PedGenie: an analysis approach for genetic association testing in extended pedigrees and genealogies of arbitrary size

Background  

We present a general approach to perform association analyses in pedigrees of arbitrary size and structure, which also allows for a mixture of pedigree members and independent individuals to be analyzed together, to test genetic markers and qualitative or quantitative traits. Our software, PedGenie, uses Monte Carlo significance testing to provide a valid test for related individuals that can be applied to any test statistic, including transmission disequilibrium statistics. Single locus at a time, composite genotype tests, and haplotype analyses may all be performed. We illustrate the validity and functionality of PedGenie using simulated and real data sets. For the real data set, we evaluated the role of two tagging-single nucleotide polymorphisms (tSNPs) in the DNA repair gene, NBS1, and their association with female breast cancer in 462 cases and 572 controls selected to be BRCA1/2 mutation negative from 139 high-risk Utah breast cancer families.     

Social structures and social relations--an archaeological and anthropological examination of three early Medieval separate burial sites in Bavaria

As part of an interdisciplinary cooperation, three early medieval separated burial sites from central Bavaria were subjected to archaeological and anthropological examinations. Separated burial sites are probably an expression of social stratification. This paper focuses on two characteristic aspects of these separated burial sites: (1) structure of the site, and (2) biological manifestation of a social upper class. The separated burial grounds Etting/Sandfeld (31 individuals), Grossmehring (44 individuals) and Kelheim (43 individuals), all located in southern Bavaria, were analyzed. Sex and age at death of all individuals were determined, and dietary behaviour was reconstructed by means of carbon and nitrogen isotope ratios in bone collagen. Local conditions such as climate, soil conditions or the intensity of agriculture can provoke significant variations in plant delta15N-values, which could lead to a shift of the baseline values of the corresponding trophic web. To facilitate the comparison of isotopic data from different sites, delta15N values of cattle bones were taken as a reference for the human data (presuming the diet to consumer chain). The results of dietary reconstruction indicate that the populations enjoyed very good living conditions with a primarily animal protein-based diet. Furthermore, the isotope analysis revealed more detailed indications for certain individuals regarding their social status. Some individuals can even be appointed as possible chiefs of the population, since anthropological and archaeological interpretations were in total agreement: It was possible to identify persons of a higher social status based on the structure of the burial site, grave goods and the isotopic analysis.     

swinger: a user‐friendly computer program to establish captive breeding groups that minimize relatedness without pedigree information

Captive breeding programmes are often a necessity for the continued persistence of a population or species. They typically have the goal of maintaining genetic diversity and minimizing inbreeding. However, most captive breeding programmes have been based on the assumption that the founding breeders are unrelated and outbred, even though in situ anthropogenic impacts often mean these founders may have high relatedness and substantial inbreeding. In addition, polygamous group‐breeding species in captivity often have uncertain pedigrees, making it difficult to select the group composition for subsequent breeding. Molecular‐based estimates of relatedness and inbreeding may instead be used to select breeding groups (≥two individuals) that minimize relatedness and filter out inbred individuals. swinger constructs breeding groups based on molecular estimates of relatedness and inbreeding. The number of possible combinations of breeding groups quickly becomes intractable by hand. swinger was designed to overcome this major issue in ex situ conservation biology. The user can specify parameters within swinger to reach breeding solutions that suit the mating system of the target species and available resources. We provide evidence of the efficiency of the software with an empirical example and using simulations. The only data required are a typical molecular marker data set, such as a microsatellite or SNP data set, from which estimates of inbreeding and pairwise relatedness may be obtained. Such molecular data sets are becoming easier to gather from non‐model organisms with next‐generation sequencing technology. swinger is an open‐source software with a user‐friendly interface and is available at http://www.molecularecology.flinders.edu.au/molecular-ecology-lab/software/swinger/swinger/ and https://github.com/Yuma248/Swinger .     

Hemoglobin A1C,Mean Glucose,and Persistence of Glycation Ratios in Insulin-Treated Diabetes

ObjectiveDetermine the relationship between mean glucose (MG), as assessed by continuous glucose monitoring (CGM), and hemoglobin A_1c (A1C) in insulin-requiring adults in a clinical practice setting and examine the persistence of this relationship over time.MethodsIn this retrospective record review in a diabetes practice, a linear regression model was developed using data sets from all patients with ≥ 1 available download of a Dexcom SevenPlus CGM device in which there was > 50% utilization in the 60 days prior to a laboratory A1C. Persistence of the MG to A1C relationship was examined in patients with ≥ 2 data sets available.ResultsA total of 139 patients had ≥ 1 data set available for evaluation, and 101 patients had ≥ 2 data sets (range, 2 to 6; total, 279). The slope of the MG versus A1C curve was 19.5 mg/dL for each 1% change in A1C, with an intercept of 17.7 mg/dL. Although 88% of the measured MG values were within 15% of the A1C-predicted MG, there was substantial variation in individuals, with differences as large as ± 26%. The MG to A1C (MG:A1C) ratio, which is a measure of glycation, was normally distributed, with a median of 21.6. Spearman correlation coefficients for the MG:A1C ratio on repeated measures ranged from 0.52 to 0.73, demonstrating persistence.ConclusionThe relationship between MG and A1C is linear in a population but can vary between individuals. The MG:A1C ratio was normally distributed, tended to persist in individuals over time, and thus could be useful to identify apparent high and low glycators. Glycemic goals may need to be modified in such patients. (Endocr Pract. 2014;20:252-260)     

Les tranchées des Capucins de Ferrières (Martigues,Bouches-du-Rhône,France). Un charnier de l’épidémie de peste de 1720 à 1722 en Provence

We present the global results of the rescue excavation of a burial place linked to the plague epidemic that affected Provence in 1720–1722. The inhumation area, which is in Martigues (“Bouches-du-Rhône” County), consists of five parallel trenches corresponding to as many burials. While the observed funerary customs are all succinct, we could identify some slight nuances in the layout of the corpses’ interment. These variations seem to reflect a fluctuation of epidemic intensity. On the whole, 208 skeletons were collected on the site. This osteoarchaeological series increases the available data from the rescue excavation of another burial place due to the same epidemic in Martigues at the beginning of the 18th century: the “Délos” site (39 individuals).     

ABC inference of multi‐population divergence with admixture from unphased population genomic data

Rapidly developing sequencing technologies and declining costs have made it possible to collect genome‐scale data from population‐level samples in nonmodel systems. Inferential tools for historical demography given these data sets are, at present, underdeveloped. In particular, approximate Bayesian computation (ABC) has yet to be widely embraced by researchers generating these data. Here, we demonstrate the promise of ABC for analysis of the large data sets that are now attainable from nonmodel taxa through current genomic sequencing technologies. We develop and test an ABC framework for model selection and parameter estimation, given histories of three‐population divergence with admixture. We then explore different sampling regimes to illustrate how sampling more loci, longer loci or more individuals affects the quality of model selection and parameter estimation in this ABC framework. Our results show that inferences improved substantially with increases in the number and/or length of sequenced loci, while less benefit was gained by sampling large numbers of individuals. Optimal sampling strategies given our inferential models included at least 2000 loci, each approximately 2 kb in length, sampled from five diploid individuals per population, although specific strategies are model and question dependent. We tested our ABC approach through simulation‐based cross‐validations and illustrate its application using previously analysed data from the oak gall wasp, Biorhiza pallida.     

Allozymes and nDNA markers show different levels of population differentiation in the mussel Mytilus?edulis on British coasts

In order to test the hypothesis that natural selection can be operating on allozymes, six nuclear DNA markers were used to study population structure in six Mytilus edulis (Linnaeus, 1758) populations around the British Isles and the results compared with previous allozyme data from the same (two sites) or very close localities (the other four sites). Allozymes and nDNA markers show significant differentiation between populations at the P < 0.01 level, with the exception of the nDNA marker PLIIa. The results also indicate significant differences (modified version of the Lewontin–Krakauer test) between the two sets of markers which are about one order of magnitude higher for nDNA than for the allozyme loci. The bootstrap analysis was carried out to correct for the possibility that this difference is a sample size artefact. These results are consistent with the operation of balancing selection on allozymes or on loci in linkage disequilibrium with them. Handling editor: C. Sturmbauer     

Burial rates and stoichiometry of sedimentary carbon,nitrogen and phosphorus in Midwestern US reservoirs

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Robust Prediction of Expression Differences among Human Individuals Using Only Genotype Information

Many genetic variants that are significantly correlated to gene expression changes across human individuals have been identified, but the ability of these variants to predict expression of unseen individuals has rarely been evaluated. Here, we devise an algorithm that, given training expression and genotype data for a set of individuals, predicts the expression of genes of unseen test individuals given only their genotype in the local genomic vicinity of the predicted gene. Notably, the resulting predictions are remarkably robust in that they agree well between the training and test sets, even when the training and test sets consist of individuals from distinct populations. Thus, although the overall number of genes that can be predicted is relatively small, as expected from our choice to ignore effects such as environmental factors and trans sequence variation, the robust nature of the predictions means that the identity and quantitative degree to which genes can be predicted is known in advance. We also present an extension that incorporates heterogeneous types of genomic annotations to differentially weigh the importance of the various genetic variants, and we show that assigning higher weights to variants with particular annotations such as proximity to genes and high regional G/C content can further improve the predictions. Finally, genes that are successfully predicted have, on average, higher expression and more variability across individuals, providing insight into the characteristics of the types of genes that can be predicted from their cis genetic variation.     

When less can yield more – Computational preprocessing of MS/MS spectra for peptide identification

The effectiveness of database search algorithms, such as Mascot, Sequest and ProteinPilot is limited by the quality of the input spectra: spurious peaks in MS/MS spectra can jeopardize the correct identification of peptides or reduce their score significantly. Consequently, an efficient preprocessing of MS/MS spectra can increase the sensitivity of peptide identification at reduced file sizes and run time without compromising its specificity. We investigate the performance of 25 MS/MS preprocessing methods on various data sets and make software for improved preprocessing of mgf/dta‐files freely available from http://hci.iwr.uni‐heidelberg.de/mip/proteomics or http://www.childrenshospital.org/research/steenlab .     

hapConstructor: automatic construction and testing of haplotypes in a Monte Carlo framework

SUMMARY: Haplotypes carry important information that can direct investigators towards underlying susceptibility variants, and hence multiple tagging single nucleotide polymorphisms (tSNPs) are usually studied in candidate gene association studies. However, it is often unknown which SNPs should be included in haplotype analyses, or which tests should be performed for maximum power. We have developed a program, hapConstructor, which automatically builds multi-locus SNP sets to test for association in a case-control framework. The multi-SNP sets considered need not be contiguous; they are built based on significance. An important feature is that the missing data imputation is carried out based on the full data, for maximal information and consistency. HapConstructor is implemented in a Monte Carlo framework and naturally extends to allow for significance testing and false discovery rates that account for the construction process and to related individuals. HapConstructor is a useful tool for exploring multi-locus associations in candidate genes and regions. AVAILABILITY: http://www-genepi.med.utah.edu/Genie.     

Parameterizing Spatial Models of Infectious Disease Transmission that Incorporate Infection Time Uncertainty Using Sampling-Based Likelihood Approximations

A class of discrete-time models of infectious disease spread, referred to as individual-level models (ILMs), are typically fitted in a Bayesian Markov chain Monte Carlo (MCMC) framework. These models quantify probabilistic outcomes regarding the risk of infection of susceptible individuals due to various susceptibility and transmissibility factors, including their spatial distance from infectious individuals. The infectious pressure from infected individuals exerted on susceptible individuals is intrinsic to these ILMs. Unfortunately, quantifying this infectious pressure for data sets containing many individuals can be computationally burdensome, leading to a time-consuming likelihood calculation and, thus, computationally prohibitive MCMC-based analysis. This problem worsens when using data augmentation to allow for uncertainty in infection times. In this paper, we develop sampling methods that can be used to calculate a fast, approximate likelihood when fitting such disease models. A simple random sampling approach is initially considered followed by various spatially-stratified schemes. We test and compare the performance of our methods with both simulated data and data from the 2001 foot-and-mouth disease (FMD) epidemic in the U.K. Our results indicate that substantial computation savings can be obtained—albeit, of course, with some information loss—suggesting that such techniques may be of use in the analysis of very large epidemic data sets.     

Non-homogeneous models of sequence evolution in the Bio++ suite of libraries and programs

Background  

Accurately modeling the sequence substitution process is required for the correct estimation of evolutionary parameters, be they phylogenetic relationships, substitution rates or ancestral states; it is also crucial to simulate realistic data sets. Such simulation procedures are needed to estimate the null-distribution of complex statistics, an approach referred to as parametric bootstrapping, and are also used to test the quality of phylogenetic reconstruction programs. It has often been observed that homologous sequences can vary widely in their nucleotide or amino-acid compositions, revealing that sequence evolution has changed importantly among lineages, and may therefore be most appropriately approached through non-homogeneous models. Several programs implementing such models have been developed, but they are limited in their possibilities: only a few particular models are available for likelihood optimization, and data sets cannot be easily generated using the resulting estimated parameters.     

CoaSim: A flexible environment for simulating genetic data under coalescent models

Background  

Coalescent simulations are playing a large role in interpreting large scale intra-specific sequence or polymorphism surveys and for planning and evaluating association studies. Coalescent simulations of data sets under different models can be compared to the actual data to test the importance of different evolutionary factors and thus get insight into these.     

Twenty-five thousand-year-old triple burial from Dolní Věstonice: An ice-age family?

In 1986 a palaeolithic triple burial was discovered near Dolní Věstonice (Czech Republic). The occurrence of anatomic variants in all three skeletons gave rise to speculations that the buried individuals may have been closely related. To test this hypothesis the skeletons were submitted to a systematic kinship analysis based on odontologic and other non-metric traits. Statistical tests showed that the coincident occurrence of several rare traits in the individuals is highly unlikely to occur at random. This and further data included in the analysis therefore suggest that the three individuals buried together were genetically related and actually belonged to one family. Am J Phys Anthropol 102:123–131. © 1997 Wiley-Liss, Inc.     

Rarity in large data sets: Singletons,modal values and the location of the species abundance distribution

Species abundance data in 12 large data sets, holding 10 × 10³ to 125 × 10⁶ individuals in 350 to 10 × 10³ samples, were studied. Samples and subsets, for instance the summarized data of samples over years, and whole sets were analysed. Two methods of the binning of data, assigning abundance values to classes for histograms, have been applied in the past: bins of equal size and bins of exponentially increasing size (‘octaves’). A hump in a histogram with exponential bins does not represent a mode of primary, non-transformed abundance values, but of log transformed abundance values. A proper interpretation of the hump is given. Moreover, the extrapolation to the left of a histogram with exponential bins, below an abundance of unity, lifting a ‘veil’, hiding species present in the community but absent from the sample, is rejected. The literature is confusing at these points and, as a result, prevents a proper view on the species abundance distribution. Applying bins of equal size, modal values equalled or approached unity. The number of singletons increased with sample size in some data sets but decreased in others. However, singletons remain present in large samples, subsets or sets, in agreement with the results on modal values. The relatively high number of singletons in small samples is no artefact of undersampling. The mode at unity, that is at the left end of the species abundance distribution, independent of scale (sample, subset or set), is an important statistical property of the species abundance distribution. Our results may have implications for theory development in community ecology: the selection and/or development of an accurate species abundance model, and, connected to this, the formulation of improved assembly rules, and the selection and/or development of more precise species richness estimators.     

Hybrid dynamics in a species group of swallowtail butterflies

Hybrid zones provide unique natural laboratories for studying mechanisms of evolution. But identification and classification of hybrid individuals (F1, F2, backcross, etc.) can be complicated by real population changes over time as well as by use of different marker types, both of which challenge documentation of hybrid dynamics. Here, we use multiple genetic markers (mitochondrial DNA, microsatellites and genomewide single nucleotide polymorphisms) to re‐examine population structure in a hybrid zone between two species of swallowtail butterflies in western Canada, Papilio machaon and P. zelicaon. Our aim was to test whether their hybrid dynamics remain the same as found 30 years ago using morphology and allozymes, and we compared different genetic data sets as well as alternative hybrid identification and classification methods. Overall, we found high differentiation between the two parental species, corroborating previous research from the 1980s. We identified fewer hybrid individuals in the main zone of hybridization in recent years, but this finding depended on the genetic markers considered. Comparison of methods with simulated data sets generated from our data showed that single nucleotide polymorphisms were more powerful than microsatellites for both hybrid identification and classification. Moreover, substantial variation among comparisons underlined the value of multiple markers and methods for documenting evolutionarily dynamic systems.     

Comparative study of gene set enrichment methods

Background  

The analysis of high-throughput gene expression data with respect to sets of genes rather than individual genes has many advantages. A variety of methods have been developed for assessing the enrichment of sets of genes with respect to differential expression. In this paper we provide a comparative study of four of these methods: Fisher's exact test, Gene Set Enrichment Analysis (GSEA), Random-Sets (RS), and Gene List Analysis with Prediction Accuracy (GLAPA). The first three methods use associative statistics, while the fourth uses predictive statistics. We first compare all four methods on simulated data sets to verify that Fisher's exact test is markedly worse than the other three approaches. We then validate the other three methods on seven real data sets with known genetic perturbations and then compare the methods on two cancer data sets where our a priori knowledge is limited.     

Unraveling hierarchical genetic structure in a marine metapopulation: A comparison of three high‐throughput genotyping approaches

Marine metapopulations often exhibit subtle population structure that can be difficult to detect. Given recent advances in high‐throughput sequencing, an emerging question is whether various genotyping approaches, in concert with improved sampling designs, will substantially improve our understanding of genetic structure in the sea. To address this question, we explored hierarchical patterns of structure in the coral reef fish Elacatinus lori using a high‐resolution approach with respect to both genetic and geographic sampling. Previously, we identified three putative E. lori populations within Belize using traditional genetic markers and sparse geographic sampling: barrier reef and Turneffe Atoll; Glover's Atoll; and Lighthouse Atoll. Here, we systematically sampled individuals at ~10 km intervals throughout these reefs (1,129 individuals from 35 sites) and sequenced all individuals at three sets of markers: 2,418 SNPs; 89 microsatellites; and 57 nonrepetitive nuclear loci. At broad spatial scales, the markers were consistent with each other and with previous findings. At finer spatial scales, there was new evidence of genetic substructure, but our three marker sets differed slightly in their ability to detect these patterns. Specifically, we found subtle structure between the barrier reef and Turneffe Atoll, with SNPs resolving this pattern most effectively. We also documented isolation by distance within the barrier reef. Sensitivity analyses revealed that the number of loci (and alleles) had a strong effect on the detection of structure for all three marker sets, particularly at small spatial scales. Taken together, these results illustrate empirically that high‐throughput genotyping data can elucidate subtle genetic structure at previously‐undetected scales in a dispersive marine fish.