Desirable Traits Research Articles

Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations.

South Africa boasts a diverse range of pig populations, encompassing intensively raised commercial breeds, as well as indigenous and village pigs reared under low-input production systems. The aim of this study was to investigate how natural and artificial selection have shaped the genomic landscape of South African pig populations sampled from different genetic backgrounds and production systems. For this purpose, the integrated haplotype score (iHS), as well as cross population extended haplotype homozygosity (XP-EHH) and Lewontin and Krakauer's extension of the Fst statistic based on haplotype information (HapFLK) were utilised. Our results revealed several population-specific signatures of selection associated with the different production systems. The importance of natural selection in village populations was highlighted, as the majority of genomic regions under selection were identified in these populations. Regions under natural and artificial selection causing the distinct genetic footprints of these populations also allow for the identification of genes and pathways that may influence production and adaptation. In the context of intensively raised commercial pig breeds (Large White, Kolbroek, and Windsnyer), the identified regions included quantitative loci (QTLs) associated with economically important traits. For example, meat and carcass QTLs were prevalent in all the populations, showing the potential of village and indigenous populations' ability to be managed and improved for such traits. Results of this study therefore increase our understanding of the intricate interplay between selection pressures, genomic adaptations, and desirable traits within South African pig populations.

Genome-wide identification of rubber tree pathogenesis-related 10 (PR-10) proteins with biological relevance to plant defense

Pathogenesis-related 10 (PR-10) is a group of small intracellular proteins that is one of 17 subclasses of pathogenesis-related proteins in plants. The PR-10 proteins have been studied extensively and are well-recognized for their contribution to host defense against phytopathogens in several plant species. Interestingly, the accumulation of PR-10 proteins in the rubber tree, one of the most economically important crops worldwide, after being infected by pathogenic organisms has only recently been reported. In this study, the homologous proteins of the PR-10 family were systemically identified from the recently available rubber tree genomes in the NCBI database. The sequence compositions, structural characteristics, protein physical properties, and phylogenetic relationships of identified PR-10 proteins in rubber trees support their classification into subgroups, which mainly consist of Pru ar 1-like major allergens and major latex-like (MLP) proteins. The rubber tree PR10-encoding genes were majorly clustered on chromosome 15. The potential roles of rubber tree PR-10 proteins are discussed based on previous reports. The homologous proteins in the PR-10 family were identified in the recent genomes of rubber trees and were shown to be crucial in host responses to biotic challenges. The genome-wide identification conducted here will accelerate the future study of rubber tree PR-10 proteins. A better understanding of these defense-related proteins may contribute to alternative ways of developing rubber tree clones with desirable traits in the future.

Deciphering the potential of diverse barley genotypes for improving the malt quality

The quality of barley grains and malt significantly influences the fermentation process and the ultimate quality of beer. However, the diverse range of desired quality requirements complicates the selection of suitable malting barley varieties. Achieving a combination of all desirable traits within a single genotype poses a significant challenge. This study aimed to identify the most promising malting genotypes by evaluating the malting potential of 29 barley genotypes, considering various grain (plumpness, hectolitre weight, grain protein, starch and β-glucan content) and malt quality (diastatic power, filtration rate, hot water extract, kolbach index and green malt β-glucanase activity and β-glucan content) traits. Significant genotypic variations were observed for individual grain and malt traits. Low malt β-glucanase activity led to high β-glucan content and low diastatic power, affecting the profile of fermentable sugars in the wort. Therefore, β-glucanase activity and β-glucan content were identified as potential additional selection criteria for producing high-quality malt. A weighted scoring system based on eight quality traits identified ten barley genotypes that outperformed the check varieties. Among them, three genotypes (BL1523 > PL807 > BL1748) exhibited exceptionally higher scores than the check varieties. Furthermore, wort sugar profiling confirmed the potential of these genotypes as valuable contributors to future barley improvement programs aimed at enhancing malt quality.

Plastid-encoded RNA polymerase variation in Pelargonium sect Ciconium

Cyto-Nuclear Incompatibility (CNI), in which there is a mismatch in the interaction between organelles and nucleus, impacts plant species evolution as it has a direct effect on the fitness of plants. It can reduce fertility and/or result in bleached plants devoid of functional chloroplasts. Understanding the processes leading to CNI could help to improve breeding efforts, especially in cases where species with desirable traits need to be crossed into existing cultivars. To better understand the occurrence of CNI and its effects on plant phenotype, we combined near comprehensive crossing series across a clade of species from Pelargonium section Ciconium with comparative genomics and protein modelling for plastid-encoded RNA polymerase (PEP), as the rpo genes encoding PEP subunits were found to be unusually highly divergent, especially in two length-variable regions. Of all plastome-encoded genes, we found these genes to contain more variation than observed across angiosperms and that this underlies structural variation inferred for PEP in P. sect. Ciconium. This variation, resulting in differing physico-chemical properties of the rpo-encoded peptides, provides a possible explanation for the observed CNI, but we cannot directly correlate plastid related CNI phenotypes to rpo genotypes. This suggests that more than one interaction between the nuclear genome and the plastome genes are needed to fully explain the observed patterns.

Genome-wide analysis of the Tritipyrum NAC gene family and the response of TtNAC477 in salt tolerance

NAC transcription factors are widely distributed in the plant kingdom and play an important role in the response to various abiotic stresses in plant species. Tritipyrum, an octoploid derived from hybridization of Triticum aestivum (AABBDD) and Thinopyrum elongatum (EE), is an important genetic resource for integrating the desirable traits of Th. elongatum into wheat. In this study, we investigated the tissue distribution and expression of Tritipyrum NAC genes in the whole genomes of T. aestivum and Th. elongatum after obtaining their complete genome sequences. Based on phylogenetic relationships, conserved motifs, gene synthesis, evolutionary analysis, and expression patterns, we identified and characterized 732 Tritipyrum NAC genes. These genes were divided into six main groups (A, B, C, D, E, and G) based on phylogenetic relationships and evolutionary studies, with members of these groups sharing the same motif composition. The 732 TtNAC genes are widely distributed across 28 chromosomes and include 110 duplicated genes. Gene synthesis analysis indicated that the NAC gene family may have a common ancestor. Transcriptome data and quantitative polymerase chain reaction (qPCR) expression profiles showed 68 TtNAC genes to be highly expressed in response to various salt stress and recovery treatments. Tel3E01T644900 (TtNAC477) was particularly sensitive to salt stress and belongs to the same clade as the salt tolerance genes ANAC019 and ANAC055 in Arabidopsis. Pearson correlation analysis identified 751 genes that correlated positively with expression of TtNAC477, and these genes are enriched in metabolic activities, cellular processes, stimulus responses, and biological regulation. TtNAC477 was found to be highly expressed in roots, stems, and leaves in response to salt stress, as confirmed by real-time PCR. These findings suggest that TtNAC477 is associated with salt tolerance in plants and might serve as a valuable exogenous gene for enhancing salt tolerance in wheat.

Application of functional genomics for domestication of novel non-model microbes.

The development of genome scale CRISPR-based libraries in new microbes enables discovery of genetic factors linked to desired traits for engineering more robust microbial systems.

Enhancing the Counseling Process: The Significance of Counselor's Personality Traits

This paper examines the significance of counselor's personal qualities in the counseling process. The research highlights the impact of counselor's personality on counseling attitudes and behaviors, emphasizing the counselor's role in establishing a strong counseling relationship. The study draws on a literature review of selected articles and scientific papers to explore the relationship between counselor's personal qualities and the effectiveness of counseling services. The findings indicate that the success of the counseling process is highly dependent on the counselor's personal characteristics, which include empathy, respect, acceptance, appreciation, and honesty. Furthermore, the quality of the counseling relationship, characterized by the interaction between the counselor and the individual seeking guidance, plays a pivotal role in achieving positive counseling outcomes. The research underscores the importance of counselor's personal qualities in shaping the counseling experience and highlights the need for counselors to possess desirable character traits. The implications of this study extend to counselor training programs and professional development, emphasizing the significance of nurturing and enhancing counselor's personal qualities to provide effective counseling services.

Effects of Different Levels of Gamma Radiation on Growth and Yield Characteristics of Groundnut

One of the key strategy for improving the crops is plant mutation breeding, which generates a large germplasm pool to improve crop characteristics. In this field experiment, the effects of different levels of gamma radiation on the growth and yield characteristics of groundnut were investigated. "Gamma chamber 1200 Cobalt-60" research irradiator was used to irradiate the groundnut seeds. Two experiments were conducted, with the first exposing the seeds to gamma radiation levels ranging from 0 to 100 Gy, and the second exposing them to levels from 0 to 500 Gy. Irradiated seeds were sown in poly bags and kept under shade. After 2 weeks, seedlings were transplanted in an open field using a Randomized Complete Block Design with five replications. Growth and yield parameters were collected, and statistical analysis was carried out using SAS 9.1 software, with treatment means compared using DMRT at 0.05 level. Results from experiment one showed no significant (P ≥ 0.05) differences among treatments. However, in experiment two, treatments showed significant differences in the measured variables. Seeds exposed to 200 Gy had increased shoot fresh weight (123.3%), root fresh weight (69.8%), number of pods (46%), 100-seed weight (47.7%), and total yield (65.6%). The study recommends 200 Gy as a more suitable level of gamma radiation to create desirable characteristics in groundnut. In conclusion, gamma radiation can be an effective tool for inducing mutations in plants for crop improvement. The findings of this radiation study could contribute to the improvement of new cultivars of groundnut with desirable traits, such as increased yield and improved plant growth.

Asymmetric and parallel subgenome selection co-shape common carp domestication

BackgroundThe common carp (Cyprinus carpio) might best represent the domesticated allopolyploid animals. Although subgenome divergence which is well-known to be a key to allopolyploid domestication has been comprehensively characterized in common carps, the link between genetic architecture underlying agronomic traits and subgenome divergence is unknown in the selective breeding of common carps globally.ResultsWe utilized a comprehensive SNP dataset in 13 representative common carp strains worldwide to detect genome-wide genetic variations associated with scale reduction, vibrant skin color, and high growth rate in common carp domestication. We identified numerous novel candidate genes underlie the three agronomically most desirable traits in domesticated common carps, providing potential molecular targets for future genetic improvement in the selective breeding of common carps. We found that independently selective breeding of the same agronomic trait (e.g., fast growing) in common carp domestication could result from completely different genetic variations, indicating the potential advantage of allopolyploid in domestication. We observed that candidate genes associated with scale reduction, vibrant skin color, and/or high growth rate are repeatedly enriched in the immune system, suggesting that domestication of common carps was often accompanied by the disease resistance improvement.ConclusionsIn common carp domestication, asymmetric subgenome selection is prevalent, while parallel subgenome selection occurs in selective breeding of common carps. This observation is not due to asymmetric gene retention/loss between subgenomes but might be better explained by reduced pleiotropy through transposable element-mediated expression divergence between ohnologs. Our results demonstrate that domestication benefits from polyploidy not only in plants but also in animals.

Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch

Genomic dissection of genetic effects on desirable traits and the subsequent use of genomic selection hold great promise for accelerating the rate of genetic improvement of forest tree species. In this study, a total of 661 offspring trees from 66 open-pollinated families of Japanese larch (Larix kaempferi (Lam.) Carrière) were sampled at a test site. The contributions of additive and non-additive effects (dominance, imprinting and epistasis) were evaluated for nine valuable traits related to growth, wood physical and chemical properties, and competitive ability using three pedigree-based and four Genomics-based Best Linear Unbiased Predictions (GBLUP) models and used to determine the genetic model. The predictive ability (PA) of two genomic prediction methods, GBLUP and Reproducing Kernel Hilbert Spaces (RKHS), was compared. The traits could be classified into two types based on different quantitative genetic architectures: for type I, including wood chemical properties and Pilodyn penetration, additive effect is the main source of variation (38.20-67.46%); for type II, including growth, competitive ability and acoustic velocity, epistasis plays a significant role (50.76-91.26%). Dominance and imprinting showed low to moderate contributions (< 36.26%). GBLUP was more suitable for traits of type I (PAs = 0.37–0.39 vs. 0.14–0.25), and RKHS was more suitable for traits of type II (PAs = 0.23–0.37 vs. 0.07–0.23). Non-additive effects make no meaningful contribution to the enhancement of PA of GBLUP method for all traits. These findings enhance our current understanding of the architecture of quantitative traits and lay the foundation for the development of genomic selection strategies in Japanese larch.

In-Law Preferences for Similarity: Comparing Parent and Child Preferences for In-Law/Intimate Partner Similarity.

Parents want daughters- and sons-in-law who are similar to their children, and children want spouses who are similar to themselves. In turn, the question arises: Do parents agree among themselves on how much similarity they desire in their prospective in-laws concerning their children? Moreover, do parents and children agree on the level of similarity they desire in an in-law and a spouse, respectively? Furthermore, to exercise an in-law preference for similarity, parents need to assess how their children score in traits deemed desirable in a spouse. This raises the question of whether mothers and fathers perceive their children similarly, and whether they perceive their children in the same way their children perceive themselves in these traits. The current study aimed to address these questions using a sample of 356 families from China, focusing on four desirable traits: good looks, good providers, good economic prospects, and good family background. Our results indicated that parents preferred sons- and daughters-in-law who were similar to their children, and mothers and fathers concurred on the level of similarity they desired between their children and their in-laws. Additionally, parents desired as much similarity between their children and their in-laws as their children desired between themselves and their spouses. Furthermore, we found that mothers and fathers concurred on how they perceive their children across the four desirable traits. Finally, both parents scored their children higher in these traits than their children scored themselves.

Deep learning-based elaiosome detection in milk thistle seed for efficient high-throughput phenotyping.

Milk thistle, Silybum marianum (L.), is a well-known medicinal plant used for the treatment of liver diseases due to its high content of silymarin. The seeds contain elaiosome, a fleshy structure attached to the seeds, which is believed to be a rich source of many metabolites including silymarin. Segmentation of elaiosomes using only image analysis is difficult, and this makes it impossible to quantify the elaiosome phenotypes. This study proposes a new approach for semi-automated detection and segmentation of elaiosomes in milk thistle seed using the Detectron2 deep learning algorithm. One hundred manually labeled images were used to train the initial elaiosome detection model. This model was used to predict elaiosome from new datasets, and the precise predictions were manually selected and used as new labeled images for retraining the model. Such semi-automatic image labeling, i.e., using the prediction results of the previous stage for retraining the model, allowed the production of sufficient labeled data for retraining. Finally, a total of 6,000 labeled images were used to train Detectron2 for elaiosome detection and attained a promising result. The results demonstrate the effectiveness of Detectron2 in detecting milk thistle seed elaiosomes with an accuracy of 99.9%. The proposed method automatically detects and segments elaiosome from the milk thistle seed. The predicted mask images of elaiosome were used to analyze its area as one of the seed phenotypic traits along with other seed morphological traits by image-based high-throughput phenotyping in ImageJ. Enabling high-throughput phenotyping of elaiosome and other seed morphological traits will be useful for breeding milk thistle cultivars with desirable traits.

Graphic analysis of various sulfur applications on safflower fatty acids profile.

In this study, we examined the effects of seven different sulfur treatments on safflower seeds. The treatments included: no sulfur application (S0), 25 kg/ha of pure bulk sulfur (S25), 50 kg/ha of pure bulk sulfur (S50), 25 kg/ha of sulfur phosphate (Sp25), 50 kg/ha of sulfur phosphate (Sp50), 25 kg/ha of zinc sulfate (Zs25), and 50 kg/ha of zinc sulfate (Zs50). Our evaluation covered various seed quality attributes, including ash percentage (ASH), oil percentage (OIL), and protein percentage (PRO). Additionally, we analyzed the fatty acid composition, including palmitic acid 16 : 0 (PAL), stearic acid 18 : 0 (STE), oleic acid 18 : 1 (OLE), linoleic acid 18 : 2 (LINL), arachidic acid 20 : 0 (ARA), and linolenic acid 18 : 3 (LINN). The vector-view of the biplot illustrated positive associations among the fatty acids STE, PAL, and OLE, whereas ASH exhibited negative associations with OIL, LINL, and LINN. The polygon-view graph was divided into four sectors, with the genotype S50 emerging as the top performer for attributes such as OIL, PRO, LINL, ARA, and LINN. Treatment Zs50 occupied the vertex of another sector and displayed the highest values for palmitic acid PAL, STE, and OLE, while treatment S0 was positioned at the vertex of the next sector, characterized by its high ASH content. By utilizing the ideal tester tool of treatment by trait biplot, we identified OIL as the desirable trait that most effectively represented the data. The qualitative properties of safflower oil were notably influenced by sulfur application, with treatment S50 proving to be the most effective in enhancing these properties.

Efficient and Powerful Integration of Targeted Metabolomics and Transcriptomics for Analyzing the Metabolism Behind Desirable Traits in Plants.

Through current mass spectrometry methods and multiple RNA-Seq technologies, large metabolomics and transcriptomics datasets are readily obtainable, which provide a powerful and global perspective on metabolism. Indeed, one "omics" method is often not enough to draw strong conclusions about metabolism. Combining and interpreting multiple "omics" datasets remains a challenging task that requires careful statistical considerations and pre-planning. Here we describe a protocol for obtaining high-quality metabolomics and transcriptomics datasets in developing plant embryos followed by a robust approach to integration of the two. This protocol is readily adjustable and scalable to any other metabolically active organ or tissue.

What predicts involuntary singlehood: Investigating the effects of self-esteem and having desirable traits in a Greek-speaking sample.

What predicts involuntary singlehood: Investigating the effects of self-esteem and having desirable traits in a Greek-speaking sample.

Cas12a and MAD7, genome editing tools for breeding.

Food shortages due to population growth and climate change are expected to occur in the near future as a problem that urgently requires solutions. Conventional breeding techniques, notably crossbreeding and mutation breeding, are known for being inefficient and time-consuming in obtaining seeds and seedlings with desired traits. Thus, there is an urgent need for novel methods for efficient plant breeding. Breeding by genome editing is receiving substantial attention because it can efficiently modify the target gene to obtain desired traits compared with conventional methods. Among the programmable sequence-specific nucleases that have been developed for genome editing, CRISPR-Cas12a and CRISPR-MAD7 nucleases are becoming more broadly adopted for the application of genome editing in grains, vegetables and fruits. Additionally, ST8, an improved variant of MAD7, has been developed to enhance genome editing efficiency and has potential for application to breeding of crops.

Bayesian discrete lognormal regression model for genomic prediction.

Genomic prediction models for quantitative traits assume continuous and normally distributed phenotypes. In this research, we proposed a novel Bayesian discrete lognormal regression model. Genomic selection is a powerful tool in modern breeding programs that uses genomic information to predict the performance of individuals and select those with desirable traits. It has revolutionized animal and plant breeding, as it allows breeders to identify the best candidates without labor-intensive and time-consuming phenotypic evaluations. While several statistical models have been developed, most of them have been for quantitative continuous traits and only a few for count responses. In this paper, we propose a discrete lognormal regression model in the Bayesian context, that with aGibbs sampler to explore the corresponding posterior distribution and make the predictions. Two datasets of resistance disease is used in the wheat crop and are then evaluated against the traditional Gaussian model and a lognormal model. The results indicate the proposed model is a competitive and natural model for predicting count genomic traits.

Genome editing of DWARF and SELF-PRUNING rapidly confers traits suitable for plant factories while retaining useful traits in tomato.

Plant factories with artificial light are less affected than open-air areas to environmental factors in crop cultivation and are attracting attention as one of the solutions to the world's food problems. However, the cost of cultivation in plant factories is higher than open-air cultivation, and currently, profitable factory-grown crop varieties are limited to those that are small or have a short growing period. Tomatoes are one of the main crops consumed around the world, but due to their large plant height and width, they are not yet suitable for mass production in plant factories. In this study, the DWARF (D) and SELF-PRUNING (SP) genes of the GABA hyperaccumulating tomato variety #87-17 were genome-edited by the CRISPR-Cas9 method to produce dwarf tomato plants. The desired traits were obtained in the T1 genome-edited generation, and the fruit traits were almost the same as those of the original variety. On the other hand, the F2 cross between #87-17 and Micro-Tom containing the d and sp mutations was dwarfed, but the fruit phenotype was a mixture of the traits of the two varieties. This indicates that genome editing of these two genes using CRISPR-Cas9 can efficiently impart traits suitable for plant factory cultivation while retaining the useful traits of the original cultivar.

Nanocarbon-based sensors for the structural health monitoring of smart biocomposites.

Structural health monitoring (SHM) is a critical aspect of ensuring the safety and durability of smart biocomposite materials used as multifunctional materials. Smart biocomposites are composed of renewable or biodegradable materials and have emerged as eco-friendly alternatives of traditional non-biodegradable glass fiber-based composite materials. Although biocomposites exhibit fascinating properties and many desirable traits, real-time and early stage SHM is the most challenging issue to enable their long-term use. Smart biocomposites are integrated with sensors for in situ identification of the progress of damage and composite failure. The sensitivity of such smart biocomposites is a key functionality, which can be tuned by the introduction of an appropriate filler. In particular, nanocarbons hold promising potential to be incorporated in SHM applications of biocomposites. This review focused on the potential applications of nanocarbons in SHM of biocomposites. The aspects related to fabrication techniques and working mechanism of sensors are comprehensively discussed. Furthermore, their unique mechanical and electrical properties and sustainable nature ensure seamless integration into biocomposites, allowing for real-time monitoring without compromising the material's properties. These sensors offer multi-parameter sensing capabilities, such as strain, pressure, humidity, temperature, and chemical exposure, allowing a comprehensive assessment of biocomposite health. Additionally, their durability and longevity in harsh conditions, along with wireless connectivity options, provide cost-effective and sustainable SHM solutions. As research in this field advances, ongoing efforts seek to enhance the sensitivity and selectivity of these sensors, optimizing their performance for real-world applications. This review highlights the significant advances, ongoing efforts to enhance the sensitivity and selectivity, and performance optimization of nanocarbon-based sensors along with their working mechanism in the field of SHM for smart biocomposites. The key challenges and future research perspectives facing the conversion of nanocarbons to smart biocomposites are also displayed.

Genetic profile and association of candidate gene polymorphism with productivity of Kalmyk cattle

The research was carried out in the laboratory of molecular genetic examination of the RNPC on reproduction of farm animals of the KalmSU named after B. B. Gorodovikov. The purpose of the research was to study the genetic profile and identify the influence of polymorphic candidate genes on the selection and breeding qualities of Kalmyk breed cattle. Analysis of these results by PCR-PDRF of Kalmyk bulls by the Tg locus revealed that 31% of 80 animal heads were carriers of the TT genotype associated with desirable traits, according to the GH locus in the breeding reproducer “Plodovitoye” revealed that 44% of 86 animals were carriers of the VV genotype associated with desirable economic characteristics and valuable qualities. This can be explained by the purposeful conduct of breeding work on breeding indicators in farms. Carriers of the VV genotype exceed their peers in the TT genotype by 9.1 kg (P&gt;0.95). Based on the results obtained, it can be assumed that GH polymorphism has a positive effect on the meat productivity of Kalmyk bulls in comparison with TG.