Vegetation classification,mapping, and monitoring at Voyageurs National Park,Minnesota: An application of the U.S. National Vegetation Classification

Question: How can the U.S. National Vegetation Classification (USNVC) serve as an effective tool for classifying and mapping vegetation, and inform assessments and monitoring? Location: Voyageurs National Park, northern Minnesota, U.S.A and environs. The park contains 54 243 ha of terrestrial habitat in the sub-boreal region of North America. Methods: We classified and mapped the natural vegetation using the USNVC, with ‘alliance’and ‘association’as base units. We compiled 259 classification plots and 1251 accuracy assessment test plots. Both plot and type ordinations were used to analyse vegetation and environmental patterns. Color infrared aerial photography (1:15840 scale) was used for mapping. Polygons were manually drawn, then transferred into digital form. Classification and mapping products are stored in publicly available databases. Past fire and logging events were used to assess distribution of forest types. Results and Discussion: Ordination and cluster analyses confirmed 49 associations and 42 alliances, with three associations ranked as globally vulnerable to extirpation. Ordination provided a useful summary of vegetation and ecological gradients. Overall map accuracy was 82.4%. Pinus banksiana - Picea mariana forests were less frequent in areas unburned since the 1930s. Conclusion: The USNVC provides a consistent ecological tool for summarizing and mapping vegetation. The products provide a baseline for assessing forests and wetlands, including fire management. The standardized classification and map units provide local to continental perspectives on park resources through linkages to state, provincial, and national classifications in the U.S. and Canada, and to NatureServe's Ecological Systems classification.     

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence,full structure,and active site microenvironment similarity

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods.     

Predator and detritivore niche width helps to explain biocomplexity of experimental detritus-based food webs in four aquatic and terrestrial ecosystems

In the study of food webs, the existence and explanation of recurring patterns, such as the scale invariance of linkage density, predator–prey ratios and mean chain length, constitute long-standing issues. Our study focused on litter-associated food webs and explored the influence of detritivore and predator niche width (as δ¹³C range) on web topological structure. To compare patterns within and between aquatic and terrestrial ecosystems and take account of intra-habitat variability, we constructed 42 macroinvertebrate patch-scale webs in four different habitats (lake, lagoon, beech forest and cornfield), using an experimental approach with litterbags. The results suggest that although web differences exist between ecosystems, patterns are more similar within than between aquatic and terrestrial web types. In accordance with optimal foraging theory, we found that the niche width of predators and prey increased with the number of predators and prey taxa as a proportion of total taxa in the community. The tendency was more marked in terrestrial ecosystems and can be explained by a lower per capita food level than in aquatic ecosystems, particularly evident for predators. In accordance with these results, the number of links increased with the number of species but with a significantly sharper regression slope for terrestrial ecosystems. As a consequence, linkage density, which was found to be directly correlated to niche width, increased with the total number of species in terrestrial webs, whereas it did not change significantly in aquatic ones, where connectance scaled negatively with the total number of species. In both types of ecosystem, web robustness to rare species removal increased with connectance and the niche width of predators. In conclusion, although limited to litter-associated macroinvertebrate assemblages, this study highlights structural differences and similarities between aquatic and terrestrial detrital webs, providing field evidence of the central role of niche width in determining the structure of detritus-based food webs and posing foraging optimisation constraints as a general mechanistic explanation of food web complexity differences within and between ecosystem types.     

Molecular investigation of mental retardation locus gene PRSS12 by linkage analysis

The present study was carried out to determine the prevalence of families having mental retardation in Pakistani population. We enrolled seven mentally retarded (MR) families with two or more affected individuals. Family history was taken to minimize the chances of other abnormalities. Pedigrees were drawn using the Cyrillic software (version 2.1). The structure of pedigrees shows that all the marriages are consanguineous and the families have recessive mode of inheritance. All the families were studied by linkage analysis to mental retardation locus (MRT1)/gene PRSS12. Three STR markers (D4S191, D4S2392, and D4S3024) in vicinity of mental retardation (MR) locus (MRT1)/gene PRSS12 were amplified on all the sample of each family by PCR. The PCR products were then genotyped on non denaturing polyacrylamide gel electrophoresis (PAGE). The Haplotype were constructed to determine the pattern of inheritance and also to determine that a family was linked or unlinked to gene PRSS12. One out of the seven families was potentially linked to gene PRSS12, while the other six families remain unlinked.     

利用与PKD1紧密连锁的微卫星多态性对黑龙江省汉族人群进行ADPKD的症前诊断

目的：利用与PKD1紧密连锁的微卫星的多态性对黑龙江省汉族人群常染色体显性遗传性多裳肾病（autosomal dominant polycystic diseaseADPKD）家系成员进行症状前诊断。方法：扩增PKD1基因内部（KG8）及基因两侧（AC2．5、CW4）共三个微卫星遗传标记,并采用聚丙烯酰胺凝胶电泳进行检测,银染,最后进行家系连锁分析。结果：家系1中一名男孩携带了PKD1突变基因,处于发病前期。结论：通过连锁分析ADPKD进行连锁分析能高效、快捷、准确地进行早期诊断.     

Haplotype structure and phylogenetic shadowing of a hypervariable region in the CAPN10 gene

It has been proposed that variation in calpain 10 (CAPN10) contributes to the risk of type 2 diabetes (T2D). A previous survey of CAPN10 in ethnically diverse populations revealed an intronic region with a significant excess of polymorphism levels relative to inter-species sequence divergence, suggesting that this region was the target of long-standing balancing selection. Based on the thrifty genotype hypothesis, variation that increases risk to T2D in contemporary humans at one time conferred a survival advantage in ancestral populations. Thus, the signature of positive natural selection in a T2D candidate gene could identify a genomic region containing variation that influences disease susceptibility. Here, we investigate this hypothesis by re-sequencing the CAPN10 region with unusual polymorphism levels in T2D cases and controls (n=91) from a Mexican American (MA) population, and by using networks to infer the evolutionary relationships between the major haplotypes. Haplotype tag SNPs (htSNPs) were then selected in each population sample and in MA cases and controls. By placing the htSNPs on the haplotype network, we investigate how cross-population differences in CAPN10 genetic architecture may affect the detection of the disease association. Interestingly, despite the small scale of our case-control study, we observe a nearly significant signal of association between T2D and variation in the putative target of balancing selection. Finally, we use phylogenetic shadowing across 10 primate species to search for conserved non-coding elements that may affect the expression and function of CAPN10. These elements are postulated to be the targets of long-standing balancing selection.     

Effective size of populations under partial inbreeding and selection on a set of linked additive genes

The prediction theory of effective population size (Ne) is extended to cover selection on a set of linked additive genes and partial inbreeding (partial selfing or partial full-sib mating). Ne under selection is generally expressed as a function of the cumulative change in frequency of a neutral gene due to the random association between the neutral and selected genes generated by finite sampling. In this study, the association under partial selfing was classified into two types, the association between the neutral and selected genes on the same gamete, and the association between the neutral and selected genes each on the different gametes in the same parent. For partial full-sib mating, an additional association, i.e., the association between the neutral and selected genes each in the different parents in the same family, was included in the model. According to this classification of the association, the coefficient accounting for the cumulative change in frequency of the neutral gene was partitioned into two or three components. A method for computing the partitioned coefficients was obtained from the transition matrix approach, in which the joint effect of linkage, selection and partial inbreeding was taken into account. To assess the joint effects of linkage, selection and partial inbreeding on Ne, numerical computations with the obtained expressions were carried out. The effect of linkage on Ne was generally small, except for an extremely small genome size, while the partial inbreeding resulted in a drastic reduction in Ne. For a given genome size, Ne was essentially independent of the length and number of chromosomes. Some of these results were verified by stochastic simulations.     

A population-based LD map of the human chromosome 6p

The recent publication of the complete sequence of human chromosome 6 provides a platform from which to investigate genomic sequence variation. We report here a detailed linkage disequilibrium (LD) pattern map across the entire human chromosome 6p by using a set of 1152 single nucleotide polymorphisms (SNPs) in a population of 198 Singaporean Chinese, with 326 SNPs focused in the major histocompatibility complex (MHC) region. Our analysis shows some unexpectedly high segments of strong LD in a 10-Mb region that includes the extremely polymorphic and gene-rich MHC loci and many non-MHC genes. These include the telomeric peri-MHC region that harbors olfactory receptors, histones and zinc finger clusters, and the centromeric peri-MHC region that contains several unknown open reading frames. The data also help refine a human–mouse synteny break in the region between 28.6 and 29.4 Mb. The population-based LD map presented here will provide an essential resource for understanding the genomic sequence variation of chromosome 6p and LD mapping of disease genes of complex genetic traits. Electronic supplementary material Electronic supplementary material is available for this article at and accessible for authorised users. H. Yu and J.-M. Chia should be regarded as joint first authors.     

Conditional likelihood score functions for mixed models in linkage analysis

In this paper, we develop a general strategy for linkage analysis, applicable for arbitrary pedigree structures and genetic models with one major gene, polygenes and shared environmental effects. Extending work of Whittemore (1996), McPeek (1999) and Hossjer (2003d), the efficient score statistic is computed from a conditional likelihood of marker data given phenotypes. The resulting semiparametric linkage analysis is very similar to nonparametric linkage based on affected individuals. The efficient score S depends not only on identical-by-descent sharing and phenotypes, but also on a few parameters chosen by the user. We focus on (1) weak penetrance models, where the major gene has a small effect and (2) rare disease models, where the major gene has a possibly strong effect but the disease causing allele is rare. We illustrate our results for a large class of genetic models with a multivariate Gaussian liability. This class incorporates one major gene, polygenes and shared environmental effects in the liability, and allows e.g. binary, Gaussian, Poisson distributed and life-length phenotypes. A detailed simulation study is conducted for Gaussian phenotypes. The performance of the two optimal score functions S(wpairs) and S(normdom) are investigated. The conclusion is that (i) inclusion of polygenic effects into the score function increases overall performance for a wide range of genetic models and (ii) score functions based on the rare disease assumption are slightly more powerful.