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Guo Mengpei,Ma Xiaolong,Zhou Yan,Bian Yinbing,Liu Gaolei,Cai Yingli,Huang Tianji,Dong Hongxia,Cai Dingjun,Wan Xueji,Wang Zhihong,Xiao Yang,Kang Heng 한국미생물학회 2023 The journal of microbiology Vol.61 No.1
The basidiomycetous edible mushroom Stropharia rugosoannulata has excellent nutrition, medicine, bioremediation, and biocontrol properties. S. rugosoannulata has been widely and easily cultivated using agricultural by-products showing strong lignocellulose degradation capacity. However, the unavailable high-quality genome information has hindered the research on gene function and molecular breeding of S. rugosoannulata. This study provided a high-quality genome assembly and annotation from S. rugosoannulata monokaryotic strain QGU27 based on combined Illumina-Nanopore data. The genome size was about 47.97 Mb and consisted of 20 scaffolds, with an N50 of 3.73 Mb and a GC content of 47.9%. The repetitive sequences accounted for 17.41% of the genome, mostly long terminal repeats (LTRs). A total of 15,726 coding gene sequences were putatively identified with the BUSCO score of 98.7%. There are 142 genes encoding plant cell wall degrading enzymes (PCWDEs) in the genome, and 52, 39, 30, 11, 8, and 2 genes related to lignin, cellulose, hemicellulose, pectin, chitin, and cutin degradation, respectively. Comparative genomic analysis revealed that S. rugosoannulata is superior in utilizing aldehyde-containing lignins and is possible to utilize algae during the cultivation.
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Li, Qian,Wang, Shuyu,Lee, Dong‐,Kyou,Tang, Jianping,Niu, Xiaorui,Hui, Pinhong,Gutowski Jr., William J.,Dairaku, Koji,McGregor, John L.,Katzfey, Jack,Gao, Xuejie,Wu, Jia,Hong, Song‐,You,Wan Wiley 2016 International journal of climatology Vol.36 No.13
<P><B>ABSTRACT</B></P><P>Under the framework of an project ‘Building Asian Climate Change Scenarios by Multi‐Regional Climate Models Ensemble’, the ability of eight regional climate models and two fine‐resolution global climate models to reproduce late 20th century (1981–2000) precipitation climatology is assessed. Future precipitation change (2041–2060) under the A1B scenario is also quantified by applying four different ensemble methods: equal weighting, weighted mean (WM), reliability ensemble averaging (REA) and performance‐based ensemble averaging, after applying fourfold cross‐validation using observation and multi‐model‐simulated precipitation. The results indicate that the ensemble of simulated precipitation outperforms any single RCM in many aspects. Among the four ensemble approaches, the WM and REA methods show better skill in improving the simulation results, and are used for ensemble prediction of regional climate in Asia. Under the A1B scenario, the WM method estimates future precipitation change of approximately 0.2 mm day<SUP>−1</SUP> with less precipitation in northern and western China and northern India, and more precipitation in most other areas in Asia. The future annual precipitation will decrease by 0.1‐0.5 mm day<SUP>−1</SUP> in northern India, Pakistan and the central area of southern China. No significant change is found over eastern Kazakhstan, Mongolia, north‐central and western China.</P>
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