Introduction

Rice (Oryza sativa) is a staple food for more than half of the world’s population. It is grown in 114 countries worldwide (Food and Agriculture Organization Corporate Statistical Database 2022), with 90% of rice production in Asian countries (Fukagawa and Ziska 2019). Global rice demand is increasing yearly, and global rice production is expected to grow by 58 million tons and reach 567 million tons by 2030 (OECD and Food and Agriculture Organization of the United Nations 2021). Global rice consumption is expected to increase from 2.7 to 3 billion tons by 2030 (OECD and Food and Agriculture Organization of the United Nations 2021). Rice ranks second after corn in yield and harvest among cereal crops (Mukhina et al. 2020) and provides more than 20% of the calories consumed worldwide (Fukagawa and Ziska 2019).

Due to the world’s booming population, which may reach up to 9 billion in 2050, there is a need to increase the productivity of food crops to satisfy the rising food demand (Fahad et al. 2017). Moreover, the production of stress-tolerant cultivars is also necessary since various biotic and abiotic stresses limit crop productivity (Fahad et al. 2017). Researchers and breeders work together to solve these problems by utilizing traditional genetic engineering (Shanmugam et al. 2020, 2021), hybridization (Goulet et al. 2017), mutation breeding (Zakir 2018), polyploidy breeding (Jain et al. 2022), tissue culture (Brown and Thorpe 1995), molecular breeding, and marker-assisted selection (MAS) (Parihar and Shiwani 2022), as well as modern crop improvement technologies such as genomic selection (Heffner et al. 2009), nanotechnology (Rezaei Cherati et al. 2021), CRISPR/Cas9 technology (Liu et al. 2021), and multi-omics technologies (Yang et al. 2021). Pre-breeding enhances genetic variability by using a wider range of germplasm, acting as a connecting link between genetic resources and crop improvement (Jain and Prakash 2019). Breeders use pre-breeding or germplasm resources to select accessions with desirable traits or genes, such as high yield or its components or resistance to stresses, and incorporate them into the intermediate or modern breeding materials (Jain and Prakash 2019).

Irrespective of the crop enhancement methods used, the aim is crop improvement or the development of crops or cultivars with high yield, pest resistance, and tolerance to various abiotic stresses. Some of the desired traits or genes in rice are grain number gene Gn1a, wealthy farmers panicle gene (WFP), cold tolerance genes (qSCT-11 and qCTS12), and the anaerobic germination genes (AG1 and AG2). In addition, the wide compatibility (S5-n allele) and the restorer factor gene (Rf) are useful in hybrid rice breeding.

Panicle weight and grain number

Rice grain yield is determined by three component traits: number of panicles per plant, number of grains per panicle, and grain weight (Song et al. 2022). These agronomic traits are controlled by multiple genes or quantitative trait loci (QTLs) (Feng et al. 2021). Gn1a is one of the candidate genes that enhance grain number or yield in plants (Reyes et al. 2021). The Gn1a QTL carries a mutation in the OsCKX2 gene, which is responsible for producing the enzyme cytokinin oxidase/dehydrogenase, an enzyme that reduces the amount of cytokinin in plants (Ashikari et al. 2005). Reduced expression of this enzyme leads to the accumulation of cytokinin in the inflorescence meristems and increases the number of spikelets, thereby increasing grain production (Ashikari et al. 2005). Thus, Gn1a has excellent potential for application in breeding rice cultivars with higher yields and enhanced productivity.

The incorporation of the WFP allele (OsSLP-14) into Nipponbare increased its panicle branching, leading to higher yield (Miura et al. 2010). The overexpression of this allele has led to improved physiological changes in rice, in terms of growth period, leaf development, hormonal levels, culm composition, and grain quality (Lian et al. 2020). Integrating the WFP allele in the elite indica cultivars (PR37951, PR38012, IR04A115, IR05N412, IRRI 123, IRRI 146, IRRI 154, IRRI 156, CT5803, CT5805, IRGA 427, and Parao) has improved the panicle traits and grain yield (Kim et al. 2018).

Cold stress tolerance

Cold stress is one of the major factors limiting rice productivity worldwide (Cruz et al. 2013; Zhang et al. 2014; Sahu and Tiwary 2017). Breeding for tolerance to cold stress will be beneficial to the farmers who plant early in the season in subtropical countries, as this leads to increased crop productivity. Several cold tolerance genes have been identified (Zhi-Hong et al. 2005; Andaya and Tai 2006), two of which are qSCT-11 and qCTS-12, which are major QTLs conferring cold tolerance in the early seedling stage of rice. Other cold tolerance genes include CTB4a (Zhang et al. 2017), COLD1 (Ma et al. 2015), LTG1 (Lu et al. 2014), and QTL qLTG3-1 (Fujino et al. 2008).

Anaerobic germination

Submerged conditions gives anaerobic stress on germinating seeds. AG1 and AG2 genes have improved the growth and physiology during anaerobic germination in rice or under flooded or submerged conditions (Mondal et al. 2020b). OsTPP7 (Trehalose 6-phosphate phosphatase) enhances the anaerobic germination tolerance in rice (Kretzschmar et al. 2015). SUB1A confers tolerance to complete submergence in rice at the vegetative stage (Fukao and Bailey-Serres 2008), while SNORKEL regulates plant development and elongation to escape deep water (Oe et al. 2022). In addition, PDC-ALDH-ACS and ALDH are excellent candidate genes for flooding tolerance in rice (Miro and Ismail 2013).

Rice blast disease resistance

Biotic stresses, especially diseases, are limiting factors of rice crop productivity, and the development of disease-resistant cultivars is a major economical solution. Rice blast disease caused by the fungus Magnaporthe oryzae is one of the most damaging rice diseases worldwide (Valent 2021), as it affects rice growth, grain yield, and quality (Koutroubas et al. 2009). It causes 10–30% crop loss worldwide annually (Miller and Arkansas 2018). Genes that have provided resistance to rice blast include Pi-b, Pi-kh (Tanweer et al. 2015), Pita, Pita2, Ptr (Meng et al. 2020), Pi54 (Singh et al. 2020), and NLR (Wang et al. 2019). These genes can be used in rice breeding to develop cultivars resistant to this fungal disease (Xing et al. 2019).

Wide-compatibility and restoring ability

Intersubspecific crosses are useful in rice crop improvement, especially in the introgression of useful traits from one subspecies to another (Kato and Mii 2012). However, hybrid sterility is a major problem in these wide intersubspecific (i.e., indica × japonica) crosses. A major regulator for the reproductive barrier and cross-compatibility between indica and japonica in rice is the S5 gene (Chen et al. 2008). The S5 locus has three alleles: S5-i (indica), S5-j (japonica), and S5-n (neutral). Hybrids produced from S5-i × S5-j parents tend to be sterile (Chen et al. 2008). S5-n is a neutral allele that produces fertile offspring when crossed with the indica or japonica allele (Ji et al. 2012). To overcome the potential problem of sterility in intersubspecific hybrids, there is a need to develop parental lines that possess the wide compatibility (WC) or S5-n allele (Priyadarshi et al. 2018). Parental lines with the WC gene have the potential to produce fertile indica x japonica F1s, which can be used as highly heterotic hybrids or as progenitors of breeding populations.

In hybrid rice, the cytoplasmic male sterile (CMS) lines need to be pollinated by male plants that possess a restorer gene (Rf) (Itabashi et al. 2011) to produce fertile F1 plants. A restorer fertility gene, such as Rf4, must be present in the male parent that is used to pollinate the CMS line and produce fertile F1 seeds (Tang et al. 2014). One of the major challenges in hybrid rice breeding is the low frequency of restorers with desirable agronomic traits. Since partial restorers cannot be directly used in hybrid rice breeding, restorer lines with the Rf4 need to be identified or bred.

The objective of this study was to analyze 240 diverse rice entries from the Germplasm Resources Information Network (GRIN) for the presence or absence of genes for grain number (Gn1a), panicle weight (WFP), cold tolerance (qSCT-11 and qCTS12), anaerobic germination (AG1, AG2), blast resistance (Ptr, Pita, Piz, Pib), wide compatibility (S5-n), and restoring ability (Rf4). The phenotypic validation of the 240 rice accessions is being conducted in separate research. The results from these analyses will be useful for rice breeders interested in improving or modifying their breeding lines for grain yield and quality, stress tolerance (cold, anaerobic germination, and disease), and hybrid seed production.

Materials and methods

Plant material

Seeds of 240 diverse rice cultivars or genotypes were obtained from the GRIN genebank, which has passport data that indicates the source or country of origin of its accessions. The rice accessions used in this study originated from the top 8 countries from which the US imports rice (Brazil, Pakistan, Italy, India, Australia, Vietnam, Thailand, and China) and the top 8 countries to which the US exports rice (Colombia, Guatemala, Haiti, Honduras, Japan, Venezuela, Turkey, and Mexico). Among the rice cultivars of countries from which the US imports rice, this study evaluated 9 from India, 45 from Brazil, 6 from Pakistan, 49 from Italy, 7 from Australia, 4 from Australia (but originally bred in the United States), 8 from Vietnam, 8 from Thailand, and 5 cultivars from China. The rice cultivars of countries to which the US exports rice include 10 cultivars from Colombia, 5 from Guatemala, 13 from Haiti, 2 from Honduras, 37 from Japan, 6 from Venezuela, 3 from Turkey, and 13 from Mexico. Some cultivars like Baldo, Veneria, Ribe, Cica-7, and Cica-8 are grown in two countries. For example, Baldo is grown in Italy and Japan (Russo and Callegarin 2007). Veneria and Ribe are grown in Italy and Turkey (Surek 1990), whereas Cica-7 and Cica-8 are grown in Brazil and Colombia (Spijkers 1983). Another rice cultivar, IR 22, is grown in Venezuela and Brazil (Brown 1969). Some cultivars (Caloro, Caloro II, Calrose, and Lemont) were developed in the US but also grown in Australia (Blakeney et al. 1996). Sixteen cultivars developed in rice-growing states of the US (Cheniere, Jupiter, L-203, M-401, Presidio, Rex, Thad, Titan, Roy J, Wells, ARoma 17, Cocodrie, Lakast, Diamond, MM17, and M-202) served as check cultivars.

DNA extraction, polymerase chain reaction, and gel lectrophoresis

The 240 accessions were planted in the Texas A&M AgriLife Research Center at Beaumont in the summer of 2020. Each accession was planted in a 3-row plot that was 2.4 m long with a row spacing of 28 cm. At the 4-leaf stage, a leaf from each accession was sampled and prepared for DNA extraction and MAS to evaluate their genes for panicle size or grain number (Gn1a and WFP), cold tolerance (qSCT-11 and qCTS12), anaerobic germination (AG1, AG2), blast resistance (Ptr, Pita, Piz, Pib), wide compatibility (S5-n), and restoring ability (Rf4). DNA from each accession was extracted using the NaOH ‘quick and dirty’ method (Collard et al. 2007). One hundred (100) μL of 0.5 M NaOH and 800 μL of 100 mM Tris solution, pH 8.0, was added to each leaf sample. The samples were placed in 96-well deep well plates with two grinding balls in each well and ground for 3 min using a SPEX MiniG homogenizer (SPEX SamplePrep, Metuchen, NJ, USA) and centrifuged 139 g (RCF) for 5 min (Collard et al. 2007). The supernatant containing the DNA was collected and stored at − 20 °C.

For each 20 μL volume of polymerase chain reaction (PCR) solution, 0.2 μL of DNA solution was transferred to a 96-well PCR plate along with 0.3–0.4 μL of both reverse and forward primers (10 µM concentration) for specific markers, 10 μL of DNA master mix (New England Biolabs Quick-Load® Taq 2X Master Mix), and 7.1–7.2 μL of ddH2O. PCR was performed using Bio-Rad T100 thermal cyclers (Bio-Rad Laboratories, Hercules, CA, USA). The forward and reverse primers used for detecting specific markers are listed in Table 1, while the PCR profile applied for each gene is shown in Table 2.

Table 1 Forward and reverse primers used for the detection of specific markers
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Table 2 PCR conditions used for the amplification of genes using specific primers
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The PCR products were resolved using 1% agarose gel electrophoresis stained with ethidium bromide, in which the presence or absence of a gene marker can be determined by viewing in a Gel Documentation system-BL (Axygen, Corning Brand, United States) under UV (365 nm) light.

Results

Considerable allelic variation was observed between the 240 accessions in the specific genes we studied in this project (Fig. 1, Table 3). Among the 240 accessions, 192 (80.0%) have the Gn1a gene, 168 (70.0%) possess the qSCT-11 cold tolerance gene, 139 (57.9%) carry the Rf4 gene, 152 (63.3%) have the qCTS12 cold tolerance gene, 87 (36.25%) have blast resistance genes, and 84 (35.0%) possess the anaerobic germination tolerance AG1gene. As for the other genes, 44 (18.3%) possess the WC gene, and 16 (6.6%) carry the AG2 gene. None of the 240 entries possess the WFP gene.

Fig. 1
figure 1

Agarose gel images of the allelic specific markers used in this study. The first 18 lines (1-Loto, 2-Akebono, 3-Nakate-Shinsenbon, 4-Reiho, 5-Koshihikari, 6-IRGA 408, 7-BR-IRGA 414, 8-MM17, 9-Yunnan Bir, 10-Calrose, 11-Akinishiki, 12-Titan, 13-EMBRAPA 6 CHUI, 14-RD 6, 15-M-401, 16-JUPITER 17-Hoyoku, 18-Reimei) are shown as the representative lines in this study (L ladder, M missing results, + indicates presence of the respective allele and − indicates the absence of the respective allele)

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Table 3 Genotypic data for yield-related and stress tolerance traits of 240 rice accessions from countries where the United States imports and exports rice
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Cultivars of countries from which the US imports rice

Among the countries from which the United States imports rice, cultivars from Italy and Brazil possess the most cold tolerance genes (Table 4). Italy and Brazil had 35 and 30 cultivars, respectively, with the qSCT-11 gene, and had 37 and 24 cultivars, respectively, with the qCTS-12 gene. On the other hand, only two cultivars from Vietnam possess the qSCT-11 gene, and none of the US-made cultivars grown in Australia possess the qCTS-12 gene.

Table 4 Countries from which the US imports rice and their number of accessions possessing favorable genes
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Most rice cultivars from Brazil possess the anaerobic germination genes (AG1 and AG2), which improve germination in wet-seeded conditions. Twenty-one and five rice cultivars from Brazil possess the AG1 and AG2 genes, respectively. Similarly, 18 rice cultivars from Italy possess the AG1 gene.

Brazil had the most rice cultivars with blast resistance genes. Piz was the most common blast resistance gene found in the 240 rice cultivars evaluated in this study.

Cultivars of countries to which the US exports rice

Most rice cultivars of Japan possess the cold tolerance genes (qSCT-11 and qCTS-12) (Table 5). Twenty-six possess the qSCT-11 gene, and 26 possess the qCTS-12 gene. Honduras had the least number of cultivars with cold tolerance genes. Two cultivars of Honduras possess the qSCT-11 gene, and another two possess the qCTS-12 gene.

Table 5 Countries to which the US exports rice and their number of accessions possessing favorable genes
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Most rice cultivars of Japan and Colombia possess the anaerobic germination and blast resistance genes. Twelve rice cultivars of Japan possess the AG1 gene, and two of Colombia possess the AG2 gene.

Eight rice cultivars of Japan (temperate) and eight of Colombia (fully tropical) possess blast resistance genes. Out of these, two cultivars from each country possess two blast resistance genes.

Discussion

Cold tolerance

Among the major abiotic stresses, the incorporation of cold tolerance is an important breeding objective, especially in temperate regions where it is cold during planting. Several QTLs contributing to cold tolerance in the japonica alleles were detected, suggesting an important role of japonica germplasm in breeding for low-temperature tolerance in indica lines (Ranawake et al. 2014). A major QTL conferring cold tolerance, qSCT-11, is linked to the microsatellite marker RM202 in chromosome 11 (Zhi-Hong et al. 2005). The possession of cold tolerance genes will allow for better rice vigor when planted early during the rice crop season, even when the temperatures are still low (14 °C/12 °C) (Najeeb et al. 2020). Planting early can also enable the rice crop to avoid high summer temperatures, which increases maintenance respiration and reduces grain yield and quality (Li et al. 2021). The QTL qCTSL-12-1 confers seedling stage cold tolerance, which is enhanced when other cold tolerance QTLs co-segregate with it (Biswas et al. 2017). The QTL network for cold tolerance at the reproductive stage was also studied using the cold tolerance (CT) introgression lines of rice (Liang et al. 2018). Identification of novel QTLs for cold tolerance during the fertilization (CTF) stage has been studied, and these can be used to develop rice lines with enhanced CTF levels using MAS (Shinada et al. 2014).

In general, most rice cultivars with cold tolerance genes were present in temperate and sub-tropical countries, with a few grown in fully tropical countries. Rice cultivars of Japan (temperate), Italy (sub-tropical), and Brazil (partially tropical) possess the most cold tolerance genes, while those of Vietnam (fully tropical), Australia (partially tropical), and Honduras (fully tropical) possess few to none of the cold tolerance genes. Developing rice cultivars with enhanced cold tolerance results in better seedling vigor when planted early during the rice crop season in temperate regions. Cold tolerance also results in good grain filling when cold fronts occur late in the crop season, thus preventing grain yield reduction.

Research has identified QTLs associated with low-temperature tolerance during the germination and bud stages of rice and have identified 6 QTLs out of the 11 tested to show a total phenotypic variance explained (PVE) of 5.13–9.42% during the germination stage and 5 QTLs showed a total PVE of 4.17–6.42% during the bud stage (Yang et al. 2020). In another study, QTLs associated with cold tolerance at the seedling stage were identified with a phenotypic variation (R2) ranging from 6.1 to 16.5% (Kim et al. 2014). Similar to the above study, QTL qSCT-11 conferring cold tolerance at the early seedling stage in rice was identified with a PVE of up to 30% (Zhi-Hong et al. 2005), while the PVE by qCTS12 was over 40% (Andaya and Tai 2006).

Anaerobic germination

Another important abiotic stress that reduces crop productivity is flooding or anaerobic stress during germination. Around 25% of rice crops in Asia are damaged yearly due to flooding (Loo et al. 2015). AG1 and AG2 QTLs in the rice lines make them more tolerant to submerged conditions by showing higher seedling growth and faster plant elongation when the dry seeds were planted in flooded soil (Mondal et al. 2020b). Four japonica backcross lines were developed by incorporating AG1 and AG2 genes from an indica KHO (Khao Hlan On) into a japonica Dongan by marker-assisted backcross breeding (Kim et al. 2019). The introgression of AG1–AG2 QTLs into rice did not negatively affect the germination rate and growth of rice seedlings subjected to flooding stress (Mondal et al. 2020a).

In this study, the rice cultivars from countries where direct wet seeding or direct seeding in saturated soil is a widely adopted practice possess the anaerobic germination genes, such as Brazil (Fischer and Antigua 1996), Italy (Hill et al. 1991), Japan (Ye and Qian 2019), and Colombia (Arango-Londoño et al. 2020). Rice breeders can use the cultivars that possess AG1 and AG2 QTLs, as identified by this study, as donors to develop new cultivars with tolerance to submergence, flooding, or anaerobic germination stresses.

A study that characterized a major QTL for anaerobic germination (AG2) has also shown that the total PVE ranged from 9.9 to 39.7% (Tnani et al. 2021). A high-density genetic mapping study has identified QTLs for anaerobic germination in rice with a total PVE ranging from 0.34 to 11.17% (Liang et al. 2022). In a study that evaluates the anaerobic germination in rice, a major QTL AG1 showed a total PVE of 64.3% (Kuya et al. 2019).

Rice blast resistance

Rice blast disease, caused by the fungal pathogen Magnaporthe oryzae, has been estimated to contribute 30% of yield loss in rice worldwide (Nalley et al. 2016). Rice blast can be found in all rice-growing regions of the United States, including Arkansas, California, Louisiana, and Texas (Greer and Webster 2001; Wang et al. 2017). Due to the widespread presence and impact of the disease, millions of dollars are spent annually to mitigate its effects (Nalley et al. 2016).

Rice blast resistance genes, such as Pi-ta, Pi-b, and Pi-k, confer resistance to this disease and are present in rice cultivars, including IR64, Saber, and Kanto51 (Ashikawa et al. 2012; Roychowdhury et al. 2012a, 2012b; Meng et al. 2019). Integrating one or more R-genes into rice cultivars using marker-assisted backcrossing (MABC) has been used to incorporate R-genes such as Pi-54 in Samba Mahsuri (Kumar et al. 2018), Pi54 and Piz-5 in Basmati rice PRR78 restorer line (Singh et al. 2012), Pi1, Pita, and Pi54 into aromatic Mushk Budgi (Khan et al. 2018), Pi9 or Pi2 in restorer line Hui 316 (Tian et al. 2019) and Pi-b and Pi-kh into MR218 (Tanweer et al. 2015).

The occurrence of rice blast disease is high in tropical and humid regions (Kirtphaiboon et al. 2021), but it can also cause severe yield losses in temperate regions (Nalley et al. 2016). Blast-resistant rice cultivars are bred and adopted in countries where blast is a major constraint, such as Brazil (Guimaraes et al. 2000), Colombia (Victoria and Martinez 2009), and Japan (Kawasaki-Tanaka et al. 2016), as observed in this study.

Inheritance research conducted on the US rice cultivars for characterizing genes that show resistance to the pathotype Magnaporthe oryzae has identified 3 Pi- resistance genes (pi-n, pi-g, and pi-d), which were resistant to blast races IB-54, IG-1, and IB-1, respectively, and were identified in Brazos (pi-n), Gulfrose (pi-g) and Lebonnet (pi-d) cultivars (Marchetti 1987). Another unnamed Pi gene resistant to the blast race IB-49 was identified in the blast-differential cultivar Usen (Marchetti 1987). The molecular analysis and phenotypic validation of blast resistance genes Pita and Pita2 indicate that they confer resistance to different races (Mo-ni-0066, Mo-ni-0052, Mo-nwi-32) of rice blast fungus (Shikari et al. 2013). Similarly, the Pi-z gene confers resistance to a wide range of races of rice blast fungus, including an avirulent strain (IE1k) and two virulent strains (IB33, IB49) (Roychowdhury et al. 2012a, 2012b). Similarly, the Pi-b gene in rice has shown resistance to different blast races, including IE1k, IB1, and IB54 (Roychowdhury et al. 2012a, 2012b). An allelic variant of the broad spectrum blast resistance gene Ptr in weedy rice has been reported to show resistance to the most virulent blast race IB-33 (Zhao et al. 2022a).

Panicle size and grain number

Rice grain productivity links various phenotypical traits, such as tiller number, grain filling, grain size, and grain number, to the increased yield of the plants (Lu et al. 2022). Instead of just selecting for high grain yield alone, the selection of desirable plant types or yield-related alleles is gaining popularity in plant research and breeding programs. The wealthy farmer’s panicle (WFP) gene shows the potential to increase grain yield, as its introgression into elite indica rice cultivars (e.g., PR37951, IR04A115, IRRI 123, CT5803, IRGA 427, Parao) increased the grain number per panicle (GNPP) and yield significantly (Kim et al. 2018). The incorporation of Gn1a from high-yielding indica cultivar Habataki into temperate japonica cultivars Koshihikari and Sasanishiki improves their grain number per panicle by 21% and 28–37%, respectively (Ashikari et al. 2005; Ohsumi et al. 2011). In addition, the yield of the elite rice Kongyu 131 was improved by the Gn1a locus (Feng et al. 2017). The QTLs Gn1a and WFP were introgressed in selected NERICA cultivars (NERICA 1, NERICA 4, and NERICA 6) through MABC (Reyes et al. 2021). These investigations indicate the strong possibility of increasing the yield potential of rice cultivars through allele mining and its application.

When Gn1a was introgressed into an elite japonica rice cultivar Kongyu 131, grain yield increased by up to 11.9% (Feng et al. 2017). In another study, a mutation in the RGN1a (Regulator of Grain Number 1a) gene caused a decrease in the grain number, primary branch number per panicle, secondary branch number per panicle, and panicle length by 37.2, 27.8, 51.2 and 25.5%, respectively (Zhang et al. 2022). Similarly, it has been reported that WFP explains 35.7% of the phenotypic variation in primary branch number (Miura et al. 2010).

Wide compatibility and restorer genes

Wide-compatible rice cultivars, when used as parents in japonica × indica crosses, produced fertile hybrids (Vijayakumar et al. 1999). There is an improvement in embryo-sac fertility to 14.7–32.9% in these hybrids when the S5-n allele is in one of the parental lines (Mi 2016). A restriction fragment length polymorphism analysis of the wide compatibility genes in rice has shown that S5n conferred a phenotypic variance of 32.3% associated with spikelet fertility (Yan et al. 2000). A new QTL associated with the wide compatibility locus in inter-subspecific hybrids of rice has been identified and is reported to have a PVE of 17.9% and 18.4% in pollen and spikelet fertilities, respectively (Zhao et al. 2022b). Genetic analysis indicates that S5-interacting genes regulate hybrid sterility in rice and explain phenotypic variations of 7.02% (QTL qSIG3.1) and 10.44% (QTL qSIG5.1) (Rao et al. 2021).

The implementation of Rf4-specific markers can lead to the precise identification of restorer lines, thereby supporting the importance of transferring these genes into elite cultivars through MAS in a hybrid rice breeding program (Pranathi et al. 2016). The significant association of the novel Rf4 SNP marker with the WA-CMS restorer lines supports the molecular identification of restorers (Chen et al. 2017), differentiating them from potential maintainer lines. Fine mapping of Rf3 and Rf4 fertility restorer loci of wild abortive cytoplasmic male sterility (WA-CMS) in rice have identified a PVE of 66–72%, thus conferring their use in developing a marker for the identification of fertility restorers for WA-CMS (Balaji Suresh et al. 2012). A genetic analysis study of novel fertility restoration genes (qRf3 and qRf6) has shown a fertility restoration of 16.56% and 15.12%, respectively (Cai et al. 2023). GWAS revealing the genetic basis of fertility restoration in CMS-WA and CMS-HL in xian/indica and aus accessions in rice reported that different loci for pollen fertility; BSS (seed-setting rate of bagged panicles) and NSS (seed-setting rate of natural panicles) showed a phenotypic variation explained ranging from 2.9 to 48.5% for CMS-WA and 6.4–31.1% for CMS-HL (Li et al. 2020).

Conclusion

Several factors affect rice productivity worldwide, and breeders are developing rice cultivars that possess multiple desirable characteristics, such as yield-contributing traits and tolerance to various biotic and abiotic stresses, without compromising its nutritional quality. Conventional and traditional breeding techniques are very time-consuming and laborious. However, smart technologies such as MAS and gene pyramiding are now used to quickly screen and develop cultivars possessing the desirable alleles of important traits. This study used marker-assisted selection to screen rice cultivars of several countries based on valuable traits. The results identified cultivars useful as donor parents in crossing nurseries for specific traits to breed new cultivars or for pyramiding desirable traits. This study helps US rice breeders to develop cultivars with useful genes (yield-related traits, abiotic stress tolerance, and disease resistance), making them more productive and competitive in the rice industry.