铜绿丽金龟线粒体全基因组及其系统发育分析

doi:10.13560/j.cnki.biotech.bull.1985.2022-0689

摘要/Abstract

摘要：

铜绿丽金龟Anomala corpulenta是一种重要的农林害虫。本文采用Illumina HiSeq X平台对其进行线粒体基因组测序，对基因组序列进行拼装、注释，并对线粒体基因组结构特征和碱基组成进行分析。基于13个蛋白质编码基因的核苷酸序列，采用最大似然法和贝叶斯法构建金龟科系统发育树。结果表明，铜绿丽金龟线粒体基因组全长为16 673 bp，包括13个蛋白质编码基因、22个tRNA基因、2个rRNA基因和一段长约1 074 bp的A+T富集区。基因排布与已知的其他丽金龟科昆虫完全相同，且遵循祖先模式，未发生基因重排。系统发育分析显示，丽金龟亚科的所有物种聚在同一分支，支持该亚科的单系性；异丽金龟属Anomala与彩丽金龟属Mimela的亲缘关系较其与弧丽金龟Popillia和喙丽金龟属Adoretus更近。本研究获得了第一条丽金龟亚科最大属——异丽金龟属Anomala昆虫的线粒体基因组全序列，有助于加深对丽金龟亚科线粒体基因组学和系统发育关系的理解。

关键词: 丽金龟亚科, 异丽金龟属, 铜绿丽金龟, 线粒体基因组测序, 系统发育

Abstract:

Anomala corpulenta is an important agricultural and forestry insect pest. In the present study, high-throughput sequencing of A. corpulenta mitochondrial genome was performed using the Illumina HiSeq X platform and the genome sequences were assembled and annotated. Then the structure features and base composition of A. corpulenta mitochondrial genome were analyzed. Based on the nucleotide sequences of 13 protein-coding genes（PCGs）, the maximum likelihood and Bayesian methods were used to reconstruct the phylogenetic relationship of Scarabaeidae. The results showed that the complete mitogenome of Anomala corpulenta was 16 673 bp in size, including 13 PCGs, 22 tRNA genes, 2 rRNA genes and an A+T region with the length of 1 074 bp. The gene arrangement is consistent with those of the known insect species of Rutelinae, and follows the ancestral pattern without gene rearrangement. Phylogenetic analysis showed that all species of Rutelinae belonged to the same branch, confirming Rutelinae to be a monophyly. Genus Anomala was more closely related to Mimela than to Popillia or Adoretus. This is the first report of a complete mitochondrial genome of genus Anomala, the largest genus of Rutelinae, and it will contribute to increasing our knowledge about the mitogenomics and the phylogeny of Rutelinae.

Key words: Rutelinae, Genus Anomala, Anomala corpulenta, mitochondrial genome sequencing, phylogeny

曲春娟, 朱悦, 江晨, 曲明静, 王向誉, 李晓. 铜绿丽金龟线粒体全基因组及其系统发育分析[J]. 生物技术通报, 2023, 39(2): 263-273.

QU Chun-juan, ZHU Yue, JIANG Chen, QU Ming-jing, WANG Xiang-yu, LI Xiao. Whole Mitochondrial Genome and Phylogeny Analysis of Anomala corpulenta[J]. Biotechnology Bulletin, 2023, 39(2): 263-273.

图/表 7

参考文献 35

[1]	鞠倩, 郭晓强, 李晓, 等. 铜绿丽金龟对寄主植物挥发物的触角电生理及行为反应[J]. 植物保护学报, 2016, 43(2): 281-287.
	Ju Q, Guo XQ, Li X, et al. EAG and behavioral responses of copper-green chafer Anomala corpulenta Motschulsky(Coleoptera: Rutelidae)[J]. J Plant Prot, 2016, 43(2): 281-287.
[2]	Li X, Ju Q, Jie WC, et al. Chemosensory gene families in adult antennae of Anomala corpulenta Motschulsky(Coleoptera: Scarabaeidae: Rutelinae)[J]. PLoS One, 2015, 10(4): e0121504.
[3]	Bouchard P, Bousquet Y, Davies AE, et al. Family-group names in Coleoptera(Insecta)[J]. ZooKeys, 2011(88): 1-972. doi: 10.3897/zookeys.88.807 pmid: 21594053
[4]	路园园, 丁强, 杨星科, 等. 中国丽金龟亚科昆虫分类学研究进展[J]. 环境昆虫学报, 2022. http://kns.cnki.net/kcms/detail/44.1640.Q.20220509.1919.002.html.
	Lu YY, Ding Q, Yang XK, et al. Advances in taxonomy of Chinese Rutelinae[J]. J Environ Entomol, 2022. http://kns.cnki.net/kcms/detail/44.1640.Q.20220509.1919.002.html.
[5]	Cameron SL. Insect mitochondrial genomics: implications for evolution and phylogeny[J]. Annu Rev Entomol, 2014, 59: 95-117. doi: 10.1146/annurev-ento-011613-162007 pmid: 24160435
[6]	Wei SJ, Shi M, Chen XX, et al. New views on strand asymmetry in insect mitochondrial genomes[J]. PLoS One, 2010, 5(9): e12708. doi: 10.1371/journal.pone.0012708 URL
[7]	方晨晨, 郭晓华, 刘广纯, 等. 基因序列在金龟总科(Scarabaeoidea)分子系统学研究中的应用[J]. 应用昆虫学报, 2012, 49(4): 1048-1055.
	Fang CC, Guo XH, Liu GC, et al. Application of gene sequences to the molecular systematics of the Scarabaeoidea[J]. Chin J Appl Entomol, 2012, 49(4): 1048-1055.
[8]	申欣, 李晓, 徐启华. 日本鼓虾与鲜明鼓虾线粒体基因组全序列的分析比较[J]. 海洋学报, 2012, 34(5): 147-153.
	Shen X, Li X, Xu QH. Comparison and analysis of Alpheus japonicus and A. distinguendus complete mitochondrial genome sequences[J]. Acta Oceanol Sin, 2012, 34(5): 147-153. doi: 10.1007/s13131-015-0766-9 URL
[9]	薛清, 杜虹锐, 薛会英, 等. 苜蓿滑刃线虫线粒体基因组及其系统发育研究[J]. 生物技术通报, 2021, 37(7): 98-106. doi: 10.13560/j.cnki.biotech.bull.1985.2021-0628
	Xue Q, Du HR, Xue HY, et al. Mitochondrial genome and phylogeny of Aphelenchoides medicagus[J]. Biotechnol Bull, 2021, 37(7): 98-106.
[10]	Ye F, Samuels DC, Clark T, et al. High-throughput sequencing in mitochondrial DNA research[J]. Mitochondrion, 2014, 17: 157-163. doi: 10.1016/j.mito.2014.05.004 pmid: 24859348
[11]	Yang WZ, Zhang Y, Feng SQ, et al. The first complete mitochondrial genome of the Japanese beetle Popillia japonica(Coleoptera: Scarabaeidae)and its phylogenetic implications for the superfamily Scarabaeoidea[J]. Int J Biol Macromol, 2018, 118(Pt B): 1406-1413. doi: 10.1016/j.ijbiomac.2018.06.131 URL
[12]	Song N, Zhang H. The mitochondrial genomes of phytophagous scarab beetles and systematic implications[J]. J Insect Sci, 2018, 18(6): 11.
[13]	万书波. 中国花生栽培学[M]. 上海: 上海科学技术出版社, 2003.
	Wan SB. Peanut cultivation in China[M]. Shanghai: Shanghai Scientific & Technical Publishers, 2003.
[14]	张鸿飞. 蓖麻对华北地区关键金龟甲种类趋性、交配和解毒代谢的影响[D]. 郑州: 河南农业大学, 2018.
	Zhang HF. Effects of Castor bean on taxis, mating, and detoxification of key scarab species in North China[D]. Zhengzhou: Henan Agricultural University, 2018.
[15]	Patel RK, Jain M. NGS QC Toolkit: a toolkit for quality control of next generation sequencing data[J]. PLoS One, 2012, 7(2): e30619. doi: 10.1371/journal.pone.0030619 URL
[16]	Bankevich A, Nurk S, Antipov D, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing[J]. J Comput Biol, 2012, 19(5): 455-477. doi: 10.1089/cmb.2012.0021 pmid: 22506599
[17]	Boetzer M, Henkel CV, Jansen HJ, et al. Scaffolding pre-assembled contigs using SSPACE[J]. Bioinformatics, 2011, 27(4): 578-579. doi: 10.1093/bioinformatics/btq683 pmid: 21149342
[18]	Bernt M, Donath A, Jühling F, et al. MITOS: improved de novo metazoan mitochondrial genome annotation[J]. Mol Phylogenet Evol, 2013, 69(2): 313-319. doi: 10.1016/j.ympev.2012.08.023 URL
[19]	Lowe TM, Chan PP. tRNAscan-SE On-line: integrating search and context for analysis of transfer RNA genes[J]. Nucleic Acids Res, 2016, 44(W1): W54-W57. doi: 10.1093/nar/gkw413 URL
[20]	Tamura K, Stecher G, Kumar S. MEGA11: molecular evolutionary genetics analysis version 11[J]. Mol Biol Evol, 2021, 38(7): 3022-3027. doi: 10.1093/molbev/msab120 pmid: 33892491
[21]	Larkin MA, Blackshields G, Brown NP, et al. Clustal W and Clustal X version 2.0[J]. Bioinformatics, 2007, 23(21): 2947-2948. doi: 10.1093/bioinformatics/btm404 pmid: 17846036
[22]	Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis[J]. Mol Biol Evol, 2000, 17(4): 540-552. doi: 10.1093/oxfordjournals.molbev.a026334 pmid: 10742046
[23]	Vaidya G, Lohman DJ, Meier R. SequenceMatrix: concatenation software for the fast assembly of multi-gene datasets with character set and Codon information[J]. Cladistics, 2011, 27(2): 171-180. doi: 10.1111/j.1096-0031.2010.00329.x URL
[24]	Lefort V, Longueville JE, Gascuel O. SMS: smart model selection in PhyML[J]. Mol Biol Evol, 2017, 34(9): 2422-2424. doi: 10.1093/molbev/msx149 pmid: 28472384
[25]	Kalyaanamoorthy S, Minh BQ, Wong TKF, et al. ModelFinder: fast model selection for accurate phylogenetic estimates[J]. Nat Methods, 2017, 14(6): 587-589. doi: 10.1038/nmeth.4285 pmid: 28481363
[26]	Guindon S, Dufayard JF, Lefort V, et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0[J]. Syst Biol, 2010, 59(3): 307-321. doi: 10.1093/sysbio/syq010 pmid: 20525638
[27]	Ronquist F, Huelsenbeck JP. MrBayes 3: Bayesian phylogenetic inference under mixed models[J]. Bioinformatics, 2003, 19(12): 1572-1574. doi: 10.1093/bioinformatics/btg180 pmid: 12912839
[28]	Ojala D, Montoya J, Attardi G. tRNA punctuation model of RNA processing in human mitochondria[J]. Nature, 1981, 290(5806): 470-474. doi: 10.1038/290470a0 URL
[29]	Liao F, Wang L, Wu S, et al. The complete mitochondrial genome of the fall webworm, Hyphantria cunea(Lepidoptera: Arctiidae)[J]. Int J Biol Sci, 2010, 6(2): 172-186.
[30]	Wolstenholme DR. Animal mitochondrial DNA: structure and evolution[J]. Int Rev Cytol, 1992, 141: 173-216. pmid: 1452431
[31]	Clary DO, Wolstenholme DR. The mitochondrial DNA molecular of Drosophila yakuba: nucleotide sequence, gene organization, and genetic code[J]. J Mol Evol, 1985, 22(3): 252-271. pmid: 3001325
[32]	Bohacz C, James GH, Ahrens D. Comparative morphology of antennal surface structures in pleurostict scarab beetles(Coleoptera)[J]. Zoomorphology, 2020, 139(3): 327-346. doi: 10.1007/s00435-020-00495-0 URL
[33]	Ayivi SPG, Tong Y, Storey KB, et al. The mitochondrial genomes of 18 new pleurosticti(Coleoptera: Scarabaeidae)exhibit a novel trnQ-NCR-trnI-trnM gene rearrangement and clarify phylogenetic relationships of subfamilies within Scarabaeidae[J]. Insects, 2021, 12(11): 1025. doi: 10.3390/insects12111025 URL
[34]	Ahrens D. The phylogeny of Sericini and their position within the Scarabaeidae based on morphological characters(Coleoptera: Scarabaeidae)[J]. Syst Entomol, 2006, 31(1): 113-144. doi: 10.1111/j.1365-3113.2005.00307.x URL
[35]	Coca-Abia MM. Phylogenetic relationships of the subfamily melolonthinae(Coleoptera, Scarabaeidae)[J]. Insect Syst Evol, 2007, 38(4): 447-472. doi: 10.1163/187631207794760921 URL

基因 Gene	位置 Position/bp	编码链 Coding strand	长度 Length/bp	起始密码子 Start codon	终止密码子 Stop codon	反密码子 Anticodon	基因间隔 Intergenic length/bp
tRNA^Ile	915-979	J	65			GAT	-
tRNA^Gln	976-1 045	N	70			TTG	-4
tRNA^Met	1 044-1 113	J	70			CAT	-2
nad2	1 113-2 121	J	1 009	ATG	TAA		-1
tRNA^Trp	2 135-2 203	J	69			TCA	13
tRNA^Cys	2 195-2 257	N	63			GCA	-9
tRNA^Tyr	2 257-2 322	N	66			GTA	-1
cox1	2 314-3 859	J	1 546	ATT	TAA		-9
tRNA^Leu（UUR）	3 854-3 919	J	66			TAA	-6
cox2	3 919-4 627	J	709	ATC	TAA		-1
tRNA^Lys	4 607-4 678	J	72			CTT	-21
tRNA^Asp	4 680-4 745	J	66			GTC	1
atp8	4 745-4 901	J	157	ATT	TAA		-1
atp6	4 897-5 569	J	673	ATA	TAA		-5
cox3	5 568-6 356	J	789	ATG	TA（A）		-2
tRNA^Gly	6 355-6 420	J	66			TCC	-2
nad3	6 420-6 774	J	355	ATC	TAG		-1
tRNA^Ala	6 772-6 836	J	65			TGC	-2
tRNA^Arg	6 836-6 901	J	66			TCG	-1
tRNA^Asn	6 901-6 966	J	66			GTT	-1
tRNA^Ser（AGN）	6 966-7 033	J	68			TCT	-1
tRNA^Glu	7 033-7 098	J	66			TTC	-1
tRNA^Phe	7 096-7 163	N	68			GAA	-3
nad5	7 162-8 878	N	1 717	ATT	TAA		-2
tRNA^His	8 881-8 944	N	64			GTG	2
nad4	8 943-10 280	N	1 338	ATG	TA（A）		-2
nad4l	10 273-10 606	N	334	TTG	TAA		-8
tRNA^Thr	10 566-10 631	J	66			TGT	-41
tRNA^Pro	10 631-10 696	N	66			TGG	-1
nad6	10 697-11 201	J	505	ATC	TAA		0
cytb	11 200-12 343	J	1 144	ATG	TAG		-2
tRNA^Ser（UCN）	12 341-12 406	J	66			TGA	-3
nad1	12 422-13 370	N	949	ATA	TAG		15
tRNA^Leu（CUN）	13 374-13 440	N	67			TAG	3
16S rRNA	13 404-14 753	N	1 350				-37
tRNA^Val	14 731-14 801	N	71			TAC	-23
12S rRNA	14 801-15 599	N	800				-1
Control Region	15 600-16 673	J	1 074

基因 Gene	位置 Position/bp	编码链 Coding strand	长度 Length/bp	起始密码子 Start codon	终止密码子 Stop codon	反密码子 Anticodon	基因间隔 Intergenic length/bp
tRNA^Ile	915-979	J	65			GAT	-
tRNA^Gln	976-1 045	N	70			TTG	-4
tRNA^Met	1 044-1 113	J	70			CAT	-2
nad2	1 113-2 121	J	1 009	ATG	TAA		-1
tRNA^Trp	2 135-2 203	J	69			TCA	13
tRNA^Cys	2 195-2 257	N	63			GCA	-9
tRNA^Tyr	2 257-2 322	N	66			GTA	-1
cox1	2 314-3 859	J	1 546	ATT	TAA		-9
tRNA^Leu（UUR）	3 854-3 919	J	66			TAA	-6
cox2	3 919-4 627	J	709	ATC	TAA		-1
tRNA^Lys	4 607-4 678	J	72			CTT	-21
tRNA^Asp	4 680-4 745	J	66			GTC	1
atp8	4 745-4 901	J	157	ATT	TAA		-1
atp6	4 897-5 569	J	673	ATA	TAA		-5
cox3	5 568-6 356	J	789	ATG	TA（A）		-2
tRNA^Gly	6 355-6 420	J	66			TCC	-2
nad3	6 420-6 774	J	355	ATC	TAG		-1
tRNA^Ala	6 772-6 836	J	65			TGC	-2
tRNA^Arg	6 836-6 901	J	66			TCG	-1
tRNA^Asn	6 901-6 966	J	66			GTT	-1
tRNA^Ser（AGN）	6 966-7 033	J	68			TCT	-1
tRNA^Glu	7 033-7 098	J	66			TTC	-1
tRNA^Phe	7 096-7 163	N	68			GAA	-3
nad5	7 162-8 878	N	1 717	ATT	TAA		-2
tRNA^His	8 881-8 944	N	64			GTG	2
nad4	8 943-10 280	N	1 338	ATG	TA（A）		-2
nad4l	10 273-10 606	N	334	TTG	TAA		-8
tRNA^Thr	10 566-10 631	J	66			TGT	-41
tRNA^Pro	10 631-10 696	N	66			TGG	-1
nad6	10 697-11 201	J	505	ATC	TAA		0
cytb	11 200-12 343	J	1 144	ATG	TAG		-2
tRNA^Ser（UCN）	12 341-12 406	J	66			TGA	-3
nad1	12 422-13 370	N	949	ATA	TAG		15
tRNA^Leu（CUN）	13 374-13 440	N	67			TAG	3
16S rRNA	13 404-14 753	N	1 350				-37
tRNA^Val	14 731-14 801	N	71			TAC	-23
12S rRNA	14 801-15 599	N	800				-1
Control Region	15 600-16 673	J	1 074

基因Gene	A/%	T/%	G/%	C/%	（A+T）/%	（G+C）/%	AT-skew	GC-skew
全基因组 Whole genome	38.97	36.89	9.21	14.93	75.87	24.13	0.027	-0.237
13PCGs	32.16	42.71	12.25	12.88	74.87	25.13	-0.141	-0.025
22tRNAs	38.79	37.75	13.46	10.01	76.54	23.46	0.014	0.147
2rRNAs	36.41	39.39	16.76	7.45	75.79	24.21	-0.039	0.385
Control region	41.99	39.01	4.19	14.80	81.01	18.99	0.037	-0.559
16S rRNA	36.84	40.85	15.64	6.67	77.69	22.31	0.052	0.402
12S rRNA	35.67	36.92	18.65	8.76	72.59	27.41	-0.017	0.361
nad2	35.52	41.27	7.04	16.17	76.79	23.21	-0.075	-0.393
cox1	31.26	37.35	14.24	17.15	68.61	31.39	-0.089	-0.093
cox2	34.32	38.14	11.72	15.82	72.46	27.54	-0.053	-0.149
atp8	39.10	37.82	8.33	14.74	76.92	23.08	0.017	-0.278
atp6	31.99	42.26	11.16	14.58	74.26	25.74	-0.138	-0.133
cox3	31.22	40.23	13.07	15.48	71.45	28.55	-0.127	-0.084
nad3	32.20	44.07	9.89	13.84	76.27	23.73	-0.158	-0.166
nad5	31.59	45.98	13.29	9.15	77.56	22.44	-0.186	0.184
nad4	30.96	46.67	14.06	8.30	77.64	22.36	-0.202	0.258
nad4l	30.33	50.75	13.21	5.71	81.08	18.92	-0.252	0.396
nad6	37.50	43.45	6.55	12.50	80.95	19.05	-0.074	-0.312
cytb	32.46	39.63	11.90	16.01	72.09	27.91	-0.099	-0.147
nad1	28.38	48.00	15.30	8.33	76.37	23.63	-0.257	0.295

基因Gene	A/%	T/%	G/%	C/%	（A+T）/%	（G+C）/%	AT-skew	GC-skew
全基因组 Whole genome	38.97	36.89	9.21	14.93	75.87	24.13	0.027	-0.237
13PCGs	32.16	42.71	12.25	12.88	74.87	25.13	-0.141	-0.025
22tRNAs	38.79	37.75	13.46	10.01	76.54	23.46	0.014	0.147
2rRNAs	36.41	39.39	16.76	7.45	75.79	24.21	-0.039	0.385
Control region	41.99	39.01	4.19	14.80	81.01	18.99	0.037	-0.559
16S rRNA	36.84	40.85	15.64	6.67	77.69	22.31	0.052	0.402
12S rRNA	35.67	36.92	18.65	8.76	72.59	27.41	-0.017	0.361
nad2	35.52	41.27	7.04	16.17	76.79	23.21	-0.075	-0.393
cox1	31.26	37.35	14.24	17.15	68.61	31.39	-0.089	-0.093
cox2	34.32	38.14	11.72	15.82	72.46	27.54	-0.053	-0.149
atp8	39.10	37.82	8.33	14.74	76.92	23.08	0.017	-0.278
atp6	31.99	42.26	11.16	14.58	74.26	25.74	-0.138	-0.133
cox3	31.22	40.23	13.07	15.48	71.45	28.55	-0.127	-0.084
nad3	32.20	44.07	9.89	13.84	76.27	23.73	-0.158	-0.166
nad5	31.59	45.98	13.29	9.15	77.56	22.44	-0.186	0.184
nad4	30.96	46.67	14.06	8.30	77.64	22.36	-0.202	0.258
nad4l	30.33	50.75	13.21	5.71	81.08	18.92	-0.252	0.396
nad6	37.50	43.45	6.55	12.50	80.95	19.05	-0.074	-0.312
cytb	32.46	39.63	11.90	16.01	72.09	27.91	-0.099	-0.147
nad1	28.38	48.00	15.30	8.33	76.37	23.63	-0.257	0.295

氨基酸Amino acid	密码子Codon	使用次数Usage frequency	RSCU	氨基酸Amino acid	密码子Codon	使用次数Usage frequency	RSCU
Phe（F）	UUU	322	1.62	Pro（P）	CCU	39	1.73
	UUC	75	0.38		CCC	27	1.20
Leu（L）	UUA	258	2.92		CCA	22	0.98
	UUG	53	0.60		CCG	2	0.09
	CUU	108	1.22	Thr（T）	ACU	74	1.72
	CUC	20	0.23		ACC	21	0.49
	CUA	72	0.82		ACA	67	1.56
	CUG	19	0.22		ACG	10	0.23
Ile（I）	AUU	287	1.69	Ala（A）	GCU	52	2.29
	AUC	52	0.31		GCC	12	0.53
Met（M）	AUA	164	1.55		GCA	25	1.10
	AUG	47	0.45		GCG	2	0.09
Val（V）	GUU	72	1.81	Tyr（Y）	UAU	212	1.51
	GUC	13	0.33		UAC	68	0.49
	GUA	56	1.41	His（H）	CAU	69	1.73
	GUG	18	0.45		CAC	11	0.28
Ser（S）	UCU	69	1.71	Gln（Q）	CAA	56	1.58
	UCC	25	0.62		CAG	15	0.42
	UCA	56	1.39	Asn（N）	AAU	147	1.47
	UCG	9	0.22		AAC	53	0.53
	AGU	50	1.24	Lys（K）	AAA	84	1.47
	AGC	21	0.52		AAG	30	0.53
	AGA	58	1.44	Asp（D）	GAU	53	1.58
	AGG	34	0.84		GAC	14	0.42
Glu（E）	GAA	57	1.50	Cys（C）	UGU	34	1.31
	GAG	19	0.50		UGC	18	0.69
Trp（W）	UGA	75	1.53	Gly（G）	GGU	29	0.91
	UGG	23	0.47		GGC	9	0.28
Arg（R）	CGU	10	1.25		GGA	70	2.19
	CGC	1	0.13		GGG	20	0.63
	CGA	19	2.38	*	UAA*	152	1.33
	CGG	2	0.25		UAG*	76	0.67