621 research outputs found
Primary succession of nitrogen cycling microbial communities along the deglaciated forelands of Tianshan Mountain, China
Structural succession and its driving factors for nitrogen (N) cycling microbial communities during the early stages of soil development (0-44 years) were studied along a chronosequence in the glacial forelands of the Tianshan Mountain No.1 glacier in the arid and semi-arid region of central Asia. We assessed the abundance and population of functional genes affiliated with N-fixation (nifH), nitrification (bacterial and archaeal amoA), and denitrification (nirK/S and nosZ) in a glacier foreland using molecular methods. The abundance of functional genes significantly increased with soil development. N cycling community compositions were also significantly shifted within 44 years and were structured by successional age. Cyanobacterial nifH gene sequences were the most dominant N fixing bacteria and its relative abundance increased from 56.8-93.2% along the chronosequence. Ammonia-oxidizing communities shifted from the Nitrososphaera cluster (AOA-amoA) and the Nitrosospira cluster ME (AOB-aomA) in younger soils (0 and 5 years) to communities dominated by soil and sediment 1 (AOA-amoA) and Nitrosospira Cluster 2 Related (AOB-aomA) in older soils (=17 years). Most of the denitrifers closest relatives were potential aerobic denitrifying bacteria, and some other types of denitrifying bacteria (like autotrophic nitrate-reducing, sulfide-oxidizing bacteria and denitrifying phosphorus removing bacteria) were also detected in all soil samples. The regression analysis showed that N cycling microbial communities were dominant in younger soils (0-5 years) and significantly correlated with soil total carbon, while communities that were most abundant in older soils were significantly correlated with soil total nitrogen. These results suggested that the shift of soil C and N contents during the glacial retreat significantly influenced the abundance, composition and diversity of N cycling microbial communities. © 2016 Zeng, Lou, Zhang, Wang, Hu, Shen, Zhang, Han, Zhang, Lin, Chalk and He
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An efficient multi-locus mixed model framework for the detection of small and linked QTLs in F2
In the genetic system that regulates complex traits, metabolites, gene expression levels, RNA editing levels and DNA methylation, a series of small and linked genes exist. To date, however, little is known about how to design an efficient framework for the detection of these kinds of genes. In this article, we propose a genome-wide composite interval mapping (GCIM) in F2. First, controlling polygenic background via selecting markers in the genome scanning of linkage analysis was replaced by estimating polygenic variance in a genome-wide association study. This can control large, middle and minor polygenic backgrounds in genome scanning. Then, additive and dominant effects for each putative quantitative trait locus (QTL) were separately scanned so that a negative logarithm P-value curve against genome position could be separately obtained for each kind of effect. In each curve, all the peaks were identified as potential QTLs. Thus, almost all the small-effect and linked QTLs are included in a multi-locus model. Finally, adaptive least absolute shrinkage and selection operator (adaptive lasso) was used to estimate all the effects in the multi-locus model, and all the nonzero effects were further identified by likelihood ratio test for true QTL identification. This method was used to reanalyze four rice traits. Among 25 known genes detected in this study, 16 small-effect genes were identified only by GCIM. To further demonstrate GCIM, a series of Monte Carlo simulation experiments was performed. As a result, GCIM is demonstrated to be more powerful than the widely used methods for the detection of closely linked and small-effect QTLs
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