Non-additive Genetic Variance Research Articles

Molecular Diversity and Combining Ability in Newly Developed Maize Inbred Lines under Low-Nitrogen Conditions.

Nitrogen is an essential element for maize growth, but excessive application can lead to various environmental and ecological issues, including water pollution, air pollution, greenhouse gas emissions, and biodiversity loss. Hence, developing maize hybrids resilient to low-N conditions is vital for sustainable agriculture, particularly in nitrogen-deficient soils. Combining ability and genetic relationships among parental lines is crucial for breeding superior hybrids under diverse nitrogen levels. This study aimed to assess the genetic diversity of maize inbred lines using simple sequence repeat (SSR) markers and evaluate their combining ability to identify superior hybrids under low-N and recommended conditions. Local and exotic inbred lines were genotyped using SSR markers, revealing substantial genetic variation with high gene diversity (He = 0.60), moderate polymorphism information content (PIC = 0.54), and an average of 3.64 alleles per locus. Twenty-one F1 hybrids were generated through a diallel mating design using these diverse lines. These hybrids and a high yielding commercial check (SC-131) were field-tested under low-N and recommended N conditions. Significant variations (p < 0.01) were observed among nitrogen levels, hybrids, and their interaction for all recorded traits. Additive genetic variances predominated over non-additive genetic variances for grain yield and most traits. Inbred IL3 emerged as an effective combiner for developing early maturing genotypes with lower ear placement. Additionally, inbreds IL1, IL2, and IL3 showed promise as superior combiners for enhancing grain yield and related traits under both low-N and recommended conditions. Notably, hybrids IL1×IL4, IL2×IL5, IL2×IL6, and IL5×IL7 exhibited specific combining abilities for increasing grain yield and associated traits under low-N stress conditions. Furthermore, strong positive associations were identified between grain yield and specific traits like plant height, ear length, number of rows per ear, and number of kernels per row. Due to their straightforward measurability, these relationships underscore the potential of using these traits as proxies for indirect selection in early breeding generations, particularly under low-N stress. This research contributes to breeding nitrogen-efficient maize hybrids and advances our understanding of the genetic foundations for tolerance to nitrogen limitations.

The Effect of Genome Parametrization and SNP Marker Subsetting on Genomic Selection in Autotetraploid Alfalfa.

Alfalfa, the most economically important forage legume worldwide, features modest genetic progress due to long selection cycles and the extent of the non-additive genetic variance associated with its autotetraploid genome. To improve the efficiency of genomic selection in alfalfa, we explored the effects of genome parametrization (as tetraploid and diploid dosages, plus allele ratios) and SNP marker subsetting (all available SNPs, only genic regions, and only non-genic regions) on genomic regressions, together with various levels of filtering on reading depth and missing rates. We used genotyping by sequencing-generated data and focused on traits of different genetic complexity, i.e., dry biomass yield in moisture-favorable (FE) and drought stress (SE) environments, leaf size, and the onset of flowering, which were assessed in 143 genotyped plants from a genetically broad European reference population and their phenotyped half-sib progenies. On average, the allele ratio improved the predictive ability compared with other genome parametrizations (+7.9% vs. tetraploid dosage, +12.6% vs. diploid dosage), while using all the SNPs offered an advantage compared with any specific SNP subsetting (+3.7% vs. genic regions, +7.6% vs. non-genic regions). However, when focusing on specific traits, different combinations of genome parametrization and subsetting achieved better performances. We also released Legpipe2, an SNP calling pipeline tailored for reduced representation (GBS, RAD) in medium-sized genotyping experiments.

Diallel crosses in Picea abies V. Can early testing predict long-term performance?

Abstract Genetic variation and performance of up to 40-year-old Norway spruce (Picea abies (L.) Karst.) families from half-diallel crosses made in natural populations where studied, and the results were compared with results from nursery test of seedlings (1-2 years from seed) and short-term farm-field tests at 6-10 years from seed. The diallel analyses revealed significant levels of additive genetic variance for growth and phenology traits. The non-additive genetic variance was generally small to moderate. Strong genetic correlations for growth performance were found between the short-term and long-term trials but not between the nursery and long-term trials. Similarly, genetic correlations for phenology traits were strong between short-term trials and long-term trials, whereas the nursery tests generally did not predict phenology at older age well. The findings indicate that early selection for growth and adaptive traits based on short-term trials is effective for improvement of long-term performance in field if the test site is not outside the normal range of deployment of the reproductive material.

Heterosis and combining ability in intraspecific (G. hirsutum L.) and interspecific (G. hirsutum L. × G. barbadense L.) cotton hybrids

The inheritance of most important economic characters, heterosis and combining ability were studied in six interspecific (G. hirsutum L. × G. barbadnese L.) and three intraspecific hybrid combinations. There were found different types of inheritance of productivity, boll weight and lint percentage and fiber length in the individual crosses. The genetic variance for productivity and fiber length was mainly non-additive, while for lint percentage it was additive. Although non-additive genetic variance prevailed for productivity and fiber length, only individual crosses showed positive heterosis, outperforming the better parent. Of the female forms, the cultivar Helius was identified as a very good general combiner for productivity. From the male forms the cultivar Ashkabat emerged as a very good general combiner for productivity, boll weight and lint percentage. The cultivars Mytra (female), Karshinski-2 and C-6037 (male) were determined as very good general combiners for fiber length. All these cultivars, with the exception of C-6037, had low SCA variances, their high GCA was mainly due to additive gene effects, and they were very suitable for synthetic selection. The cross Helius × Ashkabat was found to be most valuable for the selection of productivity because of the highest mean performance and the highest level of heterosis with high SCA effects. All intraspecific hybrids were found to be most promising for improving lint percentage. The interspecific cross combinations Mytra × C-6037, Helius × C-6037 and Mytra × Karshinski-2, having the longest fibers, the first two with high SCA effects were most valuable for fiber length improvement.

Heterosis and combining ability studies in Sesame

The present investigation on heterosis and combining ability using line × tester analysis at NRS, NAU, Vanarasi Gujarat indicated that there is sufficient amount of variation present in the tested material for seed yield and its components. Non-additive genetic variances were important in the inheritance of all the traits. The preponderance of non-additive genetic variance was observed in the inheritance of days to 50 % flowering, days to maturity, plant height, effective branches/plant, capsules/plant, capsule length, seeds/capsule, 1000-seed weight, harvest index, seed yield/plant and oil content which suggested that heterosis breeding would be more suitable for the improvement of these traits in sesame. Further the crosses which exhibited high seed and oil yield along with high heterosis and heterobeltiosis should be exploited through pedigree method to obtain desirable transgressive segregants with high seed yield along with high oil content.

Investigating the impact of non-additive genetic effects in the estimation of variance components and genomic predictions for heat tolerance and performance traits in crossbred and purebred pig populations

BackgroundNon-additive genetic effects are often ignored in livestock genetic evaluations. However, fitting them in the models could improve the accuracy of genomic breeding values. Furthermore, non-additive genetic effects contribute to heterosis, which could be optimized through mating designs. Traits related to fitness and adaptation, such as heat tolerance, tend to be more influenced by non-additive genetic effects. In this context, the primary objectives of this study were to estimate variance components and assess the predictive performance of genomic prediction of breeding values based on alternative models and two independent datasets, including performance records from a purebred pig population and heat tolerance indicators recorded in crossbred lactating sows.ResultsIncluding non-additive genetic effects when modelling performance traits in purebred pigs had no effect on the residual variance estimates for most of the traits, but lower additive genetic variances were observed, especially when additive-by-additive epistasis was included in the models. Furthermore, including non-additive genetic effects did not improve the prediction accuracy of genomic breeding values, but there was animal re-ranking across the models. For the heat tolerance indicators recorded in a crossbred population, most traits had small non-additive genetic variance with large standard error estimates. Nevertheless, panting score and hair density presented substantial additive-by-additive epistatic variance. Panting score had an epistatic variance estimate of 0.1379, which accounted for 82.22% of the total genetic variance. For hair density, the epistatic variance estimates ranged from 0.1745 to 0.1845, which represent 64.95–69.59% of the total genetic variance.ConclusionsIncluding non-additive genetic effects in the models did not improve the accuracy of genomic breeding values for performance traits in purebred pigs, but there was substantial re-ranking of selection candidates depending on the model fitted. Except for panting score and hair density, low non-additive genetic variance estimates were observed for heat tolerance indicators in crossbred pigs.

Additive and non-additive genetic variance in juvenile Sitka spruce (Picea sitchensis Bong. Carr)

Many quantitative genetic models assume that all genetic variation is additive because of a lack of data with sufficient structure and quality to determine the relative contribution of additive and non-additive variation. Here the fractions of additive (fa) and non-additive (fd) genetic variation were estimated in Sitka spruce for height, bud burst and pilodyn penetration depth. Approximately 1500 offspring were produced in each of three sib families and clonally replicated across three geographically diverse sites. Genotypes from 1525 offspring from all three families were obtained by RADseq, followed by imputation using 1630 loci segregating in all families and mapped using the newly developed linkage map of Sitka spruce. The analyses employed a new approach for estimating fa and fd, which combined all available genotypic and phenotypic data with spatial modelling for each trait and site. The consensus estimate for fa increased with age for height from 0.58 at 2 years to 0.75 at 11 years, with only small overlap in 95% support intervals (I95). The estimated fa for bud burst was 0.83 (I95=[0.78, 0.90]) and 0.84 (I95=[0.77, 0.92]) for pilodyn depth. Overall, there was no evidence of family heterogeneity for height or bud burst, or site heterogeneity for pilodyn depth, and no evidence of inbreeding depression associated with genomic homozygosity, expected if dominance variance was the major component of non-additive variance. The results offer no support for the development of sublines for crossing within the species. The models give new opportunities to assess more accurately the scale of non-additive variation.

PSXII-3 Including Non-Additive Genetic Effects in Genomic Prediction and Estimation of Variance Components for Performance and Heat Stress Traits in Pigs

Abstract Non-additive genetic effects may have important roles in the phenotypic expression of performance and adaptation traits in livestock. Therefore, we aimed to evaluate the inclusion of non-additive genetic effects in genomic prediction models and variance component estimation of performance traits in a purebred pig population and heat tolerance indicators in a crossbred pig population. The first dataset consisted of 3,534 individuals with genotypes for 52,843 SNPs and five pre-adjusted phenotypes from a public database of a purebred pig line. Twelve models fitting or not dominance and/or epistasis effects (additive-by-additive, additive-by-dominance, and dominance-by-dominance) and inbreeding were used to estimate variance components. Prediction ability was assessed based on 10-fold cross-validation and the bias, dispersion, and accuracy estimates were computed based on the LR method. We also evaluated the impact of including non-additive genetic effects on the ranking of the animals’ breeding value and in the proportion of commonly selected individuals. The second dataset consisted of records from 1,645 lactating sows (Large White x Landrace cross) genotyped for 50,703 SNPs and traits related to heat stress response: skin temperature (ear, shoulder, rump, and tail), vaginal temperature measured every 10 minutes, and the average of the six records per hour corresponding to 08:00, 12:00, 16:00, and 20:00 hours during four days; respiration rate, panting score (PS; score scale from 0 to 3), and hair density (HD, score scale from 0 to 2). Four models including or not, inbreeding and the effect of dominance and additive-by-additive epistasis were used to estimate variance components. There was no effect on residual variance estimates due to the inclusion of non-additive genetic effects in the models for most traits. However, non-additive genetic effects reduced additive variance estimates, especially when additive-by-additive epistasis was fitted. Including non-additive genetic effects in the model did not improve the prediction accuracy of breeding values for purebreds, but there was a substantial change in the ranking of the animals and in the proportion of commonly selected individuals. For the crossbred traits, small non-additive genetic variance with large standard error estimates were obtained. Nevertheless, PS and HD presented notable additive-by-additive epistatic variance. PS presented h2aa estimates of 0.15 and additive-by-additive epistasis corresponding to 86.76% of the total genetic variance, while HD presented additive-by-additive epistatic heritability (h2aa) estimates from 0.46 to 0.49 and the proportion of total genetic variance explained by additive-by-additive epistasis ranged from 66.91% to 71.87%. In conclusion, including non-additive genetic effects did not improve the accuracy of prediction of breeding values for purebreds, but it changed the ranking of animals and selection decisions. Although PS and HD had large additive-by-additive epistasis effects, most of the traits related to heat stress in the crossbred population did not present relevant non-additive genetic effects.

Does the definition of a novel environment affect the ability to detect cryptic genetic variation?

Anthropogenic change exposes populations to environments that have been rare or entirely absent from their evolutionary past. Such novel environments are hypothesized to release cryptic genetic variation, a hidden store of variance that can fuel evolution. However, support for this hypothesis is mixed. One possible reason is a lack of clarity in what is meant by 'novel environment', an umbrella term encompassing conditions with potentially contrasting effects on the exposure or concealment of cryptic variation. Here, we use a meta-analysis approach to investigate changes in the total genetic variance of multivariate traits in ancestral versus novel environments. To determine whether the definition of a novel environment could explain the mixed support for a release of cryptic genetic variation, we compared absolute novel environments, those not represented in a population's evolutionary past, to extreme novel environments, those involving frequency or magnitude changes to environments present in a population's ancestry. Despite sufficient statistical power, we detected no broad-scale pattern of increased genetic variance in novel environments, and finding the type of novel environment did not explain any significant variation in effect sizes. When effect sizes were partitioned by experimental design, we found increased genetic variation in studies based on broad-sense measures of variance, and decreased variation in narrow-sense studies, in support of previous research. Therefore, the source of genetic variance, not the definition of a novel environment, was key to understanding environment-dependant genetic variation, highlighting non-additive genetic variance as an important component of cryptic genetic variation and avenue for future research.

Elucidation of Combining Ability and Gene in Bottle Gourd [Lagenaria siceraria (Mol.) Standl.

Aims: To Study combining ability effects and evaluate gene action for fruit yield with associated traits of bottle gourd.&#x0D; Study Design: Randomized block design.&#x0D; Place and Duration of Study: The seeds of F1 hybrids were produced during summer 2021 at Potato Research Station, S. D. Agricultural University, Deesa.&#x0D; Methodology: The experimental material consisted of twelve parents, their 35 Line × Tester crosses and one standard check (ABGH 1).&#x0D; Results: The analysis of variance for combining ability revealed that the mean sum of squares due to female (lines) and male (testers) were highly significant for all the traits except fruit girth, average fruit weight, chlorophyll a, chlorophyll b and total chlorophyll. The gca effects indicated that four male parents ABGS 14-25, ABGS 11-17, ABGS 11-24 and PUNJAB LONG and three female parents DBG 5, NDBG 132 and LOCAL were found good general combiners for fruit yield per plant and its some of the contributing traits. Based on estimates of sca effects, the most promising hybrids for fruit yield per plant were DBG 5 × ABGS 14-27, NDBG 132 × PUNJAB LONG and GPBG 108 × ABGS 11-24. The good general combiners for fruit yield and contributing traits can be utilized in intensive crossing programme and select transgressive segregants for desired characters in segregating generations to develop superior lines.&#x0D; Conclusion: The ratio of σ2GCA / σ2SCAwas less than unity for all the characters under study, which suggested greater role of non-additive genetic variance in the inheritance of these characters. The genetic components of variance revealed that different type of gene action were involved for fruit yield associated with different traits in bottle gourd.

The combining ability of extra-early maturing quality protein maize (Zea mays) inbred lines and the performance of their hybrids in Striga-infested and low-nitrogen environments

Maize production in sub-Saharan Africa (SSA) faces challenges due to the damage caused by the parasitic weed, Striga hermonthica (Del.) Benths and low soil nitrogen. To address these constraints and improve food security and nutrition, this study assessed the combining ability of 47 inbred lines and four testers, grouped them into heterotic groups, identified effective testers, and determined the stability of the lines in hybrid combinations under contrasting research conditions. The study was conducted at Mokwa and Abuja during the 2019 and 2020 growing seasons. One hundred and ninety-six hybrids comprising 188 testcrosses, 6 hybrids derived by intermating the four testers, and two commercial checks were evaluated using a 14 × 14 lattice design with two replicates. Results revealed that under Striga infestation, the best quality protein maize (QPM) hybrid, TZEEQI 468 × TZEEQI 321, outyielded the best check, TZEEQI 342 × TZEEQI 7, by 24%. Under low-N, QPM hybrid, TZEEQI 515 × TZEEQI 321 outyielded the best check, TZEEQI 507 × TZEEQI 7 by 11% while under optimal conditions the best QPM hybrid, TZEEQI 506 × TZEEQI 321 outyielded the best check, TZEEQI 342 × TZEEQI 7 by 2%. General combining ability (GCA) and specific combining ability (SCA) significantly influenced grain yield and other measured traits across the test environments. These indicated the importance of both additive and non-additive genetic variances in trait inheritance. GCA was more important than SCA for grain yield and most traits in contrasting environments. Four inbred lines had significant and positive GCA effects for grain yield under Striga-infested conditions, while three lines had similar GCA effects under low-nitrogen conditions. These lines demonstrated outstanding potential for developing Striga-resistant and low-nitrogen-tolerant hybrids. The study identified four heterotic groups using the heterotic grouping method based on the general combining ability of multiple traits (HGCMAT). Inbred lines TZEEQI 490 and TZEEQI 460 were identified as testers. The QPM hybrid TZEEQI 515 × TZEEQI 321 exhibited outstanding yield and stability across contrasting environments, highlighting the need for extensive on-farm trials to confirm its superiority and potential for commercialization in SSA.

Evaluation of reciprocal F1 crosses of Fayoumi with two exotic chicken breeds 2: additive and non-additive effects on egg quality traits

The current study evaluates additive and non-additive genetic variances for egg quality traits in six genotypes generated through pure mating and reciprocal crossing of Fayoumi (FM) with Koekoek (KK) and White Leghorn (WL). For each genotype, measurements were taken on 30 eggs randomly sampled at 32, 36, and 40 weeks of age to evaluate both external and internal egg quality parameters. The results revealed significant differences (P < 0.001) among the genotypes in all external quality traits and most internal quality traits, including yolk weight (YW), albumen weight (AW), and yolk height (YH). The results also showed that variations due to purebred effect (PE), general combining ability (GCA), maternal effect (ME), and specific combining ability (SCA) were significant in most traits, which reflects that both additive and non-additive variances are important for the inheritances of the parameters investigated. In most of the traits, the ME and PE were higher in KK and WL, while GCA was higher in KK and FM. The FM x WL had higher SCA than FM x KK. The results suggest the likelihood of genetic improvement in these genotypes through selection and crossbreeding strategies and/or a combination of the two.

Combining ability analysis for seed yield and its attributes in Indian mustard [Brassica juncea (L.) Czern and Coss

The hybrids were developed by adopting diallel mating design excluding reciprocals involving ten diverse Indian mustard genotypes during rabi 2007-08. The resultant 45 hybrids along with their parents were evaluated in a Randomized Block Design with three replications under four environments viz., timely sown at Sardarkrushinagar (E1) and Ladol (E2), and late sown at Sardarkrushinagar (E3) and Ladol (E4), during rabi 2008-09. Combining ability analysis on pooled basis, revealed importance of both additive and non-additive genetic variances for the control of various traits. However, the ratio σ2 gca/σ2 sca indicated preponderance of non-additive gene action for days to 50% flowering, days to maturity, seed yield/plant and oil content, while additive gene action was preponderant for rest of the traits. The parents RK 9501, GM 1 and GM 2 were good general combiners, whereas, the crosses 'RK 9501 x GM 2', 'GM 1 x GM 3' and 'GM 3 x SKM 139' were found to be the best specific combinations for seed yield/plant and some of the important yield contributing traits. However, on the basis of per se performance, exploitable heterosis and significant sca effects for seed yield/plant and some of its important components, the above hybrids were considered to be the most promising for exploitation of heterosis.

Genetic and molecular analysis of stem rot (Sclerotinia sclerotiorum) resistance in Brassica napus (canola type)

Identifying the molecular and genetic basis of resistance to Sclerotinia stem rot (Sclerotinia sclerotiorum) is critical for developing long-term and cost-effective management of this disease in rapeseed/canola (Brassica napus). Current cultural or chemical management options provide, at best, only partial and/or sporadic control. Towards this, a B. napus breeding population (Mystic x Rainbow), including the parents, F1, F2, BC1P1 and BC1P2, was utilized in a field study to determine the inheritance pattern of Sclerotinia stem rot resistance (based on stem lesion length, SLL). Broad sense heritability was 0.58 for SLL and 0.44 for days to flowering (DTF). There was a significant negative correlation between SLL and stem diameter (SD) (r = −0.39) and between SLL and DTF (r = −0.28), suggesting co-selection of SD and DTF traits, along with SLL, should assist in improving overall resistance. Non-additive genetic variance was evident for SLL, DTF, and SD. In a genome wide association study (GWAS), a significant quantitative trait locus (QTL) was identified for SLL. Several putative candidate marker trait associations (MTA) were located within this QTL region. Overall, this study has provided valuable new understanding of inheritance of resistance to S. sclerotiorum, and has identified QTL, MTAs and transgressive segregants with high-level resistances. Together, these will foster more rapid selection for multiple traits associated with Sclerotinia stem rot resistance, by enabling breeders to make critical choices towards selecting/developing cultivars with enhanced resistance to this devastating pathogen.

Tests for associations between sexual dimorphism and patterns of quantitative genetic variation in the water strider, Aquarius remigis

The evolution of sexual dimorphisms requires divergence between sexes in the evolutionary trajectories of the traits involved. Discerning how genetic architecture could facilitate such divergence has proven challenging because of the difficulty in estimating non-additive and sex-linked genetic variances using traditional quantitative genetic designs. Here we use a three-generation, double-first-cousin pedigree design to estimate additive, sex-linked and dominance (co)variances for 12 traits in the water strider, Aquarius remigis. Comparisons among these traits, which have size ratios ranging from 1 to 5 (larger/smaller), allow us to ask if sexual dimorphisms are associated with characteristic patterns of quantitative genetic variation. We frame our analysis around three main questions, derived from existing theory and empirical evidence: Are sexual dimorphisms associated with (1) lower additive inter-sex genetic correlations, (2) higher proportions of sex-linked variance, or (3) differences between sexes in autosomal additive and dominance genetic variances? For questions (1) and (2), we find weak and non-significant trends in the expected directions, which preclude definitive conclusions. However, in answer to question (3), we find strong evidence for a positive relationship between sexual dimorphism and differences between sexes in proportions of autosomal dominance variance. We also find strong interactions among the three genetic components indicating that their relative influence differs among traits and between sexes. These results highlight the need to include all three components of genetic (co)variance in both theoretical evolutionary models and empirical estimations of the genetic architecture of dimorphic traits.

Combining Ability Analysis for Seed Yield and Attributing Traits in Linseed (Linum usitatissimum L.)

A complete set of 79 entries comprising of twelve parents, their 66 F1s and one check RLC-92 were evaluated during rabi 2020-21 at two locations i.e., ARS, Dahod, and BTRS, Anand, under two dates of sowing i.e., 2nd fortnight of October and 1st fortnight of November. The present study aimed to investigate the combining ability analysis over environments for seed yield and attributing traits in linseed (Linum usitatissimum L.). Among the all four environments, E1 had higher mean value for seed yield per plant and all other important yield contributing traits by sowing in second fortnight at Dahod conditions best for linseed cultivation. Combining ability analysis revealed importance of both additive and non-additive variances with prime role of non-additive genetic variance for seed yield per plant and its related traits in all environments as well as pooled over environments suggesting heterosis breeding would be more useful for development of superior hybrids if sterility system available. Among the parents; Shekhar, GS 384, KB 9610 and K 29 were good general combiners for seed yield per plant and test weight and capsules per plant. The parent viz., IPI 10, H 45, GS 384 and RLC 133 were good general combiners for earliness. The cross Indira × ILS 264, Gaurav × H 45 and RLC 133 × Shekhar showed higher sca effects for seed yield and test weight. Most of the crosses with high per se performance involved at least one good general combining parent such as Shekhar, GS 384, KB 9610 and K 29 through out for all studied characters.

Genetic dissection of complex traits in citrus: additive and non-additive genetic variances, inbreeding depression, and single-chromosome heritability

Genetic evaluation in breeding programs generally considers only additive genetic effects; however, non-additive genetic effects may also contribute to phenotypic and genotypic values. Furthermore, the distributions of causal variants in target traits are associated with the efficiency of accumulation of favorable alleles and are therefore important for plant breeding. Despite this, non-additive effects remain to be fully investigated in citrus. Moreover, although quantitative trait loci in citrus have been previously identified, they cannot adequately explain the genetic variance. Therefore, we attempted to estimate non-additive effects, such as dominance and additive-by-additive effects, together with directional dominance as an indicator of inbreeding depression and with chromosome heritability, which reflects the distributions of causal variants for fruit-quality traits in citrus. Phenotypic records of the fruit weight, sugar content, and acid content of 455 cultivars and their progeny were analyzed. Genomic relationship matrices for non-additive effects and single-chromosome genetic effects were constructed using 2319 genome-wide single nucleotide polymorphism loci, which were also used to evaluate directional dominance. These phenotype and genotype records were analyzed using genomic best linear unbiased prediction models. Through this analysis, we showed (1) overestimation of narrow-sense heritability due to substantial contributions of non-additive effects in the tested traits, (2) evidence of inbreeding depression in fruit weight, and (3) highly polygenic architectures in the tested traits. These findings could contribute to precise evaluation of genotypic values and the development of efficient breeding strategies.

Increasing genomic prediction accuracy for unphenotyped full-sib families by modeling additive and dominance effects with large datasets in white spruce.

Genomic selection is becoming a standard technique in plant breeding and is now being introduced into forest tree breeding. Despite promising results to predict the genetic merit of superior material based on their additive breeding values, many studies and operational programs still neglect non-additive effects and their potential for enhancing genetic gains. Using two large comprehensive datasets totaling 4,066 trees from 146 full-sib families of white spruce (Picea glauca (Moench) Voss), we evaluated the effect of the inclusion of dominance on the precision of genetic parameter estimates and on the accuracy of conventional pedigree-based (ABLUP-AD) and genomic-based (GBLUP-AD) models. While wood quality traits were mostly additively inherited, considerable non-additive effects and lower heritabilities were detected for growth traits. For growth, GBLUP-AD better partitioned the additive and dominance effects into roughly equal variances, while ABLUP-AD strongly overestimated dominance. The predictive abilities of breeding and total genetic value estimates were similar between ABLUP-AD and GBLUP-AD when predicting individuals from the same families as those included in the training dataset. However, GBLUP-AD outperformed ABLUP-AD when predicting for new unphenotyped families that were not represented in the training dataset, with, on average, 22% and 53% higher predictive ability of breeding and genetic values, respectively. Resampling simulations showed that GBLUP-AD required smaller sample sizes than ABLUP-AD to produce precise estimates of genetic variances and accurate predictions of genetic values. Still, regardless of the method used, large training datasets were needed to estimate additive and non-additive genetic variances precisely. This study highlights the different quantitative genetic architectures between growth and wood traits. Furthermore, the usefulness of genomic additive-dominance models for predicting new families should allow practicing mating allocation to maximize the total genetic values for the propagation of elite material.

Diallel crosses in Picea abies IV. Genetic variation and inheritance patterns in short-term trials

Abstract The complete diallel cross is the only mating design that provides estimates of variance components of general combining (GCA), specific combining ability (SCA), maternal and reciprocal effects, in addition to heritabilities and genetic correlations. To obtain such estimates, complete diallels were made among 10 trees in each of three natural Norway spruce populations from altitude 300 and 500 m in southern Norway. Seedlings from families from the diallels and open pollinations were tested in short-term tests on agricultural soil at one site at altitude 85 m until age 10 years from seed. Tree height at ages 7 and 10 years and diameter at age 10 had strongly significant GCA variance components within each population. The components for SCA and maternal effects were small and not significant, indicating low levels of non-additive genetic variation. For the days of initiation and cessation of the shoot elongation period the GCA components were dominating and had the highest heritability estimates in two of the diallels. Estimates of genetic correlations between traits measured in earlier nursery trials and height and diameter in the short-term trials had low and not consistent values in the three diallels. The duration of the shoot growth period and rate of growth showed positive relationships with height and diameter. Strong relationships were present between half-sib family means from the diallels and open-pollinated families for height, diameter and phenology traits. Progeny trials testing open-pollinated half-sib families from natural populations can be used for selection of candidates for the initial breeding populations.

Genetic Variability Parameters and Character Associations among Yield Attributing Traits in Advanced Backcross Lines of Groundnut

Groundnut is currently a major industrial oilseed crop with good commercial significance. It is highly variable in phenotypic characters and thus it is important to investigate the variations and associations of these morphological features. 20 advanced Groundnut lines were planted in Randomized Complete Block Design along with parental lines and two checks and they were evaluated for 13 traits. Significant variations were revealed in analysis of variance. High GCV (20.21) coupled with high heritability (91.2) and GAM (39.77) were observed is plant height suggested that environment had lesser influence on the expression of this trait, as this character is governed by an additive gene action, making them effective for selection. High heritability combined with low GCV and GAM were recorded in oil content, days to 50 percent flowering, shelling outturn and number of secondary branches per plant revealed that non-additive genetic variation played a significant role in the expression of this trait thus, selection for this character would be inefficient. Pod yield per plant showed a positive and significant association with seed yield per plant, plant height, number of secondary branches per plant, pod length, pod width and number of pods per plant. Path coefficient analysis have revealed that positive direct effects towards pod yield per plant were reported for seed yield per plant, plant height, number of secondary branches per plant, pod length, pod width, and number of pods per plant. Thus the characters seed yield per plant, number of pods per plant, pod length and number of secondary branches per plant which are the most essential characters contributed significantly towards higher pod yield per plant.