Genome-Wide Characterization of Ascorbate Peroxidase Gene Family in Peanut (Arachis hypogea L.) Revealed Their Crucial Role in Growth and Multiple Stress Tolerance.

Ascorbate peroxidase (APX), an important antioxidant enzyme, plays a significant role in ROS scavenging by catalyzing the decrease of hydrogen peroxide under various environmental stresses. Nevertheless, information about the APX gene family and their evolutionary and functional attributes in peanut (Arachis hypogea L.) was not reported. Therefore, a comprehensive genome-wide study was performed to discover the APX genes in cultivated peanut genome. This study identified 166 AhAPX genes in the peanut genome, classified into 11 main groups. The gene duplication analysis showed that AhAPX genes had experienced segmental duplications and purifying selection pressure. Gene structure and motif investigation indicated that most of the AhAPX genes exhibited a comparatively well-preserved exon-intron pattern and motif configuration contained by the identical group. We discovered five phytohormones-, six abiotic stress-, and five growth and development-related cis-elements in the promoter regions of AhAPX. Fourteen putative ah-miRNAs from 12 families were identified, targeting 33 AhAPX genes. Furthermore, we identified 3,257 transcription factors from 38 families (including AP2, ARF, B3, bHLH, bZIP, ERF, MYB, NAC, WRKY, etc.) in 162 AhAPX genes. Gene ontology and KEGG enrichment analysis confirm the role of AhAPX genes in oxidoreductase activity, catalytic activity, cell junction, cellular response to stimulus and detoxification, biosynthesis of metabolites, and phenylpropanoid metabolism. Based on transcriptome datasets, some genes such as AhAPX4/7/17/77/82/86/130/133 and AhAPX160 showed significantly higher expression in diverse tissues/organs, i.e., flower, leaf, stem, roots, peg, testa, and cotyledon. Likewise, only a few genes, including AhAPX4/17/19/55/59/82/101/102/137 and AhAPX140, were significantly upregulated under abiotic (drought and cold), and phytohormones (ethylene, abscisic acid, paclobutrazol, brassinolide, and salicylic acid) treatments. qRT-PCR-based expression profiling presented the parallel expression trends as generated from transcriptome datasets. Our discoveries gave new visions into the evolution of APX genes and provided a base for further functional examinations of the AhAPX genes in peanut breeding programs.

Introduction

Plants are regularly subjected to various environmental factors (abiotic and biotic), which substantially influence crop productivity and cause challenges to food security (Sabagh et al., 2021; Mir et al., 2022; Raza et al., 2022a,b; Saeed et al., 2022; Sharma et al., 2022). These factors can enhance the generation of reactive oxygen species (ROS), damaging cellular systems and supermolecules consisting of DNA, proteins, and lipids, and ultimately leading to cell death (Fahad et al., 2015, 2017; Mittler, 2017; Hasanuzzaman et al., 2020). ROS are mainly produced in different locations including chloroplast, apoplast, plasma membrane, mitochondrion, endoplasmic reticulum, peroxisomes, and cell walls (Mittler, 2017; Hasanuzzaman et al., 2020). In plants, ROS are formed as chemical by-products due to the imperfect decline of oxygen metabolism. Further, ROS are considered as signaling elements that regulate stress tolerance mechanisms in plant molecular biology (Das and Roychoudhury, 2014; Mittler, 2017; Hasanuzzaman et al., 2020). Current progress has revealed that ROS homeostasis is essential for maintaining typical cellular characteristics (Mittler, 2017; Hasanuzzaman et al., 2020, 2021). Subsequently, for regular ROS signaling, plants have developed defense systems including enzymatic and non-enzymatic antioxidant enzymes to maintain the equilibrium between ROS-scavenging and production under stress conditions (Das and Roychoudhury, 2014; Mittler, 2017; Hasanuzzaman et al., 2020, 2021).

In plants, among diverse antioxidant enzymes entailed in ROS-scavenging mechanisms, ascorbate peroxidase (APX; EC, 1.11.1.11) belongs to the heme peroxidase superfamily (Hodges et al., 1999; Teixeira et al., 2004; Lazzarotto et al., 2011). In higher plants, APXs are one of the main antioxidant enzymes involved in regulating the ascorbate-glutathione cycle and take parts to scavenge hydrogen peroxide (H2O2) from chloroplast and the cytoplasm. Mainly, it utilized the ascorbic acid as an electron giver to scavenge H2O2 generated in plants and thus enhances tolerance to oxidative and other stresses in plants (Cao et al., 2017; Pandey et al., 2017; Hasanuzzaman et al., 2021; Raza et al., 2021a). Additionally, APX enzymes are automated by APX gene family involved in stress tolerance has been thoroughly explored in diverse plant species using various in silico approaches. For example, five APX genes have been discovered in wild watermelon (Citrullus lanatus) (Malambane et al., 2018); six in shrub (Ammopiptanthus nanus) (Wang et al., 2022); eight in rice (Oryza sativa L.) (Teixeira et al., 2004) and Arabidopsis thaliana (Panchuk et al., 2002, Panchuk et al., 2005); nine in sorghum (Sorghum bicolor L.) (Akbudak et al., 2018); 13 in kiwifruit (Actinidia chinensis) (Liao et al., 2020); 16 APX genes in tomato (Solanum lycopersicum L.) (Najami et al., 2008); 21 in wheat (Triticum aestivum L.) (Tyagi et al., 2020); and 26 in cotton (Gossypium hirsutum L.) (Tao et al., 2018). Nevertheless, the APX gene family in peanut (Arachis hypogea L.) has not been systematically reported, and their roles in peanut development and stress tolerance still remain ambiguous.

Cultivated peanut/groundnut (A. hypogaea L.), an allotetraploid crop, is one of the most valuable and economic oilseed food crops globally (Agarwal et al., 2018; Bertioli et al., 2019; Chen X. et al., 2019; Zhuang et al., 2019). This crop is being widely cultivated in the tropical and subtropical regions globally; however, several abiotic and biotic factors significantly affect its growth and production, including many important agronomic traits (Agarwal et al., 2018; Gangurde et al., 2020, 2021; Kumar et al., 2020; Pandey et al., 2020; Shasidhar et al., 2020; Sinha et al., 2020; Jadhav et al., 2021; Soni et al., 2021; Aravind et al., 2022; Bomireddy et al., 2022; Liu et al., 2022; Patel et al., 2022). Therefore, it is vital to identify new potential genes associated with multiple stress tolerance and trait improvement in peanut for better protein-rich food supply, particularly in Asian and African countries. In this regard, the recently sequenced peanut genome and recent advances in genomics-assisted breeding make it easier for us to carry out a comprehensive systematic analysis of new gene families (Varshney et al., 2019, 2020, 2021a,b). To our best knowledge, APX gene family was yet to be comprehensively characterized in peanut. Thus, the current study performed a genome-wide identification and characterized the APX gene family in peanut (AhAPX). Several in silico analysis, such as characterization, genomic evolution, gene structure, conserved motifs, cis-regulatory elements, putative miRNA and transcription factors, functional annotations, etc., were utilized to get insights into the novel roles of AhAPX genes. Furthermore, their expression profiling in diverse tissues/organs, under phytohormones and abiotic stress conditions were also performed using transcriptome and qRT-PCR techniques. In short, this report offered evolutionary and functional roles of AhAPX genes which could open new windows for further functional studies on the novel roles of AhAPX genes in peanut breeding programs under stress conditions.

Materials and Methods

Discovery and Physicochemical Features of APX Genes

As explained earlier (Li et al., 2021; Raza et al., 2021b; Su et al., 2021), two approaches, i.e., BLASTP and the Hidden Markov Model (HMM), were applied to identify APX genes in the peanut (A. hypogea) genome. The peanut genome sequence was taken from peanut Genome Resource (PGR) database[1] (Zhuang et al., 2019). In the first approach, the sequences of eight Arabidopsis thaliana APX genes were gained from TAIR Arabidopsis genome database[2] (Rhee et al., 2003). Then, these sequences were utilized as a query to perform the BLASTP against peanut genome. In the second approach, HMMER 3.1[3] (Finn et al., 2015) software was employed to seek out the APX genes with default controls. Later, the HMM file of the ascorbic acid peroxidase domain (PF00141) was retrieved from the Pfam database[4] (El-Gebali et al., 2019). Lastly, the sequences comprising the PF00141 domain were chosen as putative APX genes, and finally, 166 AhAPX genes were discovered by uniting the results obtained from both approaches in the peanut genome. Following the same approaches, APX genes were also discovered in diploid parents, i.e., A. duranensis (90 genes; AdAPX1-AdAPX90) and A. ipaensis (102 genes; AiAPX1-AiAPX102). Their genome sequences were downloaded from PeanutBase database[5] (Dash et al., 2016). The detailed information (including gene name, gene ID, and protein sequences) of all identified APX genes is given in Supplementary Table 1.

Physicochemical features of AhAPX were assessed utilizing the ProtParam tool[6] in the ExPASy server (Gasteiger et al., 2005). Subcellular localization of AhAPX proteins was estimated from CELLO v.2.5[7] (Yu et al., 2006). Exon-intron configuration of all AhAPX were determined using TBtools software (v1.09867)[8] (Chen et al., 2020). The conserved motifs of AhAPX sequences were documented using the MEME website[9] (Bailey et al., 2009).

Evaluation of Chromosomal Location, Phylogenetic Relationships, and Synteny Analysis of APX Genes

The data about the chromosomal location of AhAPX was attained from the PGR database, and the TBTools was utilized to map the genes on chromosomes. To discover the evolutionary link of the APX proteins, a phylogenetic tree among A. hypogea (AhAPXs), A. duranensis (AdAPXs), A. ipaensis (AiAPXs), and A. thaliana (AtAPXs) was created. Multiple sequence alignment was implemented using MEGA7 software[10] (Kumar et al., 2018). The neighbor-joining (NJ) method was undertaken to design a phylogenetic tree with 1,000 bootstrap replicates and iTOL was used to beautify the tree[11] (Letunic and Bork, 2021).

The syntenic associations of APX genes between A. hypogea, A. duranensis, A. ipaensis, and A. thaliana were executed through the MCScanX toolkit and were pictured by the Advance Circos package in the TBTools software (Chen et al., 2020). Additionally, the multiple collinearity analysis of APX genes was completed via multiple synteny Plot packages in TBTools software. The Ka/Ks ratios of all AhAPX were predicted via simple Ka/Ks calculator in TBTools software.

Prediction of cis-Regulatory Elements in the AhAPX Promoters

To predict the putative cis-regulatory elements in the AhAPX promoters, the 2 Kb sequences upstream of start codons were separated from the peanut genome. The promoter sequences of all AhAPX genes were observed with PlantCARE website[12] (Lescot et al., 2002), and the picture was illustrated using TBtools software.

Prediction of Putative miRNAs Targeting AhAPX Genes and Functional Annotation Evaluation

The CDS of all AhAPX was used to predict the miRNA target sites with psRNATarget website[13] (Dai et al., 2018) with default considerations. The interactive network figure among the putative miRNAs and AhAPX genes was made via Cytoscape software (v3.9)[14] (Shannon et al., 2003). Gene ontology (GO) and Kyoto encyclopedia of genes and genomics (KEGG) annotation evaluation was undertaken by submitting all AhAPX protein sequences to the eggNOG v4.0[15] (Powell et al., 2014). At the same time, GO and KEGG enrichment evaluations were performed with TBtools software.

Prediction of Transcription Factor Regulatory Network of AhAPX Genes

To predict the putative transcription factors (TFs) and regulatory network, the 500 bp nucleotide sequences from upstream regions of AhAPX genes were removed and complied to the PlantRegMap (Transcriptional Regulatory Map)[16] with p-value ≤ 1e–6 (Tian et al., 2020). The regulatory network of predicted TFs and AhAPX genes was created with Cytoscape v3.9 software.

Expression Profiling of AhAPX Genes

The expression levels of all AhAPX genes at diverse developmental tissues/organs (embryo, cotyledon, testa, pericarp, peg, root and stem, root nodule, root tip, root, step tip, stem, leaf, and flower), under various hormones (ethylene, abscisic acid, paclobutrazol, brassinolide, and salicylic acid), and abiotic stress (drought and cold) conditions were evaluated using openly available transcriptome dataset of cultivated peanut (cultivar Shitouqi) at PGR database (see text footnote 1; BioProject PRJNA480120) (Zhuang et al., 2019). The detailed procedure for sample harvesting and data analysis is presented in our recent paper (Zhuang et al., 2019). Owing to the great differences in the expression trends, we normalize the log2 of fragments per kilobase of transcript per million (FPKM) values. Finally, the circular heat maps were designed by TBtools software.

Plant Material and Stress Conditions

In this study, a widely cultivated peanut variety in southeast China, “Minhua-6” was used for stress treatments. The same variety was also used for transcriptome analysis in our recent paper (Zhuang et al., 2019). The seeds of the “Minhua-6” cultivar were obtained from the FAFU, Fuzhou, China. The vigor seeds were cultured on small pots having a mix of vermicompost. For stress treatment, germinated seedlings at the four-leaf stage were exposed to cold stress at 4°C and ABA (10 μg mL–1) for 0 (CK), 3, 6, 9, and 12 h with three biological repetitions. All of the samples were instantly frozen in liquid nitrogen and were kept at -80°C until RNA extraction.

RNA Extraction and qRT-PCR-based Expression Analysis

Total RNA was isolated utilizing the CTAB method as described in our recent work (Sharif et al., 2021), and cDNA was prepared with the help of Evo M-MLV RT Kit with gDNA Clean for qPCR II (Code No. AG11711; Hunan Aikerui Biological Engineering Co., Ltd., China) following the developer guidelines. The comprehensive information on qRT-PCR reaction has been described in our recent work (Sharif et al., 2021). The peanut Actin gene was used as a housekeeping gene to stabilize the expression (Chi et al., 2012). The expression data of three biological repeats were normalized using the 2–ΔΔCT method (Livak and Schmittgen, 2001). All the primers used for qRT-PCR are given in Supplementary Table 2. The graphs were made with GraphPad Prism v9.0.0 software[17] (Swift, 1997).

Results

Comprehensive Characterization of AhAPX Genes in Peanut Genome

In this study, a total of 166 AhAPX genes were discovered in the peanut genome (Table 1). Henceforward, these genes are labeled as “AhAPX1–AhAPX166.” These genes were irregularly mapped in the cultivated peanut genome. The maximum number (15) of AhAPX genes were mapped on Chr14, followed by Chr04/Chr11 with 11 genes on each chromosome. While, Chr01/Chr06/Chr10/Chr20 were found to have ten genes, followed by Chr05/Chr15/Chr16 with nine genes, Chr07/Chr19 with eight genes, Chr09/Chr13 with seven genes, Chr03/Chr08/Chr17/Chr18 with six genes on each chromosome. The lowest number (1 and 4) of AhAPX genes were mapped on Chr02 and Chr12, respectively. Notably, three AhAPX genes (AhAPX1/2/3) were also mapped on an unassembled region (Chr00) (Figure 1).

TABLE 1

The data of 166 AhAPX genes identified in peanut genome.

Gene name	Gene ID	Genomic region	CDS length (bp)	Exon	Intron	Protein length (aa)	MW (KDa)	PI	GRAVY	Subcellular localization
AhAPX1	AH00G01650.1	Chr00 (2097889, 2103344, +)	1260	11	10	419	44.68	8.64	−0.156	Chloroplast
AhAPX2	AH00G03280.1	Chr00 (4356387, 4358168, +)	756	7	6	251	27.79	5.39	−0.491	Cytoplasmic
AhAPX3	AH00G04650.1	Chr00 (6939173, 6940468, −)	987	4	3	328	35.75	6.17	−0.223	Extracellular and nuclear
AhAPX4	AH01G28620.1	Chr01 (102500998, 102502258, −)	1011	4	3	336	37.9	8.48	−0.37	Nuclear
AhAPX5	AH01G31200.1	Chr01 (105607976, 105610045, +)	972	4	3	323	35.1	6.59	−0.101	Extracellular
AhAPX6	AH01G01000.1	Chr01 (1376119, 1378806, −)	1005	4	3	334	36.6	8.23	−0.169	Extracellular
AhAPX7	AH01G11780.1	Chr01 (19611835, 19615124, +)	981	4	3	326	35.23	8.87	−0.056	Extracellular
AhAPX8	AH01G05760.1	Chr01 (7328535, 7331547, +)	969	4	3	322	34.26	6.28	0.029	Extracellular and plasma membrane
AhAPX9	AH01G05770.1	Chr01 (7337595, 7340770, −)	987	3	2	328	36.11	9.57	−0.173	Extracellular
AhAPX10	AH01G05780.1	Chr01 (7349081, 7354713, −)	969	3	2	322	35.44	8.68	−0.441	Nuclear
AhAPX11	AH01G21450.1	Chr01 (93462135, 93464576, +)	987	4	3	328	35.34	6.08	0.017	Extracellular
AhAPX12	AH01G22400.1	Chr01 (94528243, 94529833, +)	990	3	2	329	36.09	9.2	−0.206	Extracellular
AhAPX13	AH01G26210.1	Chr01 (99439266, 99440500, −)	999	4	3	332	35.7	4.5	−0.139	Extracellular
AhAPX14	AH02G25000.1	Chr02 (95622557, 95623515, +)	660	3	2	219	24.43	8.99	−0.35	Extracellular
AhAPX15	AH03G45630.1	Chr03 (139181976, 139183516, +)	966	3	2	321	34	6.51	−0.088	Extracellular
AhAPX16	AH03G12620.1	Chr03 (14627327, 14629723, +)	978	4	3	325	35.45	6.55	−0.021	Plasma membrane
AhAPX17	AH03G01960.1	Chr03 (2186290, 2188245, −)	756	9	8	251	27	5.52	−0.319	Cytoplasmic
AhAPX18	AH03G05320.1	Chr03 (5424432, 5426098, +)	978	4	3	325	34.52	8.71	0.015	Extracellular
AhAPX19	AH03G06180.1	Chr03 (6345566, 6348916, −)	867	9	8	288	31.66	6.67	−0.311	Cytoplasmic
AhAPX20	AH03G07350.1	Chr03 (7481431, 7483098, −)	978	4	3	325	34.61	8.71	0.019	Extracellular and plasma membrane
AhAPX21	AH04G21680.1	Chr04 (106761278, 106763236, +)	954	4	3	317	33.53	8.05	−0.061	Extracellular
AhAPX22	AH04G21700.1	Chr04 (106776477, 106779460, +)	957	4	3	318	34	4.94	−0.057	Extracellular
AhAPX23	AH04G09710.1	Chr04 (16167517, 16170131, +)	912	4	3	303	33.45	7.53	0.003	Extracellular
AhAPX24	AH04G09790.1	Chr04 (16461353, 16464502, −)	1068	4	3	355	38.16	6.58	0.005	Extracellular and plasma membrane
AhAPX25	AH04G09830.1	Chr04 (16586332, 16594630, −)	1923	7	6	640	69.4	5.78	−0.138	Extracellular and plasma membrane
AhAPX26	AH04G09840.1	Chr04 (16603008, 16606152, −)	1113	4	3	370	39.73	5.72	−0.016	Extracellular
AhAPX27	AH04G09850.1	Chr04 (16611949, 16615189, −)	1077	4	3	358	38.56	5.74	−0.085	Extracellular
AhAPX28	AH04G09870.1	Chr04 (16648330, 16651554, −)	1080	4	3	359	38.83	7.51	−0.154	Extracellular
AhAPX29	AH04G10990.1	Chr04 (20506854, 20510294, +)	1047	3	2	348	38.82	5.58	−0.139	Extracellular and plasma membrane
AhAPX30	AH04G12400.1	Chr04 (28356898, 28358984, −)	990	4	3	329	36	7.58	−0.1	Extracellular
AhAPX31	AH04G06960.1	Chr04 (8749652, 8755948, +)	999	4	3	332	36	5.85	−0.117	Extracellular
AhAPX32	AH05G33570.1	Chr05 (109243748, 109247060, +)	1032	4	3	343	37.89	5.3	0.039	Plasma membrane
AhAPX33	AH05G34100.1	Chr05 (110343093, 110344607, −)	753	2	1	250	27.34	7.04	−0.191	Cytoplasmic
AhAPX34	AH05G02820.1	Chr05 (2952742, 2957237, +)	849	9	8	282	31.57	7.72	−0.496	Cytoplasmic
AhAPX35	AH05G12980.1	Chr05 (33401595, 33403392, −)	1269	2	1	422	45.9	5.21	−0.302	Cytoplasmic, nuclear, and extracellular
AhAPX36	AH05G03640.1	Chr05 (3964114, 3966683, +)	1047	4	3	348	39.09	5.89	−0.224	Extracellular
AhAPX37	AH05G04730.1	Chr05 (5512010, 5518889, −)	984	4	3	327	35.78	9.05	−0.147	Extracellular
AhAPX38	AH05G05760.1	Chr05 (7138559, 7139891, −)	984	4	3	327	35.88	6.42	0	Extracellular
AhAPX39	AH05G21680.1	Chr05 (87703778, 87704768, +)	645	3	2	214	23.47	5.95	−0.169	Extracellular
AhAPX40	AH05G21770.1	Chr05 (87831257, 87833413, −)	984	4	3	327	36	5.5	−0.127	Extracellular
AhAPX41	AH06G24710.1	Chr06 (101560772, 101566207, +)	990	3	2	329	35.4	5.31	−0.142	Extracellular and chloroplast
AhAPX42	AH06G24750.1	Chr06 (101678350, 101681066, −)	978	3	2	325	35.12	5.87	−0.095	Extracellular
AhAPX43	AH06G26990.1	Chr06 (106045942, 106046919, −)	981	1	0	326	35.92	8.33	−0.187	Extracellular and chloroplast
AhAPX44	AH06G12580.1	Chr06 (17096141, 17097919, −)	1050	4	3	349	38.3	9.06	−0.146	Extracellular
AhAPX45	AH06G12600.1	Chr06 (17107249, 17113857, −)	1923	16	15	640	70.66	8.94	−0.077	Chloroplast
AhAPX46	AH06G12640.1	Chr06 (17206186, 17208105, +)	1047	4	3	348	38	9.26	−0.121	Extracellular
AhAPX47	AH06G13400.1	Chr06 (18468981, 18470093, −)	957	3	2	318	34.52	8.79	−0.068	Extracellular
AhAPX48	AH06G00870.1	Chr06 (2535291, 2536767, −)	981	4	3	326	34.46	5.77	−0.012	Extracellular
AhAPX49	AH06G20810.1	Chr06 (88751346, 88752854, −)	954	2	1	317	34.17	9.07	−0.038	Extracellular
AhAPX50	AH06G20840.1	Chr06 (88866272, 88866907, −)	639	1	0	212	22.93	6.82	0.017	Chloroplast
AhAPX51	AH07G12530.1	Chr07 (18527530, 18532254, −)	972	4	3	323	35	9.76	−0.198	Extracellular and mitochondrial
AhAPX52	AH07G12560.1	Chr07 (18594967, 18601313, +)	1005	3	2	334	36.23	5.8	−0.22	Extracellular
AhAPX53	AH07G12590.1	Chr07 (18635964, 18639438, −)	900	4	3	299	32.1	6.41	0.088	Plasma membrane
AhAPX54	AH07G16820.1	Chr07 (44801964, 44806304, +)	1035	3	2	344	38.1	8.78	−0.11	Plasma membrane
AhAPX55	AH07G19820.1	Chr07 (62509939, 62515927, −)	1065	11	10	354	38.47	8.59	−0.324	Mitochondrial
AhAPX56	AH07G22100.1	Chr07 (73486525, 73488901, −)	1221	4	3	406	45.08	5.58	−0.359	Nuclear, extracellular, and plasma membrane
AhAPX57	AH07G07450.1	Chr07 (8286104, 8288644, −)	975	4	3	324	34.37	8.54	−0.083	Extracellular
AhAPX58	AH07G07460.1	Chr07 (8308573, 8309778, +)	762	4	3	253	27.57	8.83	−0.272	Extracellular and mitochondrial
AhAPX59	AH08G05850.1	Chr08 (10750010, 10755089, +)	1338	12	11	445	48.75	8.67	−0.428	Chloroplast
AhAPX60	AH08G13980.1	Chr08 (28333679, 28334962, −)	756	7	6	251	27.75	5.39	−0.48	Cytoplasmic
AhAPX61	AH08G15100.1	Chr08 (29841553, 29842344, −)	795	1	0	264	28.8	4.85	−0.335	Nuclear and cytoplasmic
AhAPX62	AH08G16780.1	Chr08 (31925820, 31927225, +)	984	4	3	327	35.85	8.93	−0.108	Extracellular
AhAPX63	AH08G19120.1	Chr08 (35244506, 35247372, +)	975	3	2	324	34.42	8.75	−0.044	Extracellular
AhAPX64	AH08G26960.1	Chr08 (47233841, 47238063, −)	993	10	9	330	35.63	8.42	−0.221	Chloroplast
AhAPX65	AH09G23660.1	Chr09 (106807615, 106809134, +)	984	2	1	327	35.95	8.06	−0.046	Extracellular and mitochondrial
AhAPX66	AH09G31660.1	Chr09 (116756835, 116759702, −)	984	4	3	327	35.92	6.09	−0.202	Extracellular
AhAPX67	AH09G08990.1	Chr09 (12467446, 12469586, +)	1011	4	3	336	36	9.22	−0.113	Nuclear and plasma membrane
AhAPX68	AH09G11440.1	Chr09 (19596211, 19598370, −)	1008	2	1	335	36.05	8.1	−0.094	Chloroplast and extracellular
AhAPX69	AH09G02450.1	Chr09 (2707377, 2709690, +)	1365	4	3	454	50.07	4.69	−0.35	Nuclear and plasma membrane
AhAPX70	AH09G19280.1	Chr09 (84644615, 84652197, +)	858	4	3	285	31.31	8.41	−0.263	Chloroplast
AhAPX71	AH09G20940.1	Chr09 (95646878, 95647778, −)	327	3	2	108	11.59	9.34	−0.157	Extracellular
AhAPX72	AH10G22530.1	Chr10 (100608918, 100612037, −)	1038	3	2	345	38.57	5.47	−0.136	Cytoplasmic
AhAPX73	AH10G28820.1	Chr10 (111234752, 111235885, −)	969	2	1	322	35.56	6.6	−0.064	Plasma membrane
AhAPX74	AH10G28830.1	Chr10 (111237536, 111239429, −)	975	3	2	324	35	5.98	0.028	Plasma membrane
AhAPX75	AH10G10440.1	Chr10 (17084135, 17085775, +)	966	4	3	321	35.11	9.49	−0.117	Mitochondrial
AhAPX76	AH10G05800.1	Chr10 (5516527, 5517924, −)	981	3	2	326	34.81	7.54	−0.036	Extracellular
AhAPX77	AH10G05810.1	Chr10 (5525856, 5527195, +)	996	2	1	331	35.55	8.98	−0.037	Extracellular
AhAPX78	AH10G06100.1	Chr10 (5774246, 5774909, −)	594	2	1	197	21	5.61	0.36	Plasma membrane and extracellular
AhAPX79	AH10G17560.1	Chr10 (81389354, 81391402, +)	957	3	2	318	3.85	9.4	−0.17	Extracellular
AhAPX80	AH10G20050.1	Chr10 (93192984, 93194610, +)	972	4	3	323	34.97	5.46	0.043	Plasma membrane
AhAPX81	AH10G21960.1	Chr10 (99235900, 99237538, +)	654	3	2	217	23.87	5.29	0.004	Plasma membrane
AhAPX82	AH11G28810.1	Chr11 (138798034, 138799289, +)	1011	4	3	336	37.9	8.48	−0.37	Nuclear
AhAPX83	AH11G31650.1	Chr11 (143323830, 143325073, +)	999	4	3	332	35.72	4.41	−0.172	Extracellular
AhAPX84	AH11G35510.1	Chr11 (148378457, 148381103, −)	885	3	2	294	32.16	9.23	−0.199	Extracellular
AhAPX85	AH11G36340.1	Chr11 (149098252, 149100518, −)	987	4	3	328	35.31	6.07	0.007	Extracellular
AhAPX86	AH11G11550.1	Chr11 (24493194, 24496183, +)	981	4	3	326	35.26	8.88	−0.057	Extracellular
AhAPX87	AH11G11700.1	Chr11 (25189097, 25190336, +)	687	3	2	228	24.68	4.81	−0.188	Extracellular
AhAPX88	AH11G02890.1	Chr11 (3085958, 3089759, −)	984	4	3	327	35.36	8.91	−0.135	Extracellular
AhAPX89	AH11G02910.1	Chr11 (3130507, 3135477, +)	1020	3	2	339	37.34	9.07	−0.284	Extracellular
AhAPX90	AH11G02940.1	Chr11 (3154813, 3157814, +)	858	3	2	285	31.1	9.36	−0.12	Extracellular
AhAPX91	AH11G02950.1	Chr11 (3166698, 3169834, −)	888	5	4	295	31.26	5.06	−0.145	Extracellular
AhAPX92	AH11G14080.1	Chr11 (38404886, 38409314, −)	1404	12	11	467	52.19	9.02	−0.453	Nuclear
AhAPX93	AH12G26730.1	Chr12 (108404606, 108406854, +)	975	4	3	324	35.2	8.28	−0.002	Extracellular
AhAPX94	AH12G26740.1	Chr12 (108408697, 108410986, +)	990	3	2	329	36.09	8.8	−0.234	Extracellular, mitochondrial and chloroplast
AhAPX95	AH12G26750.1	Chr12 (108428068, 108430589, +)	987	3	2	328	35.84	5.66	−0.264	Extracellular
AhAPX96	AH12G38300.1	Chr12 (122043858, 122045120, +)	996	3	2	331	37.38	6.26	−0.412	Extracellular
AhAPX97	AH13G48270.1	Chr13 (139486821, 139487952, +)	966	3	2	321	34	6.51	−0.101	Extracellular
AhAPX98	AH13G58440.1	Chr13 (149092750, 149095384, +)	975	3	2	324	35	5.88	0.011	Plasma membrane
AhAPX99	AH13G58450.1	Chr13 (149097506, 149098640, +)	969	2	1	322	35.33	6.31	−0.038	Extracellular
AhAPX100	AH13G15620.1	Chr13 (18204851, 18207371, +)	978	4	3	325	35.49	8.05	−0.013	Extracellular and plasma membrane
AhAPX101	AH13G03790.1	Chr13 (3974837, 3976803, −)	756	9	8	251	27	5.52	−0.319	Cytoplasmic
AhAPX102	AH13G08510.1	Chr13 (8737422, 8740756, +)	867	9	8	288	31.66	6.67	−0.311	Cytoplasmic
AhAPX103	AH13G09650.1	Chr13 (9945748, 9947398, −)	978	4	3	325	34.5	8.71	0.015	Extracellular
AhAPX104	AH14G24560.1	Chr14 (102202325, 102204136, +)	984	4	3	327	35.79	8.44	−0.154	Extracellular
AhAPX105	AH14G25410.1	Chr14 (105306662, 105308874, −)	924	4	3	307	32.74	5	−0.086	Extracellular
AhAPX106	AH14G25420.1	Chr14 (105316704, 105318852, −)	954	4	3	317	33.51	8.05	−0.034	Extracellular
AhAPX107	AH14G25430.1	Chr14 (105327285, 105329671, −)	957	4	3	318	33.64	8.51	−0.084	Extracellular
AhAPX108	AH14G08400.1	Chr14 (10636078, 10640476, +)	999	4	3	332	36.11	5.77	−0.137	Extracellular
AhAPX109	AH14G08420.1	Chr14 (10696309, 10699909, +)	1068	4	3	355	38.31	6.44	−0.153	Extracellular
AhAPX110	AH14G08430.1	Chr14 (10719836, 10722950, +)	1074	4	3	357	38.44	5.74	−0.075	Extracellular
AhAPX111	AH14G08440.1	Chr14 (10740576, 10743027, +)	1077	4	3	358	38.25	5.57	0.027	Extracellular
AhAPX112	AH14G08450.1	Chr14 (10751673, 10756427, +)	1068	4	3	355	38	4.99	−0.048	Extracellular
AhAPX113	AH14G08480.1	Chr14 (10795498, 10798919, +)	1068	4	3	355	38.14	6.2	−0.005	Extracellular
AhAPX114	AH14G08550.1	Chr14 (11049580, 11052270, −)	927	4	3	308	33.87	8.05	−0.041	Extracellular
AhAPX115	AH14G13430.1	Chr14 (22102438, 22105949, +)	1047	3	2	348	38.8	5.68	−0.149	Extracellular and plasma membrane
AhAPX116	AH14G16980.1	Chr14 (39854809, 39855923, +)	570	3	2	189	20.65	6.7	0.287	Extracellular and plasma membrane
AhAPX117	AH14G16990.1	Chr14 (39859734, 39860093, +)	363	1	0	120	13.39	9.03	−0.37	Extracellular
AhAPX118	AH14G21760.1	Chr14 (89731359, 89733140, −)	909	5	4	302	32.95	8.35	−0.201	Extracellular
AhAPX119	AH15G18730.1	Chr15 (105800589, 105804751, −)	1032	4	3	343	37.88	5.3	0.024	Plasma membrane
AhAPX120	AH15G00780.1	Chr15 (1195384, 1202015, −)	984	4	3	327	35.78	9.05	−0.147	Extracellular
AhAPX121	AH15G33980.1	Chr15 (148489966, 148492117, +)	984	4	3	327	36.17	5.88	−0.164	Extracellular and nuclear
AhAPX122	AH15G33990.1	Chr15 (148500369, 148501868, +)	705	4	3	234	25.5	4.8	−0.226	Cytoplasmic and chloroplast
AhAPX123	AH15G34130.1	Chr15 (148706618, 148708110, −)	834	5	4	277	30.66	6.22	−0.226	Extracellular and plasma membrane
AhAPX124	AH15G35170.1	Chr15 (149938106, 149940460, −)	669	3	2	222	24.22	7.67	−0.021	Extracellular
AhAPX125	AH15G37650.1	Chr15 (152607618, 152611276, −)	1092	3	2	363	40.13	5.51	−0.222	Extracellular
AhAPX126	AH15G09760.1	Chr15 (17115019, 17116810, +)	1257	2	1	418	45.61	5.4	−0.337	Extracellular, cytoplasmic and nuclear
AhAPX127	AH15G01790.1	Chr15 (3022442, 3024001, −)	984	4	3	327	36	6.87	−0.042	Extracellular
AhAPX128	AH16G05890.1	Chr16 (10586280, 10589926, −)	987	4	3	328	35.89	7.97	−0.131	Extracellular
AhAPX129	AH16G06030.1	Chr16 (10824424, 10825859, +)	882	4	3	293	32.28	8.53	−0.268	Extracellular
AhAPX130	AH16G25780.1	Chr16 (114921710, 114923167, −)	954	2	1	317	33.99	8.98	−0.027	Extracellular
AhAPX131	AH16G25800.1	Chr16 (115100883, 115101305, −)	426	1	0	141	15.52	6.28	−0.05	Extracellular, cytoplasmic and chloroplast
AhAPX132	AH16G30440.1	Chr16 (129635392, 129640099, +)	990	3	2	329	35.36	5.32	−0.127	Extracellular and chloroplast
AhAPX133	AH16G30490.1	Chr16 (129750891, 129753522, −)	975	3	2	324	34.81	5.87	−0.047	Extracellular
AhAPX134	AH16G33620.1	Chr16 (135979748, 135980725, −)	981	1	0	326	35.95	8.69	−0.161	Extracellular
AhAPX135	AH16G03520.1	Chr16 (7153751, 7155209, −)	981	4	3	326	34.38	5.31	−0.009	Extracellular
AhAPX136	AH16G01030.1	Chr16 (993418, 995239, +)	1050	4	3	349	38.29	9.17	−0.139	Extracellular
AhAPX137	AH17G30310.1	Chr17 (125992323, 125997218, −)	1338	12	11	445	48.73	8.8	−0.44	Chloroplast
AhAPX138	AH17G11990.1	Chr17 (20654955, 20659787, −)	972	4	3	323	34.93	9.74	−0.18	Extracellular
AhAPX139	AH17G12030.1	Chr17 (20764144, 20766484, +)	735	2	1	244	26.45	6.81	−0.317	Extracellular
AhAPX140	AH17G18150.1	Chr17 (49822929, 49829110, +)	1068	11	10	355	38.64	8.79	−0.338	Mitochondrial
AhAPX141	AH17G06310.1	Chr17 (7780769, 7782202, −)	963	4	3	320	34.92	8.65	−0.145	Extracellular
AhAPX142	AH17G06350.1	Chr17 (7839321, 7842337, +)	966	4	3	321	34	8.54	−0.113	Extracellular
AhAPX143	AH18G23730.1	Chr18 (103745127, 103747854, +)	1014	3	2	337	37.31	9.13	−0.136	Mitochondrial and plasma membrane
AhAPX144	AH18G10570.1	Chr18 (14253327, 14256241, +)	972	3	2	323	34.3	8.75	−0.044	Extracellular
AhAPX145	AH18G15530.1	Chr18 (26788797, 26795823, −)	1416	16	15	471	52.82	9	−0.639	Nuclear
AhAPX146	AH18G05400.1	Chr18 (5046262, 5048240, −)	969	2	1	322	35.34	5.8	−0.104	Plasma membrane
AhAPX147	AH18G07180.1	Chr18 (7610724, 7612104, +)	987	4	3	328	35.93	8.82	−0.101	Extracellular
AhAPX148	AH18G22460.1	Chr18 (92176526, 92178893, +)	1218	4	3	405	45.05	5.81	−0.101	Extracellular, nuclear and plasma membrane
AhAPX149	AH19G24230.1	Chr19 (108739539, 108750043, −)	996	4	3	331	36.82	6.95	−0.132	Extracellular
AhAPX150	AH19G26520.1	Chr19 (124514590, 124517216, −)	996	4	3	331	40.26	7.97	0	Extracellular and chloroplast
AhAPX151	AH19G29790.1	Chr19 (138198709, 138200248, +)	984	2	1	327	35.98	8.06	−0.054	Extracellular and mitochondrial
AhAPX152	AH19G36370.1	Chr19 (152526370, 152529191, +)	984	4	3	327	36.19	5.9	−0.225	Extracellular and nuclear
AhAPX153	AH19G42570.1	Chr19 (158270903, 158272107, −)	975	3	2	324	35.69	9.04	−0.179	Extracellular
AhAPX154	AH19G11940.1	Chr19 (16033083, 16035651, +)	1014	4	3	337	36.06	8.91	−0.113	Extracellular and plasma membrane
AhAPX155	AH19G14960.1	Chr19 (24411814, 24415355, −)	1278	3	2	425	46.49	6.47	−0.117	Chloroplast
AhAPX156	AH19G03800.1	Chr19 (3648102, 3650393, +)	1365	4	3	454	49.95	4.72	−0.351	Nuclear
AhAPX157	AH20G22440.1	Chr20 (100242945, 100244252, −)	987	4	3	328	35.74	6.17	−0.213	Extracellular and nuclear
AhAPX158	AH20G23580.1	Chr20 (107122955, 107124841, +)	957	3	2	318	33.85	9.4	−0.173	Extracellular
AhAPX159	AH20G08720.1	Chr20 (10757292, 10758717, −)	981	3	2	326	34.71	6.07	−0.028	Extracellular
AhAPX160	AH20G08730.1	Chr20 (10773674, 10775017, +)	999	2	1	332	35.59	8.98	−0.023	Extracellular
AhAPX161	AH20G09010.1	Chr20 (11124003, 11124708, −)	636	2	1	211	22.75	4.93	0.392	Plasma membrane
AhAPX162	AH20G26300.1	Chr20 (119159975, 119161601, +)	972	2	1	323	35	5.32	0.067	Plasma membrane
AhAPX163	AH20G28750.1	Chr20 (126510516, 126511240, +)	465	2	1	154	17	6.4	−0.372	Nuclear
AhAPX164	AH20G28770.1	Chr20 (126544791, 126546815, +)	927	4	3	308	33.85	4.89	−0.132	Extracellular and cytoplasmic
AhAPX165	AH20G29320.1	Chr20 (128237247, 128240109, −)	1038	3	2	345	38.54	5.38	−0.138	Cytoplasmic
AhAPX166	AH20G14810.1	Chr20 (25055084, 25056732, +)	969	4	3	322	35.15	9.54	−0.139	Mitochondrial

In the genomic position, the positive (+) and negative (−) sign shows the presence of a gene on the positive and negative strand of that specific marker correspondingly. MW, molecular weight; PI, isoelectric points; bp, base pair; aa, amino acids.

FIGURE 1

Chromosomal mapping of AhAPX genes on A. hypogea genome. (A) Distribution map of AhAPX genes on 20 chromosomes, including one unassembled region. Representative chromosome numbers are shown on the left side of each bar. The scale on the left side represents the chromosomal distance and is in megabases (Mb). (B) Graph indicates the number of AhAPX genes mapped on each chromosome.

Comprehensive information of all predicted 166 AhAPX genes is presented in Table 1. In short, the CDS length varied from 327 bp (AhAPX71) to 1,923 bp (AhAPX25/45), and the amino acid length assorted from 108 (AhAPX71) to 640 (AhAPX25/45) amino acids. The number of exons varied from one (AhAPX43/50/61/117/131/134) to 16 (AhAPX45/145) (Table 1). Particularly, only two genes (AhAPX45 and AhAPX145) had the uppermost number of introns (i.e., 15), and quite a few genes lack introns (i.e., AhAPX43/50/61/117/131/134) (Table 1). The anticipated molecular weights (MW) of the 166 AhAPX proteins increased from 3.85 kDa (AhAPX79) to 70.66 kDa (AhAPX45), the isoelectric points (PI) extended from 4.41 (AhAPX83) to 9.76 (AhAPX51), and the GRAVY ranged from -0.639 (AhAPX145) to 0.392 (AhAPX161). The transformations in MW and PI are primarily due to the elevated content of necessary amino acids and post-translational alterations. The in silico subcellular localization discovered that 115 AhAPX proteins were situated on the extracellular matrix, 14 AhAPX proteins on plasma membrane, 12 AhAPX proteins on cytoplasm, nine AhAPX proteins on chloroplast, and five AhAPX proteins on mitochondrion (Table 1). Notably, some AhAPX proteins were found to be located in more than one location (Table 1).

On the other hand, eight genes (AtAPXs) from A. thaliana, 90 genes (AdAPX1-AdAPX90) from A. duranensis, and 102 genes (AiAPX1-AiAPX102) from A. ipaensis genomes were also recognized to study the evolution of APX genes between tetraploid and diploid parents (Supplementary Table 1).

Insights From Phylogenetic Relationships of APX Proteins

To determine the in-depth evolutionary and phylogenetic history between the AhAPX (166 members), AdAPX (90 members), AiAPX (102 members), and AtAPX proteins (8 members), an unrooted phylogenetic tree was built by a multiple sequence alignment, which was divided into 11 main groups (group1–group11) (Figure 2). The discoveries exposed that group1 comprised of seven APX members (2 AhAPX, 2 AiAPX, and 3 AdAPX) followed by group4/5 (eight APX members), and group3 (14 APX members). Notably, the maximum number of APX members (66 AhAPX, 39 AiAPX, and 33 AdAPX) were found in group 11 followed by group7 (38 APX members), group2/6 (37 APX members), group8/9 (28 APX members), and group10 (24 APX members) (Figure 2). All AtAPX members were clustered only in one group, i.e., group 2. In general, APXs grouped into the indistinguishable sub-group may retain corresponding functions. It is worth stating that A. hypogea APX (AhAPXs) were distributed in each group with homologs from A. duranensis, A. ipaensis, and A. thaliana., and group11 was detected to have more AhAPX members than the other 10 groups (Figure 2). Furthermore, it was observed that the AhAPXs showed a greater phylogenetic network with the AdAPXs and AiAPXs in each group.

FIGURE 2

An unrooted neighbor-joining phylogenetic tree of APX proteins from A. hypogea, A. duranensis, A. ipaensis, and A. thaliana. On the whole, 166 AhAPXs from A. hypogea (blue circles), 90 AdAPXs from A. duranensis (yellow circles), 102 AiAPXs from A. ipaensis (red circles), and 8 AtAPXs from Arabidopsis thaliana (green circles) were clustered into 11 groups based on sequence similarities, domain, and 1,000 bootstrap values. The percentage of bootstrap values is shown in the notes.

Insights Into Synteny and Collinearity of APX Genes

Gene duplications (i.e., tandem and segmental) are thought to be the main factors in supporting the expansion and evolution of new gene families in plants (Cannon et al., 2004). Hence, gene duplication procedures were assessed between AhAPXs, AdAPXs, AiAPXs, and AtAPXs (Supplementary Table 3). The results of gene duplication study showed that there were 92 AhAPX gene pairs, and these pairs were unevenly mapped on different chromosomes (Figure 3 and Supplementary Table 3). Mainly, chromosome 13 had a maximum number (i.e., 16) of AhAPX gene pairs, followed by chromosome 5 with 12 AhAPX gene pairs. The least number of gene pairs (i.e., two) was discovered on chromosome 12, and no gene pair was found on chromosome 2 (Figure 3 and Supplementary Table 3). The results reveal that segmental duplications have contributed to the expansion of AhAPX genes in the cultivated peanut genome (Supplementary Table 3). Notably, no tandem duplicated gene pairs were identified.

FIGURE 3

Chromosomal positions and inter-chromosomal groups of duplicated AhAPX gene pairs. Gray lines in the background demonstrate all syntenic blocks in the A. hypogea genome, and the blue lines exhibit the segmental or tandem duplication network zones among AhAPX genes. The near location of AhAPX genes is marked with black lines outside with chromosome names.

Similarly, 10 duplicated gene pairs were detected between AhAPX and AtAPX (Supplementary Figure 1 and Supplementary Table 3); 171 pairs between AhAPX and AiAPX (Supplementary Figure 2 and Supplementary Table 3); and 160 pairs between AhAPX and AdAPX (Supplementary Figure 3 and Supplementary Table 3). All these gene pairs were irregularly mapped on different chromosomes. Taken together, these conclusions explained that the duplication activities played a vital role in enlarging the APX genes between diploid and tetraploid parents. Further, it can also be concluded that A. hypogea might have lost some genes during genome evolution.

Collinearity analysis was carried out to review the evolutionary association of the APX genes between A. hypogea, A. duranensis, A. ipaensis, and A. thaliana (Figure 4 and Supplementary Table 3). The results discovered a strong orthologous of APX genes among these four species (Figure 4). On the whole, several A. hypogea genes presented syntenic networks with different AdAPX, AiAPX, and AtAPX genes. Particularly, only one gene (AhAPX14) at chromosome Ah2 exhibited a syntenic connection with AdAPX85 gene at chromosome Ad02 (Figure 4 and Supplementary Table 3), while other homologous genes present on other A. hypogea chromosomes also showed a syntenic relationship with many AdAPX, AiAPX and AtAPX genes (Figure 4 and Supplementary Table 3). These findings indicate that whole-genome or segmental duplication procedures are considered a main evolutionary force in the evolution of AhAPX genes in the peanut genome (Figure 4 and Supplementary Table 3).

FIGURE 4

Multiple collinearity analysis of APX genes between A. hypogea, A. duranensis, A. ipaensis, and A. thaliana chromosomes. Gray lines in the background specify the collinear blocks within A. hypogea and other three genomes, while the red lines highlight the syntenic APX orthologous gene pairs.

The Ka/Ks ratio is considered as a huge diagnostic marker in evaluating the sequence evolution in terms of selection pressures and duplication types (Hurst, 2002). Thus, to understand the evolutionary story of the AhAPX, the Ka, Ks, and Ka/Ks ratio was revealed (Supplementary Table 3). The dataset unveiled that all duplicated AhAPX gene pairs had a Ka/Ks ratio of <1 (Supplementary Table 3), demonstrating that the AhAPX genes may have experienced strong purifying selective pressure and segmental duplications throughout the evolution procedure (Supplementary Table 3).

Insights Into Gene Structures and Conserved Motifs of AhAPX Genes

The exon-intron arrangements and conserved motifs of the AhAPX genes were analyzed to get insights into the advancement of the APX family genes in peanut genome (Figure 5 and Supplementary Table 4). The outcomes revealed that the number of exons and introns varied from 16 to 1 and 0 to 15, respectively (Figure 5B and Supplementary Table 10). In short, 6 genes have 1 exon and zero intron; 13 genes have 2 exons and 1 intron; 5 genes have 3 exons and 2 introns; 18 genes have 2 exons and 1 intron; 41 genes have 3 exons and 2 introns; 81 genes have 4 exons and 3 introns; 3 genes have 5/7 exons and 4/6 introns; 5 genes have 9 exons and 8 introns; only 1 gene has 10 exons and 9 introns; 3 genes have 11/12 exons and 10/11 introns; and only 2 genes have a maximum number of exons (16) and introns (15) (Figure 5B and Supplementary Table 10). Above all, genes belonging to the same sub-tree almost had parallel structures apart from a few genes (Figure 5B). Among all genes, AhAPX149 possess the longest structure, and only a few genes have a complex structure, such as AhAPX17, AhAPX19, AhAPX34, AhAPX45, AhAPX55, AhAPX59, AhAPX64, AhAPX92, AhAPX101, AhAPX102, and AhAPX145 (Figure 5B). Exon loss or gain has been found during the evolution of APX family genes. The results recommended that APX genes held a somewhat frequent exon-intron composition throughout the evolution of peanut genome. Furthermore, AhAPX gene participants inside a sub-tree had exceptionally corresponding gene structures, steady with their phylogenetic clusters.

FIGURE 5

The gene structure and motif analysis of the AhAPX genes. (A) Arrangements of predicted conserved motifs in AhAPXs. Unique color boxes exhibit individual motifs. (B) The gene structure of the AhAPXs. Light green color indicates the UTR regions; yellow color shows the CDS regions, and gray horizontal line displays the introns.

The conserved motif of the AhAPX genes ranged from one (AhAPX55/140) to three (AhAPX2/71/117/131) (Figure 5A). In total, 10 conserved motifs were recognized, and their complete dataset, including motif names, sequences, width, and E-value, is given in Supplementary Table 4. Similar to gene structure, the motif distributions were also similar within the sub-trees (Figure 5A), while some motifs were found to be specific to some genes. For instance, some genes such as AhAPX2/17/101/34/59/137 were limited to motifs 2, 3, and 10. While AhAPX60 gene only contained motifs 3 and 10; AhAPX71 contained motifs 3, 8, and 9; AhAPX117 contained motifs 4, 6, and 10; AhAPX131 contained motifs 4, 9, and 10; and AhAPX71 contained motifs 3, 8, and 9 (Figure 5A). Almost all other motifs were present on all genes except in a few cases (Figure 5A). In summary, the consistency of gene organizations within sub-trees was credibly constant by appraising the conserved motif structures, gene structures, and phylogenetic relations, representing that the APX proteins have enormously well-sustained amino acid deposits and APX members belonging to the same tree may hold corresponding roles.

Cis-Elements: Key Players in the Promoter Regions of AhAPX Genes

To better understand the regulatory role of AhAPX genes toward peanut growth and development, and tolerance to abiotic stress and phytohormones treatment, cis-regulatory elements in the promoter of AhAPX were explored. The complete dataset of cis-elements is presented in Supplementary Table 5. We emphasized and recognized three categories of cis-elements, including abiotic stress-responsive, phytohormones responsive, and growth and development responsive elements (Figures 6, 7 and Supplementary Table 5). Mainly, six abiotic stress-responsive (drought, light, low temperature, wound, defense and stress, and anaerobic) elements were detected. These elements consist of I-box, ATCT-motif, Box 4, GT1-motif, GA-motif, etc. (light-responsive, 77%), ARE (13%), MBS (3%), TC-rich repeats (3%), LTR (3%), and WUN-motif (0.15%) (Figures 7A,B and Supplementary Table 5). Overall, results showed that most of the abiotic stress-related elements were predicted to be specific to some genes and unevenly distributed (Figure 6 and Supplementary Table 5), indicating their defensive role against stress conditions.

FIGURE 6

Analysis of cis-regulatory elements in the AhAPX promoter regions. Diverse cis-elements with functional resemblance are represented by similar colors.

FIGURE 7

Cis-regulatory elements in the AhAPX promoter regions. (A,C,E) The total number of AhAPX genes involved in abiotic stress, phytohormones, and growth and development categories of cis-elements. (B,D,F) The percentage (%) ratio of the several cis-elements from each category is shown in pie charts, i.e. (B) abiotic stress-responsive, (D) phytohormones responsive, and (F) plant growth and development responsive. Diverse colors signify different cis-acting elements and their ratio present in AhAPX genes.

Likewise, five phytohormone-responsive elements [methyl jasmonate (MeJA), abscisic acid, gibberellin, salicylic acid, and auxin] consist of CGTCA-motif/TGACG-motif (36%), ABRE (35%), P-box/TATC-box/GARE-motif (11%), TCA-element/SARE (11%), and AuxRR-core/TGA-element/TGA-box (7%) (Figures 7C,D and Supplementary Table 5). Some of the elements were found to be specific to some genes and unevenly distributed (Figure 6 and Supplementary Table 5). These outcomes suggest that element-specific genes could be considered as candidate players for further functional studies to reveal their protective role under hormone treatments.

Moreover, five growth and development-related (zein metabolism, meristem expression, endosperm expression, circadian control, and cell cycle regulation) elements were discovered. These key elements include O2-site (34%), CAT-box (31%), GCN4_motif/AACA_motif (17%), circadian (14%), and MSA-like (5%) (Figures 7E,F and Supplementary Table 5), suggesting their dynamic role in different growth and developmental stages of peanut. In a nutshell, these discoveries suggested that some of the key elements are widely and randomly distributed in some genes, while some of the elements are found to be specific to some genes. It can be concluded that the expression profiles of AhAPX genes may fluctuate under different developmental stages, phytohormone and abiotic stress conditions.

Genome-Wide Investigation of miRNAs Targeting AhAPX Genes

To better comprehend the miRNA-arbitrated post-transcriptional alteration of AhAPX genes, we identified 14 miRNAs targeting 33 genes (Figure 8A and Supplementary Table 6). These miRNAs belong to 12 different families. To give an overview, the miRNA-targeted sites of AhAPX29 and AhAPX147 are shown in Figures 8B,C, whereas the complete dataset of all miRNAs targeted sites/genes is provided in Supplementary Table 6. The results showed that ahy-miR159 and ahy-miR3513-3P targeted the most number (5) of genes. Three miRNAs, including ahy-miR3518, ahy-miR3520-3P, and ahy-miR3513-5P targeted four genes, followed by ahy-miR3520-5P that targeted three genes (AhAPX38, AhAPX127, and AhAPX118). While six miRNAs including ahy-miR3512, ahy-miR3510, ahy-miR167-3P, ahy-miR3514-5P, ahy-miR3509-3P, and ahy-miR3508 targeted two different genes individually. Notably, only two miRNAs (ahy-miR156b-5p and ahy-miR3516) targeted one gene, AhAPX155 and AhAPX128, respectively (Figure 8A and Supplementary Table 6). Some common genes like AhAPX29, AhAPX62, AhAPX115, AhAPX147, AhAPX74, and AhAPX98 are found to be targeted by more than one miRNA. Hence, the expression profiling of these predicted miRNAs and their targeted genes necessitates confirmation to oversee their biological roles in the cultivated peanut genome.

FIGURE 8

miRNA targeting AhAPX genes. (A) Network map of projected miRNA targeting AhAPX genes. The green boxes correspond to AhAPX genes, and various color shapes indicate predicted miRNAs. (B) The graphic illustration indicates the AhAPX29 gene is targeted by miRNAs (ahy-miR159 and ahy-miR3513-3p). (C) The graphic illustration shows the AhAPX147 gene is targeted by miRNAs (ahy-miR3518 and ahy-miR3513-3p). Black thick bar indicates the chromosomal location of gene. Blue thick bar indicates the location of miRNAs on gene sequence. The RNA sequence of each complementary site from 5′ to 3′ and the predicted miRNA sequence from 3′ to 5′ are shown in the green and red line boxes. The complete dataset of predicted miRNAs is shown in Supplementary Table 6.

Transcription Factor Regulatory Network of AhAPX Genes

To get further insights into the regulatory role of transcription factors (TFs) in regulating the transcription of AhAPX genes, we identified 3,257 TFs in 162 AhAPX genes (Figure 9 and Supplementary Table 7). The results showed that these TFs belong to 38 diverse TFs families, including AP2, ARF, B3, bHLH, bZIP, Dof, ERF, MYB, NAC, WRKY, HSF, GATA, etc. (Figure 9 and Supplementary Table 7). The amplest TFs families were Dof (742 members), ERF (698 members), MYB (545 members), BBR-BPC (344 members), NAC (308 members), WRKY (238 members), GATA (223 members), MIKC_MADS (210 members), C2H2 (177 members), bHLH/bZIP (163 members), B3 (157 members), AP2 (154 members), and HSF (102 members) (Figure 9B and Supplementary Table 7). However, the least ample TFs families were ARR-B/RAV/SRS (2 members), followed by GrBP (4 members), S1Fa-like (6 members), SBP (7 members), C3H (8 members), etc. (Figure 9B and Supplementary Table 7). In contrast, other TFs families contained less than 100 members. Nearly, all 162 AhAPX genes were anticipated to be targeted by various TFs belonging to diverse families. For instance, AhAPX150 gene was abundantly tarted by 314 TFs, followed by AhAPX56 by 172 TFs, AhAPX148 by 145 TFs, AhAPX55 by 107 TFs, AhAPX92 by 93 TFs, AhAPX45 by 96 TFs., etc. (Figure 9 and Supplementary Table 7). Some genes were nominally targeted, e.g., AhAPX5/79/99 by 1 TF, AhAPX83/90/93 by 2 TFs, AhAPX9/15 by 3 TFs, AhAPX7 by 4 TFs, AhAPX8/70/80 by 5 TFs., etc. (Figure 9 and Supplementary Table 7). Overall, these results showed that abiotic and phytohormone-related TFs could be engineered to develop improved peanut cultivars.

FIGURE 9

The regulatory network of putative transcription factors of AhAPX genes. (A) Circular network of transcription factors. AhAPX genes are shown around the circle. The small inner circles denote the transcription factors, and their color pink to yellow represents the degree of interaction. (B) Graph indicates the number of AhAPX genes and their representative putative transcription factor families. The complete dataset of putative transcription factors is shown in Supplementary Table 7.

Gene Ontology and Kyoto Encyclopedia of Genes and Genomics Enrichment Analysis of AhAPX Genes

To advance our knowledge about the dynamic roles of AhAPX genes at molecular level, GO and KEGG enrichment analysis were performed (Figure 10 and Supplementary Table 8). The GO annotation outcomes of biological process (BP), molecular function (MF), and cellular component (CC) classes presented quite a few substantially enriched terms (Figure 10A and Supplementary Table 8). For instance, in MF class, the highly enriched terms were cytochrome-c peroxidase activity (GO:0004130), oxidoreductase activity (GO:0016491), catalytic activity (GO:0003824), antioxidant activity (GO:0016209), and peroxidase activity (GO:0004601). In CC class, the most enriched terms were cell wall (GO:0005618), and cell junction (GO:0030054). Whereas in BP class, the highly enriched terms were cellular response to stimulus (GO:0051716), cellular detoxification (GO:1990748), response to chemical (GO:0042221), hydrogen peroxide catabolic process (GO:0042744), response to zinc ion (GO:0010043), modulation by symbiont of host defense response (GO:0052031), obsolete oxidation-reduction process (GO:0055114), detoxification (GO:0098754)., etc. (Figure 10A and Supplementary Table 8).

FIGURE 10

Gene ontology (GO) and KEGG enrichment analysis of AhAPX genes. (A) The highly enriched GO terms from MF, CC, BP classifications in AhAPX genes. (B) The highly enriched KEGG pathways in AhAPX genes.

Furthermore, KEGG pathway enrichment study discovered six pathways participating in diverse functions of AhAPX genes (Figure 10B and Supplementary Table 8). The highly enriched pathways include biosynthesis of other secondary metabolites (B09110), metabolism (A09100), phenylpropanoid biosynthesis (00940), followed by ascorbate and aldarate metabolism (00053), glutathione metabolism (00480), and metabolism of other amino acids (B09106) (Figure 10B and Supplementary Table 8). Briefly, it can be concluded that GO and KEGG enrichment study validates the functional contribution of AhAPX genes in several cellular, molecular, and biological processes, that are associated with antioxidant defense systems, ROS scavenging, response to stresses, and biosynthesis of different metabolites.

Expression Profiling of AhAPX Genes at Diverse Developmental Tissues

The expression profiling of 166 AhAPX genes was observed in various tissues and organs, including embryo, cotyledon, testa, pericarp, peg, root and stem, root nodule, root tip, root, step tip, stem, leaf, and flower using openly available transcriptome dataset (Supplementary Table 9). Overall, the expression heatmap indicated that only a few genes were highly expressed in certain organs/tissues (Figure 11 and Supplementary Table 9). For example, some genes including AhAPX4, AhAPX7, AhAPX17, AhAPX19, AhAPX28, AhAPX42, AhAPX51, AhAPX76, AhAPX77, AhAPX82, AhAPX86, AhAPX101, AhAPX102, AhAPX130, AhAPX133, and AhAPX160 were highly expressed in almost all the organs/tissues (Figure 11). While some genes were found to be specific to some tissues like AhAPX12 showed considerable expression in cotyledon, root and stem, root tip, and stem; AhAPX109, AhAPX111, and AhAPX13 expressed in stem, roots and peg; AhAPX135 expressed in pericarp; and AhAPX138 expressed in cotyledon (Figure 11). Particularly, a few genes also exhibited modest expressions in a variety of tissues. On the whole, expression dataset shows that some particular genes may substantially participate in peanut growth and development. Hence, the functional characterization of these genes may perhaps be carried out in future studies.

FIGURE 11

Expression profiling of AhAPX genes in various developmental tissues of peanut. In the expression bar, the red, white and blue colors show high to low expression levels. The circular heat map was designed by taking log2 of fragments per kilobase of transcript per million (FPKM) values.

Expression Profiling of AhAPX Genes Under Abiotic Stress and Hormones Treatments

To further study the contribution of all AhAPX genes toward abiotic and hormones stress tolerance in peanut, an openly available transcriptome dataset was used to evaluate the expression levels (Figure 12 and Supplementary Table 9). Similar to tissue-specific trend, only a few genes showed higher expressions in both cold and drought stresses. For instance, AhAPX4, AhAPX17, AhAPX19, AhAPX82, AhAPX101, and AhAPX102 were highly expressed under stress (cold and drought) and CK conditions. Likewise, some genes also showed moderate expression levels, such as AhAPX27, AhAPX34, AhAPX51, AhAPX55, AhAPX59, AhAPX113, AhAPX137, AhAPX138, AhAPX140, and AhAPX157 under stress (cold and drought) and normal conditions. On the other hand, AhAPX720, AhAPX21, AhAPX51, AhAPX77, AhAPX106, AhAPX130, AhAPX158, and AhAPX160 displayed considerable expression under cold stress compared to CK conditions (Figure 12A).

FIGURE 12

Expression profiling of AhAPX genes under different (A) abiotic stress, including cold and drought stress, and (B) phytohormone treatments such as abscisic acid, salicylic acid, ethylene, brassinolide, and paclobutrazol. In both maps, the label “CK” refers to the control plants in comparison to the stress-treated plants. In the expression bar, the red, white and blue colors show high to low expression levels. The circular heat map was designed by taking log2 of fragments per kilobase of transcript per million (FPKM) values.

Under phytohormones treatments, AhAPX4, AhAPX17, AhAPX55, AhAPX59, AhAPX82, AhAPX101, AhAPX102, AhAPX137, and AhAPX140 displayed significantly higher expression patterns throughout the treatments. In comparison to CK, some genes are specifically expressed under certain hormones, such as AhAPX21 under paclobutrazol, AhAPX27 under ethylene and abscisic acid, AhAPX51 under abscisic acid, and AhAPX88 under abscisic acid and paclobutrazol (Figure 12B). Notably, most of the genes did not show any expression under any type of stress conditions. The candidate genes with higher expression could be genetically engineered to improve the tolerance against multiple hormones and abiotic stress (cold and drought) conditions.

qRT-PCR-Based Expression Profiling of AhAPX Genes Under Cold and ABA Treatment

For qRT-PCR-based expression profiling, 10 highly upregulated AhAPX genes were selected based on transcriptome datasets to validate their transcript levels under ABA and cold treatment at various time points (Figure 13). Under ABA treatment, almost all genes demonstrated higher expression levels at all time points compared to CK, excluding a few cases. Such as, AhAPX55 and AhAPX140 showed relatively low expression at 9 and 12 h compared to CK and other time points (Figure 13A). In response to cold stress, although all the genes were upregulated; nevertheless, some genes showed relatively low expression levels compared to CK, such as AhAPX4, AhAPX19, AhAPX55, AhAPX82, AhAPX102, AhAPX137, and AhAPX140. Whereas AhAPX17 and AhAPX59 showed considerably higher expression than CK (Figure 13B). In short, all the preferred genes display parallel expression trends (i.e., upregulated) to those developed from transcriptome datasets (Supplementary Figure 4), therefore representing the reliability of the transcriptome datasets.

FIGURE 13

Expression profiling of the AhAPX genes under (A) abscisic acid and (B) cold stress treatments. The time points include 0 (CK), 3, 6, 9, and 12 h when the samples were picked for expression analysis after the stress treatment. Error bars signify the SD of three biological repeats (n = 3).

Discussion

Characterization and Evolution of APX Gene Family in Plants

Cultivated peanut is widely known as an essential oilseed, protein-enrich food crop worldwide and retains important breeding traits during domestication (Zhuang et al., 2019; Bohra et al., 2022). Even so, peanut production is still substantially influenced by numerous biotic and abiotic factors (Agarwal et al., 2018; Gangurde et al., 2020, 2021; Kumar et al., 2020; Shasidhar et al., 2020; Sinha et al., 2020; Jadhav et al., 2021; Pandey et al., 2021; Soni et al., 2021; Aravind et al., 2022; Bomireddy et al., 2022; Liu et al., 2022; Patel et al., 2022). When plants are exposed to diverse abiotic and biotic factors, APX enzyme as a primary marker can quickly eliminate unnecessary H2O2 (i.e., ROS scavenging) from plant cells by adjusting several physiological and biochemical activities to safeguard cells from the noxiousness of overproduction of ROS (Das and Roychoudhury, 2014; Mittler, 2017; Hasanuzzaman et al., 2020, 2021). During the past few years, excessive advancement has been achieved in studying the mode of action of APX genes; however, their vital role still requires more examination. Recent peanut genome sequencing data allow us to comprehensively discover new gene family members and recognize their functional and defensive mechanisms against stress conditions.

Usually, APX gene family of plants comprises a few genes. In this study, 166 AhAPX genes have been discovered in peanut genome (Supplementary Table 10), a larger APX family than previously reported APX gene families in watermelon (Malambane et al., 2018), shrub (Wang et al., 2022), rice (Teixeira et al., 2004), A. thaliana (Panchuk et al., 2002, Panchuk et al., 2005), sorghum (Akbudak et al., 2018), kiwifruit (Liao et al., 2020), tomato (Najami et al., 2008), wheat (Tyagi et al., 2020), and cotton (Tao et al., 2018). Deviations in the APX members amongst diverse plant species may perhaps be attributed to gene duplication events involving tandem and segmental repeats and play a role in expanding APXs for deviation. Repetition of APX genes was also discovered in several plant species (Teixeira et al., 2004; Panchuk et al., 2005; Akbudak et al., 2018; Liao et al., 2020; Wang et al., 2022). Our outcomes confirmed that AhAPXs had suffered segmental duplications (Supplementary Table 3). Subsequently, these reports recommended that AhAPXs duplicate cases may possibly play an essential role in gene evolution.

Previous studies showed that APX family genes are usually clustered into four major groups based on their subcellular localization or tree topologies (Pandey et al., 2011; Malambane et al., 2018; Tyagi et al., 2020). In the present study, all APX genes from four plant species were grouped into 11 main groups based on tree topologies and sequence similarities (Figure 2). This grouping was also recently supported by a new study on brassica crops (B. napus and B. rapa), where all APX genes were grouped into 13 subfamilies (Ma et al., 2021). Further, gene structure analysis also showed that genes belonging to the same subtree possess almost similar exon-intron patterns, ranging from 16 to 1 (exons) and 0 to 15 (introns) (Figure 5B and Supplementary Table 10). A significant difference was observed in gene structures where some genes have many exons-introns while some lack introns. Similar gene structure patterns were also reported in previous reports, such as in wheat number of exons extended from 7 to 12 (Tyagi et al., 2020). In Actinidia chinensis, the gene structure possesses 4–22 introns (Liao et al., 2020), which are higher than our observations. The exon-intron organization disparity was practiced by three important methods (exon/intron gain/loss, exonization/pseudoexonization, and insertion/deletion), and they are clearly supported by structural inconsistency (Xu et al., 2012). Notably, the AhAPX genes in each group almost exhibited comparable exon-intron group and conserved motifs (Figure 5), suggesting that these genes may possibly contribute to the similar tasks associated with several abiotic stressors. These outcomes are in agreement with earlier studies of kiwifruit (Liao et al., 2020), and wheat (Tyagi et al., 2020), where genes inside the same group comprise distinct structures and motifs organizations.

The Contribution of APX Genes Toward Stress Responses and Tolerance Mechanisms

To boost our understanding into the involvement of AhAPX genes contrary to numerous environmental factors, cis-elements were predicted in the promoter of AhAPX genes. The discoveries showed that three types of cis-elements were recognized, i.e., abiotic stress, phytohormones, and growth and development-related elements (Figures 6, 7). Recent studies show that the cis-elements in APX genes contribute to the plant abiotic and phytohormones stress responses. Similar types of abiotic and phytohormone-related cis-regulatory elements have been identified in previous studies (Akbudak et al., 2018; Malambane et al., 2018; Tao et al., 2018; Liao et al., 2020; Tyagi et al., 2020; Wang et al., 2022). Furthermore, AhAPXs gene functions were further predicted by GO enrichment analysis (Figure 10), which also supported the role of these genes in ROS scavenging and stress response mechanisms. To get further insights into the role of AhAPX genes, their expression levels were examined under various hormones and abiotic stress treatments (Figures 12, 13). Our results showed that a few genes significantly contribute to specific stress responses like cold, drought, and ABA. These results are in agreement with the previous reports of Akbudak et al. (2018), where some SbAPX genes were significantly induced by drought stress in the leaves and roots of two genotypes. Similarly, many genes showed higher expression levels in A. nanus under cold and osmotic stress (Wang et al., 2022). Many BrAPX and BnAPX genes showed higher expression trends in cold-tolerant varieties in response to cold stress (Ma et al., 2021). Under drought stress, most of the ClAPX genes were significantly upregulated and displayed elevated expression in watermelon (Malambane et al., 2018). These conclusions can enhance our perception of AhAPX genes under various stress conditions, especially cold and drought.

Recent reports also suggest that manipulating APX genes could contribute to stress tolerance in plants. For instance, a novel ScAPX6 gene from sugarcane was overexpressed in tobacco (Nicotiana benthamiana), and transgenic plants showed improved resistance to the biotic stress (Pseudomonas solanacearum and Fusarium solani) by positively regulating the phytohormones contents (Liu et al., 2018). The overexpression of PcAPX from Chinese white poplar (Populus tomentosa) improves tolerance to multiple stresses, including salinity, drought, and oxidative stress in transgenic tobacco plants by improving biochemical mechanisms (Cao et al., 2017). Likewise, the overexpression of Populus peroxisomal PpAPX gene enhances drought stress tolerance in transgenic tobacco plants (Li et al., 2009). Transgenic tobacco overexpressing cytosolic APX gene alleviated the drought stress tolerance (Faize et al., 2011). Ectopic overexpression of the peroxisomal SbpAPX gene improves salinity tolerance in transgenic peanut (Singh et al., 2014). So far, this is the only APX gene that has been functionally characterized in peanut. These studies recommend that the genetic engineering of APX genes is of great importance in conferring various stress tolerance in crop plants, including peanut.

Among various identified TFs, ERF TFs have been functionally characterized from peanut. The results exhibited that overexpression of AhERF008 impaired the root magnitude of A. thaliana; however, overexpression of AhERF019 improved tolerance to heat, salinity and drought stresses in A. thaliana (Wan et al., 2014). Ectopic overexpression of MYB repressor gene (GmMYB3a) increases drought tolerance and physiological mechanisms in transgenic peanut under drought stress (He et al., 2020). Another NAC TF gene (AhANC4) from peanut enhances drought tolerance in transgenic tobacco plants due to improved stomatal closure and advanced water use efficiency (Tang et al., 2017). A novel WRKY TF gene (AhWRKY75) improved salinity tolerance in transgenic peanut plants by improving antioxidant mechanisms, ROS scavenging, stomatal conductance, and photosynthesis under salinity stress (Zhu et al., 2021). All these studies suggest that the genetic engineering of TF is a promising approach to improve peanut performance under stressed conditions.

The Contribution of APX Genes in Numerous Organs/Tissues

Here, the tissue-specific expression profiling of 166 AhAPX genes was carried out in various organs/tissues using publically available transcriptome datasets. Overall, the results showed that only a few AhAPX genes showed higher expression levels, particularly in roots, stem, leaf, peg, pericarp, testa, and flowers (Figure 11). In A. nanus, the RNA-seq data was used to observe the expression levels in leaves. The results displayed that only one gene showed substantially higher expression in leaf (Wang et al., 2022). In wheat, most of the genes showed higher expression patterns in root, stem, leaf, spike, and grain. Especially, almost half of the APX genes were found to be leaf-specific due to significantly higher expression (Tyagi et al., 2020). In A. chinensis, qRT-PCR-based expression profiling of 13 AhAPX genes was performed in various fruit developmental stages. The outcomes demonstrated that eight AcAPX genes had the utmost expression patterns during the color turn-off phase (Liao et al., 2020). It can be concluded that the tissue-specific APX genes (such as AhAPX4, AhAPX17, AhAPX77, AhAPX82, AhAPX101, and AhAPX130) could be considered as target candidates for further molecular studies to fully reveal their role and mechanisms in peanut growth and development.

MicroRNA: Emerging Players for Crop Improvement and Stress Tolerance

MicroRNAs (miRNAs) are a group of tiny-non-coding RNAs formed from individual-strand hairpin RNA precursors. These miRNAs switch gene expression by attaching to corresponding sequences surrounded by target mRNAs (Jamla et al., 2021; Patil et al., 2021). Extensive progress has been put together in finding the targets of peanut miRNAs that contribute to various stresses and developmental activities (Zhao et al., 2010, 2015; Chi et al., 2011; Zhang et al., 2017; Chen H. et al., 2019; Figueredo et al., 2020; Tong et al., 2021). The present predicted 14 miRNAs belonging to 12 different families targeting 33 AhAPX genes (Figure 8 and Supplementary Table 6). Notably, none of the previous studies predicted the miRNAs that can target APX genes, expect one study. A recent study supports our findings where 51 miRNAs have been identified targeting 29 TaAPX genes in wheat (Tyagi et al., 2020). However, these target genes are yet to be characterized in wheat. In another study, a new miRNA (ath-miR447a-3p) was found to be targeting APX3 gene, and its expression analysis showed that it negatively regulated the expression of APX3, which is directly involved in the APX synthesis under drought stress in Zanthoxylum bungeanum (Fei et al., 2020).

However, some of the identified miRNAs have been reported to take part in stress tolerance and developmental processes. For instance, spatio-temporal expression patterns of miRNA159 family representatives have been found targeting MYB genes in grapevine (Vitis vinifera L.). The results showed that miRNA159c-VvGAMYB module is involved in gibberellin-tempted parthenocarpy in grapevine (Wang et al., 2018). Another study discovered that miR167A is the main member of miR167 family that regulates the A. thaliana reproduction. Further, miR167A acts as a parental gene that works mostly via ARF6 and ARF8 genes in maternal management of embryonic and seed growth (Yao et al., 2019). A member of miRNA156 family has been reported to be involved in the interaction between ABA and miRNA156, which regulates the expression profile of anthocyanin biogenesis genes in drought-stressed plants (González-Villagra et al., 2017). Notably, several miRNA families such as miR3513, miR3518, miR3520, miR3513, miR3516, etc., have not been functionally characterized; therefore, the future work could also be focused on these unique miRNAs to reveal their potential in plant growth and development. Moreover, the expression profiling of prophesied miRNAs and their targeted genes demands validation to direct their biological roles in the peanut breeding programs.

Conclusion

Altogether, we recognized 166 putative AhAPX genes in the cultivated peanut genome, which are mapped on all chromosomes, including unassembled ones. Comprehensive in silico examination of AhAPX genes, i.e., characterization, evolution, gene structure, conserved motifs, cis-elements, putative miRNA and TFs prediction, GO and KEGG enrichment were executed to increase our understanding of AhAPX genes in peanut. Their expression trends were also evaluated in various developmental organs/tissues, phytohormones, and abiotic stress conditions. In brief, this report set the foundation for further functional experiments (such as overexpression, gene editing via CRISPR/Cas system, etc.) of some candidate genes such as AhAPX4/17/19/55/59/82/101/102/137 and AhAPX140, which can advance the peanut breeding programs under undesirable stress conditions.

Data Availability Statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: NCBI BioProject–PRJNA480120.

Author Contributions

AR and WZ conceived the idea. AR analyzed the data and wrote the manuscript. YS and KC helped with qRT-PCR analysis. YS, KC, CZ, LW, HF, AC, and HC helped in literature search and data analysis. WZ and RKV supervised the research, and reviewed and improved the manuscript. All authors have read and approved the final version of the manuscript.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

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