Use of Zr/Rb ratios in Chinese loess sequences to trace paleo-winter monsoon winds strength

IEECAS SKLLQG

Astronomical signals in different climate proxies from the quaternary loess-soil sequences in China

IEECAS SKLLQG

Magnetic properties of Jiaxian red clay sequences from northern Chinese Loess Plateau and its paleoclimatic significance

IEECAS SKLLQG

Novel uncultivated labyrinthulomycetes revealed by 18S rDNA sequences from seawater and sediment samples

Labyrinthulomycetes (Labyrinthulea) are ubiquitous marine osmoheterotrophic protists that appear to be important in decomposition of both allochthonous and autochthonous organic matter. We used a cultivation-independent method based on the labyrinthulomycete-specific primer LABY-Y to PCR amplify, clone, and sequence 68 nearly full-length 18S rDNA amplicons from 4 sediment and 3 seawater samples collected in estuarine habitats around Long Island, New York, USA. Phylogenetic analyses revealed that all 68 amplicons belonged to the Labyrinthulea. Only 15 of the 68 amplicons belonged to the thraustochytrid phylogenetic group (Thraustochytriidae). None of these 15 were similar to cultivated strains, and 11 formed a novel group. The remaining 53 amplicons belonged either to the labyrinthulid phylogenetic group (Labyrinthulidae) or to other families of Labyrinthulea. that have not yet been described. Of these amplicons, 37 were closely related to previously cultivated Aplanochytrium spp. and Oblongichytrium spp. Members of these 2 genera were also cultivated from 1 of the sediment samples. The 16 other amplicons were not closely related to cultivated strains, and 15 belonged to 5 groups of apparently novel labyrinthulomycetes. Most of the novel groups of amplicons also contained environmental sequences from surveys of protist diversity using universal 18S rDNA primers. Because the primer LABY-Y is biased against several groups of labyrinthulomycetes, particularly among the thraustochytrids, these results may underestimate the undiscovered diversity of labyrinthulomycetes.

Uncovering the rules for protein-protein interactions from yeast genomic data

Identifying protein-protein interactions is crucial for understanding cellular functions. Genomic data provides opportunities and challenges in identifying these interactions. We uncover the rules for predicting protein-protein interactions using a frequent pattern tree (FPT) approach modified to generate a minimum set of rules (mFPT), with rule attributes constructed from the interaction features of the yeast genomic data. The mFPT prediction accuracy is benchmarked against other commonly used methods such as Bayesian networks and logistic regressions under various statistical measures. Our study indicates that mFPT outranks other methods in predicting the protein-protein interactions for the database used. We predict a new protein-protein interaction complex whose biological function is related to premRNA splicing and new protein-protein interactions within existing complexes based on the rules generated.