Comparative analysis of SIMILAR TO RCD ONE (SRO) family from tetraploid and diploid cottons depicts its role in growth and development

doi:10.21203/rs.3.rs-3321308/v1

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Comparative analysis of SIMILAR TO RCD ONE (SRO) family from tetraploid and diploid cottons depicts its role in growth and development

https://doi.org/10.21203/rs.3.rs-3321308/v1

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Background

SRO (Similar to RCD1) genes family is largely recognized for their importance in growth, development and in responding to environmental stresses. However, genome-wide identification and functional characterization of SRO genes from cotton species have not reported so far.

Results

A total of 36 SRO genes were identified from four cotton species. Phylogenetic analysis divided these genes into three groups with distinct structure. Syntenic and chromosomal distribution analysis indicated uneven distribution of GaSRO, GrSRO, GhSRO and GbSRO genes on A2, D5 genomes, Gh-At, Gh-Dt and Gb-At, Gb-Dt subgenomes, respectively. Gene duplication analysis revealed the presence of six duplicated gene pairs among GhSRO genes. In promoter analysis, several elements responsive to growth, development and hormones were interpreted in GhSRO genes, implying the reason for their induction during growth and developmental stages. Several miRNAs responsive to plant growth and abiotic stress responses were predicted that target 12 GhSRO genes. Organ-specific expression profiling explored the roles of GhSRO genes in one or more tissues. In addition, specific expression pattern of some GhSRO genes during ovule developmental stages depicted their involvement in these developmental processes.

Conclusion

The data presented in this report laid a foundation for understanding the classification and functions of SRO genes in cotton.

Cotton

SRO

miRNAs

Gene duplications

Gene expression

ovule development

Changing climatic conditions adversely affects plants that directly or in-directly affect their growth, development and thus influencing the production. Due to sessile nature, plants cannot move its positions, instead have to adapt to environmental stresses by making changes at the cellular, molecular and physiological level. During evolution, plants have evolved an advanced mechanism to cope with multiple stresses. Several phytohormones i.e. SA, JA, ethylene together with ROS and kinases participate either in synergistic or antagonistic interactions to regulate these stress responses (1). Additionally, plant-specific proteins and transcription factors WRKY, MYC2, NAC, ARF, AP2 and DOF (2–9) also intricate in plant development and stress responses. Among the plant-specific protein families, SRO (similar to radical-induced cell death one) protein family is the recently recognized protein family that had multiple regulatory roles in plant development and mitigating stress responses (10–12). The SRO genes family belongs to plant-specific proteins group that is characterized by the presence of two domains, a PARP (poly (ADP-ribose) polymerase) domain and a C-terminal catalytic RST (RCD1-SRO-TAF4) domain (13). Moreover, some SRO proteins also possessed another N-terminal WWE domain along with PARP and RST domains (14). It is presumed that WWE domain initiate interactions between proteins (15) while RST domain promotes interaction with transcription factors (16). SRO proteins from Arabidopsis constitute a small family, with one RCD1 (AtRCD1) and five SRO (AtSRO1-AtSRO5) genes. AtRCD1 (also known as AtCEO), first characterized SRO gene in Arabidopsis was reported to complement oxidative stress responses in S. cerevisiae (17). Loss of functional mutation of AtRCD1caused pleotropic effects in Arabidopsis ranging from developmental defects to enhanced sensitivity to abiotic stresses (16, 18–20). Further, mutation studies revealed that AtRCD1regulates several stress related genes and act as a key regulator in phytohormonal signaling pathways (21, 22). AtRCD1and AtSRO1are the two closest homologs, play overlapping roles during growth and developmental processes in plants (18). Both genes harbor an additional WWE domain along with PARP and RST domains and categorized in group I (16), while other Arabidopsis SRO genes (AtSRO2-AtSRO5) only contain PARP and RST domains and categorized in group II (13). Although, AtSRO1 and AtRCD1 have functional redundancy related to plant development but functional variations exist in response to abiotic stresses (18). For example, mutations of AtSRO1 could improve plant tolerance under osmotic and oxidative stresses (10) but mutations of AtRCD1 compromised plant tolerance to salt stress (23).

Moreover, other members of Arabidopsis SRO gene family have also been documented in increasing plant tolerance or adaptability against several abiotic stresses, such as AtSRO2/3 participate in tolerance of strong light, salt and ozone stresses (13), and AtSRO5 improves plant tolerance to salt stress by modulating level of H₂O₂ in roots (24). Apart from Arabidopsis, functional characterization of SRO genes from non-model crops including wheat (25), rice (26), maize (12), tomato (27), cabbage (28), and banana (29) have also been reported. For example, out of six SRO genes in banana, MaSRO4 was reported to be the key regulator of multiple stresses by making interactions with NAC6 and MYB4 transcription factors (29). Similarly, apple MdRCD1 gene has multiple functions; could increases root growth and improves plant’s ability to tolerate salt, oxidative and drought stresses by regulating ABA (abscisic acid) signaling pathway (30). Moreover, BrSRO8 strongly respond to heat stress in cabbage (28) and OsSRO1c gene in rice could increase plant tolerance to oxidative and drought stresses by interacting with transcription factors SNAC1, DST and modulating H₂O₂ level (26). Interestingly, SlSRO1is closely related to AtSRO5 based on higher sequence similarity, strongly induced following salt stress and regulates stress responses in tomato (27).

Cotton, a natural fiber producing crop provides major raw material to the textile industry of developing countries. Sustainable production of cotton is seriously affected by a number of biotic and abiotic stresses during its growth period, such as flooding, drought, heat waves and pathogen infections (31). With the increments and advancements of transcriptomic and genomics data of cotton species, it has now become possible to characterize functions of specific genes in cotton. Considering the important roles of SRO genes family during various growth and development related responses in plants, comparative analysis of SRO genes among cotton species is crucial to be studied in depth. Here, four species of cotton were screened for identification of putative SRO genes. Next, chromosomal mapping, gene duplication, syntenic relationship, phylogeny, conserved domains, exons-introns map, motifs distribution, cis-elements and miRNAs were predicted to dissect the potential roles of GhSRO genes. Moreover, transcript abundance of GhSRO genes in various organs and during different ovule developmental stages were analyzed to explore the potential candidate genes. Our results provide useful information and lay foundation in deciphering the specific roles of SRO genes in cotton that will be helpful for improving growth and stress-related breeding approaches in cotton.

Screening and sequence retrieval of SRO domain carrier genes from cotton species

Putative SRO genes from four species of cotton were retrieved from corresponding reference genome at cottongen database (https://www.cottongen.org/blast/protein/protein) (32). Redundant, overlapping and non-targeted hits were discarded manually. Further, protein sequences of cotton SRO genes were checked using pFAM (http://pfam.xfam.org/) (33) and NCBI conserved domain databases (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) (34) for verification of potential domains. All the redundant sequences with missing potential domains were manually discarded. The complete genome, proteome and coding DNA sequences of putative SRO genes of cotton species were obtained through browsing cottongen website (https://www.cottongen.org/) (32) and nomenclature criteria was set based on their physical positions on chromosomes. Physicochemical properties of putative SRO genes were obtained from online web tool ExPasy (http://web.expasy.org/protparam/) (35) and cottonfgd website ((https://cottonfgd.org/). The CELLO v2.5 (http://cello.life.nctu.edu.tw/) (36) and WOLF PSORT (https://www.genscript.com/wolf-psort.html?src=leftbar) (37) software were employed to infer the subcellular localization of cotton SRO genes.

Chromosomal mapping, duplications and syntenic analysis of cotton SRO genes

Information obtained from cottongen database (www.cottongen.org) was utilized to find out the chromosomal positions of putative cotton SRO genes. Their positions were visualized on chromosomes using PhenoGram web tool (http://visualization.ritchielab.psu.edu/phenograms/plot). Duplication and syntenic analysis were performed using online BLAST program available at cottonfgd website (https://cottonfgd.org/sequenceserver/) (38). Criteria opted for duplication study among homologs of three cotton species (G. hirsutum, G. arboreum and G. raimondii) was as similarity > 80% and alignment percentage > 80% compared to total length of proteins (39). For visualization of syntenic relations, a circos plot was generated among the four studies species of cotton, with the help of Circos program (TBtools software) (40). Clustal omega (http://www.ebi.ac.uk/Tools/msa/clusalo/) was used for sequence alignment and aligned sequence file was submitted to PAL2NAL web tool (http://www.bork.embl.de/pal2nal/) (41) for determining of Ka, Ks and Ka/Ks values.

Phylogenetic analysis of cotton SRO genes

Protein sequences from Arabidopsis and cotton species were aligned using the clustal W software (42) with default parameters. Alignment file was submitted in MEGA7.0 software (43) for creation of unrooted tree using NJ method with 1000 replication.

Structural, motifs and promoter region-specific analysis of GhSRO genes

Gene structural diagram was generated in Gene Structural Display Server (GSDS 2.0)( http://gsds.cbi.pku.edu.cn/) (44) using the full length genome and the corresponding DNA sequences. Potential conserved motifs in GhSRO genes were explored using the Online MEME software with default setting (45). A 1500 bp upstream promoter region from start codon of each GhSRO gene was obtained from cottongen database. The potential cis-elements in these promoter regions were identified via accessing PlantCare web tool (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/) (46).

Putative miRNAs and their target GhSRO genes prediction analysis

Putative miRNA sequences were obtained from various miRNA databases such as plant miRNA database (http://bioinformatics.cau.edu.cn/PMRD/), the cotton EST database (http://www.leonxie.com/), the miRBase (http://www.mirbase.org/) and published articles. Targets of miRNAs in GhSRO genes were predicted using the online psRNATarget server (http://plantgrn.noble.org/psRNATarget/home) with default parameters (47).

Transcriptomic data and expression analysis of GhSRO genes

Transcriptomic data related to different tissues and various ovule developmental stages were downloaded and analyzed from cottonfgd website (https://cottonfgd.org/) (38).

Identification, classification and properties of SRO genes of cotton species

The Arabidopsis SRO genes were placed as query during BLASTP search against whole genomic databases of four species of cotton; as a result, total 36 SRO genes were identified, including 12, 11, 6 and 7 SRO genes from G. hirsutum, G. barbadense, G. arboreum and G. raimondii, respectively (Table S1). All these putative SRO genes were checked for presence of characteristic SRO domains using pFAM and NCBI conserved domain databases. According to numbers of characteristic SRO domains, all the putative SRO genes were classified into three groups, Group I includes those genes which consists of three domains WWE, RST super family and PARP super family domains, Group II genes lack WWE domain and contain other two domains, while Group III harbors only single RST super family domain. Among total 36 SRO genes, 11 belong to group I, 8 belong to group II and the 17 belong to group III (Table S2). The detailed information related to their physio-chemical attributers were determined using ExPASy and cottonfgd web tools. The number of amino acids ranged from 305 bp to 616 bp, molecular weight 37.056 kDa to 68.973, isoelectric point 6.744 to 9.077, charge − 1 to 17 and grand average of hydropathy range from − 0.479 to -0.215 (Table S2).

Phylogeny and evolutionary analysis of cotton SRO genes

To explore the phylogeny among cotton SRO genes with other well characterized SRO genes from Arabidopsis, maize, potato and apple, an unrooted tree was generated using their protein sequences. In this phylogenetic tree, all the 45 SRO genes were scattered among three groups (Group I, Group II and Group III) which consisted of 12, 17, and 16 genes, respectively (Fig. 1). Cotton SRO genes were randomly distributed in all three groups. Among the GhSRO genes, GhSRO12, GhSRO6, GhSRO10 and GhSRO4 were clustered in group III with most of the Arabidopsis SRO genes (AtSRO2, AtSRO3, AtSRO4 and AtSRO5) and one potato SRO gene (SlocSRO2), four GhSRO genes (GhSRO8, GhSRO2, GhSRO7 and GhSRO1) were clustered in group I. Maximum number of SRO genes were clustered in Group II, including GhSRO11, GhSRO5, GhSRO3 and GhSRO9 from upland cotton, two Arabidopsis SRO genes (AtRCD1 and AtSRO1), one maize SRO gene (ZmSRO5) and one apple SRO gene (MdRCD1). As seen in Fig. 1, many orthologous genes were found among four cotton species, but no orthologues were found between Arabidopsis and cotton species. Maximum seven orthologous pairs were found between G. hirsutum and G. barbadense (GhSRO6/GbSRO6, GhSRO8/GbSRO8, GhSRO7/GbSRO7, GhSRO1/GbSRO1, GhSRO11/GbSRO10, GhSRO3/ GbSRO3, and GhSRO9/GbSRO9). Two orthologues were found between G. arboreum and G. barbadense (GaSRO6/GbSRO4 and GaSRO2/GbSRO2), One between G. raimondii and G. hirsutum (GrSRO3/GhSRO10) and one between G. arboreum and G. hirsutum (GaSRO5/GhSRO5). Interestingly, no orthologous pair was found between diploid species of cotton.

Chromosomal distribution and syntenic study of cotton SRO genes

To explore the evolutionary dynamics and syntenic relations among cotton SRO genes, a circos plot was generated among two diploid species and two allotetraploid cotton species. Results showed that putative GaSRO, GrSRO, GhSRO and GbSRO genes were unevenly distributed among three chromosomes of A2 (Ga-A05, Ga-A08, Ga-A12), D5 (Gr-D04, Gr-D08, Gr-D09), At (Gh-A05, Gh-A08, Gh-A12), Dt (Gh-D05, Gh-D08, Gh-D12), At (Gb-A05, Gb-A08, Gb-A12) and Dt (Gb-D05, Gb-D08, Gb-D12) genomes, respectively (Fig. 2). The gene number varies between one to four, with one gene on Ga-A08, Gr-D04, Gh-A08, Gh-D08, Gb-A08 and Gb-D08. Two genes on Ga-A05, Gr-D09, Gh-A05, Gh-D05, Gh-D12, Gb-A05, Gb-D05, Gb-D12 and three genes on Ga-A12, Gh-A12, Gh-D12, Gb-A12 and maximum numbers of genes (four) were found on Gr-D08 chromosome (Table S3, Fig. 2). Gene duplication analysis of GhSRO genes revealed six duplicated pairs which shared more than 95% similarity in nucleotide sequences. These pairs are GhSRO1-7, GhSRO2-8, GhSRO3-9, GhSRO4-10, GhSRO5-11 and GhSRO6-12 (Fig. S1). Interestingly, all the duplicated gene pairs undergo segmental duplication and followed the purifying selection pressure (Table S4).

Structure and motifs analysis of GhSRO genes

Gene structural analysis comprising of introns/exons distribution and numbers showed that Group II members had highest number of exons and introns (Exon = 6 and Intron = 5). All members of Group I and Group III possessed 4 exons and 3 introns, while two members of Group III contained 5 exons and 4 introns (Fig. 3A&B). Collectively, structural diagram discovered the conservation in number and distribution of exons/introns among closely related members within the groups. Conserved domains/motifs analysis provides clues about gene duplications and functional conservation during evolution. Using online MEME tool, seven motifs were found in GhSRO genes and their distributions were displayed in Fig. 3C&D. Different GhSRO genes contained different motifs; however, motifs 1 and 4 were conserved among all members of GhSRO genes. Moreover, GhSRO genes of similar structure harbored similar motifs within subgroups.

Cis -elements analysis

Promoter regions of every gene possess certain elements that control or regulate gene expression. These regulatory elements are known as cis-elements. To comprehend specific functionality of GhSRO genes during cotton developmental stages and responses to different stress factors, we comprehensively investigated the cis-regulatory elements of GhSRO genes. As shown in Fig. 4A, mainly four types of elements were found in GhSRO genes, including light responsive, growth or development related, hormones-responsive and stress related. Light responsive elements were predominant (59%) in GhSRO genes, followed by hormones (17%), stress related elements (17%) and plant growth responsive (7%). A diversity of cis-elements presents in each GhSRO genes and the pattern of these cis-elements varied among members of GhSRO genes. Comparing to other GhSRO genes, GhSRO4 have maximum number of low temperature-responsive, development-related, ABA-responsive and GA-related elements. Captivatingly, only GhSRO5 and GhSRO7 have cis-elements responsive to defense or stress related (Fig. 4B).

Identification of potential miRNA targeting sites in GhSRO genes

MiRNAs are tiny (∼22-nucleotide long) non-coding RNAs known to participate in certain regulatory functions of genes in eukaryotes (48, 49). Recently, the regulatory roles of these small RNAs in plant developmental processes and stress responses are widely studied (50–53). To further elucidate the functions of GhSRO genes in cotton and to predict potential targets of miRNAs, coding DNA sequences of GhSRO genes were submitted in psRNATarget server (http://plantgrn.noble.org/psRNATarget/home). The results revealed the 23 miRNAs of upland cotton that targeted 12 GhSRO genes (Fig. 5, Table S5). The predicted miRNAs were related to fiber development, growth stages and environmental stresses in plants (54). These miRNAs were identified during various RNA-sequencing and bioinformatics approaches. The functions of some identified miRNAs have been validated through experiments, while others are only predicted. The results showed that ghr-mir2868 targeted GhSRO2, GhSRO8 genes and targeted sites was present in RST domain. Similarly, GhSRO4, GhSRO10 and GhSRO6, GhSRO12 were targeted by ghr-miR2529 and novel-miR-27, respectively. Other miRNAs like ghr-mir482d, ghr-miR414f, ghr-n72, ghr-miR2595, ghr-mir482a and ghr-miR482h targeted GhSRO1, GhSRO3, GhSRO5, GhSRO7, GhSRO9 and GhSRO11, respectively. In addition to above reported miRNAs, other miRNAs also targeted GhSRO genes, like GhSRO1 was also targeted by ghr-miR2673, ghr-n3, ghr-miR2595, ghr-miR835, ghr-miR838a, novel_miR_43 and GhSRO2 by ghr-miR414f and ghr-miR7. The complete details comprising predicted miRNAs and their potential targets in GhSRO genes are provided in Table S5.

Expression profiling of GhSRO genes in various tissues and ovule developmental stages of cotton

Genes expression pattern partly reflect their functions. SRO genes have been reported to regulate various developmental processes in plants (13, 29). To preliminary investigate the biological functions of GhSRO genes in upland cotton in various tissues and during ovule development stages, we analyzed transcriptomic data (38). Differential expression pattern from all the candidate GhSRO genes were observed in most of the studied tissues (roots, stem, leaf, sepal, petal, anther, filaments, pistils, bract and torus). Of the total 12 candidate genes, six GhSRO genes (GhSRO6, GhSRO4, GhSRO12, GhSRO10, GhSRO7, and GhSRO1) were predominantly induced in anthers. However, the expressions of other six genes were higher in some tissues, very low or not obvious in some tissues. Such as, GhSRO8 highly expressed in sepals and torus, lesser in anthers and filaments while barely detectable in roots and bracts (Fig. 6A). As shown in Fig. 6B, all the candidate SRO genes induced differentially during different ovule developmental stages. Two genes (GhSRO4 and GhSRO10) more specifically induced during the later developmental stages, while two genes (GhSRO8 and GhSRO2) during mid-developmental stages, while others are differentially induced during initial and later stages. Moreover, four genes including GhSRO11, GhSRO5, GhSRO3 and GhSRO9 were more or less constitutively induced during most of ovule developmental stages. Remarkably, GhSRO10 most preferentially induced during ovule development at 25 dpa, indicating its specific functions at this physiological stage (Fig. 6B). Collectively, our expression profiling data advocates the important roles of GhSRO genes during various growth and developmental stages of cotton.

Cotton being a natural fiber and oil producing crop contributes a major share in the economy of many developing countries. Due to global climate change, various environmental stresses have become a major obstacle in sustainable production of cotton (55, 56). Therefore, it is very important to discover stress responsive candidate genes under changing environmental conditions for their best utilization in cotton breeding programs. Availability of genomics, transcriptomic data of important cotton species and advancement of bioinformatics tools has provided the opportunity to characterize key genes that participate in growth/developmental processes and regulate various stress responses in plants. SRO is a unique family of small proteins that regulate multiple growth related processes in plants (28). However, cotton SRO genes have not been comprehensively characterized before. Here, comprehensive analysis of SRO genes from four species of cotton, two diploid (G. arboreum, G. raimondii) and two allotetraploid (G. barbadense, G. hirsutum) were performed, with an aim to explore their diverse functions in cotton growth and developmental processes. The identified SRO genes in tetraploid species is roughly twice to that of diploid species, this suggests that duplication events in diploid species occur before the emergence of tetraploid cotton. In addition, variations exist in the number of SRO genes among diploid and tetraploid species corresponds to variations in genome size of these species, consistent with other study Chattha et al., (2020) (9). Domain analysis of total 36 putative cotton SRO genes revealed that 11 cotton SRO genes harbor all the three characteristics domains (PARP, RST, WWE), 8 SRO genes possesses two domains (PARP, RST), while 17 SRO genes constitute only RST domain. In general, presence or absence of these domains is somehow representative of their functional similarity or diversification. As previous studies have reported that PARPs are specific enzymes that perform regulatory processes in plants including chromatin modification, transcription, DNA damage repair and cell death pathways (57–59). RST domain permits interactions between RCD1 and other transcription factors to regulate important developmental processes in plants (16), while WWE domain is thought to be required in facilitation of interactions between proteins by forming specific globular structure (15). The specific domain architecture of cotton SRO genes is representative of their special functions in cotton growth and developmental processes.

In phylogenetic tree, cotton SRO genes of four species were randomly distributed in three groups (Group I, Group II, Group III) along with SRO genes from other plant species including Arabidopsis, maize, potato and apple. One way to predict the functional similarity of genes is to find the close association of those genes through phylogenetic tree. According to phylogenetic analysis, Group II cotton SRO genes were found to be more related to AtSRO1, AtRCD1, MdRCD1 and ZmSRO5. In this group, AtSRO1 and AtRCD1 have been studied more comprehensively and reported to regulate several growth/developmental processes and stress responses in Arabidopsis (16, 60). While, MdRCD1 in apple and ZmSRO5 in maize perform multiple functions related to root growth and tolerance against several abiotic stress factors (12, 30). Similarly, Group III cotton SRO genes showed more resemblance with SlocSRO2 and four Arabidopsis genes (AtSRO2, AtSRO3, AtSRO4 and AtSRO5), depicting their functional similarity in different species. Gene distribution pattern of cotton SRO genes on chromosomes was uneven. Out of 13 chromosomes, all the GaSRO, GrSRO, GhSRO and GbSRO genes were distributed only across three chromosomes of A2, D5 genomes and Gh-At, Gh-Dt, Gb-At and Gb-Dt subgenomes, respectively. Gene duplication or replication is an important evolutionary mechanism for any organism to expand gene family and adopts novel functions. Segmental and tandem duplication are the ways through which genes are more frequently duplicated in plants. Same chromosomes localized replicated gene pairs represents the tandem duplication, whilst different chromosomes harboring duplicated gene pairs consider under segmental duplication event (61). In current study, segmental duplication was found to be the main cause for expansion of GhSRO gene family in cotton; this corroborates the previous findings Chattha et al., (2020) and Shaban et al., (2021) (9, 39). Generally, synonymous (Ks) and non-synonymous (Ka) substitution values are computed to explain the duplication mechanism (62). More captivatingly, all the duplicated pairs have Ka/Ks ratio less than 1, therefore these follow the more purifying selection pressure, suggesting that they do not reflect much functional diversification during evolution.

Comparative structural analysis including exon/intron architecture and predicted motifs among GhSRO genes revealed the variations between subgroups and conservation within subgroups. This further supports the phylogenetic clustering and evolutionary relationship among closely related GhSRO genes. High structural conservation of SRO genes within groups was also perceived in other plant species (12, 25). Promoter regions located cis-elements fine tune gene expression and their analysis provide clues about functional characterization of genes (63). PlantCARE database is the collection of previously reported cis-elements in plants (46), it helped us to investigate promoter regions of candidate GhSRO genes in details. The discovery of several growth/development related, light responsive, hormones responsive, and stress responsive cis-elements in the promoter regions of GhSRO genes predicts their multiple functions in different biological processes of plants. Recently, a number of miRNAs are characterized for their potential functions in post-transcriptional regulation during developmental and stress related responses in plants (48, 49). Similarly, SRO genes have been extensively characterized during various growth/developmental stages and in monitoring stress responses in multiple plant species (12, 28, 29) but, their regulation being mediated by miRNAs were not studied before. In this study, 23 miRNAs of upland cotton inclusive conserved and novel miRNAs were found to target 12 GhSRO genes. These miRNAs, for example ghr-miR482d, ghr-miR414f, ghr-n72 and novel_miR_27 regulate various developmental processes and abiotic and biotic stresses in cotton (53, 54, 64). Our prediction results revealed that most closely related genes are targeted by same miRNAs and these might be conserved in upland cotton. The prediction of above mentioned miRNAs is based on computational approaches; further experimental validation of these miRNAs and their target genes using relevant molecular techniques is needed to verify their biological roles in upland cotton.

Generally, the pattern of gene expression predicts their functions. Expression pattern of GhSRO genes in different organs and at various ovule developmental stages provide clues for their functional specificity in cotton growth and developmental processes. Previously, the SRO genes was found to be tissue-specific in multiple plant species, such as in maize (12), wheat (25) and banana (29), corresponding to their functional specificity in these species. In this study, half of the candidate GhSRO genes were dominantly expressed in anthers, signifying their functional redundancy in development or regulation of this organ. While, the other half of GhSRO genes showed differential expression in the studied tissues, implying their functional diversity across different tissues. Interestingly, some GhSRO genes such as GhSRO4 and GhSRO10 dominantly induced during later stages of ovule development, two genes GhSRO8 and GhSRO2 induced during mid-developmental stages and others during initial and later stages of ovule development indicating their spatio-temporal roles in these developmental stages. More intriguingly, our expression pattern results justify the phylogenetic clustering, such as GhSRO5, GhSRO11 and GhSRO3, GhSRO9 clustered together in phylogenetic tree and had somewhat similar expression pattern in different tissues and ovule developmental stages. Collectively, our expression pattern results suggest that GhSRO genes perform very important regulatory roles during various growth and developmental stages in cotton.

Using bioinformatics tools 36 putative SRO genes were identified from four species of cotton, distributed among three chromosomes of A2, D5, and At and Dt genomes, respectively. During evolution, SRO genes in upland cotton were expanded through segmental duplication. Genes belonging to same groups or subgroups revealed similar phylogeny, structural and motifs distribution. The presence of wide variety of cis-elements in the promoter region of GhSRO genes envisaged their roles during various growth and developmental stages of cotton. The transcriptomic based expression pattern revealed differential expression of GhSRO genes in different tissues and during ovule developmental stages. This could provide deep insights for the possible involvement of specific GhSRO genes in cotton growth and development stages. The data presented here provides fundamental information to further explore the specific functions of GhSRO genes in cotton growth and development.

SRO; Similar to RCD1

RCD1; Radical-Induced Cell Death1

JA; Jasmonic Acid

SA; Salicylic Acid

ROS; Reactive Oxygen Species

ABA; Abscisic acid

H₂O_2; Hydrogen peroxide

PARP; Poly ADP-ribose polymerase

Acknowledgment

The authors are grateful to Muhammad Mahmood Ahmad from Islamia University Bahawalpur, Pakistan, for their valuable insights and discussions that greatly contributed to the development of this research.

Author Contributions

Shaban M conducted this study, Shaban M, Tabassum R and Rana IA designed the research and wrote the manuscript. Atif RM, Azmat MA and Iqbal Z helped in analysis. Azhar MT supervised the research and carefully revised the manuscript. All the authors read and approved the final manuscript.

Funding

Not applicable

Availability of data and materials

All the materials or data discussed in the current study is available as supplementary files

Consent for publication

All authors have agreed to submit the research article in Journal of Cotton Research.

Competing interests

The authors declare that they have no competing interests.

Author details

¹Department of Plant Breeding and Genetics, University of Agriculture Faisalabad, Sub-Campus Burewala, Vehari, Pakistan. ²Department of Chemistry and Biochemistry, University of Agriculture Faisalabad, Pakistan. ³Centre of Agricultural Biochemistry and Biotechnology, University of Agriculture, Faisalabad 38400, Pakistan. ⁴Department of Plant Breeding and Genetics, University of Agriculture Faisalabad 38400, Pakistan. ⁵State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, Henan, China. ⁶School of Agriculture Sciences, Zhengzhou University, Zhengzhou-450000, China.

Blazquez MA, Nelson DC, Weijers D. Evolution of Plant Hormone Response Pathways. Annu Rev Plant Biol. 2020;71(1):327-53.
Wang CT, Ru JN, Liu YW, Li M, Zhao D, Yang JF, et al. Maize WRKY Transcription Factor ZmWRKY106 Confers Drought and Heat Tolerance in Transgenic Plants. Int J Mol Sci. 2018;19(10):3046.
Wang Y, Li Y, He SP, Gao Y, Wang NN, Lu R, et al. A cotton (Gossypium hirsutum) WRKY transcription factor (GhWRKY22) participates in regulating anther/pollen development. Plant Physiol Biochem. 2019;141:231-9.
Du M, Zhao J, Tzeng DTW, Liu Y, Deng L, Yang T, et al. MYC2 Orchestrates a Hierarchical Transcriptional Cascade That Regulates Jasmonate-Mediated Plant Immunity in Tomato. The Plant Cell. 2017;29(8):1883-906.
Zhang Y, Ji TT, Li TT, Tian YY, Wang LF, Liu WC. Jasmonic acid promotes leaf senescence through MYC2-mediated repression of CATALASE2 expression in Arabidopsis. Plant Sci. 2020;299:110604.
Singh S, Koyama H, Bhati KK, Alok A. The biotechnological importance of the plant-specific NAC transcription factor family in crop improvement. J Plant Res. 2021;134(3):475-95.
Xiao G, He P, Zhao P, Liu H, Zhang L, Pang C, et al. Genome-wide identification of the GhARF gene family reveals that GhARF2 and GhARF18 are involved in cotton fibre cell initiation. Journal of Experimental Botany. 2018;69(18):4323-37.
Gu C, Guo ZH, Hao PP, Wang GM, Jin ZM, Zhang SL. Multiple regulatory roles of AP2/ERF transcription factor in angiosperm. Bot Stud. 2017;58(1):6.
Chattha WS, Atif RM, Iqbal M, Shafqat W, Farooq MA, Shakeel A. Genome-wide identification and evolution of Dof transcription factor family in cultivated and ancestral cotton species. Genomics. 2020;112(6):4155-70.
Jaspers P, Brosche M, Overmyer K, Kangasjarvi J. The transcription factor interacting protein RCD1 contains a novel conserved domain. Plant Signal Behav. 2010;5(1):78-80.
Liu S, Liu S, Wang M, Wei T, Meng C, Wang M, et al. A wheat SIMILAR TO RCD-ONE gene enhances seedling growth and abiotic stress resistance by modulating redox homeostasis and maintaining genomic integrity. Plant Cell. 2014;26(1):164-80.
Jiang H, Xiao Y, Zhu S. Genome-wide identification, systematic analysis and characterization of SRO family genes in maize (Zea mays L.). Acta Physiologiae Plantarum. 2018;40(10):176.
Jaspers P, Overmyer K, Wrzaczek M, Vainonen JP, Blomster T, Salojarvi J, et al. The RST and PARP-like domain containing SRO protein family: analysis of protein structure, function and conservation in land plants. BMC Genomics. 2010;11(1):170.
Webb C, Upadhyay A, Giuntini F, Eggleston I, Furutani-Seiki M, Ishima R, et al. Structural features and ligand binding properties of tandem WW domains from YAP and TAZ, nuclear effectors of the Hippo pathway. Biochemistry. 2011;50(16):3300-9.
Aravind L. The WWE domain: a common interaction module in protein ubiquitination and ADP ribosylation. Trends in biochemical sciences. 2001;26(5):273-5.
Jaspers P, Blomster T, Brosche M, Salojarvi J, Ahlfors R, Vainonen JP, et al. Unequally redundant RCD1 and SRO1 mediate stress and developmental responses and interact with transcription factors. The Plant journal : for cell and molecular biology. 2009;60(2):268-79.
Belles-Boix E, Babiychuk E, Van Montagu M, Inze D, Kushnir S. CEO1, a new protein from Arabidopsis thaliana, protects yeast against oxidative damage. FEBS letters. 2000;482(1-2):19-24.
Teotia S, Lamb RS. The paralogous genes RADICAL-INDUCED CELL DEATH1 and SIMILAR TO RCD ONE1 have partially redundant functions during Arabidopsis development. Plant physiology. 2009;151(1):180-98.
Katiyar-Agarwal S, Zhu J, Kim K, Agarwal M, Fu X, Huang A, et al. The plasma membrane Na+/H+ antiporter SOS1 interacts with RCD1 and functions in oxidative stress tolerance in Arabidopsis. Proceedings of the National Academy of Sciences of the United States of America. 2006;103(49):18816-21.
Ahlfors R, Brosche M, Kollist H, Kangasjarvi J. Nitric oxide modulates ozone-induced cell death, hormone biosynthesis and gene expression in Arabidopsis thaliana. The Plant journal : for cell and molecular biology. 2009;58(1):1-12.
Ahlfors R, Lang S, Overmyer K, Jaspers P, Brosche M, Tauriainen A, et al. Arabidopsis RADICAL-INDUCED CELL DEATH1 belongs to the WWE protein-protein interaction domain protein family and modulates abscisic acid, ethylene, and methyl jasmonate responses. Plant Cell. 2004;16(7):1925-37.
Overmyer K, Tuominen H, Kettunen R, Betz C, Langebartels C, Sandermann H, Jr., et al. Ozone-sensitive arabidopsis rcd1 mutant reveals opposite roles for ethylene and jasmonate signaling pathways in regulating superoxide-dependent cell death. Plant Cell. 2000;12(10):1849-62.
Zhao X, Gao L, Jin P, Cui L. The similar to RCD-one 1 protein SRO1 interacts with GPX3 and functions in plant tolerance of mercury stress. Biosci Biotechnol Biochem. 2018;82(1):74-80.
Borsani O, Zhu J, Verslues PE, Sunkar R, Zhu JK. Endogenous siRNAs derived from a pair of natural cis-antisense transcripts regulate salt tolerance in Arabidopsis. Cell. 2005;123(7):1279-91.
Jiang W, Geng Y, Liu Y, Chen S, Cao S, Li W, et al. Genome-wide identification and characterization of SRO gene family in wheat: Molecular evolution and expression profiles during different stresses. Plant Physiol Biochem. 2020;154:590-611.
You J, Zong W, Du H, Hu H, Xiong L. A special member of the rice SRO family, OsSRO1c, mediates responses to multiple abiotic stresses through interaction with various transcription factors. Plant Mol Biol. 2014;84(6):693-705.
Babajani G, Effendy J, Plant AL. Sl-SROl1 increases salt tolerance and is a member of the radical-induced cell death 1—similar to RCD1 gene family of tomato. Plant Science. 2009;176(2):214-22.
Qiao Y, Gao X, Liu Z, Wu Y, Hu L, Yu J. Genome-Wide Identification and Analysis of SRO Gene Family in Chinese Cabbage (Brassica rapa L.). Plants (Basel). 2020;9(9):1235.
Zhang L, Zhou D, Hu H, Li W, Hu Y, Xie J, et al. Genome-wide characterization of a SRO gene family involved in response to biotic and abiotic stresses in banana (Musa spp.). BMC Plant Biol. 2019;19(1):211.
Li H, Li R, Qu F, Yao J, Hao Y, Wang X, et al. Identification of the SRO gene family in apples (Malus×domestica) with a functional characterization of MdRCD1. Tree Genetics & Genomes. 2017;13(5):94.
Mahmood S, Hussain B. Development of Transgenic Cotton for Combating Biotic and Abiotic Stresses. Cotton Production and Uses: Springer; 2020. p. 527-45.
Yu J, Jung S, Cheng CH, Ficklin SP, Lee T, Zheng P, et al. CottonGen: a genomics, genetics and breeding database for cotton research. Nucleic Acids Res. 2014;42(Database issue):D1229-36.
El-Gebali S, Mistry J, Bateman A, Eddy SR, Luciani A, Potter SC, et al. The Pfam protein families database in 2019. Nucleic Acids Res. 2019;47(D1):D427-D32.
Yang M, Derbyshire MK, Yamashita RA, Marchler-Bauer A. NCBI's Conserved Domain Database and Tools for Protein Domain Analysis. Curr Protoc Bioinformatics. 2020;69(1):e90.
Bjellqvist B, Basse B, Olsen E, Celis JE. Reference points for comparisons of two-dimensional maps of proteins from different human cell types defined in a pH scale where isoelectric points correlate with polypeptide compositions. Electrophoresis. 1994;15(3-4):529-39.
Yu CS, Chen YC, Lu CH, Hwang JK. Prediction of protein subcellular localization. Proteins. 2006;64(3):643-51.
Horton P, Park KJ, Obayashi T, Fujita N, Harada H, Adams-Collier CJ, et al. WoLF PSORT: protein localization predictor. Nucleic Acids Res. 2007;35(Web Server issue):W585-7.
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):101.
Shaban M, Khan AH, Noor E, Qayyum A, Malik W, Shehzad M, et al. Genome-wide dissection, characterization, and expression profiling of cotton GASA genes reveal their importance in regulating abiotic stresses. Intl J Agric Biol. 2021;25:181‒90.
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.
Suyama M, Torrents D, Bork P. PAL2NAL: robust conversion of protein sequence alignments into the corresponding codon alignments. Nucleic Acids Research. 2006;34(suppl_2):W609-W12.
Thompson JD, Gibson TJ, Higgins DG. Multiple sequence alignment using ClustalW and ClustalX. Curr Protoc Bioinformatics. 2002;Chapter 2(1):Unit 2 3.
Kumar S, Stecher G, Tamura K. MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets. Molecular biology and evolution. 2016;33(7):1870-4.
Hu B, Jin J, Guo AY, Zhang H, Luo J, Gao G. GSDS 2.0: an upgraded gene feature visualization server. Bioinformatics (Oxford, England). 2015;31(8):1296-7.
Bailey TL, Johnson J, Grant CE, Noble WS. The MEME Suite. Nucleic Acids Res. 2015;43(W1):W39-49.
Lescot M, Dehais 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.
Dai X, Zhuang Z, Zhao PX. psRNATarget: a plant small RNA target analysis server (2017 release). Nucleic Acids Res. 2018;46(W1):W49-W54.
Wang W, Liu D, Zhang X, Chen D, Cheng Y, Shen F. Plant MicroRNAs in Cross-Kingdom Regulation of Gene Expression. Int J Mol Sci. 2018;19(7).
Hua C, Zhao JH, Guo HS. Trans-Kingdom RNA Silencing in Plant-Fungal Pathogen Interactions. Mol Plant. 2018;11(2):235-44.
Xie F, Zhang B. microRNA evolution and expression analysis in polyploidized cotton genome. Plant biotechnology journal. 2015;13(3):421-34.
Wei M, Wei H, Wu M, Song M, Zhang J, Yu J, et al. Comparative expression profiling of miRNA during anther development in genetic male sterile and wild type cotton. BMC Plant Biol. 2013;13:66.
Ma C, Burd S, Lers A. miR408 is involved in abiotic stress responses in Arabidopsis. The Plant journal : for cell and molecular biology. 2015;84(1):169-87.
Xie F, Wang Q, Sun R, Zhang B. Deep sequencing reveals important roles of microRNAs in response to drought and salinity stress in cotton. J Exp Bot. 2015;66(3):789-804.
Wang W, Chen D, Liu D, Cheng Y, Zhang X, Song L, et al. Comprehensive analysis of the Gossypium hirsutum L. respiratory burst oxidase homolog (Ghrboh) gene family. BMC Genomics. 2020;21(1):91.
Rahman MHu, Ahmad A, Wang X, Wajid A, Nasim W, Hussain M, et al. Multi-model projections of future climate and climate change impacts uncertainty assessment for cotton production in Pakistan. Agricultural and Forest Meteorology. 2018;253-254:94-113.
Jans Y, von Bloh W, Schaphoff S, Müller C. Global cotton production under climate change – Implications for yield and water consumption. Hydrology and Earth System Sciences. 2021;25(4):2027-44.
De Block M, Verduyn C, De Brouwer D, Cornelissen M. Poly(ADP-ribose) polymerase in plants affects energy homeostasis, cell death and stress tolerance. The Plant journal : for cell and molecular biology. 2005;41(1):95-106.
Lamb RS, Citarelli M, Teotia S. Functions of the poly(ADP-ribose) polymerase superfamily in plants. Cellular and molecular life sciences : CMLS. 2012;69(2):175-89.
Kim MY, Zhang T, Kraus WL. Poly(ADP-ribosyl)ation by PARP-1: 'PAR-laying' NAD+ into a nuclear signal. Genes & development. 2005;19(17):1951-67.
Zhao X, Gao L, Ren J, Pan F. Arabidopsis SIMILAR TO RCD-ONE genes are ubiquitous and respond to multiple abiotic stresses through diverse signaling pathways. Journal of Biosciences. 2019;44(6):129.
Song S, Hao L, Zhao P, Xu Y, Zhong N, Zhang H, et al. Genome-wide Identification, Expression Profiling and Evolutionary Analysis of Auxin Response Factor Gene Family in Potato (Solanum tuberosum Group Phureja). Sci Rep. 2019;9(1):1755.
Hurst LD, Williams EJ, Pal C. Natural selection promotes the conservation of linkage of co-expressed genes. Trends Genet. 2002;18(12):604-6.
Hernandez-Garcia CM, Finer JJ. Identification and validation of promoters and cis-acting regulatory elements. Plant Sci. 2014;217-218:109-19.
Zhu QH, Fan L, Liu Y, Xu H, Llewellyn D, Wilson I. miR482 regulation of NBS-LRR defense genes during fungal pathogen infection in cotton. PLoS One. 2013;8(12):e84390.

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Fig. S1. Chromosomal distribution and gene duplication analysis of SRO genes Chromosome number is displayed below each bar. The chromosome size is showed by its relative length using the information from cottongen database. Different groups of genes were marked with different colors. Solid lines were drawn to show the gene duplication among GhSRO genes.
SumpplementaryTableS1toS5.xlsx

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Editorial decision: Minor revision
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Reviewers invited by journal
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Comparative analysis of SIMILAR TO RCD ONE (SRO) family from tetraploid and diploid cottons depicts its role in growth and development

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Version 1

Abstract

Figures

Introduction

Materials and Methods

Screening and sequence retrieval of SRO domain carrier genes from cotton species

Chromosomal mapping, duplications and syntenic analysis of cotton SRO genes

Phylogenetic analysis of cotton SRO genes

Results

Identification, classification and properties of SRO genes of cotton species

Phylogeny and evolutionary analysis of cotton SRO genes

Chromosomal distribution and syntenic study of cotton SRO genes

Discussion

Conclusion

Abbreviations

Declarations

References

Supplementary Files

Status:

Version 1