Combined next‐generation sequencing and morphology reveal fine‐scale speciation in Crocodile Skinks (Squamata: Scincidae: Tribolonotus)

Next‐generation sequencing has vast potential to revolutionize the fields of phylogenetics and population genetics through its ability to collect genomic scale data sets of thousands of orthologous loci. Despite this potential, other types of data (e.g. morphology, ecology) remain important, particularly for studies endeavouring to delimit species. Here, we integrate next‐generation sequencing with morphology to examine divergence between populations of Tribolonotus pseudoponceleti on the islands of Buka and Bougainville in the Solomon Archipelago. We used the Ion Torrent PGM to collect over 648 Mbp of sequence data for 12 samples, representing 1526 loci recovered from all samples, and 3342 were recovered from at least six samples. Genetic structure analyses strongly support the distinctiveness of these two populations, and Bayes factor delimitations decisively select speciation between Buka and Bougainville. Principal components and discriminant function analyses reveal concordant morphological divergence. Finally, demographic analyses via diffusion approximation and approximate Bayesian computation prefer a complex model of mid‐Pleistocene divergence with migration, and a later decrease or cessation of migration and population size shift, suggesting a scenario in which migration was enabled by Pleistocene merging of these two islands, and limited when isolated by higher sea levels. Further analysis of four Sanger sequenced loci in IMa2 had limited power to distinguish among models including and excluding migration, but resulted in similar population size and divergence time estimates, although with much broader confidence intervals. This study represents a framework for how next‐generation sequencing and morphological data can be combined and leveraged towards validating putative species and testing demographic scenarios for speciation.     

Best Linear Unbiased Prediction (BLUP) for regional yield trials: a comparison to additive main effects and multiplicative interaction (AMMI) analysis

Multilocation trials are often used to analyse the adaptability of genotypes in different environments and to find for each environment the genotype that is best adapted; i.e. that is highest yielding in that environment. For this purpose, it is of interest to obtain a reliable estimate of the mean yield of a cultivar in a given environment. This article compares two different statistical estimation procedures for this task: the Additive Main Effects and Multiplicative Interaction (AMMI) analysis and Best Linear Unbiased Prediction (BLUP). A modification of a cross validation procedure commonly used with AMMI is suggested for trials that are laid out as a randomized complete block design. The use of these procedure is exemplified using five faba bean datasets from German registration trails. BLUP was found to outperform AMMI in four of five faba bean datasets.     

Proposed minimum reporting standards for chemical analysis

There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at or . Further, community input related to this document can also be provided via this electronic forum. The contents of this paper do not necessarily reflect any position of the Government or the opinion of the Food and Drug Administration Sponsor: Metabolomics Society http://www.metabolomicssociety.org/ Reference: http://msi-workgroups.sourceforge.net/bio-metadata/reporting/pbc/ http://msi-workgroups.sourceforge.net/chemical-analysis/ Version: Revision: 5.1 Date: 09 January, 2007     

Prediction of herbage yield in grassland: How well do Ellenberg N‐values perform?

Question: How useful are Ellenberg N‐values for predicting the herbage yield of Central European grasslands in comparison to approaches based on ordination scores of plant species composition or on soil parameters? Location: Central Germany (11°00′‐11°37’E, 50°21‐50°34’N, 500–840 m a.s.l.). Methods: Based on data from a field survey in 2001, the following models were constructed for predicting herbage yield in montane Central European grasslands: (1) Linear regression of mean Ellenberg N‐, R‐ and F‐values; (2) Linear regression of ordination scores derived from Non‐metric Multidimensional Scaling (NMDS) of vegetation data; and (3) Multiple linear regression (MLR) of soil variables. Models were evaluated by cross‐validation and validation with additional data collected in 2002. Results: Best predictions were obtained with models based on species composition. Ellenberg N‐values and NMDS scores performed equally well and better than models based on Ellenberg R‐ or F‐values. Predictions based on soil variables were least accurate. When tested with data from 2002, models based on Ellenberg N‐values or on NMDS scores accurately predicted productivity rank order of sites, but not the actual herbage yield of particular sites. Conclusions: Mean Ellenberg N‐values, which are easy to calculate, are as accurate as ordination scores in predicting herbage yield from plant species composition. In contrast, models based on soil variables may be useful for generating hypotheses about the factors limiting herbage yield, but not for prediction. We support the view that Ellenberg N‐values should be called productivity values rather than nitrogen values.     

Validation of Fecal Glucocorticoid Metabolite Assays for South African Herbivores

ABSTRACT Fecal glucocorticoid metabolite (FGM) assays are a popular means of monitoring adrenocortical activity (i.e., physiological stress response) in wildlife. Species-specific differences in glucocorticoid metabolism and excretion require assay validation, including both laboratory and biological components, before assay use in new species. We validated a commercially available radioimmunoassay (MP ¹²⁵I corticosterone RIA kit [MP Biomedicals, Solon, OH]) for measuring FGMs of several South African herbivores, including giraffe (Giraffa camelopardalis), impala (Aepyceros melampus), nyala (Tragelaphus buxtoni), kudu (Tragelaphus strepsiceros), wildebeest (Connochaetes taurinus), and zebra (Equus burchelli). These herbivores are important in South African parks and reserves for ecotourism and as a prey base for predators and serve an integral role in ecosystem processes. Standard biochemical validations (e.g., recovery of exogenous corticosterone, intra- and interassay variation, and parallelism) demonstrated that the assay accurately and precisely measured FGMs of all 6 herbivore species. Our biological validations demonstrated that the assay was sensitive enough to detect changes in FGM production associated with season. Samples collected during the dry season (Jun-Aug) contained higher FGM concentrations than those from the wet season (Dec-Feb) in all species. We established optimal sample dilutions and reference FGM levels for these 6 herbivores, which can now be used to monitor the effects of management and ecotourism activities on the stress responses of these herbivores.     

Cryo‐EM model validation using independent map reconstructions

An increasing number of cryo‐electron microscopy (cryo‐EM) density maps are being generated with suitable resolution to trace the protein backbone and guide sidechain placement. Generating and evaluating atomic models based on such maps would be greatly facilitated by independent validation metrics for assessing the fit of the models to the data. We describe such a metric based on the fit of atomic models with independent test maps from single particle reconstructions not used in model refinement. The metric provides a means to determine the proper balance between the fit to the density and model energy and stereochemistry during refinement, and is likely to be useful in determining values of model building and refinement metaparameters quite generally.     

流域水碳过程耦合模拟——WaSSI-C模型的率定与检验

在复杂的气候变化条件下, 利用水碳耦合模型进行生态水文学研究成为主要的研究手段和途径。该文以杂谷脑河上游流域为例, 在确定生态水文模型WaSSI-C模拟尺度的基础上, 探讨水碳耦合模型在中国西南湿润地区的适用性。杂古脑河上游流域位于岷江上游, 隶属于长江流域。在分析和讨论了模型结构和机理的基础上, 分别对模型蒸散和融雪计算进行了补充改进, 以提高模型的适用性。将1988-1996年作为模型的率定期, 1997-2006年作为模型的验证期, 分别在率定期和验证期利用实测的径流数据和中分辨率成像光谱仪数据的总初级生产力、蒸散(ET)数据, 对模拟结果进行对比验证。并利用决定系数(R²)和Nash-Sutcliffe效率系数(NS)两个指标对模拟效果进行评价。流域总径流率定期和验证期对比验证的R²分别为0.86和0.78; NS分别为0.82和0.67。总生态系统生产力和ET验证期的R²分别为0.89和0.78。可见模型模拟结果的两个评价指标都处于较为理想的区间内, 说明WaSSI-C模型在研究区内具有较好的适用性。并对模型的蒸散计算方法进行了讨论, 在此基础上提出了模型中存在的问题和改进的方向。     

Comparative immunological characterization of various photosynthetic cytochromes c from pro- and eukaryotic algae

Photosynthetic c-type cytochromes isolated from various pro- and eukaryotic algae have been compared by an immunochemical method. Thereby the extent of cross-reactivity of several cytochromes with antisera to cytochrome c from Spirulina platensis, Bumilleriopsis filiformis, and Scenedesmus acutus was quantitatively determined by antigen-binding tests. When immunological relationship is taken as a measure of structural relationship, the following conclusions can be drawn: (1) c-type cytochromes from Anabaena variabilis, Nostoc muscorum, Calothrix membranacea, and Spirulina platensis show large differences in cross-reactivity. (2) The acidic Spirulina cytochrome c is fairly closely related to the two eukaryotic cytochromes assayed here.Abbreviations SAUG Sammlung von Algenkulturen am Pflanzenphysiologischen Institut der Universität Göttingen, FRG - PCC Pasteur Culture Collection     

Neurogenomics of speech and language disorders: the road ahead

Next-generation sequencing is set to transform the discovery of genes underlying neurodevelopmental disorders, and so offer important insights into the biological bases of spoken language. Success will depend on functional assessments in neuronal cell lines, animal models and humans themselves.