Presently, QTL-seq is one of the most successful approach developed for the gene discovery and trait dissection (Kumar et al., 2020; Pandey et al., 2020). This approach offers preliminary idea for positional cloning for linked genetic factors or genes, and it has excellent success in marker-assisted selection for crop improvement programs (Xu F. et al., 2015). With the advancements in NGS technologies new approaches like quantitative trait locus sequencing (QTL-seq) has been utilized for exploring rapid QTL or gene identification (Takagi et al., 2013). In QTL-seq approach, the extreme highest and lowest genotypes are selected from the mapping population for target traits, followed by mixing an equal amount of DNA from each bulk to build up two extreme bulk (High bulk and low bulk). Then, each bulk is sequenced and assembled and gene annotation is performed. This approach combined with Bulked segregant analysis, accompanied by whole genome re-sequencing technologies, is more effective and capable than the previous QTL detection methods (Takagi et al., 2013). Utilizing QTL-seq approach several QTLs and genes for different rice phenotypes (Takagi et al., 2013; Daware et al., 2016; Ogiso-Tanaka et al., 2017; Yang et al., 2017; Kadambari et al., 2018; Qin et al., 2018; Bommisetty et al., 2020; Nubankoh et al., 2020), soybean (Song et al., 2017; Zhang X. et al., 2018), chickpea (Singh et al., 2016; Deokar et al., 2019), tomato (Illa-Berenguer et al., 2015), groundnut (Kumar et al., 2020; Luo et al., 2019; Zhao et al., 2020), have been effectively identified. This approach has also been deployed across in several crops due to its inherent ability to understand both qualitative and quantitative traits (Table 2). For instance, Kumar et al. (2020) identified the role of two genes RING-H2 finger protein and zeaxanthin epoxidase in fresh seed dormancy in groundnut; both genes are known to control abscisic acid (ABA) accumulation. Very recently, Ramos et al. (2020) identified three QTLs (genomic regions) viz QtlPC-C04, QtlPC-C11 and QtlPC-C14 (linked to genes R1R2R3) associated with resistance to Phytophthora capsici Leonian which causes crown rot in squash (Cucurbita moschata). The most significant benefit of whole genome sequencing is that it allows the identification of causative mutations in target chromosomal regions. Additionally, this method identifies molecular markers which are located inside the harboring chromosomal region that can also be used to narrow down the genomic region which will help in mining the trait linked genes.

Advances in RNA sequencing (RNA-seq) technologies and approaches have made significant impact toward trait discovery, and have enabled plant developmental studies characterizing expression patterns of all the functional genes as well as regulatory RNAs (Nayak et al., 2019). RNA-seq is a more robust approach for precise measurement of transcripts and has been widely used for transcript profiling in several plant species (Cloonan et al., 2008; Wang et al., 2009). This data is vital for improving genome annotations, and offers precise gene position information for functional characterization and genome editing. The RNA-seq approach has been deployed for molecular characterization of several important agronomic traits such as seed size (Wan et al., 2017), seed coat color (Wan et al., 2018), seed coat cracking (Wan et al., 2016), seed and bud dormancy (Qi et al., 2015; Zhu et al., 2015; Khalil-Ur-Rehman et al., 2017), fatty acid biosynthesis and oil quality (Nayak et al., 2019), nutritional quality traits (Reddy and Ulaganathan, 2015), etc., which can offer precise gene information for developing designer crops for future. Also, RNA-seq have been used to understand the molecular mechanisms associated with salt tolerance in rice (Zhou et al., 2016; Lei et al., 2020); Chinese rye grass (Sun et al., 2013), and maize (Liang and Schnable, 2016). In wheat, RNA-seq study reported the drought responsive molecular pathways along with key candidate genes and molecular markers in the root tissue (Iquebal et al., 2019). RNA-seq has also been shown to be highly useful in combination with other -omics methods for gene discovery and pathway investigations.

Knowledge of proteomics is being used to map the translated genes and loci controlling the expression of respective genes. It helps in identification of proteins responsible for bringing intricate phenotypic variations. High throughput proteomics has gone beyond the identification of individual proteins, to quantitative profiling, post translational modification studies, signaling, protein–protein interaction and many more areas. Photosynthesis plays major role in biomass production and yield. Change in protein profile studies was performed in chlorophyll deficient Brassica napus leaves which established the relationship between chlorophyll biosynthesis and photosynthesis (Chu et al., 2015). Xylem sap proteomics has revealed several insights related to cell wall formation (Zhang M. et al., 2014), leaf senescence (Wang et al., 2012) biotic and abiotic stress response (Alvarez et al., 2008; González et al., 2012), cell to cell communication (Agrawal et al., 2010), and root–shoot communication (Krishnan et al., 2011). The enhanced level of redox proteins, stress and defense related proteins, calcium ion regulation proteins, signaling G-protein and RNA metabolism related proteins were induced in phloem sap study. Recently, proteomics study revealed that low light stress obstructs carbon fixation and OsGAPB overexpression augment tolerance to low light stress conceivably by increasing CO₂ assimilation and chlorophyll accumulation in rice (Liu et al., 2020). Interestingly, simultaneous upregulation of both biotic and abiotic stress responsive protein has been observed during bacterial blight infection in rice, which indicate the activation of common pathway (Kumar et al., 2015). Whereas in case of rice-M. oryzae interaction PBZ1, OsPR-10, SalT, Glu1, Glu2, and TLP proteins were up-regulated (Kim et al., 2004). iTRAQ proteomics study of Oryza officinalis provided evidences that proteins related to biosynthesis of secondary metabolites and carbon metabolism were mostly enriched after planthopper infestation (Zhang et al., 2019c). Several proteomics and transcriptomics study conducted on seed dormancy study revealed the important role of antioxidant mechanism, protein thiol and redox regulation along with hormonal signaling in rice, wheat and barley (Hu et al., 2015). Mass spectrometry (MS) based proteomics study demonstrated the cultivar specific induction of proteins in salt stress condition such as glutathione-based detoxification of ROS was highly induced in tolerant variety whereas proteins involved in iron uptakes were more expressed in salt sensitive variety in barley (Witzel et al., 2009). Similarly, the role of OsCYP2 in moderating the antioxidant enzymes was established in transgenic rice overexpressing cyclophilin during salt stress (Ruan et al., 2011). Seed proteomics of various developmental stages during different stresses have revealed the process involved in seed dormancy, seed germination, and seed development (Finnie et al., 2011). Proteomics related to environmental changes and abiotic stress focused on water supply responsive proteins in wheat against drought, high temperature, low temperature, frost, salt and heavy metals have been carried out (Yang et al., 2011; Han et al., 2013; Kosová et al., 2013; Alvarez et al., 2014; Capriotti et al., 2014; Kang et al., 2015). These studies offered novel insights and better understanding of crop physiology and metabolism during various kinds of stresses.

Holistic metabolomics based to study trails in plants were started late, particularly this approach was started through the introduction of untargeted metabolome detection (Alonso et al., 2015). Several studies have been reported where a particular metabolic pathways have been mapped (Sharma et al., 2021). For instance, the substantial changes in the various phytohormones was investigated in poplar leaf (Novák et al., 2008), rice various aerial organs (Kojima et al., 2009), rosemary leaves et al. (Müller and Munné-Bosch, 2011), Arabidopsis developing seeds (Kanno et al., 2010), strawberry fruits (Gu et al., 2019), potato tuber (Peivastegan et al., 2019), wheat developing seeds (Matsuura et al., 2019), watermelon fruit (Kojima et al., 2021), etc. The targeted approach has been also applied to explore the carotenoid pathway (Fernandez-Orozco et al., 2013; Kim et al., 2016; Mibei et al., 2017; Yoo et al., 2017; Price et al., 2018; Di Lena et al., 2019), flavonoid pathways (Karimi et al., 2011; Dong X. et al., 2014; Torres et al., 2019), amino acids (Torres et al., 2019; Praveen et al., 2020), and fatty acids (Talebi et al., 2013; Vidigal et al., 2018). Such profiling studies has helped in improving several important traits in plants by targeting specific pathways. Almost 10 years back Liu et al. (2011) targeted fatty acids biosynthesis pathways for enhancing biofuel production. Very recently and fatty acid desaturase 2 was targeted in several crops such as canola (Okuzaki et al., 2018), peanut (Yuan et al., 2019), rice (Abe et al., 2018), false flax (Morineau et al., 2017), and Soybean (Wu et al., 2020), for enhanced production of oleic acid (C18:1), respectively.

Several un-targeted metabolomics approach has been utilized to target multiple class of metabolites (amines, sugars, organic acids, etc.) from a sample extracted from various tissues of the model and crop plants such as Arabidopsis, apple, groundnut, kiwi fruit, alpine bird’s-foot-trefoil, strawberry, grapes, mango, maize, medicago, orange, pear, sunflower, soybean, tomato, rice, white lupin, etc. (Sharma et al., 2021). Now, the targeted and un-targeted metabolomics approach have been coupled with genomics data for carrying out metabolomics-based quantitative trait locus (mQTL) and metabolic genome-wide association studies (mGWAS) studies (Wen et al., 2015; Chen et al., 2016); which simultaneously identifies the genomic region, causal genes and key metabolites and associated metabolic pathways that govern particular trait in plants. Recently, Li K. et al. (2019) identified 65 primary metabolites viz 22 amino acids, 21 organic acids, 12 sugars, four amines and six miscellaneous metabolites in the leaf of teosinte (an ancestor of maize) and identifies advantageous genes present in the wild relative associated with grain yield and shape trait in maize. In tomato, for one of the important trait accumulation of secondary metabolite in fruit was analyzed, and reported several subset of mQTLs- including mQTLs associated with acyl-sugar, hydroxycinnamates, naringenin chalcone, and a range of glycoalkaloids (Alseekh et al., 2015). Likewise, there are several studies which identified key genomic regions, candidate genes and mQTLs related to important traits through mQTL and mGWAS based studies including some domesticated traits, this was extensively reviewed by Sharma et al. (2021).

Previously, a combined transcriptome, proteome and metabolomics approach was used to investigate the ripening process with a final aim of extending tomato fruit shelf life (Osorio et al., 2011). This study showed a strong relationship between metabolites and their associated transcripts controlling ripening such as sugars, organic acids, and cell wall metabolism pathways. Similar studies have been done for banana which led to identification of genes including ERF1B, fructose-1,6-bisphosphatase and polygalacturonase as key regulators of pulp ripening (Li T. et al., 2019). Recently, a combined transcriptome and metabolome study was deployed to study the molecular aspects of resistance and the interaction between Trichoderma harzianum strain T22 with tomato during defense responses against aphids (Coppola et al., 2019). This study demonstrated the importance of plant transcription factor families such as ZIP, MYB, NAC, AP2-ERF, and WRKY in biotic stress resistance. These examples show the potential of the -omics studies, working in tandem to characterize complex molecular interactions. These data have been used for the development of several gene expression/proteome/metabolome atlases to facilitate omics-driven crop improvement (Table 3).

From an evolutionary viewpoint, natural selection allows wild plant species to have specific functions to disperse seeds and fruits. Although from the agronomic viewpoint, natural seed dispersal is an undesirable trait in crops as it leads to significant seed loss in harvest. Consequently, natural seed dispersal was strongly chosen against by ancient humans to ensure productive cultivation during the domestication period (Purugganan and Fuller, 2009; Lenser and Theißen, 2013). The non-shattering traits were considered as the landmark of domestication in seed crops, as it makes the domesticated species mostly rely on human activity for propagation and enables the fixation of other domestication traits (Purugganan and Fuller, 2009). Seed crops have established their reduction of seed shattering ability independently and it is a convergent morphological adaptation to artificial selection (Purugganan and Fuller, 2009; Olsen and Wendel, 2013).

In cereal, seed shattering or fruit dehiscence is enacted through an abscission layer in the lemma-pedicel joint. Various transcription factors (TFs) coding genes were found in rice (Oryza sativa), which are involved in decreasing seed shattering. Shattering4 (Sh4) encodes the TF with Myb3 homology and is important for the formation of a functional abscission layer in the pedicle (Li et al., 2006). A single change of amino acid in DNA binding domain of Sh4 is intimately linked to the reduced seed shattering in domesticated rice. Also, the expression of the domesticated allele has been substantially reduced compared to the wild allele (Li et al., 2006). Thus, the combination of coding and regulatory alteration of Sh4 seems to affect the formation of the abscission layer, and consequently tries to weaken the shattering phenotype (Li et al., 2006). qSH1 is a major QTL on chromosome 1 involved in seed shattering in rice. The main gene, qSH1, codes a homeobox transcription factor-like BEL1 which is homologous to AtRPL (Konishi et al., 2006). A single nucleotide polymorphism (SNP) in the 5′-regulatory region effectively nullifies qSH1 expression in the preliminary abscission layer in the early development stage and contributes to non-shattering traits of rice (Konishi et al., 2006). Interestingly, the regulatory SNP in the homologs of RPL promoter are also amenable for distinct structures of seed dispersal based on natural selection of Brassica species with diminished replum development (Arnaud et al., 2011). These studies show a notable convergent mechanism where the same regulatory SNP could describe developmental variations in seed dispersal structures, which are important for both domestication and natural selection in distant species (Arnaud et al., 2011; Gasser and Simon, 2011). SH5 is another homeobox type BEL1 gene with a high qSH1 homology. SH5 has been expressed in the abscission layer (Yoon et al., 2014). Knockout of SH5 inhibits abscission layer formation and prevents seed shattering. Over-expression of SH5 leads to higher seed shattering, a consequence of decreased pedicel lignin levels (Yoon et al., 2014). The regulatory pathway of abscission layer formation has recently been expanded to include Shattering abortion 1 (SHAT1), an AP2 transcription factor encoding gene (Zhou et al., 2012). SHAT1 is needed for seed shattering by specifying abscission layer. Sh4 positively regulates the SHAT 1 expression in the abscission layer. qSH1 expression is lost in abscission layer in both the shat1 and sh4 mutant background, indicating qSH1 acts downstream of the shat1 and sh4 in the abscission layer establishment (Zhou et al., 2012). Intriguingly, qSH 1 is also needed in the abscission layer for expression of SH1 and Sh4. Thus the qSH 1 possibly takes part in a positive feedback loop of SH1 and Sh4 by establishing the SHAT1 and Sh4 expression in the abscission layer (Zhou et al., 2012). While SH5 and SHAT1 play a role in differentiating the abscission layer, the question remains whether both are artificially selected domestication genes. Like rice, decrease of seed shattering in domesticated sorghum is a result of loss of abscission in the joint that connects the seed hull with the pedicel. In sorghum, seed shattering is regulated by a single gene, Shattering1 (Sh1), which encodes a transcription factor YABBY. The non-shattering trait can be accounted for by any one of the three different loss-of-function mutations selected independently during sorghum domestication process (Lin et al., 2012). The notable mutations in Sh1 orthologs in rice and maize may be related to the shattering decrease in these crops (Lin et al., 2012). Whether Sh1 has been rewired into an SH5-directed seed shattering network in rice remains to be investigated in the future. In a wild relative of sorghum (Sorghum propinquum), seed shattering is conferred by the SpWRKY gene. It is believed that SpWRKY controls cell wall biosynthesis genes negatively in the abscission layer. Even so, SpWRKY was not crafted by artificial selection to contribute to the non-shattering characteristic for domesticated sorghum (Tang et al., 2013). These above studies together have raised a fascinating potential that the convergent domestication of non-shattering crops may have achieved the same underlying genetic goals by parallel selection (Lenser and Theißen, 2013).

In domesticated wheat (Triticum aestivum) free-threshing trait (loss of spike shattering tendency) is conferred by important Q gene (Simons et al., 2006). Q-gene encodes the AP2-family transcription factor. The domesticated Q allele is abundantly transcribed than the wild q allele. Besides, both alleles differ in single amino acid, which significantly improves the homo-dimerization ability of the cultivated allele (Simons et al., 2006). Similar to Sh4, the development of the free-threshing character in cultivated wheat might also have been due to the combination of the coding and regulatory changes in the cultivated gene. The difference of expression between Q and q seems more significant as it can clarify the free threshing character in cultivated wheat (Simons et al., 2006; Zhang et al., 2011). Even though mutation which gives rise to Q has a significant effect on the process of wheat domestication, as it helps farmers to harvest the grain more effectively, the exact cellular cause contributing to free-threshing character is still unclear. Similar research has been progressed in non-cereals crop such as overexpression AtFUL to make the pods shattering resistance in Brassica juncea (Østergaard et al., 2006).

Hormonal homeostasis and interactions have been found recently as direct downstream effects of the core genetic network. As an example indehiscent (IND) expression is involved in the formation of local auxin minimum at the margin of the valve by regulating the auxin efflux in the separation layer cells (Sorefan et al., 2009). Further findings reveal that another b-HLH class SPATULA (SPT) transcription factor, required for carpel fusion early in the female reproductive organ development, may interact physically with IND (Girin et al., 2011). Auxins and cytokinins play an antagonistic role in plant growth and development (Bishopp et al., 2011). This scenario also indicates that the cytokinin signaling pathway is active at the valve margins and such a signaling pathway is interrupted in the shp1/2 and ind mutant. Consequently, local application of cytokinins in the fruit development can help to restore valve margin formation and further enhance dehiscence in shp1/2 and ind mutants, suggesting that cytokinins play a crucial role in valve margin differentiation (Marsch-Martínez et al., 2012). Recent studies reveal gibberellins (GAs) are also involved in the establishment of separation layer cell identity, in addition to auxins and cytokinins (Arnaud et al., 2010). As per the “relief of restraint” model, GA-mediated degradation of DELLA protein is important for GA signaling and also necessary to trigger expression of downstream genes (Harberd, 2003; Sun and Gubler, 2004). GA3ox1, which facilitates the final step in bioactive GAs synthesis, is shown as the direct target of IND. ALC interacts physically with DELLA repressors and local GAs production destabilizes the DELLA protein and relieves ALC to play its role in SL cell specification (Arnaud et al., 2010). In summary, these findings show that many phytohormones participate in the DZ specification and indicate that precise balance between biosynthesis and response is important. Notwithstanding the studies where the function of hormones in the development of DZ have been elucidated, very few studies about how such hormonal signals are coordinated in DZ have been carried out. One of the key challenges is to unravel the complete context of the molecular mechanisms and interactions of plant hormones underlying DZ-specification.

There are many ways for minimizing crop losses due to crop shattering ranging from conventional parental selection with minimum shattering to the screening of mutants and gene editing methods. By advancing the next-generation sequencing and the marker traits associations, many genes involved in pod dehiscence were found, and a series of mutations underlying shattering resistance in several crops and their wild relatives have been identified (Fuller and Allaby, 2009; Dong and Wang, 2015). Attempts have been made to improve shattering resistance in Brassica, which include interfering in the dehiscence process by manipulating the molecular and hormonal control pathways (Fuller and Allaby, 2009; Altpeter et al., 2016) and developing transgenic lines with pod-shattering resistance (Liljegren et al., 2000, 2004). In future, studies should focus, alongside gene-editing methods, on fine-tuning of the degree of shatter-resistance with RNA interference or the use of mutated forms of genes related to shattering in various crops.

The plant architecture is genetically controlled by a set of genes which subsequent affect yield and productivity of crop plant species. Often, mutation or knockdown of a single gene could also lead to significant change in the overall plant growth and development, subsequently plant architecture (Spielmeyer et al., 2002). In 1960s, the agricultural transformation that increased the production of rice and wheat was via the introduction of cultivars with a genetic predisposition to a short stature due to restricted elongation of stem (Silverstone and Sun, 2000). This phenotype enabled a significant partitioning of photosynthate produced from photosynthesis to sink organs like grains (Sun and Frelich, 2011).

Currently introduction of dwarfing genes is the most important aspect deployed in modern cereal breeding. The stems of tall wheat and rice crops are not strong enough to sustain heavy grains of the high yielding cultivars, which result in significant yield losses. In addition, the proportion of assimilates partitioned in grain increases yields. Genes associated with the semi-dwarf growth of the wheat and rice cultivars have been studied. In wheat, Reduced height (Rht) gene has been identified which is shown to interfere with GA signaling transduction pathway (Peng et al., 1999). Subsequently, three research groups investigated semi dwarf1 (SD1) gene from rice and found that the same hormone impair the biosynthesis (Monna et al., 2002; Sasaki et al., 2002; Spielmeyer et al., 2002). Thus, gibberellin hormone appears to be central to plant stature control.

The incidences of uncertain rain and flood have been increased due to continued climate change. Today, more than 30 percent of the rice-planting land is vulnerable to flooding resulting in crop loss. In 1960s, the development of semi-dwarf variety was one of greatest achievement which significantly addressed the issue of global hunger threat caused due to human population explosion. The suppression of GAs production in the stem reportedly made high yielding semi-dwarf rice varieties susceptible to one of the most important abiotic stress “water logging.” These developed semi-dwarf rice varieties lacked submergence tolerance. The lower nodes of these varieties unable to produce enough gibberellins to trigger elongation of the internode.