External environment seriously affect plant growth and food security (Waqas et al., 2019). Among them, abiotic stresses, such as UV-B, drought, chilling, heavy metals, etc., inevitably lead to the decline of medicinal material quality and the accumulation of harmful substances (Jiang et al., 2020). The discovery of large-scale gene families that are involved in abiotic stress opens up new ways to deal with and control harmful conditions (Song et al., 2022a). Bioinformatics is an emerging field developed by integrating biology with computer science and mathematics (Kan et al., 2021). It tackles the barrier of processing huge amounts of biological data by applying computer science and technology and statistical methodologies thoroughly. With the advancement of high-throughput sequencing technology, genome assembly and sequencing, in conjunction with bioinformatics algorithms, have catapulted life sciences into the “omics” era (Jing and Liu, 2018; Song et al., 2021). The quantity of data contained in these omics metadata is enormous, and the relationships between the datasets are intricate. To comprehend the relationship between the structure and function of regulatory elements, it is often necessary to study several genes simultaneously (Patro et al., 2017). This mainly includes structural genomes, comparative genomes, and functional genomes. The investigation of the differentially expressed genes generated from the experiment involves large-scale data analysis of online services and local area networks, providing researchers with reference and optional data analysis tools (Kang et al., 2020). Computational biology is frequently employed to decode medicinal plant genomes, pan-genomes and molecular markers, as well as to explore the origin and evolution of related species, structural variation of genomes, neofunctionalization of gene families, and systematic biology, among other applications (Nadler et al., 1997). In terms of genome assembly, the assembly strategy and an algorithm based on overlapping graphs are applied to construct the process. PacBio CCS sequencing with Hi-C technology, Oxford Nanopore, and other third-generation sequencing technologies has been extensively employed to sequence non-model species in recent years (Sun et al., 2020; Ye et al., 2021). In terms of gene prediction, de novo sequencing based on hidden Markov models enhances prediction accuracy (Wang F et al., 2021). Regarding functional gene mining, bioinformatics can closely integrate the metabolome, genome, transcriptome and proteome, and examine the natural variation of metabolic regulatory genes using principle component analysis, hierarchical clustering analysis, and correlation analysis (Srivastava et al., 2018). Some researchers also use metabolome-genome wide association analysis (mGWAS) to investigate the underlying genetic basis of metabolite biosynthesis pathways (Zhang et al., 2020).

D. officinale is a perennial herb in the orchid family that belongs to the Dendrobium genus (Wang Y et al., 2021). It is mainly distributed in the Ta-pieh Mountain of Anhui, Zhengjiang, Guangzhou, Guangxi, Yunnan, and other provinces (Song et al., 2022b). D. officinale has considerable effects on immunity and hematopoiesis, as well as anti-oxidation, anti-tumor, anti-fatigue, and hypoglycemic properties (Song et al., 2022d). WRKY transcription factor family is one of the most extensive transcription factor families found in higher plants (Li et al., 2020). It is a crucial class of transcription factors that regulates plant growth, development, and stress tolerance (Guo et al., 2019; Jue et al., 2018). The representative aspect of WRKY transcription factors is the conserved WRKY domain, which consists of the highly conserved WRKYGQK heptapeptide and C2-H2 (C-X4-C-X22-23-H-X1-H) or C2-HC (C-X4-C-X23-H-X1-C) type zinc finger motifs (Cui et al., 2018; Jiao et al., 2018). WRKY transcription factors have a strong affinity for the common W-box element, which has a structural base consisting of a heptapeptide sequence and a zinc finger motif (Nan and Gao, 2019). Accordingly, WRKY proteins are classified into three major groups (I-III) based on the number of WRKY domains and the structure of their zinc finger motifs. The group II is further divided into five subclasses: II-a, II-b, II-c, II-d, and II-e. Since the first WRKY gene SPF1, was cloned from sweet potato, a vast number of WRKY members have been discovered in plants (He et al., 2017; Hu et al., 2021).

Genome-wide identification of gene families clarified the structure and function of each gene, and provided a theoretical foundation for future functional verification (Tang et al., 2021). Simultaneously, using the homologous gene alignment of many species, related gene sequences with high affinity for their motifs may be determined, as they are regarded as the probable functions of homologous genes. In 2015, Chen and his collaborators started developing BioCJava (the origin of TBtools). It is a biological large-scale data analysis software written in Java with over 140 functional modules and a good human-computer interface. The JIGplot engine provides a user-friendly interface for displaying graphs (Chen et al., 2020). Here, bioinformatics methods were used to identify the DoWRKY transcription factors. The amino acid alignment, gene structure analysis, phylogenetic tree construction, and chromosomal location were performed by TBtools (v.1.097), MEGA (v.6.06), and some other bioinformatics analysis softwares. The conserved motifs, cis-acting regions, and amino acid binding site found in the data can help enrich our understanding of WRKY genes and roles, as well as provide some theoretical references for further investigation.

As a crucial family of transcription factors in the regulation of plant growth, development, and stress resistance, WRKY transcription factors are involved in a variety of physiological processes in plants. The genome-wide investigation of the WRKY gene family has been undertaken thoroughly in hundreds of species, and the genomes of many species have begun to be sequenced gradually (Li et al., 2019). Owing to the achievement of cutting-edge high-throughput sequencing technology, some Dendrobium species have been widely sequenced in the last 5 years. In this study, the WRKY genes in the Dendrobium genome were identified, and 74 of them met the criteria. This was less than the 91 WRKY transcription factors found in the Arabidopsis genome. The majority of them shared similar domains with AtWRKYs, and they all have the WRKYGQK and zinc finger structures with ZF. The heptapeptide sequences of DoWRKY include WTKTGQK, WKKYGQK, WRKYGRD, WRKYGKK, and other types. The group II WRKY transcription factors in Dendrobium have a maximum of 44 members, whereas groups I and III merely have 13 and 17 members, respectively. The phylogenetic analysis indicated that groups I and III of Dendrobium are more closely related than groups II-a and II-b. The same branch is closely connected, and II-d and II-e are likewise related. The conserved domains showed that DoWRKY genes contain multiple conserved domains. There are additional subgroups of typical conserved domains in addition to the core WRKUGQK conserved domains. The conserved domains of DoWRKY are mostly similar. The group I DoWRKYs have the most conserved domains and may have significant regulatory functions (He et al., 2017; Tang et al., 2021). In Arabidopsis, the proteins AtWRKY25 and AtWRKY23 may interact with MAP kinase four substrate 1 (MKS1), which is essential for the regulation of SA-dependent resistance. The SA-related defense gene PR1 was identified to be expressed at a higher level in an Atwrky33 mutant (Andreasson et al., 2005). AtWRKY50 and AtWRKY51 proteins controled both SA- and low oleic acid-dependent inhibition of JA signaling, resulting in greater resistance to Alternaria brassicicola but increased susceptibility to Botrytis cinerea (Gao et al., 2011). AtWRKY57 regulates the plant immune response process and competes with AtWRKY33 by binding to the promoters of JAZ1 and JAZ5 (Jiang and Yu 2016). DoWRKY11 and DoWRKY14 clustered with AtWRKY25 and 33 in one clade, while DoWRKY40 clustered with AtWRKY23 in another subclade. DoWRKY30, DoWRKY34, and AtWRKY50/51 merged a single branch. These results imply that DoWRKY11, 14, 40 and DoWRKY30, 34 have different regulatory effects on the target genes involved in SA signaling. In addition to being involved in phytohormone signaling, WRKY genes are involved in leaf senescence. AtWRKY22, AtWRKY54, AtWRKY70, AtWRKY57, AtWRKY45, AtWRKY75, AtWRKY6, AtWRKY46, AtWRKY25, AtWRKY53, and AtWRKY55 participate in the progression of leaf senescence. AtWRKY54, 70, has high homology with DoWRKY12, 13, and DoWRKY21, 59, respectively. DoWRKY15 and AtWRKY55 were clustered into one branch, which suggested that they might be involved in the leaves senescence process of D. officinale. Many studies had also shown that some members of the WRKY family helped mediate the biosynthesis of secondary metabolites in plants (Schluttenhofer and Yuan, 2015). D. officinale is also an important Chinese herbal medicine. It will be of great significance if some key DoWRKY genes can be isolated. AtWRKY18 and AtWRKY40 are implicated in camalexin and indole-glucosinolate biosynthesis, and the accumulation of these compounds was required for resistance toward Golovinomyces orontii (Schön et al., 2013). The ectopic expression of AtWRKY18, AtWRK40, and AtMYC2 activated the MEP pathway genes of Salvia sclarea, leading to an increase in abietane diterpene levels (Alfieri et al., 2018). In this study, DoWRKY26 shared a high level of homology with AtWRKY18, 40, and 60; hence, it was suggested that WRKY26 might be involved in the transcriptional regulation of secondary metabolite biosynthetic genes (Figure 8).

Gene duplications are critical to the rapid expansion of the genome and the evolution of gene families (Song et al., 2022c). Polyploidy drives species adaption, genetic diversity, and genome evolution. In the field of horticulture, chromosomal polyploidy produces a number of excellent orchid varieties (Vilcherrez-Atoche et al., 2022). Much evidence indicated that duplication and expansion of WRKY genes occurred in the interspecies (Yang et al., 2018). Numerous evidence suggested that duplication and expansion of WRKY genes occurred among species (Yang et al., 2018). The sequencing of the whole genome of A. shenzhenica boosts our knowledge of the history and evolution of those subfamilies (Zhang et al., 2017). It is notable that whole genome duplication (WGD) has occurred more than once in plant genomes (Clark and Donoghue, 2018). Large-scale tandem duplication or segmental duplication start driving the generation of new genes and speciation evolution (Clark and Donoghue, 2018). Typically, orchids have experienced WGD repetitively, including a historical WGD event and a recent WGD event shared by all orchids. Mycoheterotrophic and parasitic orchids exist with the great majority of ornamental orchids. The loss and survival of symbiotic genes connected to the evolution of particular symbionts spans from the ancestral arbuscular mycorrhiza to the recent ericoid and orchid mycorrhizae (Barrett et al., 2019; Gao et al., 2020). Here, nine tandem duplication gene pairs of DoWRKY were confirmed in peusodochromosomes. Those distributed across multiple scaffolds with a high degree of similarity may result in segmental duplications. This observation is consistent with that of several model plants. The gene structure of DoWRKYs within the same family is comparable, as are the number of CDS and initiation sites, as well as the number and location of introns, despite the major differences within families, such as group I. The number of CDSs and intron sites differs significantly between group I and III, implying that class I WRKY transcription factors have more functions. DoWRKYs are unevenly located on different chromosomes or segments, and some have not yet been located on the chromosome, such as DoWRKY54/59.

The WRKY transcription factor family, as one of the largest TF families, plays a significant and necessary role in plants. Over the years, it has been demonstrated that WRKYs not only contribute to plant growth and development but also exhibit intricate regulatory mechanisms. Here, the identification of DoWRKY reveals the membership of the DoWRKY gene family and elucidates the function and structure of each gene, which could provide a theoretical basis for future functional verification studies. Using the homologous gene alignment of several species, it is possible to simultaneously identify similar homologous genes with great affinity for their motifs as well as infer the potential functions of related subgroup genes. We combined TBtools, MEGA, and other software to identify 74 DoWRKY genes, along with the analysis of amino acid alignment, gene structure, conserved motif, phylogeny, and chromosomal location. Large-scale gene duplication may contribute to the functional preference of the WRKY genes. This includes the emergence of tandem replicated genes. By analyzing conserved motifs and domains, we can divide WRKY genes into three groups. Analysis of phylogenetic tree indicated that some DoWRKY genes shared homology with AtWRKY, which allowed us to speculate on their potential functions. In addition, we preliminarily deduced that DoWRKY5, 54, 57, and 21 may be involved in the JA signaling by analyzing the expression patterns. As a result, we can learn more about WRKY transcription factors and how they work, and we can also use the results of this analysis to learn more about WRKY genes and their functions in other species.