Yang et al/Comparative from all four clades.Differential expression of clade 3 genes Total RNA extraction,cDNA library construction, is obviously responsible for differences between inner and and Illumina deep sequencing outer tepals,whereas differential expression of clade 4 genes Total RNA was extracted from petal and labella samples differentiates the lateral inner tepals from the labella [2,3]. using a Trizol kit (Takara,Japan).Total RNA quality and Orchid PI/GLO-like genes,found to be present in the AP3/ quantity were analyzed using a Nanodrop 2000 instrument DEF-like gene copies,are also necessary for current floral (Thermo Scientific)and a ChipRNA 7500 Series II Bioana- tissue development [4].Despite this knowledge,however,the lyzer (Agilent).The two total RNA samples were delivered regulatory network controlling orchid floral development to Beijing Biomarker Biotechnology Co.(Beijing,China) remains unclear. for the construction of cDNA libraries using an mRNA-Seq Flower color is derived from the three major classes of Sample Preparation kit (Illumina)according to the manu- plant pigments:anthocyanins,betalains,and carotenoids [5]. facturer's instructions.The sequencing of the two samples Of these,anthocyanins are the major contributors to flower was performed on an Illumina HiSeq 2000 system. color [6].A class of water-soluble flavonoids,anthocyanins are synthesized in the cytosol and localized in vacuoles. Sequence assembly and annotation Through the phenylpropanoid pathway,they provide a wide The raw image data produced from sequencing was range of colors,ranging from orange-red to violet-blue in transformed by base calling into raw reads.Transcriptome dark-colored flowers [5].Despite their structural variety, de novo assembly was carried out with the Trinity short-read anthocyanins are only categorized into six chromophore assembly program,which generated in turn contigs,tran- forms:pelargonidin,cyanidin,peonidin,delphinidin,pe- scripts,and unigenes.To identify unigene putative functions, tunidin,and malvidin [7,8].The anthocyanin biosynthetic their sequences were aligned using BLASTX(E-value s10-5) pathway has been well elaborated [9]. against the following public protein databases:National In orchids,the primary anthocyanin in red flowers is a Center for Biotechnology Information non-redundant(Nr) cyanidin derivative that is typically modified by glycosylation and nucleotide (Nt)databases and SwissProt,TrEMBL, and acylation [10].The glycosylation-related gene PeU-FGT3 Clusters of Orthologous Groups(COG),Gene Ontology plays a critical role in red color formation in Phalaenopsis (GO),and Kyoto Encyclopedia of Genes and Genomes [8].Several important enzymes,such as chalcone synthase (KEGG)databases.The Blast2GO software package was (CHS),chalcone isomerase(CHI),dihydroflavonol 4-reduc- used to compare and determine unigene GO annotations. tase (DFR),and anthocyanidin synthase (ANS),are involved Finally,WEGO software was used to obtain GO functional in the formation of colored anthocyanidins [5]. classifications for all annotated unigenes. Compared with studies in other flowering plants,the molecular basis of floral color development has not been Identification of differentially expressed genes(DEGs) well characterized in orchids.A better understanding of To identify DEGs between the two samples,the following the molecular mechanisms underlying orchid flower color formula was used to calculate significance(P)of differences and floral organ formation is thus needed.Furthermore,few in transcript accumulation for each gene: transcriptomic-based investigations of the functions of genes N2 related to flower color and floral differentiation have been (x+y)! P(y/x)= N1 reported for Phalaenopsis.To expand knowledge regarding 01+e* flower color and diversity for Phalaenopsis breeding,in this study we analyzed differential gene expression between where NI and N2 represent the total number of clean reads petals and labella using the Illumina RNA-Seq method. from petals and labella,respectively,and x and y represent Our study generated a huge number of Phalaenopsis tran- the number of reads mapping to the given gene.We then script sequences during floral formation that can be used to discover putative genes related to flower color and floral differentiation.By comparing relative gene expression levels between petals and labella,novel insights can be gleaned into orchid floral development.Our study therefore provides a foundation for future research on mechanisms underlying floral development in Phalaenopsis and other orchids. Material and methods Plant material and sample collection Phalaenopsis plants with white petals and red labella Peta Labella (Fig.1)were grown in greenhouses at Nanjing Agriculture University under natural light conditions and a controlled temperature of 22-27C.Petals and labella were collected at the full-bloom stage.The two samples were immersed in liquid nitrogen and stored at-80C until subjected to total RNA extraction. Fig.I Photographic image of selected flower materials The Author(s)2014 Published by Polish Botanical Soclety Acta Soc Bot Pol 83(3):191-199 192© The Author(s) 2014 Published by Polish Botanical Society Acta Soc Bot Pol 83(3):191–199 192 Yang et al. / Comparative transcriptome analysis of Phalaenopsis flowers from all four clades. Differential expression of clade 3 genes is obviously responsible for differences between inner and outer tepals, whereas differential expression of clade 4 genes differentiates the lateral inner tepals from the labella [2,3]. Orchid PI/GLO-like genes, found to be present in the AP3/ DEF-like gene copies, are also necessary for current floral tissue development [4]. Despite this knowledge, however, the regulatory network controlling orchid floral development remains unclear. Flower color is derived from the three major classes of plant pigments: anthocyanins, betalains, and carotenoids [5]. Of these, anthocyanins are the major contributors to flower color [6]. A class of water-soluble flavonoids, anthocyanins are synthesized in the cytosol and localized in vacuoles. Through the phenylpropanoid pathway, they provide a wide range of colors, ranging from orange-red to violet-blue in dark-colored flowers [5]. Despite their structural variety, anthocyanins are only categorized into six chromophore forms: pelargonidin, cyanidin, peonidin, delphinidin, pe￾tunidin, and malvidin [7,8]. The anthocyanin biosynthetic pathway has been well elaborated [9]. In orchids, the primary anthocyanin in red flowers is a cyanidin derivative that is typically modified by glycosylation and acylation [10]. The glycosylation-related gene PeU-FGT3 plays a critical role in red color formation in Phalaenopsis [8]. Several important enzymes, such as chalcone synthase (CHS), chalcone isomerase (CHI), dihydroflavonol 4-reduc￾tase (DFR), and anthocyanidin synthase (ANS), are involved in the formation of colored anthocyanidins [5]. Compared with studies in other flowering plants, the molecular basis of floral color development has not been well characterized in orchids. A better understanding of the molecular mechanisms underlying orchid flower color and floral organ formation is thus needed. Furthermore, few transcriptomic-based investigations of the functions of genes related to flower color and floral differentiation have been reported for Phalaenopsis. To expand knowledge regarding flower color and diversity for Phalaenopsis breeding, in this study we analyzed differential gene expression between petals and labella using the Illumina RNA-Seq method. Our study generated a huge number of Phalaenopsis tran￾script sequences during floral formation that can be used to discover putative genes related to flower color and floral differentiation. By comparing relative gene expression levels between petals and labella, novel insights can be gleaned into orchid floral development. Our study therefore provides a foundation for future research on mechanisms underlying floral development in Phalaenopsis and other orchids. Material and methods Plant material and sample collection Phalaenopsis plants with white petals and red labella (Fig. 1) were grown in greenhouses at Nanjing Agriculture University under natural light conditions and a controlled temperature of 22–27°C. Petals and labella were collected at the full-bloom stage. The two samples were immersed in liquid nitrogen and stored at −80°C until subjected to total RNA extraction. Total RNA extraction, cDNA library construction, and Illumina deep sequencing Total RNA was extracted from petal and labella samples using a Trizol kit (Takara, Japan). Total RNA quality and quantity were analyzed using a Nanodrop 2000 instrument (Thermo Scientific) and a ChipRNA 7500 Series II Bioana￾lyzer (Agilent). The two total RNA samples were delivered to Beijing Biomarker Biotechnology Co. (Beijing, China) for the construction of cDNA libraries using an mRNA-Seq Sample Preparation kit (Illumina) according to the manu￾facturer’s instructions. The sequencing of the two samples was performed on an Illumina HiSeq 2000 system. Sequence assembly and annotation The raw image data produced from sequencing was transformed by base calling into raw reads. Transcriptome de novo assembly was carried out with the Trinity short-read assembly program, which generated in turn contigs, tran￾scripts, and unigenes. To identify unigene putative functions, their sequences were aligned using BLASTX (E-value ≤10−5) against the following public protein databases: National Center for Biotechnology Information non-redundant (Nr) and nucleotide (Nt) databases and SwissProt, TrEMBL, Clusters of Orthologous Groups (COG), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The Blast2GO software package was used to compare and determine unigene GO annotations. Finally, WEGO software was used to obtain GO functional classifications for all annotated unigenes. Identification of differentially expressed genes (DEGs) To identify DEGs between the two samples, the following formula was used to calculate significance (P) of differences in transcript accumulation for each gene: where N1 and N2 represent the total number of clean reads from petals and labella, respectively, and x and y represent the number of reads mapping to the given gene. We then 𝑃𝑃𝑃𝑃(𝑦𝑦𝑦𝑦/𝑥𝑥𝑥𝑥) = ( 𝑁𝑁𝑁𝑁2 𝑁𝑁𝑁𝑁1 )! 𝑥𝑥𝑥𝑥 + 𝑦𝑦𝑦𝑦 ! 𝑥𝑥𝑥𝑥! 𝑦𝑦𝑦𝑦 ! (1 + 𝑁𝑁𝑁𝑁2 𝑁𝑁𝑁𝑁1)(!!!!!) Fig. 1 Photographic image of selected flower materials