Molecular technologies ending with ‘omics’: The driving force toward sustainable plant production and protection [version 1; peer review: awaiting peer review]

As the global population is surging, the agricultural industry is required to meet the food demand while simultaneously providing eco-friendly sustainable crops that can withstand numerous abiotic and biotic stresses. The current era requires high-throughput biotechnology approaches to alleviate the current plant production and protection crisis. Omics approaches are regarded as a collection of high throughput technologies ending with “omics” such as genomics, proteomics, transcriptomics, metabolomics, phenomics and epigenomics. Furthermore, omics provide the best tactic to increase high quality crop production yield. A body of evidence has shown that microbial diversity, abundance, composition, functional gene patterns, and metabolic pathways at the genome level could also assist in understanding the contributions of the microbial community towards plant growth and protection. In addition, the link between plant genomes and phenotypes under physiological and environmental settings is highlighted by the integration of functional genomics with other omics. However, application of single omics technologies results in one disciplinary solution while raising multiple questions without answers. To address these challenges, we need to find new age solutions. For instance, omics technologies focusing on plant production and protection. Multi-layered information gathered from systems biology provides a comprehensive understanding of molecular regulator networks for improving


Introduction
In this era, global population growth outstrips agricultural production which might lead to food insecurity, world hunger, poverty, and depopulation. The Food and Agriculture Organization of the United Nations 1 reported that in 2020, 811 million people globally experienced hunger which is an increase of up to 161 million people from 2019. 1 It was projected that the global population will surge by 25% by 2050, thus agricultural production will need to be increased by 49% in order to meet the food demand. 2 Food security incorporates nutritional quality as well quantity, which are essential requirements to meet an increasing global population and reduce hunger. However, food security is strongly inhibited by abiotic and biotic factors that negatively affect crop yield and production. 3 In addition, several challenges contribute to the global food security crisis with climate change at the forefront. 2,3 Climate change has worsened the situation with unstable rainfall patterns, extreme temperatures (high or low), salinity, pathogens and pest severity, distribution and resistance to pesticides. 4 According to the United Nations (UN), this is the "decade of action" whereby the 17 Sustainable Development Goals need to transform our world and be achieved by 2030 such as combating poverty. 5 How do we develop food systems that are resilient and sustainable, in order to feed the billions of people globally? This is the burning question that the scientific community are working on tirelessly. To address these challenges, high-throughput biotechnology approaches has become the focal point of many strategies to improve plant production and protection. Moreover, omics provide the best tactic which will aid an increased high-quality yield in crop production. 6 Omics is a multi-disciplinary science-based discipline that investigates the interaction of various organisms with their environment and such characterization is gathered from the genome profiles, transcriptomes, proteomes, metabolomes and a variety of other related "omes". A combination of omics technologies have proven to be valuable in agriculture, by exploring plant systems response pathways to various abiotic and biotic factors. 7 In addition, multiple omics approaches assist in the elucidation of complex gene functions under various physiological and environmental stress conditions. 8 The application of multipleomics approaches have proven to be successful in breaking down the components of stress response in various economically important crops. 9,10 Thus, a combination of omics technologies are needed to offer solutions to feed the growing population, through the development of high yielding transgenic crop varieties. 11 Application of these technologies would assist in understanding plants response pathways to different abiotic and biotic stresses. Recently various omics strategies have improved and brought transgenic crop varieties that have gained popularity due to their ability to possess various useful agronomic traits. 12 Combined omics approaches have proven to complement each other well in analysing complex biological processes. For instance, this was illustrated in halophytes through differential regulation of metabolites, proteins and ions in response to salinity stress. 13 For plants to survive both abiotic and biotic stresses they need to adjust their omics profiles accordingly. 8 Thus, it is important for a combination of omics techniques to be incorporated in plants response research studies to illuminate molecular pathways that actively control abiotic stresses and provide comprehensive information for biological system analysis. 14 This review summarizes the important multiple-omics approaches, their applications, bioinformatics tools and anticipated implementations in agriculture to improve crop yields, productivity and enhanced protection against abiotic and biotic stresses ( Figure 1).

Research methodology
The current review was articulated from high-quality specialized search engines such as Google Scholar, Scopus, ScienceDirect, and PubMed. A body of evidence was collected by screening and selecting the most current and definitive original publications using several keywords (agriculture, biotechnology, genomics, metabolomics, multi-omics, transcriptomics, proteomics) with the goal of narrowing the search to the most relevant studies. The search only looked for peer-reviewed, full-text articles in the English language.

Genomics
During the previous decades, the conceptualization, development, and utilization of genomic technologies provided a wealth of information that has yet to be discovered. 15 The power of first-generation sequencing technologies has revealed the helix to monitor and screen diseases as well as to discover the biosynthetic logic and genetic basis for the synthesis of novel bioactive metabolites in the healthcare and agricultural industries. 16 Combining genome mining with synthetic biology has been reported as progressive growth.

Innovative techniques used in plant genomics
Genomics is the study of recombinant DNA, DNA sequencing techniques, bioinformatics, examining the structure, function, evolution, mapping, epigenomic, mutagenomics of genes and genomes. 8 DNA sequences and annotations, among other genomic tools, are now deposited in publicly available databases. 17 The progressive improvement of computers and networks is required for the storing and handling of these resources. In natural and engineered strains, genomics enables high-throughput DNA sequencing and large-scale bimolecular modelling of metabolic and signalling networks. 18 In this era, genomic technologies have been applied to improvement of crop breeding, plant promotion and protection. A body of evidence has shown that bacteria and fungi co-exist with their host plants, thus promoting plant growth and protection. 19,20 Tremendous progress has been made in structural genomics indicating morphological and genetic maps to find features of interest.

Application based genomics and plant protection
Countless studies have expressed several genes related to stress tolerance, 21 nitrogen fixation, 22 for mineral acquisition (Fe, P, etc.), 23 phytohormone production (IAA, GA, etc.), adhesion, and other colonization related genes, 24 which are significantly important in microbial endophytes existence. The introduction of beneficial microorganisms to crops might lead to plant growth along with antagonistic activity against plant diseases. 25 It is worth noting, that the agriculture industries are becoming increasingly involved in finding more sustainable, greener, and environmentally friendly products, which aligns to the 17 Sustainable Development Goals (SDGs). In addition, this is also in response to the worldwide problem of pesticide exploitation and overuse. 26 Microbial products can be employed as biofertilizers, plant strengtheners, phyto-stimulators, and biopesticides, depending on their mode of action and effects. 27 Tremendous progress has been made in improving the scale-up and bioprocess development of microbial inoculants. The application of genomic technologies, particularly microbial inoculants, have massive benefits. 19 Genomics analysis Sequencing technologies has cemented a "gold standard" for the detection of both known and unknown variants in genomics. Depending on the intended downstream application, different strategies are utilized for each phase. Subsequently, nucleic acid-based sequences will go through cleaning, filtering, assembly, alignment, variant calling, annotation, and functional predictions. 27 Shotgun sequencing was one of the most popular techniques utilized with long strands of DNA as well as complete genomes. The conventional chain-termination approach, also known as the "Sanger method," which is based on the selective incorporation of chain-terminating dideoxynucleosides by DNA polymerase during in vitro DNA replication, was the technology behind shotgun sequencing for a significant portion of its history. In addition, Sanger sequencing is time consuming hence the use of high throughput technologies nowadays, e.g., next generation sequencing (NGS). High-throughput sequencing or microarray hybridization, as well as bioinformatics, are essential genomic analysis methods. 28

Limitations of genomics technologies
Despite the massive benefits, microbial inoculants are based on various modes of action, and their interactions are influenced by environmental factors. Another key concern is that microbial inoculants are intended for a wide range of crops globally, they thus might react differently in different species. 19 Moreover, to obtain an "ideal" inoculant, culturable microbial species require optimal growth conditions and in-depth understanding of plant/host relationships. 29 To address this, fermentation and formulation procedures need to be improved further. Government legislation remains an obstacle in safety aspects of commercialized microbial inoculants. 30 Moreover, microbial strains may also act differently in culture than they do in their native habitats. As a result, it is critical to create cultivation-independent methodologies for studying microbial communities. 31 Genomic technologies are taking a leap in the right direction by developing innovative biotechnology strategies in plant growth and protection. 19 Unfortunately, genomics technologies can only say whether genes are present or not. To address this, transcriptomics can determine when and where each gene is turned on or off. The RNA sequence mirrors the DNA sequence from which it was transcribed, ultimately gene expression is the logical followup in research advancements. To gain insight into plant breeding, biotechnological and genetic engineering, a multidisciplinary approach linking structural, functional, mutational and comparative genomics is required ( Figure 2).

Transcriptomics
Transcriptomics is basically a collection of RNA single-stranded nucleic acid copies encoded by the genome under stressful physiological environments in a specific cell type/tissue. 32,33 Furthermore, transcriptomics measure gene expression at the RNA level and in most cases, it will measure either messenger RNA (mRNA), transfer RNA (tRNA), ribosomal RNA (rRNA), or even non-coding RNA (ncRNA). 34 Such innovative technological approaches provide researchers with an advance tool to investigate the microbial populations related to various plants. Gene expression studies provide a magnification into gene structure and function, subsequently expanding on the understanding of biochemical pathways engaged in biological processes. 35 A number of studies have reported that the transcriptomics tool provides an innovative approach to improving our knowledge of biology and disease. 36,37 In a general sense, transcriptomics is considered as the next step in innovation and it aligns with all the criteria for a true "omics technology". Despite the impressive breadth of the data collected, challenges such as analysis remain an issue. The creation of appropriate expression measures for expression level comparisons and strategies for identifying differentially expressed genes are two of the most pressing issues (and exons). 38

Innovative techniques used in plant transcriptomics
Compounds have an impact on gene expression, which might provide insight into their functional and toxicological features. Expression investigations on disease and disease-free clinical samples may lead to the discovery of new biomarkers. Importantly, gene expression analysis can also be utilized to learn more about the physiological effects of plant genetic manipulation. 39 Outdated techniques such as Northern blotting, serial analysis of gene expression have massive drawbacks that make them inappropriate for analysing significant numbers of expression products at the same time. The development of DNA microarray technology has recently resulted in a significant increase in the sensitivity and throughput of expression screening. 40 Despite a number of technological and methodological challenges, microarray research has resulted in major improvements in our understanding of biological processes. It can be a low-cost method of identifying the most likely interesting subsets of samples that will produce results in other technological tools. 16 Highthroughput technologies have overtaken the omics world and transcriptomics is no exception with the introduction of whole-genome and next-generation transcriptome. Hence, transcriptome profiling is easily accomplished as a result of use of deep-sequencing technology.

Application based transcriptomics on plant protection
Microarrays have now been surpassed as the preferred approach for gene expression profiling by RNA-seq. Furthermore, it also allows for much more exact determination of transcript amounts and isoforms than other approaches. In a recent study conducted by Ahmad and co-workers, 41 based on RNA sequencing, the molecular basis of Brassica rapa plant resistance to Hyaloperonospora brassicae (a fungus-like pathogen) was determined. The elevation of PR genes resulted in a physiological response. The loci Bra003774 and Bra025730 in the PR gene family showed a two-fold increase in expression, indicating that WRKY22 and PR1 are overexpressed. PR1 was identified as a delayed response factor to the assaulting pathogen due to its end location in defence responses. PR1, zinc finger protein metabolism was the second most strongly active activity in Brassica cells, with 42% of genes showing increased expression. The plant's transcriptome profile was identified in order to better understand how the host reacts to the pathogenic onslaught and ensure its survival. The authors suggested that the study will be extremely beneficial to global plant protection efforts. 41 In another study, heavy metal particularly cadmium (Cd) tolerance was determined by using transcriptomic profiling in the Calotropis gigantea plant. To deal with Cd, the leaves triggered a number of Cd detoxification pathways, including overexpression of genes involved in Cd transport such as absorption, efflux and enzyme activation. The phytoremediation capacity of C. gigantea in Cd-contaminated soils was investigated using Cd tolerance parameters and molecular mechanisms. 42 RNA-sequencing was used to exam the reactions of two varieties inoculated with Alternaria alternata, a resistant type and a susceptible type. A total of 2235 differentially expressed genes (DEGs) in diseaseresistant cultivars and 4958 in susceptible cultivars were examined. Furthermore, the expression of DEGs as a defensive response, detection of resistance genes and signal transduction pathways, which will aid in the exploration of resistance mechanisms in response to A. alternata infection, were determined. 43 Transcriptomic research has aided in the identification of key functional genes and pathways that may show memory behaviour. Moreover, studies have also been useful in elucidating the function of memory processes in the modulation of ABA-related gene expression in response to drought. 44 Transcriptomics bioinformatics analysis RNA-Seq, the NGS based technology, has become the main choice to measure gene expression levels and comparing gene expression patterns at unprecedented resolution. Transcriptomics identifies the genes expressed in response to biotic and abiotic stress. A basic reference-based RNA-Seq data analysis pipeline includes pre-processing (removing lowquality sequences to improve alignment), alignment of raw reads with the reference genome, transcript assembly, and detection of differentially expressed genes. 45 The new tuxedo suite has been developed because it requires less memory amongst other advantages. It includes three tools for transcript-level analysis of RNA-Seq data, including HISAT2 for spliced alignment of reads to the genome, assembly of transcripts based on mapping to the genome, including novel transcripts, and quantification of these transcripts. 46 The final step for the new tuxedo suite is to identify differentially expressed genes and transcripts using Ballgown. 47 Pathway approaches analyze databases and gene expression data to identify the significantly impacted pathways in a given condition. 48 Limitations of transcriptomics technologies Despite the potential benefits, there has been records of noticeable downfalls of using transcriptomics. Transcriptomics is not suitable for recognizing adaptive stress response genes. This is due to the massive change in gene expression which may not always translate into a large influence on fitness, enormous gene effects are uncommon, protein activity is most relevant to fitness, and mRNA abundance is an inconsistent predictor of protein activity. It can be computationally difficult to annotate sequences accurately and interpret data, especially when there is no reference genome available. 49 Furthermore, biases established during the creation of the cDNA library and sequence alignment can have an impact on the quantification of transcripts. Reproducibility can be hampered by differences in read depth between sequencing platforms. Although RNA-seq has become more economical, many laboratories still cannot afford it. A key component in transcriptomics is that the start-up expenses are high, as well as the cost of each sequencing reaction, which depends on the read depth. 50 However, the benefits outweigh the shortfalls, especially when advanced multi-omics is applied. Our better understanding provides new knowledge regarding the relationship between gene expression and fitness in demanding environmental settings.

Proteomics
Proteomics is the study of the total number of proteins expressed in an organism and is divided into several categories, including sequence, structural, functional, and expression proteomics. 51 When compared to genomics and transcriptomics with post-transcriptional modifications, this technique is more advanced and reliable; it provides a better understanding of functional molecules (proteins) that carry out various cellular processes (functions), and it can be easily integrated with other omics approaches to elucidate complex plant stress responses. 52 There are numerous proteome approaches, and new ones are emerging to address or improve target protein isolation, resolution, chemical and physical properties, and functions.
Among these, sequence proteomics is concerned with identifying amino acid sequences and characterizing them using high performance liquid chromatography (HPLC). 53 Then structural proteomics involves the mapping out of the structure of protein complexes or proteins present in a specific cellular organelle in order to understand their inferred function. 54 Thirdly, functional proteomics investigates protein functions using a variety of techniques such as yeast-one or two hybrids and protein microarray profiling. 55 Lastly, expression proteomics investigates the quantitative and qualitative expression of proteins using a variety of methods, including separation of proteins on 1-DE sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) based on their molecular mass, and 2-DE based on their net charge in the first dimension and molecular mass in the second dimension. 54 Innovative techniques used in plant proteomics Plant proteomics research has advanced and brought improvements in protein extraction and separation to larger scales, moreover becoming a complement technique to transcriptomics and metabolomics. 56 Though proteomics could be a powerful approach it requires a series of steps from protein separation and identification to protein functional analysis and bioinformatics inferences involved in crop stress response. 57 As opposed to the old conventional proteomics techniques that were mostly chromatography based, recent techniques including SDS-PAGE, 2-DE, and two-dimensional differential gel electrophoresis (2D-DIGE) were developed and are gel based. 33 On the same level, protein microarrays/chips utilize minimal sample for protein expression analysis. Additionally, advanced isotope labelling has played a very important role in quantitative proteomic analysis especially in crop improvement studies of abiotic stress adaptation. 33 For key molecular weights identification MALDI-TOF, electrospray ionization (ESI), and collision-induced dissociation (CID) are utilized. 58 Plant proteome bioinformatic tools Several bioinformatics tools and databases have been developed for various applications including genomics analysis, transcriptomics, proteomics and metabolomics, while a comprehensive list of each approach has been provided separately. 59 Proteomics studies generates a large data set using various analytical techniques that are spectrometry or gel based, however such analyses are mainly dependent on several bioinformatic software tools that process, interpret, mine, assess and annotate functions. A bioinformatic tool used for data interpretation obtained from 2-DE gels include the SWISS-2DPAGE. Moreover, multiple databases exist that provide evolutionary and functional annotations of orthologs, predict protein's subcellular locations such include OrthoDB, OMA orthology, UnitprotKB, WoLF PSORT. 60 Various studies have been carried out on the identification of subcellular locations of various proteins to gain guidance for further experimental investigations. 61,62 Gene Ontology (GO) term identification provides terminology for biological processes and group associated genes according to various functional terms that describe the "biological process", "molecular function" or "cellular component". 63 For larger data sets and systematic approaches, tools such as MaxQuant, Proteome Discoverer 64 and X!tandem are used for proteomic annotations. 65 Furthermore, several bioinformatics databases exist that provide proteomics analysis as indicated in Table 1.

Application based proteomics in plant protection
Functional proteomics has identified different biochemical components such as reactive oxygen species (ROS) including such as quinone reductase, g-glutamylcysteine synthetase, dehydrins, and dehydroascorbate reductase reported in tomato and sunflower crops. 73 Important chaperones, such as heat shock proteins, have been identified during proteome functional analyses in wheat and sugarcane. 74 Quantitative proteomic studies have also been shown to play a crucial role in various crop responses against abiotic stresses. For example, the use of the iTRAQ method in differential expression of proteins in potato and in two coconut varieties under abiotic stress. 75,76 Furthermore, iTRAQ combined with the LC-MS/MS technique has proven to be an effective method widely used for fast identification and quantification of complex protein mixtures in abiotic and biotic stress responses in plants. 77 A combination of numerous proteomics approaches including MALDI-TOF, SDS-PAGE, MS, 2-DE, and PMF have been utilized to study response to diverse abiotic stresses in various crops such as rapeseed, soybean, wheat, sugarcane, and cotton. 74,78 Limitations of proteomics analysis There are various limitations that exist in proteomics analysis that normally originate from the initial stage that includes preparation and extraction of samples especially in recalcitrant crops with high content of polyphenols, 79 lack of a detailed number of proteins observed and inadequate tools in proteomic data analysis. Furthermore, challenges in peptide separation is a major inhibiting factor to downstream analysis, mass spectrometry-based analysis and bioinformatics tools. 80 Another limitation includes lack of a one-step quantification approach that can fully integrate a multi-functional system allowing comprehensive quantification of a wide spectrum of proteins from model and non-model plants. 81

Metabolomics
Metabolomics deals with the identification and quantification of all metabolites which participate in different cellular events of an organism at a particular time. 82 In plant systems metabolites are synthesized through various metabolic pathways. 83 In contrast to other omics studies, metabolomic profiling depends on an organism's cellular location, organ type, tissue and cell types, and the environmental stimuli it's exposed to or any stress factor. 84 Metabolites are divided into two classes, the primary (central) and secondary (specialized) metabolites. The initial class (primary) deals with small molecules used for cell viability, while secondary metabolites are essential for the viability of an organism mainly involved in defence mechanisms. 84 Innovative plant metabolomics techniques Several analytical techniques are used to generate metabolic profiles of a given plant sample, including thin layer chromatography (TLC), gas/liquid chromatography-mass spectrometry (GC/LC-MS), liquid chromatographyelectrochemistry-mass spectrometry (LCEC-MS), nuclear magnetic resonance (NMR), direct infusion mass spectrometry (DIMS), Fourier-transfer infrared (FT-IR), and capillary electrophoresis. 82,85 These methods depend on the approach's sensitivity, selectivity, speed, and accuracy. The methods CE-MS, GC-MS, LC-MS, and NMR are typically employed to profile metabolites from various plant materials. 86 Nuclear magnetic resonance is considered to be fast and selective with respect to metabolite profiling as opposed to mass spectrometry-based approaches. 84 However, a combination of NMR (semi-quantitative) and MS (quantitative) is advisable since it offers a better understanding of metabolome quantification due to the complementarity of these two approaches. 18 Metabolomics, combined with other omics approaches such as genomics, transcriptomics, and proteomics serve as a powerful approach that offer solid insights on molecular response pathways, plant biochemical and physiological mechanisms; and their related functions, 87 thus ultimately result in its relevance in food security.
Plant metabolomic data processing and bioinformatics software tools Several plant metabolomic bioinformatic tools are used to analyse metabolic raw data generated by various analytical tools for data processing, mining, annotation, interpretation and statistical analysis. 88 Different web-based programs are used for data pre-processing of metabolites those includes XCMS, METLIN, AMDIS, MeltDB, MetaboAnalys, MetAlign, MZmine 2, and AnalyzerPro for varying analytical techniques. XCMS is a web-based program that assists the user with data processing and statistical analysis, 89 while METLIN is mainly used for metabolite annotation. 90 MeltDB tool is used for data assessment, processing, and statistical analysis. 91 Lastly, AMDIS, KNApSAcK and KOMICS are mainly used for data processing and metabolites present in crop species. 92  93 Rice cultivars demonstrated identification of several metabolites using GC-MS against a pathogen gall midge biotype 1 (GMB1). 94 Several metabolite analyses were reported in wheat, maize, tomato, and soybean crops in response to drought, cold and heat stress. 95,96 Therefore, metabolomics offers a significant advantage compared to its counteromics approaches such as transcriptomics and proteomics, in that it reveals the downstream products synthesized by genes and expressed by proteins. 83 However, to comprehensively classify metabolites according to their various chemical/physical properties relevant preparation methods and instrumentation need to be utilized for enhancing metabolite performance. 97

Limitations of metabolomics analysis
There are several disadvantages that impede the full characterization of metabolites from a given organism, including the complex physicochemical properties that cannot be characterized by single or limited analytical techniques, hence combined multiple analysis tools are recommended for a full metabolome analysis. 82 Another limitation in creating metabolomics profiles is the consistency of growth conditions and preparation of plant samples due to the instability of metabolites undergoing multiple modifications such as hydrolysis or oxidation. Improper harvesting, handling, extract preparation, and sample storage are the most likely sources of instability in plant metabolite analysis. 98 In addition, simple metabolomics analysis requires the use of expensive equipment compared to genetic analysis, hence there are still limited data on these studies. Metabolomic analysis in plant pathology is challenging as it cannot distinguish between plant and microbial metabolites resulting from the interaction between (host and pathogen) plants and microbes as a metabolic response pathway. 99 Limited universal metabolite-specific standards and reference compounds to assist in identifying metabolomes. 100

Metagenomics
Microorganisms that are effective, play a crucial role in the management of biotic and abiotic stress, reduce the use of chemical fertilizers and increase the plant's yield by influencing elemental cycling. 101,102 Additionally, studying plant pathogens is an effective means for screening the presence of potentially agriculturally important pathogens. 103 Substantial understanding of the microbial community structure, annotation of functional genes, as well as metabolic pathways could aid in better understanding the benefits towards plant growth and protection. 104

Innovative techniques used in plant metagenomics
The introduction of high-throughput sequencing (HTS) has revolutionized the field of microbial ecology. 105 Previously, identification of bacteria and fungi was largely done using culture dependent techniques, which are inefficient as some microorganisms cannot be cultured on artificial media. Traditional methods for detecting viruses, such as polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) (PCR), typically target a few viral species and require prior virus knowledge to detect. 106 HTS sequencing allows for the study of microbes by sequencing the genetic material directly on the environment, 107 avoiding the need for culturing, termed metagenomics. 108

Marker sequencing metagenomic technique
The most exhausted high-throughput sequencing application in microbial ecology is target-gene amplicon sequencing. The 16S rRNA gene is found in all bacteria and has either high or low sequence variability. 109 This gene contains nine hypervariable regions (V1-V9) that show significant sequence diversity among bacteria. 110 Although no single hypervariable region can distinguish between all bacteria, regions V2, V3, and V6 have the greatest discriminating power and contain the most information in plants. However, Kembel et al. 111 argued that the 16S rRNA marker may be inconvenient due to variable copy numbers, with some taxa having up to 15 copies of this gene. As a result, there may be taxa overrepresentation in the final set of sequences, resulting in biased community structure estimations. Nevertheless, the benefits of using 16S rRNA gene markers outweigh the inconvenience, which is why amplicon sequencing is widely used in surveys.
The internal transcribed spacer (ITS) of fungi is a non-coding region that is highly polymorphic and contains the taxa that can separate sequences into species. 112 It is found in the ribosomal RNA operon and ranges in length from 450 to 750 bp. 113 The benefit of using ITS for-DNA barcoding is that it has been used in numerous studies and has updated reference sequences in the NCBI database. 114 ITS1, ITS2, ITS3, and ITS4 are the most used oligonucleotides for sequence-based fungal classification at the species level. 115 Therefore, amplicon sequencing forms the basis in characterizing bacteria and fungi and is an ideal tool to begin studying the microbiome as it is reasonably inexpensive.

Shotgun metagenomic sequencing technique
Shotgun metagenomics has transformed microbiome detection and discovery by enabling untargeted characterisation of entire microbiomes. It has revolutionised plant science by enabling the untargeted, simultaneous detection of multiple viruses, bacteria, archaea and fungi regardless of their genomic nature and can deliver species level identification. 116 This includes annotations for metabolic and functional processes. Shotgun-based approaches typically generate large, sequenced data. 117 However, their ability to accurately group DNA sequences or assembled sequence contigs into single-species genomes has remained limited. 118 Recently a powerful approach has been introduced for metagenomic analysis that can address the challenges with shotgun. 119 Hi-C is a technology that provides direct and quantitative measurements of DNA sequences from shotgun sequencing. 120 This technology yields higher numbers of high-quality genomes and captures strain-resolution insights. Hi-C eliminates the need for guesswork in metagenomic studies as direct evidence sequences. 121 The technique allows for accurate attribution of plasmids, phages, antibiotic resistance genes and other mobile genetic elements to host cells. 120 Bioinformatic analysis: Amplicon sequencing data analysis Bioinformatic analysis of plant microbiomes demands the use of pipelines that effectively analyze the high throughput data generated by shotgun and target sequencing for microbial profiling and gene annotations. Several pipelines for analysing 16S rRNA gene sequencing data are available, including Quantitative Insights into Microbial Ecology (QIIME2), 122 MOTHUR, and Metagenomics -Rapid Annotation using Subsystems Technology (MG-RAST). 123 CLC Genomics workbench 124 and MEGAN. 125 The comparison between the diversity and taxonomic compositions generated by MG-RAST and QIIME using samples was investigated. 126 The study concluded that QIIME2 produced compositional assignments that are more accurate. Similarly, Plummer 127 found that QIIME2 performance outweighed other platforms. Analysis with the platforms cluster similar sequences into operational taxonomic units (OTUs) or amplicon sequence variants (ASVs) and assign them to a taxonomic reference database, such as GTDB, the most updated bacterial database. 128 Bioinformatic analysis: Shotgun data analysis Essentially the data analysis of metagenome shotgun involves assembly, which includes joining reads into contig sequences that are larger. Newbler, AMOS, MIRA methods were used in assembling metagenomes at an early stage of metagenomics. 129 However, due to the low coverage and complexity of metagenomic reads, de novo assemblers, beginning with SOAPdenovo, were preferred for reference mapping. Genovo, 130 Meta-IDBA, 131 MetaVelvet, 132 MAP, 133 and Ray Meta are among the improved assemblers now available. 134 Following assembly, microbial communities are binned and taxonomically characterized. Functional annotations mainly use BLASTX search against several databases, including SEED, KEGG, EggNOG and COG. 57 Further graphical and statistical analysis is carried out using R software in conjunction with RStudio software and various microbiome-related R-packages. 135 Application based metagenomics on plant protection Metagenomics has been widely applied on different agriculturally important plants and on different microenvironments including the root and leaves. This has also been conducted in response to both abiotic and biotic stresses. For instance, Xu and colleagues 136 revealed the role of iron metabolism in drought-induced rhizosphere microbiome dynamics using metagenomic tools. Similarly, patterns in the microbial community and the functional genes associated with salt-tolerant plants and root associated microbiomes of potato grown in Alfisols have been conducted in response to abiotic stress. [137][138][139] Metagenomics studies in response to different bacterial, fungal, and viral diseases have also been conducted in pear fruits, citrus, grapes, tomato, and bananas. [138][139][140][141][142] Limitations of metagenomics Plant chloroplast and mitochondrial genomes, as well as bacterial 16S rRNA sequences, are similar, making bacterial rRNA gene amplification and sequencing challenging. As a result, the majority of the sequence data is from plant sequences, which are irrelevant to the study. Zarraonaindia et al. 141 showed that chloroplast sequences were the most problematic for Vitis vinefera, accounting for up to 98 percent of the total, as opposed to the mitochondrial sequences. It has been proposed that universal peptide nucleic acid (PNA) clamps can obstruct the host plant derived mitochondrial (mPNA) and plastid (pPNA) sequences at the V4 16S rRNA locus. 143 However, universal PNA efficacy was tested on Arabidopsis thaliana and the sorghum plant and was discovered to be effective in preventing the amplification of nontargeted sequences. 38,144 Additionally, another primer set has also shown to reduce non-targeted plant DNA amplification when performing metagenomic research on microbial endophyte communities. 10 The current study has highlighted some shortfalls of using a single omics approach and Table 2 provides a multidisciplinary approach by supplementing some limitations with other omics approaches, hence providing a multi-layered information system.

Concluding remarks
A growing body of evidence has cautioned that food safety will be progressively compromised in future due to over population, thus becoming a massive global health and economic crisis. To sustain an ever-growing population, biotechnological based approaches such as "omics" technologies should be implemented as valuable tools for plant production and protection. Omics technologies are a collection of innovative tools such as genomics, proteomics, metabolomics, next-generation sequencing, whole genome sequencing and transcriptomics. Furthermore, they are the  140,141 key ingredients in the next ground-breaking biotechnology-based products in the agricultural industry. Introduction of other "omics" technologies in relation to genomics as a multi-disciplinary approach have sparked interest in the research community. Most researchers are in agreement with the multi-disciplinary approach of "omics" technologies in order to leverage the benefits and omit the drawbacks. In light of this, the ever-increasing developments in omics technologies provide new opportunities in addressing fundamental issues in food safety, plant production and protection. Thus, opening the door towards eco-friendly sustainable plant production as well as agricultural industry.

Author contributions
All authors (Tshegofatso B. Dikobe, Kedibone Masenya and Madira C. Manganyi) have conceptualized, written, reviewed and edited the manuscript. The final manuscript version has been read and agreed upon by all authors.

Data availability
No data are associated with this article.