Scientia Agricultura Sinica ›› 2018, Vol. 51 ›› Issue (18): 3600-3613.doi: 10.3864/j.issn.0578-1752.2018.18.016

• ANIMAL SCIENCE·VETERINARY SCIENCE·RESOURCE INSECT • Previous Articles     Next Articles

Differential Expression Analysis of Long Non-Coding RNAs During the Developmental Process of Apis mellifera ligustica Worker’s Midgut

Rui GUO1(), SiHai GENG1(), CuiLing XIONG1, YanZhen ZHENG1, ZhongMin FU1, HaiPeng WANG1, Yu DU1, XinYu TONG1, HongXia ZHAO2, DaFu CHEN1()   

  1. 1College of Bee Science, Fujian Agriculture and Forestry University, Fuzhou 350002
    2Guangdong Institute of Applied Biological Resources, Guangzhou 510260
  • Received:2018-03-17 Accepted:2018-05-08 Online:2018-09-16 Published:2018-09-16

Abstract:

【Objective】Long non-coding RNA (lncRNA) plays an important role in regulation of gene expression, epigenetics and cell cycle in eukaryotes. The objective of this study is to investigate the expression profile and role of lncRNAs in the developmental process of Apis mellifera ligustica worker’s midgut. 【Method】In this study, 7- and 10-day-old worker’s midguts of A. m. ligustica (Am7, Am10) were sequenced using RNA-seq technology and strand-specific library construction method. Using Perl script, raw reads were filtered to obtain clean reads with high-quality. Bowtie tool was used to compare clean reads to the ribosome database, and TopHat2 software was employed to compare unmapped clean reads to the reference genome. CPC and CNCI softwares were utilized to predict coding capacity of the transcripts. RT-PCR was performed to identify partial lncRNAs. Investigation of differentially expressed lncRNAs (DElncRNAs) was carried out with edgeR, followed by prediction of upstream and downstream genes, for which GO and KEGG pathway enrichment analyses were performed. RNAhybrid, Miranda and TargetScan softwares were utilized together to predict target miRNAs of DElncRNAs and target genes of miRNAs, and DElncRNAs-miRNAs-mRNAs regulation networks were visualized via Cytoscape. Finally, RT-qPCR was conducted to verify reliability of the sequencing data.【Result】134 802 058 and 147 051 470 raw reads were gained from deep sequencing of Am7 and Am10, respectively, and after stringent filtration, 134 166 157 and 146 293 288 were obtained. In total, 6 353 lncRNAs were predicted, and 3 890 DElncRNAs were obtained based on expression calculation, including 2 005 up-regulated lncRNAs and 1 885 down-regulated lncRNAs. The result of RT-PCR suggested the expected signal bands could be amplified from 8 lncRNAs, implying their true existence. There were 1 793 upstream and downstream genes of DElncRNAs, which were involved in 42 GO terms, including metabolic processes, developmental processes, cellular processes, stress responses, immune system processes and so forth. They were also associated with 251 KEGG pathways, including material metabolism pathways such as carbon metabolism, purine metabolism and fatty acid biosynthesis; energy metabolism pathways such as sulfur metabolism, methane metabolism and oxidative phosphorylation; signaling pathways such as Hippo, Wnt and Notch signaling pathways; cellular immune pathways such as lysosome, endocytosis and ubiquitin mediated proteolysis; humoral immune pathways such as MAPK, Jak-STAT and NF-kappa B pathways, these results demonstrated the DElncRNAs were involved in the material and energy metabolism, cell life activity and immunity regulation in the developmental process of A. m. ligustica worker’s midgut. Further analysis showed TCONS_00020918 might play a regulatory part in the nutrient absorption and caste differentiation in the worker’s midgut. Analysis of regulation networks demonstrated that complex networks existed between DElncRNAs and target miRNAs and mRNAs, partial DElncRNAs lie in the central of the networks and link many miRNAs, and partial miRNAs could be bound by many DElncRNAs, which indicated that these DElncRNAs might play an important role during the developmental process of the worker’s midgut. Finally, 5 DElncRNAs were randomly selected for RT-qPCR assay, and the result proved the reliability of sequencing data in this study.【Conclusion】DElncRNA is widely involved in the metabolism, cellular activity and immune regulation of A. m. ligustica worker’s midgut, and plays a role as a competitive endogenous RNA (ceRNA). The results provide the necessary data support for the screening and functional study of key lncRNA.

Key words: Apis mellifera ligustica, midgut, development, long non-coding RNA, upstream and downstream genes

Fig. 1

Artificial rearing of A. m. ligustica worker"

Table 1

Overview of RNA-seq datasets"

样品 Sample 原始读段 Raw reads 有效读段 Clean reads 99.9%的碱基正确率 Q20 (%) 99.99%的碱基正确率 Q30 (%)
Am7-1 160844082 160049106 (99.51%) 97.41 94.00
Am7-2 129878194 129283918 (99.54%) 97.56 94.19
Am7-3 113683898 113165446 (99.54%) 97.52 94.03
Am10-1 160537248 159765346 (99.52%) 97.27 93.84
Am10-2 149230808 148494716 (99.51%) 97.28 93.77
Am10-3 131386354 130619802 (99.42%) 96.98 93.34

Fig. 2

Pearson correlation between every two biological repeats within each A. m. ligustica midgut sample The horizontal and vertical coordinates represent gene expression level (FPKM)"

Fig. 3

RT-PCR validation of RNA-seq data M: DNA marker; 1: TCONS_00020918; 2: TCONS_00021005; 3: TCONS_00019675; 4: TCONS_00019678; 5: TCONS_00025221; 6: TCONS_00025232; 7: TCONS_00025235; 8: TCONS_00025236"

Table 2

Information of primers for RT-PCR and RT-qPCR"

引物名称
Primer name
引物序列
Primer sequence (5′-3′)
1-F GGCTGAAGATTTCGGATTC
1-R AGAAGGAGGCAAGGAGGAT
2-F GCAAAGACGGAAAGATGG
2-R CCGATGAGTGTGTTCAGTTT
3-F GCCTGTTAGCCATAGTAAGACG
3-R AGAGTGTTGAGCAGCGTTG
4-F CGAGGATGAGCAACTGACA
4-R GCTACGAGCCAGAAGTCTTT
5-F CGCAGTAATGAAAGCATAGG
5-R CGCATCGTGTAACCATAAGA
6-F CCTCTTGGAGATTCCGATACAG
6-R CGTTACCACCATTCAACACG
7-F CCTCTTGGAGATTCCGATACAG
7-R ACCATTCAACACGAGCACC
8-F CCTCTTGGAGATTCCGATACAG
8-R ACCACCATTCAACACGAGC
RE1-F GTTGCTCAAACATCCGAGT
RE1-R CGTTCCATCTTCCTCCAAG
RE2-F TCGTATTCTACAGGGCTTGG
RE2-R TCGCTTCCTTCGTTTAGG
RE3-F GGTTTACTATGCTCCGACGA
RE3-R GGTGATACCGATGGACTCA
RE4-F AGCCAACAGGTGAAATGTG
RE4-R AGGTGTCAGACTGCGGTAA
RE5-F CGTTTCTCGTGCTGCTCTCT
RE5-R AGATGCCACACTTGGATGG
Actin-F CACTCCTGCTATGTATGTCGC
Actin-R GGCAAAGCGTATCCTTCA

Fig. 4

GO classification of DElncRNAs’ upstream and downstream genes"

Fig. 5

KEGG pathway enrichment analysis of DElncRNA’s upstream and downstream genes Enrichment analysis;General picture of Hippo signaling pathway"

Fig. 6

Regulation network of DElncRNAs during the developmental process of A. m. ligustica worker’s midgut"

Fig. 7

RT-qPCR validation of transcriptome data"

[1] PARK D, JUNG J W, CHIO B S, JAYAKODI M, LEE J, LIM J, YU Y, CHOI Y S, LEE M L, PARK Y, CHOI I Y, YANG T Y, EDWARDS O R, NAH G, KWON H W.Uncovering the novel characteristics of Asian honey bee,Apis cerana, by whole genome sequencing. BMC Genomics, 2015, 16(1): 1.
doi: 10.1186/1471-2164-16-1 pmid: 25553907
[2] National Research Council, Division on Earth and Life Studies, Board on Agriculture and Natural Resources, Board on Life Sciences. Committee on the Status of Pollinators in North America. Status of Pollinators in North America. Washington, D.C: National Academies Press, 2007.
[3] 周冰峰. 蜜蜂饲养管理学. 厦门: 厦门大学出版社, 2002.
ZHOU B F.Feeding and Management of Honeybee. Xiamen: Xiamen University Publishing Company, 2002. (in Chinese)
[4] DJEBALI S, DAVIS C A, MERKEL A, DOBIN A, LASSMANN T, MORTAZAVI A, TANZER A, LAGARDE J, LIN W, SCHLESINGER F, XUE C, MARINOV G K, KHATUN J, WILLIAMS B A, ZALESKI C, ROZOWSKY J, RODER M, KOKOCINSKI F, ABDELHAMID R F, ALIOTO T, ANTOSHECHKIN I, BAER M T, BAR N S, BATUT P, BELL K, BELL I, CHAKRABORTTY S, CHEN X, CHRAST J, CURADO J, DERRIEN T, DRENKOW J, DUMAIS E, DUMAIS J, DUTTAGUPTA R, FALCONNET E, FASTUCAM, FEJES-TOTH K, FERREIRA P, FOISSAC S, FULLWOOD M J, GAO H, GONZALEZ D, GORDON A, GUNAWARDENA H, HOWALD C, JHA S, JOHNSON R, KAPRANOV P, KING B, KINGSWOOD C, LUO O J, PARK E, PERSAUD K, PREALL J B, RIBECA P, RISK B, ROBYR D, SAMMETH M, SCHAFFER L, SEE L H, SHAHAB A, SKANCKE J, SUZUKI A M, TAKAHASHI H, TILGNER H, TROUT D, WALTERS N, WANG H, WROBEL J, YU Y, RUAN X, HAYASHIZAKI Y, HARROW J, GERSTEIN M, HUBBARD T, REYMOND A, ANTONARAKIS S E, HANNON G, GIDDINGS M C, RUAN Y, WOLD B, CARNINCI P, GUIGO R, GINGERAS T R. Landscape of transcription in human cells. Nature, 2012, 489(7414): 101-108.
doi: 10.1038/nature11233 pmid: 3684276
[5] GORODKIN J, HOFACKER I L.From structure prediction to genomic screens for novel non-coding RNAs. PLoS Computational Biology, 2011, 7(8): e1002100.
doi: 10.1371/journal.pcbi.1002100 pmid: 21829340
[6] KANDURI C.Kcnq1ot1: a chromatin regulatory RNA. Seminars in Cell & Developmental Biology, 2011, 22(4): 343-350.
doi: 10.1016/j.semcdb.2011.02.020 pmid: 21345374
[7] TRIPATHI V, SHEN Z, CHAKRABORTY A, GIRI S, FREIER S M, WU X, ZHANG Y, GOROSPE M, PRASANTH S G, LAL A, PRASANTH K V.Long noncoding RNA MALAT1 controls cell cycle progression by regulating the expression of oncogenic transcription factor B-MYB. PLoS Genetics, 2013, 9(3): e1003368.
doi: 10.1371/journal.pgen.1003368 pmid: 23555285
[8] LI M, SUN X, CAI H, SUN Y, PLATH M, LI C, LAN X, LEI C, LIN F, BAI Y, CHEN H.Long non-coding RNA ADNCR suppresses adipogenic differentiation by targeting miR-204. Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms, 2016, 1859(7): 871-882.
doi: 10.1016/j.bbagrm.2016.05.003 pmid: 27156885
[9] ULITSKY I, BARTEL D P.LincRNAs: genomics, evolution, and mechanisms. Cell, 2013, 154(1): 26-46.
doi: 10.1016/j.cell.2013.06.020 pmid: 3924787
[10] HUNG T, WANG Y, LIN M F, KOEGEL A K, KOTAKE Y, GRANT G D, HORLINGS H M, SHAH N, UMBRICHT C, WANG P, WANG Y, KONG B, LANEROD A, BORRESEN-DALE A L, KIM S K, VAN D V M, SUKUMAR S, WHITFIELD M L, KELLIS M, XIONG Y, WONG D J, CHANG H Y. Extensive and coordinated transcription of noncoding RNAs within cell cycle promoters. Nature Genetics, 2011, 43(7): 621-629.
doi: 10.1038/ng.848 pmid: 3652667294610
[11] YOON J H, ABDELMOHSEN K, SRIKANTAN S, YANG X, MARTINDALE J L, DE S, HUARTE M, BECKER K G, GOROSPE M.LincRNA-p21 suppresses target mRNA translation. Molecular Cell, 2012, 47(4): 648-655.
doi: 10.1016/j.molcel.2012.06.027 pmid: 22841487
[12] CHOONIEDASS-KOTHARI S, EMBERLEY E, HAMEDANI M K, TROUP S, WANG X, CZOSNEK A, HUBE F, MUTAWE M, WATSON P H, LEYGUE E.The steroid receptor RNA activator is the first functional RNA encoding a protein. FEBS Letters, 2004, 566(1/3): 43-47.
doi: 10.1016/j.febslet.2004.03.104 pmid: 15147866
[13] OGAWA Y, SUN B K, LEE J T.Intersection of the RNA interference and X-inactivation pathways. Science, 2008, 320(5881): 1336-1341.
doi: 10.1126/science.1157676 pmid: 18535243
[14] KENIRY A, OXLEY D, MONNIER P, KYBA M, DANDOLO L, SMITS G, REIK W.The H19 lincRNA is a developmental reservoir of miR-675 which suppresses growth and Igf1r. Nature Cell Biology, 2012, 14(7): 659-665.
doi: 10.1038/ncb2521
[15] MUDGE J M, HARROW J.Creating reference gene annotation for the mouse C57BL6/J genome assembly. Mammalian Genome, 2015, 26(9/10): 366-378.
doi: 10.1007/s00335-015-9583-x pmid: 4602055
[16] HON C C, RAMILOWSKI J A, HARSHBARGER J, BERTIN N, GOUGH J, DENISENKO E, SCHMEIER S, POULSEN T M, SEVERIN J, LIZIO M, KAWAJI H, KASUKAWA T, ITOH M, BURROUGHS A M, NOMA S, DJEBALI S, ALAM T, MEDVEDEVA Y A, TESTA A C, LIPOVICH L, YIP C W, ABUGESSAISA I, MENDEZ M, HASEGAWA A, TANG D, LASSMANN T, HEUTINK P, BABINA M, WELLS C A, KOJIMA S, NAKAMURA Y, SUZUKI H, DAUB C O, DE-HOON M J, ARNER E, HAYASHIZAKI Y, CARNINCI P, FORREST A R. An atlas of human long non-coding RNAs with accurate 5′ ends. Nature, 2017, 543(7644): 199-204.
doi: 10.1038/nature21374 pmid: 28241135
[17] 朱斌, 梁沛, 高希武. 长链非编码RNA (lncRNA)及其在昆虫学研究中的进展. 昆虫学报, 2016, 59(11): 1272-1281.
doi: 10.16380/j.kcxb.2016.11.016
ZHU B, LIANG P, GAO X W.Long noncoding RNAs (lncRNAs) and their research advances in entomology. Acta Entomologica Sinica, 2016, 59(11): 1272-1281. (in Chinese)
doi: 10.16380/j.kcxb.2016.11.016
[18] 郭昱, 苏松坤, 陈盛禄, 张少吾, 陈润生. LncRNA在蜜蜂级型分化中的功能研究. 生物化学与生物物理进展, 2015, 42(8): 750-757.
GUO Y, SU S K, CHEN C L, ZHANG S W, CHEN R S.The function of lncRNAs in the caste determination of the honeybee. Progress in Biochemistry and Biophysics, 2015, 42(8): 750-757. (in Chinese)
[19] HUMANN F C, TIBERIO G J, HARTFELDER K.Sequence and expression characteristics of long noncoding RNAs in honey bee caste development-potential novel regulators for transgressive ovary size. PLoS ONE, 2013, 8(10): e78915.
doi: 10.1371/journal.pone.0078915 pmid: 3814967
[20] CHEN X, MA C, CHEN C, LU Q, SHI W, LIU Z G, WANG H H, GUO H K.Integration of lncRNA-miRNA-mRNA reveals novel insights into oviposition regulation in honey bees.PeerJ, 2017, 5: e3881.
doi: 10.7717/peerj.3881 pmid: 5632538
[21] JAYAKODI M, JUNG J W, PARK D, AHN Y J, LEE S C, SHIN S Y, CHIN C,YANG T J, KWON H W.Genome-wide characterization of long intergenic non-coding RNAs (lincRNAs) provides new insight into viral diseases in honey beesApis cerana and Apis mellifera. BMC Genomics, 2015, 16(1): 680.
doi: 10.1186/s12864-015-1868-7 pmid: 4559890
[22] BABENDREIER D, JOLLER D, ROMEIS J, BIGLER F, WIDMER F.Bacterial community structures in honeybee intestines and their response to two insecticidal proteins. FEMS Microbiology Ecology, 2007, 59(3): 600-610.
doi: 10.1111/fem.2007.59.issue-3
[23] KOCH H, ABROL D P, LI J, SCHMID-HEMPEL P.Diversity and evolutionary patterns of bacterial gut associates of corbiculate bees. Molecular Ecology, 2013, 22(7): 2028-2044.
doi: 10.1111/mec.12209 pmid: 23347062
[24] ELLEGAARD K M, TAMARIT D, JAVELIND E, OLOFSSON T C, ANDERSSON S G, VASQUEZ A.Extensive intra-phylotype diversity in lactobacilli and bifidobacteria from the honeybee gut. BMC Genomics, 2015, 16(1): 284.
doi: 10.1186/s12864-015-1476-6
[25] MOHR K I, TEBBE C C.Diversity and phylotype consistency of bacteria in the guts of three bee species (Apoidea) at an oilseed rape field. Environmental Microbiology, 2006, 8(2): 258-272.
doi: 10.1111/j.1462-2920.2005.00893.x pmid: 16423014
[26] ENGEL P, MARTINSON V G, MORAN N A.Functional diversity within the simple gut microbiota of the honey bee. Proceedings of the National Academy of Sciences of the United States of America, 2012, 109(27): 11002-11007.
doi: 10.4161/gmic.22517
[27] GILLIAM M, VALENTINE D K.Enterobacteriaceae isolated from foraging worker honey bees,Apis mellifera. Journal of Invertebrate Pathology, 1974, 23(1): 38-41.
[28] LANGMEND B, TRAPNELL C, POP M, SALZBERG S L.Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biology, 2009, 10(3): R25.
doi: 10.1186/gb-2009-10-3-r25 pmid: 19261174
[29] KIM D, PERTEA G, TRAPNELL C, PIMENTEL H, KELLEY R, SALZBERG S L.TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biology, 2013, 14(4): R36.
doi: 10.1186/gb-2013-14-4-r36
[30] Honeybee Genome Sequencing Consortium. Insights into social insects from the genome of the honeybeeApis mellifera. Nature, 2006, 443(7114): 931-949.
[31] KONG L, ZHANG Y, YE Z Q, LIU X Q, ZHAO S Q, WEI L, GAO G.CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine. Nucleic Acids Research, 2007, 35(Web Server issue): 345-349.
doi: 10.1093/nar/gkm391 pmid: 1933232
[32] SUN L, LUO H, BU D, ZHAO G, YU K, ZHANG C, LIU Y, CHEN R, ZHAO Y.Utilizing sequence intrinsic composition to classify protein-coding and long non-coding transcripts. Nucleic Acids Research, 2013, 41(17): e166.
doi: 10.1093/nar/gkt646
[33] ROBINSON M D, MCCARTHY D J, SMYTH G K.EdgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 2010, 26(1): 139-140.
doi: 10.1093/bioinformatics/btp616
[34] REHMSMEIER M, STEFFEN P, HOCHSMANN M, GIEGERICH R.Fast and effective prediction of microRNA/target duplexes. RNA, 2004, 10(10): 1507-1517.
doi: 10.1261/rna.5248604 pmid: 15383676
[35] BETEL D, WILSON M, GABOW A, MARKS D S, SANDER C.The microRNA.org resource: targets and expression. Nucleic Acids Research, 2008, 36(Database issue): 149-153.
doi: 10.1093/nar/gkm995 pmid: 18158296
[36] ALLEN E, XIE Z, GUSTAFSON A M, CARRINGTON J C.MicroRNA-directed phasing during trans-acting siRNA biogenesis in plants. Cell, 2005, 121(2): 207-221.
doi: 10.1016/j.cell.2005.04.004 pmid: 15851028
[37] SMOOT M E, ONO K, RUSCHEINSKI J, WANG P L, IDEKER T.Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics, 2011, 27(3): 431-432.
doi: 10.1093/bioinformatics/btq675
[38] SALMENA L, POLISENO L, TAY Y KATS L, PANDOLFI P P. AceRNA hypothesis: The Rosetta stone of a hidden RNA language? Cell, 2011, 146(3): 353-358.
doi: 10.1016/j.cell.2011.07.014 pmid: 3235919
[39] FLIRIAN K, JOSHUA T M.Functional classification and experimental dissection of long noncoding RNAs.Cell, 2018, 172(3): 393-407.
doi: 10.1016/j.cell.2018.01.011
[40] 赵亚周, 田文礼, 胡熠凡, 彭文君. 蜜蜂蜂王浆主蛋白 (MRJPs)的研究进展. 应用昆虫学报, 2012, 49(5): 1345-1353.
ZHAO Y Z, TIAN W L, HU Y F, PENG W J.Research advances in major royal jelly proteins of honeybee. Chinese Journal of Applied Entomology, 2012, 49(5): 1345-1353. (in Chinese)
[41] HALDER G, JOHNSON R L.Hippo signaling: growth control and beyond. Development, 2011, 138(1): 9-22.
doi: 10.1242/dev.045500 pmid: 21138973
[42] PAN D.The hippo signaling pathway in development and cancer. Developmental Cell, 2010, 19(4): 491-505.
doi: 10.1016/j.devcel.2010.09.011 pmid: 3124840
[43] CAMARGO F D, GOKHALE S, JOHNNIDIS J B, FU D, BELL G W, JAENISCH R, BRUMMELKAMP T R.YAP1 increases organ size and expands undifferentiated progenitor cells. Current Biology, 2007, 17(23): 2054-2060.
doi: 10.1016/j.cub.2007.10.039 pmid: 17980593
[44] BITEAU B, HOCHMUTH C E, JASPER H.JNK activity in somatic stem cells causes loss of tissue homeostasis in the agingDrosophila gut. Cell Stem Cell, 2008, 3(4): 442-455.
doi: 10.1016/j.stem.2008.07.024 pmid: 18940735
[45] ORIHEL T C.The peritrophic membrane: its role as a barrier to infection of the arthropod host//Invertebrate Immunity. Academic Press, 1975: 65-73.
[46] ARONSTEIN K A, MURRAY K D.Chalkbrood disease in honey bees. Journal of Invertebrate Pathology, 2010, 103(Suppl. 1): 20-29.
doi: 10.1016/j.jip.2009.06.018 pmid: 19909969
[47] KARRENTH F A, TAY Y, PERNA D, ALA U, TAN S M, RUST A G, DENICOLA G, WEBSTER K A, WEISS D, PEREZ-MANCERA P A, KRAUTHAMMER M, HALABAN R, PROVERO P, ADAMS D J, TUVESON D A, PANDOLFI P P.In vivo identification of tumor suppressive PTEN ceRNAs in an oncogenic BRAF-induced mouse model of melanoma. Cell, 2011, 147(2): 382-395.
doi: 10.1016/j.cell.2011.09.032 pmid: 3236086
[48] COLLINS D H, MOHORIANU I, BECKERS M, MOULTON V, DALMAY T, BOURKE A F.MicroRNAs associated with caste determination and differentiation in a primitively eusocial insect. Scientific Reports, 2017, 7: 45674.
doi: 10.1038/srep45674 pmid: 28361900
[49] LI E H, ZHAO X, ZHANG C, LIU W.Fragile X mental retardation protein participates in non-coding RNA pathways. Hereditas, 2018, 40(2): 87-94.
doi: 10.16288/j.yczz.17-255 pmid: 29428901
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