78 research outputs found

    BRAD, the genetics and genomics database for Brassica plants

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    <p>Abstract</p> <p>Background</p> <p>Brassica species include both vegetable and oilseed crops, which are very important to the daily life of common human beings. Meanwhile, the Brassica species represent an excellent system for studying numerous aspects of plant biology, specifically for the analysis of genome evolution following polyploidy, so it is also very important for scientific research. Now, the genome of <it>Brassica rapa </it>has already been assembled, it is the time to do deep mining of the genome data.</p> <p>Description</p> <p>BRAD, the Brassica database, is a web-based resource focusing on genome scale genetic and genomic data for important Brassica crops. BRAD was built based on the first whole genome sequence and on further data analysis of the Brassica A genome species, <it>Brassica rapa </it>(Chiifu-401-42). It provides datasets, such as the complete genome sequence of <it>B. rapa</it>, which was <it>de novo </it>assembled from Illumina GA II short reads and from BAC clone sequences, predicted genes and associated annotations, non coding RNAs, transposable elements (TE), <it>B. rapa </it>genes' orthologous to those in <it>A. thaliana</it>, as well as genetic markers and linkage maps. BRAD offers useful searching and data mining tools, including search across annotation datasets, search for syntenic or non-syntenic orthologs, and to search the flanking regions of a certain target, as well as the tools of BLAST and Gbrowse. BRAD allows users to enter almost any kind of information, such as a <it>B. rapa </it>or <it>A. thaliana </it>gene ID, physical position or genetic marker.</p> <p>Conclusion</p> <p>BRAD, a new database which focuses on the genetics and genomics of the Brassica plants has been developed, it aims at helping scientists and breeders to fully and efficiently use the information of genome data of Brassica plants. BRAD will be continuously updated and can be accessed through <url>http://brassicadb.org</url>.</p

    Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: a perspective from long‐term data assimilation

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    It is critical to accurately estimate carbon (C) turnover time as it dominates the uncertainty in ecosystem C sinks and their response to future climate change. In the absence of direct observations of ecosystem C losses, C turnover times are commonly estimated under the steady state assumption (SSA), which has been applied across a large range of temporal and spatial scales including many at which the validity of the assumption is likely to be violated. However, the errors associated with improperly applying SSA to estimate C turnover time and its covariance with climate as well as ecosystem C sequestrations have yet to be fully quantified. Here, we developed a novel model-data fusion framework and systematically analyzed the SSA-induced biases using time-series data collected from 10 permanent forest plots in the eastern China monsoon region. The results showed that (a) the SSA significantly underestimated mean turnover times (MTTs) by 29%, thereby leading to a 4.83-fold underestimation of the net ecosystem productivity (NEP) in these forest ecosystems, a major C sink globally; (b) the SSA-induced bias in MTT and NEP correlates negatively with forest age, which provides a significant caveat for applying the SSA to young-aged ecosystems; and (c) the sensitivity of MTT to temperature and precipitation was 22% and 42% lower, respectively, under the SSA. Thus, under the expected climate change, spatiotemporal changes in MTT are likely to be underestimated, thereby resulting in large errors in the variability of predicted global NEP. With the development of observation technology and the accumulation of spatiotemporal data, we suggest estimating MTTs at the disequilibrium state via long-term data assimilation, thereby effectively reducing the uncertainty in ecosystem C sequestration estimations and providing a better understanding of regional or global C cycle dynamics and C-climate feedback

    A sequence-based genetic linkage map as a reference for Brassica rapa pseudochromosome assembly

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    <p>Abstract</p> <p>Background</p> <p><it>Brassica rapa </it>is an economically important crop and a model plant for studies concerning polyploidization and the evolution of extreme morphology. The multinational <it>B. rapa </it>Genome Sequencing Project (BrGSP) was launched in 2003. In 2008, next generation sequencing technology was used to sequence the <it>B. rapa </it>genome. Several maps concerning <it>B. rapa </it>pseudochromosome assembly have been published but their coverage of the genome is incomplete, anchoring approximately 73.6% of the scaffolds on to chromosomes. Therefore, a new genetic map to aid pseudochromosome assembly is required.</p> <p>Results</p> <p>This study concerns the construction of a reference genetic linkage map for <it>Brassica rapa</it>, forming the backbone for anchoring sequence scaffolds of the <it>B. rapa </it>genome resulting from recent sequencing efforts. One hundred and nineteen doubled haploid (DH) lines derived from microspore cultures of an F1 cross between a Chinese cabbage (<it>B. rapa </it>ssp. <it>pekinensis</it>) DH line (Z16) and a rapid cycling inbred line (L144) were used to construct the linkage map. PCR-based insertion/deletion (InDel) markers were developed by re-sequencing the two parental lines. The map comprises a total of 507 markers including 415 InDels and 92 SSRs. Alignment and orientation using SSR markers in common with existing <it>B. rapa </it>linkage maps allowed ten linkage groups to be identified, designated A01-A10. The total length of the linkage map was 1234.2 cM, with an average distance of 2.43 cM between adjacent marker loci. The lengths of linkage groups ranged from 71.5 cM to 188.5 cM for A08 and A09, respectively. Using the developed linkage map, 152 scaffolds were anchored on to the chromosomes, encompassing more than 82.9% of the <it>B. rapa </it>genome. Taken together with the previously available linkage maps, 183 scaffolds were anchored on to the chromosomes and the total coverage of the genome was 88.9%.</p> <p>Conclusions</p> <p>The development of this linkage map is vital for the integration of genome sequences and genetic information, and provides a useful resource for the international <it>Brassica </it>research community.</p

    Molecular Squares, Coordination Polymers and Mononuclear Complexes Supported by 2,4-Dipyrazolyl-6H-1,3,5-triazine and 4,6-Dipyrazolylpyrimidine Ligands

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    The Fe[BF4]2 complex of 2,4-di(pyrazol-1-yl)-6H-1,3,5-triazine (L1) is a high-spin molecular square, [{Fe(L1)}4(μ-L1)4][BF4]8, whose crystals also contain the unusual HPzBF3 (HPz = pyrazole) adduct. Three other 2,4-di(pyrazol-1-yl)-6H-1,3,5-triazine derivatives with different pyrazole substituents (L2-L4) are unstable in the presence of first row transition ions, but form mononuclear, polymeric or molecular square complexes with silver(I). Most of these compounds involve bis-bidentate di(pyrazolyl)triazine coordination, which is unusual for that class of ligand, and the molecular squares encapsulate one or two BF4‒, ClO4‒ or SbF6‒ ions through combinations of anion...π, Ag...X and/or C‒H...X (X = O or F) interactions. Treatment of Fe[NCS]2 or Fe[NCSe]2 with 4,6-di(pyrazol-1-yl)-2H-pyrimidine (L5) or its 2-methyl and 2-amino derivatives L6 and L7) yields mononuclear [Fe(NCE)2L2] and/or the 1D coordination polymers catena-[Fe(NCE)2(μ-L)] (E = S or Se, L = L5-L7). Alcohol solvates of isomorphous [Fe(NCS)2L2] and [Fe(NCSe)2L2] compounds show different patterns of intermolecular hydrogen bonding, reflecting the acceptor properties of the anion ligands. These iron compounds are all high-spin, although annealing solvated crystals of [Fe(NCSe)2(L5)2] affords a new phase exhibiting an abrupt, low-temperature spin transition. Catena-[Fe(H2O)2(μ-L5)][ClO4]2 is a coordination polymer of alternating cis and trans iron centres

    Evaluating the Applicability of Phi Coefficient in Indicating Habitat Preferences of Forest Soil Fauna Based on a Single Field Study in Subtropical China.

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    Phi coefficient directly depends on the frequencies of occurrence of organisms and has been widely used in vegetation ecology to analyse the associations of organisms with site groups, providing a characterization of ecological preference, but its application in soil ecology remains rare. Based on a single field experiment, this study assessed the applicability of phi coefficient in indicating the habitat preferences of soil fauna, through comparing phi coefficient-induced results with those of ordination methods in charactering soil fauna-habitat(factors) relationships. Eight different habitats of soil fauna were implemented by reciprocal transfer of defaunated soil cores between two types of subtropical forests. Canonical correlation analysis (CCorA) showed that ecological patterns of fauna-habitat relationships and inter-fauna taxa relationships expressed, respectively, by phi coefficients and predicted abundances calculated from partial redundancy analysis (RDA), were extremely similar, and a highly significant relationship between the two datasets was observed (Pillai's trace statistic = 1.998, P = 0.007). In addition, highly positive correlations between phi coefficients and predicted abundances for Acari, Collembola, Nematode and Hemiptera were observed using linear regression analysis. Quantitative relationships between habitat preferences and soil chemical variables were also obtained by linear regression, which were analogous to the results displayed in a partial RDA biplot. Our results suggest that phi coefficient could be applicable on a local scale in evaluating habitat preferences of soil fauna at coarse taxonomic levels, and that the phi coefficient-induced information, such as ecological preferences and the associated quantitative relationships with habitat factors, will be largely complementary to the results of ordination methods. The application of phi coefficient in soil ecology may extend our knowledge about habitat preferences and distribution-abundance relationships, which will benefit the understanding of biodistributions and variations in community compositions in the soil. Similar studies in other places and scales apart from our local site will be need for further evaluation of phi coefficient
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