scholarly journals Phenotypic Variations and Heritability in Hybrid Populations of Bearded Iris

HortScience ◽  
2019 ◽  
Vol 54 (6) ◽  
pp. 988-992
Author(s):  
Zhuping Fan ◽  
Yike Gao ◽  
Ling Guo ◽  
Ying Cao ◽  
Rong Liu ◽  
...  
Keyword(s):  
Flower Color ◽  
Broad Sense ◽  
Phenotypic Traits ◽  
Broad Sense Heritability ◽  
Trait Variation ◽  
Correlation Distribution ◽  
Hybrid Complex ◽  
Phenotypic Variations ◽  
Trait Correlation ◽  
Selection Of

Bearded iris (Iris ×hybrida Hort.) is a large horticultural hybrid complex in the Iris genus, and the lack of understanding about its inheritance laws has seriously hindered the breeding process. From parental bearded iris ‘Indian Chief’ and ‘Sugar Blues’, four hybrid populations—including F1, F2, BC1P1, and BC1P2—were generated through hybridization. Fifteen key phenotypic traits, including plant height (PH), scape height (SH), length of fall (LF), width of fall (WF), length of standard (LS), width of standard (WS), and so on, were measured, and several genetic parameters (e.g., trait variation, heritability, trait correlation, distribution of flower color) were analyzed. The variation of phenotypic traits indicated that the F1 generation could produce larger flowers and a greater number of blooming stems than other generations, whereas backcrossing was beneficial at producing more flowers on one scape in the offspring of ‘Indian Chief’ and ‘Sugar Blues’. WF had the greatest broad-sense heritability (73.91%) among the 15 phenotypic traits, whereas the broad-sense heritability of SH was the lowest (2.06%). The correlation between a vegetative trait (PH) and a reproductive trait (WS) provided a path to early selection of germplasm. Furthermore, four important floral traits (LF, WF, LS, and WS) also correlated significantly to each other, thus simplifying the selection of larger flowers. Genes regulating fuchsia flower color were dominant over those for bluish purple flowers. Genetic effects of flower color in recurrent parents could be reinforced by backcrossing, thereby providing a potential way to modify flower color through hybridization.

scholarly journals Heritability of Simulated Wear and Traffic Tolerance in Three Fine Fescue Species

HortScience ◽  
2018 ◽  
Vol 53 (4) ◽  
pp. 416-420 ◽  
Author(s):  
Austin L. Grimshaw ◽  
Yuanshuo Qu ◽  
William A. Meyer ◽  
Eric Watkins ◽  
Stacy A. Bonos
Keyword(s):  
Broad Sense ◽  
Potential Candidate ◽  
Single Individual ◽  
Broad Sense Heritability ◽  
The North ◽  
Heritability Estimates ◽  
Traffic Tolerance ◽  
Fine Fescue ◽  
Selection Of ◽  
Wear Tolerance

In recent years, turfgrass breeders have given increased attention to the development of lower maintenance turfgrass cultivars. Fine fescues (Festuca spp.) have been identified as potential candidate species for low-maintenance lawns because of their reduced need for water, mowing, and fertilizer. Unfortunately, these species have some weaknesses that must be improved to facilitate their use; perhaps, the most important of these is tolerance to wear and traffic. For this trait to be improved in new cultivars, there must be sufficient heritable variation available for plant breeders to exploit; however, little is known about the heritability of this complex trait in fine fescue species. Therefore, the objective of this study was to determine the heritability of wear and traffic tolerance in three fine fescue species. Replicated field studies were established in North Brunswick, NJ, and St. Paul, MN, and each included 157 Chewing’s fescue (Festuca rubra L. subsp. fallax), 155 hard fescue (Festuca brevipilia), and 149 strong creeping red fescue (F. rubra L. subsp. rubra) genotypes. Wear tolerance was evaluated in North Brunswick and traffic tolerance was evaluated in St. Paul during 2015 and 2016 using different simulators to determine both plant performance and broad-sense heritability estimates for wear and traffic tolerance. Broad-sense heritability estimates for the three species when calculated on a clonal basis was between 0.69 and 0.82 for wear tolerance in the North Brunswick location and between 0.49 and 0.60 for traffic tolerance in the St. Paul location. On a single-plant basis, broad-sense heritability estimates for the three species were between 0.31 and 0.45 for wear tolerance in the North Brunswick location and 0.09 and 0.12 for traffic tolerance in St. Paul. However, this research does indicate that improvement of wear and traffic tolerance in fine fescues is possible through recurrent breeding methods based on selection of replicated clonally propagated genotypes rather than selection of single individual plants of a population. This was the first study to determine the genetic effects of wear and traffic tolerance in any turfgrass species.

scholarly journals Inheritance of Resistance to Colletotrichum Species in Strawberry

1991 ◽  
Vol 116 (4) ◽  
pp. 724-727 ◽  
Author(s):  
Creighton L. Gupton ◽  
Barbara J. Smith
Keyword(s):  
Recurrent Selection ◽  
Major Gene ◽  
Broad Sense ◽  
Inheritance Of Resistance ◽  
Broad Sense Heritability ◽  
Narrow Sense ◽  
Narrow Sense Heritability ◽  
Genetic Variances ◽  
Heritability Estimates ◽  
Selection Of

Experiments were conducted to estimate the relative importance of additive and dominance genetic variances and non-allelic interactions in the inheritance of resistance to Colletotrichum spp. in strawberry (Fragaria × ananassa Duch.). Progeny of 40 parents crossed in a Comstock and Robinson Design II Mating scheme were inoculated with three isolates of C. fragariae and one isolate of C. acutatum. Disease development on each plant was rated visually. Variance components were estimated and converted to genetic variances. Estimates of were six to 10 times higher than those for Within-family variance not accounted for by equaled 35% and 38% of the total genetic variance in females and males, respectively, indicating probable epistatic effects. The frequency distribution of disease severity ratings was bimodal in both experiments, suggesting major gene action. Narrow-sense heritability estimates were 0.37 and 0.26, and broad-sense heritability estimates were 0.87 and 0.85 for females and males, respectively. Narrow-sense heritability estimates are probably sufficient to produce gains from recurrent selection. Gains from selection of clonal value should be possible because of the high broad sense heritability estimates. It appears feasible to establish a broad genetic-based population resistant to Colletotrichum spp. from which selections could be evaluated per se and/or recombined to produce improved populations.

scholarly journals QTL Mapping for Gummy Stem Blight Resistance in Watermelon (Citrullus spp.)

Plants ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 500
Author(s):  
Eun Su Lee ◽  
Do-Sun Kim ◽  
Sang Gyu Kim ◽  
Yun-Chan Huh ◽  
Chang-Gi Back ◽  
...  
Keyword(s):  
Chromosome 8 ◽  
Chromosome 6 ◽  
Potential Candidate ◽  
Stem Blight ◽  
Gummy Stem Blight ◽  
F2 Population ◽  
Leaf Lesion ◽  
Phenotypic Variations ◽  
A Minor ◽  
Selection Of

Watermelon (Citrulluslanatus) is an economically important fruit crop worldwide. Gummy stem blight (GSB) is one of the most damaging diseases encountered during watermelon cultivation. In the present study, we identified quantitative trait loci (QTLs) associated with GSB resistance in an F2 population derived from a cross between maternal-susceptible line ‘920533’ (C. lanatus) and the paternal-resistant line ‘PI 189225’ (C. amarus). The resistance of 178 F2 plants was assessed by two different evaluation methods, including leaf lesion (LL) and stem blight (SB). To analyze the QTLs associated with GSB resistance, a linkage map was constructed covering a total genetic distance of 1070.2 cM. QTL analysis detected three QTLs associated with GSB resistance on chromosome 8 and 6. Among them, two QTLs, qLL8.1 and qSB8.1 on chromosome 8 identified as major QTLs, explaining 10.5 and 10.0% of the phenotypic variations localizing at same area and sharing the same top markers for both LL and SB traits, respectively. A minor QTL, qSB6.1, explains 9.7% of phenotypic variations detected on chromosome 6 only for the SB trait. High-throughput markers were developed and validated for the selection of resistant QTLs using watermelon accessions, and commercial cultivars. Four potential candidate genes were predicted associated with GSB resistance based on the physical location of flanking markers on chromosome 8. These findings will be helpful for the development of watermelon cultivars resistant to GSB.

scholarly journals Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 599
Author(s):  
Miguel A. Gutierrez-Reinoso ◽  
Pedro M. Aponte ◽  
Manuel Garcia-Herreros
Keyword(s):  
Dairy Cattle ◽  
Production Efficiency ◽  
Association Studies ◽  
Phenotypic Traits ◽  
Progeny Testing ◽  
Genome Wide Association Studies ◽  
Genetic Progress ◽  
Breeding Programs ◽  
Increased Risk ◽  
Selection Of

Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.

scholarly journals Machine learning, transcriptome, and genotyping chip analyses provide insights into SNP markers identifying flower color in Platycodon grandiflorus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Go-Eun Yu ◽  
Younhee Shin ◽  
Sathiyamoorthy Subramaniyam ◽  
Sang-Ho Kang ◽  
Si-Myung Lee ◽  
...  
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Feature Selection Method ◽  
Flower Color ◽  
Classification Performance ◽  
Snp Markers ◽  
Rna Seq ◽  
Color Classification ◽  
Dna Pcr ◽  
Selection Of

AbstractBellflower is an edible ornamental gardening plant in Asia. For predicting the flower color in bellflower plants, a transcriptome-wide approach based on machine learning, transcriptome, and genotyping chip analyses was used to identify SNP markers. Six machine learning methods were deployed to explore the classification potential of the selected SNPs as features in two datasets, namely training (60 RNA-Seq samples) and validation (480 Fluidigm chip samples). SNP selection was performed in sequential order. Firstly, 96 SNPs were selected from the transcriptome-wide SNPs using the principal compound analysis (PCA). Then, 9 among 96 SNPs were later identified using the Random forest based feature selection method from the Fluidigm chip dataset. Among six machines, the random forest (RF) model produced higher classification performance than the other models. The 9 SNP marker candidates selected for classifying the flower color classification were verified using the genomic DNA PCR with Sanger sequencing. Our results suggest that this methodology could be used for future selection of breeding traits even though the plant accessions are highly heterogeneous.

High Heritability of Glycyrrhizic Acid, Glabridin, Liquiritin and Liquiritigenin in Licorice (Glycyrrhiza Glabra L.) Populations of Iran

2021 ◽  
Author(s):  
Ghasem Eghlima ◽  
Mohsen Sanikhani ◽  
Azizollah Kheiry ◽  
Javad Hadian
Keyword(s):  
Coefficient Of Variation ◽  
Morphological Traits ◽  
Glycyrrhizic Acid ◽  
Correlation Coefficients ◽  
Glycyrrhiza Glabra ◽  
Broad Sense ◽  
Phenotypic Correlation ◽  
Broad Sense Heritability ◽  
Narrow Sense Heritability ◽  
Perennial Plant

Abstract Glycyrrhiza glabra L. is an herbaceous, perennial plant with high distribution in Iran. Genetic variability, heritability and correlation among characters in 22 populations of G. glabra L. were studied. The genetic parameters among the traits including phenotypic variances, genotypic variances, genotype by environment variances, broad-sense heritability and genotypic and phenotypic correlation coefficients were studied. Variance components analysis showed that the extent of phenotypic coefficient of variation (PCV) was fairly higher for all the examined traits compared with genotypic coefficient of variation (GCV). Glabridin (GLA) exhibited high GCV and PCV (156.07% and 156.68%, respectively). The broad sense heritability varied from 38.92–99.79% and narrow sense heritability ranged from 9.70 % to 24.94%. Heritability of GLA, glycyrrhizic acid (GLY), liquiritin (LI), liquiritigenin (LIQ), rutin (RU) and rosmarinic acid (RA) were very high, exhibiting more than 97% heritability. Therefore, these critical characteristics can efficiently be selected and inherited in breeding programs. In most traits, the genotypic correlations showed the same direction as the phenotypic correlations. The contents of GLA and LIQ showed a positive correlation with majority of morphological traits. Therefore, selecting individual plants having desired morphological traits can be correlated with high contents of bioactive compounds in the harvested root.

scholarly journals Genetic variation and correlation of agronomic traits in meadow bromegrass (Bromus riparius Rehm) clones

2004 ◽  
Vol 34 (2) ◽  
pp. 505-510 ◽  
Author(s):  
Marcelo Renato Alves de Araújo ◽  
Bruce Coulman
Keyword(s):  
Genetic Variation ◽  
Crude Protein ◽  
Genetic Correlations ◽  
Neutral Detergent Fiber ◽  
Broad Sense ◽  
Grass Species ◽  
Broad Sense Heritability ◽  
Bromus Riparius ◽  
Heritability Estimates ◽  
Meadow Bromegrass

Meadow bromegrass (Bromus riparius Rehm.) is a recently introduced pasture grass in western Canada. Its leafy production and rapid regrowth have made it a major grass species for pasturing beef animals in this region. As relatively little breeding work has been done on this species, there is little information on its breeding behaviour. The main objective of this study was to estimate total genetic variability, broad-sense heritability, phenotypic and genetic correlations. Forty-four meadow bromegrass clones were evaluated for agronomic characters. Genetic variation for dry matter yield, seed yield, fertility index, harvest index, plant height, plant spread, crude protein, neutral detergent fiber and acid detergent fiber, was significant. Broad-sense heritability estimates exceeded 50% for all characters. Heritability estimates were at least 3.5 times greater than their standard errors. Phenotypic and genetic correlation between all possible characters were measured. There was general agreement in both sign and magnitude between genetic and phenotypic correlations. Correlations between the different characters demonstrated that it is possible to simultaneously improve seed and forage yield. Based on the results, it appears that the development of higher yielding cultivars with higher crude protein, and lower acid and neutral detergent fibers concentration should be possible.

scholarly journals Genotypic parameters for egg production in pure breed hens by using random regression model

2017 ◽  
Vol 47 (5) ◽  
Author(s):  
Priscila Becker Ferreira ◽  
Paulo Roberto Nogara Rorato ◽  
Fernanda Cristina Breda ◽  
Vanessa Tomazetti Michelotti ◽  
Alexandre Pires Rosa ◽  
...  
Keyword(s):  
Regression Model ◽  
Regression Models ◽  
Egg Production ◽  
Random Regression ◽  
Broad Sense Heritability ◽  
Residual Matrix ◽  
Random Regression Model ◽  
Residual Covariance ◽  
Genotypic Correlations ◽  
Selection Of

ABSTRACT: This study aimed to test different genotypic and residual covariance matrix structures in random regression models to model the egg production of Barred Plymouth Rock and White Plymouth Rock hens aged between 5 and 12 months. In addition, we estimated broad-sense heritability, and environmental and genotypic correlations. Six random regression models were evaluated, and for each model, 12 genotypic and residual matrix structures were tested. The random regression model with linear intercept and unstructured covariance (UN) for a matrix of random effects and unstructured correlation (UNR) for residual matrix adequately model the egg production curve of hens of the two study breeds. Genotypic correlations ranged from 0.15 (between age of 5 and 12 months) to 0.99 (between age of 10 and 11 months) and increased based on the time elapsed. Egg production heritability between 5- and 12-month-old hens increased with age, varying from 0.15 to 0.51. From the age of 9 months onward, heritability was moderate with estimates of genotypic correlations higher than 90% at the age of 10, 11, and 12 months. Results suggested that selection of hens to improve egg production should commence at the ninth month of age.

Clonal testing efficiency: the trade-offs between clones tested and ramets per clone

1986 ◽  
Vol 16 (5) ◽  
pp. 925-930 ◽  
Author(s):  
J. H. Russell ◽  
W. J. Libby
Keyword(s):  
Clonal Selection ◽  
Simulation Models ◽  
Radiata Pine ◽  
Fixed Number ◽  
Broad Sense ◽  
Optimum Level ◽  
Broad Sense Heritability ◽  
Selection Intensity ◽  
Trade Offs ◽  
Clonal Testing

Three contrasting simulation models were developed to investigate testing efficiencies in a clonal selection program. The variables investigated were number of total plants tested, number of candidate clones tested, number of ramets per clone, number of clones selected, selection intensity, and broad-sense heritability. The model deemed appropriate to most clonal forestry situations selected a fixed number of clones in an experiment with the total number of plants in the test held constant. In this model, as the number of ramets per clone was varied, the number of candidate clones tested and the selection intensity necessarily also varied. This model indicates that cloning individuals for testing is useful when selection is based on a characteristic or index with broad-sense heritability less than about 0.6. At the lower heritabilities, two to six ramets per clone per site usually produces the optimum level of cloning, the exact number depending upon the selection intensity and heritability. Predictions generated by this fixed number of selected clones model were compared with average phenotypic values of selections using different subsamples of data for 8-year height and for 8-year diameter in a radiata pine (Pinusradiata D. Don) clonal experiment. Agreement between predictions and average phenotypic values in both these two comparisons was close.

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