Albumin Yanomama-2, a ‘private’ polymorphism of serum albumin

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65429/1/j.1469-1809.1974.tb01949.x.pd

Testing the Mantel statistic with a spatially‐constrained permutation procedure

International audience1. Mantel tests are widely used in ecology to assess the significance of the relationship between two distance matrices computed between pairs of samples. However, recent studies demonstrated that the presence of spatial autocorrelation in both distance matrices induced inflations of parameter estimates and type I error rates. These results also hold for partial Mantel test which is supposed to control for the spatial structures. 2. To address the issue of spatial autocorrelation in testing the Mantel statistic, we developed a new procedure based on spatially constrained randomizations using Moran spectral randomization. A simulation study was conducted to assess the performance of this new procedure. Different scenarios were considered by manipulating the number of variables, the number of samples, the regularity of the sampling design and the level of spatial autocorrelation. 3. As identified by previous studies, we found that Mantel statistic and its associated type I error rate are inflated in simple and partial Mantel tests when both distances matrices are spatially structured. We showed that these biases increased with the number of variables, decreased with the number of samples and were slightly lower for regular than irregular sampling. The new procedure succeeded in correcting the spurious inflations of the parameter estimates and type I error rates in any of the presented scenarios. 4. Our results suggest that studies from several fields (e.g. genetic or community ecology) could have been overestimating the relationship between two distances matrices when both presented spatial autocorrelation. We proposed an alternative solution applicable in every field to correctly compute Mantel statistic with a fair type I error rate

Foraging patterns of acorn woodpeckers (Melanerpes formicivorus) on valley oak (Quercus lobata Née) in two California oak savanna-woodlands

Landscape characteristics and social behavior can affect the foraging patterns of seed-dependent animals. We examine the movement of acorns from valley oak (Quercus lobata) trees to granaries maintained by acorn woodpeckers (Melanerpes formicivorus) in two California oak savanna-woodlands differing in the distribution of Q. lobata within each site. In 2004, we sampled Q. lobata acorns from 16 granaries at Sedgwick Reserve in Santa Barbara County and 18 granaries at Hastings Reserve in Monterey County. Sedgwick has lower site-wide density of Q. lobata than Hastings as well as different frequencies of other Quercus species common to both sites. We found acorn woodpeckers foraged from fewer Q. lobata seed source trees (Kg = 4.1 ± 0.5) at Sedgwick than at Hastings (Kg = 7.6 ± 0.6) and from fewer effective seed sources (Nem* = 2.00 and 5.78, respectively). The differences between sites are due to a greater number of incidental seed sources used per granary at Hastings than at Sedgwick. We also found very low levels of seed source sharing between adjacent granaries, indicating that territoriality is strong at both sites and that each social group forages on its own subset of trees. We discovered an interesting spatial pattern in the location of granaries. At Sedgwick, acorn woodpeckers situated their granaries within areas of higher-than-average tree density, while at Hastings, they placed them within areas of lower-than-average tree density, with the outcome that granaries at the two sites were located in areas of similar valley oak density. Our results illustrate that landscape characteristics might influence the number of trees visited by acorn woodpeckers and the locations of territories, while woodpecker social behavior, such as territoriality, shapes which trees are visited and whether they are shared with other social groups

The self-reported Montgomery-Åsberg depression rating scale is a useful evaluative tool in major depressive disorder

Abstract Background The use of Patient-reported Outcomes (PROs) as secondary endpoints in the development of new antidepressants has grown in recent years. The objective of this study was to assess the psychometric properties of the 9-item, patient-administered version of the Montgomery-Åsberg Depression Rating Scale (MADRS-S). Methods Data from a multicentre, double-blind, 8-week, randomised controlled trial of 278 outpatients diagnosed with Major Depressive Disorder were used to evaluate the validity, reliability and sensitivity to change of the MADRS-S using psychometric methods. A Receiver Operating Characteristic (ROC) curve was plotted to identify the most appropriate threshold to define perceived remission. Results No missing values were found at the item level, indicating good acceptability of the scale. The construct validity was satisfactory: all items contributed to a common underlying concept, as expected. The correlation between MADRS-S and physicians' MADRS was moderate (r = 0.54, p Conclusion Taking account of patient's perceptions of the severity of their own symptoms along with the psychometric properties of the MADRS-S enable its use for evaluative purposes in the development of new antidepressant drugs.</p

Genetic Structure of Bluefin Tuna in the Mediterranean Sea Correlates with Environmental Variables

Abstract Background Atlantic Bluefin Tuna (ABFT) shows complex demography and ecological variation in the Mediterranean Sea. Genetic surveys have detected significant, although weak, signals of population structuring; catch series analyses and tagging programs identified complex ABFT spatial dynamics and migration patterns. Here, we tested the hypothesis that the genetic structure of the ABFT in the Mediterranean is correlated with mean surface temperature and salinity. Methodology We used six samples collected from Western and Central Mediterranean integrated with a new sample collected from the recently identified easternmost reproductive area of Levantine Sea. To assess population structure in the Mediterranean we used a multidisciplinary framework combining classical population genetics, spatial and Bayesian clustering methods and a multivariate approach based on factor analysis. Conclusions FST analysis and Bayesian clustering methods detected several subpopulations in the Mediterranean, a result also supported by multivariate analyses. In addition, we identified significant correlations of genetic diversity with mean salinity and surface temperature values revealing that ABFT is genetically structured along two environmental gradients. These results suggest that a preference for some spawning habitat conditions could contribute to shape ABFT genetic structuring in the Mediterranean. However, further studies should be performed to assess to what extent ABFT spawning behaviour in the Mediterranean Sea can be affected by environmental variation.(undefined

The influence of habitat structure on genetic differentiation in red fox populations in north-eastern Poland

The red fox (Vulpes vulpes) has the widest global distribution among terrestrial carnivore species, occupying most of the Northern Hemisphere in its native range. Because it carries diseases that can be transmitted to humans and domestic animals, it is important to gather information about their movements and dispersal in their natural habitat but it is difficult to do so at a broad scale with trapping and telemetry. In this study, we have described the genetic diversity and structure of red fox populations in six areas of north-eastern Poland, based on samples collected from 2002–2003. We tested 22 microsatellite loci isolated from the dog and the red fox genome to select a panel of nine polymorphic loci suitable for this study. Genetic differentiation between the six studied populations was low to moderate and analysis in Structure revealed a panmictic population in the region. Spatial autocorrelation among all individuals showed a pattern of decreasing relatedness with increasing distance and this was not significantly negative until 93 km, indicating a pattern of isolation-by-distance over a large area. However, there was no correlation between genetic distance and either Euclidean distance or least-cost path distance at the population level. There was a significant relationship between genetic distance and the proportion of large forests and water along the Euclidean distances. These types of habitats may influence dispersal paths taken by red foxes, which is useful information in terms of wildlife disease management

Problems in the assessment of relative risk of chronic disease among biological relatives of affected individuals

A question often asked in regard to a chronic disease is whether the risk to a biological relative of a case is elevated, and if so by how much the risk is altered. To answer this question, data may be collected directly with genetic objectives in mind by ascertaining populations of pedigrees. More often, the initial assessment of the question comes from family history data collected in an incidental manner in the course of a case-control or similar type of study. This paper discusses some limitations to the inferences which can be derived from such casual family history data. These include (i)poor statistical properties of standard relative risk measures, (ii) interpretational problems of observed relative risks when affected cases arise from genetic as well as nongenetic causes and when genes may not always be expressed in individuals in whom they are present, and (iii)confounding effects which may occur when a high risk allele alters the age of onset pattern of the disease. These problems result largely from a loss of design control over the degree of exposure of individuals ascertained and can lead to a small observed relative risk value even when genetic factors are important. Suggestions for handling such casual family history data are offered.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24125/1/0000382.pd

Manifold Learning for Human Population Structure Studies

The dimension of the population genetics data produced by next-generation sequencing platforms is extremely high. However, the “intrinsic dimensionality” of sequence data, which determines the structure of populations, is much lower. This motivates us to use locally linear embedding (LLE) which projects high dimensional genomic data into low dimensional, neighborhood preserving embedding, as a general framework for population structure and historical inference. To facilitate application of the LLE to population genetic analysis, we systematically investigate several important properties of the LLE and reveal the connection between the LLE and principal component analysis (PCA). Identifying a set of markers and genomic regions which could be used for population structure analysis will provide invaluable information for population genetics and association studies. In addition to identifying the LLE-correlated or PCA-correlated structure informative marker, we have developed a new statistic that integrates genomic information content in a genomic region for collectively studying its association with the population structure and LASSO algorithm to search such regions across the genomes. We applied the developed methodologies to a low coverage pilot dataset in the 1000 Genomes Project and a PHASE III Mexico dataset of the HapMap. We observed that 25.1%, 44.9% and 21.4% of the common variants and 89.2%, 92.4% and 75.1% of the rare variants were the LLE-correlated markers in CEU, YRI and ASI, respectively. This showed that rare variants, which are often private to specific populations, have much higher power to identify population substructure than common variants. The preliminary results demonstrated that next generation sequencing offers a rich resources and LLE provide a powerful tool for population structure analysis

Dissimilar responses of fungal and bacterial communities to soil transplantation simulating abrupt climate changes.

Both fungi and bacteria play essential roles in regulating soil carbon cycling. To predict future carbon stability, it is imperative to understand their responses to environmental changes, which is subject to large uncertainty. As current global warming is causing range shifts toward higher latitudes, we conducted three reciprocal soil transplantation experiments over large transects in 2005 to simulate abrupt climate changes. Six years after soil transplantation, fungal biomass of transplanted soils showed a general pattern of changes from donor sites to destination, which were more obvious in bare fallow soils than in maize cropped soils. Strikingly, fungal community compositions were clustered by sites, demonstrating that fungi of transplanted soils acclimatized to the destination environment. Several fungal taxa displayed sharp changes in relative abundance, including Podospora, Chaetomium, Mortierella and Phialemonium. In contrast, bacterial communities remained largely unchanged. Consistent with the important role of fungi in affecting soil carbon cycling, 8.1%-10.0% of fungal genes encoding carbon-decomposing enzymes were significantly (p &lt; 0.01) increased as compared with those from bacteria (5.7%-8.4%). To explain these observations, we found that fungal occupancy across samples was mainly determined by annual average air temperature and rainfall, whereas bacterial occupancy was more closely related to soil conditions, which remained stable 6 years after soil transplantation. Together, these results demonstrate dissimilar response patterns and resource partitioning between fungi and bacteria, which may have considerable consequences for ecosystem-scale carbon cycling

Craniometric Data Supports Demic Diffusion Model for the Spread of Agriculture into Europe

BACKGROUND:The spread of agriculture into Europe and the ancestry of the first European farmers have been subjects of debate and controversy among geneticists, archaeologists, linguists and anthropologists. Debates have centred on the extent to which the transition was associated with the active migration of people as opposed to the diffusion of cultural practices. Recent studies have shown that patterns of human cranial shape variation can be employed as a reliable proxy for the neutral genetic relationships of human populations. METHODOLOGY/PRINCIPAL FINDINGS:Here, we employ measurements of Mesolithic (hunter-gatherers) and Neolithic (farmers) crania from Southwest Asia and Europe to test several alternative population dispersal and hunter-farmer gene-flow models. We base our alternative hypothetical models on a null evolutionary model of isolation-by-geographic and temporal distance. Partial Mantel tests were used to assess the congruence between craniometric distance and each of the geographic model matrices, while controlling for temporal distance. Our results demonstrate that the craniometric data fit a model of continuous dispersal of people (and their genes) from Southwest Asia to Europe significantly better than a null model of cultural diffusion. CONCLUSIONS/SIGNIFICANCE:Therefore, this study does not support the assertion that farming in Europe solely involved the adoption of technologies and ideas from Southwest Asia by indigenous Mesolithic hunter-gatherers. Moreover, the results highlight the utility of craniometric data for assessing patterns of past population dispersal and gene flow