Selection For Traits Research Articles

Variability and Diversity Studies Using Morpho-physiological Traits in Wheat (Triticum aestivum L.) under Irrigated and Rainfed Conditions

A study was conducted at Rice and Wheat Research Centre, Malan and Department of Genetics and Plant Breeding, CSK HPKV, Palampur, Himachal Pradesh, India during October, 2013 to May, 2014 to identify traits for developing reliable selection criteria and conduct diversity analysis. In the present investigation, fifty-six diverse wheat genotypes were evaluated in an alpha-design using various yield attributes and drought indices under irrigated and moisture-stress environments over three environments in two locations. Results from the study indicated significant differences for almost all the traits under all three environments and pooled environments. Variability studies showed high phenotypic and genotypic coefficient of variability with high heritability coupled with high genetic advance for seedling vigour under irrigated conditions as well as under moisture-stress conditions along with membrane stability index, dry matter accumulation and grain yield. On the basis of low DSI and high DRI values and relative ranking of morpho-physiological traits, seven genotypes HPW 368, NI 5439, CM 33, CM 19, HPW 236, CM 11 and HPW 349 have been found to be moisture-stress tolerant. Association studies showed that grains spike-1, harvest index, thousand grain weight, excised leaf water loss and days to 75% maturity are most important traits for selection of tolerant genotypes. On the basis of D2 statistics, 56 genotypes were grouped into twelve main clusters and genotypes HPW 277, HPW 297 and NIAW 1415 were found superior as well as diverse for most of the traits. Hence, these genotypes can be used in breeding programmes aimed at enhancing drought tolerance.

Multivariate analysis and image-based phenotyping of cayenne fruit traits in selection and diversity mapping of multiple F1 cross lines

The phenomenon of fluctuating chili prices can be resolved in stages, one of which is through multiple crosses. However, this cross requires precise methods in the evaluation and selection process, especially regarding fruit characteristics. Image-based phenotyping 4.0 approaches can increase the potential precision of such evaluation genotypes, especially when this approach is combined with multivariate analysis. Therefore, both methods are needed to evaluate and select these cayenne multiple crosses. This research aims to identify the effectiveness of multivariate analysis and image-based explanatory characteristics of fruit phenotypes and to select multiple crosses that can continue to the F2 generation. The research was designed with a randomized complete block design of ten F1 multiple cross-genotypes and four check varieties. Each genotype was repeated three times, so there were 42 experimental units. Based on the results, multivariate was considered adequate in determining image explanatory characters based on fruit phenotype and genotype mapping of the population diversity of multiple crosses of cayenne pepper. The characteristics of fruit height, fruit area, and fruit Intden are image-based explanatory characters that can map the completeness of cayenne pepper fruit between multiple crosses well. This indicates that image-based phenotyping and multivariate analysis can provide more detailed image information of the potential of cayenne fruit from multiple crosses than just based on fruit weight. Therefore, both approaches are recommended for analyzing cayenne paper fruit potential, especially for multiple crosses. In addition, three crosses (MC4, MC8, and MC9) are optimal for the next generation to be recommended and continued.

Validation of SNP Markers for Diversity Analysis, Quality Control, and Trait Selection in a Biofortified Cassava Population.

A validated marker system is crucial to running an effective genomics-assisted breeding program. We used 36 Kompetitive Allele-Specific PCR (KASP) markers to genotype 376 clones from the biofortified cassava pipeline, and fingerprinted 93 of these clones with DArTseq markers to characterize breeding materials and evaluate their relationships. The discriminating ability of the 36-quality control (QC) KASP and 6602 DArTseq markers was assessed using 92 clones genotyped in both assays. In addition, trait-specific markers were used to determine the presence or absence of target genomic regions. Hierarchical clustering identified two major groups, and the clusters were consistent with the breeding program origins. There was moderate genetic differentiation and a low degree of variation between the identified groups. The general structure of the population was similar using both assays. Nevertheless, KASP markers had poor resolution when it came to differentiating the genotypes by seed sources and overestimated the prevalence of duplicates. The trait-linked markers did not achieve optimal performance as all markers displayed variable levels of false positive and/or false negative. These findings represent the initial step in the application of genomics-assisted breeding for the biofortified cassava pipeline, and will guide the use of genomic selection in the future.

Phenotyping Alfalfa (Medicago sativa L.) Root Structure Architecture via Integrating Confident Machine Learning with ResNet-18.

Background: Root system architecture (RSA) is of growing interest in implementing plant improvements with belowground root traits. Modern computing technology applied to images offers new pathways forward to plant trait improvements and selection through RSA analysis (using images to discern/classify root types and traits). However, a major stumbling block to image-based RSA phenotyping is image label noise, which reduces the accuracies of models that take images as direct inputs. To address the label noise problem, this study utilized an artificial intelligence model capable of classifying the RSA of alfalfa (Medicago sativa L.) directly from images and coupled it with downstream label improvement methods. Images were compared with different model outputs with manual root classifications, and confident machine learning (CL) and reactive machine learning (RL) methods were tested to minimize the effects of subjective labeling to improve labeling and prediction accuracies. Results: The CL algorithm modestly improved the Random Forest model's overall prediction accuracy of the Minnesota dataset (1%) while larger gains in accuracy were observed with the ResNet-18 model results. The ResNet-18 cross-population prediction accuracy was improved (~8% to 13%) with CL compared to the original/preprocessed datasets. Training and testing data combinations with the highest accuracies (86%) resulted from the CL- and/or RL-corrected datasets for predicting taproot RSAs. Similarly, the highest accuracies achieved for the intermediate RSA class resulted from corrected data combinations. The highest overall accuracy (~75%) using the ResNet-18 model involved CL on a pooled dataset containing images from both sample locations. Conclusions: ResNet-18 DNN prediction accuracies of alfalfa RSA image labels are increased when CL and RL are employed. By increasing the dataset to reduce overfitting while concurrently finding and correcting image label errors, it is demonstrated here that accuracy increases by as much as ~11% to 13% can be achieved with semi-automated, computer-assisted preprocessing and data cleaning (CL/RL).

Path Analysis and Correlations Among Yield and Related Traits in Different Genotypes of Soybean (Glycine Max (L.) Merill) in the Benishangul Gumuz Region, Western Ethiopia

Soybean is a warm-climate industrial crop, thrives in low- to medium-altitude legume crops. However, its production in Ethiopia lags behind global standards due to limited improved varieties and reliance on narrow genetic base materials, resulting in low productivity. Consequently, an experiment was undertaken to evaluate the genetic variability and associations among traits in various soybean genotypes concerning grain yield and related factors. Forty-nine soybean genotypes were assessed using a simple lattice design with two replications at Assosa Agricultural Research Center during the main cropping season of 2020. The majority of the characteristics displayed positive correlations both at phenotypic and genotypic levels. Seed yield had highly significant and positive correlations, genetically and phenotypically, with the total number of seeds/ plant, number of pods/primary branch per plant, and the weight of a hundred seeds, indicating the potential for concurrent enhancement of grain yields and these associated traits. The total number of seeds/ plant had the greatest genotypic (0.94) and phenotypic (0.51) -+direct influence on seed yield, followed by the number of pods/primary branch per plant and the weight of a hundred seeds, which showed higher genotypic direct effects on seed yield. This suggests that specific emphasis should be placed on these traits for direct selection aimed at improving yield. Moreover, through examinations of genetic diversity, it has been confirmed that there exists significant variability among the evaluated genotypes. This discovery offers valuable insights for future soybean breeding programs. The identification of such variability is crucial as it allows breeders to select and develop soybean varieties with desirable traits, ultimately contributing to the improvement and advancement of soybean varieties.

Modeling embryo survival: Genetic and environmental influences on eye-up rate in a north American Atlantic salmon selective breeding program

Selective breeding programs improve target traits but can also unintentionally change genetically correlated traits in the selected strain. The U.S. Department of Agriculture–Agricultural Research Service National Cold Water Marine Aquaculture Center (NCWMAC) in Franklin, Maine maintains a North American Atlantic salmon selective breeding program focused on improving commercially important traits (e.g., carcass weight). However, the program has experienced a significant decline in the percent of eyed embryos over its 14 years of operation, leading to concerns that reproductive performance was being unintentionally changed by selection for the target traits. The aims of this study were to 1) model eye up success as a potentially heritable trait utilizing the recorded pedigree and 2) assess the relationship between eye-up rate and environmental conditions experienced by the broodstock. Over 14 years of data encompassing 1537 full-sib families produced by 1537 dams and 885 sires was analyzed. Counts of eyed embryos and carcass weight were analyzed with a linear multi-trait trait model that included maternal genetic effects and a spawn year effect to determine the strength of genetic and environmental influences on the eyed embryo rate. To investigate the environmental influences in more detail, we assessed the correlation between water quality parameters in the broodstock rearing system observed over the same 14-year time period and the estimated spawn year effects. There was small heritability of the direct genetic effect (0.059 ± 0.009) and the maternal genetic effect (0.039 ± 0.013). Comparatively, the proportion of phenotypic variance explained by the maternal environmental effect was moderate (0.165 ± 0.012). The genetic correlations between carcass weight and eye up rate were very small and had a large amount of uncertainty. The correlation between the direct genetic effects on eye-up and carcass weight was −0.0528 ± 0.1469 while the correlation between the maternal genetic effect on eye-up and the direct genetic effect on carcass weight was 0.2030 ± 0.1791. The correlation between maternal common environmental effects on the two traits was also low at 0.0676 ± −0.0804. The effect of spawn year was statistically significant (p < 0.01), and the values were negatively correlated with mean un-ionized ammonia (mg/L, −0.56, p = 0.04,), nitrate concentrations (mg/L r = −0.65, p = 0.01) and temperature (°C, r = −0.61, p = 0.02) experienced by the broodstock prior to spawning. Overall, the results suggest that the decrease in eyed embryos over time was not caused by inadvertent selection but instead due to increases in water temperature and/or nitrogenous waste concentrations in the broodstock rearing system. Further investigation of the mechanisms behind these apparent environmentally induced declines and potential mitigation measures to prevent decreases in eye-up rates are needed.

Association Analysis of METTL23 Gene Polymorphisms with Reproductive Traits in Kele Pigs.

Methyltransferase-like 23 (METTL23) is a kind of RNA methyltransferase that catalyzes the methylation transfer to the N6-adenosine of RNA, serving as one of the key mediators in this process. However, the METTL23 gene has been poorly researched in pigs. In this study, we investigated the genetic effects of METTL23 single-nucleotide polymorphism(SNPs) on reproductive traits in Kele pigs. The DNA was extracted from 228 healthy multiparous Kele sows, and Sanger sequencing revealed three SNPs, g.4804958 G > T (intron 2), g.4805082 C > T (exon 2), and g.4806821 A > G (exon 3). The polymorphism information content (PIC) for each SNP was 0.264, 0.25, and 0.354, indicating moderate polymorphism (0.25 < PIC < 0.5) and providing genetic information. Linkage disequilibrium analysis showed no strong linkage disequilibrium between the three SNPs. The association analysis revealed that in the SNP g.4804958 G > T individuals with the GG genotype had a significantly higher number of piglets born alive, litter birth weight, number of weaned piglets, and weaning litter weight compared to those with the TT genotype (p < 0.05). Individuals with the GG genotype in the SNP g.4806821 A > G group had significantly higher litter birth weight and average birth weight than those with the AA genotype (p < 0.05). The H4H4 diplotype showed significant effects on the number of piglets born alive, litter birth weight, number of weaned piglets, weaning litter weight, and weaning weight (p < 0.05). Together, the METTL23 gene could be used as a candidate gene for the selection of reproductive traits in Kele pigs.

Genomic prediction of the performance of tropical doubled haploid maize lines under artificial Striga hermonthica (Del.) Benth. infestation.

Striga hermonthica (Del.) Benth., a parasitic weed, causes substantial yield losses in maize production in sub-Saharan Africa. Breeding for Striga resistance in maize is constrained by limited genetic diversity for Striga resistance within the elite germplasm and phenotyping capacity under artificial Striga infestation. Genomics-enabled approaches have the potential to accelerate identification of Striga resistant lines for hybrid development. The objectives of this study were to evaluate the accuracy of genomic selection for traits associated with Striga resistance and grain yield (GY) and to predict genetic values of tested and untested doubled haploid maize lines. We genotyped 606 doubled haploid lines with 8,439 rAmpSeq markers. A training set of 116 doubled haploid lines crossed to 2 testers was phenotyped under artificial Striga infestation at 3 locations in Kenya. Heritability for Striga resistance parameters ranged from 0.38-0.65 while that for GY was 0.54. The prediction accuracies for Striga resistance-associated traits across locations, as determined by cross-validation (CV) were 0.24-0.53 for CV0 and from 0.20 to 0.37 for CV2. For GY, the prediction accuracies were 0.59 and 0.56 for CV0 and CV2, respectively. The results revealed 300 doubled haploid lines with desirable genomic estimated breeding values for reduced number of emerged Striga plants (STR) at 8, 10, and 12 weeks after planting. The genomic estimated breeding values of doubled haploid lines for Striga resistance-associated traits in the training and testing sets were similar in magnitude. These results highlight the potential application of genomic selection in breeding for Striga resistance in maize. The integration of genomic-assisted strategies and doubled haploid technology for line development coupled with forward breeding for major adaptive traits will enhance genetic gains in breeding for Striga resistance in maize.

Phenotypic diversity in qualitative and quantitative traits for selection of high yield potential field pea genotypes

Field pea (Pisum sativum L.) needs improvement to increase productivity due to its high price and demand. However, the incidence of powdery mildew (PM) disease limits its production. This study aimed to analyze the diversity of qualitative and quantitative traits against powdery mildew resistance by utilizing cluster and principal component analysis to explore PM resistance high-yield potential field peas. Shannon–Weaver's diversity index (Hʹ) displayed high intra-genotype diversity for quantitative and qualitative aspects. Heterogeneity was identified for resistance against powdery mildew infections. Eighty-five genotypes were divided into five groups using Mohalanobis generalized distance (D2) statistics. The highest inter-cluster D2 value was observed between clusters 2 and 3 (11.89) while the lowest value was found between clusters 3 and 4 (2.06). Most of the genotypes had noticeable differences, so these could be employed in a crossing scheme. Twelve genotypes were extremely resistant, 29 genotypes were resistant, 25 genotypes were moderately resistant, 18 genotypes were fairly susceptible, and 1 genotype was susceptible to powdery mildew disease. Among 29 resistant genotypes, BFP77, BFP74, BFP63, BFP62, BFP43, and BFP80 were high yielders and, could be used directly and/or transferred through hybridization to high-yielding disease-susceptible genotypes. Among the 25 moderately resistant genotypes, BFP78, BFP45, BFP79, and BFP48 were found to be high yielders. In principal component analysis (PCA), the first four PCs with Eigen values > 1 accounted for 88.4% variability for quantitative traits. Clustering sorted genotypes into five groups, where groups 1 to 5 assembled 37, 28, 1, 8, and 11 genotypes, respectively. Genotypes of cluster 4 were identified as high yielders with its attributes. Pearson correlation significantly and positively correlated across all traits except for PM. This variation suggested that there is a mechanism to select promising genotypes for field pea breeding. Considering all features, BFP78, BFP77, BFP74, BFP63, BFP62, BFP45, BFP79, and BFP80 could be preferred as high yielders and PM resistance owing to longer pod lengths, seeds per pod and pods per plant.

Rational selection of morphological phenotypic traits to extract essential similarities in chemical perturbation in the ergosterol pathway

Terbinafine, fluconazole, and amorolfine inhibit fungal ergosterol synthesis by acting on their target enzymes at different steps in the synthetic pathway, causing the accumulation of various intermediates. We found that the effects of these three in- hibitors on yeast morphology were different. The number of morphological parameters commonly altered by these drugs was only approximately 6% of the total. Using a rational strategy to find commonly changed parameters,we focused on hidden essential similarities in the phenotypes possibly due to decreased ergosterol levels. This resulted in higher apparent morphological similarity. Improvements in morphological similarity were observed even when canonical correlation analysis was used to select biologically meaningful morphological parameters related to gene function. In addition to changes in cell morphology, we also observed differences in the synergistic effects among the three inhibitors and in their fungicidal effects against pathogenic fungi possibly due to the accumulation of different intermediates. This study provided a comprehensive understanding of the properties of inhibitors acting in the same biosynthetic pathway.

Seed mass affects emergence but not germination in native grassland forage species

For ecological restoration of degraded grasslands, species selection and knowledge of the species biology are essential. Seed germination and seedling establishment, as well as seed regenerative traits, can partially determine direct seeding success in this context. The objectives of this study are (1) to characterize the seeds of 29 native forage species of the Pampa Austral grasslands, (2) to evaluate their germination and emergence, and (3) to evaluate the relationship between germination and emergence and seed traits (mass, length, width, and length/width ratio), to test the usefulness of these traits for rapid species selection. We studied the germination percentage of untreated (UG) and treated (TG) seeds under laboratory conditions of 29 native forage species (four legumes, nine cool season, and 16 warm‐season grasses) and the percentage of field emergence (FE) for 17 of those species, selected based on their UG. Additionally, all species were characterized, including thousand‐seed mass, length, width, and length/width ratio. Average UG was 53.30 ± 3.17% for Poaceae and 25.63 ± 5.73% for Fabaceae. Four cool season and eight warm‐season grasses had UG greater than 60%. Mean FE was 35.18 ± 0.66% 2 months after sowing. FE has a direct relationship with seed mass (r2 = 0.69; p &lt; 0.001), while this relationship was not observed for UG under laboratory conditions (r2 = 0.15; p = 0.7174). In Pampa Austral grasslands, seed mass proved to be a relevant trait for species selection given its strong relationship with FE.

Genomic Selection for Growth and Wood Traits in Castanopsis hystrix

Genomic Selection for Growth and Wood Traits in Castanopsis hystrix

Sexual selection and life history interact to influence the evolution of paternal care.

Parental care is essential to offspring survival in many species. Understanding why males of some species provide care, whereas others do not, has received substantial attention. Previous research has found that sexual selection can favor paternal care, yet we still do not fully understand why sexual selection favors male care in some species but not others. It is also unclear when paternal care versus other preferred male trait(s) will be favored by sexual selection. We hypothesize that sexual selection can interact with basic life history to influence the conditions under which paternal care and/or another preferred male trait will be favored by sexual selection. We used a mathematical approach in which males alone provide parental care and exhibit a non-care trait that is preferred in mate choice. Using this approach, we demonstrate that life-history characteristics (stage-specific mortality, fertilization success, gamete numbers) can interact with sexual selection to influence the evolution of paternal care and/or a preferred non-care trait. In particular, whether (1) adult mortality, egg mortality, and fertilization success are high versus low and (2) a tradeoff exists between paternal care and a non-care preferred trait will influence whether selection most strongly favors additional paternal care or a non-care preferred trait. In general, we would expect strong selection for more male care when it is preferred in mate choice. In some cases, mate preferences for paternal care can inhibit selection for a preferred non-care trait. Mate preferences for paternal care can also broaden the life-history conditions under which we would expect the elaboration of male care to occur.

Long‐term trends in the genotypic integrity, phenotype and reproductive development of perennial ryegrass (Lolium perenne L.) populations in New Zealand dairy pastures: Implications for pasture persistence

AbstractFailure of perennial ryegrass‐based pastures to persist beyond 3 years post‐sowing is an increasing threat to the sustainability of livestock industries in the north of New Zealand. Little is known of the long‐term responses of plants and populations to the environmental stresses responsible for persistence failure, or the effects of ryegrass genetics on those responses. Plants were collected from 10‐year‐old pastures sown in two environments (Waikato, North Island: warm‐temperate, summer/autumn dry; Canterbury, South Island: cool temperate, irrigated) to four ryegrass functional types and grazed by dairy cattle. Surviving plants in Canterbury pastures were almost all true‐to‐type for the original genotype, whereas there was substantial ingress of volunteer plants in the diploid cultivars in Waikato. Plants confirmed as true‐to‐type were compared to reference plants grown from the original seed lines. Leaf mass was lower in survivor plants than in reference plants for all functional types. This effect was reversed by recruitment of new plants from seed in a grazing deferment treatment applied at the Waikato site 18 months before plant collection, in a manner consistent with epigenetic control. Reproductive development was delayed by 4–6 days in survivors of mid‐ and late flowering diploid cultivars: this effect appeared to be the result of true genetic differentiation. There was less aftermath heading in the Canterbury survivors, but not Waikato survivors, compared with the reference plants. The relevance of these findings for ryegrass survival strategies and targeted selection of traits for improved persistence is discussed.

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.

Ant-following behavior is correlated with plumage traits in African understory birds

Ant-following behavior is a common phenomenon in birds of Neotropical and Afrotropical rainforests but yet little is known from Central Africa. We here report on the phenomenon in lowland rainforest in Cameroon, quantifying the strength of the interaction of different ant-following bird species with driver ants and test the hypothesis that higher levels of specialization in ant-following behavior are associated with dominance or aggression-dependent plumage and other morphological traits. Flock size varied between 1 and 11 individuals with a mean size of 5.34 ± 2.68 (mean ± SD) individuals occurring at the same time. The maximum number of species present during one raid observed was ten, whereas the minimum number was four with an overall species richness of 6.89 ± 2.1 species. The 21 attending bird species strongly varied in the degree of ant-following behavior. In an interspecific comparison, plumage traits such as the presence of a colored crown, eyespots, and bare skin around the eye, in combination with metatarsus length and weight, were significantly correlated with ant-following behavior. These results suggest that—in size and identity of species—ant-following bird assemblages in Central Africa are similar to those reported from East Africa. They also suggest that ant following favors the selection of traits that signal dominance in interactions between individuals struggling for valuable food resources in the forest understory.

Genome size and chromosome number variation in sugarcane (Saccharum spp.) families and phenotypically contrasting Saccharum genotypes

AbstractModern sugarcane (Saccharum spp.) cultivars originated from an intricate hybridization process, resulting in complex polyploid and aneuploid genomes. Flow cytometry (FCM), which has emerged as a precise and fast method for research on genome size in plants, has potential to unveil key aspects of sugarcane cytogenetics. In this study, FCM probes were conducted to estimate 2C DNA content in 175 Saccharum genotypes embracing phenotypically contrasting canes (commercial cultivars, energy‐cane hybrids, and a Saccharum spontaneum accession) and full‐sib sugarcane families. FCM‐mediated DNA content estimates exhibited high accuracy in predicting chromosome numbers, offering a time‐efficient alternative to classical cytogenetic procedure. Low‐magnitude correlations detected between DNA content and phenotypic traits suggest that indirect selection of agronomic traits using FCM‐mediated DNA content estimates may not be efficient. DNA content variation patterns in sugarcane families varied according to the crossing, and revealed transgressive variations associated with rampant aneuploidy. Altogether, the findings uncover that loss or gain of genetic material constitutes a source of high genetic variability that may substantially impact on crop breeding.

Genome-Wide Association Study as an Efficacious Approach to Discover Candidate Genes Associated with Body Linear Type Traits in Dairy Cattle.

Body shape traits are very important and play a crucial role in the economic development of dairy farming. By improving the accuracy of selection for body size traits, we can enhance economic returns across the dairy industry and on farms, contributing to the future profitability of the dairy sector. Registered body conformation traits are reliable and cost-effective tools for use in national cattle breeding selection programs. These traits are significantly related to the production, longevity, mobility, health, fertility, and environmental adaptation of dairy cows. Therefore, they can be considered indirect indicators of economically important traits in dairy cows. Utilizing efficacious genetic methods, such as genome-wide association studies (GWASs), allows for a deeper understanding of the genetic architecture of complex traits through the identification and application of genetic markers. In the current review, we summarize information on candidate genes and genomic regions associated with body conformation traits in dairy cattle worldwide. The manuscript also reviews the importance of body conformation, the relationship between body conformation traits and other traits, heritability, influencing factors, and the genetics of body conformation traits. The information on candidate genes related to body conformation traits provided in this review may be helpful in selecting potential genetic markers for the genetic improvement of body conformation traits in dairy cattle.

Expression of ovine MYH3 gene and its polymorphisms and association analysis with growth traits in Hu sheep

The growth rate of sheep determines their productivity; the faster the growth rate, the higher the productivity. Sheep growth is usually measured by body weight, which is an important indicator of overall growth, and body size, which reflects body shape and structure. Therefore, in sheep production, the selection and improvement of growth traits is one of the important means to improve production efficiency. In this study, 857 males of Hu sheep were selected to record growth traits, including body weight, height, length, and chest, and cannon circumference at 80, 100, 120, 140, 160 and 180 days of age, as well as live weight before slaughter and carcass weight. Correlation analyses conducted between these growth traits at different stages were significantly correlated with both live weight before slaughter and carcass weight. And the strongest correlation was observed for body weight, while body height showed the weakest correlation. The myosin heavy chain 3 (MYH3) gene in the MYH gene family was selected as the target gene, and a synonymous mutation (MYH3 g.33834192A>G) in the exon 12 region of MYH3 was identified by polymerase chain reaction (PCR) and Sanger sequencing. Further association analysis using competitive allele-specific PCR (KASPar) technique showed that the MYH3 g.33834192A>G locus was significantly (P < 0.05) associated with growth traits (including body weight from 80 to 160 days of age, body height at 80 and 100 days of age, body length at 100 and 140 days of age, chest circumference at 80, 100, 160, and 180 days of age, cannon circumference at 80–140 days of age and carcass weight). Among them, the dominant genotype was GG. Meanwhile, the tissue expression results indicated that the highest level of MYH3 gene expression was found in muscle tissues. Therefore, this locus can be used as a candidate molecular genetic marker for improving growth traits in Hu sheep.

ИСТОЧНИКИ КРУПНОЯГОДНОСТИ СОРТОВ ВИНОГРАДА АНАПСКОЙ АМПЕЛОГРАФИЧЕСКОЙ КОЛЛЕКЦИИ

The aim of the study is to examine grape varieties in the collection of the Anapa Experimental Station in order to identify genetic sources of large-berry fruit. Varieties that are donors or sources of economically valuable traits, such as high productivity, large-berry fruit, stress resistance, adaptability, and taste, are found among representatives of the eco-geographical groups of European-Asian grapes. This work is relevant because it is the foundation for the selection process of grape culture and the production of new zoned large-berry varieties that are in great demand on the market and necessary in times of import substitution. Currently, the collection consists of many varieties of different eco-geographical origins, table and technical uses. The gene pool of grapes is replenished every year. These varieties are used annually in breeding to develop new high-quality grape varieties. The objects of research were the source varieties of large-berry grapes from different geographical zones. In this research work, modern programs and me-thods were used along with traditional breeding methods. The paper presents four sources of large-berry grapes, gives their brief characteristics, shows the dynamics of the main phenological and agrobiological indicators for 2021–2023. Among the source varieties, the following varieties stand out in terms of the frui-ting coefficient: Brigantina (K1 – 1.0–1.2) and Muromets (K1 – 1.0–1.1), and in terms of yield per bush – Pobeditel, Brigantina and Yubiley Moldavii. These varieties are used in experimental work on varietal directed crossing of supposed carriers of economically valuable selection traits and further obtaining seeds of new hybrid offspring.