Genetic Variance Components Research Articles

Elucidation of gene action and estimation of combining ability effects for fruit yield attributes and biochemical traits in brinjal (Solanum melongena L.)

Abstract The present investigation was undertaken in brinjal (Solanum melongena L.) to estimate combining ability and gene action following a half diallel mating design using ten parents. The ratio of genetic variance components, σ2gca/σ2sca and σ2D/σ2A, showed dominant gene action, indicating the presence of non-additive genetic variance for days to 50% flowering, fruit yield per plant, total phenol, antioxidant activity and total soluble sugar. The traits fruits per plant, fruit girth, and fruit weight showed additive genetic variance. Among the parental genotypes, AB 15-08, ABSR 2 and AB 20-13 were found to be good general combiners for fruit yield, fruits per plant, and total soluble solids. The three highest-ranking hybrids were AB 15-08 × AB 20-13, AB 15-08 × AB 20-03 and AB 20-07 × GP BRJ 224. The above hybrids would be rewarding for harnessing heterosis. Keywords: Diallel cross, brinjal, combining ability, fruit yield, antioxidant activity

Analysis of Component of Genetic Variance, Combining Ability, Gene Action and Heterotic Response in Rice (Oryza sativa. L)

Rice (Oryza sativa L.) is an important staple crop, particularly in Asia, where it feeds more than half the world's population. The analysis of variance (ANOVA) for nine traits in a rice breeding experiment with seven lines, three testers, 24 F1 hybrids, and two checks indicated significant variations between treatments, showing significant genetic diversity. General combining ability (GCA) effects revealed that line MTU 1010 and tester NDR 2026 had favorable GCA effects on grain yield per plant, but NDR 2064 and Barani Deep had negative effects. Three crosses, showed considerable favorable benefits on grain yield due to specific combining ability (SCA). Heterosis analysis identified promising crosses, including Gopal Bhag × Prakhar and NDR-2064 × NDR-2026, that demonstrated considerable positive heterosis above the parent and standard varieties Shushk Samrat and Ashwani. These findings emphasize the possibility of specific crosses to improve grain production in rice breeding efforts.

347 Quantifying phenotypic and genetic variation for cow fertility phenotypes in American Simmentals using total herd reporting data

Abstract Inefficiencies in reproduction are the largest drivers of loss in United States beef production. Nearly all reproductive traits are at least modestly heritable, making genetic selection and improvement possible over the long term. Cow-centric reproductive traits present unique challenges, as they are not expressed in male animals and will not be observed until later in the productive life of a female, if at all. This makes cow-centric fertility traits ideal candidates for selection with Expected Progeny Differences (EPDs). We used a commercially generated dataset from the American Simmental Association (ASA) to explore the phenotypic and genetic variation in these traits. The dataset comprised Total Herd Enrollment (THE) records, which required unbiased reporting of enrollment, calving, and disposal for 303,158 females (132,403 cows and 170,755 heifers). Using the THE data, we calculated three continuous and two discrete traits that are indicators of heifer and cow fertility and rebreeding ability. These traits were: 1) calving date (calving date of the cow relative to the start of the calving season), 2) calving interval (days between calves), 3) first calving interval (calving interval observation between the first and second calving record for a female), 4) heifer pregnancy (did the animal calve as 2-yr-old?), and 5) discrete early calving (did animal calve in the first 30 d of the calving season?). We observed a significant difference in calving date in mature cows that calved in the first 30 d of the calving season of their contemporary group as heifers compared with those that calved later (Table 1). Early calving heifers averaged a nearly 10 d sooner calving date throughout their productive lives compared with those that calved after 30 d as heifers (29.9 d vs. 40.2 d, P-value < 0.01). We used a combined pedigree and genomic approach, implemented in GIBBSF90+, to estimate genetic, environmental, and permanent environmental variance components. We estimated heritabilities of 0.24 (± 0.037215) for heifer pregnancy, 0.06 (± 0.009265) for calving date, 0.07 (± 0.015451) for discrete early calving, 0.04 (± 0.003954) for calving interval, and 0.04 (± 0.009604) for first calving interval. We observed positive phenotypic and genetic correlations between these traits, ranging from 0.01 to 0.96 (Table 2). This work provides an extensive population survey of phenotypic trends in reproductive performance and management in a large seedstock population. The heritable nature of the inspected traits motivates further work in understanding their genetic architectures and how they are affected by heterosis in crossbreeding programs.

Estimation of (co)variance components for body weight traits in intercross synthetic sheep

This study was carried out on the recently developed intercross sheep developed from Bharat merino and Gaddi sSynthetic in the temperate region in the state of Himachal Pradesh of India. Study aimed to estimate the genetic parameters and (co)variance components for body weights at birth (BW) and 3-month (3BW), 6-month (6BW), 9-month (9BW) and 12-month (12BW) month age in a closed flock of intercross sheep maintained at North Temperate Regional Station of ICAR-CSWRI, Garsa, India. Data records on 1505 sheep descended from 565 dams and 154 sires over the period of 10 years were utilized. Data were corrected for possible fixed environmental effects such as lambing year, parity, sex of lamb, ewe weight at lambing for further genetic analysis. The restricted maximum likelihood procedure fitting animal models with different combinations of direct and maternal effects were used for genetic analysis. Analysis revealed significant influences of lambing year, parity, sex of lamb and ewe weight at lambing on studied traits. Direct heritability estimates for BW, 3BW, 6BW, 9BW and 12BW were 0.14±0.04, 0.18±0.05, 0.00±0.04, 0.05±0.05 and 0.05±0.05, respectively. Maternal effects significantly influenced the BW and estimated maternal heritability for the trait was 0.17±0.03. The correlation among body weights were medium to high except between BW and 12BW and it ranged from 0.16±0.51 to 0.99±0.19. Results suggest that maternal effects were important for initial growth performance. The heritability estimates for weaning weight was moderate and its positive association with other growth traits indicated that the present selection practice at six months may be shifted to early selection at weaning weight for further genetic improvement.

Genetic divergence and truncation and simultaneous selection in inbred families (S1) of elephant grass for bioenergetic purposes via mixed models

The State University of North Fluminense Darcy Ribeiro (UENF) has been developing for fifteen years a breeding program that aims at the development of new cultivars of elephant grass due to its high potential and the low availability of cultivars developed by genetic breeding programs that meet the needs of producers in the State of Rio de Janeiro. In this sense, inbred families were also obtained as a way of fixing potential alleles for traits related to production, as the inbreeding process apparently does not strongly affect elephant grass in aspects related to inbreeding depression. This study aimed to estimate genetic diversity, variance components and prediction of genotypic values in 11 (S1) elephant grass families, and perform the truncation and simultaneous selection of traits using the selection index, by mixed models. The experimental design consisted of randomized blocks with 11 (S1) families, three replications, and six plants per plot. For variables dry matter production, percentage of dry matter, plant height, stem diameter, number of tillers and leaf blade width, was performed the estimation of genetic parameters and selection of the best genotypes based selection index using mixed model. The descriptors were subjected to correlation analysis, distance matrices were generated by the Mahalanobis method, and individuals were grouped by the UPGMA method. In the selection via mixed models (REML/BLUP), families 6, 11, 8, 1, 3, 7, and 9 contributed most of the genotypes selected for the evaluated traits, indicating their high potential to generate superior genotype. The selection indices via mixed models indicated that the multiplicative index presented a greater selection gain.The phenotypic correlations showed the possibility of performing an indirect selection from six evaluated traits.The genotypes were separated into 18 groups by the Mahalanobis distance, allowing the observation of a wide genetic diversity. The most divergent and productive genotypes were self-fertilized to obtain the second generation (S2), continuing the development program.

Assessment of Genetic Variability, Correlation, and Path Coefficient for Yield and Its Contributing Traits in Pigeon Pea [Cajanus cajan (L.) Millspaugh

The experimental material consisted of 155 pigeon pea genotypes sown in a Randomized Block Design (RBD) with three replications during the Kharif, 2023-2024 crop season at the N. E. B. Crop Research Centre of G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand. The genetic variance components, correlation, and path coefficient for seed yield and its components were estimated using these 155 pigeon pea genotypes. The highest phenotypic coefficient of variation (PCV) values (> 20%) were recorded for traits such as the number of pods per plant (26.45%), number of secondary branches per plant (22.72%), and seed yield per plant (20.27%). In contrast, the lowest PCV estimates (< 10%) were found for days to maturity (7.39%) and days to 50% flowering (6.73%). High estimates of the genotypic coefficient of variation (GCV) (> 20%) were recorded only for the number of pods per plant (23.6%). The lowest GCV estimates (< 10%) were observed for hundred seed weight (9.63%), number of seeds per pod (9.55%), plant height (9.49%), pod length (7.18%), days to maturity (6.85%), and days to 50% flowering (6.5%). The hundred seed weight showed a high positive direct effect on seed yield per plant (Genotypic = 0.58, Phenotypic = 0.47) along with a positive and significant correlation (Genotypic correlation coefficient, (rg = 0.599); Phenotypic correlation coefficient, (rp = 0.485)). Based on this investigation, it is evident that exploring genetic variability, correlations, and path analyses provides a more effective approach for selecting superior cultivars for yield and related traits.

Assessment of gene action and combining ability for advancement of yield andits attributing traits in pansy (<i>Viola </i>× <i>wittrockiana </i>Gams.) through diallel mating design

Pansy is one of the most important bedding winter annual for sub-tropical climatic conditions. Twenty-eight F1 hybrids of pansy were evaluated in randomized block design with three replications, to study the combining ability for vegetative and floral characters. The analysis of variance indicated significant variability among all the genotypes for all the characters. The ratio of genetic component of variance indicated the equal importance of additive and non-additive gene action in governing the flower yield and its component traits of pansy. Estimates of general combining ability effects showed that parents Pa-64-1-5-14, Pa-62-4-12-18, Pa-63-1-7-25 and Pa-32-8-7-6 were good general combiners for most of the traits except stalk length and flower size. The specific combining ability effects showed that for yield traits the best cross combinations were Pa-64-1-5-14 × Pa-62-4-12-18, Pa-13-1-2-3 × Pa-47-1-3, Pa-11-1-3-7 × Pa- 62-4-12-18, Pa-64-1-5-14 × Pa-63-1-7-25 and Pa-11-1-3-7 × Pa-64-1-5-14. The study on gene effect of different characters indicated the predominance of non-additive gene effects for most of the characters. The gca variances was higher for branches number, flower size, days from bud initiation to flowering and flowers number than sca variances, indicating additive gene action, and progeny selection will be effective for the genetic improvement of these traits.

Combining ability and multiple parent‐based approach to derive simultaneous transgressive segregants for multiple traits in cotton (Gossypium hirsutum L.)

AbstractPlant breeders are always in pursuit of desirable genes and gene complexes, leading to identification of potential and promising individuals/segregants often exhibiting traits with higher intensity. Identifying segregants with desirable combination of multiple traits would enable a breeder to develop superior cultivars. In this study, combining ability and multiple parent‐based approach was employed to derive segregants simultaneously superior for multiple traits. Single and double crosses were developed by crossing 11 parental lines in half diallel fashion and were evaluated under seven environments. To create crosses, the parental lines with the highest positive gca effects were selected in addition to desirable yield and fibre quality traits (SCYP, NOBP, BW, GOT, UHML and FS). The positive and significantly higher gca effects in these parents is an evidence of prominence of additive and additive × additive component of genetic variance. To identify desirable segregants, six F2 populations derived from four single and their two double crosses were evaluated by raising an optimal population size of 910–935 and 3040–3055 plants for single and double crosses, respectively. In each population, proportion of desirable and simultaneous transgressive segregants was estimated. A total of 19 (2.87%), 22 (3.32%) and 24 (3.60%) plants were transgressive in nature simultaneously for multiple traits in single crosses, namely, RAHH‐1755 and RAHH‐455, and double cross, namely, RHDC‐1933, of Group I, respectively. While in Group II, 22 (3.32%), 22 (3.32%) and 24 (3.60%) plants showed simultaneous transgressive segregation in RAHH‐1702, SHH‐818 and RHDC‐1940, respectively. The per cent simultaneous transgressive segregants were found to be higher in the double crosses compared with their respective single crosses, possibly for the reason that double crosses involve more number of parents owing to increased recombination. Hence, breeding for desirable segregating recombinants using diallel and multiple parent‐based approach paves the way towards directional selection based on combining ability making it more efficient compared with conventional means of hybridization followed by selection.

The Garden of Forking Paths: Reinterpreting Haseman-Elston Regression for a Genotype-by-Environment Model.

Haseman-Elston regression (HE-reg) has been known as a classic tool for detecting an additive genetic variance component. However, in this study we find that HE-reg can capture GxE under certain conditions, so we derive and reinterpret the analytical solution of HE-reg. In the presence of GxE, it leads to a natural discrepancy between linkage and association results, the latter of which is not able to capture GxE if the environment is unknown. Considering linkage and association as symmetric designs, we investigate how the symmetry can and cannot hold in the absence and presence of GxE, and consequently we propose a pair of statistical tests, Symmetry Test I and Symmetry Test II, both of which can be tested using summary statistics. Test statistics, and their statistical power issues are also investigated for Symmetry Tests I and II. Increasing the number of sib pairs is important to improve statistical power for detecting GxE.

Estimation of genetic parameters for maintenance energy requirements and residual feed intake in Nellore cattle.

We estimated heritabilities and genetic and phenotypic correlation estimates for maintenance energy requirements (NEmR), residual feed intake (RFI), growth, carcass and reproductive indicator traits, using data from 41 feed efficiency trials in Brazil, comprising 4381 males and females. Continuous traits were analysed using a linear animal model and threshold traits were analysed using a threshold animal model. The heritability estimates were low for RFI (0.190) and NEmR (0.193); other heritabilities were mainly moderate (growth and carcass traits) or high (sexual precocity traits). The genetic correlation of RFI with NEmR was high (0.701). The genetic correlations of NEmR were low with carcass and reproductive traits, and moderate with growth traits. Thus, selection to improve weaning weight and female sexual precocity indicator traits would not affect maintenance energy requirement. Genetic selection to reduce maintenance energy requirements is feasible and would also reduce DMI and RFI. Selection to improve RFI can be used to identify animals with lower maintenance energy requirements. Long-term selection to reduce RFI and NEmR would have favourable effects on yearling weight, carcass muscle indicator traits and female sexual precocity. Genetic (co)variance component estimates for NEmR, in conjunction with economic values of selection criteria, may be used to develop novel approaches for genetic selection to improve efficiency of beef production.

Cohort Effects on Tobacco Consumption and Its Genetic and Environmental Variance Among Finnish Adults Born Between 1880 and 1957

Abstract Introduction Population research indicates that smoking behaviors in Finland have varied over time by sex and birth cohort. Smoking behaviors are influenced by genes and the environment; like the behaviors themselves, these underlying influences are not necessarily stable over time and may be modifiable by national drug policy. Aims and Methods We utilized longitudinal mixed-effects models and causal–common–contingent twin models to evaluate sex and cohort effects on tobacco consumption and the underlying genetic and environmental variance components in a birth cohort sample of same-sex twins born in Finland between 1880 and 1957, assessed in 1975, 1981, 1990, and 2011. Results We identified significant main effects of age, sex, and cohort on quantity of cigarette consumption, as well as significant age × cohort and sex × cohort interactions. We also identified sex and cohort effects on the liability to initiate regular smoking and the magnitude of variation underlying quantity of cigarette consumption. That said, heritability and environmental contributions to both traits were not different between the four sex × cohort groups. Conclusions Our results indicate sex and cohort effects on the prevalence of smoking and its underlying variation. Our results on changing prevalence mirror existing population-level research in Finnish samples, but we did not identify differences in heritability found in other studies of cohort effects in tobacco use, potentially due to power issues. These results highlight the importance of considering age, cohort, and timing of policy changes when evaluating changes in substance consumption across time. Implications This study identifies sex and cohort effects influencing tobacco consumption in a sample of Finnish adult twins born between 1880 and 1957. Our results are in line with other population-level research in Finland and research on cohort effects influencing alcohol use in the same sample. Our results highlight the intertwining effects of age, cohort, sex, and substance policies on substance use.

Evaluation of non-additive genetic effects on carcass and meat quality traits in Korean Hanwoo cattle using genomic models

The traditional genetic evaluation methods generally consider additive genetic effects only and often ignore non-additive (dominance and epistasis) effects that may have contributed to genetic variation of complex traits of livestock species. The available dense single nucleotide polymorphisms (SNPs) panels offer to investigate the potential benefits of including non-additive genetic effects in the genomic evaluation models. Data from 16 971 genotyped (Illumina Bovine 50 K SNP chip) Korean Hanwoo cattle were used to estimate genetic variance components and prediction accuracy of genomic breeding values (GEBVs) for four carcass and meat quality traits: carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT) and marbling score (MS). Five different genetic models were evaluated through including additive, dominance and epistatic interactions (additive by additive, A × A; additive by dominance, A × D and dominance by dominance, D × D) successively in the models. The estimates of additive genetic variances and narrow sense heritabilities (ha2) were found similar across the evaluated models and traits except when additive interaction (A × A) was included. The dominance variance estimates relative to phenotypic variance ranged from 1.7–3.4% for CWT and MS traits, whereas, they were close to zero for EMA and BFT traits. The magnitude of A × A epistatic heritability (haa2) ranged between 14.8 and 27.7% in all traits. However, heritability estimates for A × D and D × D epistatic interactions (had2 and hdd2) were quite low compared to haa2 and were contributed only 0.0–9.7% of the total phenotypic variation. In general, broad sense heritability (hG2) estimates were almost twice (ranging between 0.54 and 0.68) the ha2 for all of the investigated traits. The inclusion of dominance effects did not improve the prediction accuracy of GEBV but improved 2.0–3.0% when epistatic effects were included in the model. More importantly, rank correlation revealed that partitioning of variance components considering dominance and epistatic effects in the model would enable to re-rank of top animals with better prediction of GEBV. The present result suggests that dominance and epistatic effects could be included in the genomic evaluation model for better estimates of variance components and more accurate prediction of GEBV for carcass and meat quality traits in Korean Hanwoo cattle.

Overexpression of P5CDH from Cleistogenes songorica improves alfalfa growth performance under field drought conditions

Water stress affects the metabolic regulation and delays the growth and development of alfalfa, causing a reduction in biomass. New alfalfa germplasm was created with improved drought tolerance in greenhouse conditions by introducing the key gene P5CDH1 from C. songorica, a xerophytic grass. However, the field adaptability and response mechanism of new drought-tolerant alfalfa germplasms under water stress are still unclear. In the present study, the yield and quality traits of transgenic CsP5CDH1 alfalfa lines under water stress and normal irrigation conditions were measured and analyzed for two years. The genetic variance components of the tested traits were calculated from the data fitted by the mixed linear model. The plant height of all lines showed significant genotypic variation (σ2g) (P < 0.05), and the stem diameter, stem number, and dry weight of all lines had a significant genotype × environment interaction (σ2ge) (P < 0.05). The heritability (H) of plant height, stem diameter, stem number, dry weight and leaf-to-stem ratio of alfalfa lines were 0.87, 0.52, 0.59, 0.52 and 0.50, respectively. There were significant genotype × environment interactions (σ2ge) (P < 0.05) for the quality traits of all lines. The heritabilities (H) of acid detergent fiber and neutral detergent fiber were 0.65 and 0.64, respectively. The results of transcriptional expression analysis with RNA-seq showed that the genes MsProDH1, MsProDH4, MsProDH5, MsP5CDH1, MsP5CS5, MsP5CS9, and MsP5CR1, which are involved in the proline metabolism pathway, played an important role in the drought tolerance of innovative alfalfa germplasm. Under water stress, with the regulation of key genes in the proline metabolism pathway, the proline content of all alfalfa lines increased to varying degrees. Among them, the proline content in the shoots and roots of transgenic line L6 was 7.29 times and 12.22 times that under normal irrigation conditions, respectively. The present study helped to clarify that the new germplasm of alfalfa transformed with the CsP5CDH gene synthesized a large amount of proline under water stress, and effectively slowed leaf water loss, thus improving the drought resistance of alfalfa.

Dissecting the genetic architecture of quantitative traits using genome-wide identity-by-descent sharing.

Additive and dominance genetic variances underlying the expression of quantitative traits are important quantities for predicting short-term responses to selection, but they are notoriously challenging to estimate in most non-model wild populations. Specifically, large-sized or panmictic populations may be characterized by low variance in genetic relatedness among individuals which, in turn, can prevent accurate estimation of quantitative genetic parameters. We used estimates of genome-wide identity-by-descent (IBD) sharing from autosomal SNP loci to estimate quantitative genetic parameters for ecologically important traits in nine-spined sticklebacks (Pungitius pungitius) from a large, outbred population. Using empirical and simulated datasets, with varying sample sizes and pedigree complexity, we assessed the performance of different crossing schemes in estimating additive genetic variance and heritability for all traits. We found that low variance in relatedness characteristic of wild outbred populations with high migration rate can impair the estimation of quantitative genetic parameters and bias heritability estimates downwards. On the other hand, the use of a half-sib/full-sib design allowed precise estimation of genetic variance components and revealed significant additive variance and heritability for all measured traits, with negligible dominance contributions. Genome-partitioning and QTL mapping analyses revealed that most traits had a polygenic basis and were controlled by genes at multiple chromosomes. Furthermore, different QTL contributed to variation in the same traits in different populations suggesting heterogeneous underpinnings of parallel evolution at the phenotypic level. Our results provide important guidelines for future studies aimed at estimating adaptive potential in the wild, particularly for those conducted in outbred large-sized populations.

Genetic variance components of the growth curve for Isfahan indigenous chicken.

Being able to model a growth curve using three or four non-linear functional parameters could help explain the growth phenomenon in a precise way and would allow the comparison of an animal's development rate, optimize management and feeding strategies and guide animal production strategies. The goal of this study was to estimate the genetic parameters of growth traits of Isfahan indigenous chicken in Iran and to determine the best non-linear model describing the growth curve. The prediction of additive genetic parameters was performed using the REML method by WOMBAT. Direct heritability of the studied traits and genetic correlations between them were obtained. The Logistic, Gompertz, von Bertalanffy, Brody, Negative exponential, Weibull, Janoschek and Bridges models were compared based on the coefficient of determination (R2 ), mean square error (MSE) and akaike information criterion. The Gompertz model was identified as the best model for describing the growth curve for Isfahan native chicken. The heritability of maturity weights (A), initial weight (B) and maturity rate (K) parameters were 0.223±0.002, 0.016±0.005 and 0.087±0.001, respectively. This study shows that Isfahan indigenous chicken has the genetic potential for improving growth and reproduction based on their desirable heritabilities and correlations using appropriate models.

A Genetically Informed Study of the Association Between Perceived Stress and Loneliness

Although research shows a strong positive association between perceived stress and loneliness, the genetic and environmental etiology underlying their association remains unknown. People with a genetic predisposition to perceived stress, for example, may be more prone to feeling lonely and vice versa. Conversely, unique factors in people’s lives may explain differences in perceived stress levels that, in turn, affect feelings of loneliness. We tested whether genetic factors, environmental factors, or both account for the association between perceived stress and loneliness. Participants were 3,066 individual twins (nFemale = 2,154, 70.3%) from the Washington State Twin Registry who completed a survey during April–May, 2020. Structural equation modeling was used to analyze the item-level perceived stress and loneliness measures. The correlation between latent perceived stress and latent loneliness was .68. Genetic and nonshared environmental variance components underlying perceived stress accounted for 3.71% and 23.26% of the total variance in loneliness, respectively. The genetic correlation between loneliness and perceived stress was .45 and did not differ significantly between men and women. The nonshared environmental correlation was .54 and also did not differ between men and women. Findings suggest that holding constant the strong genetic association between perceived stress and loneliness, unique life experiences underlying people’s perceived stress account for individual differences in loneliness.

Diurnal variation in genetic parameters for locomotor activity in Drosophila melanogaster assessed under natural thermal conditions.

In nature, organisms are exposed to variable and occasionally stressful environmental conditions. Responses to diurnal and seasonal fluctuations, such as temperature and food accessibility, involve adaptive behavioural and physiological changes. While much work has been done on understanding the genetic architecture and evolutionary potential of stress tolerance traits under constant thermal conditions, there has been less focus on the quantitative genetic background in variable environments. In this study, we use the Drosophila Genetic Reference Panel (DGRP) to investigate the locomotor activity, a key behavioural trait, under variable natural thermal conditions during the summer in a temperate environment. Male flies from 100 DGRP lines were exposed to natural thermal and light conditions in Drosophila activity monitors across three experimental days. We found that activity was highly temperature and time dependent and varied between lines both within and between days. Furthermore, we observed variation in genetic and environmental variance components, with low to moderate estimates of the heritability for locomotor activity, consistently peaking in the afternoons. Moreover, we showed that the estimated genetic correlations of locomotor activity between two time points decreased, as the absolute differences in ambient temperature increased. In conclusion, we find that the genetic background for locomotor activity is environment specific, and we conclude that more variable and unpredictable future temperatures will likely have a strong impact on the evolutionary trajectories of behavioural traits in ectotherms.

Elucidation of Genetic Variability for Seed Yield and Its Component Traits, along with Association Studies in pigeonpea [Cajanus cajan (L.) Millspaugh.

The experimental material consisted of fifty-five pigeonpea genotypes sown in Randomized Block Design (RBD) with three replications during the kharif, 2020-2021 crop seasons at the N. E. B. Crop Research Centre of G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand. The components of genetic variance, correlation, and path coefficient were estimated for seed yield and its component by using fifty five pigeonpea genotypes. The highest PCV (&gt; 20%) was recorded for characters, viz. number of secondary branches per plant (62.34%), number of primary branches per plant (37.65%), number of pods per plant (33.00 %), and seed yield per plant (31.84%), and lowest estimates (&lt; 10%) of PCV were found for days to 50% flowering (9.45%) and days to maturity (5.74%). The high estimates of GCV (&gt; 20%) were recorded for traits viz., number of secondary branches (42.16%), number of pods per plant (32.65 %), and seed yield/plant (30.54%), and lowest estimates of GCV were (&lt;10%) for days to 50% flowering (9.43%) and days to maturity (5.71%) number of seeds per pod (5.28 %) and 100-seed weight (9.51 %). The number of pods per plant, (0.858) had high positive direct effects on the seed yield per plant along with a positive and significant correlation (rp=0.77). Based on the present investigation, it is evident that delving into genetic variability, correlations, and path analyses provides a more effective approach for selection of superior cultivars for yield and related traits.

Genetic Variability in Garden Pea (Pisum sativum L.): A Review

The estimation of variability parameters, particularly heritability and genetic gain, holds significant importance in assessing the potential for character improvement through selection. It is observed that selection based on highly heritable traits tends to yield more successful outcomes. Hence, the utilization of heritability, in conjunction with other measures of variability, enables the prediction of gains under specific selection intensities. Additionally, the concept of predicted genetic gain provides insight into the degree of change achievable in a trait through simple selection. However, the process of selecting for features related to yield and quality can be enhanced by having access to information regarding the correlation between these traits. This can be further improved by doing a path coefficient analysis to gain a deeper knowledge of the relationship between the important characteristics. In order to enhance the traits that did not exhibit a favorable response to selection, it becomes necessary to divide the non-additive component of genetic variance through the process of hybridization, which can be accomplished by conducting genetic divergence studies.

Genetic analysis of growth parameters and optimum age and weight slaughter prediction in Kurdi sheep

The objective of this study was twofold: first, it aimed at estimating genetic parameters related to growth curve using nonlinear models (Brody, Gompertz, Logistic, Von Bertalanffy, and Richards); secondly identifying an optimum age and weight for both male and female Kurdi sheep breed. To this end, the information related to the pedigree (n = 17,669) due to sires (n = 162) and dams (n = 1968) for body weight traits Viz. birth weight (BW), 3-month-old weight (3 MW), 6-month-old weight (6 MW), 9-month-old weigh (9 MW) and 12-month-old weight (12 MW) were used. To find the best-fitted model, several measures were employed including the Akaike information criterion (AIC), root mean square error (RMSE), coefficient of determination (R2), mean absolute deviation (MAD), and Bayesian information criterion (BIC). The DMU software was employed to determine the growth genetic variance components. Given AIC, MSE, and R2, the Brody model was selected as the best-fitted one for describing the growth curve in the Kurdi sheep breed. The fitted parameters A (estimated mature weight), B (an integration constant related to initial animal weight), and K (maturation rate) were estimated for models by sex separately. However, since Brody does not have a turning point to determine the appropriate turning point, we used the results of the second best-fitted model, viz Von Bertalanffy model, to find the optimum age and weight slaughter in Balafrej, (2019) equations. According to the results, there was a greater variance in weight between males and females at 12 MW compared to other ages. The optimal slaughter weights for males and females were 28.14 and 22.44 kg, respectively, and the corresponding ages were 120.49 and 90.31 days. By utilizing a multivariate animal model, the prediction of heritability for parameters A, B, and K was calculated to be 0.055, 0.117, and 0.012 respectively; indicating that genetic variation is relatively insignificant in these growth parameters. Further analysis revealed negative genetic correlations between growth parameters at rates of − 0.200 (A-B), − 0.471 (A-K), and, − 0.220 (B-K). The prediction of genetic trends for A, B, and K parameters was obtained as 0.043, 0.043, and 0.001gr/yr which could reflect different modes of selection pressure over these parameters. Despite not being the best-fitted model for Kurdi growth data, the Von Bertalanffy model can still be utilized to predict the live weight of the Kurdi sheep breed. Nonetheless, for genetic-based decision-making aimed at picking out superior animals based on accurate growth parameter predictions, it is recommended that findings from the Brody model be adapted for downstream genetic analysis in the Kurdi sheep breed.