DiveRsity: An R package for the estimation and exploration of population genetics parameters and their associated errors

Summary: We present a new R package, diveRsity, for the calculation of various diversity statistics, including common diversity partitioning statistics (?, G) and population differentiation statistics (D, GST ', ? test for population heterogeneity), among others. The package calculates these estimators along with their respective bootstrapped confidence intervals for loci, sample population pairwise and global levels. Various plotting tools are also provided for a visual evaluation of estimated values, allowing users to critically assess the validity and significance of statistical tests from a biological perspective. diveRsity has a set of unique features, which facilitate the use of an informed framework for assessing the validity of the use of traditional F-statistics for the inference of demography, with reference to specific marker types, particularly focusing on highly polymorphic microsatellite loci. However, the package can be readily used for other co-dominant marker types (e.g. allozymes, SNPs). Detailed examples of usage and descriptions of package capabilities are provided. The examples demonstrate useful strategies for the exploration of data and interpretation of results generated by diveRsity. Additional online resources for the package are also described, including a GUI web app version intended for those with more limited experience using R for statistical analysis. © 2013 British Ecological Society.

Empirical assessment of non-invasive population genetics in bats:Comparison of DNA quality from faecal and tissue samples

Non-invasive population genetics has become a valuable tool in ecology and conservation biology, allowing genetic studies of wild populations without the need to catch, handle or even observe the study subjects directly. We address some of the concerns regarding the limitations of using non-invasive samples by comparing the quality of population genetic information gained through DNA extracted from faecal samples and biopsy samples of two elusive bat species, Myotis mystacinus and Myotis nattereri. We demonstrate that DNA extracted from faeces and tissue samples gives comparable results for frequency based population genetic analyses, despite the occurrence of genotyping errors when using faecal DNA. We conclude that non-invasive genetic sampling for population genetic analysis in bats is viable, and although more labour-intensive and expensive, it is an alternative to tissue sampling, which is particularly pertinent when specimens are rare, endangered or difficult to capture. © 2012 Museum and Institute of Zoology PAS.

Genetics of New-Onset Diabetes after Transplantation

New-onset diabetes after transplantation is a common complication that reduces recipient survival. Research in renal transplant recipients has suggested that pancreatic ß-cell dysfunction, as opposed to insulin resistance, may be the key pathologic process. In this study, clinical and genetic factors associated with new-onset diabetes after transplantation were identified in a white population. A joint analysis approach, with an initial genome-wide association study in a subset of cases followed by de novo genotyping in the complete case cohort, was implemented to identify single-nucleotide polymorphisms (SNPs) associated with the development of new-onset diabetes after transplantation. Clinical variables associated with the development of diabetes after renal transplantation included older recipient age, female sex, and percentage weight gain within 12 months of transplantation. The genome-wide association study identified 26 SNPs associated with new-onset diabetes after transplantation; this association was validated for eight SNPs (rs10484821, rs7533125, rs2861484, rs11580170, rs2020902, rs1836882, rs198372, and rs4394754) by de novo genotyping. These associations remained significant after multivariate adjustment for clinical variables. Seven of these SNPs are associated with genes implicated in ß-cell apoptosis. These results corroborate recent clinical evidence implicating ß-cell dysfunction in the pathophysiology of new-onset diabetes after transplantation and support the pursuit of therapeutic strategies to protect ß cells in the post-transplant period.

Health status and 6 years survival of 552 90+ Italian sib-ships recruited within the EU Project GEHA (GEnetics of Healthy Ageing).

In a scenario of increasing life expectancy worldwide, it is mandatory to identify the characteristics of a healthy aging phenotype, including survival predictors, and to disentangle those related to environment/lifestyle versus those related to familiarity/genetics. To this aim we comprehensively characterised a cohort of 1,160 Italian subjects of 90 years and over (90+, mean age 93 years; age range 90-106 years) followed for 6 years survival, belonging to 552 sib-ships (familiar longevity) recruited (2005-2008) within the EU-funded GEHA project in three Italian geographic areas (Northern, Central and Southern Italy) different for urban/rural and socio-economical characteristics. On the whole, the following factors emerged as significant predictors of survival after 90 years of age: absence of cognitive impairment and physical disability, high hand grip strength scores and body mass index (BMI) values, "excellent/good" self-reported health, high haemoglobin and total cholesterol levels and low creatinine levels. These parameters, excluding BMI values, were also significantly associated within sib-ships, suggesting a strong familial/genetic component. Geographical micro-heterogeneity of survival predictors emerged, such as functional and physical status being more important in Southern than in Central and Northern Italy. In conclusion, we identified modifiable survival predictors related to specific domains, whose role and importance vary according to the geographic area considered and which can help in interpreting the genetic results obtained by the GEHA project, whose major aim is the comprehensive evaluation of phenotypic and genetic data.

An application of bi-directional evolutionary structural optimisation for optimising energy absorbing structures using a material damage model

The Bi-directional Evolutionary Structural Optimisation (BESO) method is a numerical topology optimisation method developed for use in finite element analysis. This paper presents a particular application of the BESO method to optimise the energy absorbing capability of metallic structures. The optimisation objective is to evolve a structural geometry of minimum mass while ensuring that the kinetic energy of an impacting projectile is reduced to a level which prevents perforation. Individual elements in a finite element mesh are deleted when a prescribed damage criterion is exceeded. An energy absorbing structure subjected to projectile impact will fail once the level of damage results in a critical perforation size. It is therefore necessary to constrain an optimisation algorithm from producing such candidate solutions. An algorithm to detect perforation was implemented within a BESO framework which incorporated a ductile material damage model.

Mutational Analysis of the Rhodopsin Gene in Sector Retinitis Pigmentosa

Background: To determine the role of rhodopsin (RHO) gene mutations in patients with sector retinitis pigmentosa (RP) from Northern Ireland.

Design: A case series of sector RP in a tertiary ocular genetics clinic.

Participants: Four patients with sector RP were recruited from the Royal Victoria Hospital (Belfast, Northern Ireland) and Altnagelvin Hospital (Londonderry, Northern Ireland) following informed consent.

Methods: The diagnosis of sector RP was based on clinical examination, International Society for Clinical Electrophysiology of Vision (ISCEV) standard electrophysiology, and visual field analysis. DNA was extracted from peripheral blood leucocytes and the coding regions and adjacent flanking intronic sequences of the RHO gene were polymerase chain reaction (PCR) amplified and cycle sequenced.

Main Outcome Measure: Rhodopsin mutational status.

Results: A heterozygous missense mutation in RHO (c.173C > T) resulting in a non-conservative substitution of threonine to methionine (p. Thr58Met) was identified in one patient and was absent from 360 control individuals. This non-conservative substitution (p.Thr58Met) replaces a highly evolutionary conserved polar hydrophilic threonine residue with a non-polar hydrophobic methionine residue at position 58 near the cytoplasmic border of helix A of RHO.

Conclusions: The study identified a RHO gene mutation (p.Thr58Met) not previously reported in RP in a patient with sector RP. These findings outline the phenotypic variability associated with RHO mutations. It has been proposed that the regional effects of RHO mutations are likely to result from interplay between mutant alleles and other genetic, epigenetic and environmental factors.

Genetics of Diabetic Nephropathy: a Long Road of Discovery

The global prevalence of diabetic nephropathy is rising in parallel with the increasing incidence of diabetes in most countries. Unfortunately, up to 40 % of persons diagnosed with diabetes may develop kidney complications. Diabetic nephropathy is associated with substantially increased risks of cardiovascular disease and premature mortality. An inherited susceptibility to diabetic nephropathy exists, and progress is being made unravelling the genetic basis for nephropathy thanks to international research collaborations, shared biological resources and new analytical approaches. Multiple epidemiological studies have highlighted the clinical heterogeneity of nephropathy and the need for better phenotyping to help define important subgroups for analysis and increase the power of genetic studies. Collaborative genome-wide association studies for nephropathy have reported unique genes, highlighted novel biological pathways and suggested new disease mechanisms, but progress towards clinically relevant risk prediction models for diabetic nephropathy has been slow. This review summarises the current status, recent developments and ongoing challenges elucidating the genetics of diabetic nephropathy.

Pool Evolution: A Parallel Pattern for Evolutionary and Symbolic Computing

We introduce a new parallel pattern derived from a specific application domain and show how it turns out to have application beyond its domain of origin. The pool evolution pattern models the parallel evolution of a population subject to mutations and evolving in such a way that a given fitness function is optimized. The pattern has been demonstrated to be suitable for capturing and modeling the parallel patterns underpinning various evolutionary algorithms, as well as other parallel patterns typical of symbolic computation. In this paper we introduce the pattern, we discuss its implementation on modern multi/many core architectures and finally present experimental results obtained with FastFlow and Erlang implementations to assess its feasibility and scalability.

Molecular pedigree reconstruction and estimation of evolutionary parameters in a wild Atlantic salmon river system with incomplete sampling: a power analysis

Background: Pedigree reconstruction using genetic analysis provides a useful means to estimate fundamental population biology parameters relating to population demography, trait heritability and individual fitness when combined with other sources of data. However, there remain limitations to pedigree reconstruction in wild populations, particularly in systems where parent-offspring relationships cannot be directly observed, there is incomplete sampling of individuals, or molecular parentage inference relies on low quality DNA from archived material. While much can still be inferred from incomplete or sparse pedigrees, it is crucial to evaluate the quality and power of available genetic information a priori to testing specific biological hypotheses. Here, we used microsatellite markers to reconstruct a multi-generation pedigree of wild Atlantic salmon (Salmo salar L.) using archived scale samples collected with a total trapping system within a river over a 10 year period. Using a simulation-based approach, we determined the optimal microsatellite marker number for accurate parentage assignment, and evaluated the power of the resulting partial pedigree to investigate important evolutionary and quantitative genetic characteristics of salmon in the system.

Results: We show that at least 20 microsatellites (ave. 12 alleles/locus) are required to maximise parentage assignment and to improve the power to estimate reproductive success and heritability in this study system. We also show that 1.5 fold differences can be detected between groups simulated to have differing reproductive success, and that it is possible to detect moderate heritability values for continuous traits (h(2) similar to 0.40) with more than 80% power when using 28 moderately to highly polymorphic markers.

Conclusion: The methodologies and work flow described provide a robust approach for evaluating archived samples for pedigree-based research, even where only a proportion of the total population is sampled. The results demonstrate the feasibility of pedigree-based studies to address challenging ecological and evolutionary questions in free-living populations, where genealogies can be traced only using molecular tools, and that significant increases in pedigree assignment power can be achieved by using higher numbers of markers.