 80 codominant markers segregating 1:2:1 (P < 0.05) were initially used to establish the linkage groups. Distorted and dominant markers were subsequently included in the map. The resulting linkage map consists of 11 linkage groups covering 1,230.89 cM of total map distance, with an average distance of 7.24 cM between markers. This is the first microsatellite-based map published for Arachis, and the first map based on sequences that are all currently publicly available. Because most markers used were derived from ESTs and genomic libraries made using methylation-sensitive restriction enzymes, about one-third of the mapped markers are genic. Linkage group ordering is being validated in other mapping populations, with the aim of constructing a transferable reference map for Arachis.

PHYLOGENETIC STUDIES OF SOME SPECIES OF THE GENUS COFFEA .2. NUMERICAL-ANALYSIS OF ISOENZYMATIC DATA

Thirteen species of Coffea were studied for five enzymes systems, including alpha and beta esterase, alkaline phosphatase, acid phosphatase, malate dehydrogenase and acid dehydrogenase. Three coefficients of similarity: Simple Matching, Jaccard and Ochiai and three different clustering methods: Single Linkage, Complete Linkage and Unweighted Pair Group, using Arithmetic Averages (UPGMA) were used to analyse the data.The phylogenetic relationships among the twelve diploid species and between them and the tetraploid species C. arabica showed that similarity among species of the same subsection is not always greater than among species of different subsections. In addition, although there are several similarity groups in common, established by isoenzymatic polymorphism, morphological characteristics, chemical data, crossability and geographic distribution, there is no common trend among the phylogenetic relationships as indicated by all these different evaluating procedures.

Genetic data of 10 X-chromosomal loci in Vitória population (Espírito Santo State, Brazil)

Genetic population data for 10 X-STR (DXS8378, DXS9898, DXS7133, GATA31E08, GATA172D05, DXS7423, DXS6809, DXS7132, DXS9902 and DXS6789) were obtained from Vitória population (Espírito Santo State, Brazil). No deviations from the Hardy-Weinberg equilibrium and linkage disequilibrium were observed. The combined powers of discrimination in males and females were 0.9999995 and 0.99999999996, respectively. These high values show the potential of this system in human identification in Vitória population, Brazil. © 2009 Elsevier B.V. All rights reserved.

Study of whole genome linkage disequilibrium in Nellore cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Precision of distances and ordering of microsatellite markers in consensus linkage maps of chromosomes 1, 3 and 4 from two reciprocal chicken populations using bootstrap sampling

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)