Determination of population structure and stock composition of chum salmon (Oncorhynchus keta) in Russia determined with microsatellites

Variation at 14 microsatellite loci was examined in 34 chum salmon (Oncorhynchus keta) populations from Russia and evaluated for its use in the determination of population structure and stock composition in simulated mixed-stock fishery samples. The genetic differentiation index (Fst) over all populations and loci was 0.017, and individual locus values ranged from 0.003 to 0.054. Regional population structure was observed, and populations from Primorye, Sakhalin Island, and northeast Russia were the most distinct. Microsatellite variation provided evidence of a more fine-scale population structure than those that had previously been demonstrated with other genetic-based markers. Analysis of simulated mixed-stock samples indicated that accurate and precise regional estimates of stock composition were produced when the microsatellites were used to estimate stock compositions. Microsatellites can be used to determine stock composition in geographically separate Russian coastal chum salmon fisheries and provide a greater resolution of stock composition and population structure than that previously provided with other techniques

Protein structure and phenotypic analysis of pathogenic and population missense variants in STXBP1

Background: Syntaxin-binding protein 1, encoded by STXBP1, is highly expressed in the brain and involved in fusing synaptic vesicles with the plasma membrane. Studies have shown that pathogenic loss-of-function variants in this gene result in various types of epilepsies, mostly beginning early in life. We were interested to model pathogenic missense variants on the protein structure to investigate the mechanism of pathogenicity and genotype–phenotype correlations. Methods: We report 11 patients with pathogenic de novo mutations in STXBP1 identified in the first 4293 trios of the Deciphering Developmental Disorder (DDD) study, including six missense variants. We analyzed the structural locations of the pathogenic missense variants from this study and the literature, as well as population missense variants extracted from Exome Aggregation Consortium (ExAC). Results: Pathogenic variants are significantly more likely to occur at highly conserved locations than population variants, and be buried inside the protein domain. Pathogenic mutations are also more likely to destabilize the domain structure compared with population variants, increasing the proportion of (partially) unfolded domains that are prone to aggregation or degradation. We were unable to detect any genotype–phenotype correlation, but unlike previously reported cases, most of the DDD patients with STXBP1 pathogenic variants did not present with very early-onset or severe epilepsy and encephalopathy, though all have developmental delay with intellectual disability and most display behavioral problems and suffered seizures in later childhood. Conclusion: Variants across STXBP1 that cause loss of function can result in severe intellectual disability with or without seizures, consistent with a haploinsufficiency mechanism. Pathogenic missense mutations act through destabilization of the protein domain, making it prone to aggregation or degradation. The presence or absence of early seizures may reflect ascertainment bias in the literature as well as the broad recruitment strategy of the DDD study

Isolation by distance in a population of a small land snail Trochoidea geyeri : evidence from direct and indirect methods

Population structure was estimated in a continuous population of a small land snail (Trochoidea geyeri). Mark-recapture experiments and randomly amplified polymorphic DNA analyses indicate that the population structure can be described by the isolation by distance model of Wright (1946). Estimates of density and dispersal suggest a neighbourhood size of 70-208 individuals on an area of 13-21 m². A principal component analysis of the randomly amplified polymorphic DNA data reveals clinal variation of genetic composition across the population, as predicted by the neighbourhood concept. An analysis of molecular variance indicates substantial genetic structuring. Comparisons of the genetic distances, expressed as euclidean distances among individuals, versus the geographic distance between sampling sites yield a highly significant positive correlation (Mantel test: r = 0.567, p<0.0001). The revealed pattern of populational subdivision on a microgeographic scale seems to be one of the principal processes generating and maintaining genetic diversity within populations of small land gastropods

Population Structure and Cryptic Relatedness in Genetic Association Studies

We review the problem of confounding in genetic association studies, which arises principally because of population structure and cryptic relatedness. Many treatments of the problem consider only a simple ``island'' model of population structure. We take a broader approach, which views population structure and cryptic relatedness as different aspects of a single confounder: the unobserved pedigree defining the (often distant) relationships among the study subjects. Kinship is therefore a central concept, and we review methods of defining and estimating kinship coefficients, both pedigree-based and marker-based. In this unified framework we review solutions to the problem of population structure, including family-based study designs, genomic control, structured association, regression control, principal components adjustment and linear mixed models. The last solution makes the most explicit use of the kinships among the study subjects, and has an established role in the analysis of animal and plant breeding studies. Recent computational developments mean that analyses of human genetic association data are beginning to benefit from its powerful tests for association, which protect against population structure and cryptic kinship, as well as intermediate levels of confounding by the pedigree.Comment: Published in at http://dx.doi.org/10.1214/09-STS307 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Investigating the population structure of Xanthomonas citri pv. citri. Which molecular markers to use to distinguish between low polymorphic bacterial populations? : [P-96]

Comprehensive knowledge of pathogen population structures is crucial to understand the epidemiology and history of infectious diseases, but such data is largely unavailable for plant pathogenic bacteria. This constitutes a challenge for genetically monomorphic bacteria. #Xanthomonas citri# pv. #citri#, which causes asiatic citrus canker, a major disease and potential threat of citrus worldwide, is listed as a quarantine organism in many countries. Analysis of the molecular epidemiology of this bacterium is hindered by a lack of molecular typing techniques suitable for surveillance and outbreak investigation. We report a comparative evaluation of two typing techniques, insertion sequence ligation-mediated PCR (IS-LM-PCR) typing and multilocus variable-number tandem-repeat analysis (MLVA), in terms of the information derived from the techniques and their effectiveness for analysis of genetic and population structure of 557 strains of #X. citri# pv. #citri# originating from Vietnam. The results were as follows: (1) a higher level of polymorphism was observed for MLVA as shown by the greater number of haplotypes and the higher value of Simpson's index of diversity for MLVA data; (2) Pairwise correlations between genetic distances among individual strains or pairwise population genetic differentiation were highly significant for two typing methods; (3) The two molecular markers yielded similar phylogenetic trees and population structure of #X. citri# pv. #citri# in Vietnam. These results provide guidance for the effective use of these molecular methods in the genetic analysis and epidemiology of #Xanthomonas citri# pv. #citri# at different temporal or spatial scales. (Résumé d'auteur

Optimal Population Coding, Revisited

Cortical circuits perform the computations underlying rapid perceptual decisions within a few dozen milliseconds with each neuron emitting only a few spikes. Under these conditions, the theoretical analysis of neural population codes is challenging, as the most commonly used theoretical tool &#x2013; Fisher information &#x2013; can lead to erroneous conclusions about the optimality of different coding schemes. Here we revisit the effect of tuning function width and correlation structure on neural population codes based on ideal observer analysis in both a discrimination and reconstruction task. We show that the optimal tuning function width and the optimal correlation structure in both paradigms strongly depend on the available decoding time in a very similar way. In contrast, population codes optimized for Fisher information do not depend on decoding time and are severely suboptimal when only few spikes are available. In addition, we use the neurometric functions of the ideal observer in the classification task to investigate the differential coding properties of these Fisher-optimal codes for fine and coarse discrimination. We find that the discrimination error for these codes does not decrease to zero with increasing population size, even in simple coarse discrimination tasks. Our results suggest that quite different population codes may be optimal for rapid decoding in cortical computations than those inferred from the optimization of Fisher information

Towards the Human Genotope

The human genotope is the convex hull of all allele frequency vectors that can be obtained from the genotypes present in the human population. In this paper we take a few initial steps towards a description of this object, which may be fundamental for future population based genetics studies. Here we use data from the HapMap Project, restricted to two ENCODE regions, to study a subpolytope of the human genotope. We study three different approaches for obtaining informative low-dimensional projections of this subpolytope. The projections are specified by projection onto few tag SNPs, principal component analysis, and archetypal analysis. We describe the application of our geometric approach to identifying structure in populations based on single nucleotide polymorphisms

Landscape genetics reveal broad and fine‐scale population structure due to landscape features and climate history in the northern leopard frog (Rana pipiens) in North Dakota

Prehistoric climate and landscape features play large roles structuring wildlife populations. The amphibians of the northern Great Plains of North America present an opportunity to investigate how these factors affect colonization, migration, and current population genetic structure. This study used 11 microsatellite loci to genotype 1,230 northern leopard frogs (Rana pipiens) from 41 wetlands (30 samples/wetland) across North Dakota. Genetic structure of the sampled frogs was evaluated using Bayesian and multivariate clustering methods. All analyses produced concordant results, identifying a major east–west split between two R. pipiens population clusters separated by the Missouri River. Substructuring within the two major identified population clusters was also found. Spatial principal component analysis (sPCA) and variance partitioning analysis identified distance, river basins, and the Missouri River as the most important landscape factors differentiating R. pipiens populations across the state. Bayesian reconstruction of coalescence times suggested the major east– west split occurred ~13–18 kya during a period of glacial retreat in the northern Great Plains and substructuring largely occurred ~5–11 kya during a period of extreme drought cycles. A range‐wide species distribution model (SDM) for R. pipiens was developed and applied to prehistoric climate conditions during the Last Glacial Maximum (21 kya) and the mid‐Holocene (6 kya) from the CCSM4 climate model to identify potential refugia. The SDM indicated potential refugia existed in South Dakota or further south in Nebraska. The ancestral populations of R. pipiens in North Dakota may have inhabited these refugia, but more sampling outside the state is needed to reconstruct the route of colonization. Using microsatellite genotype data, this study determined that colonization from glacial refugia, drought dynamics in the northern Great Plains, and major rivers acting as barriers to gene flow were the defining forces shaping the regional population structure of R. pipiens in North Dakota