Comparative Transcriptome Analysis of Different Tissues in Burbot (Lota lota) Based on RNA-seq
YANG Tian-Yan1, JIANG Yan-Lin1, HAN Zhi-Qiang1, MENG Wei2*
1 Fishery College, Zhejiang Ocean University, Zhoushan 316022, China; 2 Marine Fisheries Research Institute of Zhejiang / Key Laboratory of Sustainable Utilization of Technology Research for Fisheries Resources of Zhejiang Province / Scientific Observing and Experimental Station of Fishery Resources for Key Fishing Grounds, Ministry of Agriculture, Zhoushan 316021, China
Abstract Burbot (Lota lota) is a cold-water fish with economic value, which is the only freshwater species of Gadiformes. Therefore, it is an important material for studying the evolutionary mechanism of temperature and salinity adaptation. The transcriptome of brain, kidney and liver tissues from L. lota were sequenced based on Illumina Hiseq-2500 high throughput sequencing platform. A total of 20.78 Gb clean data were obtained after removing raw reads by quality control. The high quality clean reads of different tissues were 22 254 637 (brain), 22 843 364 (kidney) and 24 168 330 (liver), respectively. 106 084 unigenes with the average length of 706 bp were assembled by Trinity software. The unigenes were subjected to annotation analysis by matching sequences against related databases. The results showed that 32 745 (30.87%) of these unigenes were significantly matched. In addition, all annotated unigenes were screened against the Gene Ontology (GO) database, in which all the unigenes were divided into 3 categories with 56 branches. The unigenes were divided into 25 categories according to Cluster of Orthologous Groups of Proteins (COG) function classification, and were grouped into 6 categories with 195 classes based on KEGG database. The transcriptome sequencing data and functional annotation in this study will be expected to provide reference materials for the further exploration of the functional genetic resources for L. lota in the future.
YANG Tian-Yan,JIANG Yan-Lin,HAN Zhi-Qiang, et al. Comparative Transcriptome Analysis of Different Tissues in Burbot (Lota lota) Based on RNA-seq[J]. 农业生物技术学报, 2020, 28(2): 291-301.
[1] 车荣波. 2015. 基于转录组数据的鮸鱼分子标记筛选及基因差异表达分析[D]. 硕士学位论文, 浙江海洋大学, 导师: 徐田军. pp. 5-6. (Che R B.2015. Development of molecule markers and gene differential expression analysis of Miichthys miiuy based on transcriptome sequencing data[D]. Thesis for M.S., Zhejiang Ocean University, Supervisor: Xu T J, pp. 5-6.) [2] 崔军. 2013. 基于RNA-Seq技术的红鳍东方鲀鳃和鳔转录组的初步研究[D]. 硕士学位论文, 大连海洋大学, 导师: 王秀利. pp. 57-58. (Cui J.2013. Preliminary research on the transciptome of the gills and swimbladder of Takifugu rubripes by RNA-Seq[D]. Thesis for M.S., Dalian Ocean University, Supervisor: Wang X L, pp. 57-58. ) [3] 李思忠, 张春光. 2011. 中国动物志硬骨鱼纲银汉鱼目鳉形目颌针鱼目蛇鳚目鳕形目[M]. 北京: 科学出版社, pp. 617-621. (Li S Z, Zhang C G.2011. Fauna Sinica Osteichthyes Atheriniformes Cyprinodontiformes Beloniformes Ophidiiformes Gadiformes[M]. Beijing: Science Press, pp. 617-621.) [4] 李育东, 胡光源, 辛玉文. 2015. 江鳕生物学特性及资源保护[J]. 现代化农业, 12: 41-43. (Li Y D, Hu G Y, Xin Y W.2015. Biological characteristics and resource conservation of burbot[J]. Modernizing Agriculture, 12: 41-43.) [5] 黄文, 盛竹梅, 于仕斌, 等. 2015. 人工养殖与野生江鳕肌肉营养成分比较分析[J]. 浙江海洋学院学报(自然科学版), 34(1): 36-39. (Huang W, Sheng Z M, Yu S B, et al.2015. Comparative analysis of farmed and wild burbot muscle nutrients[J]. Journal of Zhejiang Ocean University (Natural Science), 34(1): 36-39.) [6] 刘凯, 谢楠, 冯晓宇, 等. 2015. 基于RNA-seq技术对乌鳢和斑鳢肝脏的转录组分析. 经济动物学报, 19(4): 213-219. (Liu K, Xie N, Feng X Y, et al.2015. Transcriptome analysis of livers in Channa argus and Channa maculatus based on RNA-Seq technique[J]. Journal of Economic Animal, 19(4): 213-219.) [7] 祁云霞, 刘永斌, 荣威恒. 2011. 转录组研究新技术:RNA-Seq及其应用[J]. 遗传, 33(11): 1191-1202. (Qi Y X, Liu Y B, Rong W H.2011. RNA-Seq and its applications: A new technology for transcriptomics[J]. Hereditas, 33(11): 1191-1202.) [8] 全俊龙. 2013. 日本七鳃鳗(Lampetra japonica)血液、肝脏组织的比较转录组学研究[D]. 硕士学位论文, 辽宁师范大学, 导师: 李庆伟. pp. 27-29. (Quan J L.2013. Comparative transcriptome analysis of Lampetra japonica, based on the liver and blood ESTs sequencing[D]. Thesis for M.S., Liaoning Normal University, Supervisor: Li Q W, pp. 27-29.) [9] 史为良. 1985. 鱼类动物区系复合体学说及其评价[J]. 水产科学, 4(2): 42-45. (Shi W L.1985. The theory and evaluation of fish fauna complex[J]. Fisheries Science, 4(2): 42-45. ) [10] 徐革锋, 王裕玉, 白庆利, 等. 2013. 江鳕肌肉营养成分分析与品质评价[J]. 动物营养学报, 25(12): 3027-3032. (Xu G F, Wang Y Y, Bai Q L, et al.2013. Analysis of nutrient components and evolution of nutritive quality in muscle of Lota lota (Linnaeus)[J]. Chinese Journal of Animal Nutrition, 25(12): 3027-3023.) [11] 徐革锋, 王裕玉, 白庆利, 等. 2014. 野生江鳕肌肉氨基酸含量及其营养评价[J]. 水产学杂志, 27(2): 25-28. (Xu G F, Wang Y Y, Bai Q L, et al.2014. Nutritional evaluation of amino acids in the muscle of Lota lota[J]. Chinese Journal of Fisheries, 27(2): 25-28. ) [12] 郑晓飞, 梅柱中, 付汉江, 等. 2004. RNA实验技术手册[M]. 北京: 科学出版社, pp. 24-26. (Zheng X F, Mei Z Z, Fu H J, et al.2004. RNA Experimental Technical Manual[M]. Science Press, Beijing, China. pp. 24-26.) [13] 张俊丽, 高天翔, 方华华, 等. 2008. 黑龙江多布库尔河和新疆额尔齐斯河江鳕的形态特征及生化遗传分析[J]. 中国水产科学, 15(3): 386-391. (Zhang J L, Gao T X, Fang H H, et al.2008. Morphological comparison and isozyme analysis of Lota lota populations in Duobuku'er river and eerqisi river[J]. Journal of Fishey Sciences of China, 15(3): 386-391.) [14] 张燕萍, 章海鑫, 崔璀, 等. 2018. 基于RNA-seq的黄尾鲴肝脏转录组测序与分析[J]. 水生态学杂志, 39(6): 87-94. (Zhang Y P, Zhang H X, Cui C, et al.2018. Transcriptome analysis of Xenocypris davidi Bleeker based on RAN sequencing[J]. Journal of Hydroecology, 39(6): 87-94.) [15] 赵文, 高峰英, 石振广. 2014. 达氏鳇肌肉组织转录组测序和功能分析[J]. 水产学报, 38(9): 1255-1262. (Zhao W, Gao F Y, Shi Z G.2014. The transcriptome sequencing and functional analysis of muscle tissue of Kaluga (Huso dauricus)[J]. Journal of Fisheries of China, 38(9): 1255-1262.) [16] 赵永丽, 夏明哲, 吴蓉蓉, 等. 2018. 基于高通量测序的花斑裸鲤转录组及功能分析[J]. 青海大学学报(自然科学版), 36(1): 1-8. (Zhao Y L, Xia M Z, Wu R R, et al.2018. High-throughput transcriptome sequencing and functional analysis of Gymncypris eckloni[J]. Journal of Qinghai University, 36(1): 1-8. ) [17] 邹立, 蔡绍先, 陈玮莹. 2007. 细胞粘附分子与肝脏疾病[J]. 国际检验医学杂志, 28(11): 1010-1012. (Zou L, Cai S X, Chen W Y.2007. Cell adhesion molecules and liver diseases[J]. International Journal of Laboratory Medicine, 28(11): 1010-1012. ) [18] Altschul S F, Madden T L, Scaffer A A, et al.1997. Gapped BLAST and PSI BLAST: A new generation of protein database search programs[J]. Nucleic Acids Research, 25(17): 3389-3402. [19] Apweiler R, Bairoch A, Wu C H, et al.2004. UniProt: The universal protein knowledgebase[J]. Nucleic Acids Research, 32(Database issue): D115-D119. [20] Ashburner M, Ball C A, Blake J A, et al.2000. Gene ontology: Tool for the unification of biology[J]. Nature genetics, 25(1): 25-29. [21] Avise J C.2000. Phylogeography: The history and formation of species[M]. Cambridge: Harvard University Press, pp. 135-142. [22] Deng Y Y, Li J Q, Wu S F, et al.2006. Integrated NR database in protein annotation system and its localization[J]. Computer Engineering, 32(5): 71-74. [23] Djebali S, Davis C A, Merkel A, et al.2012. Landscape of transcription in human cells[J]. Nature, 489(7414): 101-108. [24] Finn R D, Clements J, Eddy S R.2011. HMMER web server: Interactive sequence similarity searching[J]. Nucleic Acids Research, 39(Web Server issue): 29-37. [25] Finn R D, Bateman A, Clements J, et al.2013. Pfam: The protein families database[J]. Nucleic Acids Research, 36(Database issue): D281-D288 [26] Garber M, Grabherr M G, Guttman M, et al.2011. Computational methods for transcriptome annotation and quantification using RNA-seq[J]. Nature Methods, 8(6): 469-77. [27] Grabherr M G, Haas B J, Yassour M, et al.2011. Full-length transcriptome assembly from RNA-Seq data without a reference genome[J]. Nature Biotechnology, 29(7): 644-652. [28] Hewitt G M.2000. The genetic legacy of the Quaternary ice ages[J]. Nature, 405(6789): 907-913. [29] Kanehisa M, Goto S, Kawashima S, et al.2004. The KEGG resource for deciphering the genome[J]. Nucleic Acids Research, 32(Database issue): D277-D280. [30] Koonin E V, Fedorova N D, Jackson J D, et al.2004. A comprehensive evolutionary classification of proteins encoded in complete eukaryotic genomes[J]. Genome Biology, 5(2): R7. [31] Langmead B, Trapnell C, Pop M, et al.2009. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome[J]. Genome Biology, 10(3): R25 [32] Leng N, Dawson J A, Thomson J A, et al.2013. EBSeq: An empirical bayes hierarchical model for inference in RNA-seq experiments[J]. Bioinformatics, 29(8): 1035-1043. [33] Li B, Dewey C N.2011. RSEM: Accurate transcript quantification from RNA Seq data with or without a reference genome[J]. BMC Bioinformatics. 12(1): 323-323. [34] Morozova O, Hirst M, Marra M A.2009. Applications of new sequencing technologies for transcriptome analysis[J]. Annual Review of Genomics and Human Genetics, 10(1): 135-151. [35] Nelson J S.2006. Fishes of the world (4th ed)[M]. New Jersey, USA. John Wiley & Sons Inc., pp. 11-14. [36] Taberlet P, Fumagalli L, Wust-Saucy A G, et al.2002. Comparative phylogeography and postglacial colonization routes in Europe[J]. Molecular Ecology, 7(4): 453-464. [37] Tatusov R L, Galperin M Y, Natale D A.2000. The COG database: A tool for genome scale analysis of protein functions and evolution[J]. Nucleic Acids Research, 28(1): 33-36. [38] Trapnell C, Williams B A, Pertea G, Mortazavi A, et al.2010. Transcript assembly and quantification by RNA Seq reveals unannotated transcripts and isoform switching during cell differentiation[J]. Nature Biotechnology, 28(5): 511-515. [39] van Houdt J K J, Hellemans B, Volckaert F A M.2003. Phylogenetic relationships among Palearctic and Nearctic burbot (Lota lota): Pleistocene extinctions and recolonization[J]. Molecular Phylogenetics and Evolution, 29(3): 599-612. [40] van Houdt J K J, Cleyn L D, Perretti A, et al.2005. A mitogenic view on the evolutionary history of the Holarctic freshwater gadoid, burbot (Lota lota)[J]. Molecular Ecology, 14(8): 2445-2457. [41] Zhao Y Y, Li J, Sun X W, et al.2009. Isolation and characterization of new microsatellite markers from the burbot (Lota Lota)[J]. Conservation Genetics, 10(4): 1005-1007.
