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RAD gene family analysis in cotton provides some key genes for flowering and stress tolerance in upland cotton G. hirsutum



RADIALIS (RAD), belongs to the MYB gene family and regulates a variety of functions including floral dorsoventral asymmetry in Antirrhinum majus and development of fruit proteins in Solanum lycopersicum. RAD genes contain an SNF2_N superfamily domain. Here, we comprehensively identified 68 RAD genes from six different species including Arabidopsis and five species of cotton.


Phylogenetic analysis classified RAD genes into five groups. Gene structure, protein motifs and conserved amino acid residues indicated that GhRAD genes were highly conserved during the evolutionary process. Chromosomal location information showed that GhRAD genes were distributed unevenly on different chromosomes. Collinearity and selection pressure analysis indicated RAD gene family expansion in G. hirsutum and G. barbadense with purifying selection pressure. Further, various growth and stress related promotor cis-acting elements were observed. Tissue specific expression level indicated that most GhRAD genes were highly expressed in roots and flowers (GhRAD2, GhRAD3, GhRAD4 and GhRAD11). Next, GhRAD genes were regulated by phytohormonal stresses (JA, BL and IAA). Moreover, Ghi-miRN1496, Ghi-miR1440, Ghi-miR2111b, Ghi-miR2950a, Ghi-miR390a, Ghi-miR390b and Ghi-miR7495 were the miRNAs targeting most of GhRAD genes.


Our study revealed that RAD genes are evolutionary conserved and might be involved in different developmental processes and hormonal stress response. Data presented in our study could be used as the basis for future studies of RAD genes in cotton.

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MYB gene family members mainly regulate apoptosis, cell differentiation and proliferation. A- MYB, B- MYB and C-MYB are three groups of MYB gene family [1]. These three groups are largely present in vertebrates, fungi, slime molds and insects [2, 3]. For the very first time, MYB gene C1 was isolated from maize and found to regulate biosynthesis of anthocyanin [4]. MYB proteins play a key role in different developmental processes including trichome differentiation, biosynthesis of anthocyanin and flavonoids, floral symmetry, cell proliferation and control of cell cycles [5, 6]. In Antirrhinum majus, two dorsal petals of zygomorphic flowers were larger than ventral and lateral ones with single aborted stamen [7]. RADIALIS (RAD) belongs to MYB gene family. RAD is involved in creating the dorsal identity and regulating the domain activity of DIVIRICATA (DIV) (another transcription factors of MYB gene family) by restricting it to ventral regions of the flower [8]. RAD and DIV, interact with each other and control dorsoventral asymmetry of flowers [9].

In Arabidopsis, RAD and DIV gene families have 198 paralogs and they largely contribute in determining orthology across taxa. MYB genes contained three alpha helices. RAD and DIV have 64 members in Arabidopsis and are further classified into five subgroups. Among five subgroups, RAD falls in the I-box-like subgroup while R-R-type subgroups include DIV. RAD was the result of loss of the second MYB domain of DIV [10]. First two helices of RAD share more similarity with the N terminal MYB domain of DIV as compared to third helix and third helix include DNA binding domain of both RAD and DIV [11].

RAD5, is a member of Snf2 helicase family, encodes two domains including RING-finger domain and HIRAN domain. In yeast (Saccharomyces cerevisiae), RAD5 is the key component in the RAD5-dependent error free branch of postreplication repair. AtRAD5a and AtRAD5b share significant identity to RAD5 of yeast. AtRAD5a and AtRAD5b encodes same domain and these two genes have significant similarities with each other as compared to RAD5 of yeast. However, both AtRAD5a and AtRAD5b differ in their function [12]. On the basis of epistatic analysis, yeast DNA repair genes can be classified into three different groups, including RAD3, RAD52 and RAD6 groups. RAD3 group control nucleotide excision repair and also eliminate DNA damages caused by ultraviolet radiation [13]. However, the RAD52 group mainly functions in the repair of double-strand breaks induced by ionizing radiation and RAD6 group overcomes damages of DNA replication and also arrest replication forks [14]. These DNA repair groups encodes members of the DNA helicase-like-SNF2-gene family [15]. SNF2 family members undergo three main functions including binding of specific proteins to chromatin, destabilization of nucleosome structure and alteration of contact points between DNA and proteins [16, 17].

Cotton is an economic crop of the world and provides raw materials for the textile industry and edible oils [18]. G. hirsutum and G. barbadense are the two allotetraploid species of cotton and provide fiber, seed oil and protein meal to the industry [19]. G. hirsutum is famous for its high yield and moderate fiber qualities, while G. barbadense is important for superior quality fibers and accounts for 3% of the world’s cotton production [20]. Although some RAD genes have been previously reported in model organisms Arabidopsis and yeast, the function of RAD gene family in cotton has not been reported. In the present research, we systematically identified RAD genes in six different species and analyze their phylogenetic relationship, exon and intron structure, conserved protein motifs, biophysical properties, cis-acting elements of promoter regions, sequence logos, chromosomal localization, collinearity and miRNA target sites. Present study will increase our understanding about RAD gene family and provide insight into the molecular mechanisms of RADs in different Gossypium species.


Identification of RAD genes in Gossypium species

In this study we used different bioinformatic analysis to identify RAD genes in various plant species. We identified 17 RAD genes in G. hirsutum, 16 genes in G. barbadense, eight genes each in G. herbaceum and G. arboreum and nine genes in G. raimondii. Furthermore, we also identified 10 RAD genes in Arabidopsis. SMART (, PROSITE ( and InterProscan 63.0 (http: // were used for confirmation of RAD genes in different species. We found that among all the selected plant species, G. hirsutum had the highest number of RAD genes (Table S1) elucidating that during hybridization, GhRAD genes underwent polyploidization and experienced significant dupli- cation events. The biophysical properties of the GhRAD genes including number of amino acids, chromosomal position, isoelectric point, molecular weight, grand average of hydropathicity and protein localization were observed (Table S2). The number of amino acids of GhRAD proteins range from 885 (GhRAD1) to 1374 (GhRAD13). The isoelectric point (pI) of GhRAD genes range from 5.26 (GhRAD14) to (9.04) (GhRAD8). Molecular weight ranges from 76561.78 Da (GhRAD11) to 151381.67 Da (GhRAD13). Moreover, predicted subcellular localization indicated that out of 17 GhRAD genes 16 genes were located in the nucleus while only one gene was located in the cytoplasm.

Phylogenetic analysis, structural features, conserved domain and motifs analysis of GhRAD genes

To study the phylogenetic relationships of RAD gene family, 68 genes from six plant species were used to create a phylogenetic tree (Fig. 1). RAD genes were classified into five clades with 24 members in RAD-a clade, nine members in RAD-b, 14 members in RAD-c while RAD-d and RAD-e contained 18 and two members respectively. RAD-a with maximum number of genes contained RAD proteins from all six plant species while RAD-e, the smallest clade contained two genes from G. hirsutum and G. raimondii. All five clades contained genes from six species except RAD-e and one gene of Arabidopsis (AtRAD6) did not fall in any clade. Moreover, we created another phylogenetic tree to explore the evolutionary relationship between G. hirsutum and Arabidopsis (Fig. S1). Phylogenetic tree divided 17 G. hirsutum and 10 Arabidopsis RAD genes into three clades. Rad-c was the largest clade with 12 members, while Rad-b was the smallest one with four members. GhRAD9 did not fall in any clade, demonstrating that this genes was dissimilar from each other and it has some special function in species evolution.

Fig. 1
figure 1

Phylogenetic analysis of RAD proteins in six different species. Prefixes Gh, Gb, Ghe, Ga, Gr and At were used to identify RAD genes from G. hirsutum, G. barbadense, G. herbaceum, G. arboreum, G. raimondii and Arabidopsis

Next to study the structural features of GhRADs, we analyzed the exon and intron structure, conserved domain and motifs using the GSDS program and MEME tool respectively. Multiple numbers of exons in GhRAD genes ranging from 3 to 24 were observed (Fig. S2). Maximum number of exons were present in GhRAD9 while GhRAD8 had minimum number of exons. Similarly, GhRAD9 contained the highest number of introns while GhRAD16 contained two introns. Number of introns ranged from 2 to 23 for GhRAD genes. GhRAD11 had the longest genomic sequence of more than 8 kb while GhRAD16 had the shortest genomic sequence of 4 kb. Next, we analyzed the conserved domain of GhRAD proteins. Results of conserved domain analysis showed that all GhRAD proteins contain SNF2_N superfamily domain (Fig. S3). Furthermore, we analyzed the motif distribution pattern of GhRADs and found that ten conserved motifs were identified in GhRAD proteins (Fig. S4). Results indicated that GhRAD genes had conserved gene structure and protein motif distribution pattern although the process of gene duplication took place a long time ago during evolution.

Chromosomal position information and synteny analysis

Chromosomal position of GhRADs exhibited that 17 GhRADs were distributed unevenly to 11 chromosomes. Out of 17 genes, six genes were mapped on At sub-genome, while nine GhRAD genes were mapped on Dt subgenome and two genes were present in the form of scaffolds (Fig. S5). This uneven distribution pattern of GhRAD genes on chromosomes illustrated the presence of genetic variability during the evolutionary process. More deeper insights showed that the maximum number of genes were mapped on chromosome D02. Most chromosomes contained a single GhRAD gene and no gene was located on chromosome A02 and A04 of At sub-genome as well as chromosome D03 of Dt sub-genome.

Collinearity analysis between orthologs of At and Dt sub genomes revealed that the different GhRAD and GbRAD loci showed significantly conserved pattern among At and Dt sub-genomes (Fig. 2 A and B and Table S3, S4). Our results indicated that At and Dt sub-genomes are orthologous in the A genome (G. arboreum) or D genome (G. raimondii). Upland cotton (G. hirsutum) was produced after hybridization between G. arboreum and G. raimondii. In our study, 112 and 15 orthologous/paralogous gene pairs were identified in G. hirsutum and G. barbadense respectively.

Fig. 2
figure 2

Collinearity analysis of GhRAD and GbRAD genes. Orthologous/paralogous gene pairs were indicated by blue color lines

Ka/Ks ratios of GhRAD and GbRAD genes were calculated by Ka/Ks calculator 2.0 (Table S3, S4). In the course of evolution, duplicated gene pairs underwent non-functionalization, neofunctionalization and sub-functionalization [21]. In G. hirsutum 74 gene pairs exhibited Ka/Ks values below 0.5, illustrating that GhRAD genes bear purifying selection pressure while 15 genes showed Ka/Ks ratio above 0.5 and only three genes have Ka/Ks ratio of less than 0.1. While in G. barbadense 15 genes exhibited Ka/Ks ratio of less than 0.5. Taken together, our results indicated that purification selection pressure has a great contribution in maintaining the functional divergence of GhRAD and GbRAD genes.

Sequence logos and cis-acting elements

We created the protein sequence logos of Arabidopsis, G. hirsutum and G. raimondii to reveal the conservation of RAD genes during the process of evolution. Sequence logos provide valuable information about sequence similarities of selected plant species. Results indicated that protein sequence logos were conserved among all observed plant species at most sites within and between species across the N and C terminals (Fig. 3).

Fig. 3
figure 3

Sequence logos for conserved amino acid residues in G. hirsutum, G. raimondii and Arabidopsis. Protein sequence logos were created using online software WEBLOG

Next, we identified different cis-acting elements of GhRAD genes. Process of gene expression and transcription can be well studied by analyzing the promotor cis-acting elements present in specific gene. The 17 putative GhRAD promoter regions possessed typical core cis-acting elements that were related to different phytohormones like MeJA, gibberellin, auxin, salicylic acid and abscisic acid (Fig. 4). Most of the GhRAD genes promoter shared numerous elements for plant growth and development such as seed specific regulation, meristem and endosperm expression and cell cycle regulation. Additionally, we found that many drought responsive elements, flavonoid biosynthesis, stress responsive elements, light and low temperature responsive elements, anaerobic induction, anoxic specific inducibility and wound responsive elements were also present in GhRADs promotor regions.

Fig. 4
figure 4

Analysis of promoter cis-acting elements of GhRAD genes. Cis-acting elements were confirmed using PlantCARE database. Cis-acting elements were represented by different colour boxes

Expression profile of GhRAD genes in different tissues and hormonal stresses

Analysis of gene expression patterns is helpful to predict the biological functions of genes. We downloaded the RNA-seq data from NCBI. We investigated the gene expression pattern of GhRADs in various tissue samples and a heatmap was generated (Fig. S6). As shown in figure, GhRAD1 and GhRAD10 showed high transcript level in almost all selected tissues demonstrating that these two genes have multiple biological functions and they have some special functions related to fiber development while GhRAD6 and GhRAD15 were poorly expressed in some tissues showing that these two genes might be pseudo genes and have limited role in cotton growth and development. Next to validate the results of RNA-seq data, we performed qRT-PCR analysis in eight different tissues including root, leaf, stem, flower and 0, 5, 10 and 20 DPA fiber (Fig. 5). Results indicated that most of the GhRAD genes showed preferential expression in root except GhRAD11 whose expression was preferentially high in 20 DPA fiber, indicating its potential role in fiber elongation and biosynthesis of secondary cell wall. GhRAD2, GhRAD3, GhRAD4 and GhRAD11 showed high expression in flower tissues demonstrating that these RAD genes might function in reproductive development.

Fig. 5
figure 5

Tissue specific expression patterns analysis of GhRAD genes. Tissues were collected at different development stages such as root, stem, leaf, flower and 0, 5, 10 and 20 DPA fiber

Next, we inspected the transcript level of GhRADs under three phytohormonal treatments (BL, JA and IAA) at 1, 3, 6 and 12 h of treatment (Fig. 6). Results revealed that most of the GhRAD genes showed up and downregulated expression patterns in different hormones with different time points. GhRAD1, GhRAD2 and GhRAD9 showed upregulated expression in all three selected phytohormonal stresses, illustrating that these genes might respond to various hormone signaling pathways. GhRAD1 showed significantly upregulated expression at 1, 3, 6 and 12 h of GA treatment, indicating its potential role in GA signaling pathway. Moreover, transcript level of GhRAD12 was preferentially high at 1, 3 and 6 h of IAA treatment, suggesting that GhRAD12 might respond positively to IAA signal. Taken together our results illustrated that GhRAD genes were important in several phytohormone signaling pathways.

Fig. 6
figure 6

Expression pattern analysis of GhRAD genes under different phytohormonal stresses including BL, GA and IAA at 1, 3, 6 and 12 h of treatment by qRT-PCR analysis

Prediction of miRNA target sites

In plants, microRNAs (miRNAs) help in regulation of gene expression by activating mRNA translational repression [22]. To explore miRNA mediated post-transcriptional regulation of GhRAD genes, coding sequences of 17 GhRAD genes for putative target sites were searched with the help of psRNATarget server. Results indicated that GhRAD1 was targeted by Ghi-miRN1438 with a site in SNF2_N superfamily domain (Fig. 7 and Table S5). Similarly, GhRAD2, GhRAD3 and GhRAD4 were targeted by Ghi-miRN1496, Ghi-miR1440 and Ghi-miR2111b respectively. Further, Ghi-miR2950a, Ghi-miR390a, Ghi-miR390b and Ghi-miR7495 regulated GhRAD9, GhRAD10, GhRAD11 and GhRAD12 respectively, with SNF2_N superfamily domain. These results suggested that GhRAD genes can be regulated by different miRNAs.

Fig. 7
figure 7

The miRNA-mediated target sites of GhRAD genes. Green color boxes indicated ORFs (open reading frames) of GhRADs. SNF2_N superfamily domain was represented by orange box while miRNA complementary sites with the nucleotide positions of RAD genes were indicated by red color


Cotton is an important economic crop of the world and contributes largely to the textile industry. Different gene families such as GGPPS [23], LOG [24], BES1 [25], GH3 [26], GSK [27], GATL [28], GhPHD [29] and GhAA1 [30] have been identified in cotton, but there is no published research about RAD gene family in cotton. Previous studies reported that RAD51 participate in DNA repair, homologous recombination and genome stability. Members of the recA_RAD51 family perform functions that have differentiated during evolution [31]. Human RAD51 is a homologue of the Escherichia coli RecA protein and function in recombinational repair of double-stranded DNA breaks. Mutations of RAD51 reduce repair of double-stranded DNA breaks. Loss of RAD51 function result in an elevated mutation rate and accumulation of DNA damage therefore increase risk of cancer in human [32]. In Antirrhinum, RADIALIS gene is associated with regulation of floral asymmetry [33]. Induction of recessive mutation in RADIALIS gene produce symmetrical floral morphology. The Arabidopsis RAD gene family contains four members, including RSM1, RSM2, RSM3 and RSM4, RADIALIS-LIKE SANT/MYB 1–4). Arabidopsis RAD-like (RSM) genes might function in developmental process that is not necessarily relevant to the floral architecture [34] [35].

Gossypium genus contain 45 diploid and six tetraploid species [36, 37]. Two allotetraploid species including, G. hirsutum and G. barbadense arisen through interspecific hybridization of A and D genome progenitors [19]. Polyploidy occurred around 1–2 million years ago and produced allotetraploid species [38]. G. hirsutum and G. barbadense are the two oldest allotetraploid species of cotton [39] [40]. Here, we comprehensively identified RAD genes in different plant species to identify the diverse functions of RAD gene family during the process of plant growth and development. Our study will provide basic information about biological and functional mechanisms and could be helpful for further research of RAD gene family in different cotton species.

GhRAD genes show evolutionary conservation

In this study, we identified RAD genes from Arabidopsis and five Gossypium species. Interestingly, the number of GhRAD genes was higher as compared to GaRAD and GrRAD genes, possibly because G. hirsutum is an allotetraploid crop resulting from hybridization of A and D genome progenitors. In upland cotton, both At and Dt sub-genome donors are orthologous relatives, leading to the GhRAD gene duplication [41]. Because of duplication and doubling of GhRAD genes, the numbers of GhRAD genes were equal to the total number of GaRAD and GrRAD genes. Phylogenetic analysis naturally classified RAD genes into five clades from RAD-a to RAD-e with 24 genes in RAD-a clade and two genes in RAD-e clade. Most of the RAD genes from diploids and allotetraploids were distributed closely in the phylogenetic tree, indicating that tetraploid cotton was produced after the hybridization of A and D genomes progenitors. From the phylogenetic tree we observed that RAD-a, RAD-b and RAD-d clades were ancient groups containing RAD genes from all selected plant species. Whereas, RAD-e clade might be more advanced containing RAD genes from only two selected plant species including G. hirsutum and G. raimondii, however, RAD-c clade lacks the genes from Arabidopsis.

Analysis of sequence logos of G. hirsutum, G. raimondii and Arabidopsis also supported these findings as the results of sequence logos showed significantly conserved pattern of amino acid across N and C terminals. Each conserved amino acid showed similar positions in three different species.

Interaction between transcription factors and promoter binding sites is important for gene regulation at the transcriptional level and transcriptional regulation is mainly responsible for regulation of gene expression. Different external signals activated inducible promoters and cis-acting elements in promoter regions are specific and consistent, for example, cis-acting elements of AuxRE were generally present in auxin-induced promoters regions [42], similarly AT-rich cis-acting elements, I-box, G-box, and GT1-motif were generally present in the light-induced promoters [43,44,45]. Likewise, CACG and CATGTG cis-acting elements were found in drought-induced promoters [46]. In our study, we extracted the upstream promoter fragments of candidate genes. Phytohormone (IAA, SA, ABA, GA and MeJA) responsive cis-acting elements were present in GhRAD genes promotors. Previous studies have shown that phytohormones maintain the integrity of plant cell walls. MeJA mediates gene expression in responses to plant injury [47]. Auxin regulates cell walls by induction of cell wall looseness [48]. In strawberry, ethylene promotes fruit softening and ripening by regulating the synthesis of pectin [49]. Stress responsive cis-acting elements help plants to respond quickly to stress and improve plant resistance to environmental stresses by activating different stress related genes. GhRAD promoter regions contain different cis-acting elements related to phyto- hormones, plant growth and development, seed specific regulation, meristem and endosperm expression and cell cycle regulation. In the present study, we found the uneven distribution of GhRADs on the chromosomes of At and Dt sub-genome. Uneven distribution of GhRAD genes indicated that during evolution and hybridization, these genes might have experienced gene duplication.

Gene structure is important to predict gene evolution [50]. Here, we found that the number of exons ranged from 3 to 24 while the number of introns ranged from 2 to 23. We observed that length of intron is significantly different, suggesting that during functional diversification of GhRADs intron length might play major roles. It has been reported that gene structure is associated with the evolution of different plant species [51]. The evolutionary analysis within the RAD genes showed that most of the RAD genes were greatly conserved during evolution. As RAD genes introns were not lost during evolution and at the early expansion stages of evolution, these genes diverged, whereas, over evolutionary time, other genes lost their introns [52], indicating that group specific genes may have similar functions. Insertion/deletion events might be the reason for structural differences of exon/intron and may help to identify different evolutionary mechanisms [53]. Gene families with fewer number of introns are considered to be advanced gene families [54] while gene families showing more introns have acquired some novel functions during the evolutionary process. Furthermore, motif distribution pattern of GhRAD genes was conserved indicating that the proteins with similar kind of motif distribution pattern might have some specific functions in cotton growth and development.

Diverse expression patterns of GhRADs, prediction of their miRNA target sites and selection pressure

In the recent years, different researches have been done to identify the function of RAD genes in different plant species but no research has been conducted to find the functional mechanisms of RAD genes in cotton. As our results indicated that promotor of GhRADs contain elements related to phytohormones, plant growth and development, seed specific regulation, meristem and endosperm expression and cell cycle regulation, so to check the potential regulatory functions of GhRADs during cotton growth and development, we evaluated the transcript patterns of 17 GhRAD genes using qRT-PCR. Results indicated that many GhRAD genes showed high expression in roots. However, GhRAD2, GhRAD3, GhRAD4 and GhRAD11 showed significantly high expression in flower tissues. Results indicated that GhRAD genes might be playing a positive role in root and flower development. All GhRAD genes showed poor expression in fiber development stages except GhRAD11 had relatively high expression at 20 DPA fiber.

Different research studies indicated that phytohormones respond positively to abiotic stress response [55]. Auxin response factors (ARFs) activate auxin responsive genes and ARFs are the potential mediators that help the plants to respond to adverse environmental conditions [56]. Ethylene response factors of AP2/ARF transcription factor family play a positive function in plant growth, disease resistance and phytohormone response [57]. In this study, analysis of GhRADs for three different phytohormones indicated that GhRAD genes can be regulated by the exposure of phytohormones such as BL, IAA and JA. GhRAD1 and GhRAD2 showed upregulated expression for observed phytohormones, suggesting that these genes may have a positive role in phytohormones signaling.

Previous studies reported that miRNAs have significant functions in plant growth and development, regulation of cell growth and different metabolism associated with cotton fiber development and also respond to different environmental stresses including cold, heat and drought [58]. In the past few years, different miRNAs have been identified in cotton and they are preferentially expressed in different vegetative tissues as well as during abiotic stresses [59, 60]. For instance, 32 families of miRNA were found to be differentially expressed in cotton ovules and leaves. With the help of RNA-seq data of cotton leaf and ovule, a total of 65 families of cotton miRNA have been identified [61]. In our study we identified different GhRAD genes targeted by various miRNA. Precisely, Ghi-miRN1496, Ghi-miR1440, Ghi-miR2111b, Ghi-miR2950a, Ghi-miR390a, Ghi-miR390b and Ghi-miR7495 were the miRNAs targeting most of GhRAD genes. Our results will lay the foundation for future research about biological functions of GhRAD miRNAs and also their target sites in G. hirsutum.

Next we calculated the Ka/Ks ratios of GhRADs and GbRADs. Genes with Ka/Ks = 1.0 are considered as pseudogenes as a result of neutral selection, Ka/Ks less than1.0 demonstrates the tendency of duplicated genes for purifying selection, while Ka/Ks ratios greater than 1.0 exhibits positive selection of accelerated evolution. Ka/Ks values of most GhRAD and GbRAD were less than 1 indicating that during the long-term evolutionary process, RAD gene family experienced purifying selection pressure.


In the present study, we conducted a comprehensive genome wide analysis to identify phylogenetic relationship, sequence conservation and biological functions of RAD genes. Phylogenetic analysis divided RAD genes into five clades on the basis of sequence homology. Sequence logos, exon-intron structure, protein motifs and conserved domain analysis indicated that GhRAD genes were highly conserved during evolution with the uneven distribution on the chromosomes. Collinearity and selection pressure analysis indicated the expansion of RAD gene family in G. hirsutum and G. barbadense with purifying selection pressure. Promoter cis-acting elements analysis indicated the presence of several plant growth and stress related regulatory elements. Tissue specific expression pattern analysis of GhRAD genes indicated that some GhRAD genes showed significantly high expression in roots and flowers, except GhRAD11 had maximum expression at 20 DPA fiber. Further, GhRADs showed regulatory response under three phytohormonal stresses indicating candidate genetic material for cotton breeding against different stresses.


Identification of RAD gene family

The database of cotton species including (G. hirsutum, G. raimondii, G. arboreum, G. barbadense and G. herbaceum) were acquired from the Cotton FGD ( [62]. The Arabidopsis protein sequences of RAD genes were acquired from Arabidopsis Information Resource, version 10 (TAIR 10) ( The AtRAD genes were used as queries to identify the RAD genes in other plant species. SMART ( and Interproscan 63.0 ( were used to confirm RAD protein sequences [63, 64]. Furthermore, Pfam: ( and hidden Markov model (HMM) was used to identify the conserved domain of RADs [65]. Moreover, to predict the biophysical properties of RAD genes, ExPASy-ProtParam tool ( was used. Subcellular localization was predicted by CELLO v2.5 server [66].

Phylogenetic analysis and sequence logos

For phylogenetic analysis of RAD gene family, Clustal W was used for multiple sequence alignment [67] with the default settings and the phylogenetic tree was generated by iTOL [68] with 1000 bootstrap replicates. For sequence logos, RAD proteins of Arabidopsis, G. hirsutum and G. raimondii were aligned with Clustal W [69] and protein sequence logos were created using online software WEBLOG with default parameters [70].

Chromosomal location, gene structure and analysis of protein motif

Chromosomal position of GhRADs was determined by cotton genome annotation data ( hirsutum/NAU-NBI_G) and extracted gff3-files was used in MapInspect software ( to map genes to their corresponding chromosomes. For gene structure analysis of GhRADs, Gene Structure Display Server 2.0 (GSDS) was used ( [71]. Online program MEME ( [72] was used to determined conserved motifs of GhRAD gene family and finally motifs were displayed by TBtools [73].

Promoter cis-acting elements, synteny, Ka/Ks ratio and transcriptome data analysis

For analysis of promotor cis-acting element, 2-kb upstream promotor regions were downloaded from Cotton FGD website [62] and subjected to Plant CARE Database [74]. During collinearity, analysis orthologous/paralogous data were obtained by the previously described methods [75, 76] and circos was used to generate the figure [77]. Non-synonymous (Ka) and synonymous (Ks) divergence level ratios were calculated by aligning duplicated gene pair protein sequences in Clustal X 2.0, after which they were translated into complementary DNA (cDNA) sequences using the PAL2NAL program ( Finally, Ka and Ks values were calculated with the help of the CODEML program using the PAML package. For expression pattern analysis of GhRADs, RNA seq data ( was used and heatmap was generated by using TBtools [73].

Prediction of miRNA target sites of GhRAD genes

Plant MicroRNA database ( [78], miRBase (http:// [79] and the Cotton EST database ( were used to obtain MicroRNA sequences of G. hirsutum. Predictions of miRNA target sites were done with the help of psRNATarget server ( as described previously [67].

RNA extraction and RT-qPCR analysis

In this research, the CRI24 variety was used for gene expression analysis. Total RNA was extracted by collecting cotton samples from the field. For tissue specific expression pattern analysis, plant samples such as root, stem, leaf, flower and 0, 5, 1 and 20 DPA fiber were used. Similarly, for hormonal stresses, cotton seedlings were subjected to JA, BL and IAA treatment for 1, 3, 6 and 12 h. RNA extraction was done with the help of RNAprep Pure Plant Kit (Tiangen, Beijing, China), after that cDNA was synthesized by using the Prime-Script®RT reagent kit (Takara, Dalian, China). Green qPCR SuperMix was used to conduct qRT-PCR assay and GhHis3 (GenBank accession no. AF024716) was used as internal control. PCR reaction was done in three replications. Results of qRT-PCR were calculated as described previously [80]. Primers used for RT-qPCR analysis were presented in (Table S6).

Availability of data and materials

All data used in this study are included in this article and additional files. Transcriptome data used for gene expression analysis could be downloaded from ( The Genome sequence and annotation datasets that supported our findings are available in: A. thaliana: (, COTTON: ( and Other species: ( All the genes used in this study for phylogeny and subsequent analysis are mentioned in additional file 13, table S7 and can be downloaded from Cotton FGD (







Gibberellic acid


Indole − 3-acetic acid


3 Dimension


Days post anthesis


  1. 1.

    Klempnauer K-H, Gonda TJ, Bishop JM. Nucleotide sequence of the retroviral leukemia gene v-myb and its cellular progenitor c-myb: the architecture of a transduced oncogene. Cell. 1982;31(2):453–63.

    CAS  PubMed  Google Scholar 

  2. 2.

    Weston K. Myb proteins in life, death and differentiation. Curr Opin Genet Dev. 1998;8(1):76–81.

    CAS  PubMed  Google Scholar 

  3. 3.

    Nomura N, Takahashi M, Matsui M, Ishii S, Date T, Sasamoto S, et al. Isolation of human cDNA clones of myb-related genes, A-myb and B-myb. Nucleic Acids Res. 1988;16(23):11075–89.

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Paz-Ares J, Ghosal D, Wienand U, Peterson P, Saedler H. The regulatory c1 locus of Zea mays encodes a protein with homology to myb proto-oncogene products and with structural similarities to transcriptional activators. EMBO J. 1987;6(12):3553–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Raimundo J, Sobral R, Bailey P, Azevedo H, Galego L, Almeida J, et al. A subcellular tug of war involving three MYB-like proteins underlies a molecular antagonism in a ntirrhinum flower asymmetry. Plant J. 2013;75(4):527–38.

    CAS  PubMed  Google Scholar 

  6. 6.

    Zhai R, Wang Z, Zhang S, Meng G, Song L, Wang Z, et al. Two MYB transcription factors regulate flavonoid biosynthesis in pear fruit (Pyrus bretschneideri Rehd.). J Exp Bot. 2016;67(5):1275–84.

    CAS  PubMed  Google Scholar 

  7. 7.

    Luo D, Carpenter R, Vincent C, Copsey L, Coen E. Origin of floral asymmetry in Antirrhinum. Nature. 1996;383(6603):794–9.

    CAS  PubMed  Google Scholar 

  8. 8.

    Reardon W, Gallagher P, Nolan KM, Wright H, Cardeñosa-Rubio MC, Bragalini C, et al. Different outcomes for the MYB floral symmetry genes DIVARICATA and RADIALIS during the evolution of derived actinomorphy in P lantago. New Phytol. 2014;202(2):716–25.

    CAS  PubMed  Google Scholar 

  9. 9.

    Baxter CE, Costa MMR, Coen ES. Diversification and co-option of RAD-like genes in the evolution of floral asymmetry. Plant J. 2007;52(1):105–13.

    CAS  PubMed  Google Scholar 

  10. 10.

    Stevenson CE, Burton N, Costa MM, Nath U, Dixon RA, Coen ES, et al. Crystal structure of the MYB domain of the RAD transcription factor from Antirrhinum majus. Proteins: Struct Funct Bioinformatics. 2006;65(4):1041–5.

    CAS  Google Scholar 

  11. 11.

    Yanhui C, Xiaoyuan Y, Kun H, Meihua L, Jigang L, Zhaofeng G, et al. The MYB transcription factor superfamily of Arabidopsis: expression analysis and phylogenetic comparison with the rice MYB family. Plant Mol Biol. 2006;60(1):107–24.

    PubMed  Google Scholar 

  12. 12.

    Chen I-P, Mannuss A, Orel N, Heitzeberg F, Puchta H. A homolog of ScRAD5 is involved in DNA repair and homologous recombination in Arabidopsis. Plant Physiol. 2008;146(4):1786–96.

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Prakash S, Prakash L. Nucleotide excision repair in yeast. Mutat Res/Fundament Mol Mechanisms Mutagen. 2000;451(1–2):13–24.

    CAS  Google Scholar 

  14. 14.

    Aylon Y, Kupiec M. New insights into the mechanism of homologous recombination in yeast. Mutat Res/Rev Mutat Res. 2004;566(3):231–48.

    CAS  Google Scholar 

  15. 15.

    Flaus A, Martin DM, Barton GJ, Owen-Hughes T. Identification of multiple distinct Snf2 subfamilies with conserved structural motifs. Nucleic Acids Res. 2006;34(10):2887–905.

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Pazin MJ, Kadonaga JT. SWI2/SNF2 and related proteins: ATP-driven motors that disrupt-protein–DNA interactions? Cell. 1997;88(6):737–40.

    CAS  PubMed  Google Scholar 

  17. 17.

    Sprouse RO, Brenowitz M, Auble DT. Snf2/Swi2-related ATPase Mot1 drives displacement of TATA-binding protein by gripping DNA. EMBO J. 2006;25(7):1492–504.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Gong Q, Yang Z, Wang X, Butt HI, Chen E, He S, et al. Salicylic acid-related cotton (Gossypium arboreum) ribosomal protein GaRPL18 contributes to resistance to Verticillium dahliae. BMC Plant Biol. 2017;17(1):1–15.

    Google Scholar 

  19. 19.

    Chen ZJ, Scheffler BE, Dennis E, Triplett BA, Zhang T, Guo W, et al. Toward sequencing cotton (Gossypium) genomes. Plant Physiol. 2007;145(4):1303–10.

    CAS  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Rathore KS, Campbell LM, Sherwood S, Nunes E. Cotton (Gossypium hirsutum L.). In: Agrobacterium protocols. New York: Springer; 2015. p. 11–23.

  21. 21.

    Lynch M, Conery JS. The evolutionary fate and consequences of duplicate genes. science. 2000;290(5494):1151–5.

    CAS  PubMed  Google Scholar 

  22. 22.

    Zhang N, Zhang D, Chen SL, Gong B-Q, Guo Y, Xu L, et al. Engineering artificial microRNAs for multiplex gene silencing and simplified transgenic screen. Plant Physiol. 2018;178(3):989–1001.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Ali F, Qanmber G, Wei Z, Yu D, Hui Li Y, Gan L, et al. Genome-wide characterization and expression analysis of geranylgeranyl diphosphate synthase genes in cotton (Gossypium spp.) in plant development and abiotic stresses. BMC Genomics. 2020;21(1):1–15.

    Google Scholar 

  24. 24.

    Wang R, Liu L, Kong Z, Li S, Lu L, Chen G, et al. Identification of GhLOG gene family revealed that GhLOG3 is involved in regulating salinity tolerance in cotton (Gossypium hirsutum L.). Plant Physiol Biochem. 2021;1:328–40.

  25. 25.

    Liu Z, Qanmber G, Lu L, Qin W, Liu J, Li J, et al. Genome-wide analysis of BES1 genes in Gossypium revealed their evolutionary conserved roles in brassinosteroid signaling. Sci China Life Sci. 2018;61(12):1566–82.

    CAS  PubMed  Google Scholar 

  26. 26.

    Yu D, Qanmber G, Lu L, Wang L, Li J, Yang Z, et al. Genome-wide analysis of cotton GH3 subfamily II reveals functional divergence in fiber development, hormone response and plant architecture. BMC Plant Biol. 2018;18(1):1–18.

    CAS  Google Scholar 

  27. 27.

    Wang L, Yang Z, Zhang B, Yu D, Liu J, Gong Q, et al. Genome-wide characterization and phylogenetic analysis of GSK gene family in three species of cotton: evidence for a role of some GSKs in fiber development and responses to stress. BMC Plant Biol. 2018;18(1):1–21.

    Google Scholar 

  28. 28.

    Zheng L, Wu H, Qanmber G, Ali F, Wang L, Liu Z, et al. Genome-wide study of the GATL gene family in Gossypium hirsutum L. reveals that GhGATL genes act on pectin synthesis to regulate plant growth and Fiber elongation. Genes. 2020;11(1):64.

    CAS  PubMed Central  Google Scholar 

  29. 29.

    Wu H, Zheng L, Qanmber G, Guo M, Wang Z, Yang Z. Response of phytohormone mediated plant homeodomain (PHD) family to abiotic stress in upland cotton (Gossypium hirsutum spp.). BMC Plant Biol. 2021;21(1):1–20.

    Google Scholar 

  30. 30.

    Qanmber G, Lu L, Liu Z, Yu D, Zhou K, Huo P, et al. Genome-wide identification of GhAAI genes reveals that GhAAI66 triggers a phase transition to induce early flowering. J Exp Bot. 2019;70(18):4721–36.

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Lin Z, Kong H, Nei M, Ma H. Origins and evolution of the recA/RAD51 gene family: evidence for ancient gene duplication and endosymbiotic gene transfer. Proc Natl Acad Sci. 2006;103(27):10328–33.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Lose F, Lovelock P, Chenevix-Trench G, Mann GJ, Pupo GM, Spurdle AB. Variation in the RAD51 gene and familial breast cancer. Breast Cancer Res. 2006;8(3):1–7.

    Google Scholar 

  33. 33.

    Corley SB, Carpenter R, Copsey L, Coen E. Floral asymmetry involves an interplay between TCP and MYB transcription factors in Antirrhinum. Proc Natl Acad Sci. 2005;102(14):5068–73.

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Urzainqui A, Bevan M, Martin C, Smeekens S, Tonelli C, Paz-Ares J, et al. The MYB transcription factor superfamily of Arabidopsis: expression analysis and phylogenetic comparison with the rice MYB family. Plant Mol Biol. 2006;60(1):107–24 PubMed PMID.

    Google Scholar 

  35. 35.

    Riechmann JL, Heard J, Martin G, Reuber L, Jiang C-Z, Keddie J, et al. Arabidopsis transcription factors: genome-wide comparative analysis among eukaryotes. science. 2000;290(5499):2105–10.

    CAS  PubMed  Google Scholar 

  36. 36.

    Hawkins JS, Kim H, Nason JD, Wing RA, Wendel JF. Differential lineage-specific amplification of transposable elements is responsible for genome size variation in Gossypium. Genome Res. 2006;16(10):1252–61.

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Grover C, Zhu X, Grupp K, Jareczek J, Gallagher J, Szadkowski E, et al. Molecular confirmation of species status for the allopolyploid cotton species, Gossypium ekmanianum Wittmack. Genet Resour Crop Evol. 2015;62(1):103–14.

    Google Scholar 

  38. 38.

    Wendel JF, Cronn RC. Polyploidy and the evolutionary history of cotton. Adv Agron. 2003;78:139.

    Google Scholar 

  39. 39.

    Marcussen T, Sandve SR, Heier L, Spannagl M, Pfeifer M, Jakobsen KS, et al. Ancient hybridizations among the ancestral genomes of bread wheat. science. 2014;345(6194):1250092.

  40. 40.

    Chalhoub B, Denoeud F, Liu S, Parkin IA, Tang H, Wang X, et al. Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome. science. 2014;345(6199):950–3.

    CAS  PubMed  Google Scholar 

  41. 41.

    Li F, Fan G, Lu C, Xiao G, Zou C, Kohel RJ, et al. Genome sequence of cultivated upland cotton (Gossypium hirsutum TM-1) provides insights into genome evolution. Nat Biotechnol. 2015;33(5):524–30.

    PubMed  Google Scholar 

  42. 42.

    Ulmasov T, Murfett J, Hagen G, Guilfoyle TJ. Aux/IAA proteins repress expression of reporter genes containing natural and highly active synthetic auxin response elements. Plant Cell. 1997;9(11):1963–71.

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Foster R, Izawa T, Chua NH. Plant bZIP proteins gather at ACGT elements. FASEB J. 1994;8(2):192–200.

    CAS  PubMed  Google Scholar 

  44. 44.

    Gilmartin PM, Memelink J, Hiratsuka K, Kay SA, Chua N-H. Characterization of a gene encoding a DNA binding protein with specificity for a light-responsive element. Plant Cell. 1992;4(7):839–49.

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45.

    Lam E, Chua N-H. ASF-2: a factor that binds to the cauliflower mosaic virus 35S promoter and a conserved GATA motif in cab promoters. Plant Cell. 1989;1(12):1147–56.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Tran L-SP, Nakashima K, Sakuma Y, Simpson SD, Fujita Y, Maruyama K, et al. Isolation and functional analysis of Arabidopsis stress-inducible NAC transcription factors that bind to a drought-responsive cis-element in the early responsive to dehydration stress 1 promoter. Plant Cell. 2004;16(9):2481–98.

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Creelman RA, Tierney ML, Mullet JE. Jasmonic acid/methyl jasmonate accumulate in wounded soybean hypocotyls and modulate wound gene expression. Proc Natl Acad Sci. 1992;89(11):4938–41.

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Majda M, Robert S. The role of auxin in cell wall expansion. Int J Mol Sci. 2018;19(4):951.

    PubMed Central  Google Scholar 

  49. 49.

    Villarreal NM, Marina M, Nardi CF, Civello PM, Martínez GA. Novel insights of ethylene role in strawberry cell wall metabolism. Plant Sci. 2016;252:1–11.

    CAS  PubMed  Google Scholar 

  50. 50.

    Xu G, Guo C, Shan H, Kong H. Divergence of duplicate genes in exon–intron structure. Proc Natl Acad Sci. 2012;109(4):1187–92.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. 51.

    Roy SW, Gilbert W. The evolution of spliceosomal introns: patterns, puzzles and progress. Nat Rev Genet. 2006;7(3):211–21.

    PubMed  Google Scholar 

  52. 52.

    Qanmber G, Ali F, Lu L, Mo H, Ma S, Wang Z, et al. Identification of histone H3 (HH3) genes in Gossypium hirsutum revealed diverse expression during ovule development and stress responses. Genes. 2019;10(5):355.

    CAS  PubMed Central  Google Scholar 

  53. 53.

    Lecharny A, Boudet N, Gy I, Aubourg S, Kreis M. Introns in, introns out in plant gene families: a genomic approach of the dynamics of gene structure. J Struct Funct Genom. 2003;3(1):111–6.

    CAS  Google Scholar 

  54. 54.

    Roy SW, Penny D. A very high fraction of unique intron positions in the intron-rich diatom Thalassiosira pseudonana indicates widespread intron gain. Mol Biol Evol. 2007;24(7):1447–57.

    CAS  PubMed  Google Scholar 

  55. 55.

    Roosjen M, Paque S, Weijers D. Auxin response factors: output control in auxin biology. J Exp Bot. 2018;69(2):179–88.

    CAS  PubMed  Google Scholar 

  56. 56.

    Bouzroud S, Gouiaa S, Hu N, Bernadac A, Mila I, Bendaou N, et al. Auxin response factors (ARFs) are potential mediators of auxin action in tomato response to biotic and abiotic stress (Solanum lycopersicum). PLoS One. 2018;13(2):e0193517.

    PubMed  PubMed Central  Google Scholar 

  57. 57.

    Huang P-Y, Catinot J, Zimmerli L. Ethylene response factors in Arabidopsis immunity. J Exp Bot. 2016;67(5):1231–41.

    CAS  PubMed  Google Scholar 

  58. 58.

    Hou J, Lu D, Mason AS, Li B, Xiao M, An S, et al. Non-coding RNAs and transposable elements in plant genomes: emergence, regulatory mechanisms and roles in plant development and stress responses. Planta. 2019;250(1):23–40.

    CAS  PubMed  Google Scholar 

  59. 59.

    Liu G, Wu M, Pei W, Li X, Wang N, Ma J, et al. A comparative analysis of small RNAs between two upland cotton backcross inbred lines with different fiber length: expression and distribution. Crop J. 2019;7(2):198–208.

    Google Scholar 

  60. 60.

    Yin Z, Li Y, Yu J, Liu Y, Li C, Han X, et al. Difference in miRNA expression profiles between two cotton cultivars with distinct salt sensitivity. Mol Biol Rep. 2012;39(4):4961–70.

    CAS  PubMed  Google Scholar 

  61. 61.

    Xie F, Jones DC, Wang Q, Sun R, Zhang B. Small RNA sequencing identifies miRNA roles in ovule and fibre development. Plant Biotechnol J. 2015;13(3):355–69.

    CAS  PubMed  Google Scholar 

  62. 62.

    Zhu T, Liang C, Meng Z, Sun G, Meng Z, Guo S, et al. CottonFGD: an integrated functional genomics database for cotton. BMC Plant Biol. 2017;17(1):1–9.

    CAS  Google Scholar 

  63. 63.

    Jones P, Binns D, Chang H-Y, Fraser M, Li W, McAnulla C, et al. InterProScan 5: genome-scale protein function classification. Bioinformatics. 2014;30(9):1236–40.

    CAS  PubMed  PubMed Central  Google Scholar 

  64. 64.

    Letunic I, Doerks T, Bork P. SMART: recent updates, new developments and status in 2015. Nucleic Acids Res. 2015;43(D1):D257–60.

    CAS  PubMed  Google Scholar 

  65. 65.

    Finn RD, Coggill P, Eberhardt RY, Eddy SR, Mistry J, Mitchell AL, et al. The Pfam protein families database: towards a more sustainable future. Nucleic Acids Res. 2016;44(D1):D279–85.

    CAS  PubMed  Google Scholar 

  66. 66.

    Yu CS, Lin CJ, Hwang JK. Predicting subcellular localization of proteins for gram-negative bacteria by support vector machines based on n-peptide compositions. Protein Sci. 2004;13(5):1402–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  67. 67.

    Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, et al. Clustal W and Clustal X version 2.0. Bioinformatics. 2007;23(21):2947–8.

    CAS  PubMed  Google Scholar 

  68. 68.

    Trifinopoulos J, Nguyen L-T, von Haeseler A, Minh BQ. W-IQ-TREE: a fast online phylogenetic tool for maximum likelihood analysis. Nucleic Acids Res. 2016;44(W1):W232–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  69. 69.

    Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG. The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 1997;25(24):4876–82.

    CAS  PubMed  PubMed Central  Google Scholar 

  70. 70.

    Crooks GE, Hon G, Chandonia J-M, Brenner SE. WebLogo: a sequence logo generator. Genome Res. 2004;14(6):1188–90.

    CAS  PubMed  PubMed Central  Google Scholar 

  71. 71.

    Hu B, Jin J, Guo A-Y, Zhang H, Luo J, Gao G. GSDS 2.0: an upgraded gene feature visualization server. Bioinformatics. 2015;31(8):1296–7.

    PubMed  Google Scholar 

  72. 72.

    Bailey TL, Williams N, Misleh C, Li WW. MEME: discovering and analyzing DNA and protein sequence motifs. Nucleic Acids Res. 2006;34(suppl_2):W369–73.

    CAS  PubMed  PubMed Central  Google Scholar 

  73. 73.

    Chen C, Chen H, Zhang Y, Thomas HR, Frank MH, He Y, et al. TBtools: an integrative toolkit developed for interactive analyses of big biological data. Mol Plant. 2020;13(8):1194–202.

    CAS  PubMed  Google Scholar 

  74. 74.

    Lescot M, Déhais P, Thijs G, Marchal K, Moreau Y, Van de Peer Y, et al. PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences. Nucleic Acids Res. 2002;30(1):325–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  75. 75.

    Suyama M, Torrents D, Bork P. PAL2NAL: robust conversion of protein sequence alignments into the corresponding codon alignments. Nucleic Acids Res. 2006;34(suppl_2):W609–12.

    CAS  PubMed  PubMed Central  Google Scholar 

  76. 76.

    Yang Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol. 2007;24(8):1586–91.

    CAS  PubMed  Google Scholar 

  77. 77.

    Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, et al. Circos: an information aesthetic for comparative genomics. Genome Res. 2009;19(9):1639–45.

    CAS  PubMed  PubMed Central  Google Scholar 

  78. 78.

    Zhang Z, Yu J, Li D, Zhang Z, Liu F, Zhou X, et al. PMRD: plant microRNA database. Nucleic Acids Res. 2010;38(suppl_1):D806–13.

    CAS  PubMed  Google Scholar 

  79. 79.

    Kozomara A, Griffiths-Jones S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 2014;42(D1):D68–73.

    CAS  PubMed  Google Scholar 

  80. 80.

    Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2− ΔΔCT method. methods. 2001;25(4):402–8.

    CAS  PubMed  Google Scholar 

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We thank Huo Peng (Zhengzhou Research Center, Institute of Cotton Research of CAAS, Zhengzhou) for technical assistance.


This research was financially supported by the National Natural Science Foundation of China (31621005, 31701476).

Author information




NZ and GW designed the research project. NK, GQ, LL and YXW performed the experiments and analyzed the data. NK, GQ, XZ, ZS and LZ wrote and reviewed the manuscript. All authors read and approved the manuscript.

Corresponding authors

Correspondence to Na Zhao or Gang Wang.

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The research using field studies of collected plant material, comply with relevant institutional, national, and international guidelines and legislation. The plant material used in this study was provided by State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences. No specific permits are required for sample collection in this study. This article did not contain any studies with wild species at risk of extinction.

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Supplementary Information

Additional file 1

: Figure S1. Phylogenetic relationship between G. hirsutum and Arabidopsis. Phylogenetic tree was constructed using RAD protein sequences by iTOL software.

Additional file 2

: Figure S2. Gene structure of GhRAD genes. Yellow boxes represent exons while black lines indicate introns.

Additional file 3

: Figure S3. Conserved domain analysis of GhRAD proteins. Each domain was represented in different colors and their names were mentioned with color boxes.

Additional file 4 : Figure S4.

Protein motif analysis of GhRAD proteins. Each motif was indicated with different color and phylogenetic analysis grouped GhRAD proteins according to the protein motif distribution pattern.

Additional file 5

: Figure S5. Chromosomal distribution of GhRAD genes. MapInspect software ( was used to map genes to their corresponding chromosomes.

Additional file 6

: Figure S6. RNA-seq data analysis of 17 GhRAD genes in root, stem, leaf, torus, petal, stamen, pistil, calycle, − 3, − 1, 0, 1, 3, 5, 10, 20, 25 and 35 DPA ovules and 5, 10, 20 and 25 DPA fiber.

Additional file 7

: Table S1. RAD5/RAD16-like Gene Family members.

Additional file 8

: Table S2. Biophysical properties of the GhRAD genes.

Additional file 9

: Table S3. Orthologous.paralogous gene pairs and Ks/Ks values of GhRAD gene family members.

Additional file 10

: Table S4. Orthologous.paralogous gene pairs and Ks/Ks values of GbRAD gene family members.

Additional file 11

: Table S5. MicroRNA (miRNA) target sites of GhRAD genes.

Additional file 12

: Table S6. GhRAD genes primers for qRT-PCR.

Additional file 13

: Table S7. Proposed name of RAD gene family members.

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Kabir, N., Zhang, X., Liu, L. et al. RAD gene family analysis in cotton provides some key genes for flowering and stress tolerance in upland cotton G. hirsutum. BMC Genomics 23, 40 (2022).

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  • RAD
  • G. hirsutum
  • Phylogenetic tree
  • Phytohormones
  • Sequence logs
  • Cis-acting elements