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Yue Teng

Publications and source records attributed to Yue Teng.

2 recordsLinked to original sources

Increased precipitation decelerates temporal succession of grassland soil microbial communities.

Global precipitation regimes have been shifted in recent decades, imposing significant consequences in water-limited grassland ecosystems. However, the effects of increased precipitation on the succession of soil microbial communities remain unclear, mainly due to the scarcity of long-term experiments with time-series data. Here, we examined temporal succession of grassland soil microbial communities in a long-term increased precipitation experiment. Both soil microbial taxonomic and functional structures were significantly altered by increased precipitation. Increased precipitation significantly decelerated the succession rates of soil microbial functional structure (i.e. time-decay relationships). Consistent with the increased microbial decomposition and heterotrophic respiration, the abundances of soil microbial carbon decomposition genes were markedly enhanced by increased precipitation. Furthermore, increased precipitation stimulated genes involved in nutrient cycling processes, potentially promoting plant growth. Collectively, the contributions of stochastic processes in shaping microbial communities were increased under increased precipitation, suggesting that microbial successional trajectories may shift toward multiple alternative states characterized by greater stochasticity under future altered precipitation regimes.

Soil Microbiology↗

Component plane presentation integrated self-organizing map for microarray data analysis.

We describe a powerful approach, component plane presentation integrated self-organizing map (SOM), for the analysis of microarray data. This approach allows the display of multi-dimensional SOM outputs of microarray data in multiple sample specific presentations, providing distinct advantages in visual inspection of biological significances of genes clustered in each map unit with respect to each RNA sample. Beneficial potentials of the approach are highlighted by processing microarray data from yeast cells as well as human breast malignancies.

Gene Expression Profiling↗