Molecular,genetic and evolutionary analysis of a paracentric inversion in Arabidopsis thaliana

Chromosomal inversions can provide windows onto the cytogenetic, molecular, evolutionary and demographic histories of a species. Here we investigate a paracentric 1.17‐Mb inversion on chromosome 4 of Arabidopsis thaliana with nucleotide precision of its borders. The inversion is created by Vandal transposon activity, splitting an F‐box and relocating a pericentric heterochromatin segment in juxtaposition with euchromatin without affecting the epigenetic landscape. Examination of the RegMap panel and the 1001 Arabidopsis genomes revealed more than 170 inversion accessions in Europe and North America. The SNP patterns revealed historical recombinations from which we infer diverse haplotype patterns, ancient introgression events and phylogenetic relationships. We find a robust association between the inversion and fecundity under drought. We also find linkage disequilibrium between the inverted region and the early flowering Col‐FRIGIDA allele. Finally, SNP analysis elucidates the origin of the inversion to South‐Eastern Europe approximately 5000 years ago and the FRI‐Col allele to North‐West Europe, and reveals the spreading of a single haplotype to North America during the 17th to 19th century. The ‘American haplotype’ was identified from several European localities, potentially due to return migration.     

Extensive Phylogenetic Analysis of a Soil Bacterial Community Illustrates Extreme Taxon Evenness and the Effects of Amplicon Length,Degree of Coverage,and DNA Fractionation on Classification and Ecological Parameters

To thoroughly investigate the bacterial community diversity present in a single composite sample from an agricultural soil and to examine potential biases resulting from data acquisition and analytical approaches, we examined the effects of percent G+C DNA fractionation, sequence length, and degree of coverage of bacterial diversity on several commonly used ecological parameters (species estimation, diversity indices, and evenness). We also examined variation in phylogenetic placement based on multiple commonly used approaches (ARB alignments and multiple RDP tools). The results demonstrate that this soil bacterial community is highly diverse, with 1,714 operational taxonomic units demonstrated and 3,555 estimated (based on the Chao1 richness estimation) at 97% sequence similarity using the 16S rRNA gene. The results also demonstrate a fundamental lack of dominance (i.e., a high degree of evenness), with 82% of phylotypes being encountered three times or less. The data also indicate that generally accepted cutoff values for phylum-level taxonomic classification might not be as applicable or as general as previously assumed and that such values likely vary between prokaryotic phyla or groups.Efforts to describe bacterial species richness and diversity have long been hampered by the inability to cultivate the vast majority of bacteria from natural environments. New methods to study bacterial diversity have been developed in the last two decades (32), many of which rely on PCR-based procedures and phylogenetic comparison of 16S rRNA gene sequences. However, PCR using complex mixtures of templates (as in the case of total microbial community DNA) is presumed to preferentially amplify certain templates in the mixture (23) based on their primary sequence, percent G+C (hereafter GC) content, or other factors, resulting in so-called PCR bias. Moreover, the amplification of template sequences depends on their initial concentration and tends to skew detection toward the most abundant members of the community (23). To further complicate matters, subsequent random cloning steps on amplicon mixtures are destined to result in the detection of numerically dominant sequences, especially where relative abundance can vary over orders of magnitude. Indeed, any analysis based on random encounter is destined to primarily detect numerically dominant populations. This is especially of concern where limited sampling is performed on highly complex microbial communities exhibiting mostly even distribution of populations with only a few showing any degree of dominance, as typically perceived for soils (17). These artifacts and sampling limitations represent major hurdles in bacterial community diversity analysis, since the vast majority of bacterial diversity probably lies in “underrepresented minority” populations (24, 30). This is important because taxa that are present only in low abundance may still perform important ecosystem functions (e.g., ammonia-oxidizing bacteria). Of special concern is that biases in detection might invalidate hypothesis testing on complex communities where limited sampling is performed (5).Recently, there has been a concerted effort toward addressing problems impeding comprehensive bacterial diversity studies (7, 13, 24, 26, 28). In recent years, studies have increased sequencing efforts, with targeted 16S rRNA gene sequence libraries approaching 2,000 clones (11) and high-throughput DNA-sequencing efforts (e.g., via 454 pyrosequencing and newer-generation high-throughput approaches) of up to 149,000 templates from one or a few samples (25, 30). These technological advances have come as researchers recognize that massive sequencing efforts are required to accurately assess the diversity of populations that comprise complex microbial communities (29, 30). Alternatively, where fully aligned sequence comparisons need to be made, novel experimental strategies that allow more-comprehensive detection of underrepresented bacterial taxa can be applied. One such approach involves the application of prefractionation of total bacterial community genomic DNA based on its GC content (hereafter GC fractionation) prior to subsequent molecular manipulations of total community DNA (14). This strategy has been successfully applied in combination with denaturing gradient gel electrophoresis (13) and 16S rRNA gene cloning (2, 21) to study microbial communities. This approach separates community genomic DNA, prior to any PCR, into fractions of similar percent GC content, effectively reducing the overall complexity of the total community DNA mixture by physical separation into multiple fractions. This facilitates PCR amplification, cloning, and detection of sequences in fractions with relatively low abundance in the community, thereby enhancing the detection of minority populations (13). Collectively, this strategy reduces the biases introduced by PCR amplification and random cloning of the extremely complex mixtures of templates of different GC content, primary sequence, and relative abundance present in total environmental genomic DNA.Any large molecular survey that relies on sequencing further requires the analysis of large amounts of data that must be catalogued into phylogenetically relevant groups. This is usually done using high-throughput methods like RDP Classifier or Sequence Match (6) or a tree-based method like Greengenes (8) or ARB (18). Two major pitfalls that are encountered using these former approaches are the presence of huge numbers of unclassified sequences in databases and the lack of representative sequences from all phyla. This leads to most surveys having large portions of their phylotypes designated as unclassified. The latter tree-based approaches, although better suited for classification schemes, are also dependent on having a comprehensive database with well-classified sequences for reproducible results. This reproducibility becomes especially important when trying to compare data across different studies, especially those that utilize different approaches and study systems.In the current study, we analyzed an extensive (∼5,000 clones) partial 16S rRNA gene library from a single soil sample that was generated using very general primers and GC-fractionated DNA. Total DNA was extracted from soil at a cultivated treatment plot at the National Science Foundation Long Term Ecological Research (NSF-LTER) site at the Kellogg Biological Station (KBS) in mid-Michigan (http://www.kbs.msu.edu/lter). To test the effect of GC fractionation on recovery of 16S rRNA gene sequences, we conducted a direct comparison with a nonfractionated library generated from the same soil sample. Using the GC-fractionated library, we also calculated several measures of bacterial diversity and examined the effects of sampling size and sequence length on Shannon-Weaver diversity index, Simpson''s reciprocal index (1/D, where D is the probability that two randomly selected individuals from a sample belong to the same species), evenness, and Chao1 richness estimation. The results show that GC fractionation is a powerful tool to help mitigate limitations of random PCR- and cloning-based analyses of total microbial community diversity, resulting in the recovery of underrepresented taxa and, in turn, reducing the sampling size needed for accurate estimations of bacterial richness. The results also provided evidence for the need to expand the typical scale of sequence-based survey efforts, particularly in environments where evenness abounds or where minority bacterial populations may have important effects on community function and processes. We suggest that there is a need for the establishment of standardized approaches for the analysis of sequence data from community diversity studies in order to maximize data comparisons across independent studies and show examples of software programs developed to facilitate comparative analysis of large sequence datasets.     

Prefrontal deep projection neurons enable cognitive flexibility via persistent feedback monitoring

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A Forward Genetic Screen Targeting the Endothelium Reveals a Regulatory Role for the Lipid Kinase Pi4ka in Myelo- and Erythropoiesis

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Conservation in a cup of water: estimating biodiversity and population abundance from environmental DNA

Three mantras often guide species and ecosystem management: (i) for preventing invasions by harmful species, ‘early detection and rapid response’; (ii) for conserving imperilled native species, ‘protection of biodiversity hotspots’; and (iii) for assessing biosecurity risk, ‘an ounce of prevention equals a pound of cure.’ However, these and other management goals are elusive when traditional sampling tools (e.g. netting, traps, electrofishing, visual surveys) have poor detection limits, are too slow or are not feasible. One visionary solution is to use an organism’s DNA in the environment (eDNA), rather than the organism itself, as the target of detection. In this issue of Molecular Ecology, Thomsen et al. (2012) provide new evidence demonstrating the feasibility of this approach, showing that eDNA is an accurate indicator of the presence of an impressively diverse set of six aquatic or amphibious taxa including invertebrates, amphibians, a fish and a mammal in a wide range of freshwater habitats. They are also the first to demonstrate that the abundance of eDNA, as measured by qPCR, correlates positively with population abundance estimated with traditional tools. Finally, Thomsen et al. (2012) demonstrate that next‐generation sequencing of eDNA can quantify species richness. Overall, Thomsen et al. (2012) provide a revolutionary roadmap for using eDNA for detection of species, estimates of relative abundance and quantification of biodiversity.     

Plant genome archaeology: evidence for conserved ancestral chromosome segments in dicotyledonous plant species

We have developed genetic maps, based on expressed sequence tags (ESTs) that are homologous to Arabidopsis genes, in four dicotyledonous crop plant species from different families. A comparison of these maps with the physical map of Arabidopsis reveals common genome segments that appear to have been conserved throughout the evolution of the dicots. In the four crop species analysed these segments comprise between 16 and 33% of the Arabidopsis genome. Our findings extend the synteny patterns previously observed only within plant families, and indicate that structural and functional information from the model species will be, at least in part, applicable in crop plants with large genomes.     

Photophosphorylation and related properties of reaggregated vesicles from spinach Photosystem I particles

The small Photosystem I particles prepared from spinach chloroplasts by the action of Triton X-100 (TSF 1 particles) reaggregate into membrane structures when they are incubated with soybean phospholipids and cholate and then subjected to a slow dialysis. The membranes so formed are vesicular in nature and show the capability of catalyzing phenazine methosulfate-mediated cyclic photophosphorylalation at rates which are usually about 20% of those observed with chloroplasts, but higher rates have been obtained. When coupling factor is removed from the chloroplasts by treatment with EDTA, a requirement for coupling factor can be shown for the subsequent ATP formation. The uncouplers carbonylcyanide 3-chlorophenyl-hydrazone, valinomycin, Triton X-100 and NH⁺₄ are effective with the reformed vesicles, which do not show the typical light-induced pH gradient observed with chloroplasts. Incubation of the TSF 1 particles with phospholipids alone allows for the formation of membrane vesicles, but such vesicles are only slightly active in ATP formation. In most properties investigated, the reformed membrane vesicles resemble the original chloroplast membrane so far as phenazine methosulfate-mediated cyclic photophosphorylation is concerned, which indicates a high degree of selectivity in the reaggregation process. The major difference between chloroplasts and the reformed vesicles is the failure of the latter to show a light-induced pH gradient.     

Does stream flow structure woody riparian vegetation in subtropical catchments?

The primary objective of this study was to test the relevance of hydrological classification and class differences to the characteristics of woody riparian vegetation in a subtropical landscape in Queensland, Australia. We followed classification procedures of the environmental flow framework ELOHA – Ecological Limits of Hydrologic Alteration. Riparian surveys at 44 sites distributed across five flow classes recorded 191 woody riparian species and 15, 500 individuals. There were differences among flow classes for riparian species richness, total abundance, and abundance of regenerating native trees and shrubs. There were also significant class differences in the occurrence of three common tree species, and 21 indicator species (mostly native taxa) further distinguished the vegetation characteristics of each flow class. We investigated the influence of key drivers of riparian vegetation structure (climate, depth to water table, stream‐specific power, substrate type, degree of hydrologic alteration, and land use) on riparian vegetation. Patterns were explained largely by climate, particularly annual rainfall and temperature. Strong covarying drivers (hydrology and climate) prevented us from isolating the independent influences of these drivers on riparian assemblage structure. The prevalence of species considered typically rheophytic in some flow classes implies a more substantial role for flow in these classes but needs further testing. No relationships were found between land use and riparian vegetation composition and structure. This study demonstrates the relevance of flow classification to the structure of riparian vegetation in a subtropical landscape, and the influence of covarying drivers on riparian patterns. Management of environmental flows to influence riparian vegetation assemblages would likely have most potential in sites dominated by rheophytic species where hydrological influences override other controls. In contrast, where vegetation assemblages are dominated by a diverse array of typical rainforest species, and other factors including broad‐scale climatic gradients and topographic variables have greater influence than hydrology, riparian vegetation is likely to be less responsive to environmental flow management.     

The interchangeability of global positioning system and semiautomated video-based performance data during elite soccer match play

In elite-level soccer, player motion characteristics are commonly generated from match play and training situations using semiautomated video analysis systems and global positioning system (GPS) technology, respectively. Before such data are used collectively to quantify global player load, it is necessary to understand both the level of agreement and direction of bias between the systems so that specific interventions can be made based on the reported results. The aim of this report was to compare data derived from both systems for physical match performances. Six elite-level soccer players were analyzed during a competitive match using semiautomated video analysis (ProZone? [PZ]) and GPS (MinimaxX) simultaneously. Total distances (TDs), high speed running (HSR), very high speed running (VHSR), sprinting distance (SPR), and high-intensity running distance (HIR; >4.0 m·s(-1)) were reported in 15-minute match periods. The GPS reported higher values than PZ did for TD (GPS: 1,755.4 ± 245.4 m; PZ: 1,631.3 ± 239.5 m; p < 0.05); PZ reported higher values for SPR and HIR than GPS did (SPR: PZ, 34.1 ± 24.0 m; GPS: 20.3 ± 15.8 m; HIR: PZ, 368.1 ± 129.8 m; GPS: 317.0 ± 92.5 m; p < 0.05). Caution should be exercised when using match-load (PZ) and training-load (GPS) data interchangeably.