Growth-related Traits Research Articles

Genotypic variation in winter wheat for fusarium foot rot and its biocontrol using Clonostachys rosea.

Biological control to manage plant diseases is an environmentally friendly alternative to using chemical pesticides. However, little is known about the role of genetic variation in plants affecting the efficacy of biological control agents (BCAs). The aim of this study was to explore the genetic variation in winter wheat for disease susceptibility to fusarium foot rot caused by Fusarium graminearum and variation in biocontrol efficacy of the fungal BCA Clonostachys rosea to control the disease. In total, 190 winter wheat genotypes were evaluated under controlled conditions in two treatments, i.e. (i) F. graminearum (Fg) and (ii) F. graminearum infection on C. rosea treated seeds (FgCr). Alongside disease severity, plant growth-related traits such as shoot length and root length were also measured. Comparison of genotypes between the two treatments enabled the dissection of genotypic variation for disease resistance and C. rosea efficacy. The study revealed significant variation among plant genotypes for fusarium foot rot susceptibility and other growth traits in treatment Fg. Moreover, significant variation in C. rosea efficacy was also observed in genotype contrasts between the two treatments for all traits. Using a 20K marker array, a genome-wide association study was also performed. We identified a total of 18 significant marker-trait associations for disease resistance and C. rosea efficacy for all the traits. Moreover, the markers associated with disease resistance and C. rosea efficacy were not co-localized, highlighting the independent inheritance of these traits, which can facilitate simultaneous selection for cultivar improvement.

Differential Variability of Maize (Zea mays L.) Inbred Lines to Moisture-stress at Reproductive Stages and DNA Methylation Studies of Identified Contrasting Genotypes under Moisture-Stress Conditions

An investigation was undertaken to assess the effect of moisture stress during the reproductive initiation stage on the quality and quantity of pollen grains produced in eight inbred lines (UASBM22, UASBM13, UASBM09, UASBM11, UASBM06, UASBM14, UASBM02 and UASBM10) under greenhouse conditions in three blocks viz., well-watered, stress I (for 21 days from 28 days after sowing) and stress II (for 22 days from 32 days after sowing). Moisture stress significantly affected the number of pollen grains per anther and other plant growth-related traits. The moisture stress effect was not uniform across inbred lines. The inbred lines UASBM22, UASBM13, UASBM09 and UASBM11 recorded a significant reduction in the total number of pollen grains per anther and an increase in pollen sterility while in inbred lines, UASBM06, UASBM14, UASBM02 and UASBM10, the moisture stress effect was not significant. The changes in the DNA methylation pattern in leaves and immature anthers under moisture stress of the contrasting inbred lines (UASBM06 and UASBM13) were studied through methylation- sensitive random amplification polymorphism. An increase in total DNA methylation level in both leaves and anthers was observed in drought tolerant inbred line, UASBM06 under stress while the increase was only in the leaves of the susceptible inbred line UASBM13. Leaves and anthers of UASBM06 showed hypermethylation compared to UASBM13 in moisture-stress conditions. In maize, increased DNA methylation seems to be an important mechanism associated with drought responses which probably regulates the methylation-sensitive gene expression and acclimation responses in maize.

Genetic parameters and genotype-by-environment interaction estimates for growth and feed efficiency related traits in Chinook salmon, Oncorhynchus tshawytscha, reared under low and moderate flow regimes

BackgroundA genotype-by-environment (G × E) interaction is defined as genotypes responding differently to different environments. In salmonids, G × E interactions can occur in different rearing conditions, including changes in salinity or temperature. However, water flow, an important variable that can influence metabolism, has yet to be considered for potential G × E interactions, although water flows differ across production stages. The salmonid industry is now manipulating flow in tanks to improve welfare and production performance, and expanding sea pen farming offshore, where flow dynamics are substantially greater. Therefore, there is a need to test whether G × E interactions occur under low and higher flow regimes to determine if industry should consider modifying their performance evaluation and selection criteria to account for different flow environments. Here, we used genotype-by-sequencing to create a genomic-relationship matrix of 37 Chinook salmon, Oncorhynchus tshawytscha, families to assess possible G × E interactions for production performance under two flow environments: a low flow regime (0.3 body lengths per second; bl s−1) and a moderate flow regime (0.8 bl s−1).ResultsGenetic correlations for the same production performance trait between flow regimes suggest there is minimal evidence of a G × E interaction between the low and moderate flow regimes tested in this study, for Chinook salmon reared from 82.9 ± 16.8 g (x¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\overline{\ ext{x}}}$$\\end{document} ± s.d.) to 583.2 ± 117.1 g (x¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\overline{\ ext{x}}}$$\\end{document} ± s.d.). Estimates of genetic and phenotypic correlations between traits did not reveal any unfavorable trait correlations for size- (weight and condition factor) and growth-related traits, regardless of the flow regime, but did suggest measuring feed intake would be the preferred approach to improve feed efficiency because of the strong correlations between feed intake and feed efficiency, consistent with previous studies.ConclusionThis new information suggests that Chinook salmon families do not need to be selected separately for performance across different flow regimes. However, further studies are needed to confirm this across a wider range of fish sizes and flows. This information is key for breeding programs to determine if separate evaluation groups are required for different flow regimes that are used for production (e.g., hatchery, post smolt recirculating aquaculture system, or offshore).

The Genetic Architecture of Arabidopsis thaliana in Response to Native Non-Pathogenic Bacterial Species Revealed by Genome-Wide Association Mapping in Field Conditions

Non-pathogenic bacteria can substantially contribute to plant health by mobilizing and supplying nutrients, providing protection against pathogens, and alleviating abiotic stresses. However, the number of genome-wide association studies reporting the genetic architecture of the response to individual members of the beneficial microbiota remains limited. In this study, we established a genome-wide association study under field conditions to estimate the level of genetic variation and the underlying genetic architecture among 162 accessions of Arabidopsis thaliana originating from 54 natural populations in the southwest of France in response to 13 strains of seven of the most abundant and prevalent non-pathogenic bacterial species isolated from the leaf compartment of A. thaliana in the same geographical region. Using a high-throughput phenotyping methodology to score vegetative growth-related traits, extensive genetic variation was detected among A. thaliana accessions in response to these leaf bacteria, at both the species and strain levels. The presence of crossing reaction norms between each strain and the mock treatment indicates that declaring a strain as a plant growth-promoting bacterium is highly dependent on the host genotype tested. In line with the strong genotype-by-genotype interactions, we detected a complex and highly flexible genetic architecture between the 13 strains. Finally, the candidate genes underlying the quantitative trait loci revealed significant enrichment in several biological pathways, including cell, secondary metabolism, signaling, and transport. Altogether, plant innate immunity appears as a significant source of natural genetic variation in plant–microbiota interactions and opens new avenues for better understanding the ecologically relevant molecular dialog during plant–microbiota interactions. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

QTL mapping and candidate gene identification for lower temperature tolerance and growth traits using whole genome re-sequencing in Argopecten scallops

Lower temperature tolerance (LTT) and growth traits are vital to the success of overwintering scallop farming in the North China Sea. Bohai Red, a novel selected scallop strain is the main aquaculture species in this region. However, its poor LTT hinders its growth. To improve these traits, the larger Bohai Red scallop was crossed with the smaller bay scallop (A. irradians irradians) which tolerates low temperatures. The full-sib F1 hybrids and the whole-genome resequencing (WGR) method were used to construct a high-density genetic linkage map comprising 5925 single nucleotide polymorphisms (SNPs). The consensus linkage map consisted of 16 linkage groups spanning 1343.46 cM with an average distance of 0.23 cM. Based on this genetic linkage map, 42 potentially significant quantitative trait loci (QTLs) for LTT and growth were detected in eight different linkage groups (LGs) explaining 9.2–18.6% of the phenotypic variation. LG11 may regulate both LTT and growth as 20 QTLs were localized there. Eighteen candidate genes were identified, including 2 (SCARF1, SLC28A3) for LTT and 16 for the growth-related traits. To the best of our knowledge, the present work is one of the first to fine-map the LTT and growth-related QTLs in a genetic linkage map for hybrid Argopecten spp. scallops.

Automated phenotyping empowered by deep learning for genomic prediction of body size in the tiger pufferfish, Takifugu rubripes

Although genomic selection (GS) is accelerating the genetic improvement of economically important traits in aquaculture species, the accurate phenotyping of thousands of individuals remains a bottleneck in GS programs. Computer vision (CV) technologies with the assistance of deep learning may provide a cost-efficient solution for automated phenotyping of fish body size. In this study, we designed a CV-based automated phenotyping system based on the deep learning model Mask R-CNN (region-based convolutional neural networks) and tested its ability to predict standard length (SL) of tiger pufferfish (Takifugu rubripes) fed low fishmeal (LFM) diet. Simultaneously, we investigated the impact of the automated phenotyping on genetic parameter estimation and genomic prediction for growth-related traits. We raised a test population (n = 1001) that was fed the LFM diet from three months old until harvest at 22 months. Manual phenotyping of the fish was performed at 10-, 14-, 17-, and 22-months-old. At the last two measurement times, images of each fish were collected to train Mask R-CNN for fish detection and pixel-level segmentation of the fish body excluding the tail fin. An automated phenotyping pipeline combining the trained Mask R-CNN and standard CV algorithms were designed to estimate SL. We found a high correlation (0.965–0.971) and low relative difference (0.015–0.027) between the CV-derived and manually measured SL, indicating high precision of our CV system. A high correlation (0.912–0.956) was also observed between CV-derived body area and manual body weight. The heritability estimations and genomic predictions on manual SLs were conducted using a Genomic Best Linear Unbiased Prediction (GBLUP) model using a total of 16,471 single nucleotide polymorphism (SNP). Estimated heritability at the four sampling points ranged from 0.573 to 0.622, and the predictive ability of genomic prediction for harvest size was 0.627. These values are comparable to those reported in previous studies collected from the population fed a normal fishmeal diet. Our heritability estimation and genomic prediction derived from automated SL measurements differed negligibly to those based on manual measurements. This finding indicates the utility of our CV-based automated phenotyping system for GS breeding programs.

Roles of Endophytic Fungi Isolated from Mangifera indica L. in Promoting Plant Growth.

Endophytic fungi have been shown to synthesize bioactive secondary metabolites, some of which promote plant growth through various mechanisms. In our previous study, endophytic fungi were isolated from mango trees (Mangifera indica L.). The present study examined fifty endophytic fungal isolates for mineral solubilization activity, ammonia production, and siderophore production. It was shown that these isolates could produce phytohormones indole-3-acetic acid and gibberellic acid, as well as inhibit plant pathogens, specifically Colletotrichum gloeosporioides and Lasiodiplodia theobromae. The results showed that all the isolated fungal endophytes exhibited various activities. Based on the findings, two fungal endophytes-Aureobasidium pullulans CY.OS 13 and Aspergillus tamarii CY.OS 144-were selected for dual inoculation in chili plants under pot-scale conditions to investigate their potential to improve growth-related traits such as seed germination, shoot and root length, biomass, and chlorophyll content. Seed treated with A. pullulans CY.OS 13 and/or A. tamarii CY.OS 144 showed a significant (p < 0.05) increase in seed germination and growth parameters of chili plants grown under pot-scale conditions. Particularly, chili plants whose seeds were injected with a combination of the two selected endophytic fungi showed the highest plant development traits. Therefore, the selected endophytic fungi have the potential to be used as biofertilizers, especially when combined. They could eventually replace chemical fertilizers because they are environmentally friendly, beneficial to humans, and can even promote sustainable agriculture.

Construction of a high-density linkage map and QTL detection for growth traits in South African abalone (Haliotis midae).

Haliotis midae is one of the most important molluscs in South African commercial aquaculture. In this study, a high-resolution integrated linkage map was constructed, and QTL identified using 2b-RADseq for genotyping SNPs in three families. The final integrated linkage map was composed by merging the individual family maps, resulting in 3290 informative SNPs mapping to 18 linkage groups, conforming to the known haploid chromosome number for H. midae. The total map spanned 1798.25 cM with an average marker interval of 0.55 cM, representing a genome coverage of 98.76%. QTL analysis, across all three families, resulted in a total of five QTL identified for growth-related traits, shell width, shell length, and total body weight. For shell width and total body weight, one QTL was identified for each trait respectively, whilst three QTL were identified for shell length. The identified QTL respectively explained between 7.20% and 11.40% of the observed phenotypic variance. All three traits were significantly correlated (r = 0.862-0.970; p < 0.01) and shared overlapping QTL. The QTL for growth traits were mapped back to the H. midae draft genome and BLAST searches revealed the identity of candidate genes, such as egf-1, megf10, megf6, tnx, sevp1, kcp, notch1, and scube2 with possible functional roles in H. midae growth. The constructed high-density linkage map and mapped QTL have given valuable insights regarding the genetic architecture of growth-related traits and will be important genetic resources for marker-assisted selection. It remains, however, important to validate causal variants through linkage disequilibrium fine mapping in future.

Mapping the genetic basis for sex determination and growth in hybrid tilapia (Oreochromis mossambicus × O. niloticus)

Tilapia growth and sex are key traits for aquaculture. Elucidating their molecular mechanisms can enable molecular breeding and accelerate genetic gain. To uncover the genetic basis underlying these traits for molecular breeding, we generated an F2 family by crossing Mozambique and Nile tilapia. The growth and sex traits of 284 F2 fish were recorded at 150 days post hatch. These F2 individuals exhibited sexual dimorphism in weight, body shape, and lip thickness, and were genotyped with RAD-sequencing. A high-density linkage map, consisting of 22 linkage groups with 38,102 SNPs was constructed. Association mapping revealed that QTL containing the amhy gene from male Nile tilapia largely determined sex, modulated by minor-effect loci. For growth-related traits, QTL and association analyses discovered that body weight or total length was predominantly controlled by a large-effect locus, while body shape was determined by several minor-effect loci. Analysis of transcriptomics in the liver and muscle identified novel candidate genes, including dusp2, rtn4r, bhmt1, adamts12 and s100p, for growth. These findings provide tools for sex-specific molecular breeding and valuable information for understanding the genomic architecture of growth and body shape variation. Assessing the sex-specific effects on growth can further refine selective breeding in aquaculture.

Silicon Dioxide Nanoparticles-Based Amelioration of Cd Toxicity by Regulating Antioxidant Activity and Photosynthetic Parameters in a Line Developed from Wild Rice.

An extremely hazardous heavy metal called cadmium (Cd) is frequently released into the soil, causing a considerable reduction in plant productivity and safety. In an effort to reduce the toxicity of Cd, silicon dioxide nanoparticles were chosen because of their capability to react with metallic substances and decrease their adsorption. This study examines the processes that underlie the stress caused by Cd and how SiO2NPs may be able to lessen it through modifying antioxidant defense, oxidative stress, and photosynthesis. A 100 μM concentration of Cd stress was applied to the hydroponically grown wild rice line, and 50 μM of silicon dioxide nanoparticles (SiO2NPs) was given. The study depicted that when 50 μM SiO2NPs was applied, there was a significant decrease in Cd uptake in both roots and shoots by 30.2% and 15.8% under 100 μM Cd stress, respectively. The results illustrated that Cd had a detrimental effect on carotenoid and chlorophyll levels and other growth-related traits. Additionally, it increased the levels of ROS in plants, which reduced the antioxidant capability by 18.8% (SOD), 39.2% (POD), 32.6% (CAT), and 25.01% (GR) in wild rice. Nevertheless, the addition of silicon dioxide nanoparticles reduced oxidative damage and the overall amount of Cd uptake, which lessened the toxicity caused by Cd. Reduced formation of reactive oxygen species (ROS), including MDA and H2O2, and an increased defense system of antioxidants in the plants provided evidence for this. Moreover, SiO2NPs enhanced the Cd resistance, upregulated the genes related to antioxidants and silicon, and reduced metal transporters' expression levels.

Estimation of Genetic Parameters for Growth and WSSV Resistance Traits in Litopenaeus vannamei.

The current study aimed to provide a precise assessment of the genetic parameters associated with growth and white spot syndrome virus (WSSV) resistance traits in Pacific white shrimp (Litopenaeus vannamei). This was achieved through a controlled WSSV challenge assay and the analysis of phenotypic values of five traits: body weight (BW), overall length (OL), body length (BL), tail length (TL), and survival hour post-infection (HPI). The analysis included test data from a total of 1017 individuals belonging to 20 families, of which 293 individuals underwent whole-genome resequencing, resulting in 18,137,179 high-quality SNP loci being obtained. Three methods, including pedigree-based best linear unbiased prediction (pBLUP), genomic best linear unbiased prediction (GBLUP), and single-step genomic BLUP (ssGBLUP) were utilized. Compared to the pBLUP model, the heritability of growth-related traits obtained from GBLUP and ssGBLUP was lower, whereas the heritability of WSSV resistance was higher. Both the GBLUP and ssGBLUP models significantly enhanced prediction accuracy. Specifically, the GBLUP model improved the prediction accuracy of BW, OL, BL, TL, and HPI by 4.77%, 21.93%, 19.73%, 19.34%, and 63.44%, respectively. Similarly, the ssGBLUP model improved prediction accuracy by 10.07%, 25.44%, 25.72%, 19.34%, and 122.58%, respectively. The WSSV resistance trait demonstrated the most substantial enhancement using both genomic prediction models, followed by body size traits (e.g., OL, BL, and TL), with BW showing the least improvement. Furthermore, the choice of models minimally impacted the assessment of genetic and phenotypic correlations. Genetic correlations among growth traits ranged from 0.767 to 0.999 across models, indicating high levels of positive correlations. Genetic correlations between growth and WSSV resistance traits ranged from (-0.198) to (-0.019), indicating low levels of negative correlations. This study assured significant advantages of the GBLUP and ssGBLUP models over the pBLUP model in the genetic parameter estimation of growth and WSSV resistance in L. vannamei, providing a foundation for further breeding programs.

Weighted single-step genome-wide association study for direct and maternal genetic effects associated with birth and weaning weights in sheep

Body weight is an important economic trait for sheep meat production, and its genetic improvement is considered one of the main goals in the sheep breeding program. Identifying genomic regions that are associated with growth-related traits accelerates the process of animal breeding through marker-assisted selection, which leads to increased response to selection. In this study, we conducted a weighted single-step genome-wide association study (WssGWAS) to identify potential candidate genes for direct and maternal genetic effects associated with birth weight (BW) and weaning weight (WW) in Baluchi sheep. The data used in this research included 13,408 birth and 13,170 weaning records collected at Abbas-Abad Baluchi Sheep Breeding Station, Mashhad-Iran. Genotypic data of 94 lambs genotyped by Illumina 50K SNP BeadChip for 54,241 markers were used. The proportion of variance explained by genomic windows was calculated by summing the variance of SNPs within 1 megabase (Mb). The top 10 window genomic regions explaining the highest percentages of additive and maternal genetic variances were selected as candidate window genomic regions associated with body weights. Our findings showed that for BW, the top-ranked genomic regions (1 Mb windows) explained 4.30 and 4.92% of the direct additive and maternal genetic variances, respectively. The direct additive genetic variance explained by the genomic window regions varied from 0.31 on chromosome 1 to 0.59 on chromosome 8. The highest (0.84%) and lowest (0.32%) maternal genetic variances were explained by genomic windows on chromosome 10 and 17, respectively. For WW, the top 10 genomic regions explained 6.38 and 5.76% of the direct additive and maternal genetic variances, respectively. The highest and lowest contribution of direct additive genetic variances were 1.37% and 0.42%, respectively, both explained by genomic regions on chromosome 2. For maternal effects on WW, the highest (1.38%) and lowest (0.41%) genetic variances were explained by genomic windows on chromosome 2. Further investigation of these regions identified several possible candidate genes associated with body weight. Gene ontology analysis using the DAVID database identified several functional terms, such as translation repressor activity, nucleic acid binding, dehydroascorbic acid transporter activity, growth factor activity and SH2 domain binding.

Complex genetic architecture of the chicken Growth1 QTL region.

The genetic complexity of polygenic traits represents a captivating and intricate facet of biological inheritance. Unlike Mendelian traits controlled by a single gene, polygenic traits are influenced by multiple genetic loci, each exerting a modest effect on the trait. This cumulative impact of numerous genes, interactions among them, environmental factors, and epigenetic modifications results in a multifaceted architecture of genetic contributions to complex traits. Given the well-characterized genome, diverse traits, and range of genetic resources, chicken (Gallus gallus) was employed as a model organism to dissect the intricate genetic makeup of a previously identified major Quantitative Trait Loci (QTL) for body weight on chromosome 1. A multigenerational advanced intercross line (AIL) of 3215 chickens whose genomes had been sequenced to an average of 0.4x was analyzed using genome-wide association study (GWAS) and variance-heterogeneity GWAS (vGWAS) to identify markers associated with 8-week body weight. Additionally, epistatic interactions were studied using the natural and orthogonal interaction (NOIA) model. Six genetic modules, two from GWAS and four from vGWAS, were strongly associated with the studied trait. We found evidence of both additive- and non-additive interactions between these modules and constructed a putative local epistasis network for the region. Our screens for functional alleles revealed a missense variant in the gene ribonuclease H2 subunit B (RNASEH2B), which has previously been associated with growth-related traits in chickens and Darwin's finches. In addition, one of the most strongly associated SNPs identified is located in a non-coding region upstream of the long non-coding RNA, ENSGALG00000053256, previously suggested as a candidate gene for regulating chicken body weight. By studying large numbers of individuals from a family material using approaches to capture both additive and non-additive effects, this study advances our understanding of genetic complexities in a highly polygenic trait and has practical implications for poultry breeding and agriculture.

Exploring natural genetic variation in photosynthesis-related traits of barley in the field.

Optimizing photosynthesis is considered an important strategy for improving crop yields to ensure food security. To evaluate the potential of using photosynthesis-related parameters in crop breeding programs, we measured chlorophyll fluorescence along with growth-related and morphological traits of 23 barley inbred lines across different developmental stages in field conditions. The photosynthesis-related parameters were highly variable, changing with light intensity and developmental progression of plants. Yet, the variation in photosystem II quantum yield observed among the inbred lines in the field largely reflected the variation in CO2 assimilation properties in controlled climate chamber conditions, confirming that the chlorophyll fluorescence-based technique can provide proxy parameters of photosynthesis to explore genetic variation under field conditions. Heritability (H2) of the photosynthesis-related parameters in the field ranged from 0.16 for the quantum yield of non-photochemical quenching to 0.78 for the fraction of open photosystem II center. Two parameters, the maximum photosystem II efficiency in the light-adapted state (H2=0.58) and the total non-photochemical quenching (H2=0.53), showed significant positive and negative correlations, respectively, with yield-related traits (dry weight per plant and net straw weight) in the barley inbred lines. These results indicate the possibility of improving crop yield through optimizing photosynthetic light use efficiency by conventional breeding programs.

Genome-wide analysis with additive and epistasis effects reveals growth-related loci and candidate genes in hybrid Argopecten scallops

The first filial (F1) generation from the successful hybridization of bay scallops (Argopecten irradians) and Peruvian scallops (A. purpuratus) exhibits significant heterosis, playing a crucial role in enhancing the germplasm and increasing yields of the scallops. However, there is significant variation in the growth traits of the F1 hybrid population, and there is little information concerning its hereditary basis. To unravel the heterosis mechanism and identify key loci and genes contributing to superhybrids, genome-wide association study (GWAS) with additive and epistasis models were conducted for six growth-related traits in the F1 hybrid scallop population in this study. In total, 18,789,547 single nucleotide polymorphisms (SNPs) were identified after filtering from 198 hybrid individuals, comprising 63.5% of maternal loci and 36.5% of paternal loci. The additive model revealed 2768 associated SNPs and 14 candidate genes, with most of the loci associated with the body mass traits. The additive-additive epistatic model identified 133,094 SNP interaction pairs and 20 candidate gene pairs with exon region SNPs, which were predominantly associated with shell morphology traits. Almost all the SNP pairs associated with body mass traits were maternal-maternal interactions, but the shell morphology traits had the most maternal-paternal and maternal-maternal interactions, suggesting that body mass traits might be affected mainly by maternal effects and that parental interaction effects mainly contributed to the shell size of the hybrid scallops. Both in the shell morphology and the body mass traits, multiple loci participate in epistasis, interacting with more than one locus and forming high-order epistatic interactions, which could be critical factors contributing to the heterosis observed in hybrid scallops. The identified associated loci and candidate genes not only constitute valuable resources for the molecular breeding of hybrid scallops, contributing to the improvement of growth-related traits, but also revealed mechanisms underlying heterosis in aquatic species, providing insights into the advantages of heterosis and paving the way for future research on hybridization in aquatic organisms.

A genome-wide association study on growth traits of Korean commercial pig breeds using Bayesian methods.

This study aims to identify the significant regions and candidate genes of growth-related traits (adjusted backfat thickness [ABF], average daily gain [ADG], and days to 90 kg [DAYS90]) in Korean commercial GGP pig (Duroc, Landrace, and Yorkshire) populations. A genome-wide association study (GWAS) was performed using single-nucleotide polymorphism (SNP) markers for imputation to Illumina PorcineSNP60. The BayesB method was applied to calculate thresholds for the significance of SNP markers. The identified windows were considered significant if they explained ≥1% genetic variance. A total of 28 window regions were related to genetic growth effects. Bayesian GWAS revealed 28 significant genetic regions including 52 informative SNPs associated with growth traits (ABF, ADG, DAYS90) in Duroc, Landrace, and Yorkshire pigs, with genetic variance ranging from 1.00% to 5.46%. Additionally, 14 candidate genes with previous functional validation were identified for these traits. The identified SNPs within these regions hold potential value for future markerassisted or genomic selection in pig breeding programs. Consequently, they contribute to an improved understanding of genetic architecture and our ability to genetically enhance pigs. SNPs within the identified regions could prove valuable for future marker-assisted or genomic selection in pig breeding programs.

Urban Farming Growth Monitoring System Using Artificial Neural Network (ANN) and Internet of Things (IOT)

As an introduction to this project, the growth-related traits, such as above-ground biomass and leaf area, are critical indicators to characterize the growth of indoor lettuce plants. Currently, non-destructive methods for estimating growth-related traits are subject to limitations in that the methods are susceptible to noise and heavily rely on manually designed features. It is also one of the problem statements in this project. Based on this project the next problem is manual control of nutrients may cause quality issues to the lettuce plant. If the nutrient supply is too much or less, it will disturb the growth of the lettuce plant either the lettuce plant is dead or stunted. This project is about urban farming growth monitoring system using Artificial Neural Network (ANN) and Internet of Things (IoT). In this project, a method for monitoring the growth of indoor lettuce plants was proposed by using digital images and an ANN using Deep Learning Architecture. DLA is mostly developed by the software of MATLAB or Python to insert and run the coding. DLA is mostly used for image detection, pattern recognition, and natural language processing through the graph for Neural Network. Next, the Internet of Things (IoT) is a medium to store images of indoor lettuce plant growth into the Cloud (Google Drive). Furthermore, it takes indoor lettuce plant images as the input, an ANN was trained to learn the relationship between images and the corresponding growth- related traits with other fixed parameters. The pH level parameters were controlled by other fixed parameters to take the images of indoor lettuce plant growth. The parameters used in this project are temperature and humidity. This helps to compare the results of Artificial Neural Network (ANN), widely adopted methods were also used. Concisely, this project is expected to develop the Deep Learning Architecture using an Artificial Neural Network (ANN) with digital images as a robust tool for the monitoring of the growth of indoor lettuce plants every 30 minutes per day. Generally, focused on an urban farming growth monitoring system using Artificial Neural Network (ANN) and the Internet of Things (IoT).

Elucidation of the genetic determination of body weight and size in Chinese local chicken breeds by large-scale genomic analyses.

Body weight and size are important economic traits in chickens. While many growth-related quantitative trait loci (QTLs) and candidate genes have been identified, further research is needed to confirm and characterize these findings. In this study, we investigate genetic and genomic markers associated with chicken body weight and size. This study provides new insights into potential markers for genomic selection and breeding strategies to improve meat production in chickens. We performed whole-genome resequencing of and Wenshang Barred (WB) chickens (n = 596) and three additional breeds with varying body sizes (Recessive White (RW), WB, and Luxi Mini (LM) chickens; (n = 50)). We then used selective sweeps of mutations coupled with genome-wide association study (GWAS) to identify genomic markers associated with body weight and size. We identified over 9.4million high-quality single nucleotide polymorphisms (SNPs) among three chicken breeds/lines. Among these breeds, 287 protein-coding genes exhibited positive selection in the RW and WB populations, while 241 protein-coding genes showed positive selection in the LM and WB populations. Genomic heritability estimates were calculated for 26 body weight and size traits, including body weight, chest breadth, chest depth, thoracic horn, body oblique length, keel length, pelvic width, shank length, and shank circumference in the WB breed. The estimates ranged from 0.04 to 0.67. Our analysis also identified a total of 2,522 genome-wide significant SNPs, with 2,474 SNPs clustered around two genomic regions. The first region, located on chromosome 4 (7.41-7.64Mb), was linked to body weight after ten weeks and body size traits. LCORL, LDB2, and PPARGC1A were identified as candidate genes in this region. The other region, located on chromosome 1 (170.46-171.53Mb), was associated with body weight from four to eighteen weeks and body size traits. This region contained CAB39L and WDFY2 as candidate genes. Notably, LCORL, LDB2, and PPARGC1A showed highly selective signatures among the three breeds of chicken with varying body sizes. Overall this study provides a comprehensive map of genomic variants associated with body weight and size in chickens. We propose two genomic regions, one on chromosome 1 and the other on chromosome 4, that could helpful for developing genome selection breeding strategies to enhance meat yield in chickens.

A high-density genetic linkage map and QTL identification for growth traits in dusky kob (Argyrosomus japonicus)

High-density genetic linkage maps provide a foundational genomic resource for quantitative trait locus (QTL) mapping, candidate gene localisation, and comparative genomic analysis. Data from such studies, in turn, can be incorporated into marker or genomics assisted selective breeding strategies for increased efficiency of aquaculture production. This study aimed to construct the first high-density genetic linkage map for dusky kob (Argyrosomus japonicus) a commercially important marine finfish in Asia, Australia, and South Africa. Using 2b-restriction site-associated DNA (2b-RAD) sequencing for genome-wide single nucleotide polymorphism (SNP) genotyping, in three full-sib F1 families (Family 1, n = 69 offspring; Family 2, n = 73 offspring; and Family 3, n = 70 offspring), led to the discovery and genotyping of 22,789 SNPs. Among these, 3992 quality filtered and informative SNPs were mapped to 24 linkage groups (LGs), aligning with the species' proposed haploid chromosome number. The total integrated genetic map spanned a length of 2550 cM with an average marker spacing of 0.68 cM, achieving a genome coverage of 98.61%. Male and female specific maps highlighted differential map lengths and recombination rates between the sexes, with the female map slightly longer and a lower recombination frequency than for the male. QTL analysis for growth-related traits, weight (W), standard length (sL), and Fulton's condition factor (K), identified a total of 25 QTLs of which five QTLs were found to be consistently shared across the traits. Collectively, these shared QTLs explained a substantial proportion of the phenotypic variance, accounting for between 9.30 and 19.30% of the observed variation, suggesting potential major genes for growth. These QTL regions led to the discovery of 65 potential candidate genes, including 11 genes that were specifically located within the shared QTLs. These genes were linked to essential biological processes, including metabolism, immunity, stress response, development, and vascular function. The establishment of this high-density genetic linkage map represents an important genomic resource for comprehending the genetic determinants of economically important traits in A. japonicus, with implications for advancing and optimising ongoing marker-assisted selection (MAS) initiatives in the species.

Silicon and iron nanoparticles protect rice against lead (Pb) stress by improving oxidative tolerance and minimizing Pb uptake

Lead (Pb) is toxic to the development and growth of rice plants. Nanoparticles (NPs) have been considered one of the efficient remediation techniques to mitigate Pb stress in plants. Therefore, a study was carried out to examine the underlying mechanism of iron (Fe) and silicon (Si) nanoparticle-induced Pb toxicity alleviation in rice seedlings. Si–NPs (2.5 mM) and Fe-NPs (25 mg L−1) were applied alone and in combination to rice plants grown without (control; no Pb stress) and with (100 µM) Pb concentration. Our results revealed that Pb toxicity severely affected all rice growth-related traits, such as inhibited root fresh weight (42%), shoot length (24%), and chlorophyll b contents (26%). Moreover, a substantial amount of Pb was translocated to the above-ground parts of plants, which caused a disturbance in the antioxidative enzyme activities. However, the synergetic use of Fe- and Si–NPs reduced the Pb contents in the upper part of plants by 27%. It reduced the lethal impact of Pb on roots and shoots growth parameters by increasing shoot length (40%), shoot fresh weight (48%), and roots fresh weight (31%). Both Si and Fe–NPs synergistic application significantly elevated superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and glutathione (GSH) concentrations by 114%, 186%, 135%, and 151%, respectively, compared to plants subjected to Pb stress alone. The toxicity of Pb resulted in several cellular abnormalities and altered the expression levels of metal transporters and antioxidant genes. We conclude that the synergistic application of Si and Fe-NPs can be deemed favorable, environmentally promising, and cost-effective for reducing Pb deadliness in rice crops and reclaiming Pb-polluted soils.