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Genomic selection is being used increasingly in plant breeding to accelerate genetic gain per unit time. One of the most important applications of genomic selection in maize breeding is to predict and select the best un-phenotyped lines in bi-parental populations based on genomic estimated breeding values. In the present study, 22 bi-parental tropical maize populations genotyped with low density SNPs were used to evaluate the genomic prediction accuracy ( ) of the six trait-environment combinations under various levels of training population size (TPS) and marker density (MD), and assess the effect of trait heritability ( ), TPS and MD on estimation. Our results showed that: (1) moderate values were obtained for different trait-environment combinations, when 50% of the total genotypes was used as training population and ~200 SNPs were used for prediction; (2) increased with an increase in , TPS and MD, both correlation and variance analyses showed that is the most important factor and MD is the least important factor on estimation for most of the trait-environment combinations; (3) predictions between pairwise half-sib populations showed that the values for all the six trait-environment combinations were centered around zero, 49% predictions had values above zero; (4) the trend observed in differed with the trend observed in / , and is the square root of heritability of the predicted trait, it indicated that both and / values should be presented in GS study to show the accuracy of genomic selection and the relative accuracy of genomic selection compared with phenotypic selection, respectively. This study provides useful information to maize breeders to design genomic selection workflow in their breeding programs.

Root shape in carrot ( Daucus carota subsp. sativus ), which ranges from long and tapered to short and blunt, has been used for at least several centuries to classify carrot cultivars. The subjectivity involved in determining market class hinders the establishment of metric-based standards and is ill-suited to dissecting the genetic basis of such quantitative phenotypes. Advances in digital image acquisition and analysis has enabled new methods for quantifying sizes of plant structures and shapes, but in order to dissect the genetic control of the shape features that define market class in carrot, a tool is required that quantifies the specific shape features used by humans in distinguishing between classes. This study reports the construction and demonstration of the first such platform, which facilitates rapid phenotyping of traits that are measurable by hand, such as length and width, as well as principal component analysis (PCA) of the root contour and its curvature. This latter approach is of particular interest, as it enabled the detection of a novel and significant quantitative trait, defined here as root fill, which accounts for 85% of the variation in root shape. Curvature analysis was demonstrated to be an effective method for precise measurement of the broadness of the carrot shoulder, and degree of tip fill; the first principal component of the respective curvature profiles captured 87% and 84% of the total variance. This platform’s performance was validated in two experimental panels. First, a diverse, global collection of germplasm was used to assess its capacity to identify market classes through clustering analysis. Second, a diallel mating design between inbred breeding lines of differing market classes was used to estimate the heritability of the key phenotypes that define market class, which revealed significant variation in the narrow-sense heritability of size and shape traits, ranging from 0.14 for total root size, to 0.84 for aspect ratio. These results demonstrate the value of high-throughput digital phenotyping in characterizing the genetic control of complex quantitative phenotypes.

Sperm morphology (size and shape) and sperm velocity are both positively associated with fertilization success, and are expected to be under strong selection. Until recently, evidence for a link between sperm morphology and velocity was lacking, but recent comparative studies have shown that species with high levels of sperm competition have evolved long and fast sperm. It is therefore surprising that evidence for a phenotypic or genetic relationship between length and velocity within species is equivocal, even though sperm competition is played out in the intraspecific arena. Here, we first show that sperm velocity is positively phenotypically correlated with measures of sperm length in the zebra finch Taeniopygia guttata. Second, by using the quantitative genetic “animal model” on a dataset from a multigenerational-pedigreed population, we show that sperm velocity is heritable, and positively genetically correlated to a number of heritable components of sperm length. Therefore, selection for faster sperm will simultaneously lead to the evolution of longer sperm (and vice versa). Our results provide, for the first time, a clear phenotypic and genetic link between sperm length and velocity, which has broad implications for understanding how recently described macroevolutionary patterns in sperm traits have evolved.

Rabbits are essential for commercial meat production due to their efficient growth and productivity, breeds like New Zealand White (NZW), Californian (CAL), and Gabali (GAB) rabbits offer unique genetic traits in litter, growth, and carcass traits. This study aimed to evaluate heritability (h 2 ), genetic and phenotypic correlations (rg and rp) for litter size, body weight and carcass traits across California (CAL), New Zealand white (NZW) and Gabali (GA) rabbits. Along with exploring gene expression profiles of TBC1D1 , NPY , AGRP , POMC , Leptin, GH , GHR , IGF-1 , CAA , GPR , ACC , CPT1 , FAS , and CART in the brain, liver, and meat tissues of different rabbit breeds. The breed genotype had a significant impact on litter size (LS), litter weight (LW), body weight at 12 weeks (BW12), and daily weight gain (DWG) traits. NZW rabbits displayed superior performance in terms of litter size and litter weight, while CAL rabbits recorded the highest values for BW12 and DWG. Heritability estimates (h 2 ) were generally low for litter size (ranging from 0.05 to 0.12) and medium for body weight (ranging from 0.16 to 0.31). Both genetic (r g ) and phenotypic (r p ) correlations for litter size were positive and moderate (ranging from 0.08 to 0.48), while correlations for body weight ranged from 0.21 to 0.58. Additionally, CAL rabbits exhibited higher carcass traits compared to NZW and GA rabbits. In terms of breed-specific gene expression patterns, New Zealand White (NZW) rabbits displayed the highest expression levels of key genes related to energy metabolism ( TBC1D1 ), appetite regulation ( NPY , AGRP , POMC ), nutrient transport ( CAA ), and G protein-coupled receptors ( GPR ) in both brain and liver tissues. Californian (CAL ) rabbits exhibited superior gene expression of the ACC gene in brain tissue and GH , GHR , and IGF-1 genes in brain and meat tissues. Gabali (GAB) rabbits demonstrated the highest expression levels of TBC1D1 , NPY , AGRP , GPR , and ACC genes in meat tissues. These breed-specific gene expression differences, combined with genetic evaluation efforts, have the potential to enhance reproductive and productive performance in rabbits, offering valuable insights for rabbit breeding programs and genetic selection.

In this study, the heritability, repeatability, phenotypic correlation, and genetic correlation of the reproductive and growth traits of L. vannamei were investigated and estimated. Eight traits of 385 shrimps from forty-two families, including the number of eggs (EN), number of nauplii (NN), egg diameter (ED), spawning frequency (SF), spawning success (SS), female body weight (BW) and body length (BL) at insemination, and condition factor (K), were measured,. A total of 519 spawning records including multiple spawning and 91 no spawning records were collected. The genetic parameters were estimated using an animal model, a multinomial logit model (for SF), and a sire-dam and probit model (for SS). Because there were repeated records, permanent environmental effects were included in the models. The heritability estimates for BW, BL, EN, NN, ED, SF, SS, and K were 0.49 ± 0.14, 0.51 ± 0.14, 0.12 ± 0.08, 0, 0.01 ± 0.04, 0.06 ± 0.06, 0.18 ± 0.07, and 0.10 ± 0.06, respectively. The genetic correlation was 0.99 ± 0.01 between BW and BL, 0.90 ± 0.19 between BW and EN, 0.22 ± 0.97 between BW and ED, ?0.77 ± 1.14 between EN andED, and ?0.27 ± 0.36 between BW and K. The heritability of EN estimated without a covariate was 0.12 ± 0.08, and the genetic correlation was 0.90 ± 0.19 between BW and EN, indicating that improving BW may be used in selection programs to genetically improve the reproductive output of L. vannamei during the breeding. For EN, the data were also analyzed using body weight as a covariate (EN-2). The heritability of EN-2 was 0.03 ± 0.05, indicating that it is difficult to improve the reproductive output by genetic improvement. Furthermore, excessive pursuit of this selection is often at the expense of growth speed. Therefore, the selection of high-performance spawners using BW and SS may be an important strategy to improve nauplii production.

The analysis of multiples traits has been largely employed in animal and forestry crop breeding; however, in annual crops such as common bean this approach is practically lacking. This study examined the selective accuracy and estimates of genetic parameters in common bean using single- and multi-trait analyses in several designs of genetic correlations and heritabilities by means of simulated- and real-traits. We also compared the efficiency of the Bayesian and REML methods as regarding its selective accuracy and estimates of genetic parameters. In real data experiments, 100 endogamic families of common bean were assessed for grain yield (GY) and grain type (GT) in three environments using a 10 × 10 triple lattice design. Single- and multi-trait analyses were applied for these traits using REML-based BLUP analysis and Bayesian methods. In simulated experiments, traits corresponding to GY and yield components in common bean were simulated under several levels of genetic correlations and evaluated under different levels of heritability in order to verify in which genetic/experimental design it is advantageous to apply single- or multi-trait analyses. The results obtained in this study indicated that GY and GT present low genetic correlation and, therefore, multi-trait analysis may be unjustifiable for these traits. The Bayesian and REML multi-trait analyses were equivalent in point and interval estimates of genetic parameters and predictive accuracy, both for the field and simulated experiments. In addition, it was found that multi-trait analysis is justified in situations where the traits present low/moderate heritability and medium/high genetic correlations among them. It also was found that GY in common bean may be outstandingly favored in accuracy when evaluated jointly with its components. Thus, one can conclude that the simultaneous analysis of GY and yield components in common bean may provide superior gains accuracy and selection efficiency, being the response to selection better obtained by use of the multi-trait heritability.

Objective: The phenotypic heterogeneity of metabolic syndrome (MSX) suggests heterogeneity of the underlying genotype. The aim of the present study was to examine the common genetic background that contributes to the clustering between the two main features (insulin resistance, central obesity) and different MSX component traits. Methods: In all, 492 individuals from 90 families were investigated in a three-generation family path study as part of the Kiel Obesity Prevention Study (KOPS, 162 grandparents, 66.1+/-6.7 years, 173 parents, 41.3+/-5.4 years and 157 children, 10.8+/-3.4 years). Overall heritability was estimated and common familial (genetic and environmental) influences on insulin resistance (HOMA-IR) or central obesity (elevated waist circumference, WC), respectively, and different MSX traits were compared in a bivariate cross-trait correlation model. Results: Prevalence of MSX (according to NCEP criteria) was 27.2% (f) and 27.8% (m) in adults and 3.5% (f) and 8.5% (m) in children and adolescents, respectively. MSX phenotype was found to be highly variable, comprising 16 subtypes of component trait combinations. Within-trait heritability was 38.5% for HOMA-IR and 53.5% for WC, cross-trait heritability was 53.4%. As much as 6-18% and 3-10% of the shared variance between different MSX component traits (lipid profile, blood pressure) and WC or HOMA-IR, respectively, may be genetic. With the exception of HDL-C, the shared genetic variance between MSX component traits and WC was higher than the genetic variance shared with HOMA-IR. Conclusion: A common genetic background contributes to the clustering of different MSX component traits and central obesity or insulin resistance. Common genetic influences favour central obesity as a major characteristic linking these traits.

This study aimed to investigate the genetic parameters for body weights of White and Black local chickens. The experiment conducted at College of Agric., Salahaddien Univ. during the period from Sept. 2016 until April 2018. 520 fertile eggs were taken from Agri. Res. Center, Ministry of Agric., Baghdad. Hatched chicks considered as parents (G0), and distributed randomly in to ten families. Resulted eggs from each family were collected during the peak of production for each generation to produce chicks of the next generation (G1 and G2). Body weights of resulted chicks were recorded at 1-day old and weekly till maturity. SAS program used to analyze the body weights (BW) and body weight gains (BWG) at different ages. The model includes genetic groups and generations for traits before sexing and the effect of sex added for the traits after sexing. Variance component of random effects estimated by REML and tested for positive definiteness to develop reliable estimates. Repeatability for body weights estimated. BW of chicks at 1 day, 4, 8, 9, 10, 16 and 17 week were 31.02, 292.47, 679.29, 794.58, 892.82, 1362.53 and 1252.17 g, and BWG at (1-4, 4-8, 9-10 and10-16) weeks were 261.45, 386.82, 98.24, and 469.51 g, respectively. The chicks of black group significantly excelled the white group in their weight at 1 day, 4, 8, 16 and 17, as well at ages 1-4 and 10-16 weeks. The effect of generation on BW of chicks at all ages and BWG at 1-4, 4-8 weeks was highly significant and (P<0.05) during 9-10 and 10-16 weeks. Males surpassed females significantly (p<0.01) in their BW at 9, 10 and 16 weeks and in their BWG during 9-10 and 10-16 weeks. Estimates of heritability were 0.42, 0.61, 0.76, 0.71, 0.43, 0.51, and 0.70 and of repeatability were 0.29, 0.26, 0.22, 0.38, 0.41, 0.74, and 0.78 for BW at 1 day, 4, 8, 9, 10, 16 and 17 weeks respectively. Higher (0.78) and lower (0.14) genetic correlations were recorded between BW at 8 weeks with each of BW at 10 and 17 weeks respectively. While the phenotypic correlations ranged between 0.04 (among BW at 1 day with weight at 9 weeks) and 0.58 (among BW 16 with 17 weeks).

Cowpea is an important legume crop in Africa, valued highly for its grain and also haulms, which are a tradable commodity in fodder markets. Fodder market surveys in Northern Nigeria showed that groundnut haulms were priced higher than cowpea haulms, probably because of their superior nutritive value. The economic value of haulms has prompted cowpea breeders and livestock nutritionists to explore haulm fodder traits as additional selection and breeding criteria. Fifty cowpea genotypes cultivated across five locations in Nigeria in 2013 and 2014 were evaluated for food fodder traits. Significant ( < 0.05) genotypic dependent variations were observed in yields (kg/ha) of grains (537-1082) and haulms (1173-3368), though significant ( < 0.05) effects of location and year were observed. Grain and fodder yield had a tendency to be positively correlated ( = 0.26, = 0.07). Haulms were analyzed for nitrogen (N), fiber fractions, digestibility, and metabolizable energy content. Highly significant variations were observed in all genotypic and livestock nutrition traits, although location and year had significant effects. Trade-offs between grain yield and haulm fodder quality traits were largely absent and haulm acid detergent lignin and grain yield were even inversely correlated ( = -0.28, = 0.05), that is high grain yielders had decreased haulm lignin. However, haulm N and grain yield also tended to be negatively associated ( = -0.26, = 0.07). Haulm fodder quality traits and haulm yield were mostly positively correlated ( < 0.05). Broad sense heritabilities for grain and fodder yield were 0.50 and 0.29, respectively, while heritability for haulm fodder quality traits ranged from 0.61 to 0.67, providing opportunities for concomitant increase in grain yield and haulm fodder quality traits. Selection of the 10 highest ranking genotypes for grain yield, haulm yield, haulm N, and haulm organic matter digestibility showed selection groups overlapping, suggesting that multi-trait selection is feasible. Economical evaluation showed that choice of primary traits is context specific, highlighting the need for identifying and targeting appropriate genotypes to fit different production systems. Considering haulm quantity and quality as traits of economic value can increase overall plant value in mixed crop-livestock systems.

Chilli ( Capsicum annuum L.) is regarded as one of the main commercial vegetable and spice crops at the global level. Maximum diversity can be noted among the cultivars/landraces available in India with respect to shape, size, yield, quality, and other traits. The present experiment was conducted to identify the most promising chilli variety suited for green and dry purposes, to study the genetic variability for different traits and to assess the association of different yield attributing traits with the green and dry yield of chilli. Thirty four genotypes were characterized during a 2-yr period. Most of the genotypes possessed the character constellation of C. annuum. Two genotypes, 'Chaitali Pointed' and 'BC CH Sel-4' were found most promising with respect to green fruit yield (272.79 g, 221.10 g per plant) and dry fruit yield (54.56 g, 44.44 g per plant). Phenotypic and Genotypic Coefficient of Variation values for green fruit weight (119.95%, 111.26%), green fruit girth (89.76%, 48.93%), weight of red ripe fruit (112.02%, 111.93%), weight of dry fruit (111.63%, 110.97%) and number of fruits per plant (86.05%, 85.02%) were recorded to be high. Green fruit yield per plant, ascorbic acid content, and number of fruits per plant also showed very high broad-sense heritability and genetic advance. From the study of correlation and path coefficient analyses, the number of fruits per plant, green fruit length for green chilli, weight of dry fruit and the number of fruits per plant for dry chilli were found to the most important selection indices.