Significant Effect Of Genotype Research Articles

Genome-wide analysis of miR172-mediated response to heavy metal stress in chickpea (Cicer arietinum L.): physiological, biochemical, and molecular insights.

Chickpea (Cicer arietinum L.), a critical diploid legume in the Fabaceae family, is a rich source of protein, vitamins, and minerals. However, heavy metal toxicity severely affects its growth, yield, and quality. MicroRNAs (miRNAs) play a crucial role in regulating plant responses to both abiotic and biotic stress, including heavy metal exposure, by suppressing the expression of target genes. Plants respond to heavy metal stress through miRNA-mediated regulatory mechanisms at multiple physiological, biochemical, and molecular levels. Although the Fabaceae family is well represented in miRNA studies, chickpeas have been notably underrepresented. This study aimed to investigate the effects of heavy metal-induced stress, particularly from 100 µM concentrations of cadmium (Cd), chromium (Cr), nickel (Ni), lead (Pb), and 30 µM arsenic (As), on two chickpea varieties: ILC 482 (sensitive) and Azkan (tolerant). The assessment focused on physiological, biochemical, and molecular parameters. Furthermore, a systematic characterization of the miR172 gene family in the chickpea genome was conducted to better understand the plant's molecular response to heavy metal stress. Variance analysis indicated significant effects of genotype (G), treatment (T), and genotype-by-treatment (GxT) interactions on plant growth, physiological, and biochemical parameters. Heavy metal stress negatively impacted plant growth in chickpea genotypes ILC 482 and Azkan. A reduction in chlorophyll content and relative leaf water content was observed, along with increased cell membrane damage. In ILC 482, the highest hydrogen peroxide (H₂O₂) levels in shoot tissue were recorded under As, Cd, and Ni treatments, while in Azkan, peak levels were observed with Pb treatment. Malondialdehyde (MDA) levels in root tissue were highest in ILC 482 under Cd and Ni exposure and in Azkan under As, Cr, and Cd treatments. Antioxidant enzyme activities, including superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), and ascorbate peroxidase (APX), were significantly elevated under heavy metal stress in both genotypes. Gene expression analysis revealed upregulation of essential antioxidant enzyme genes, such as SOD, CAT, and APX, with APX showing notable increases in both shoot and root tissues compared to the control. Additionally, seven miR172 genes (miR172a, miR172b, miR172c, miR172d, miR172e, miR172f, and miR172g) were identified in the chickpea genome, distributed across five chromosomes. All genes exhibited conserved hairpin structures essential for miRNA functionality. Phylogenetic analysis grouped these miR172 genes into three clades, suggesting strong evolutionary conservation with other plant species. The expression analysis of miR172 and its target genes under heavy metal stress showed varied expression patterns, indicating their role in enhancing heavy metal tolerance in chickpea. Heavy metal stress significantly impaired plant growth and physiological and biochemical parameters in chickpea genotypes, except for cell membrane damage. The findings underscore the critical role of miR172 and its target genes in modulating chickpea's response to heavy metal stress. These insights provide a foundational understanding for developing stress-tolerant chickpea varieties through miRNA-based genetic engineering approaches.

AMMI Biplot Analysis for Stability of Grain Yield in Foxtail Millet [Setaria italica (L.) P. Beauv.] Genotypes

Background: Foxtail millet cultivation in India’s NEH region holds promise due to its adaptation to diverse environments and high-quality grain. Studying G × E interaction in this region will guide breeding programs to develop foxtail millet varieties adapted to local conditions. The objective of this study was to find out foxtail millet genotypes that produce high yield in diverse environments and to identify ideal mega-environments using additive main effects and multiplicative interaction stability model analysis. Methods: In this study, 30 genotypes were evaluated at the Research Farm of the SAS, Nagaland University, Medziphema, India. The experiment was conducted during July 2022 to May 2023 involving four different environments. Two environments were rainfed and two were irrigated with weekly intervals. The experiment was conducted in randomized complete block design (RCBD) with three replications in all the environments. Result: Genotype-environment interactions significantly influenced grain yield across four environments, while replicates were non-significant. Pooled analysis revealed significant genotypic effects and seasonal impacts. AMMI analysis revealed significant effect on environmental and genotypic influences on grain yield and explained 23.47% and 27.94% variability respectively. The AMMI model effectively decomposed the intricate genotype-environment interaction into three principal components (PC1, PC2and PC3), explaining 54.5%, 28.7%and 16.8% of the interaction variance, respectively. AMMI model exposed genotypes viz G8, G9, G21and G22 as best performer and stable. AMMI stability value revealed G10 with highest stability (ASV = 0.34) followed by G15, G7, G29, G6and G13 in decreasing order indicating their consistent performance in grain yield across different environments.

Diversity of Major Yield Traits and Nutritional Components Among Greenhouse Grown Chickpea (Cicer arietinum L.) Breeding Lines, Landraces, and Cultivars of Different Origins.

This study analyzed the diversity of major yield traits and nutritional components across 122 chickpea breeding lines, cultivars, and landraces of different origins. All parameters showed significant variations, with a variance ranging from 4.61% in days to maturity (DM) to 43.04% in oleic acid. Six accessions, including CP021, CP022, CP026, CP037, CP066, and CP109, outperformed in yield traits and nutritional value. Origin significantly affected all phenotypic traits except total fatty acid contents, with Indian and Ukrainian accessions demonstrating contrasting performances. Most traits, except for the number of seeds per pod (SPP), palmitic acid, and total fatty acid contents, differed significantly among breeding lines, cultivars, and landraces. Breeding lines were the earliest to flower and to mature with average days to flowering (DF) of 50.23 days and DM of 101.50 days. They also had the highest average SPP, number of pods per plant (PPP), total seeds per plant (TSPP), total protein, crude fiber, dietary fiber, linoleic acid, and linolenic acid contents making them preferable for high yield and nutrition. Hierarchical cluster analysis classified the chickpea accessions into seven clusters, showing significant variations in yield traits and nutritional components. Principal component and Pearson's correlation analyses indicated positive correlations between DM and DF, and between SPP, PPP, and TSPP. Nutritional components also displayed varying associations, with a notable negative correlation between oleic and linoleic acids, the two essential fatty acids. Overall, this study showed the diversity of key phenotypic traits in chickpea breeding lines, cultivars, and landraces of different origins. The significant effects of genotype and origin differences on these traits could be used as a basis for future metabolomics and genomics research.

Biochemical and morpho-physiological insights revealed low moisture stress adaptation mechanisms in cotton (Gossypium hirsutum L.)

Cotton (Gossypium hirsutum L.) is a multipurpose crop. Abiotic stresses, especially extreme heat and drought, limit crop growth and thus reduce cotton yield by about 50%. In this study, 30 cotton genotypes were tested against low moisture stress in a pot experiment in triplicates along with control under wire house conditions. At the 3–4 leaf stage, different morpho-physiological and biochemical parameters were measured in order to select the low moisture stress-tolerant genotypes. For the selection of the best performing genotypes, Multi-Trait Genotype-Ideotype Distance Index (MGIDI) was used for the ranking of genotypes on the basis of multiple indices. For biochemical traits, 09 (TPC, TF, TSP, MDA, SOD, POD, CAT, APX, and Proline) out of 24 showed significant genotypic effects and were used for MGIDI. Eight genotypes (N-812 N-1296 N-696 N-377 N-121–896 N-T86, and N-3496) were observed to be best performing than others at 25% selection pressure (SI = 25%). For morpho-physiological traits, 14 out of 15 showed significant genotypic effects and used for MGIDI. Ten genotypes (N-1237 N-812 N-1296 N-696 N-9078 N-377 N-512 N-121 N-375, and N-896) were observed to be best performing at 35% selection pressure (SI = 35%). Six genotypes, i.e. N-812–1296 N-696 N-377 N-121, and N-896 were found common in both MGIDI analysis. In conclusion, three genotypes, i.e. N-696, N-896, and N-T86 proved to be most resilient to low moisture stress. Develop protocols, identified genotypes and markers that can be used for development of climate-smart cotton genotypes.

Sex differences in sleep deficits in mice with an autism-linked Shank3 mutation

BackgroundInsomnia is more prevalent in individuals with Autism Spectrum Disorder (ASD), can worsen core-symptoms and reduces quality of life of both individuals and caregivers. Although ASD is four times more prevalent in males than females, less is known about sex specific sleep differences in autistic individuals. Recent ASD studies suggest that sleep problems may be more severe in females, which aligns with the sex bias seen in insomnia for the general population. We have previously shown that male mice with a mutation in the high confidence ASD gene Shank3, Shank3∆C, recapitulate most aspects of the ASD insomnia phenotype. The objective of the present study was to leverage the Shank3∆C model to investigate sex-specific effects in sleep using polysomnography.MethodsAdult male and female Shank3∆C and wildtype (WT) littermates were first recorded for 24 h of baseline recordings. Subsequently, they were sleep deprived (SD) for five hours via gentle handling and allowed 19 h of recovery sleep to characterize the homeostatic response to SD. Vigilance states (rapid eye movement (REM) sleep, non-rapid eye movement (NREM) sleep and wake) were assigned by manual inspection using SleepSign. Data processing, statistical analysis and visualization were conducted using MATLAB.ResultsSex and genotype effects were found during baseline sleep and after SD. At baseline, male Shank3∆C mice sleep less during the dark period (active phase) while female Shank3∆C mice sleep less during the light period (rest phase) and sleep more during the dark period. Both male and female Shank3∆C mice show reduced spectral power in NREM sleep. We detect a significant effect of sex and genotype in sleep onset latency and homeostatic sleep pressure (sleepiness). In addition, while male Shank3∆C mice fail to increase sleep time following SD as seen in WT, female Shank3∆C mice decrease sleep time.ConclusionsOverall, our study demonstrates sex differences in sleep architecture and homeostatic response to SD in adult Shank3∆C mice. Thus, our study demonstrates an interaction between sex and genotype in Shank3∆C mice and supports the use of the Shank3∆C model to better understand mechanisms contributing to the sex differences in insomnia in ASD in clinical populations.

Genetic, breeding and environmental parameters for yellow sugarcane aphid (Sipha flava) damage in advanced South African sugarcane breeding populations

Yellow sugarcane aphid (YSA), a native pest of temperate and subtropical regions in North America, has spread to many regions of the world including KwaZulu-Natal and Mpumalanga sugarcane growing regions of South Africa. Cultivar differences to YSA damage have been observed in Mpumalanga where high infestation levels occur. The objectives of this study were to determine genetic, breeding, and environmental parameters for YSA damage and implications on breeding for resistance. Data for YSA damage were collected from 12 genotype populations planted in Mpumalanga. There were significant (p < 0.0001) genotype effects indicating genetic variability. Significant (p < 0.01) environment effects showed that YSA damage in February was significantly (p < 0.05) higher than in December. The significant (p < 0.01) genotype by environment interaction indicated February as the best month to screen for YSA. Higher broad sense heritability (> 0.70) suggests selecting resistant genotypes would be effective. Data collected in February produced higher broad sense heritability (> 0.80) than in December (< 0.70) suggesting February as the preferred month to score for damage. The proportion of resistant genotypes was 16.5% (range 2–34%), indicating the presence of resistant in South African advanced genotype populations. Evaluation of released cultivars showed N36, N49 and N71 are resistant while N57 and N73 are susceptible.

Identification of foxtail millet (Seteria italica (L.) P. Beauv.) genotypes for multi-season adaptability using GGE biplot analysis in Foothills of Nagaland

Foxtail millet is a main millets crop of Northeastern region of India. The genotype-by-environment analyses assist in understanding the potential performance of the genotypes over environments. The present study aimed to investigate the 30 foxtail genotypes over the four different environments to identify the genotypes with stable yield in this region. The investigation was carried out during July 2022 to May 2023 for four different dates of sowing with fifty-five days interval. Two environments maintained under rainfed condition and the remaining two environments are maintained under irrigated condition with seven days interval. The experiment was conducted in randomized complete block design with three replications in all environments. Genotype-environment interactions significantly influenced grain yield across four environments, while replicates were non-significant. Pooled analysis revealed significant genotypic effects and seasonal impacts. The “discriminating power vs. representativeness” GGE biplot showed that E4 (showing dates in January 2ndfort night) is the most ideal test environment for foxtail millet elite line selection based on discriminative ability and representativeness. The accessions that performed best in each environment based on “which-won-where” polygon biplot, genotypes G19 (FOX 4392) and G27 (FOX 4420) showed superior and stable performance in E1, however G25 (FOX 4341) and G1 (ELS 20) excelled in E2, E3, and E4.Mean vs stability biplots exposed G1 (ELS 20) is stable and high yielding performance. Ranking genotypes GGE biplot identify the G25 (FOX 4341) is an ideal genotype due to its higher yield and stability compared to the other genotypes. Keywords: GGE Biplots, Foxtail millet, Tukey's Honest Significant Difference (HSD) Test

8245 Estradiol Interacts with the Val66Met Single Nucleotide Polymorphism in the Brain-Derived Neurotrophic Factor Gene to Alter Endometrial Thickness in a Rat Model

Abstract Disclosure: S. Moosa: None. E. Kohlmeir: None. S. Kujawa: None. D. Korol: None. A. Prakapenka: None. Brain derived neurotrophic factor (BDNF) is most known for its involvement in cell development, survival, and plasticity in the nervous system. BDNF and its cognate receptors can also be found in non-neural tissue including the ovary and uterus in humans and in animal models, suggesting that BDNF signaling may regulate reproductive functions. Indeed, disruptions in BDNF signaling are associated with health conditions related to the reproductive system, such as endometriosis. Studies show that treatment with estradiol increases expression of uterine BDNF and its cognate receptors, suggesting that estradiol can modulate BDNF signaling and its effects in the reproductive system. A common human functional single nucleotide polymorphism (SNP) in the BDNF gene, Val66Met (rs6265), is thought to decrease activity-dependent release of BDNF, altering BDNF signaling. Using a CRISPR/cas9 rat model of the human Val66Met BDNF SNP, we investigated the interacting role of estradiol and this variation in the BDNF gene on female uterine structure. Middle-aged (11-14-months-old) female rats were either homozygous for the Val allele (Val/Val; control) or the Met allele (Met/Met; BDNF SNP). All rats were ovariectomized and after three weeks randomly assigned to receive subcutaneous treatment of vehicle (sesame oil) or estradiol (17beta-estradiol benzoate) for two consecutive days. Twenty-four hours after the second injection, rats were euthanized and tissue collected, weighed, and placed in fixative. Uterine tissue weights differed significantly by treatment and by genotype such that uterine horns were heavier in estradiol-treated compared to vehicle-treated rats within each genotype and uterine horns were heavier in Met/Met compared to Val/Val rats within each treatment condition. To determine which uterine layer contributed to the weight differences, uterine horns were sectioned and stained with hematoxylin and eosin. Thickness of myometrium, endometrium, and lumen were individually measured. Although there were no treatment and no genotype effects on myometrial thickness, there were significant treatment and genotype effects on endometrial thickness. Of note, the endometrium of estradiol-treated Met/Met rats was thicker compared to vehicle-treated Met/Met rats and compared to estradiol-treated Val/Val rats, suggesting that estradiol and the BDNF gene variation interact to modulate endometrial size. Lumen circumference did not differ between genotypes but did increase with estradiol compared to vehicle treatment within each genotype. Altogether, findings suggest that BDNF genotype affects uterine structure, notably the endometrium. Differences with BDNF gene variation emerged with estradiol exposure, implicating the hormone’s role in modulating BDNF signaling and warranting future research on the interactive effects of estradiol and BDNF genotype on the endometrium. Presentation: 6/2/2024

8245 Estradiol Interacts with the Val66Met Single Nucleotide Polymorphism in the Brain-Derived Neurotrophic Factor Gene to Alter Endometrial Thickness in a Rat Model

Abstract Disclosure: S. Moosa: None. E. Kohlmeir: None. S. Kujawa: None. D. Korol: None. A. Prakapenka: None. Brain derived neurotrophic factor (BDNF) is most known for its involvement in cell development, survival, and plasticity in the nervous system. BDNF and its cognate receptors can also be found in non-neural tissue including the ovary and uterus in humans and in animal models, suggesting that BDNF signaling may regulate reproductive functions. Indeed, disruptions in BDNF signaling are associated with health conditions related to the reproductive system, such as endometriosis. Studies show that treatment with estradiol increases expression of uterine BDNF and its cognate receptors, suggesting that estradiol can modulate BDNF signaling and its effects in the reproductive system. A common human functional single nucleotide polymorphism (SNP) in the BDNF gene, Val66Met (rs6265), is thought to decrease activity-dependent release of BDNF, altering BDNF signaling. Using a CRISPR/cas9 rat model of the human Val66Met BDNF SNP, we investigated the interacting role of estradiol and this variation in the BDNF gene on female uterine structure. Middle-aged (11-14-months-old) female rats were either homozygous for the Val allele (Val/Val; control) or the Met allele (Met/Met; BDNF SNP). All rats were ovariectomized and after three weeks randomly assigned to receive subcutaneous treatment of vehicle (sesame oil) or estradiol (17beta-estradiol benzoate) for two consecutive days. Twenty-four hours after the second injection, rats were euthanized and tissue collected, weighed, and placed in fixative. Uterine tissue weights differed significantly by treatment and by genotype such that uterine horns were heavier in estradiol-treated compared to vehicle-treated rats within each genotype and uterine horns were heavier in Met/Met compared to Val/Val rats within each treatment condition. To determine which uterine layer contributed to the weight differences, uterine horns were sectioned and stained with hematoxylin and eosin. Thickness of myometrium, endometrium, and lumen were individually measured. Although there were no treatment and no genotype effects on myometrial thickness, there were significant treatment and genotype effects on endometrial thickness. Of note, the endometrium of estradiol-treated Met/Met rats was thicker compared to vehicle-treated Met/Met rats and compared to estradiol-treated Val/Val rats, suggesting that estradiol and the BDNF gene variation interact to modulate endometrial size. Lumen circumference did not differ between genotypes but did increase with estradiol compared to vehicle treatment within each genotype. Altogether, findings suggest that BDNF genotype affects uterine structure, notably the endometrium. Differences with BDNF gene variation emerged with estradiol exposure, implicating the hormone’s role in modulating BDNF signaling and warranting future research on the interactive effects of estradiol and BDNF genotype on the endometrium. Presentation: 6/2/2024

APOE×BDNF Interaction and Poorer Cognitive Outcomes Among Veterans With Mild Traumatic Brain Injury: An Exploratory Study.

The authors examined the interaction between apolipoprotein E (APOE) ε4 and brain-derived neurotrophic factor (BDNF) Val66Met alleles on neuropsychological functioning among veterans with histories of mild traumatic brain injury (mTBI). Participants were 78 veterans with mTBI (85% males; mean±SD age=32.95±7.00 years; mean time since injury=67.97±34.98 months) who completed a structured clinical interview and underwent a comprehensive neuropsychological assessment. Participants also provided a buccal swab for determination of their APOE and BDNF genotypes. Three cognitive composite scores were calculated from the neuropsychological assessment, reflecting visuospatial speed (seven variables), executive functioning (10 variables), and memory (eight variables). Two-way analyses of covariance (ANCOVAs) adjusted for age, sex, and race-ethnicity were used to assess the effects of APOE (ε4+ vs. ε4-) and BDNF (Met+ vs. Met-) on cognitive functioning. ANCOVAs revealed no significant main effects of APOE or BDNF genotypes on cognitive functioning; however, there was a significant APOE-by-BDNF genotype interaction for all three cognitive composite measures (visuospatial speed: ηp2=0.055; executive functioning: ηp2=0.064; and memory: ηp2=0.068). Specifically, the ε4+/Met+ (N=8) subgroup demonstrated the poorest cognitive functioning relative to all other allele subgroups (ε4+/Met-: N=12, ε4-/Met+: N=23, and ε4-/Met-: N=35). This exploratory study is the first to show that, compared with other allele subgroups assessed, veterans with both ε4 and Met alleles demonstrated the poorest cognitive functioning across several cognitive domains known to be negatively affected in the context of mTBI. Further research with larger sample sizes is needed to replicate these findings.

Identification of high-yielding and stable cultivars of wheat under different sowing dates: Comparison of AMMI and GGE-biplot analyses

Evaluating the adaptability and yield stability of wheat varieties across different sowing dates is crucial for the success of breeding programs. In this study, we used Additive Main Effects and Multiplicative Interactions (AMMI) and Genotype × Genotype–Environment (GGE) biplot analyses to evaluate the performance of 13 wheat varieties across eight sowing dates. The main objective was to compare varieties and sowing dates to identify the most stable varieties for cultivation. Both AMMI and GGE biplot analyses showed significant effects of genotype, environment and genotype-environment (GE) interaction on grain yield. The interaction patterns identified by AMMI and GGE-biplots categorized Mihan, Oroom and Pishgam as the most stable, high yielding and early maturing wheat varieties. Furthermore, while the GGE biplot method proved to be more efficient than the AMMI model for stability analysis, our results indicate considerable overlap between the results of these two approaches. These results provide a valuable basis for optimizing genetic improvement strategies in wheat breeding programs.

Analyzing Sunflower Trait Patterns Using MANOVA, PCA, and Correlation Across Seasons and Locations

Sunflower is an important agricultural crop valued for its high oil yield, versatility in culinary and industrial applications and adaptability to diverse environments. Eight advanced sunflower genotypes were tested in a randomized complete block design (RCBD) with three replications at six locations over the 2018 and 2019 seasons. The study aimed to evaluate the effects of environmental and genotypic variations using MANOVA, PCA, and correlation analysis to discover trait patterns and relationships. The MANOVA results revealed highly significant effects of genotype, environment, and their interaction on the 11 dependent variables (p &amp;lt; 0.001). The four principal components account for 74.23% of the total variation, with key traits such as seed yield per hectare, oil yield per hectare, days to maturity, plant height, and grain filling period significantly contributing to the overall variability. Oil yield per hectare and seed yield per hectare exhibited a very strong association (0.974). Days to maturity (DM) and grain filling period (GFP) showed a strong correlation (0.666), suggesting that longer grain filling periods may enhance both maturity and yield. Additionally, plant height (PH) and seed yield per hectare (YELDK) had a moderate correlation (0.491). Breeding programs should target traits with strong correlations to boost sunflower productivity and adaptability. Future research should prioritize selecting genotypes that perform well across diverse environments, focusing on seed yield, oil yield, and traits such as maturity and grain filling period. Additionally, breeding should incorporate disease resistance and optimize days to flowering to develop more robust and productive sunflower varieties.

Stable isotope composition of long and short term carbon pools can screen drought tolerance in cassava

Leaf carbon isotope composition (δ13C) is a promising trait for assessing genotypic differences in responses to environmental stress, particularly drought. Despite its potential, comprehensive evaluations of δ13C across various carbohydrate pools and leaf positions, in comparison with other traits, are still lacking for cassava (Manihot esculenta). This study aimed to estimate the genotypic effect size and the correlation with yield for δ13C and other commonly assessed traits in cassava. We compared the δ13C values at bulk root initiation stage of fourteen genotypes grown in the wet (1450 mm annual rainfall) and dry Caribbean (950 mm annual rainfall). We focused on both non-structural (soluble sugars) as well as structural (cellulose) carbohydrate pools across multiple leaf positions. Our results revealed significant genotypic effects across nearly all pools and leaf positions, which were equal or larger than other commonly measured traits. Interestingly, correlations between isotope composition and root yield were only observed in the dry location, with upper leaves exhibiting weaker correlations across all carbohydrate pools. Notably, while soluble sugars displayed stronger correlations with yield, they also demonstrated higher susceptibility to within-field variations. Furthermore, complementary information was found when combining δ13C with other traits such as leaf retention. Combining isotope compositions across various carbohydrate pools may reveal insights into source-sink dynamics. These results underscore the potential of δ13C as a tool for improving drought tolerance in cassava and provide a basis for its integration into cassava breeding programs, when used under dry conditions. To enhance the practical utility of δ13C as a screening technique, further research is advised to validate these findings across multiple locations, growing seasons and growth stages.

Unraveling genotypic interactions in sugar beet for enhanced yield stability and trait associations

The interaction between genotype and environment (GEI) significantly influences plant performance, crucial for breeding programs and ultimately boosting crop productivity. Alongside GEI, breeders encounter another hurdle in their quest for yield improvement, notably adverse and negative correlations among pivotal traits. This study delved into the stability of white sugar yield (WSY), root yield (RY), sugar content (SC), extraction coefficient of sugar (ECS), and the interplay among essential traits including RY, SC, alpha amino nitrogen (N), sodium (Na+), and potassium (K+) across 15 sugar beet hybrids and three control varieties. The investigation spanned two locations over two consecutive years (2022–2023), employing a randomized complete block design with four replications to comprehensively analyze these factors. The analysis of variance highlighted the significant effects of environment, genotype, and GEI at the 1% probability level. Notably, the AMMI analysis of GEI revealed the significance of the first component for WSY, RY, and SC, with the first two components proving significant for ECS. Within the linear mixed model (LMM), WSY, RY, SC, and ECS demonstrated significant effects from both genotype and GEI. In the WAASB biplot, genotypes 10, 8, 17, 6, 13, 14, 15, 7, 12, and 16 exhibited stability in WSY, while genotypes 9, 10, 6, 14, 7, 8, 13, 12, 18, and 15 displayed stability in RY. Additionally, genotypes 10, 15, 12, 13, 16, 17, 6, and 14 were stable for SC, and genotypes 8, 10, 7, 6, 13, 12, 16, 17, 15, 14, and 18 showcased stability in ECS, boasting above-average yield values. In the genotype by yield × trait (GYT) biplot, genotypes 15, 18, and 16 emerged as top performers when combining RY with SC, Na+, N, and K+, suggesting their potential for inclusion in breeding programs.

Genotype by environment interaction effect and fresh root yield stability of cassava genotypes under contrasting nitrogen regimes

Nitrogen (N) is an important nutrient element needed by cassava for optimum yield and it is a vital component of nucleotides (nucleic acids), enzymes, amino acids (proteins), chlorophyll molecules and hormones, among other essential compounds required for growth and development of cassava. Nitrogen stress is a major cassava production constraint, the study aimed to examine genotype by environment interaction (GEI) effects and fresh root yield stability of 203 diverse cassava clones to identify genotypes with stable performance under low and optimum nitrogen regimes across environments using AMMI and GGE biplot analysis. Experiments were conducted using an augmented block design with three replications for two years in three locations in Nigeria. There were significant differences (p < 0.001) in the genotype’s mean performances as well as significant differences (p < 0.001) in the environment’s mean performances for all the traits measured in both nitrogen regimes. The AMMI analysis of variance showed significant effects (p < 0.001) for genotypes, environments and the interactions for fresh root yield in both nitrogen regimes. The biplot analysis showed that for fresh root yield in the optimum nitrogen regime, the principal component accounted for 81.54% of the G + GE (Genotype plus and Genotype by Environment) variation. The G + GE for fresh root yield in the low nitrogen regime accounted for a total of 71.64% of the variation. Ten genotypes were identified as the best genotypes under the optimum nitrogen regime, while eleven genotypes were the best under the low nitrogen regime. Three genotypes under optimum nitrogen regimes were high-yielding. Still, they were unstable in their fresh root yield performance across the environments and can be recommended as specifically adapted to the environments they performed best. Three other genotypes were high-yielding genotypes under low nitrogen but were highly unstable in their fresh root yield mean performance across the environments. The environments Otobi_YR1, Igbariam_YR2, and Umudike_YR1 were identified as the most discriminatory among the test environments. The environments Umudike_YR2 and Igbariam_YR1 were identified as the most representative of the test environments and can represent a mega-environment. The best 21 genotypes that performed above the grand mean for fresh root yield in both nitrogen regimes can be further evaluated on the farmer’s field for possible advancement.

The influence of genotype and sex on carcass composition, meat quality, digestive system morphometry and leg bone dimensions in Japanese quails (C. coturnix japonica)

Japanese quails (Coturnix japonica) have a high reproductive rate because they reach sexual maturity very early. This short rearing time results in increasing interest among breeders and consumers. The aim of the study was a comparative analysis of two genotypes and sexes of Japanese and Pharaoh quails and their impact on body weight, carcass composition, meat quality, digestive system morphometry and leg bone dimensions. The study involved 40 birds (10 females and 10 males), Japanese quail and Pharaoh quail, 42 days old. Quail genotype had an effect (P < 0.05) on body weight, carcass weight, and some percentage of carcass elements. In addition, there was a significant effect of quail genotype on intramuscular fat and water content of pectoral and leg muscles. The origin of the quails interacted (P < 0.05) with the lightness (L*), yellowness (b*), cutting work, hardness, springiness, chewiness, gumminess, fibre cross-sectional area, vertical fibre diameter, and perimysium thickness of pectoral muscle. In addition, genotype was found to influence some anatomical traits, such as the percentage of proventriculus, heart, and liver on body weight, lengths and diameters of duodenum, caeca, and colon, and most dimensions of leg bones (femur and tibia). The sex of the birds significantly (P < 0.05) affected body weight, carcass weight, percentage of skin with subcutaneous fat in the carcass, as well as water content, lightness (L*), and springiness, most microstructure characteristics of pectoralis muscle, and also water and protein contents, and yellowness (b*) of leg muscles. In addition, differences were found between males and females (P < 0.05) in terms of duodenum and caeca diameter, length of greatest and medial femur, and greatest length of tibia. It can be stated that in terms of body weight and carcass weight as well as some meat quality features (protein content, fat content, fiber cross-sectional area), the pharaoh quail was the better genotype, while in terms of the proportion of muscles in the carcass and selected meat quality features: hardness, gumminess, chewiness, Japanese quails turned out to be better.

Genotype-environment interaction for grain yield in maize (Zea mays L.) using the additive main effects and multiplicative interaction (AMMI) model.

Genotype-environment interaction consists of the different response of individual genotypes resulting from changing environmental conditions. Its significance is a phenomenon that makes the breeding process very difficult. On the one hand, the breeder expects stable genotypes, i.e., yielding similarly regardless of environmental conditions. On the other hand, selecting the best genotypes for each region is one of the key challenges for breeders and farmers. The aim of this study was to evaluate genotype-by-environment interaction for grain yield in new maize hybrids developed by Plant Breeding Smolice Co. Ltd., utilizing the additive main effects and multiplicative interaction (AMMI) model. The investigation involved 69 maize (Zea mays L.) hybrids, tested across five locations in a randomized complete block design with three replications. Grain yield varied from 8.76 t ha-1 (SMH_16417 in Smolice) to 16.89 t ha-1 (SMH_16043 in Płaczkowo), with a mean yield of 13.16 t ha-1. AMMI analysis identified significant effects of genotype, environment, and their interaction on grain yield. Analysis of variance indicated that 25.12% of the total variation in grain yield was due to environment factor, 35.20% to genotypic differences, and 21.18% to genotype by environmental interactions. Hybrids SMH_1706 and SMH_1707 are recommended for further breeding programs due to their high stability and superior average grain yield.

CYP2B6 and ABCB1 genotypes predict methadone plasma exposure among patients on maintenance therapy against opioid addictions in Tanzania.

Methadone maintenance therapy (MMT) exhibits significant variability in pharmacokinetics and clinical response, partly due to genetic variations. However, data from sub-Saharan African populations are lacking. We examined plasma methadone variability and pharmacogenetic influences among opioid-addicted Tanzanian patients. Patients attending MMT clinics (n = 119) in Tanzania were genotyped for common functional variants of the CYP3A4, CYP3A5, CYP2A6, CYP2B6, CYP2C19, CYP2D6, ABCB1, UGT2B7 and SLCO1B1 genotypes. Trough plasma concentrations of total methadone, S-methadone (S-MTD) and R-methadone (R-MTD), with their respective metabolites, 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP), were quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The methadone-to-EDDP metabolic ratio (MMR) was used to categorize the phenotype. The proportions of MMR-predicted ultrarapid, extensive, intermediate and slow methadone metabolizer phenotypes were 2.5%, 58.2%, 23.7% and 15.6%, respectively. CYP2B6 genotype significantly correlated with S-methadone (P = .006), total methadone (P = .03), and dose-normalized methadone plasma concentrations (P = .001). Metabolic ratios of R-methadone (R-MTD/R-EDDP), S-methadone (S-MTD/S-EDDP), and total methadone (MMR) were significantly higher among patients homozygous for defective variants (*6 or *18) than heterozygous or CYP2B6*1/*1 genotypes (P < .001). The metabolic ratio for S-MTD and total methadone was significantly higher among ABCB1c.3435T/T than in the C/C genotype. No significant effect of CYP2D6, CYP2C19, CYP3A4, CYP3A5, CYP2A6, UGT2B7 and SLCO1B1 genotypes on S-methadone, R-methadone, or total methadone was observed. Approximately one in six opioid-addicted Tanzanian patients are methadone slow metabolizers, influenced by genetic factors. Both the CYP2B6 and ABCB1 genotypes are strong predictors of methadone metabolic capacity and plasma exposure. Further investigation is needed to determine their predictive value for methadone treatment outcomes and to develop genotype-based dosing algorithms for safe and effective therapy.

The influence of PER3 VNTR genotypes on the age of onset in a group of bipolar I disorder patients: an exploratory study

BackgroundPER3 is a circadian gene that contains a variable number of tandem repeats (VNTR) which codifies for three genotypes: 4/4; 4/5; and 5/5 and is involved in non-visual response to light, a critical process associated with bipolar disorder onset. Benedetti et al. (Neurosci Lett 445(2):184–7) related this VNTR with bipolar disorder age of onset and linked genotype 5/5 with an earlier onset. In this study, we aimed to investigate these associations of PER3 VNTR genotypes with age of onset in a homogenous sample of German patients with bipolar I disorder through Kaplan-Meier curves.Methods45 patients were enrolled and divided into three groups according to PER3 VNTR genotypes. Recognizing common biological features, we built a combined group of -5 allele carriers (4/5 + 5/5). As a primary outcome, Kaplan-Meier analysis was conducted to delineate the three genotypes’ influence on age of onset. The secondary Kaplan-Meier analysis aimed to evaluate the relation between the 4/4 homozygotes group and the combined group (4/5 + 5/5) with age of onset. Finally, we proceeded to compare groups through a Log Rank Test and performed an analysis of covariance (ANCOVA).ResultsThe Kaplan-Meier analysis with three separate genotypes didn’t replicate the findings of Benedetti’s study. The analysis comparing genotype 4/4 with the combined group showed the influence of PER3 VNTR variants on the age of onset and relates genotype 4/4 to an earlier onset. ANCOVA between the combined and the 4/4 genotype groups, correlated genotype 4/4 with an increased number of depressive episodes.ConclusionThis study showed no significant effect of PER3 VNTR genotypes on the age of onset and in linking genotype 5/5 with an earlier onset age. Contrasting results may arise from intrinsic differences between the two studies but also shed light on hypothetically different levels of functioning of PER3 VNTR genotypes in the context of bipolar pathology. Further studies will require bigger and more homogeneous clinical samples.

Inter-annual and genotypic variation of morphological and physicochemical characters in moroccan loquat (Eriobotrya Japonica Lindil.) genotypes during two consecutive years.

Plant development is constantly affected by biotic and abiotic factors, which influence their morphology and chemical composition. In this context, the evaluation of morphological and physicochemical variation of 35 loquat genotypes during two consecutive years, 2015 and 2016, were carried out. The results revealed a significant difference of the morphological and the physicochemical traits between the two years. Indeed, 2016 showed high values for fruit and leaf traits as well as the physicochemical parmeters, while 2015 recoreded the highest values for seeds traits. In addition, the ANOVA results showed a significant effect of genotype on the physicochemical parameters and the morphological characters, excluding the geometric diameter and spherical index of seeds. Regarding the effect of year, it was also significant on physicochemical parameters and morphological traits except the size and shape of fruit and the seed shape. For the genotype x year interaction effect, it was significant on all traits studied, with the exception of the traits relating to geometric diameter of fruit and seed plus the sphericity index of the seed. Thus, size and shape of fruit remained stable over these two consecutive years. The identification of stable traits presents a result that could be beneficial for breeding programs.