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Analysis of codon usage patterns in Polyporus umbellatus based on transcriptome data
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Meng-meng LIU1, 2, 3, Yong-mei XING1, *, Shun-xing GUO1, *
Acta Pharmaceutica Sinica | 2020, 55(5) : 1050 - 1055
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Acta Pharmaceutica Sinica | 2020, 55(5): 1050-1055
• Original Articles •
Analysis of codon usage patterns in Polyporus umbellatus based on transcriptome data
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Meng-meng LIU1, 2, 3, Yong-mei XING1, *, Shun-xing GUO1, *
Affiliations
  • 1. Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China
  • 2. College of Traditional Chinese Medicine, Hebei University, Baoding 071002, China
  • 3. Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China
Published: 2020-05-12 doi: 10.16438/j.0513-4870.2019-0900
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We obtained 332 coding sequences from the Polyporus umbellatus transcriptome based on the BLASTx and ESTScan analyses. The codon usage patterns of P. umbellatus were calculated and statistically analyzed using CodonW. The results showed that the average GC content of genes was 53.57% and the average GC3 content was 57.98%, suggesting that genes favored codons ending with G or C. The effective number of codons (ENC) value range from 38.46 to 61, which indicates that these genes have low codon usage bias. The neutrality plot and ENC-plot analysis revealed that many factors such as mutation and selective pressure play an important role in shaping codon usage bias in P. umbellatus genes. Twenty-two optimal codons were identified as being biased toward codons ending with G or C using the high expression superior codon analysis method. This study will lay a foundation for future research on genetic engineering and molecular evolution in P. umbellatus.

Polyporus umbellatus  /  transcriptome  /  codon usage bias  /  preferred codon
Meng-meng LIU, Yong-mei XING, Shun-xing GUO. Analysis of codon usage patterns in Polyporus umbellatus based on transcriptome data[J]. Acta Pharmaceutica Sinica, 2020 , 55 (5) : 1050 -1055 . DOI: 10.16438/j.0513-4870.2019-0900
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Article Info
doi: 10.16438/j.0513-4870.2019-0900
  • Receive Date：2019-11-14
  • Online Date：2026-01-21
  • Published：2020-05-12
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  • Received：2019-11-14
  • Revised：2020-02-02
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Affiliations
    1. Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China
    2. College of Traditional Chinese Medicine, Hebei University, Baoding 071002, China
    3. Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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