4.1 Anaerobic Germination
Poor crop establishment remains a concern in areas that experience flooding after sowing and where fields are not properly leveled (Ismail et al. 2009). Flooding negatively affects germination and survival in most rice genotypes (Ismail et al. 2012). Conversely, it suppresses the growth of weeds and shrinks the cost of physical weeding and/or herbicide application. It is projected that approximately 30% of the total cultivation cost is saved when weed emergence is suppressed by flood.
The ability of seeds to sprout, grow, and survive under low oxygen (hypoxia) or very little to no oxygen (anoxia) is known as AG. This trait is a must-have for all direct-seeded rice systems. The trait ensures risk mitigation at the early stages of the crop and can be used as a weed control mechanism. The majority of the modern high-yielding rice varieties do not show any germination underwater. However, landraces that can maintain germination under flooded conditions have evolved in various parts of rice-growing areas. Some examples of such tolerant landraces are Khao Hlan On, Ma Zhan (red), Kalarata, Nanhi, and Khaiyan. Results of donor identification studies have shown tolerant landraces spread across all major groups of rice. However, indica and aus landraces have been used in genetic studies and breeding programs more than the other groups so far. Khao Hlan On and Ma Zhan (red) are currently used extensively as donors of the trait in breeding and marker-assisted selection (MAS) programs at the International Rice Research Institute (IRRI).
4.1.1 Physiology and Molecular Mechanisms of AG
Rice is the only cereal that can withstand water submergence; hence, it grows even under hypoxic conditions. In extreme conditions, submerged plants can experience anoxia when subjected to prolonged flooding. Under anoxia, the plant shifts to an alcoholic fermentation (AF) pathway rather than respiration for energy, in the form of adenosine triphosphate (ATP). During AF, only two ATPs are being produced vis-à-vis 38 ATPs are produced in aerobic respiration (Magneschi and Perata 2009). Therefore, the plant is 19 times less efficient in ATP production when exposed to anaerobic conditions. Notably, three common physiological responses allow rice seedlings to survive under anaerobic conditions: (1) longer coleoptile, (2) greater water imbibition, and (3) higher starch reserves.
According to Pradet and Bomsel, in 1978 (as cited by Kennedy et al. 1980), the only plant organ that can grow under anoxia is the rice coleoptile. Through coleoptile elongation, the plant can gain access to aeration, which enables the germination of the developing embryo (Ismail et al. 2012). Because of this, AG tolerance can be indirectly measured using coleoptile length. Hsu and Tung (2015) referred to this trait as the “anaerobic response index.” Alpi and Beevers (1983) demonstrated that seedlings develop coleoptiles at a higher speed when subjected to low environmental O2 concentration. However, they further observed that, despite its greater length, the coleoptile is thin and fragile with less fresh weight. This phenomenon can be referred to as the snorkel effect, whereby anoxia induces the development of a hollow coleoptile to access a better-aerated environment (Kordan 1974). This provides oxygen supply for the plant’s root and endosperm, which supports complete and vigorous seedling establishment. Adachi et al. (2015) evaluated the germination of tolerant (IR06F459) and intolerant (IR42) rice lines and revealed that the coleoptiles of IR06F459 had significantly longer coleoptiles than those of IR42. IR06F459 is an AG-tolerant line developed from backcrossing IR64 to Khao Hlan On. In addition, Ismail et al. (2009) revealed that water stress during germination decreased shoot and root length of intolerant genotypes by 81% and 68%, respectively (Fig. 4). This was incomparable to the decrease of 61% in shoot length and 7% in root length of the tolerant genotypes.
During flooding, seeds experience oxygen-limiting conditions. Under these conditions, the plant requires above-normal tolerance of anoxia to exhibit strong seed germination and growth (Ismail et al. 2009). In 1996, Yamauchi revealed that the use of genotypes that can withstand anaerobic conditions could help improve seedling establishment, weed control, and lodging resistance in DSR. Hence, the utility of genotypes with high germination rate (i.e., coleoptile and mesocotyl elongation) and seedling vigor under anaerobic conditions can curtail problems in crop establishment and even weed competition (Azhiri-Sigari et al. 2005). As revealed by Ismail et al. (2009) in their evaluation of tolerant (Cody, Khaiyan, Nanhi, and Khan Hlan On) and intolerant (FR13A, IR22, IR28, IR42, and IR64) genotypes, the survival of both groups decreased but there was a markedly larger decrease in the survival of the intolerant genotypes (Fig. 5). Among these tolerant genotypes, Khaiyan and Khao Hlan On displayed the highest survival rates, whereas the intolerant genotypes recorded a survival percentage of only about 5%.
The rapid germination of AG lines was credited by El-Hendawy et al. (2011) to rapid water imbibition under submerged conditions. They evaluated 58 contrasting genotypes, which showed a strong negative correlation (r = −0.46, p < 0.001) between water uptake and germination time. Further, the authors performed cluster analysis of the lines based on water content over different times of seed imbibition and revealed that tolerant genotypes clustered together within the group, which was characterized by rapid water uptake. Together, this suggests that high water uptake can induce rapid seed germination under anoxia. A proposed mechanism of action is that water uptake promotes sugar mobilization from the endosperm to the developing embryo (El-Hendawy et al. 2011), which provides energy for plant growth.
Apart from efficient water imbibition, carbohydrate content has the potential to enable plant growth under water stress. Ella and Setter (1999) suggested that the adverse effect of decreased ATP supply during AF is relieved when more carbohydrate is available for breakdown. As such, seeds with high starch content are deemed more tolerant of AG than seeds with high fat content (Magneschi and Perata 2009). Under anoxia, plant survival was found to be strongly correlated to starch content (r = 0.73–0.88) (Ella and Setter 1999). However, starch cannot be used as it is; hence, some also hypothesize the role of α-amylases, which are responsible for the breakdown of starch into soluble sugar (El-Hendawy et al. 2011). Rice, among the cereal crops under anoxia, is the only crop that expresses α-amylase mRNA (Perata et al. 1992, 1993). Also, a rice seed grown under anoxia expresses the whole set of enzymes needed for starch breakdown into its soluble forms (Ismail et al. 2009). These amylases regulate starch degradation to glucose, which is needed in the plants’ fermentative metabolism that is activated for ATP production under anoxia (Septiningsih et al. 2013). Adachi et al. (2015) reported in their study that the α-amylase activity in their tolerant line (IR06F459) was significantly higher than in the intolerant line (IR42). This was also in agreement with the findings of Illangakoon et al. (2016), for which the survival rates of their genotypes were positively correlated with α-amylase activity (r = 0.79) and soluble sugar content (r = 0.74). Ismail et al. (2009) reported that the soluble sugar concentration remained low for both tolerant and intolerant genotypes until the tolerant genotypes had higher soluble sugar at 4–8 days after sowing. These findings suggest that tolerant genotypes can break down carbohydrate reserves in the seed and mobilize the resulting monosaccharide, which can enable germination and growth under hypoxia. In 2015, Kretzschmar et al. found that OsTPP7 was expressed in the germinating tissues of a NIL-AG1 (tolerant) line while its expression was absent in IR64 (susceptible). Given that OsTPP genes (i.e., OsTPP1 and OsTPP2) in rice convert trehalose-6-phosphate (T6P) to trehalose, this mechanism can also be true for OsTPP7. Further analysis revealed that trehalose and sucrose were 2.3-fold and 2.0-fold higher in NIL-AG1 than in IR64. This suggests that OsTPP7 affects the conversion of T6P to trehalose, which signals low sugar availability; consequently, the plant enables starch mobilization from the endosperm reserve (source) to the coleoptile (sink).
Expression analysis, through RNA sequence (RNA seq), revealed that RAmy3D was highly expressed in tolerant genotypes under anoxia (Ismail et al. 2009). RAmy3D is a member of the Amy3 gene subfamily, which was found to be upregulated in rice embryos under anoxia (Hwang et al. 1999). RAmy3D, unlike RAmy1A from the Amy1 gene subfamily, lacks the gibberellic acid (GA)-responsive element in its promoter region (Lu et al. 1998) and is important in oligosaccharide degradation (Terashima et al. 1997). Under starvation, a glucose and sucrose receptor, RAmy3D, is activated by protein kinase SnRK1A (Lu et al. 2007). Meanwhile, SnRK1A is stimulated by calcineurin B-like protein kinase (CIPK15) under oxygen-limiting conditions (Kudahettige et al. 2010). Additionally, the interaction of calcineurin B-like proteins, such as CBL4 and CBL5, with CIPK15 under anoxia is viewed as a regulating mechanism in plant response during anoxia (Ho et al. 2017; Sadiq et al. 2011).
Although many other rice enzymes are downregulated during anoxia to inactivate energy-conserving steps, pyruvate decarboxylase (PDC), alcohol dehydrogenase (ADH), and aldehyde dehydrogenase (ALDH) are active in genotypes tolerant of anoxia (i.e., Khaiyan), as reported by Ismail et al. (2009). The upregulation of these enzymes proposes enhanced alcohol fermentation during anoxia, which uses nicotinamide adenine dinucleotide (NAD) for glycolysis and substrate-level phosphorylation (Saika et al. 2006; Shingaki-Wells et al. 2011). As a result, enough energy and carbon are supplied to the developing coleoptile under anoxia. Moreover, rice coleoptiles under anoxic conditions have been reported to exhibit a decrease in pH, which also suggests alcoholic fermentation pathway activation. In 2009, Ismail et al. showed that the concentration of ethylene increased significantly after only 3 days of imbibition. They also reported that the ethylene produced affects starch hydrolysis through the reduction of abscisic acid (ABA) synthesis while upregulating the synthesis of and sensitivity to gibberellic acid (GA) of the internode tissue. This enhances starch catabolite enzyme activity under stress, which enables seedling growth and survival under AG. Further, ethylene promotes coleoptile growth through cell expansion by regulating enzymes such as peroxidases, which are responsible for cell wall rigidity. Peroxidase activity decreases the plant cell wall’s lignin content and protein assembly (Waffenschmidt et al. 1993), which in turn decreases its rigidity and permits cellular elongation. Figure 6 shows the proposed mechanism of coleoptile elongation under anoxia as interpreted by Ismail et al. (2009).
Other factors that are deemed responsible for cell expansion are a group of nonenzymatic proteins called expansins, which can affect cell wall loosening. These proteins attach at the cell wall interface between cellulose microfibrils and matrix polysaccharides, which results in a disturbance of non-covalent bonds, enabling cell wall loosening (McQueen-Mason and Cosgrove 1995). Thus far, EXPA2, EXPA4, EXPA7, EXPB12, EXPA1, EXPB11, and EXPB17 were reported to be induced during submergence stress (Juang et al. 2000; Lasanthi-Kudahettige et al. 2007; Takahashi et al. 2011).
4.1.2 Genetic Factors Underlying the AG Trait
Before evaluating the genetics behind AG, it was necessary to identify lines that can germinate under very limited oxygen supply. The largest AG screening conducted has been that of Angaji et al. in 2010. They screened 8000 rice accessions from the IRRI Genetic Resources Center, which contains collections from gene bank accessions, elite breeding lines, IR64 mutants, and introgression lines. However, only 0.23% (19 lines) showed greater than or equal to 70% survival, a subset of which is present in Table 1. Nevertheless, Hsu and Tung (2017) evaluated gene expression in six genotypes and discovered 3597 genes affected by water stress irrespective of the plant’s genetic background, 5100 genes differentially affected across genotypes, and 471 genes affected in a genotype-dependent manner. Hence, the different genotypes are expected to display different degrees of tolerant response to anoxia.
Both quantitative trait loci (QTL) mapping and genome-wide association studies (GWAS) are useful in identifying genomic regions underlying different phenotypic traits. QTL mapping uses markers for a trait of interest, which can categorize the sample population into genotypic groups (Sehgal et al. 2016), while GWAS link common single nucleotide polymorphisms (SNPs) to phenotypic traits, which can provide information on the association between particular genetic variants and phenotype (Pal et al. 2015). Table 2 summarizes the results of some of the previous QTL mapping studies for AG tolerance using different rice landraces as sources.
In 2004, Jiang et al. evaluated 81 recombinant inbred lines (RILs) from a japonica/indica cross, Kinmaze/DV85. Kinmaze germinates well under anoxia; hence, it was used as the donor parent. These RILs were screened using 137 restriction fragment length polymorphism (RFLP) markers and five QTLs were detected on chromosomes 1, 2, 5, and 7. These QTLs explained phenotypic variation ranging from 10.5% to 19.6% of the shoot lengths. According to the calculated additive effects, the positive effect of three QTLs (qAG-1, qAG-2, and qAG-7) was contributed by Kinmaze. Meanwhile, AG tolerance conferred by qAG-5a and qAG-5b was improved due to the recurrent parent, DV85.
Another set of rice lines was evaluated by Jiang et al. in 2006 using USSR5 and N22 as parents. USSR5 is a japonica subspecies from the former Soviet Union while N22 is an indica type. These were crossed and the generated F2 plants were evaluated for survival under AG and then genotyped using 121 simple sequence repeat (SSR) markers. Mapping revealed two QTLs on chromosomes 5 (qAG-5) and 11 (qAG-11) contributing to AG tolerance. Both QTLs were contributed by the USSR5 allele, which accounted for 11.0–15.5% of the coleoptile length variation.
Four QTLs were identified by Angaji in 2008 from a cross using Khaiyan, an aus-type tolerant variety from Bangladesh, as a donor. Khaiyan was crossed with semi-dwarf nonaromatic indica lowland modern rice variety IR64, and the F1s were backcrossed to IR64 to produce 150 BC2F2 lines. The identified QTLs are qAG-1, qAG-2-2, qAG-11, and qAG-12, which explained 12.0–29.2% of the variation in survival of the lines, while together these QTLs accounted for a total of 51.4% of the phenotypic variation. However, based on the additive values, only the QTL qAG-1 had the allele from Khaiyan, which increased AG tolerance.
Another promising donor for AG tolerance is Khao Hlan On, which is a tall aromatic japonica upland landrace from Myanmar used by Angaji et al. in their study in 2010. They crossed Khao Hlan On with IR64 and the F1 progenies were backcrossed and selfed to produce 423 BC2F2 lines. QTL mapping was done using 135 SSRs and one InDel marker. Five QTLs accounting for 17.9–33.5% of the variation in percentage survival were detected from chromosomes 1 (qAG-1-2), 3 (qAG-3-1), 7 (qAG-7-2), and 9 (qAG-9-1 and qAG-9-2). Further, from the values of the additive effects of the QTLs, it was inferred that AG tolerance was contributed by alleles from Khao Hlan On.
More recently, in 2013, Septiningsih et al. used 118 SSR markers to assess AG tolerance alleles from Ma-Zhan (red), a highly AG-tolerant landrace from China with 90% survival (Angaji et al. 2010). Ma Zhan (red) was crossed with IR42 and then backcrossed to produce BC2F3 families. The survival rates and genotype data of 118 SSR markers in 175 families revealed six QTLs related to AG on chromosomes 2, 5, 6, and 7, accounting for 5.6–30.3% of the phenotypic variation. These QTLs are qAG-2, qAG-5, qAG-6, qAG-7-1, qAG-7-2, and qAG-7-3. It must also be noted that all five of these QTLs were donated by Ma Zhan (red). QTL qAG-7-2 explained the highest amount of phenotypic variation, amounting to 30.3% in interval mapping (IM) and 31.7% in composite interval mapping (CIM), with LOD scores of 13.7 and 14.5, respectively. This QTL was further evaluated to confirm its presence and effect. The authors developed introgression lines bearing the homozygous alleles of qAG-7-2 from Ma Zhan (red) and revealed that these introgression lines have significantly higher survival (47.58 ± 4.72%) than the introgression lines bearing homozygous IR42 alleles (16.67 ± 2.99%). Moreover, the results confirmed the effect of the QTL, which rendered an additional 30% survival in line with the homozygous allele of Ma Zhan (red). Given that Ma Zhan (red) still had the highest survival rate (73.7 ± 14.19%) among all the lines analyzed, this suggests the effect of other QTLs distributed widely in the rice genome to improve AG tolerance.
Hsu and Tung (2015) used both GWAS and QTL mapping to detect genomic regions related to AG tolerance. A total of 144 RILs from a Nipponbare and IR64 cross were used in QTL mapping with 35,501 SNPs. The authors identified a peak on chromosome 1 using both single marker analysis (SMA) and interval mapping based on the linkage map of 355 SNPs filtered after Bonferonni correction with α = 0.05. For GWAS, 153 accessions and 36,901 SNPs were used. This revealed three genomic regions on chromosome 7 (25.12, 26.92, and 27.72 Mb); however, the major QTL on chromosome 1, which was detected in QTL mapping, was not identified using GWAS. Since this QTL on chromosome 1 cannot be tagged as a rare variant based on haplotype analysis, it was proposed that the haplotype and varietal relationships can account for the inconsistency in findings. As mentioned by Kang et al. (2008), genetic association studies are confounded by population structure and relatedness, which can produce several false positives. However, Brachi et al. (2011) noted that overcorrection for these factors can lead to false-negative results.
Remarkably, some of the identified QTLs overlap across different studies. Some of these are (1) qAG-2 detected by Jiang et al. (2004) and Septiningsih et al. (2013), (2) qAG-7-2 by Angaji et al. (2010) and qAG-7-3 from Septiningsih et al. (2013), and (3) qAG-1-2 from Angaji et al. (2010) and chromosome 1 QTL from Hsu and Tung (2015). Further assessment should be done to detect whether these QTLs are controlled by the same gene(s).
At present, two QTLs have been considered of prime importance for AG tolerance, AG1 (qAG-9-2) and AG2 (qAG-7-1) identified from Khao Hlan On and Ma Zhan (red), respectively (Miro and Ismail 2013). In 2015, Kretzschmar et al. fine-mapped QTL qAG-9-2 to a 50-kb region on chromosome 9. Based on Nipponbare as the reference genome, this region encompasses four genes and one transposable element. Contrasting this region to a de novo assembled IR64 sequence revealed a 20.9-kb deletion of AG1 spanning across LOC_Os09g20390/Os09g0369400 (OsTPP7) and a deletion of neighboring loci. Meanwhile, the QTL did not show any structural variation against Nipponbare apart from a 4-kb deletion that is also present in IR64.
4.2 Seed Longevity
The life cycle of seeds involves fertilization, dormancy, and germination. Bewley (1997) defined seed dormancy as “the failure of an intact viable seed to completely germinate under favorable conditions.” Associated with dormancy is seed longevity, which is the ability of the seed to remain viable after harvesting, and this is usually evaluated through seed germination ratio or percentage.
Seed longevity varies among different rice varieties as it is governed by both genetic and nongenetic factors. Some notable nongenetic factors are ambient environmental conditions during seed development, maturity at seed harvest, mechanical damage, presence of pathogens, moisture content, and storage conditions after harvest (Copeland and McDonald 1995). Seed longevity and viability usually decrease when exposed to high temperature and moisture (Roberts 1961; McDonald 1999). Yamauchi and Winn (1996) reported that low seed longevity or seed aging is a major issue in the establishment of seeds in anaerobic environments where direct seeding is practiced. If seed longevity fails, crop establishment decreases and weed pressure proliferates. Both scenarios can dramatically decrease crop yield; hence, the importance of varieties tolerant of seed aging.
4.2.1 Physiology and Molecular Mechanisms Affecting Seed Longevity
Seeds battle aging through protection and repair. The seed protection mechanism involves the development of a glassy cytoplasm, which limits cellular metabolic activities and antioxidant production during seed storage to inhibit the buildup of oxidized macromolecules that can diminish seed viability. Conversely, the seed repair system exploits DNA glycosylases and methionine sulfoxide reductases, which prevent damage accumulation in the DNA, RNA, and/or proteins during seed imbibition (Sano et al. 2016).
Seed aging is oftentimes linked with the oxidation of nucleic acids, proteins, and lipids (Bailly 2004), causing oxidative stress. This can be combated through passive mechanisms, such as nonenzymatic reactive oxygen species (ROS)-scavenging systems, and active mechanisms, such as enzymatic ROS detoxification (Sano et al. 2016). In enzymatic responses, seeds rely on antioxidant enzymes such as superoxide dismutase, catalase, glutathione, ascorbate peroxidase, monodehydroascorbate, dehydroascorbate, and glutathione reductase (Bailly 2004; Kumar et al. 2015). Petla et al. (2016) also reported the role of the repair enzyme l-isoaspartyl O-methyltransferase, overexpressed in transgenic rice, by restricting ROS accumulation and by repairing homeostasis-disruptive isopartlyl residues in proteins.
Among the nonenzymatic responses, the most important antioxidants are tocopherols or vitamin E, which prevents nonenzymatic lipid peroxidation. Vitamin E-mediated free radical scavenging in rice decreases lipid membrane peroxidation, which results in greater seed longevity (Hameed et al. 2014).
Goufo and Trindade (2013) enumerated other biochemical factors affecting the longevity of rice seeds that include phenolic acid, flavonoids, coumarins, tannins, and anthocyanins. For example, antioxidant polyphenols such as flavonoids in the seed coat, embryo, and endosperm of Arabidopsis have been shown to increase seed longevity (Debeaujon et al. 2000). It is worth noting that AG donor lines such as Khao Hlan On have red pericarps, which may have putative roles in both seed longevity and AG tolerance.
Interest has increased in the epigenetic basis of the seed life cycle from fertilization to dormancy until germination. van Zanten et al. (2013) reported that seeds require epigenetic factors such as chromatin condensation to enable the transition from seed dormancy to germination in Arabidopsis thaliana
. These epigenetic modifications include condensation and methylation (Exner and Hennig 2008; Xiao et al. 2006), which affect chromatin accessibility under stress. Xiao et al. (2006) stated that mutated genes for DNA methylation result in nonviable seedlings and improperly developed embryo in A. thaliana. Interestingly, using a drought-tolerant barley variety, it was found that HvDME gene was highly expressed after 10 days of drought stress (Kapazoglou et al. 2013). This gene codes for DNA glycolases, which are responsible for DNA methylation affecting chromatin accessibility.
Recent work on the environmental effect on seed longevity likewise showed the influence of the pretreatments of seed drying at 45–60 °C (Whitehouse et al. 2017). It was revealed that this improves seed longevity in rice germplasm prior to storage. Furthermore, environmental transgenerational changes such as warmer parental growth environment affect the subsequent generation’s seed longevity in alpine trees (Silene vulgaris
) by providing transcripts of SvHSP17.4 and SvNRPD12 mRNAs to withstand heat stress (Mondoni et al. 2014). Moreover, the maternal environment of rice might have a putative role in seed longevity as was shown in barley (Nagel et al. 2015).
4.2.2 Genetic Factors Affecting Seed Longevity
Genome-wide association mapping in barley (Hordeum vulgare) showed that seed longevity is inherently affected by genetics, maternal environment, and seed deterioration while negating the effects of lipid-soluble tocochromanols, oil, and proteins (Nagel et al. 2015). Studies of different rice genotypes have shown that indica-type varieties have higher seed longevity than japonica-type (Chang 1991; Ellis et al. 1992). Table 3 summarizes some of the QTLs identified from different rice populations related to seed longevity.
In rice, three QTLs for seed longevity (qLG-2, qLG-4, and qLG-9) were detected on chromosomes 2, 4, and 9, respectively, using backcross inbred lines from a Nipponbare/Kasalath cross (Miura et al. 2002). QTL qLG-9 accounted for 59.5% of the phenotypic variation, which has a larger effect than the phenotypic variation effect of qLG-2 with 13.4% and qLG-4 with 11.6%. Further investigation by Sasaki et al. (2005) detected 12 germination QTLs as indices of seed longevity. In the latter study, qLG-9 was also detected and identified as RC9-2, which affected phenotypic variation by 12.5–12.8%.
Sasaki et al. (2015) fine-mapped the putative gene located in qLG-9 using advanced backcross progenies from the cross between japonica-type Nipponbare and indica-type Kasalath. They found that the candidate genes in the region encode for trehalose-6-phosphatase (Os09g039369400), TPP, and an unknown protein (Os09g039369500). Notably, Kretzschmar et al. (2015) mapped a candidate gene in the same region, which enhances anaerobic germination. This further affirms that the gene for seed longevity can be used for marker-assisted selection (MAS) for the breeding of aging tolerant rice for direct-seeded conditions to enable seedling germination and establishment even in anaerobic conditions.
4.3 Early Seedling Vigor
Seedling vigor reflects the plant’s potential to quickly emerge from the soil or water, which is a relevant trait for crop establishment, especially for direct-seeded rice. It is associated with germination and seedling growth, which enable good crop establishment and weed competition (Diwan et al. 2013). It is a complex trait that is governed by several genetic factors that affect the physiological, morphological, and biochemical processes of the plant.
4.3.1 Physiology and Molecular Mechanisms of Early Seedling Vigor
Some of the physiological traits that affect early seedling vigor are shoot length, shoot fresh weight, number of tillers per plant, mesocotyl length, root fresh and dry weight, germination rate, germination index, amylase activity, reducing sugar content, root activity, and chlorophyll content. Teng et al. (1992) evaluated the seedling growth of 38 rice varieties with differences in grain length, width, and weight. They revealed that the most vigorous seedlings were those with larger embryos and heavier endosperms.
Within the endosperm, the stored starch granules are composed of both amylose and amylopectin. These starch granules were distinguished based on their glucose residues (Huang et al. 2017). Amylose is made up of α-1,4-linked glucose residues; hence, it can be broken down into maltose by amylases. Amylopectin, however, cannot be split due to the presence of both α-1,4 and α-1,6 linkages. Starch hydrolysis is an important step for ATP production and for the generation of carbon skeletons for the development of new cellular components (Mitsui et al. 1996). Prior to photoautotrophy, seedlings gain the energy required for plant development from the breakdown of starch granules (i.e., amylose) in the endosperm (Cui et al. 2002b). This is regulated by starch-hydrolyzing enzymes such as α-amylases, which facilitate the cleavage of α-1,4-glucan bonds of starch (Hakata et al. 2012). Notably, this is considered as the first committed step in starch degradation.
α-Amylases are known to be initially expressed in the scutellar epithelial tissue and in the aleurone layer; they are then subsequently secreted into the starchy endosperm (Mitsui et al. 1996) to initiate starch breakdown. Therefore, at the seedling stage, plant vigor can be accounted for by higher amylose content and amylase activity, which provide the growing embryo with enough energy for development. Huang et al. (2017) used two cultivars, Yuxiangyouzhan and Huanghuazhan, to assess the morphophysiological traits governing seedling vigor. Yuxiangyouzhan (96%) showed a higher germination percentage than Huanghuazhan (87%). It was further revealed that Yuxiangyouzhan had higher seed amylose content and amylase activity. Additionally, Huang et al. (2017) cited the utility of using cultivars with thinner hulls, hence requiring less mechanical strength for coleoptile emergence.
4.3.2 Genetic Factors Affecting Early Seedling Vigor
Diwan et al. (2013) highlighted the importance of producing genotypes with early seedling vigor due to economic and environmental concerns. To address this, it is important to determine the genetics underlying seedling vigor. Several studies have been conducted to identify QTLs related to early seedling vigor. Table 4 summarizes some of the major QTLs related to early vigor that have been identified from different studies. Anumalla et al. (2015) surmised that RM259 and RM84 of chromosome 1; RM282, RM148, and RM85 of chromosome 3; RM26 of chromosome 5; and RM11 of chromosome 7 were the most promising markers for several seedling vigor traits. Nagavarapu et al. (2017) validated eight of the previously identified QTLs from different studies: qGR-1, qGP, and qGI-11 (Wang et al. 2010); RZ448 and RZ395 (Redoña and Mackill 1996); qFV-3-2, qFV-5-2, and qFV-10 (Zhou et al. 2007). The authors used 47 genotypes suitable for diverse ecosystems and estimated seedling vigor traits, followed by QTL analysis. Among the eight QTLs used for validation, six (qGR-1, qFV-10, qFV-3-2, qFV-5-2, qGP-6, and RZ395) were found to be associated with some of the selected genotypes. QTL qGR-1 for germination rate was detected in 12 genotypes; qFV-10 for seedling height under flooding in eight genotypes; qFV-3-2 for coleoptile emergence under flooding, qFV-5-2 for seedling height upon water draining, and RZ395 for mesocotyl elongation in three genotypes; and qGP-6 for germination percentage in two genotypes. Notably, some of the genotypes also showed multiple QTLs such as Dinesh with four and Pooja Sabita and Vivekadhan 62 each with two. Furthermore, Abe et al. (2012) identified OsGA20ox1 as a candidate gene for seedling vigor in rice. Using RILs from a cross between Kekashi and Dinghan Shali, the authors identified a putative QTL on chromosome 3, qPHS3-2, which affects 26.2% of the phenotypic variation in seedling height. This QTL region was then introduced to NILs with a background of an elite cultivar, Iwatekko. The region was fine-mapped into an 81-kb interval bearing the OsGA20ox1 gene that is related to gibberellin biosynthesis. Their further analysis revealed that both Dunghan Shali and the NILs had higher expression of OsGA20ox1 relative to Iwatekko, which suggests the utility of this gene for seedling vigor.
4.4 Breeding Rice with Improved Germination
Genetic studies on traits
such as AG, seed longevity, and early seedling vigor have shown high genetic variation between modern rice varieties, breeding lines, and traditionally evolved cultivars. Systematic extraction of genes that confer stronger germination from traditional varieties is required to develop high-yielding varieties with good crop stand and improved weed competitiveness. With DSR covering a larger proportion of rice area and quickly becoming an ask of the future, it is clear that rice varieties have to evolve from their current state and reach much higher tolerance of adverse conditions during seed germination. Although a large number of DSR breeding programs target selection for early vigor, a thorough understanding of this trait is most important to make genetic gains. For example, it is believed that increased seed size allows better germination capacity. However, in the case of rice, grain shape is an important seed quality and has to be kept in line with the product requirements of specific environments. This limits the amount of improvement for the trait as the best lines have to be selected within grain shape classes. This may also lead to higher popularity of varieties with larger grains under DSR. Similarly, grain pericarp color has been associated with higher AG tolerance and seed longevity and this needs to be addressed through systematic genetic studies to be able to develop white rice with better germination and seed longevity. Trait development and breeding methods must be combined systematically to be able to leverage the advantage of alleles with major and minor effects.
Figure 7 shows a set of pipelines that allow a systematic flow of required traits into a breeding program. Since most modern rice varieties are deficient in these traits, the work begins in the trait development pipeline with the development of a phenotyping protocol and donor identification. Once this is complete, adequate mapping populations are to be developed that can support the identification of robust QTLs. It is also to be kept in mind during this process that the recipient be chosen correctly. Ideally, these recipients should have elite genetic backgrounds that can be used in a breeding program in the future or those DSR-adapted breeding lines or varieties that are deficient in these traits. Upon the identification of the QTLs, screening a part of the mapping population in a few key locations can test their effect in the target environments. This allows developing confidence in the effect of the QTL
and investment in further fine-mapping can be carried out. Fine-mapped QTL regions and associated markers are delivered to the trait deployment pipeline, which rapidly develops high-yielding NILs of a wide range of recipient parents. Ideally, these should be the latest elite breeding lines
from the variety development pipeline. These NILs are entered into the pipeline and checked for yield potential and trait performance across key testing sites. High-performing NILs may be advanced for release as well as recycled into the crossing process to develop the next generation of breeding lines. This cyclic process allows the rapid recycling of high-performing lines as parents and allows building on the achieved genetic gain to advance it further. Once released, the varieties developed through this pipeline are managed through a seed systems team for adequate placement and deployment in collaboration with national seed systems. This team also collects feedback and provides it to the above pipeline so that any possible problems can be addressed in the next wave of varieties. The improvement of breeding lines for seed germination-related traits is important for both inbred programs and hybrid breeding programs. Hybrids provide great potential for achieving high yields in direct-seeded environments. However, for hybrids to be successful in DSR, germination and seedling survival must be high, and good crop stand be achieved with low seed rates to keep seed costs down.
All three major groups of traits discussed previously should be targeted to be able to improve germination under direct-seeded conditions. Although anaerobic germination is one of the most important traits, it cannot provide the needed robustness without other traits. Early seedling vigor helps to boost the effect of anaerobic germination and leads to better tolerance. Vigorous and rapidly growing coleoptiles can emerge from deeper soil layers efficiently and allow more uniform germination. This is specifically helpful in cases where seeding is mechanized and field preparations are not adequate. Lastly, higher seed longevity helps in maintaining germination for relatively older seeds. In cases where farmers use their own seeds, the age of seeds normally varies from 6 to 8 months. It is observed that although this duration does not affect germination to a large extent, it may have an effect on early vigor and anaerobic germination. In some cases where seeds are not adequately stored, germination may also become affected. It is observed, however, that genetic variation exists for the trait and it can be harnessed to improve modern varieties similar to the previous group of traits. In general, multiple donor lines for the three groups of traits can be crossed
to two to three elite recipient lines, each belonging to a different grain shape group. This will allow the development of nested association mapping populations with a common recipient parent within the grain shape group. Trait development activities can then be undertaken to identify and fine-map robust QTLs
for each of the grain shape groups. Finally, the identified QTLs can be introgressed singly or pyramided into the recipient lines and can be further deployed in the breeding program as donor lines.