Carotenoids are derived from the plastid-localized MEP pathway for which glyceraldehyde-3-phosphate and pyruvate act as initial substrates leading to the synthesis of GGPP, the common precursor for biosynthesis of carotenoids and several other terpenoid compounds (Farré et al., 2010; Rodriguez-Concepcion, 2010). The first committed step in the carotenoid biosynthesis pathway is condensation of two GGPP molecules by PSY to produce 15-cis-phytoene. Phytoene is converted into lycopene by two desaturation reactions catalyzed by PDS and ZDS. These enzymes give rise to poly-cis compounds which are converted to the all-trans form by ζ-carotene isomerase (ZISO) and CRTISO, as well as a light-mediated photo-isomerization. In bacteria, a single enzyme, CrtI, is believed to confer the same desaturation and isomerization reactions.

Lycopene constitutes a branching point in the pathway since it is the substrate of two competing cyclases, LCYB and LCYE. α-carotene is produced when LCYE and LCYB act together on the two ends of lycopene (β, ε-branch), whereas β-carotene is formed when LCYB acts alone (β, β-branch). Alpha-carotene and β-carotene are hydroxylated to produce lutein and zeaxanthin, respectively. These reactions are catalyzed by the β-ring carotene hydroxylase [HYDB, also known as non-heme di-iron β-carotene hydroxylase (BCH) or heme-containing cytochrome P450 β-ring hydroxylase (CYP97A and CYP97B)] and heme-containing cytochrome P450 carotene ε-ring carotene hydroxylase (CYP93C). Whereas lutein represents the natural end point of the β, ε-branch, zeaxanthin is further epoxidized by zeaxanthin epoxidase (ZEP) in a two-step reaction to produce violaxanthin via antheraxanthin. This reaction is reversed by violaxanthin deepoxidase (VDE) to give rise to the xanthophyll cycle for plants to adapt high light stress (Demmig-Adams and Adams, 2002). Violaxanthin is converted into neoxanthin by neoxanthin synthase (NXS), the final carotenoid of the β, β-branch of the classical biosynthetic pathway.

In some plants, the classical carotenoid biosynthesis pathway extends further to synthesize specialized ketocarotenoids. One such example is the red fruits of chili peppers, where the capsanthin and capsorubin are synthesized from antheraxanthin and violaxanthin by capsanthin-capsorubin synthase (CCS) enzyme (Gómez-García and Ochoa-Alejo, 2013). Another example is the ornamental plant Adonis aestivalis whose petals synthesize the red ketocarotenoid astaxanthin, which is usually found in microbes (Cunningham and Gantt, 2005). With progress in high-performance liquid chromatography-tandem mass spectrometric (HPLC-MS) and high-performance liquid chromatography-nuclear magnetic resonance (HPLC-NMR) technologies, more specialized ketocarotenoids will be detected, which will further enrich our knowledge of this pathway.

In grasses, PSY are encoded by three paralogous genes (PSY1-3; Dibari et al., 2012). PSY1 is correlated with carotenoid accumulation in grain, PSY2 is involved in protecting the photosynthetic apparatus from photo-oxidative degradation in green tissues, and PSY3 is associated with root carotenogensis channeled into ABA formation, mainly responsing to abiotic stresses, such as drought and salt (Gallagher et al., 2004; Li et al., 2008; Welsch et al., 2008). PSY duplication has provided an opportunity for subfunctionalization whereby gene family members vary in tissue specificity of expression to control carotenogenesis independently of photosynthesis or in response to certain stresses (Li et al., 2008; Welsch et al., 2008; Arango et al., 2010).

Carotenoid degradation can occur via non-specific mechanisms such as photo chemical oxidation or LOX (Siedow, 1991; Auldridge et al., 2006). However, specific tailoring of carotenoids is carried out by a family of CCDs, which appear to have different substrate preferences (Vallabhaneni and Wurtzel, 2009). The CCD gene family is divided into two types: nine-cis-epoxycarotenoid dioxygenases (NCEDs) catalyze both violaxanthin and neoxanthin to produce xanthoxin, the precursor of ABA (Seo and Koshiba, 2002; Walter et al., 2010), and CCDs that catalyze a vast array of different cleavage steps giving rise to apocarotenoids. For example, CCD1 is involved in β-ionone biosynthesis, whereas CCD7 and CCD8 are associated with strigolactone biosynthesis. These apocarotenoids are crucial for various biological processes in plants, such as regulation of growth and development and plant-insect interaction (Walter et al., 2010; Alder et al., 2012; Avendano-Vazquez et al., 2014).

Carotenoids are usually synthesized de novo in nearly all types of differentiated plastids of leaves, roots, flowers, fruits, and seeds, including chloroplasts, chromoplasts, amyloplasts, elaioplasts, leucoplasts, and etioplasts, but accumulate in large quantities in chloroplasts and chromoplasts (Howitt and Pogson, 2006; Cazzonelli and Pogson, 2010). Chloroplasts and chromoplasts differ considerably in the way they sequestrate end-product carotenoids. In chloroplasts, carotenoids are located in photosynthetic membranes and integrated with chlorophyll-binding proteins to form pigment–protein complexes (Vishnevetsky et al., 1999). Whereas, in chromoplasts, carotenoids are associated with polar lipids and carotenoid associated proteins to form carotenoid-lipoprotein sequestering substructures (e.g., globules, crystals, membranes, fibrils, and tubules) to effectively sequester and retain a large quantity of carotenoids (Vishnevetsky et al., 1999; Egea et al., 2010; Li and Yuan, 2013).

To date, there is little understanding of carotenoid degradation. Much more effort to understand CCD gene family members, their substrates and products, is still needed. In addition, some acronyms of carotenogenes were confused in the previous literature, such as β-hydroxylases being replaced by BCH and HYD in rice (Du et al., 2010), crtRB1 and HYD in maize (Yan et al., 2010), BCH in Arabidopsis (Kim et al., 2009), and CHY in potato (Diretto et al., 2007), respectively. For a better understanding and communication, international efforts are needed to uniform the acronyms.

Carotenoid biosynthesis requires an available source of isoprenoid substrates derived from the MEP pathway, which is a key bottleneck influencing flux through the entire pathway (Farré et al., 2010; Rodriguez-Concepcion, 2010). In the MEP pathway, the transcript levels of DXS, 1-deoxy-D-xylulose 5-phosphate reductoisomerase (DXR) and 1-hydroxy-2-methyl- 2-(E)-butenyl 4-diphosphate reductase (HDR) were positively correlated with carotenoid content in maize endosperm (Vallabhaneni and Wurtzel, 2009; Suwarno et al., 2015).

In addition to its role in carotenoid biosynthesis, GGPP is a precursor for synthesis of many other terpenoid compounds in plants. Therefore, the pool of GGPP represents the metabolic link between biosynthesis of carotenoids and other terpenoids, and is responsible for inter-pathway regulation via competition for GGPP. The expression level of GGPP synthase (GGPPS) was positively correlated with endosperm carotenoid content in maize (Vallabhaneni and Wurtzel, 2009; Suwarno et al., 2015). Another key regulatory issue is what mechanisms control the partitioning of precursors into various terpenoid pathways. There is clear evidence for multiple GGPPS genes in Arabidopsis, encoding dedicated enzymes for different branches of various terpenoid pathways (Okada et al., 2000).

Phytoene synthase catalyzes the first committed step in carotenoid biosynthesis and is generally accepted as the most important regulatory node in the carotenoid biosynthesis pathway, whose transcripts were positively correlated with carotenoid accumulation (Cong et al., 2009; da Silva Messias et al., 2014). Moreover, PSY seems to be a key integrator for several signals regulating carotenoid biosynthesis. For example, blocking of the MEP pathway and loss-of-function of PDS result in down-regulation of PSY, whereas increased activity of DXS induces PSY expression in tomato (Rodriguez-Concepcion et al., 2001; Laule et al., 2003). Orange (OR) protein directly interacts with PSY to regulate carotenoid biosynthesis (Zhou et al., 2015). In addition, carotenoid metabolites also regulate PSY protein level and total carotenoid content (Kachanovsky et al., 2012; Arango et al., 2014). For example, expression of the PSY gene is positively up-regulated by ABA and has been associated with pre-harvest sprouting in cereals (Fang et al., 2008; Cazzonelli, 2011).

The cyclization of lycopene has a major role in modulating the β, β/β, ε branch ratio, suggesting that coordination between LCYE and LCYB activities may be necessary for regulation of metabolic flux through different branches of the carotenoid pathway (Cazzonelli et al., 2010; Farré et al., 2011). Over-expression of LCYB shifts the balance toward the β, β-branch, whereas over-expression of LCYE has the opposite effect (Rosati et al., 2000; D’Ambrosio et al., 2004). However, expression of PSY1, CrtI, and LCYB in transgenic maize endosperm increased β, β/β, ε ratio from 1.2 to 3.5 and also enhanced flux through the β, ε-branch of the pathway, producing almost 25 times more lutein than the normal level (Zhu et al., 2008). Naqvi et al. (2011) also found that when metabolic flux is shifted toward β-carotene there is still enough flux through the β, ε-branch to produce more lutein. These examples showed that regulation of the flux through different branches of the pathway was complex.

Some other carotenogenes also regulated carotenoid content. For example, viviparous mutants vp5, vp2, and w3 in maize have defective copies of the PDS gene and exhibit increased accumulation of phytoene (Matthews et al., 2003). High expression of the ZDS gene was consistent with accumulation of lycopene during carrot root development (Clotault et al., 2008). ZISO and CRTISO are essential for establishing an equilibrium between cis- and trans- carotenoid isomers (Chen et al., 2010; Yu et al., 2011). In addition, expression of crtRB1 was negatively correlated with β-carotene levels and positively correlated with zeaxanthin levels in maize (Yan et al., 2010; da Silva Messias et al., 2014).

Apart from the carotenogenes per se, transcriptional factors regulating carotenoid biosynthesis have been reported. Reduced transcript level of RAP2.2, a member of the APETALA2 (AP2)/ethylene-responsive element-binding protein transcription factor family, was accompanied by a significant decrease in transcript levels of both PSY and PDS with a concomitant 30% decrease in carotenoid content relative to wild-type (Welsch et al., 2007). The transcription factor RIN induces PSY1 expression to regulate the flux of carotenoid biosynthesis in tomato (Martel et al., 2011). Moreover, epigenetic regulation was also considered important in carotenogenesis. A chromatin-modifying histone methyltransferase enzyme SDG8 (SET DOMAIN GROUP 8) maintains a transcriptionally permissive chromatin state surrounding the CRTISO and thus is able to regulate carotenoid content (Cazzonelli et al., 2009). Overexpression of microRNA156 in Brassica napus enhanced carotenoid content in seeds (Wei et al., 2010).

Recent studies have demonstrated that the carotenoid pool is determined in part by the rate of carotenoid degradation (Vallabhaneni and Wurtzel, 2009; Gayen et al., 2015). The expression of CCD1 or CCD4 was negatively correlated with carotenoid accumulation (Gonzalez-Jorge et al., 2013; da Silva Messias et al., 2014). It was shown that down-regulation of LOX enzyme activity reduces degradation of carotenoids in Golden Rice suggesting an effective tool to reduce large economic losses of biofortified rice seeds during storage (Gayen et al., 2015). Compared to carotenoid biosynthesis, little is known about the impact of carotenoid degradation on regulation of carotenoid accumulation, and much more work is needed to understand it.

Various studies have shown that carotenoid accumulation is greatly modulated by size, number, and anatomical structure of the plastids in which carotenoid biosynthesis and storage occur. Organelle biogenesis is a major determinant of plastid size and storage compartment number, and affects carotenoid accumulation by providing a larger sink. CHCR (chromoplast-specific carotenoid-associated protein) enhances carotenoid content in high pigment tomato mutants (hp1, hp2, and hp3) due to increased chromoplast number and/or volume (Galpaz et al., 2008; Kilambi et al., 2013). A mutation in the OR gene led to differentiation of plastids to chromoplasts causing enhanced carotenoid accumulation in the curds of cauliflower (Lu et al., 2006). A change in chromoplast architecture is associated with carotenoid composition in Capsicum fruits (Kilcrease et al., 2013).

Esterification limits degradation of xanthophylls and increases their sequestration within the chromoplast by increased lipophilic properties and integration into lipid-rich plastoglobules (Ariizumi et al., 2014; Mellado-Ortega and Hornero-Méndez, 2016). Moreover, it was suggested that carotenoid accumulation might be correlated with expression of genes influencing lipoprotein components of chromoplast structures, such as plastid-encoded acetyl coenzyme A, carboxylase D and Hsp21 (Neta-Sharir et al., 2005; Barsan et al., 2012; Carvalho et al., 2012).

Although significant progress has been made in understanding carotenoid regulatory mechanisms in plants, several key issues are yet to be addressed. Firstly, very little is known about the global regulatory mechanisms underlying carotenoid metabolism. Cross-talk between carotenoid biosynthesis and other pathways and how interaction responds to plant growth and development and environment remain unclear. Secondly, the molecular nature of regulation of metabolic feedback remains unknown. Finally, research on regulation of carotenoid biosynthesis has mostly focused on model species and such regulatory mechanisms in non-model species are not well documented, hence restricting a detailed understanding of regulation of carotenoid biosynthesis in specific crops.

Various metabolic engineering approaches have been made to increase the levels of nutritionally relevant carotenoids in staple cereals and to enable the use of plants as ‘cell factories’ for producing special carotenoids. Amplification of the rate-limiting enzyme with the highest flux control coefficient is the principal target for manipulation. Alternatively, it may be desirable to change the carotenoid composition or extend the classical carotenoid pathway in the tissue of interest.

A breakthrough in metabolic engineering of carotenoids for improved nutritional value of staple crops was achieved in rice, best-known as ‘Golden Rice.’ Here, daffodil PSY and LCYB genes together with the bacterial CrtI were transferred to a japonica rice cultivar in which the β-carotene content in the endosperm was 1.6 μg/g of seed dry weight, providing 10–20% of the recommended daily allowance (RDA) of β-carotene (Burkhardt et al., 1997; Ye et al., 2000). Further optimization of the pathway using the maize PSY gene driven by a rice glutelin promoter considerably increased carotenoid formation in transgenic rice endosperm, resulting in Golden Rice II lines with carotenoid levels up to 37 μg/g (Paine et al., 2005). Higher carotenoid accumulation was recently achieved through the combined expression of ZmPSY1, PaCRTI with AtDXS or AtOR in rice endosperm, suggesting that the supply of isoprenoid precursors and metabolic sink are important rate-limiting steps in carotenoid biosynthesis (Bai et al., 2016). Similarly, total carotenoid levels in wheat were enhanced by co-transformation with maize PSY1 and the bacterial CrtI gene, but the elevation of carotenoid content was only moderate compared with that in the donor wheat cultivar EM12 (Cong et al., 2009). In order to further enrich the provitamin A content in wheat grains, the bacterial CrtB and CrtI genes were co-transformed into cultivar Bobwhite (Wang et al., 2014), resulting in a total carotenoid content increase to 4.76 μg/g, a β-carotene increase to 3.21 μg/g, and a provitamin A content increase to 3.82 μg/g. Recently, higher levels of β-carotene accumulation up to 5.06 μg/g were obtained by simultaneously overexpressing CrtB and silencing carotenoid hydroxylase (Zeng et al., 2015b). Although the level was still insufficient to combat VAD, the progress was still important, as a small increase in carotenoid contents in wheat grains would have a large impact based on the huge daily consumption of wheat-based products throughout the world.

A wide variety of unusual keto-carotenoids and carotenoid intermediates, such as astaxanthin, adonixanthin, 3-hydroxye chinenone, and echinenone have been engineered in transgenic maize plants with seed colors ranging from white and yellow to dark-red, despite the white-endosperm genetic background (Zhu et al., 2008). The carotenoid pathway in rice was recently further extended to form astaxanthin and 4-keto-α-carotene, with co-transformation of ZmPSY1, the bacterial CrtI and β-carotene ketolase genes (Breitenbach et al., 2014).

As already mentioned, most of the research on carotenoid manipulation in staple cereals has focused on a few main carotenogenes. In the future, manipulation of carotenoid biosynthesis could be extended to different regulatory nodes, such as the MEP pathway, carotenoid degradation, and sequestration. Moreover, the current status of metabolic engineering is somewhat restricted due to its reliance on gene-by-gene approaches. In other pathways, the focus has shifted from individual genes or collections thereof toward overarching regulatory mechanisms that may allow multiple genes in the pathway to be controlled simultaneously. Although enhancement of carotenoid biosynthesis by metabolic engineering proves to be a useful tool, the transgenic lines may induce hitherto undiscovered feedback mechanisms with unpredictable results. One of the major hurdles for commercialization of genetically engineered crops is the legal requirements and acceptance by consumers in various countries. Golden Rice has not yet been released in any country although daily consumption of 75 g of Golden Rice II grains can receive the RDA of β-carotene (Paine et al., 2005).

Over the past decade, increasing carotenoid content in grains of staple cereals such as rice, maize, and wheat, has been an important breeding objective. However, conventional breeding to select for QTL with positive effects on carotenoid levels is a slow and laborious process. The identification of rate-limiting steps, the elucidation of molecular basis of known QTL, or the characterization of new alleles for higher carotenoid content, will allow development of functional markers or gene-specific markers for a more efficient selection in breeding. Such functional markers allow breeders to select quantitative traits at the gene level rather than at the phenotypic level.

In maize, previous studies showed that two polymorphic sites within PSY1 each explained 7 and 8% of the total carotenoid variation (Harjes et al., 2008); four polymorphic sites in LCYE explained 58% of β, β/β, ε branch ratio variation and a threefold difference in provitamin A compounds (Yan et al., 2010); three polymorphisms in crtRB1 were significantly associated with variation in carotenoid content (Fu et al., 2013). Allele-specific markers of three key genes involved in maize endosperm carotenoid biosynthesis were developed to facilitate provitamin A biofortification in maize through marker-assisted selection (MAS). The effectiveness of these molecular markers was verified across diverse tropical yellow maize inbred lines (Azmach et al., 2013; Babu et al., 2013). A favorable crtRB1 allele was introgressed into seven elite inbred parents using a crtRB1-specific marker, and concentration of β-carotene among crtRB1-introgressed inbreds varied from 8.6 to 17.5 μg/g, with a maximum increase of up to 12.6-fold over recurrent parent (Muthusamy et al., 2014). Introgression of a favorable allele of the crtRB1 gene using molecular markers also significantly increased provitamin A content in quality protein maize inbred lines (Liu et al., 2015). In rice, no carotenoids were detected in the endosperm due to lack of endosperm-specific PSY expression (Ye et al., 2000). Therefore, molecular marker-assisted breeding for rice carotenoid improvement is still not feasible. Although many molecular markers have been developed for genes involved in carotenoid biosynthesis in wheat as described below, there are no reports of higher carotenoid content wheat cultivars developed by marker-assisted breeding.

The objectives of Harvest Plus², a worldwide collaboration that drives biofortification as a project within the Consultative Group of International Agricultural Research (CGIAR), are to breed more nutritious cultivars of staple food crops by conventional breeding technologies strengthened with molecular markers. Provitamin A-biofortified crops, including maize, cassava, and sweet potato, have been developed and released in Nigeria, Zambia, and Uganda. Eating orange sweet potato has been shown to improve vitamin A status of children.

The carotenoid biosynthesis is very complex, therefore multiple genes must be taken into consideration during marker-assisted breeding in order to enhance the accuracy of prediction and selection. In addition, mutants with desirable carotenogenic properties generated by chemical treatment may provide new insights into carotenoid improvement in staple cereals that are not categorized as genetic manipulation and can be immediately introduced into breeding programs. Meanwhile, such mutants are not involved in the expensive and time-consuming gene transformation, and therefore, easy to be used in breeding programs.

Lutein is the predominant carotenoid in wheat, and accounts for 80–90% of total carotenoids along with small amounts of zeaxanthin, α-carotene, β-cryptoxanthin, and β-carotene (Abdel-Aal et al., 2007; Digesù et al., 2009). The pigments are variably distributed in the seed; the endosperm has the highest lutein content, whereas zeaxanthin and β-carotene are concentrated near the outer layers of the kernel (Hentschel et al., 2002; Borrelli et al., 2008). Although levels of carotenoids in wheat are low, there is significant genetic variation. Previous studies showed that primitive and wild relatives, landraces, and synthetic hexaploids usually accumulate higher levels of carotenoids. For example, einkorn (2n = 14), and Khorasan and durum wheat (2n = 28) contain higher levels of lutein (5.4–7.4 μg/g) compared to common wheat (1.9 μg/g; Hidalgo et al., 2006).

Carotenoid biosynthesis during grain development was examined using a doubled haploid (DH) bread wheat population (Howitt et al., 2009). During the early stages of grain development, carotenoids from the β, β-branch (zeaxanthin, antheraxanthin, and violaxanthin) were present at higher levels than those from the β, ε-branch (lutein). The highest amounts of lutein and zeaxanthin were detected at 10 days post anthesis (DPA). Although the level of lutein did not change significantly during endosperm development, carotenoids from the β, β-branch declined gradually and were undetectable in mature grains.

Although environmental factors play an important role in determining carotenoid contents in wheat, the genetic component is predominant and heritability is relatively high at 0.85–0.97 for YPC, a trait strictly related to carotenoids (Elouafi et al., 2001; Van Hung and Hatcher, 2011).

The genetic architecture of YPC was investigated through QTL analysis in both durum and bread wheat. QTL located in the telomeric regions of the long arms of the homeologous group 7 chromosomes, especially 7AL and 7BL, largely influenced YPC (Elouafi et al., 2001; Patil et al., 2008). Various minor QTLs were also detected on chromosomes of homeologous groups 2, 3 and 4, and chromosomes 1A, 1B, 5A, 5B, 6A, and 6B (Zhang et al., 2008; Blanco et al., 2011; Colasuonno et al., 2014). In addition, the 1BL.1RS wheat-rye translocation carried a major QTL for YPC and b^∗ explaining 25.4–32.2% of the phenotypic variance (Zhang et al., 2009; Zhai et al., 2016). Wheat cultivars with the 1BL.1RS translocation had higher total carotenoid contents (0.76 vs. 0.61 μg/g), lutein (0.46 vs. 0.40), zeaxanthin (0.08 vs. 0.07) and β-carotene (0.22 vs. 0.14) than those without the translocation (Li et al., 2016), an aspect that should be considered in breeding for higher provitamin A content in bread wheat.

Most of carotenogenes in wheat have been cloned and characterized. Briefly, the full-length genomic DNA sequence of PSY1 was cloned, and two co-dominant markers (YP7A and YP7B-1) and two dominant markers (YP7B-2 and YP7B-3) were developed for PSY-A1 and PSY-B1 (He et al., 2008, 2009). YP7A co-segregated with a QTL for YPC on chromosome 7AL and explained 20–28% of the phenotypic variance (He et al., 2008). Cultivars with PSY-B1c had the highest YPC (2.01 μg/g), followed by PSY-B1a (1.71 μg/g), whereas those with PSY-B1b had the lowest value (1.40 μg/g; He et al., 2009).

Dong (2011) cloned the full-length PDS gene and designed two complementary markers YP4B-1 and YP4B-2 corresponding to higher and lower YPC, respectively (no significant difference). The full-length genomic sequence of ZDS was cloned and co-dominant molecular markers YP2A-1 and YP2D-1 were developed for ZDS-A1 and ZDS-D1, respectively (Zhang et al., 2011; Dong et al., 2012). YP2A-1 and YP2D-1 co-segregated with QTL for YPC on chromosome 2A and 2DL, respectively, explaining 11.3–18.4% of the phenotypic variance.

The entire sequence of the LCYE gene was isolated and located on homoeologous group 3 chromosomes, and it was identified as a candidate gene underlying QTL for lutein content on chromosome 3B (Howitt et al., 2009). Dong (2011) developed a co-dominant functional marker YP3B-1 for TaLCYE-B1, but values of YPC from cultivars with TaLCYE-B1a were not significantly different from those with TaLCYE-B1b. Therefore, the effect of TaLCYE-B1 on carotenoid contents in wheat grains need to be further investigated. e-LCY3A-3, a co-dominant functional marker, was developed based on e-LYC3Aa and e-LYC3Ab alleles (Crawford and Francki, 2013b). A highly significant (P < 0.01) association with QTL on chromosome 3A indicated that e-LYC3A is functionally associated with variation in b^∗. The TaLCYB gene was cloned and shown to have a role in β-carotene biosynthesis using RNAi (Zeng et al., 2015a). In addition, HYD1, HYD2, and HYE were cloned and characterized (Kawaura et al., 2009; Qin et al., 2012). Information relating to these genes and molecular markers is provided in Table 1. The functional markers have been used in routine germplasm characterization and cultivar development.

For carotenoid degradation, three copies of the LOX-1 gene (LOX-B1.1, LOX-B1.2, and LOX-B1.3) were cloned in durum wheat (Hessler et al., 2002; Verlotta et al., 2010). In bread wheat, the full-length genomic DNA sequence of TaLOX-B1 gene was cloned, and complementary markers LOX16 and LOX18 were developed (Geng et al., 2012). However, CCD sequences of wheat have not been reported to date.

With carotenogenes identified and functional markers developed, there is a growing interest in understanding the molecular basis of QTL underpin carotenoid content in wheat.

As expected, PSY1 gene was considered as a candidate gene responsible for YPC variation in wheat grains since YP7A and YP7B co-segregated with QTL for YPC on chromosomes 7AL and 7BL (He et al., 2008; Zhang and Dubcovsky, 2008; Singh et al., 2009). Other studies indicated that a second gene other than PSY1 in the distal regions of chromosomes 7A and 7B affects YPC (Singh et al., 2009; Crawford and Francki, 2013a). The geranylgeranyl transferase I α-subunit (RGGT) gene was mapped to distal regions on chromosomes 7BL and 7DL (Crawford et al., 2008). This gene encodes enzyme involved in the terpenoid backbone biosynthesis pathway, providing the precursor GGPP for carotenoid biosynthesis, and it could be a candidate for the additional gene. Moreover, a Cat3-A1 gene was co-located to the QTL for b^∗ on 7AL, encoding a catalase enzyme which controls varying degrees of bleaching action on lutein by regulating hydrogen peroxide accumulation in developing wheat grain, and it could be another candidate for the additional gene (Crawford and Francki, 2013a; Li et al., 2015).

The LCYE gene was considered as a candidate gene for QTL affecting b^∗ variation and lutein content on chromosomes 3A and 3B in bread wheat (Howitt et al., 2009; Crawford and Francki, 2013b). In addition, a QTL for pasta color on chromosome 4B was linked to a polymorphic deletion in LOX-B1, suggesting that it was associated with pigment degradation during pasta processing (Hessler et al., 2002).

With advances in genomics and bioinformatics, some other genes were found to be associated with carotenoid biosynthesis in wheat. A genome scan for QTL in durum and SNP homology prediction against annotated proteins in the wheat and Brachypodium genomes identified diphosphomevalonate decar boxylase (DMAPD) and aldehyde oxidase (AO) co-located with the major QTL for YPC on chromosomes 5BL and 7AL, respectively (Colasuonno et al., 2014). Six candidate genes related to terpenoid backbone biosynthesis were within QTL intervals associated with four color-related traits in bread wheat (Zhai et al., 2016); these included genes for alpha-1,3-mannosyl-glycoprotein 2-beta-N-acetylglucosaminyltransferase (MGAT1), mevalonate kinase (MK), delta-cadinene synthase (DCS), ketol-acid reductoisomerase (KARI), cytokinin oxidase/dehydrogenase (CKX), and secologanin synthase (SLC). All these genes further enrich carotenoid biosynthesis pathway (Figure 1).

Because quantification of carotenoids by HPLC is expensive and time-consuming, most studies of wheat carotenoid contents have depended on indirect parameters such as YPC and b^∗. In order to deepen understanding of the carotenoid metabolism in wheat, fast, cost-effective methods to detect individual carotenoids should be developed and improved, such as UPLC (ultra-high performance liquid chromatography), UPLC-MS and UPLC-NMR. Moreover, many QTLs affecting carotenoid content could not be explained by known genes. This provides opportunities to discover additional genes controlling carotenogenesis in wheat grain. With progress in next-generation DNA sequencing and SNP chips, it will be much easier to construct high-density genetic maps useful in detecting QTL for carotenoid content, identifying candidate genes, and map-based cloning of candidate genes.