Unveiling gene effects and yield determinants in CMS-based rice hybrids through heterosis and Genotype by Yield* Trait (GYT) biplot

Introduction

Rice (Oryza sativa L.) is a self-pollinated, annual grass from the genus Oryza of the Poaceae family, having 2n = 24 chromosomes. It originated in Southeast Asia, where it exhibits significant genetic diversity (Chang, 1976) [7] . It is a widely consumed crop prized for its high content of protein, carbohydrates, vitamins, and minerals, along with low-fat content (Ullah Zaid et al., [38, 12, 1, 34] . The projected global population will rise from 7.7 billion to 9 billion by 2035, so rice demand will be expected to increase from 763 million tonnes to 850 million tonnes. However, rice yield has only increased by about 1% annually over the past decade, despite being the highest among producing nations (Gaballah et al., 2022) [16] . Rice breeders are having a hard time improving rice production because of more environmental problems and a growing population (Chen et al., 2020) [8] . To cope with this yield penalty, exploiting heterosis using superior genotypes is a potential solution to develop hybrids through crossing genetically distinct parents (Khush, 2013; Huang et al., 2015; Vaz Mondo et al., 2016) [22,19,39] . Heterosis has notably contributed to food security and environmental benefits (Duvick, 1999) [11] . CMS-based hybrid rice varieties offer yield gains of 20-25% over pure lines, making rice a commercially viable crop (Rather et al., 2001; Abebe et al., 2017; El-Namaky, 2018; Liao et al., 2021) [33,2,13,25] . The Genotype by Yield * Trait (GYT) biplot denotes a novel, comprehensive, and emphatic method for genotype evaluation across multiple traits. It graphically ranks genotypes by their combined yield and target trait strata, elucidating their strengths and weaknesses. Selection results depend merely on the traits analyzed; therefore, only indispensable traits for cultivar success should be included in GYT biplot analysis (Yan & Fregeau-Reid, 2018) [40] . Material and methods Experimental materials, site, and experimental design In this experiment, three WA-CMS rice lines were crossed with twenty testers in a modified line × tester (MLT) mating design (Arunachalam 1974) at the Rice and Wheat Research Centre (RWRC), Malan, Himachal Pradesh, during kharif-2022. Next year, in kharif-2023, 60 F 1 crosses, 20 testers, and three CMS lines were transplanted along with maintainer lines in a Randomized Block Design (RBD) with three replications. The RWRC Malan is situated between 32°01'N latitude and 76°01'E longitude at an altitude of 950 m above mean sea level (AMSL). The soil has a silty clay loam texture with a p H range of 5.8 to 6.0, which is well suited to cultivating rice in the Himalayan region.

Observations recorded

The study examined several phenological and agronomic key traits, including days to 50% flowering (DTF), days to maturity (DM), plant height (PH), total tillers plant -1 (TTPP), effective tillers plant -1 (ETPP), panicle length (PL), spikelets panicle -1 (SPP), grains panicle -1 (GPP), pollen fertility (PF), spikelet fertility (SF), grain yield plant -1 (GYPP), 1000-grains weight (TGW), grain length (GL), grain breadth (GB) and to breadth ratio (LBR). The detailed information of the studied material is depicted below in Tables 1 and2.

Statistical analysis

Analysis of variance (ANOVA) was performed using Panse & Sukhatme, (1985) [31] ; narrow-sense heritability was calculated using Singh & Chaudhary, (1977) [37] , while combining ability (Arunachalam, 1974) [5] and relative and standard check variety heterosis were studied using Singh and Chaudhary's (1977) [37] methods. For data analysis, TNAUSTAT software (version 2014) [26] was used, whereas GYT biplots, corrplot, heatmap, and dendrogram were generated using RStudio (version R 4.5.3 (March, 2026)) [9] , and a violin plot was created using the Data Tab online tool at https://datatab.net/statistics-calculator/charts/create-boxplot.

Results

Analysis of variance and per se performance

Findings of ANOVA marked significant variations (*p<0.05) across all traits, with notable differences observed among lines, testers, line × tester, and crosses. Significant differences were also found among parents and parents vs. crosses for most of the traits, except for grains panicle -1 and pollen viability. To depict the data, a violin plot was created based on the mean and range performances of the studied traits. Flowering and maturity periods of assorted parents and hybrids were examined, revealing that the average days to 50% flowering and maturity time ranged from 91.36 to 120.61 days. Hybrids IR 79156A×VL 221 and IR 58025A×HPR 1156 (80 days), were the earliest flowering hybrids, followed by IR 79156A×Naggardhan (83 days) and IR 68897A×Himalaya II (84 days), respectively. The average plant height was recorded 109.62 cm, with the shortest parent being Himalaya I at 83.67 cm and the shortest hybrid, IR 68897A×HPR 1068 (84.33 cm), followed by IR 68897A×HPR 2840 (87.13 cm) and IR 68897A×Himalaya I (87.33 cm). The mean of total and effective tillers plant -1 was 9.26 and 8.76, respectively, with hybrids depicting a higher average of effective tillers. The average panicle length general mean was 25.18 cm, generally longer in hybrids, with the parent Kasturi having the longest panicle at 29.67 cm. Among hybrids, IR 79156A×HPR 2720 had the longest panicle of 29.40 cm, followed by IR 79156A×Kasturi (29.10 cm) and IR 79156A×HPR 2866 (28.65 cm). The parent genotype HPR 2795 (188.07) had the highest spikelets panicle -1 and grains panicle -1 , while the hybrid IR 58025A×HPR 2720 (208.67) had the highest spikelets panicle -1 . Pollen viability for parents ranged from 81.91% to 99.29%, while spikelet fertility varied from 48.98% to 94.34%. Hybrids showed average pollen viability of 79.08% and spikelet fertility of 60.44%. The parent, China 988 (99.29%), had the highest pollen viability, and the highest spikelet fertility was observed in Naggardhan (94.34%). Maximum grain yield plant -1 was observed in the hybrid, IR 79156A×Naggardan (19.46 g), and the parent, IR 79156A (17.70 g). The general mean value for 1000-grain weight was 22.96 g, while the weight for parents was 23.78 g and 22.64 g for hybrids. Grain length varied from 5.12 mm to 7.69 mm in parents and 5.58 mm to 7.67 mm in hybrids. The best-performing hybrids for grain breadth were IR 58025A×HPR 2840 (2.39) followed by IR 58025A×HPR 2795 (2.26), IR 79156A×Varundhan (2.20), IR 68897A×HPR 2143 (2.18), and IR 68897A×HPU 741 (2.18). The average L: B ratio for parents was 3.44 mm, and the best-performing hybrids for grain length were IR 58025A×HPR 2720 (4.74) (Table 3 and Figure 1).

Genetic analysis

The study revealed that additive variance in traits was lower than dominance variance. Spikelet fertility (15.31) had maximum additive variance, followed by L:B ratio (10.49), spikelets panicle -1 (8.51), grain yield plant -1 (8.25), plant height at maturity (7.58), and spikelets panicle -1 (4.22), respectively. For grain breadth (0.001), L:B ratio (0.001), grain length (0.02), total tillers plant -1 (0.04), effective tillers plant -1 (0.04), panicle length (0.02), days to 50% flowering (0.76), spikelet fertility (0.48), grain yield plant -1 (0.06), and thousand grain weight (0.18), there was the lowest additive variance. The highest GAM was found in pollen viability (57.72), which was significantly high (>20%), followed by spikelet fertility (31.25), grains panicle -1 (30.60), grain yield plant -1 (30.54), spikelets panicle -1 (28.75), effective tillers plant -1 (27.03), total tillers plant -1 (25.52), plant height at maturity (24.24), L:B ratio (20.34), 1000-grain weight (20.24), and grain breadth (20.06), respectively (Table 4). Traits like days to 50% flowering (1.85), panicle length (5.63), and grain length (6.0) showed low (<10%) GAM, indicating a mix of additive and non-additive gene effects. It is evident from the table that female parents played an important role in plant height at maturity (39.85%), indicating a predominant maternal influence for this trait. Male parents contributed a larger proportion for some important traits, viz., days to 50 percent flowering (72.74%), days to maturity (68.82%), 1000-grain weight (52.63%), and total tillers plant -1 (45.73%), revealing the predominant paternal influence for these traits. For the remaining traits, viz., effective tillers plant -1 (45.97%), panicle length (49.43%), pollen viability (44.34%), spikelets panicle -1 (53.07%), grains panicle -1 (43.61%), spikelet fertility (60.02%), grain yield plant -1 (53.10%), grain length (52.50%), grain breadth (60.53%), and L:B ratio (67.08%), the contribution of maternal and paternal interaction (female × male) was observed to be highest in proportion, indicating that the concerned characters were influenced by nonadditive gene action. The line × tester interactions revealed that days to maturity (68.82%) had the greatest effect due to the paternal effect, and the L:B ratio (67.08%) again due to line × tester interactions (Table 4).

Combining Ability

The analysis of variance (ANOVA) for combining ability across studied traits revealed significant differences among lines, testers, and interactions, with specific combining ability variances exceeding general combining ability variances, indicating non-additive gene action. Negative combining ability is better for the days to flowering trait, with no significant negative effects observed among the CMS lines. The highest negative GCA effect was observed in the Himalaya Ⅱ (-6.87) parent, followed by VL 221 (-5.98) and HPR 1156 (-4.98). Five hybrids early flowered and displayed significant negative SCA effects, with the highest being IR 79156A×VL 221 (-5.67). The CMS line IR 68897A (-0.64) was the best general combiner for early maturity. The highest negative GCA effect was observed in HPR 1156 (-11.39), followed by HPR 2880 (-10.62) and Himalaya Ⅱ (-9.51). The highest negative GCA effect was observed in IR 79156A×HPR 2749 (-10.94), followed by IR 58025A×HPR 2720 (-10.47). The study found that CMS lines, such as IR 68897A (12.08) and IR 58025A (-3.04), had a significant negative GCA effect on plant height, and among testers, HPR 1068 (-16.20) showed the highest negative GCA effect. The highest negative SCA effect was observed in IR 58025A×HPR 2720 (-28.57), followed by IR 79156A×VL 221 (-22.21) and Himalaya Ⅰ (-20.08). CMS line IR 79156A (0.61) for TTPP and (0.58) for ETPP had a significant positive GCA effect, while tester HPR 2749 (2.79) for TTPP and (2.82) for ETPP had the highest positive GCA effect, followed by Kasturi and HPU 2216. Hybrid IR 79156A×HPR 2749 depicted a maximum SCA effect (2.49) for TTPP and (2.44) for ETPP. The study identified seven hybrids with significant positive GCA effects for panicle length, with the highest effect observed in IR 58025A×HPR 2795 (2.12), followed by IR 79156A×Kasturi (2.00). CMS line IR 58025A (2.87) was identified as a significant contributor to the GCA effect for spikelets panicle-1. Among the seven testers, HPR 2720 (30.65) depicted the highest significant positive GCA effect. Ten hybrids revealed significant positive SCA effects for spikelets panicle-1, maximum in IR 79156A×HPR 2866 (33.04), followed by IR 58025A×HPR 2703 (29.63), IR 79156A×Himalaya I (26.57), IR 68897A×Varundhan (23.84), and IR 58025A×HPR 2143 (16.54). For the trait GPP, a significant positive GCA effect was observed in the female parents IR 58025A (4.78) and IR 79156A (7.45) and in the male parent HPR 2720 (31.58). Significant SCA effect was noted in twenty-two hybrids, with the highest desirable SCA effect in IR 68897A×HPR 2720 (25.53), followed by IR 68897A×HPU 2216 (24.62), IR 68897A×VL 221 (23.81), IR 68897A×Naggardhan (21.4), and IR 58025A×HPR 2703 (20.5). The female parent IR 68897A (13.05) showed a significant positive GCA effect for pollen viability, while the male parent HPR 2840 (14.99) exhibited the highest GCA value. Notably, the hybrid IR 68897A×Varundhan (42.69) demonstrated the maximum specific combining ability (SCA) effect for pollen viability, followed by IR 68897A×Naggardhan (39.97), IR 68897A×VL 221 (28.97), IR 79156A×HPR 1068 (25.31), and IR 79156A×HPR 2795 (24.54). For spikelet fertility, female parents IR 58025A (2.27) and IR 79156A (3.86) depicted significant positive GCA effects. Among the male parents, nine revealed significant positive GCA effects, with HPU 2216 having the highest (11.28), followed by HPR 2866 (8.48) and HPR 2720 (6.56). Twenty-three hybrids showed significant positive SCA effects for spikelet fertility, with maximum in IR 58025A×Varundhan (25.21), followed by IR 58025A×HPR 2866 (13.3), IR 68897A×HPR 2720 (11.99), IR 79156A×HPR 2143 (10.71), and IR 79156A×HPR 2795 (10.48). The CMS lines IR 79156A (0.43) and IR 58025A (0.38), along with testers Kasturi (3.24) and HPU 2216 (2.42), were identified as significant positive contributors to GCA. For specific combining ability effects, twenty-two hybrids were recognized as effective combiners for grain yield plant -1 , and the hybrid IR 79156A×Naggardhan (4.17) was identified with highest positive SCA effect, followed by IR 68897A×Kasturi (3.60), IR 58025A×HPR 1156 (2.67), IR 58025A×Varundhan (2.59), and IR 68897A×HPU 2216 (2.43). For 1000-grain weight, CMS line IR 79156A (0.48) and IR 68897A (0.53) showed significant positive GCA effects. Among the male parents, HPR 2880 showed the highest positive GCA effect (13.96), followed by HPR 2866 (2.81) and HPR 2749 (1.78). Twelve hybrids depicted significant positive SCA effects, with the highest recorded by IR 58025A×Himalaya Ⅰ (3.48), followed by IR 68897A×HPR 2749 (3.28), IR 58025AVarundhan (2.74), IR 68897A×Naggardhan (2.47), and IR 79156A×Kasturi (2.41). Research results revealed that the positive general combining ability (GCA) effect for grain length was significant only among male parents, with the highest effect in parent HPR 2749 (0.40). The maximum specific combining ability (SCA) effect was observed in nine hybrids, peaking with IR 58025A×HPR 2720 (0.7), followed by IR 79156A×HPR 2840 (0.63), IR 79156A×HPU 2216 (0.59), IR 58025A×HPR 2143 (0.51), and IR 68897A×China 988 (0.46). Among female parents, IR 58025A (-0.4) and IR 68897A (-0.1) depicted significant negative GCA effects for grain breadth. Among male parents, nine showed significant negative GCA effects, with HPR 2720 (-0.19) followed by HPR 2703 (-0.14), HPR 1068 (-0.11), and VL 221 (-0.11). A total of 28 hybrids displayed significant negative SCA effects, with the most significant negative found in IR 68897A×Varundhan (-0.26), followed by IR 68897A×HPR 2840 (-0.24), IR 79156A×HPR 2840 (-0.24), and IR 68897A×HPR 2795 (-0.22), respectively. The CMS line IR 58025A (0.13) exhibited a significant positive general combining ability (GCA) effect for the L: B ratio, with seven male parents demonstrating notable positive GCA effects. Additionally, fifteen hybrids displayed significant specific combining ability (SCA) effects. Parent Kasturi (0.34) recorded the highest GCA effect for the L:B ratio, while the hybrid IR 58025A×HPR 2720 (0.88) had the greatest SCA effect, followed by IR 79156A×HPR 2840 (0.87), IR 68897A×Varundhan (0.76), IR 79156A×Naggardhan (0.49), and IR 58025A×VL 221 (0.46).

Heterosis

Heterosis for days to 50 percent flowering in F 1 s varied from -7.89 (IR 58025A×HPR 1156) to 13.73% (IR 79156A×Himalaya Ⅰ) for midparents and from -8.05 (IR 79156A×VL 221) to 17.24% (IR 58025A×HPR 2840) compared to the standard check variety HPR 2880 (Table 5). No hybrids exhibited significant negative mid-parent heterosis, though IR 79156A×VL 221(-8.01%) showed a notably significant negative heterosis compared to the standard check. The hybrid IR 79156A×VL 221 (-14.76%) exhibited the highest significant negative mid-parent heterosis for early maturity, followed by IR 58025A×HPR 2143 (-12.57%), IR 79156A×HPR 2703 (-12.42%), IR 79156A×Himalaya II, and IR 58025A×HPR 1156 (-11.82%). Additionally, IR 68897A×HPR 2840 (-9.52%) showed significant negative standard check variety heterosis, followed by IR 79156A×Himalaya II (-5.95%) and IR 58025A×HPR 1156 (-5.65%). The heterotic responses of F 1 hybrids for plant height ranged from -31.27 to 32.65% for the mid-parent and -26.5 to 25.86% over the standard check variety (Table 5). The hybrid IR 68897A×HPR 2703 exhibited the maximum significant negative mid-parent heterosis at -31.27%, followed by IR 68897A×HPR 2795 (-26.44%), IR 79156A×VL 221 (-25.99%), and IR 58025A×HPR 2720 (-24.77%). ). In accordance with the GCA/SCA effect, per se performance and standard check variety heterosis for the top 3 economic parents and top 5 economic hybrids for grain yield plant -1 are depicted in Table 6. 2 illustrates the correlations among the studied variables. constitutes the main source of primary healthcare in most rural populations, especially in many African countries, due to its affordability and availability. However, as the usage of these medicinal plants becomes more widespread around the world, there are questions and misgivings about the quality, efficacy, and safety of the products utilized in the health sector [2,3,4] . These concerns have hampered the sensible use and validation of bio-products derived from these herbs for the treatment and management of disorders [5] . The validation and quality assurance of medicinal plant products has been hampered by a lack of or incorrect plant identification. Cluster analysis: Cluster analysis was conducted using Euclidean distance and Ward's algorithm in RStudio software version 4.3.2 2024 to group the genotypes (parents and hybrids). As shown in Figure 3, all genotypes were classified into four clusters. Additionally, a heatmap was created to illustrate the relationship between the genotypes (parents and hybrids) and the studied traits (Figure 4)

Genotype by yield*trait (GYT) biplot analysis

The genotype by yield-trait (GYT) biplot ranks genotypes by their ability to combine yield with various breeding objectives, such as agronomic traits, grain quality, processing quality, nutritional quality, or disease resistance. It also displays their trait profiles, highlighting strengths and weaknesses. Figure 5 shows that all combinations of yield traits positively correlate with one another, as they share yield components and form acute angles between the vectors. The average tester coordinate (ATC) showed that hybrids G46, G52, G64, G67, G1, G25, and others were superior, while hybrids G55, G32, G62, G36, G12 and several more were inferior (Figure 6). To rank the genotypes by performance, a line was drawn through the biplot origin.

Using the superiority index, the hybrids were ranked by yield trait combinations from top-performing hybrids to poor performers: G46 > G52 > G64 > G1 > G67 > G25 > G29> G8 > G47, with others similarly ranked as shown in the figure. The worst-performing hybrids were G14 > G15 > G82 > G12 > G39 > G77 > G78, and others ranked similarly (Figure 7). 3). The GYT biplot was based on singular value decomposition of trait-standardized data ("Scaling=1, Centering=2") and trait-focused singular value partition ("SVP=2") 3). The GYT biplot was based on singular value decomposition of trait-standardized data ("Scaling=1, Centering=2") and trait-focused singular value partition ("SVP=2") 3). The GYT biplot was based on singular value decomposition of trait-standardized data ("Scaling=1, Centering=2") and trait-focused singular value partition ("SVP=2")

Significant variations among the traits evince improvement through both selection and hybridization (Adhikari et al., 2018) [3] . The per se performance of parental lines frequently influences the performance of the resulting hybrids (Gilbert, 1958) [18] . Maternal parent effect (39.85%) on plant height was in sync with Faiz et al., (2007) [14] . Traits like DTF (72.74%), DM (68.82%), TGW (52.63%), and TTPP (45.73%) influenced the paternal parent, consistent with findings of Ghorbani et al., (2014) [17] and Montazeri et al., (2014) [28] . σ²SCA exceeded σ²GCA for all the studied traits, indicating non-additive gene effects, where dominance variance outweighs additive variance, which was consistent with findings of Sari et al., (2020) [36] . In this study, GCA effects of the lines showed variability, with the tester Kasturi exhibiting significant positive effects on GYPP. These effects were further enhanced by factors such as ETPP, TTPP, GL, and L:B ratio. In contrast, CMS lines IR 79156A (0.43) and IR 58025A (0.38) also demonstrated significant positive GCA effects on GYPP. This study, consistent with Yuga, (2018) [41] , found no single parent exhibiting optimal GCA for all traits examined. CMS line IR 79156A exhibited the highest GCA for TTPP (0.61), ETPP (0.58), PL (0.93), GPP (7.45), TGW (0.48), and SF (3.86). The hybrid IR 79156A×Naggardhan (4.17) displayed the highest SCA effect for GYPP, coupled with superior per se performance (19.46) and standard check variety heterosis (37.91). PH, TTPP, ETPP, SPP, GPP, SF, GB, and L:B ratio exhibited high GAM (>20%), suggesting a combination of additive and non-additive gene effects in governing their inheritance. Roy & Shil, (2020) [35] observed similar results for PL, and Prasad et al., (2017) [32] for and. DTF, PL, and GL showed moderate GAM (10%-20%), aligning with Ajmera et al., (2017) [4] . Most traits exhibited low narrowsense heritability (h²(ns) < 10%), except for GL (10.24%), which was medium (10-20%). The dominance of nonadditive gene effects counsels to enhance yield by maintaining heterozygosity. Cross combinations with high SCA effects from poor × poor GCA parents may stem from dominance × dominance non-allelic gene interactions, resulting in non-fixable overdominance. In such cases, biparental mating or reciprocal recurrent selection will be plumy (Latha et al., 2013) [24] . Negative heterosis for DTF promotes earlier flowering in hybrid IR 58025A×HPR 1156 (-10.99) than in the standard check variety (Deepika et al., 2023; Nivedha et al., 2024) [10,30] . Similarly, negative heterosis for days to maturity is desirable to achieve early maturity that impels multiple cropping systems, and its maximum magnitude depicted by hybrid IR 79156A×VL 221 exhibited the highest significant negative mid-parent heterosis (-14.76), while IR 68897A×HPR 2840 showed the highest negative heterosis over the standard check (-9.52) that was familiar with prior researchers' findings with Deepika et al., (2023) [10] and Nivedha et al., (2024) [30] . Semi-dwarfing is associated with lodging resistance, making negative heterosis for plant height desirable. The most significant negative mid-parent heterosis was observed in IR 68897A×HPR 2703 (-31.27), and the highest negative standard check heterosis was in IR 68897A×HPR 1068 (-26.5), with similar patterns in rice using CMS lines (Kiruba et al., 2023; Negm et al., 2023) [23,29] . A higher number of tillers per plant is correlated with increased grain yield. Most hybrids displayed significant negative heterosis over mid-parent and standard check varieties. Hussein et al., (2021) [20] , Mohan et al., (2021) [27] , and Arunkumar & Narayanan, (2024) [6] also observed both positive and negative standard check variety heterosis for TTPP. For maximum grain yield, the relationship between grain yield and its governing traits, including number of ETPP, PH, SF, SPP, and HI, plays a key role (Faysal et al., 2022) [15] . Cluster analysis, a statistical tool, uncovers genetic relationships and diversity in rice genotypes, facilitating their use in breeding programs. Dendrogram cluster analysis groups similar genotypes, assisting breeders in selecting suitable genotypes for yield improvement. G*YT indexbased selection ensures consistently high-yielding genotypes. This method provides a robust and comprehensive approach and visually highlights each genotype's strengths and weaknesses based on combined traits with yield (Kendal, 2019) [21] . Acute angles between vectors in the GYT biplot indicate positive correlations among yield-trait combinations (Figure 5). This key feature allows meaningful graphical ranking of genotypes based on their yield*trait combinations.

Conclusion

Heterosis exploitation serves to cope with formidable rice challenges. CMS-based hybrid rice production is a highly efficient technique. Hybrids showing positive specific combining ability (SCA) effects for yield and related attributes can be utilized in hybrid rice breeding programs. Correlation analysis helped to determine key yieldattributing traits identified with significant association ship, while cluster analysis revealed significant genetic diversity among the genotypes for future breeding programmes for yield improvement. The GYT technique depicted a strong and restricted (often positive) relationship between combinations and highlighted the top-performing genotype among all genotypes in terms of grain yield* and other traits.

Acknowledgement

AcknowledgementsThe authors are grateful to CSK HPKV, Palampur, India, for providing all facilities to conduct this research smoothly and in a timely manner. MKS is grateful to the members of the advisory committee for their kind support. FundingThe authors declare that they did not receive any funds, grants, or other support while preparing this manuscript.

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