The statistical analysis of quality traits in plant improvement programs with application to the mapping of milling yield in wheat

2001 ◽  
Vol 52 (12) ◽  
pp. 1207 ◽  
Author(s):  
A. B. Smith ◽  
B. R. Cullis ◽  
R. Appels ◽  
A. W. Campbell ◽  
G. B. Cornish ◽  
...  
Keyword(s):  
Molecular Genetic ◽  
Triticum Aestivum L ◽  
Quality Trait ◽  
Quality Traits ◽  
Response To Selection ◽  
Improvement Programs ◽  
Selection For ◽  
Milling Yield ◽  
Marker Information ◽  
Phase Process

It is well known that the response to selection for grain yield is improved with the use of appropriate experimental designs and statistical analyses. The issues are more complex for quality traits since the data are obtained from a 2-phase process in which samples are collected from the field then processed in the laboratory. This paper presents a method of analysis for quality trait data that allows for variation arising from both the field and laboratory phases. Initially, an analysis suitable for standard varietal selection is presented. This is extended to include molecular genetic marker information for the purpose of detecting quantitative trait loci. The technique is illustrated using two doubled haploid wheat (Triticum aestivum L.) populations in which the trait of interest is milling yield.

scholarly journals An Overview of Key Factors Affecting Genomic Selection for Wheat Quality Traits

Plants ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 745
Author(s):  
Ivana Plavšin ◽  
Jerko Gunjača ◽  
Zlatko Šatović ◽  
Hrvoje Šarčević ◽  
Marko Ivić ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Prediction Accuracy ◽  
Molecular Genetic ◽  
Wheat Quality ◽  
Quality Traits ◽  
Key Factors ◽  
Breeding Values ◽  
Factors Affecting ◽  
Selection For ◽  
Marker Information

Selection for wheat (Triticum aestivum L.) grain quality is often costly and time-consuming since it requires extensive phenotyping in the last phases of development of new lines and cultivars. The development of high-throughput genotyping in the last decade enabled reliable and rapid predictions of breeding values based only on marker information. Genomic selection (GS) is a method that enables the prediction of breeding values of individuals by simultaneously incorporating all available marker information into a model. The success of GS depends on the obtained prediction accuracy, which is influenced by various molecular, genetic, and phenotypic factors, as well as the factors of the selected statistical model. The objectives of this article are to review research on GS for wheat quality done so far and to highlight the key factors affecting prediction accuracy, in order to suggest the most applicable approach in GS for wheat quality traits.

Correlated response to selection for litter size in pigs: II. Carcass, meat, and fat quality traits

2002 ◽  
Vol 80 (10) ◽  
pp. 2566 ◽  
Author(s):  
J. Estany ◽  
D. Villalba ◽  
M. Tor ◽  
D. Cubiló ◽  
J. L. Noguera
Keyword(s):  
Litter Size ◽  
Correlated Response ◽  
Quality Traits ◽  
Response To Selection ◽  
Fat Quality ◽  
Selection For

COMPARISON OF PREDICTED AND OBSERVED RESPONSES TO SELECTION FOR YIELD IN WHEAT

1971 ◽  
Vol 51 (3) ◽  
pp. 187-192 ◽  
Author(s):  
J. PESEK ◽  
R. J. BAKER
Keyword(s):  
Triticum Aestivum ◽  
Common Wheat ◽  
Triticum Aestivum L ◽  
Standard Errors ◽  
Selection Differential ◽  
Response To Selection ◽  
Simple Method ◽  
Different Populations ◽  
Selection For ◽  
Heritability Estimates

A simple method of calculating standard errors of heritability estimates is presented. The method is then used to conclude that observed response to selection for yield in five different populations of common wheat, Triticum aestivum L., agreed with the response predicted by multiplying estimates of heritability by the selection differential. It is suggested that a comparison of observed and predicted responses is not the best way to test the theory used in predicting response to selection.

scholarly journals 12 Genetic and phenotypic parameters for Aleutian disease tests and their correlations with growth and pelt quality traits in American mink

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 17-18
Author(s):  
Guoyu Hu ◽  
Duy Ngoc Do ◽  
Janine Gray ◽  
Karim Karimi ◽  
Younes Miar
Keyword(s):  
Fixed Effects ◽  
American Mink ◽  
Genetic Correlations ◽  
Direct Selection ◽  
Enzyme Linked Immunosorbent Assay ◽  
Quality Traits ◽  
Genetically Improved ◽  
Significant Heritability ◽  
Improvement Programs ◽  
Selection For

Abstract Aleutian disease brings tremendous financial losses to the mink industry. The ineffective immunoprophylaxis, medication, and culling strategies have urged the mink industry to select mink with low quantitative enzyme-linked immunosorbent assay (qELISA) score or negative counterimmunoelectrophoresis (CIEP) test result. However, little is known about the heritabilities of qELISA and CEIP as well as their relationships with growth and pelt quality traits. The traits, including qELISA, CIEP, body length at harvest (HLEN), the size of dried pelt (SIZE), the overall quality of dried pelt (QUA), and the nap length of dried pelt (NAP), were measured on 1,683 American mink from the Canadian Center for Fur Animal Research (Nova Scotia, Canada) and Millbank Fur Farm (Ontario, Canada). Significance (P < 0.05) of fixed effects (sex, farm, age, and color) and random effects (common litter, permanent environment, and dam) were determined by univariate analyses, while genetic and phenotypic parameters for all traits were estimated under bivariate analyses using ASREML 4.1. Estimated heritabilities (±SE) were 0.41±0.07 for qELISA, 0.06±0.06 for CIEP, 0.39±0.06 for HLEN, 0.46±0.07 for SIZE, 0.25±0.06 for QUA, and 0.46±0.08 for NAP. The qELISA showed non-significant (P > 0.05) genetic correlations with HLEN (0.05±0.13) and dried pelt traits (0.02±0.18 with SIZE, -0.21±0.20 with QUA, and -0.13±0.16 with NAP). The CIEP only showed a significant (P < 0.05) negative genetic correlation with SIZE (-0.85±0.33). The moderate-to-high heritabilities of qELISA, HLEN, SIZE, QUA, and NAP indicated that these traits can be genetically improved through a genetic/genomic selection. The low and non-significant heritability of CIEP indicated the ineffectiveness of direct selection for this trait. The estimated genetic parameters for qELISA suggested that selection for lower qELISA scores may not interfere with the selection of pelt size and quality in the genetic improvement programs of American mink.

Polymorphism of the PLIN1 gene and its association with body measures and ultrasound carcass traits in Qinchuan beef cattle

Genome ◽  
2020 ◽  
Vol 63 (10) ◽  
pp. 483-492 ◽  
Author(s):  
Sayed Haidar Abbas Raza ◽  
Li Shijun ◽  
Rajwali Khan ◽  
Nicola M. Schreurs ◽  
Zeinab Manzari ◽  
...  
Keyword(s):  
Lipid Droplets ◽  
Molecular Genetic ◽  
Carcass Traits ◽  
Subcutaneous Fat ◽  
The Body ◽  
Qinchuan Cattle ◽  
Hardy Weinberg Equilibrium ◽  
Improvement Programs ◽  
Selection For ◽  
Breed Improvement

The PLIN1 gene produces a phosphorylated protein wrapped in lipid droplets in adipocytes. This phosphorylation assists the mobilization of fat into adipose tissue. The purpose of the experiment was to study the polymorphism of the PLIN1 gene and its relationship with the body and carcass characteristics of Qinchuan cattle to find molecular genetic markers that can be used for breeding. The expression level of the PLIN1 gene was determined in various tissues by qRT-PCR. The results showed that the highest level of PLN1 expression was found in subcutaneous fat, followed by the heart and longissimus muscle, and the lowest level was found in the kidney. Five SNP loci of the PLIN1 gene were identified in 510 Qinchuan cattle, including g.3580T>C (SNP1), g.3898G>A (SNP2), g.8333G>A (SNP3), g.10517T>C (SNP4), and g.10538G>T (SNP5). The results show that SNP1, SNP2, SNP3, and SNP4 were moderately polymorphic (0.25 < PIC < 0.5), while SNP5 was minimally polymorphic (PIC < 0.25). SNP2, SNP3, and SNP5 were within Hardy–Weinberg equilibrium (P > 0.05), but SNP1 and SNP4 were not (P < 0.05). Correlation analysis showed that the five SNPs of the PLIN1 gene were correlated with back-fat depth, intramuscular fat, and chest depth of Qinchuan cattle. The double haplotype H2H4 in Qinchuan beef was associated with body and carcass traits. We conclude that variants mapped within PLIN1 can be used in marker-assisted selection for carcass quality and body traits in breed improvement programs for Qinchuan cattle.

Relationship of seed quality traits for greenhouse-grown versus field-grown high erucic acid rapesseed: Is seed quality trait selection for greenhouse-grown seed worthwhile?

2008 ◽  
Vol 88 (3) ◽  
pp. 419-423 ◽  
Author(s):  
J. Bahrani ◽  
P. B. E. McVetty
Keyword(s):  
Erucic Acid ◽  
Seed Quality ◽  
Quality Trait ◽  
Quality Traits ◽  
High Erucic Acid ◽  
Glucosinolate Concentration ◽  
The Mean ◽  
Selection For ◽  
Relationship Of ◽  
Seed Quality Traits

A study of the relationship of seed quality traits for greenhouse-grown and field-grown seed samples was conducted. Early generation high erucic acid rapeseed (HEAR) cross progeny were grown in the greenhouse, selfed and then the selfed seeds were grown in the field at the University of Manitoba. The oil, protein, erucic acid and glucosinolate concentrations of greenhouse-grown versus field-grown seed samples were compared. There were differences (P ≤ 0.01) between the means of all seed quality traits for greenhouse-grown versus field-grown seed samples. The mean oil, protein and erucic acid concentrations of field-grown seed samples were higher than for greenhouse-grown seed samples. In contrast, the mean glucosinolate concentration of greenhouse-grown seed samples was higher than for field-grown seed samples. Rank correlations between greenhouse-grown seed samples and field-grown seed samples for all seed quality traits were significant but moderate in magnitude. Selection for oil, protein, erucic acid and glucosinolate concentration in greenhouse-grown seed samples dramatically increased the number of high seed quality F4 families in the field and was successful for all seed quality traits. It is concluded that seed quality selection in greenhouse-grown seed samples is worthwhile and that this procedure could lead to greater efficiencies in Brassica plant breeding programs. Key words: Rapeseed (Brassica napus L.), oil, protein, erucic acid, glucosinolates

scholarly journals Combining metabolomic and transcriptomic approaches to assess and improve crop quality traits

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Delphine M. Pott ◽  
Sara Durán-Soria ◽  
Sonia Osorio ◽  
José G. Vallarino
Keyword(s):  
Quality Trait ◽  
Quality Traits ◽  
Crop Species ◽  
Breeding Programs ◽  
Crop Quality ◽  
Crop Varieties ◽  
New Genes ◽  
Technical Advances ◽  
Health Promoting ◽  
Selection Of

AbstractPlant quality trait improvement has become a global necessity due to the world overpopulation. In particular, producing crop species with enhanced nutrients and health-promoting compounds is one of the main aims of current breeding programs. However, breeders traditionally focused on characteristics such as yield or pest resistance, while breeding for crop quality, which largely depends on the presence and accumulation of highly valuable metabolites in the plant edible parts, was left out due to the complexity of plant metabolome and the impossibility to properly phenotype it. Recent technical advances in high throughput metabolomic, transcriptomic and genomic platforms have provided efficient approaches to identify new genes and pathways responsible for the extremely diverse plant metabolome. In addition, they allow to establish correlation between genotype and metabolite composition, and to clarify the genetic architecture of complex biochemical pathways, such as the accumulation of secondary metabolites in plants, many of them being highly valuable for the human diet. In this review, we focus on how the combination of metabolomic, transcriptomic and genomic approaches is a useful tool for the selection of crop varieties with improved nutritional value and quality traits.

Sign in / Sign up

Export Citation Format

Share Document