Genetic diversity and population structure in multiple Chinese goat populations using a SNP panel

Information about genetic diversity and population structure among goat breeds is essential for genetic improvement, understanding of environmental adaptation as well as utilization and conservation of goat breeds. Here, we measured genetic diversity and population structure in multiple Chinese goat populations, namely, Nanjiang, Qinggeda, Arbas Cashmere, Jining Grey, Luoping Yellow and Guangfeng goats. A total of 193 individuals were genotyped for about 47 401 autosomal single nucleotide polymorphisms (SNPs). We found a high proportion of informative SNPs, ranging from 69.5% in the Luoping Yellow to 93.9% in the Jining Grey goat breeds with an average mean of 84.7%. Diversity, as measured by expected heterozygosity, ranged from 0.371 in Luoping Yellow to 0.405 in Jining Grey goat populations. The average estimated pair‐wise genetic differentiation (F_ST) among the populations was 8.6%, ranging from 0.2% to 16% and indicating low to moderate genetic differentiation. Principal component analysis, genetic structure and phylogenetic tree analysis revealed a clustering of six Chinese goat populations according to geographic distribution. The results from this study can contribute valuable genetic information and can properly assist with within‐breed diversity, which provides a good opportunity for sustainable utilization of and maintenance of genetic resource improvements in the Chinese goat populations.     

Human population genetic structure and inference of group membership

A major goal of biomedical research is to develop the capability to provide highly personalized health care. To do so, it is necessary to understand the distribution of interindividual genetic variation at loci underlying physical characteristics, disease susceptibility, and response to treatment. Variation at these loci commonly exhibits geographic structuring and may contribute to phenotypic differences between groups. Thus, in some situations, it may be important to consider these groups separately. Membership in these groups is commonly inferred by use of a proxy such as place-of-origin or ethnic affiliation. These inferences are frequently weakened, however, by use of surrogates, such as skin color, for these proxies, the distribution of which bears little resemblance to the distribution of neutral genetic variation. Consequently, it has become increasingly controversial whether proxies are sufficient and accurate representations of groups inferred from neutral genetic variation. This raises three questions: how many data are required to identify population structure at a meaningful level of resolution, to what level can population structure be resolved, and do some proxies represent population structure accurately? We assayed 100 Alu insertion polymorphisms in a heterogeneous collection of approximately 565 individuals, approximately 200 of whom were also typed for 60 microsatellites. Stripped of identifying information, correct assignment to the continent of origin (Africa, Asia, or Europe) with a mean accuracy of at least 90% required a minimum of 60 Alu markers or microsatellites and reached 99%-100% when >/=100 loci were used. Less accurate assignment (87%) to the appropriate genetic cluster was possible for a historically admixed sample from southern India. These results set a minimum for the number of markers that must be tested to make strong inferences about detecting population structure among Old World populations under ideal experimental conditions. We note that, whereas some proxies correspond crudely, if at all, to population structure, the heuristic value of others is much higher. This suggests that a more flexible framework is needed for making inferences about population structure and the utility of proxies.     

Genetic polymorphism analysis of mitochondrial DNA from Chinese Xinjiang Kazak ethnic group by a novel mitochondrial DNA genotyping panel

Molecular Biology Reports - Genetic polymorphism analysis of 60 mitochondrial DNA (mtDNA) loci in Chinese Xinjiang Kazak group was conducted in this study. Blood samples from 141...     

Effects of information and group structure on evolution of altruism: analysis of two-score model by covariance and contextual analyses

An altruistic individual has to gamble on cooperation to a stranger because it does not know whether the stranger is trustworthy before direct interaction. Nowak and Sigmund (Nature 393 (1998a) 573; J. Theor. Biol. 194 (1998b) 561) presented a new theoretical framework of indirect reciprocal altruism by image scoring game where all individuals are informed about a partner's behavior from its image score without direct interaction. Interestingly, in a simplified version of the image scoring game, the evolutionarily stability condition for altruism became a similar form of Hamilton's rule, i.e. inequality that the probability of getting correct information is more than the ratio of cost to benefit. Since the Hamilton's rule was derived by evolutionarily stable analysis, the evolutionary meaning of the probability of getting correct information has not been clearly examined in terms of kin and group selection. In this study, we applied covariance analysis to the two-score model for deriving the Hamilton's rule. We confirmed that the probability of getting correct information was proportional to the bias of altruistic interactions caused by using information about a partner's image score. The Hamilton's rule was dependent on the number of game bouts even though the information reduced the risk of cooperation to selfish one at the first encounter. In addition, we incorporated group structure to the two-score model to examine whether the probability of getting correct information affect selection for altruism by group selection. We calculated a Hamilton's rule of group selection by contextual analysis. Group selection is very effective when either the probability of getting correct information or that of future interaction, or both are low. The two Hamilton's rules derived by covariance and contextual analyses demonstrated the effects of information and group structure on the evolution of altruism. We inferred that information about a partner's behavior and group structure can produce flexible pathways for the evolution of altruism.     

Genetic and physical analyses of group E exo- mutants of Rhizobium meliloti

Mutants of Rhizobium meliloti which are deficient in exopolysaccharide synthesis have been classified into six different genetic groups (A through F) (J. A. Leigh, E. R. Signer, and G. C. Walker, Proc. Natl. Acad. Sci. USA 82:6231-6235, 1985). Using physical and genetic techniques, we have demonstrated that the group E Exo- mutants carry deletions in the exoA-exoB region of the megaplasmid pRmeSU47b. We have constructed strains carrying defined deletions which remove up to 200 kilobases of pRmeSU47b, including the exoA-exoB region. These derivatives have the same phenotypes as do the group E mutants.     

2-Deoxyribose 5-phosphate aldolase: Genetic analyses of structure

A total of 33 mutant strains of Salmonella typhimurium deficient in deoxyribose 5-phosphate activity have been isolated and characterized as missense or nonsense. Three-factor transductional analyses of the mutants were used to construct a fine structure map of the deoC gene, which codes for a peptide of 28,500 molecular weight. An unusual clustering of the missense mutants was observed, where 75% of all the missense mutants mapped in an area which corresponds to 19% of the total gene length. It is suggested that this area of the protein is particularly sensitive to amino acid replacements but that other areas of the protein are reasonably tolerant of such changes. Nonsense mutations are found scattered throughout the gene. This is expected since the carboxyl-terminal tyrosine is essential for enzymatic activity.     

Genetic structure of phenotypic robustness in the collaborative cross mouse diallel panel

Developmental stability and canalization describe the ability of developmental systems to minimize phenotypic variation in the face of stochastic micro‐environmental effects, genetic variation and environmental influences. Canalization is the ability to minimize the effects of genetic or environmental effects, whereas developmental stability is the ability to minimize the effects of micro‐environmental effects within individuals. Despite much attention, the mechanisms that underlie these two components of phenotypic robustness remain unknown. We investigated the genetic structure of phenotypic robustness in the collaborative cross (CC) mouse reference population. We analysed the magnitude of fluctuating asymmetry (FA) and among‐individual variation of cranial shape in reciprocal crosses among the eight parental strains, using geometric morphometrics and a diallel analysis based on a Bayesian approach. Significant differences among genotypes were found for both measures, although they were poorly correlated at the level of individuals. An overall positive effect of inbreeding was found for both components of variation. The strain CAST/EiJ exerted a positive additive effect on FA and, to a lesser extent, among‐individual variance. Sex‐ and other strain‐specific effects were not significant. Neither FA nor among‐individual variation was associated with phenotypic extremeness. Our results support the existence of genetic variation for both developmental stability and canalization. This finding is important because robustness is a key feature of developmental systems. Our finding that robustness is not related to phenotypic extremeness is consistent with theoretical work that suggests that its relationship to stabilizing selection is not straightforward.     

生命信息安全控制体系整体结构性构建与分析

在前期生命信息安全控制原理探讨的基础上,基于整体论的思考,旨在构思能表述生命信息安全控制体系实质内涵的几何图形。所作图呈圆台形,自上而下依次为2大部分(内在部分和外延部分),5个层次(特异性识别系统、泛特异性识别系统、皮肤黏膜、共生微生物及外环境开放接触面)。在圆台形生命信息安全控制体系中,圆台形的中心轴为生命信息安全控制轴;特异性识别系统、泛特异性识别系统、皮肤、黏膜和共生微生物组成内在部分;外延部分即外环境开放接触面;内在部分各部间以及与外延部分之间存在物质、能量、信息交流沟通传递的空间界面。特异性识别系统建立在泛特异性识别系统基础上,置于最顶端,寓意着生物进化高级发展的一种客观结局,泛特异性识别系统与特异性识别系统作为一个整体和共生微生物层次联系,其中安插皮肤、黏膜组织层次,符合宏生物与微生物之间存在的完全不可分割的相关关系客观事实。共生微生物层次举足轻重,所占份额最大,主导整个体系的稳定性,成为整个体系的基座。就上述5个层次及其相互关系的解析归纳,证明构建的圆台形几何图能真实客观反映出生命信息安全控制体系各层次之间完全不可分割、相互依存影响的关系。     

Genetic analyses of a seasonal interval timer

Seasonal clocks (e.g., circannual clocks, seasonal interval timers) permit anticipation of regularly occurring environmental events by timing the onset of seasonal transitions in reproduction, metabolism, and behavior. Implicit in the concept that seasonal clocks reflect adaptations to the local environment is the unexamined assumption that heritable genetic variance exists in the critical features of such clocks, namely, their temporal properties. These experiments quantified the intraspecific variance in, and heritability of, the photorefractoriness interval timer in Siberian hamsters (Phodopus sungorus), a seasonal clock that provides temporal information to mechanisms that regulate seasonal transitions in body weight. Twenty-seven families consisting of 54 parents and 109 offspring were raised in a long-day photoperiod and transferred as adults to an inhibitory photoperiod (continuous darkness; DD). Weekly body weight measurements permitted specification of the interval of responsiveness to DD, a reflection of the duration of the interval timer, in each individual. Body weights of males and females decreased after exposure to DD, but 3 to 5 months later, somatic recrudescence occurred, indicative of photorefractoriness to DD. The interval timer was approximately 5 weeks longer and twice as variable in females relative to males. Analyses of variance of full siblings revealed an overall intraclass correlation of 0.71 +/- 0.04 (0.51 +/- 0.10 for male offspring and 0.80 +/- 0.06 for female offspring), suggesting a significant family resemblance in the duration of interval timers. Parent-offspring regression analyses yielded an overall heritability estimate of 0.61 +/- 0.2; h(2) estimates from parent-offspring regression analyses were significant for female offspring (0.91 +/- 0.4) but not for male offspring (0.35 +/- 0.2), indicating strong additive genetic components for this trait, primarily in females. In nature, individual differences, both within and between sexes, in the timekeeping properties of seasonal interval timers, and a strong heritable basis thereof, would provide ample substrate for selection to rapidly influence seasonal clocks. Balancing selection in environments where the onset of spring conditions varies from year to year could maintain genetic variance in interval timers and yield interval timers tuned to the local environment.     

Unifying life-history analyses for inference of fitness and population growth

The lifetime fitnesses of individuals comprising a population determine its numerical dynamics, and genetic variation in fitness results in evolutionary change. This dual importance of individual fitness is well understood, but empirical fitness records generally violate the assumptions of standard statistical approaches. This problem has undermined comprehensive study of fitness and impeded empirical synthesis of the numerical and genetic dynamics of populations. Recently developed aster models remedy this problem by explicitly modeling the dependence of later-expressed components of fitness (e.g., fecundity) on those expressed earlier (e.g., survival to reproduce). Moreover, aster models employ different sampling distributions for different components of fitness (e.g., binomial for survival over a given interval and Poisson for fecundity). Analysis is done by maximum likelihood, and the resulting distributions for lifetime fitness closely approximate observed data. We illustrate the breadth of aster models' utility with three examples demonstrating estimation of the finite rate of increase, comparison of mean fitness among genotypic groups, and analysis of phenotypic selection. Aster models offer a unified approach to addressing the breadth of questions in evolution and ecology for which life-history data are gathered.     

Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering

Pedigree and sibship reconstruction are important methods in quantifying relationships and fitness of individuals in natural populations. Current methods employ a Markov chain‐based algorithm to explore plausible possible pedigrees iteratively. This provides accurate results, but is time‐consuming. Here, we develop a method to infer sibship and paternity relationships from half‐sibling arrays of known maternity using hierarchical clustering. Given 50 or more unlinked SNP markers and empirically derived error rates, the method performs as well as the widely used package Colony, but is faster by two orders of magnitude. Using simulations, we show that the method performs well across contrasting mating scenarios, even when samples are large. We then apply the method to open‐pollinated arrays of the snapdragon Antirrhinum majus and find evidence for a high degree of multiple mating. Although we focus on diploid SNP data, the method does not depend on marker type and as such has broad applications in nonmodel systems.     

Combining Bayes classification and point group symmetry under Boolean framework for enhanced protein quaternary structure inference

Our ability to infer the protein quaternary structure automatically from atom and lattice information is inadequate, especially for weak complexes, and heteromeric quaternary structures. Several approaches exist, but they have limited performance. Here, we present a new scheme to infer protein quaternary structure from lattice and protein information, with all-around coverage for strong, weak and very weak affinity homomeric and heteromeric complexes. The scheme combines naive Bayes classifier and point group symmetry under Boolean framework to detect quaternary structures in crystal lattice. It consistently produces ≥90% coverage across diverse benchmarking data sets, including a notably superior 95% coverage for recognition heteromeric complexes, compared with 53% on the same data set by current state-of-the-art method. The detailed study of a limited number of prediction-failed cases offers interesting insights into the intriguing nature of protein contacts in lattice. The findings have implications for accurate inference of quaternary states of proteins, especially weak affinity complexes.     

Genetic diversity and structure in a natural Elymus caninus population from Denmark based on microsatellite and isozyme analyses

 Genetic diversity in a natural Elymus caninus population from Denmark was assessed using isozyme and microsatellite markers. A total of 119 individuals from 46 maternal plants were assayed. Microsatellite loci are shown to display higher levels of variation than isozyme loci. The mean number of alleles per locus was 1.04 for isozymes and 1.38 for microsatellites. The percentage of polymorphic loci for isozymes and microsatellites was 4.7% and 23.6% across the maternal plant, respectively. The genetic diversity at population level was 0.1 for isozymes, and 0.63 for microsatellites. The mean genetic diversity at maternal plant level was 0.027 for isozyme loci and 0.117 for microsatellite loci. The average of total allozyme diversity (H_T) was 0.22. The average of total microsatellite diversity was 0.56. Isozyme and microsatellite variation showed the same pattern of differentiation between maternal plants. More than 75% total genetic diversity was found among maternal plants. About 25% total genetic diversity was detected within maternal plants. Ten (22.7%) maternal plants produced heterozygous offspring at allozyme loci, and 30 (68.2%) maternal plants gave heterozygous offspring at microsatellite loci. Both types of markers revealed a relatively high genetic diversity in this population. Received November 7, 2000 Accepted February 15, 2001     

Hierarchical structure of the Sicilian goats revealed by Bayesian analyses of microsatellite information

Genetic structure and relationship amongst the main goat populations in Sicily (Girgentana, Derivata di Siria, Maltese and Messinese) were analysed using information from 19 microsatellite markers genotyped on 173 individuals. A posterior Bayesian approach implemented in the program STRUCTURE revealed a hierarchical structure with two clusters at the first level (Girgentana vs. Messinese, Derivata di Siria and Maltese), explaining 4.8% of variation (amova Ф_ST estimate). Seven clusters nested within these first two clusters (further differentiations of Girgentana, Derivata di Siria and Maltese), explaining 8.5% of variation (amova Ф_SC estimate). The analyses and methods applied in this study indicate their power to detect subtle population structure.     

Inferring weak population structure with the assistance of sample group information

Genetic clustering algorithms require a certain amount of data to produce informative results. In the common situation that individuals are sampled at several locations, we show how sample group information can be used to achieve better results when the amount of data is limited. New models are developed for the structure program, both for the cases of admixture and no admixture. These models work by modifying the prior distribution for each individual's population assignment. The new prior distributions allow the proportion of individuals assigned to a particular cluster to vary by location. The models are tested on simulated data, and illustrated using microsatellite data from the CEPH Human Genome Diversity Panel. We demonstrate that the new models allow structure to be detected at lower levels of divergence, or with less data, than the original structure models or principal components methods, and that they are not biased towards detecting structure when it is not present. These models are implemented in a new version of structure which is freely available online at http://pritch.bsd.uchicago.edu/structure.html.     

Genetic inference of orchid colonization of a Costa Rican lava flow

The dispersal and colonization of plant populations allow species to occupy novel habitats, migrate, and undergo range shifts in response to changing environmental factors and, as such, are fundamental ecological processes for ensuring the long-term persistence of species. Natural landscape disturbance often generates habitats available for colonization. Patterns of colonization and population expansion can be inferred from the levels and partitioning of genetic variation of plant populations with known disturbance histories, such as recent volcanic eruptions. We sampled and mapped 496 individuals from two populations of the colonizing terrestrial orchid, Sobralia chrysostoma, on the 1992 lava flow of Volcán Arenal in central Costa Rica. We used neutral co-dominant markers to genotype individuals and estimate population genetic statistics. Both populations had high mean levels of genetic diversity (P = 100%; AP = 3.31; H_e = 0.259) suggesting that the lava flow was colonized by numerous individuals that likely originated from multiple source populations. However, significant spatial genetic structure (SGS) was only present in one population at the smallest distance class (≤2 m) and was low (r = 0.032). That these large and genetically diverse populations had such low SGS and an absence of SGS, respectively is contrary to expectations and differs significantly from the pattern in Epidendrum radicans (Orchidaceae), with which S. chrysostoma is growing sympatrically. Our results suggest that these two populations either consist primarily of immigrant individuals or that seeds produced in situ dispersed over longer distances, thereby producing larger seed shadows and greater overlap of seed shadows.     

Genetic structure and linkage disequilibrium pattern of a rapeseed (Brassica napus L.) association mapping panel revealed by microsatellites

Understanding the population structure and linkage disequilibrium (LD) is a prerequisite for association mapping of complex traits in a target population. In this study, we assessed the genetic diversity, population structure and the extent of LD in a panel of 192 inbred lines of Brassica napus from all over the world using 451 single-locus microsatellite markers. The inbred lines could be divided into P1 and P2 groups by a model-based population structure analysis. Out of the 142 inbred lines in the P1 group, 126 lines were from China and Japan, and the remaining 16 lines were from Europe, Canada and Australia. In the P2 group, 33 out of the 50 lines were from Europe, Canada, and Australia, and the remaining 17 lines were from China. Structure analysis further divided each group into two subgroups. AMOVA, pairwise F (ST) and neutrality analyses confirmed the differentiation between groups and subgroups. More than 80 % of the pairwise kinship estimates between inbred lines were <0.05, indicating that relative kinship is weak in our panel. Only 6 % linked marker pairs showed LD, suggesting the low level of LD in this association panel. The LD decayed within 0.5-1 cM at the genome level, and varied considerably across each group and subgroup, due to the population size, genetic background and genetic drift. The characterization of the population structure and LD patterns would be useful for performing association studies for complex agronomic traits in rapeseed.     

Linkage disequilibrium and inference of ancestral recombination in 538 single-nucleotide polymorphism clusters across the human genome

The prospect of using linkage disequilibrium (LD) for fine-scale mapping in humans has attracted considerable attention, and, during the validation of a set of single-nucleotide polymorphisms (SNPs) for linkage analysis, a set of data for 4,833 SNPs in 538 clusters was produced that provides a rich picture of local attributes of LD across the genome. LD estimates may be biased depending on the means by which SNPs are first identified, and a particular problem of ascertainment bias arises when SNPs identified in small heterogeneous panels are subsequently typed in larger population samples. Understanding and correcting ascertainment bias is essential for a useful quantitative assessment of the landscape of LD across the human genome. Heterogeneity in the population recombination rate, rho=4Nr, along the genome reflects how variable the density of markers will have to be for optimal coverage. We find that ascertainment-corrected rho varies along the genome by more than two orders of magnitude, implying great differences in the recombinational history of different portions of our genome. The distribution of rho is unimodal, and we show that this is compatible with a wide range of mixtures of hotspots in a background of variable recombination rate. Although rho is significantly correlated across the three population samples, some regions of the genome exhibit population-specific spikes or troughs in rho that are too large to be explained by sampling. This result is consistent with differences in the genealogical depth of local genomic regions, a finding that has direct bearing on the design and utility of LD mapping and on the National Institutes of Health HapMap project.     

Genetic diversity and trait genomic prediction in a pea diversity panel

Background

Pea (Pisum sativum L.), a major pulse crop grown for its protein-rich seeds, is an important component of agroecological cropping systems in diverse regions of the world. New breeding challenges imposed by global climate change and new regulations urge pea breeders to undertake more efficient methods of selection and better take advantage of the large genetic diversity present in the Pisum sativum genepool. Diversity studies conducted so far in pea used Simple Sequence Repeat (SSR) and Retrotransposon Based Insertion Polymorphism (RBIP) markers. Recently, SNP marker panels have been developed that will be useful for genetic diversity assessment and marker-assisted selection.

Results

A collection of diverse pea accessions, including landraces and cultivars of garden, field or fodder peas as well as wild peas was characterised at the molecular level using newly developed SNP markers, as well as SSR markers and RBIP markers. The three types of markers were used to describe the structure of the collection and revealed different pictures of the genetic diversity among the collection. SSR showed the fastest rate of evolution and RBIP the slowest rate of evolution, pointing to their contrasted mode of evolution. SNP markers were then used to predict phenotypes -the date of flowering (BegFlo), the number of seeds per plant (Nseed) and thousand seed weight (TSW)- that were recorded for the collection. Different statistical methods were tested including the LASSO (Least Absolute Shrinkage ans Selection Operator), PLS (Partial Least Squares), SPLS (Sparse Partial Least Squares), Bayes A, Bayes B and GBLUP (Genomic Best Linear Unbiased Prediction) methods and the structure of the collection was taken into account in the prediction. Despite a limited number of 331 markers used for prediction, TSW was reliably predicted.

Conclusion

The development of marker assisted selection has not reached its full potential in pea until now. This paper shows that the high-throughput SNP arrays that are being developed will most probably allow for a more efficient selection in this species.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1266-1) contains supplementary material, which is available to authorized users.