In this study, we used two methods to identify GLP genes from the genome of the Solanum tuberosum. The first method was the Hidden Markov Model (HMM), and the second one was the BLASTP search (Raza et al., 2021; Zaynab et al., 2021d). Potato genome sequences were retrieved from JGI Phytozome 12.0¹ database (Goodstein et al., 2012). GLP amino acids sequences of A. thaliana were taken from TAIR² (Rhee, 2003) database and used as a query to run BLASTP search. The HMM file with Pfam ID PF00190 containing GLP genes was downloaded from Pfam³ (El-Gebali et al., 2019) database. Moreover, a local HMMER 3.1⁴ webserver was utilized to identify the GLP genes with default parameters (Finn et al., 2015). Eventually, a total of 70 GLP genes were identified from the genome of the potato. Non-redundant genes with conserved domains were serially named through StGLP1–StGLP70 and used for further analysis.

Physiochemical characteristics, including molecular weight and isoelectric points, were identified through ProtParam⁵ (Gasteiger et al., 2005).

In order to investigate the evolutionary history of the StGLP family genes, a phylogenetic tree was constructed among the amino acid sequences of Solanum lycopersicum, S. tuberosum, and A. thaliana. We used MEGA 7⁶ (Kumar et al., 2018) for the construction of phylogenetic tree. The neighbor-joining method was applied to make a phylogenetic tree with 1,000 bootstrap values. TBtools software⁷ was deployed to construct the gene structure of StGLPs (Chen et al., 2020). Conserved motifs present in StGLPs sequences were recognized through MEME⁸ (Bailey et al., 2009) server. For comparative synteny analysis, Circoletto Tool⁹ was used.

Data related to the chromosomal location was taken from general feature format (GFF) files of S. tuberosum genome database (PGSC Ref seq v4.03) (The Potato Genome Sequencing Consortium, 2011). The localization of 70 identified genes on chromosomes was performed by utilizing TBtools (Chen et al., 2020). To explore the putative cis-elements in the promoter region of StGLPs, we extracted a sequence of 2 Kb upstream of start codons in the genome of S. tuberosum. Afterward, to analyze the promoter region of each gene, we deployed them to PlantCARE¹⁰ (Lescot, 2002) and figures made by TBtools (Chen et al., 2020). Besides, the synonymous and non-synonymous substitution rate was computed by employing KaKs Calculator 2.0 software using the MYN procedure. Ks and Ka refer to the number of synonymous and non-synonymous substitutions concerning the synonymous non-synonymous site (Wang et al., 2010). Divergence time (t = Ks/2r) was estimated through exchange rate as (r = 2.6 × 10^–9) (Li et al., 2019).

For identifying miRNA targeting StGLPs, psRNAtarget¹¹ was used with default parameters (Dai et al., 2018). For illustrating the protein--protein interaction network, the STRING 11.0¹² server was employed, and for reference, the genome of S. tuberosum was used. The exhibit specifications were propped as the confidence value is 0.9 for network; and 10 for edges evidence and maximum number of interaction.

In order to investigate the expression of StGLP genes in various tissues and under various stress conditions, the transcriptome data were obtained from the available public database BioProject ID: Project: PRJEB2430. For the expression analysis of StGLP genes in different tissues and under different stresses, fragments per kilobase million (FPKM) were observed (Zaynab et al., 2021d). The obtained data were arranged according to their expression in different tissues. The observed FPKM values were utilized to construct a heatmap through TBtools after the normalization of log2 values.

The rooster variety of S. tuberosum was selected as the sample for these experiments, which were conducted at the experimental station of the National Institute for Genomics and Advanced Biotechnology (NIGAB), Islamabad, Pakistan. After 6 weeks of growth, the sample was treated with 150 mM NaCl for 0 and 24 h, respectively, for salt treatment. The first time point (0 h) served as a control. After NaCl treatment, leaves were taken, and samples were immediately frozen in liquid nitrogen and stored at −80°C for total RNA extraction.

Total RNA was extracted using TransZol Up Plus RNA Kit (TransGen Biotech, Beijing, China). For cDNA synthesis, cDNA Synthesis SuperMix was purchased from the above-mentioned Chinese company. Instructions given by manufacturers were followed during the whole process. The comprehensive knowledge about reactions of RT-qPCR has been reported in our earlier published work (Zaynab et al., 2021a). In our study, the expression data were evaluated by using the 2^–ΔΔCT methods (Zaynab et al., 2021c), and the elongation factor 1-alpha was chosen as a housekeeping gene (Zaynab et al., 2021b). The primers used in this study are given in Supplementary Table 1.

A total of 70 GLP genes were identified in the potato genome by employing sequences of A. thaliana as a query (Table 1). In this study, Batch-CD and SMART were utilized to confirm the domain with Pfam ID (PF00190). All these 70 genes contain a domain with Pfam ID (PF00190). The protein sequences of A. thaliana, S. lycopersicum, and identified StGLPs are given in Supplementary Table 2. Amino acids length varied from 94 to 567, the molecular weight from 10.650 to 65.780 kDa, and the isoelectric point values from 4.46 to 9.74 (Table 1). A phylogenetic tree was constructed using the neighbor-joining method through MEGA7 to illustrate the phylogenetic relationship among A. thaliana, S. lycoperiscum, and S. tuberosum. This study results showed that the phylogenetic tree was divided into six groups. Group-6 is the largest group, and group-3 is the smallest among all groups (Figure 1). Exons and introns are two main determinants in the gene family evolution. The detailed analysis of the phylogenetic relationship and gene composition illustration corroborated our understanding of the structures of StGLPs genes (Figure 2). The results revealed that numerical attributes of exon and intron in StGLP genes possessed high inconsistency in numbers of exons and introns (Figure 2). In this study, the StGLP46 gene possessed the most extended sequence. Some genes such as StGLP41 and StGLP38 exhibited similarities in exon numbers. Additionally, StGLP21 and StGLP57 genes were equal in exons numbers but differed in their sequence lengths. For determining structural diversification and functional characterization of these StGLPs, we analyzed full-length sequences of 70 StGLPs through MEME software to localize their conserved motifs. The motif results revealed that a total of ten motifs were identified (Figure 2). The sequences of predicted motifs are given in Supplementary Table 3. All of the StGLPs genes contained motif 1 except genes StGLP StGLP18, StGLP26, StGLP29, StGLP31, StGLP51, StGLP52, StGLP63, StGLP65, StGLP21, StGLP6, StGLP20, StGLP12, StGLP22, StGLP8, and StGLP27. The length of the motif was varied from 21 to 50 amino acids. The highest 50 amino acids were possessed by motif 3,7, and 10, while motif 2 and 5 contained the lowest 21 amino acids. In our results, motif 4 had 39 amino acids, motif 8 had 35 amino acids, while motifs 1 and 9 had 41 amino acids in their sequence. In short, the reliability of group organization was exceedingly encouraged by analyzing conserved motif conformation, genetic structures, and phylogenetic relationship, indicating that StGLP proteins possess enormously well-sustained amino acid members and remain inside a group. Thus, it can be inferred that proteins with identical motifs and structures may possess functional similarities.

Chromosomal distribution analysis of StGLPs depicted their unequal localization on all chromosomes (Figure 3). A maximum number of 29 genes were present on the 1st chromosome, while the 9th chromosome had 11 genes. There are 9 genes present on chromosome number 11. Only 2 genes are located on chromosome number 02 (Figure 3) in our results. Furthermore, there was no gene located on chromosome number 08. To determine the rate of molecular evolution of each gene pair that has been duplicated, the Ka to Ks (synonymous/non-synonymous substitution) ratios were calculated. When the value of the ratio is more than 1, then the selection effect will be positive; if its value is less than 1, then purifying selection will be exhibited, while when this ratio’s value is equal to 1, then there will be the presence of neutral selection in gene pairs (Yang and Bielawski, 2000). The cosmic majority of StGLPs genes exhibited a value of Ks more than 0.52, and the corresponding deviation time may be more than 100 million years ago (MYA). In this study, duplicated genes (StGLP4/StGLP35) showed the Ks value 3.54 while its corresponding time may be 682.30 MYA (Table 2). Comparative synteny analysis was analyzed among A. thaliana, S. tuberosum, and S. lycoperiscum which exhibited a phenomenal relationship in the evolution expression, duplication, triplication, and function of genes. Genes sequence of SlGLP17 exhibited synteny with the sequence of StGLP2. At the same time, two potato genes, StGLP20 and StGLP22, showed synteny with the SlGLP41 gene of tomato. The comparative synteny analysis revealed the conservation and duplication of inward and outward tangling events in ribbons, respectively (Figure 4).

To observe the StGLPs gene function and their regulatory role, promoter cis-elements were analyzed using the PlantCARE database. The cis-elements that are associated with plant hormones were identified. As shown in Figure 5, the number of genes associated with phytohormones indicates the importance of these genes in phytohormone stress. Furthermore, the role of anaerobic, light, and low-temperature responsive factors in this study was discovered (Figure 5). Mainly several elements that are responsive to light were categorized to be extensively distributed in all genes, indicating the significant role of StGLPs in response to light stress. Generally, findings envisaged that diversification in the expression levels of various StGLPs might be attributed to different plant hormones and environmental stress. The Hormones- and stress-related cis-elements found in the promoter regions of StGLPs are given in Supplementary Table 4.

Many researchers have reported that microRNA mediated a significant role in enhancing stress response in plants (Su et al., 2021; Xu et al., 2021). Thus, for an in-depth comprehension of miRNA-triggered post-transcriptional modulations of StGLPs, we identified miRNAs targeting StGLPs genes. Several sites that are targeted by miRNA are illustrated in Supplementary Table 1. Our findings revealed that seven members of the miR166 family target six genes, including StGLP8, StGLP54, StGLP23, StGLP24, StGLP38, and StGLP28. A gene, StGLP2, was targeted by a single member of the miR169 family. Targets StGLP51, StGLP48, and StGLP47 (Figure 6 and Supplementary Table 5) are all three members of the miRNA gene family. The findings of our study revealed that two members of the miR8040 aimed at two genes, StGLP51 and StGLP62. A gene StGLP55 was the target of two members of the miR1886 family. Our results mainly estimated two genes, StGLP40 and StGLP8, to target numerous miRNAs.

The protein–protein interaction network provided details about StGLPs in the genome of potatoes. The interaction network was observed among several proteins, including StGLP57, StGLP44, StGLP46, StGLP48, and StGLP2. These proteins depicted the concurrence, co-expression, fusion, and homology of genes. Likewise, another framework was also identified among StGLP53, StGLP63, and StGLP4 protein. Among all StGLPs, two proteins, StGLP48 and StGLP46, are responsible for framing a protein–protein interaction network, so these can be reputed as hub proteins of StGLPs (Figure 7).

Expression profiling of StGLPs revealed that many genes exhibited high expression in the tissues of roots than that in the tissues of stems and leaves. Some genes showed expression in some tissues, while some genes have no expression in others. For example, the StGLP17 gene showed a higher expression level in the tissues of roots, leaves, and stems, while the StGLP26 and StGLP45 genes showed higher expression levels in the tissues of roots and stems. Furthermore, in the tissues of leaves, StGLP5 genes showed the maximum expression in our results (Figure 8).

Transcriptional profiling of GLPs was performed when potato plants were subjected to heat stress. StGLPs may help potato plants cope better with high temperatures, according to some research. A total of 19 StGLPs genes were expressed in response to heat stress. Moreover, three genes, StGLP30, StGLP17, and StGLP14, exhibited a relatively higher expression level in potatoes after heat treatment (Figure 9). In our results, StGLP30 gene expression was higher than StGLP17 and StGLP14.

Furthermore, StGLP16 genes showed the lowest expression compared with other expressed StGLPs after heat treatment. Likewise, 29 GLPs were expressed in response to salt treatment. This study showed that StGLP54, StGLP12, and StGLP5 genes were highly expressed in potatoes after salt treatment (Figure 9), but the expression level of the StGLP5 gene was relatively higher as compared to StGLP12 and StGLP54 genes in the potato genome.

Three hormones, abscisic acid (ABA), gibberellic acid (GA3), and indole acetic acid (IAA), were selected to evaluate the hormonal response of StGLPs.

This study results showed that 22 StGLP genes were expressed after the treatment of ABA. Similarly, in the case of IAA treatment, 24 StGLP genes were expressed. Furthermore, the StGLP12 gene was highly expressed compared with others after the treatment of ABA, while StGLP5 showed the highest expression after IAA treatment (Figure 10). Additionally, 27 StGLPs were expressed when treated with GA3, and the expression of gene StGLP14 was highest among all 27 expressed genes (Figure 10). The upregulation of StGLPs after ABA, IAA, and GA3 treatment revealed the significant role of StGLP genes in mitigating the lethal effects of different hormonal and environmental stress.

Real-time-qPCR was performed to confirm the expression of five genes, namely, StGLP63, StGLP17, StGLP51, StGLP14, and StGLP47, in the tissues of roots, stems, and leaves (Figure 11). Two genes, namely, StGLP17 and StGLP14, exhibited a comparatively higher expression level in the tissues of stems than that in the tissues of roots and leaves. In contrast, the expression of StGLP47 was relatively more in the tissues of leaves than that in the tissues of roots and stems. Generally, findings depicted that StGLP genes may perform particular functions in potato plant growth and developmental process. Similarly, RT-qPCR was performed to confirm the expression of five genes, namely, StGLP5, StGLP12, StGLP30, StGLP 36, and StGLP54, in leaves treated with 150 mM NaCl. The results showed that the StGLP5 genes showed the maximum expression after 24 h of NaCl stress. In addition, genes such as StGLP12, StGLP 36, and StGLP54 were highly expressed with the extension of stress time. Moreover, StGLP30 showed expression but low expression compared with the other four genes (Figure 12).