全转录组学在畜牧业中的应用
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摘要
RNA作为一种大分子参与基因编码、解码、调控、表达等多种生物学过程。目前,对RNA的功能研究主要通过全转录组测序方法来完成。全转录组研究可以对基因结构与功能进行更深层次地分析和探究,揭示基因表达与生命现象之间的内在联系。现阶段,基于高通量测序技术的转录本结构研究、基因表达水平研究及非编码区域功能研究在模式动物、猪、禽类中已大量开展,但在羊上却鲜有报道。本文介绍了利用RNA-seq及Small RNA-seq技术研究全转录组的一般流程及常用策略,综述了全转录组学技术在畜牧业领域中的研究进展。
RNA is a polymeric molecule which is involved in various biological processes including the coding,decoding, regulation, and expression of genes. Whole transcriptome sequencing is the dominant method for studying RNA functions which assists researchers to deepen the exploration and analysis of gene structure and function and to reveal intrinsic links between gene expression and life phenomena. To date, extensive research has been done in animal husbandry models including swine and poultry by using high-throughput RNA sequencing technology. These studies included transcript structure, gene expression level and non-coding region function. In this review, we briefly introduce the general processes and strategies of RNA-seq and small RNA-seq technologies, and summarize the various achievements of the application of whole transcriptomics in animal husbandry.
RNA is a polymeric molecule which is involved in various biological processes including the coding,decoding, regulation, and expression of genes. Whole transcriptome sequencing is the dominant method for studying RNA functions which assists researchers to deepen the exploration and analysis of gene structure and function and to reveal intrinsic links between gene expression and life phenomena. To date, extensive research has been done in animal husbandry models including swine and poultry by using high-throughput RNA sequencing technology. These studies included transcript structure, gene expression level and non-coding region function. In this review, we briefly introduce the general processes and strategies of RNA-seq and small RNA-seq technologies, and summarize the various achievements of the application of whole transcriptomics in animal husbandry.
引文
[1]Lockhart DJ,Winzeler EA.Genomics,gene expression and DNA arrays.Nature,2000,405(6788):827-836.
[2]Lindberg J,Lundeberg J.The plasticity of the mammalian transcriptome.Genomics,2010,95(1):1-6.
[3]Wang Z,Gerstein M,Snyder M.RNA-Seq:a revolutionary tool for transcriptomics.Nat Rev Genet,2009,10(1):57-63.
[4]Wong ML,Medrano JF.Real-time PCR for mRNAquantitation.Biotechniques,2005,39(1):75-85.
[5]Liu C,LI X,Chen LL.Methods for genome-wide characterization of long noncoding RNAs.Chem Life,2016,(6):745-752.
[6]Yang L,Duff MO,Graveley BR,Carmichael GG,Chen LL.Genomewide characterization of non-polyadenylated RNAs.Genome Biology,2011,12(2):R16.
[7]Carthew RW,Sontheimer EJ.Origins and mechanisms of miRNAs and siRNAs.Cell,2009,136(4):642-655.
[8]Chen LL.Linking long noncoding RNA localization and function.Trends Biochem Sci,2016,41(9):761-772.
[9]Yin QF,Yang L,Zhang Y,Xiang JF,Wu YW,Carmichael G,Chen LL.Long noncoding RNAs with snoRNA ends.Mol Cell,2012,48(2):219-230.
[10]Zhang Y,Zhang X,Chen T,Xiang J,Yin Q,Xing Y,Zhu S,Yang L,Chen L.Circular intronic long noncoding RNAs.Mol Cell,2013,51(6):792-806.
[11]Zhang XO,Wang HB,Zhang Y,Lu X,Chen LL,Yang L.Complementary sequence-mediated exon circularization.Cell,2014,159(1):134-147.
[12]Qi YX,Liu YB,Rong WH.RNA-Seq and its applications:a new technology for transcriptomics.Hereditas(Beijing),2011,33(11):1191-1201.祁云霞,刘永斌,荣威恒.转录组研究新技术:RNA-Seq及其应用.遗传,2011,33(11):1191-1201.
[13]Hong QY,Bi XJ,Wang DN,Li ZZ,Yu H,Xia NS,Li SW.Research progress on RNA-Seq technology.Chin JBiochem Pharm,2017,37(6):443-448.洪奇阳,毕行建,王大宁,李子真,俞海,夏宁邵,李少伟.转录组测序技术研究进展.中国生化药物杂志,2017,37(6):443-448.
[14]Patel RK,Jain M.NGS QC toolkit:a toolkit for quality control of next generation sequencing data.PLoS One,2012,7(2):e30619.
[15]Okonechnikov K,Conesa A,García-Alcalde F.Qualimap2:advanced multi-sample quality control for high-throughput sequencing data.Bioinformatics,2016,32(2):292-294.
[16]Yang X,Liu D,Liu F,Wu J,Zou J,Xiao X,Zhao F,Zhu B.HTQC:a fast quality control toolkit for Illumina sequencing data.BMC Bioinformatics,2013,14:33.
[17]Zhou Q,Su X,Wang A,Xu J,Ning K.QC-Chain:fast and holistic quality control method for next-generation sequencing data.PLoS One,2013,8(4):e60234.
[18]Ward J,Cole C,Febrer M,Barton GJ.Almost significant:simplifying quality control of high-throughput sequencing data.Bioinformatics,2016,32(24):3850-3851.
[19]Zhang M,Sun H,Fei Z,Zhan F,Gong X,Gao S.Fastq_clean:an optimized pipeline to clean the Illumina sequencing data with quality control.In:IEEE International Conference on Bioinformatics and Biomedicine.2015,44-48.
[20]Lo CC,Chain PSG.Rapid evaluation and quality control of next generation sequencing data with FaQCs.BMCBioinformatics,2014,15(1):366.
[21]Garber M,Grabherr MG,Guttman M,Trapnell C.Computational methods for transcriptome annotation and quantification using RNA-seq.Nat Methods,2011,8(6):469-477.
[22]Yang IS,Kim S.Analysis of whole transcriptome sequencing data:workflow and software.Genomics Inform,2015,13(4):119-125.
[23]Li H,Ruan J,Durbin R.Mapping short DNA sequencing reads and calling variants using mapping quality scores.Genome Res,2008,18(11):1851-1858.
[24]Li H,Durbin R.Fast and accurate short read alignment with Burrows-Wheeler transform.Bioinformatics,2009,25(4):1754-1760.
[25]Langmead B,Trapnell C,Pop M,Salzberg SL.Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.Genome Biol,2009,10(3):R25.
[26]Trapnell C,Pachter L,Salzberg SL.TopHat:discovering splice junctions with RNA-Seq.Bioinformatics,2009,25(9):1105-1111.
[27]Wang K,Singh D,Zeng Z,Coleman SJ,Huang Y,Savich GL,He X,Mieczkowski P,Grimm SA,Perou CM,MacLeod JN,Chiang DY,Prins JF,Liu J.MapSplice:accurate mapping of RNA-seq reads for splice junction discovery.Nucleic Acids Res,2010,38(18):e178.
[28]Dobin A,Davis CA,Schlesinger F,Drenkow J,Zaleski C,Jha S,Batut P,Chaisson M,Gingeras TR.STAR:ultrafast universal RNA-seq aligner.Bioinformatics,2013,29(1):15-21.
[29]Wu TD,Nacu S.Fast and SNP-tolerant detection of complex variants and splicing in short reads.Bioinformatics,2010,26(7):873-881.
[30]Kumar S,Blaxter ML.Comparing de novo assemblers for454 transcriptome data.BMC Genomics,2010,11:571.
[31]Garg R,Patel RK,Tyagi AK,Jain M.De novo assembly of chickpea transcriptome using short reads for gene discovery and marker identification.DNA Res,2011,18(1):53-63.
[32]Margulies M,Egholm M,Altman WE,Attiya S,Bader JS,Bemben LA,Berka J,Braverman MS,Chen YJ,Chen Z.Genome sequencing in microfabricated high-density picolitre reactors.Nature,2005,437(7057):376-380.
[33]Burlibasa C,Vasiliu D,Vasiliu M.Genome sequence assembly using trace signals and additional sequence information.In:German Conference on Bioinformatics.1999,45-56.
[34]Huang X,Madan A.CAP3:a DNA sequence assembly program.Genome Res,1999,9(9):868-877.
[35]Swindell SR,Plasterer TN.SEQMAN.Contig assembly.Methods Mol Biol,1997,70:75-89.
[36]Pertea G,Huang X,Liang F,Antonescu V,Sultana R,Karamycheva S,Lee Y,White J,Cheung F,Parvizi B,Tsai J,Quackenbush J.TIGR gene indices clustering tools(TGICL):a software system for fast clustering of large EST datasets.Bioinformatics,2003,19(5):651-652.
[37]Miller RT,Christoffels AG,Gopalakrishnan C,Burke J,Ptitsyn AA.A comprehensive approach to clustering of expressed human gene sequence:the sequence tag alignment and consensus knowledge base.Genome Res,1999,9(11):1143-1155.
[38]Zerbino DR,Birney E.Velvet:Algorithms for de novo short read assembly using de Bruijn graphs.Genome Res,2008,18(5):821-829.
[39]Jackman SD,Birol?.Assembling genomes using shortread sequencing technology.Genome Biol,2010,11(1):202-202.
[40]MacCallum I,Przybylski D,Gnerre S,Burton J,Shlyakhter I,Gnirke A,Malek J,McKernan K,Ranade S,Shea TP,Williams L,Young S,Nusbaum C,Jaffe DB.ALLPATHS 2:small genomes assembled accurately and with high continuity from short paired reads.Genome Biol,2009,10(10):R103-R103.
[41]Schulz MH,Zerbino DR,Vingron M,Birney E.Oases:robust de novo RNA-seq assembly across the dynamic range of expression levels.Bioinformatics,2012,28(8):1086-1092.
[42]Li R,Li Y,Kristiansen K,Wang J,Wang J.SOAP:short oligonucleotide alignment program.Bioinformatics,2008,24(5):713-714.
[43]Surget-Groba Y,Montoya-Burgos JI.Optimization of de novo transcriptome assembly from next-generation sequencing data.Genome Res,2010,20(10):1432-1440.
[44]Grabherr MG,Haas BJ,Yassour M,Levin JZ,Thompson DA,Amit I,Adiconis X,Fan L,Raychowdhury R,Zeng Q,Chen Z,Mauceli E,Hacohen N,Gnirke A,Rhind N,di Palma F,Birren BW,Nusbaum C,Lindblad-Toh K,Friedman N,Regev A.Full-length transcriptome assembly from RNA-Seq data without a reference genome.Nat Biotechnol,2011,29(7):644-652.
[45]Huang X,Wang J,Aluru S,Yang SP,Hillier L.PCAP:a whole-genome assembly program.Genome Res,2003,13(9):2164-2170.
[46]Huh JW,Kim YH,Park SJ,Kim DS,Lee SR,Kim KM,Jeong KJ,Kim JS,Song BS,Sim BW,Kim SU,Kim SH,Chang KT.Large-scale transcriptome sequencing and gene analyses in the crab-eating macaque(Macaca fascicularis)for biomedical research.BMC Genomics,2012,13:163.
[47]Pertea M,Pertea GM,Antonescu CM,Chang TC,Mendell JT,Salzberg SL.StringTie enables improved reconstruction of a transcriptome from RNA-seq reads.Nat Biotechnol,2015,33(3):290-295.
[48]Roberts A,Pimentel H,Trapnell C,Pachter L.Identification of novel transcripts in annotated genomes using RNA-Seq.Bioinformatics,2011,27(17):2325-2329.
[49]Canzar S,Andreotti S,Weese D,Reinert K,Klau GW.CIDANE:comprehensive isoform discovery and abundance estimation.Genome Biol,2016,17:16.
[50]Boley N,Stoiber MH,Booth BW,Wan KH,Hoskins RA,Bickel PJ,Celniker SE,Brown JB.Genome-guided transcript assembly by integrative analysis of RNAsequence data.Nat Biotechnol,2014,32(4):341-346.
[51]Liu JT,Yu T,Tao J,Li GJ.TransComb:genome-guided transcriptome assembly via combing junctions in splicing graphs.Genome Biol,2016,17:213.
[52]Mezlini AM,Smith EJ,Fiume M,Buske O,Savich GL,Shah S,Aparicio S,Chiang DY,Goldenberg A,Brudno M.iReckon:simultaneous isoform discovery and abundance estimation from RNA-seq data.Genome Res,2013,23(3):519-529.
[53]Li JJ,Jiang CR,Brown JB,Huang H,Bickel PJ.Sparse linear modeling of next-generation mRNA sequencing(RNA-Seq)data for isoform discovery and abundance estimation.Proc Natl Acad Sci USA,2011,108(50):19867-19872.
[54]Hiller D,Wong WH.Simultaneous isoform discovery and quantification from RNA-seq.Stat Biosci,2013,5(1):100-118.
[55]Stanke M,Keller O,Gunduz I,Hayes A,Waack S,Morgenstern B.AUGUSTUS:ab initio prediction of alternative transcripts.Nucleic Acids Res,2006,34(web server issue):435-439.
[56]Li W,Feng J,Jiang T.IsoLasso:A LASSO regression approach to RNA-seq based transcriptome assembly.JComput Biol,2011,18(11):1693-1707.
[57]Guttman M,Garber M,Levin JZ,Donaghey J,Robinson J,Xian A,Fan L,Koziol MJ,Gnirke A,Nusbaum C.Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs.Nat Biotechnol,2010,28(5):503-510.
[58]Tomescu,Alexandru I,Kuosmanen,Anna,Makinen,Veli,Rizzi R.A novel min-cost flow method for estimating transcript expression with RNA-Seq.BMC Bioinformatics,2013,14(Suppl.5):S15.
[59]Mortazavi A,Williams BA,McCue K,Schaeffer L,Wold B.Mapping and quantifying mammalian transcriptomes by RNA-Seq.Nat Methods,2008,5(7):621-628.
[60]Pachter L.Models for transcript quantification from RNA-Seq.2013.
[61]Anders S,Pyl PT,Huber W.HTSeq-a Python framework to work with high-throughput sequencing data.Bioinformatics,2015,31(2):166-169.
[62]Liao Y,Smyth GK,Shi W.featureCounts:an efficient general purpose program for assigning sequence reads to genomic features.Bioinformatics,2014,30(7):923-930.
[63]Li B,Dewey CN.RSEM:accurate transcript quantification from RNA-Seq data with or without a reference genome.BMC,Bioinformatics,2011,12:323.
[64]Rob P,Mount SM,Kingsford C.Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms.Nat Biotechnol,2013,32(5):462-464.
[65]Bray NL,Pimentel H,Melsted P,Pachter L.Near-optimal probabilistic RNA-seq quantification.Nat Biotechnol,2016,34(5):525-527.
[66]Bullard JH,Purdom E,Hansen KD,Dudoit S.Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments.BMC Bioinformatics,2010,11:94.
[67]Ma X,Zhang X.NURD:an implementation of a new method to estimate isoform expression from non-uniform RNA-seq data.BMC Bioinformatics,2013,14:220.
[68]Oshlack A,Wakefield MJ.Transcript length bias in RNA-seq data confounds systems biology.Biol Direct2009,4:14.
[69]Robinson MD,Oshlack A.A scaling normalization method for differential expression analysis of RNA-seq data.Genome Biol,2010,11(3):1-9.
[70]Anders S,Huber W.Differential expression analysis for sequence count data.Genome Biol,2010,11:R106.
[71]Li J,Witten DM,Johnstone IM,Tibshirani R.Normalization,testing,and false discovery rate estimation for RNA-sequencing data.Biostatistics,2012,13(3):523-538.
[72]Rosenbaum PR,Rubin DB.Reducing bias in observational studies using subclassification on the propensity score.JAmer Stat Assoc,1984,79(387):516-524.
[73]Law CW,Chen Y,Wei S,Smyth GK.voom:precision weights unlock linear model analysis tools for RNA-seq read counts.Genome Biol,2014,15(2):R29.
[74]Li J,Tibshirani R.Finding consistent patterns:Anonparametric approach for identifying differential expression in RNA-Seq data.Stat Methods Med Res,2011,22(5):519-536.
[75]Mcdaneld TG,Smith TP,Doumit ME,Miles JR,Coutinho LL,Sonstegard TS,Matukumalli LK,Dan JN,Wiedmann RT.MicroRNA transcriptome profiles during swine skeletal muscle development.BMC Genomics,2009,10:77.
[76]Shen YF.Sequencing and characterization of mRNA,lncRNA,and miRNA in thytoid gland of Yorkshire and Jinhua Pigs[D].Zhejiang University,2016.沈一飞.约克夏猪和金华猪甲状腺组织mRNA、lncRNA和miRNA测序及功能分析[学位论文].浙江大学,2016.
[77]Li M,Xia Y,Gu Y,Zhang K,Lang Q,Chen L,Guan J,Luo Z,Chen H,Li Y,Li Q,Li X,Jiang AA,Shuai S,Wang J,Zhu Q,Zhou X,Gao X,Li X.MicroRNAome of porcine pre-and postnatal development.PLoS One,2010,5(7):e11541.
[78]Sun J,Xie M,Huang Z,Li H,Chen T,Sun R,Wang J,Xi Q,Wu T,Zhang Y.Integrated analysis of non-coding RNAand mRNA expression profiles of 2 pig breeds differing in muscle traits.J Anim Sci,2017,95(3):1092-1103.
[79]Jianning YU,Yan L,Chen Z,Hui LI,Ying S,Zhu H,Shi Z.Investigating right ovary degeneration in chick embryos by transcriptome sequencing.J Reprod Dev,2017,63(3):295-303.
[80]Li T,Wang S,Wu R,Zhou X,Zhu D,Zhang Y.Identification of long non-protein coding RNAs in chicken skeletal muscle using next generation sequencing.Genomics,2012,99(5):292-298.
[81]Glazov EA,Cottee PA,Barris WC,Moore RJ,Dalrymple BP,Tizard ML.A microRNA catalog of the developing chicken embryo identified by a deep sequencing approach.Genome Res,18(6):957-964.
[82]Kang B,Guo JR,Yang HM,Zhou RJ,Liu JX,Li SZ,Dong CY.Differential expression profiling of ovarian genes in prelaying and laying geese.Poult Sci,2009,88(9):1975-1983.
[83]Guo J,Tang QP,Zhang SJ,Ma YH,Lu HL.Identification of broodiness-related geese genes by suppression subtractive hybridization.Acta Veter Zootechn Sin,2011,42(10):1477-1784.郭军,汤青萍,章双杰,马月辉,陆火林,苏建东,邹剑敏,陈宽维,李慧芳.利用抑制消减杂交技术筛选鹅就巢行为相关基因.畜牧兽医学报,2011,42(10):1477-1484.
[84]Xu Q,Zhao WM,Chen Y,Tong YY,Rong GH,Huang ZY,Zhang Y,Chang GB,Wu XS,Chen GH.Transcriptome profiling of the goose(Anser cygnoides)ovaries identify laying and broodiness phenotypes.PLoS One,2013,8(2):e55496.
[85]Chen L,Luo J,Li JX,Li JJ,Wang DQ,Tian Y,Lu LZ.Transcriptome analysis of adiposity in domestic ducks by transcriptomic comparison with their wild counterparts.Anim Genetics,2015,46(3):299-307.
[86]Di R,He J,Song S,Tian D,Liu Q,Liang X,Ma Q,Sun M,Wang J,Zhao W,Cao G,Wang J,Yang Z,Ge Y,Chu M.Characterization and comparative profiling of ovarian microRNAs during ovine anestrus and the breeding season.BMC Genomics,2014,15:899.
[87]Chang W,Wang J,Tao D,Zhang Y,Jianzhong HE,Shi C.Identification of a novel miRNA from the ovine ovary by a combinatorial approach of bioinformatics and experiments.J Vet Med Sci,2015,77(12):1617-1624.
[88]Zhang SF,Wei CH,Lu J,Zhang XN,Zhou XL,Zhang SZ,Wang GK,Cao JX,Zhao FP,Zhang L,Du LX.Identification of the microRNAome in texel sheep by deep sequencing.Chin Anim Husb Veter Med,2013,40(9):19-22.张世芳,魏彩虹,陆健,张小宁,周鑫磊,张淑珍,王光凯,曹家雪,赵福平,张莉,杜立新.深度测序鉴定绵羊microRNA转录组.中国畜牧兽医,2013,40(9):19-22.
[89]Miao X,Qin QL.Genome-wide transcriptome analysis of mRNAs and microRNAs in Dorset and Small Tail Han sheep to explore the regulation of fecundity.Mol Cell Endocrinol,2015,402:32-42.
[90]Billerey C,Boussaha M,EsquerréD,Rebours E,Djari A,Meersseman C,Klopp C,Gautheret D,Rocha D.Identification of large intergenic non-coding RNAs in bovine muscle using next-generation transcriptomic sequencing.BMC Genomics,2014,15:499.
[91]Sun X,Li M,Sun Y,Cai H,Li R,Wei X,Lan X,Huang Y,Lei C,Chen H.The developmental transcriptome landscape of bovine skeletal muscle defined by Ribo-Zero ribonucleic acid sequencing.J Anim Sci,2015,93(12):5648-5658.
[92]Cánovas A,Rincon G,IslasTrejo A,Wickramasinghe S,Medrano JF.SNP discovery in the bovine milk transcriptome using RNA-Seq technology.Mamm Genome,2010,21(11-12):592-598.
[93]Yao B,Yu Z,Mei Z,Liu M,Liu H,Li J.De novo characterization of the antler tip of Chinese Sika deer transcriptome and analysis of gene expression related to rapid growth.Mol Cell Biochem,2012,364(1-2):93-100.
[94]Xie FY,Feng YL,Wang HH,Ma YF,Yang Y,Wang YC,Shen W,Pan QJ,Yin S,Sun YJ,Ma JY.De novo assembly of the donkey white blood cell transcriptome and a comparative analysis of phenotype-associated genes between donkeys and horses.PLoS One,2015,10(7):e0133258.
[95]Scott EY,Mansour T,Bellone RR,Brown CT,Mienaltowski MJ,Penedo MC,Ross PJ,Valberg SJ,Murray JD,Finno CJ.Identification of long non-coding RNA in the horse transcriptome.BMC Genomics,2017,18(1):511.
[96]Park KD,Park J,Ko J,Kim BC,Kim HS,Ahn K,Do KT,Choi H,Kim HM,Song S,Lee S,Jho S,Kong HS,Yang YM,Jhun BH,Kim C,Kim TH,Hwang S,Bhak J,Lee HK,Cho BW.Whole transcriptome analyses of six thoroughbred horses before and after exercise using RNA-Seq.BMC Genomics,2012,13:473.
[97]Niu XY,Ren KL,Cao L,Li YP,Zhen JJ,Feng GL,Huang SF.Transcriptome analysis on coat color related genes in rex rabbits.China Herb Sci,2016,36(2):1-6.牛晓艳,任克良,曹亮,李燕平,郑建婷,冯国亮,黄淑芳.利用转录组测序方法研究獭兔毛色相关基因.中国草食动物科学,2016,36(2):1-6.
[98]Song XC.Study on the mechanisms of hair pigmentation and skin transcriptome annotation in mink(neovison vison)based onhigh throughput RNA-sequencing[D].Chinese Acadamy of Agricultural Sciences,2016.宋兴超.水貂被毛色素沉积机理及基于高通量RNA-seq皮肤转录组注释研究[学位论文].中国农业科学院,2016.
[2]Lindberg J,Lundeberg J.The plasticity of the mammalian transcriptome.Genomics,2010,95(1):1-6.
[3]Wang Z,Gerstein M,Snyder M.RNA-Seq:a revolutionary tool for transcriptomics.Nat Rev Genet,2009,10(1):57-63.
[4]Wong ML,Medrano JF.Real-time PCR for mRNAquantitation.Biotechniques,2005,39(1):75-85.
[5]Liu C,LI X,Chen LL.Methods for genome-wide characterization of long noncoding RNAs.Chem Life,2016,(6):745-752.
[6]Yang L,Duff MO,Graveley BR,Carmichael GG,Chen LL.Genomewide characterization of non-polyadenylated RNAs.Genome Biology,2011,12(2):R16.
[7]Carthew RW,Sontheimer EJ.Origins and mechanisms of miRNAs and siRNAs.Cell,2009,136(4):642-655.
[8]Chen LL.Linking long noncoding RNA localization and function.Trends Biochem Sci,2016,41(9):761-772.
[9]Yin QF,Yang L,Zhang Y,Xiang JF,Wu YW,Carmichael G,Chen LL.Long noncoding RNAs with snoRNA ends.Mol Cell,2012,48(2):219-230.
[10]Zhang Y,Zhang X,Chen T,Xiang J,Yin Q,Xing Y,Zhu S,Yang L,Chen L.Circular intronic long noncoding RNAs.Mol Cell,2013,51(6):792-806.
[11]Zhang XO,Wang HB,Zhang Y,Lu X,Chen LL,Yang L.Complementary sequence-mediated exon circularization.Cell,2014,159(1):134-147.
[12]Qi YX,Liu YB,Rong WH.RNA-Seq and its applications:a new technology for transcriptomics.Hereditas(Beijing),2011,33(11):1191-1201.祁云霞,刘永斌,荣威恒.转录组研究新技术:RNA-Seq及其应用.遗传,2011,33(11):1191-1201.
[13]Hong QY,Bi XJ,Wang DN,Li ZZ,Yu H,Xia NS,Li SW.Research progress on RNA-Seq technology.Chin JBiochem Pharm,2017,37(6):443-448.洪奇阳,毕行建,王大宁,李子真,俞海,夏宁邵,李少伟.转录组测序技术研究进展.中国生化药物杂志,2017,37(6):443-448.
[14]Patel RK,Jain M.NGS QC toolkit:a toolkit for quality control of next generation sequencing data.PLoS One,2012,7(2):e30619.
[15]Okonechnikov K,Conesa A,García-Alcalde F.Qualimap2:advanced multi-sample quality control for high-throughput sequencing data.Bioinformatics,2016,32(2):292-294.
[16]Yang X,Liu D,Liu F,Wu J,Zou J,Xiao X,Zhao F,Zhu B.HTQC:a fast quality control toolkit for Illumina sequencing data.BMC Bioinformatics,2013,14:33.
[17]Zhou Q,Su X,Wang A,Xu J,Ning K.QC-Chain:fast and holistic quality control method for next-generation sequencing data.PLoS One,2013,8(4):e60234.
[18]Ward J,Cole C,Febrer M,Barton GJ.Almost significant:simplifying quality control of high-throughput sequencing data.Bioinformatics,2016,32(24):3850-3851.
[19]Zhang M,Sun H,Fei Z,Zhan F,Gong X,Gao S.Fastq_clean:an optimized pipeline to clean the Illumina sequencing data with quality control.In:IEEE International Conference on Bioinformatics and Biomedicine.2015,44-48.
[20]Lo CC,Chain PSG.Rapid evaluation and quality control of next generation sequencing data with FaQCs.BMCBioinformatics,2014,15(1):366.
[21]Garber M,Grabherr MG,Guttman M,Trapnell C.Computational methods for transcriptome annotation and quantification using RNA-seq.Nat Methods,2011,8(6):469-477.
[22]Yang IS,Kim S.Analysis of whole transcriptome sequencing data:workflow and software.Genomics Inform,2015,13(4):119-125.
[23]Li H,Ruan J,Durbin R.Mapping short DNA sequencing reads and calling variants using mapping quality scores.Genome Res,2008,18(11):1851-1858.
[24]Li H,Durbin R.Fast and accurate short read alignment with Burrows-Wheeler transform.Bioinformatics,2009,25(4):1754-1760.
[25]Langmead B,Trapnell C,Pop M,Salzberg SL.Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.Genome Biol,2009,10(3):R25.
[26]Trapnell C,Pachter L,Salzberg SL.TopHat:discovering splice junctions with RNA-Seq.Bioinformatics,2009,25(9):1105-1111.
[27]Wang K,Singh D,Zeng Z,Coleman SJ,Huang Y,Savich GL,He X,Mieczkowski P,Grimm SA,Perou CM,MacLeod JN,Chiang DY,Prins JF,Liu J.MapSplice:accurate mapping of RNA-seq reads for splice junction discovery.Nucleic Acids Res,2010,38(18):e178.
[28]Dobin A,Davis CA,Schlesinger F,Drenkow J,Zaleski C,Jha S,Batut P,Chaisson M,Gingeras TR.STAR:ultrafast universal RNA-seq aligner.Bioinformatics,2013,29(1):15-21.
[29]Wu TD,Nacu S.Fast and SNP-tolerant detection of complex variants and splicing in short reads.Bioinformatics,2010,26(7):873-881.
[30]Kumar S,Blaxter ML.Comparing de novo assemblers for454 transcriptome data.BMC Genomics,2010,11:571.
[31]Garg R,Patel RK,Tyagi AK,Jain M.De novo assembly of chickpea transcriptome using short reads for gene discovery and marker identification.DNA Res,2011,18(1):53-63.
[32]Margulies M,Egholm M,Altman WE,Attiya S,Bader JS,Bemben LA,Berka J,Braverman MS,Chen YJ,Chen Z.Genome sequencing in microfabricated high-density picolitre reactors.Nature,2005,437(7057):376-380.
[33]Burlibasa C,Vasiliu D,Vasiliu M.Genome sequence assembly using trace signals and additional sequence information.In:German Conference on Bioinformatics.1999,45-56.
[34]Huang X,Madan A.CAP3:a DNA sequence assembly program.Genome Res,1999,9(9):868-877.
[35]Swindell SR,Plasterer TN.SEQMAN.Contig assembly.Methods Mol Biol,1997,70:75-89.
[36]Pertea G,Huang X,Liang F,Antonescu V,Sultana R,Karamycheva S,Lee Y,White J,Cheung F,Parvizi B,Tsai J,Quackenbush J.TIGR gene indices clustering tools(TGICL):a software system for fast clustering of large EST datasets.Bioinformatics,2003,19(5):651-652.
[37]Miller RT,Christoffels AG,Gopalakrishnan C,Burke J,Ptitsyn AA.A comprehensive approach to clustering of expressed human gene sequence:the sequence tag alignment and consensus knowledge base.Genome Res,1999,9(11):1143-1155.
[38]Zerbino DR,Birney E.Velvet:Algorithms for de novo short read assembly using de Bruijn graphs.Genome Res,2008,18(5):821-829.
[39]Jackman SD,Birol?.Assembling genomes using shortread sequencing technology.Genome Biol,2010,11(1):202-202.
[40]MacCallum I,Przybylski D,Gnerre S,Burton J,Shlyakhter I,Gnirke A,Malek J,McKernan K,Ranade S,Shea TP,Williams L,Young S,Nusbaum C,Jaffe DB.ALLPATHS 2:small genomes assembled accurately and with high continuity from short paired reads.Genome Biol,2009,10(10):R103-R103.
[41]Schulz MH,Zerbino DR,Vingron M,Birney E.Oases:robust de novo RNA-seq assembly across the dynamic range of expression levels.Bioinformatics,2012,28(8):1086-1092.
[42]Li R,Li Y,Kristiansen K,Wang J,Wang J.SOAP:short oligonucleotide alignment program.Bioinformatics,2008,24(5):713-714.
[43]Surget-Groba Y,Montoya-Burgos JI.Optimization of de novo transcriptome assembly from next-generation sequencing data.Genome Res,2010,20(10):1432-1440.
[44]Grabherr MG,Haas BJ,Yassour M,Levin JZ,Thompson DA,Amit I,Adiconis X,Fan L,Raychowdhury R,Zeng Q,Chen Z,Mauceli E,Hacohen N,Gnirke A,Rhind N,di Palma F,Birren BW,Nusbaum C,Lindblad-Toh K,Friedman N,Regev A.Full-length transcriptome assembly from RNA-Seq data without a reference genome.Nat Biotechnol,2011,29(7):644-652.
[45]Huang X,Wang J,Aluru S,Yang SP,Hillier L.PCAP:a whole-genome assembly program.Genome Res,2003,13(9):2164-2170.
[46]Huh JW,Kim YH,Park SJ,Kim DS,Lee SR,Kim KM,Jeong KJ,Kim JS,Song BS,Sim BW,Kim SU,Kim SH,Chang KT.Large-scale transcriptome sequencing and gene analyses in the crab-eating macaque(Macaca fascicularis)for biomedical research.BMC Genomics,2012,13:163.
[47]Pertea M,Pertea GM,Antonescu CM,Chang TC,Mendell JT,Salzberg SL.StringTie enables improved reconstruction of a transcriptome from RNA-seq reads.Nat Biotechnol,2015,33(3):290-295.
[48]Roberts A,Pimentel H,Trapnell C,Pachter L.Identification of novel transcripts in annotated genomes using RNA-Seq.Bioinformatics,2011,27(17):2325-2329.
[49]Canzar S,Andreotti S,Weese D,Reinert K,Klau GW.CIDANE:comprehensive isoform discovery and abundance estimation.Genome Biol,2016,17:16.
[50]Boley N,Stoiber MH,Booth BW,Wan KH,Hoskins RA,Bickel PJ,Celniker SE,Brown JB.Genome-guided transcript assembly by integrative analysis of RNAsequence data.Nat Biotechnol,2014,32(4):341-346.
[51]Liu JT,Yu T,Tao J,Li GJ.TransComb:genome-guided transcriptome assembly via combing junctions in splicing graphs.Genome Biol,2016,17:213.
[52]Mezlini AM,Smith EJ,Fiume M,Buske O,Savich GL,Shah S,Aparicio S,Chiang DY,Goldenberg A,Brudno M.iReckon:simultaneous isoform discovery and abundance estimation from RNA-seq data.Genome Res,2013,23(3):519-529.
[53]Li JJ,Jiang CR,Brown JB,Huang H,Bickel PJ.Sparse linear modeling of next-generation mRNA sequencing(RNA-Seq)data for isoform discovery and abundance estimation.Proc Natl Acad Sci USA,2011,108(50):19867-19872.
[54]Hiller D,Wong WH.Simultaneous isoform discovery and quantification from RNA-seq.Stat Biosci,2013,5(1):100-118.
[55]Stanke M,Keller O,Gunduz I,Hayes A,Waack S,Morgenstern B.AUGUSTUS:ab initio prediction of alternative transcripts.Nucleic Acids Res,2006,34(web server issue):435-439.
[56]Li W,Feng J,Jiang T.IsoLasso:A LASSO regression approach to RNA-seq based transcriptome assembly.JComput Biol,2011,18(11):1693-1707.
[57]Guttman M,Garber M,Levin JZ,Donaghey J,Robinson J,Xian A,Fan L,Koziol MJ,Gnirke A,Nusbaum C.Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs.Nat Biotechnol,2010,28(5):503-510.
[58]Tomescu,Alexandru I,Kuosmanen,Anna,Makinen,Veli,Rizzi R.A novel min-cost flow method for estimating transcript expression with RNA-Seq.BMC Bioinformatics,2013,14(Suppl.5):S15.
[59]Mortazavi A,Williams BA,McCue K,Schaeffer L,Wold B.Mapping and quantifying mammalian transcriptomes by RNA-Seq.Nat Methods,2008,5(7):621-628.
[60]Pachter L.Models for transcript quantification from RNA-Seq.2013.
[61]Anders S,Pyl PT,Huber W.HTSeq-a Python framework to work with high-throughput sequencing data.Bioinformatics,2015,31(2):166-169.
[62]Liao Y,Smyth GK,Shi W.featureCounts:an efficient general purpose program for assigning sequence reads to genomic features.Bioinformatics,2014,30(7):923-930.
[63]Li B,Dewey CN.RSEM:accurate transcript quantification from RNA-Seq data with or without a reference genome.BMC,Bioinformatics,2011,12:323.
[64]Rob P,Mount SM,Kingsford C.Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms.Nat Biotechnol,2013,32(5):462-464.
[65]Bray NL,Pimentel H,Melsted P,Pachter L.Near-optimal probabilistic RNA-seq quantification.Nat Biotechnol,2016,34(5):525-527.
[66]Bullard JH,Purdom E,Hansen KD,Dudoit S.Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments.BMC Bioinformatics,2010,11:94.
[67]Ma X,Zhang X.NURD:an implementation of a new method to estimate isoform expression from non-uniform RNA-seq data.BMC Bioinformatics,2013,14:220.
[68]Oshlack A,Wakefield MJ.Transcript length bias in RNA-seq data confounds systems biology.Biol Direct2009,4:14.
[69]Robinson MD,Oshlack A.A scaling normalization method for differential expression analysis of RNA-seq data.Genome Biol,2010,11(3):1-9.
[70]Anders S,Huber W.Differential expression analysis for sequence count data.Genome Biol,2010,11:R106.
[71]Li J,Witten DM,Johnstone IM,Tibshirani R.Normalization,testing,and false discovery rate estimation for RNA-sequencing data.Biostatistics,2012,13(3):523-538.
[72]Rosenbaum PR,Rubin DB.Reducing bias in observational studies using subclassification on the propensity score.JAmer Stat Assoc,1984,79(387):516-524.
[73]Law CW,Chen Y,Wei S,Smyth GK.voom:precision weights unlock linear model analysis tools for RNA-seq read counts.Genome Biol,2014,15(2):R29.
[74]Li J,Tibshirani R.Finding consistent patterns:Anonparametric approach for identifying differential expression in RNA-Seq data.Stat Methods Med Res,2011,22(5):519-536.
[75]Mcdaneld TG,Smith TP,Doumit ME,Miles JR,Coutinho LL,Sonstegard TS,Matukumalli LK,Dan JN,Wiedmann RT.MicroRNA transcriptome profiles during swine skeletal muscle development.BMC Genomics,2009,10:77.
[76]Shen YF.Sequencing and characterization of mRNA,lncRNA,and miRNA in thytoid gland of Yorkshire and Jinhua Pigs[D].Zhejiang University,2016.沈一飞.约克夏猪和金华猪甲状腺组织mRNA、lncRNA和miRNA测序及功能分析[学位论文].浙江大学,2016.
[77]Li M,Xia Y,Gu Y,Zhang K,Lang Q,Chen L,Guan J,Luo Z,Chen H,Li Y,Li Q,Li X,Jiang AA,Shuai S,Wang J,Zhu Q,Zhou X,Gao X,Li X.MicroRNAome of porcine pre-and postnatal development.PLoS One,2010,5(7):e11541.
[78]Sun J,Xie M,Huang Z,Li H,Chen T,Sun R,Wang J,Xi Q,Wu T,Zhang Y.Integrated analysis of non-coding RNAand mRNA expression profiles of 2 pig breeds differing in muscle traits.J Anim Sci,2017,95(3):1092-1103.
[79]Jianning YU,Yan L,Chen Z,Hui LI,Ying S,Zhu H,Shi Z.Investigating right ovary degeneration in chick embryos by transcriptome sequencing.J Reprod Dev,2017,63(3):295-303.
[80]Li T,Wang S,Wu R,Zhou X,Zhu D,Zhang Y.Identification of long non-protein coding RNAs in chicken skeletal muscle using next generation sequencing.Genomics,2012,99(5):292-298.
[81]Glazov EA,Cottee PA,Barris WC,Moore RJ,Dalrymple BP,Tizard ML.A microRNA catalog of the developing chicken embryo identified by a deep sequencing approach.Genome Res,18(6):957-964.
[82]Kang B,Guo JR,Yang HM,Zhou RJ,Liu JX,Li SZ,Dong CY.Differential expression profiling of ovarian genes in prelaying and laying geese.Poult Sci,2009,88(9):1975-1983.
[83]Guo J,Tang QP,Zhang SJ,Ma YH,Lu HL.Identification of broodiness-related geese genes by suppression subtractive hybridization.Acta Veter Zootechn Sin,2011,42(10):1477-1784.郭军,汤青萍,章双杰,马月辉,陆火林,苏建东,邹剑敏,陈宽维,李慧芳.利用抑制消减杂交技术筛选鹅就巢行为相关基因.畜牧兽医学报,2011,42(10):1477-1484.
[84]Xu Q,Zhao WM,Chen Y,Tong YY,Rong GH,Huang ZY,Zhang Y,Chang GB,Wu XS,Chen GH.Transcriptome profiling of the goose(Anser cygnoides)ovaries identify laying and broodiness phenotypes.PLoS One,2013,8(2):e55496.
[85]Chen L,Luo J,Li JX,Li JJ,Wang DQ,Tian Y,Lu LZ.Transcriptome analysis of adiposity in domestic ducks by transcriptomic comparison with their wild counterparts.Anim Genetics,2015,46(3):299-307.
[86]Di R,He J,Song S,Tian D,Liu Q,Liang X,Ma Q,Sun M,Wang J,Zhao W,Cao G,Wang J,Yang Z,Ge Y,Chu M.Characterization and comparative profiling of ovarian microRNAs during ovine anestrus and the breeding season.BMC Genomics,2014,15:899.
[87]Chang W,Wang J,Tao D,Zhang Y,Jianzhong HE,Shi C.Identification of a novel miRNA from the ovine ovary by a combinatorial approach of bioinformatics and experiments.J Vet Med Sci,2015,77(12):1617-1624.
[88]Zhang SF,Wei CH,Lu J,Zhang XN,Zhou XL,Zhang SZ,Wang GK,Cao JX,Zhao FP,Zhang L,Du LX.Identification of the microRNAome in texel sheep by deep sequencing.Chin Anim Husb Veter Med,2013,40(9):19-22.张世芳,魏彩虹,陆健,张小宁,周鑫磊,张淑珍,王光凯,曹家雪,赵福平,张莉,杜立新.深度测序鉴定绵羊microRNA转录组.中国畜牧兽医,2013,40(9):19-22.
[89]Miao X,Qin QL.Genome-wide transcriptome analysis of mRNAs and microRNAs in Dorset and Small Tail Han sheep to explore the regulation of fecundity.Mol Cell Endocrinol,2015,402:32-42.
[90]Billerey C,Boussaha M,EsquerréD,Rebours E,Djari A,Meersseman C,Klopp C,Gautheret D,Rocha D.Identification of large intergenic non-coding RNAs in bovine muscle using next-generation transcriptomic sequencing.BMC Genomics,2014,15:499.
[91]Sun X,Li M,Sun Y,Cai H,Li R,Wei X,Lan X,Huang Y,Lei C,Chen H.The developmental transcriptome landscape of bovine skeletal muscle defined by Ribo-Zero ribonucleic acid sequencing.J Anim Sci,2015,93(12):5648-5658.
[92]Cánovas A,Rincon G,IslasTrejo A,Wickramasinghe S,Medrano JF.SNP discovery in the bovine milk transcriptome using RNA-Seq technology.Mamm Genome,2010,21(11-12):592-598.
[93]Yao B,Yu Z,Mei Z,Liu M,Liu H,Li J.De novo characterization of the antler tip of Chinese Sika deer transcriptome and analysis of gene expression related to rapid growth.Mol Cell Biochem,2012,364(1-2):93-100.
[94]Xie FY,Feng YL,Wang HH,Ma YF,Yang Y,Wang YC,Shen W,Pan QJ,Yin S,Sun YJ,Ma JY.De novo assembly of the donkey white blood cell transcriptome and a comparative analysis of phenotype-associated genes between donkeys and horses.PLoS One,2015,10(7):e0133258.
[95]Scott EY,Mansour T,Bellone RR,Brown CT,Mienaltowski MJ,Penedo MC,Ross PJ,Valberg SJ,Murray JD,Finno CJ.Identification of long non-coding RNA in the horse transcriptome.BMC Genomics,2017,18(1):511.
[96]Park KD,Park J,Ko J,Kim BC,Kim HS,Ahn K,Do KT,Choi H,Kim HM,Song S,Lee S,Jho S,Kong HS,Yang YM,Jhun BH,Kim C,Kim TH,Hwang S,Bhak J,Lee HK,Cho BW.Whole transcriptome analyses of six thoroughbred horses before and after exercise using RNA-Seq.BMC Genomics,2012,13:473.
[97]Niu XY,Ren KL,Cao L,Li YP,Zhen JJ,Feng GL,Huang SF.Transcriptome analysis on coat color related genes in rex rabbits.China Herb Sci,2016,36(2):1-6.牛晓艳,任克良,曹亮,李燕平,郑建婷,冯国亮,黄淑芳.利用转录组测序方法研究獭兔毛色相关基因.中国草食动物科学,2016,36(2):1-6.
[98]Song XC.Study on the mechanisms of hair pigmentation and skin transcriptome annotation in mink(neovison vison)based onhigh throughput RNA-sequencing[D].Chinese Acadamy of Agricultural Sciences,2016.宋兴超.水貂被毛色素沉积机理及基于高通量RNA-seq皮肤转录组注释研究[学位论文].中国农业科学院,2016.