scholarly journals Genetic analysis of three maize husk traits by QTL mapping in a maize-teosinte population

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xiaolei Zhang ◽  
Ming Lu ◽  
Aiai Xia ◽  
Tao Xu ◽  
Zhenhai Cui ◽  
...  
Keyword(s):  
Phenotypic Variation ◽  
Genetic Basis ◽  
Molecular Breeding ◽  
Best Linear Unbiased Predictor ◽  
Maize Line ◽  
Maize Varieties ◽  
Outer Covering ◽  
High Heritability ◽  
Best Linear Unbiased ◽  
Variation Explained

Abstract Background The maize husk consists of numerous leafy layers and plays vital roles in protecting the ear from pathogen infection and dehydration. Teosinte, the wild ancestor of maize, has about three layers of small husk outer covering the ear. Although several quantitative trait loci (QTL) underlying husk morphology variation have been reported, the genetic basis of husk traits between teosinte and maize remains unclear. Results A linkage population including 191 BC2F8 inbred lines generated from the maize line Mo17 and the teosinte line X26–4 was used to identify QTL associated with three husk traits: i.e., husk length (HL), husk width (HW) and the number of husk layers (HN). The best linear unbiased predictor (BLUP) depicted wide phenotypic variation and high heritability of all three traits. The HL exhibited greater correlation with HW than HN. A total of 4 QTLs were identified including 1, 1, 2, which are associated with HL, HW and HN, respectively. The proportion of phenotypic variation explained by these QTLs was 9.6, 8.9 and 8.1% for HL, HN and HW, respectively. Conclusions The QTLs identified in this study will pave a path to explore candidate genes regulating husk growth and development, and benefit the molecular breeding program based on molecular marker-assisted selection to cultivate maize varieties with an ideal husk morphology.

scholarly journals Variance Components and Estimates of Broad-sense Heritability of Nut and Kernel Traits in Hazelnut

HortScience ◽  
1997 ◽  
Vol 32 (3) ◽  
pp. 494D-494
Author(s):  
Qiang Yao ◽  
Shawn A. Mehlenbacher
Keyword(s):  
Genetic Variation ◽  
Phenotypic Variation ◽  
Variance Components ◽  
Genetic Basis ◽  
Corylus Avellana ◽  
Broad Sense ◽  
Broad Sense Heritability ◽  
Narrow Sense ◽  
High Heritability ◽  
Kernel Traits

Seventy-seven trees representing 41 hazelnut (Corylus avellana L.) genotypes were to evaluate variance components and broad-sense heritability for 10 nut and kernel traits from 1994 to 1996. All effects in the models were assumed to be random. All traits had extremely high heritability. This indicated that nearly all of the phenotypic variation had a genetic basis. Knowledge of variance components may help us efficiently allocate resources. Broad-sense heritability estimates were larger than those in narrow sense, suggesting the presence of nonadditive genetic variation in the population.

scholarly journals Fine Mapping of Qph9, A Major Quantitative Trait Locus, Responsible for Plant Height In Foxtail Millet [Setaria Italica (L.) P. Beauv.]

2021 ◽  
Author(s):  
Xiaofen Du ◽  
Zhilan Wang ◽  
Kangni Han ◽  
Shichao Lian ◽  
Yuxin Li ◽  
...  
Keyword(s):  
Plant Height ◽  
Phenotypic Variation ◽  
Quantitative Trait ◽  
Marker Assisted Selection ◽  
Major Quantitative Trait Locus ◽  
Molecular Breeding ◽  
Average Distance ◽  
Foxtail Millet ◽  
Trait Locus ◽  
Variation Explained

Abstract Plant height is vital for crop yield by influencing plant architecture and resistance to lodging. Although lots of quantitative trait loci (QTLs) controlling plant height had been mapped in foxtail millet, their contributions to phenotypic variation were generally small and mapping regions were relatively large, indicating the difficult application in molecular breeding using marker-assisted selection. In the present paper, a total of 23 QTLs involving in 15 traits were identified via a high-density Bin map containing 3024 Bin markers with an average distance of 0.48 cM from an F2 population. Among them, qPH9 with a large phenotypic variation explained (51.6%) related to plant height, was one of the major QTLs. Furthermore, qPH9 was repeatedly detected in multi-environments under field conditions using two new F2 population from the same F1 plant, and was narrowed down to a smaller interval of 281 kb using 1024 recessive individuals of F2 population. Finally, we found that there was an extremely significant correlation between marker MRI1016 and plant height, and speculated that Seita.9G088900 and Seita.9G089700 could be key candidates of qPH9. This study laid an important foundation for the cloning of qPH9 and molecular breeding of dwarf varieties via marker-assisted selection.

scholarly journals Comprehensive Genome-Wide Association Analysis Reveals the Genetic Basis of Root System Architecture in Soybean

2020 ◽  
Vol 11 ◽  
Author(s):  
Waldiodio Seck ◽  
Davoud Torkamaneh ◽  
François Belzile
Keyword(s):  
Root System ◽  
System Architecture ◽  
Phenotypic Variation ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Primary Root ◽  
Root System Architecture ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Genome Wide

Increasing the understanding genetic basis of the variability in root system architecture (RSA) is essential to improve resource-use efficiency in agriculture systems and to develop climate-resilient crop cultivars. Roots being underground, their direct observation and detailed characterization are challenging. Here, were characterized twelve RSA-related traits in a panel of 137 early maturing soybean lines (Canadian soybean core collection) using rhizoboxes and two-dimensional imaging. Significant phenotypic variation (P < 0.001) was observed among these lines for different RSA-related traits. This panel was genotyped with 2.18 million genome-wide single-nucleotide polymorphisms (SNPs) using a combination of genotyping-by-sequencing and whole-genome sequencing. A total of 10 quantitative trait locus (QTL) regions were detected for root total length and primary root diameter through a comprehensive genome-wide association study. These QTL regions explained from 15 to 25% of the phenotypic variation and contained two putative candidate genes with homology to genes previously reported to play a role in RSA in other species. These genes can serve to accelerate future efforts aimed to dissect genetic architecture of RSA and breed more resilient varieties.

A method for reducing inbreeding with Best Linear Unbiased Prediction

1993 ◽  
Vol 1993 ◽  
pp. 33-33
Author(s):  
B Grundy ◽  
WG Hill
Keyword(s):  
Best Linear Unbiased Prediction ◽  
Breeding Value ◽  
Best Linear Unbiased Predictor ◽  
Linear Unbiased Prediction ◽  
Genetic Merit ◽  
Selection Decisions ◽  
Best Linear Unbiased ◽  
Estimated Breeding Value ◽  
Commercial Environment ◽  
Unbiased Prediction

An optimum way of selecting animals is through a prediction of their genetic merit (estimated breeding value, EBV), which can be achieved using a best linear unbiased predictor (BLUP) (Henderson, 1975). Selection decisions in a commercial environment, however, are rarely made solely on genetic merit but also on additional factors, an important example of which is to limit the accumulation of inbreeding. Comparison of rates of inbreeding under BLUP for a range of hentabilities highlights a trend of increasing inbreeding with decreasing heritability. It is therefore proposed that selection using a heritability which is artificially raised would yield lower rates of inbreeding than would otherwise be the case.

scholarly journals Genetic Architecture: Dissecting the Genetic Basis of Phenotypic Variation

2002 ◽  
Vol 12 (12) ◽  
pp. R415-R416 ◽  
Author(s):  
Julian K Christians ◽  
Peter D Keightley
Keyword(s):  
Phenotypic Variation ◽  
Genetic Architecture ◽  
Genetic Basis

scholarly journals Phenotypic variation in Heliconius erato crosses shows that iridescent structural colour is sex-linked and controlled by multiple genes

2018 ◽  
Vol 9 (1) ◽  
pp. 20180047 ◽  
Author(s):  
Melanie N. Brien ◽  
Juan Enciso-Romero ◽  
Andrew J. Parnell ◽  
Patricio A. Salazar ◽  
Carlos Morochz ◽  
...  
Keyword(s):  
Phenotypic Variation ◽  
Genetic Basis ◽  
Sex Chromosome ◽  
Scattering Data ◽  
Colour Pattern ◽  
Structural Colour ◽  
X Ray Scattering ◽  
Multiple Genes ◽  
Colour Patterns ◽  
Blue Reflectance

Bright, highly reflective iridescent colours can be seen across nature and are produced by the scattering of light from nanostructures. Heliconius butterflies have been widely studied for their diversity and mimicry of wing colour patterns. Despite iridescence evolving multiple times in this genus, little is known about the genetic basis of the colour and the development of the structures which produce it. Heliconius erato can be found across Central and South America, but only races found in western Ecuador and Colombia have developed blue iridescent colour. Here, we use crosses between iridescent and non-iridescent races of H. erato to study phenotypic variation in the resulting F 2 generation. Using measurements of blue colour from photographs, we find that iridescent structural colour is a quantitative trait controlled by multiple genes, with strong evidence for loci on the Z sex chromosome. Iridescence is not linked to the Mendelian colour pattern locus that also segregates in these crosses (controlled by the gene cortex ). Small-angle X-ray scattering data show that spacing between longitudinal ridges on the scales, which affects the intensity of the blue reflectance, also varies quantitatively in F 2 crosses.

scholarly journals PREDICTION OF PHENOTYPIC AND GENOTYPIC VALUES BY BLUP/GWS AND NEURAL NETWORKS

2018 ◽  
Vol 31 (3) ◽  
pp. 532-540 ◽  
Author(s):  
ALISSON ESDRAS COUTINHO ◽  
DIOGO GONÇALVES NEDER ◽  
MAIRYKON COÊLHO DA SILVA ◽  
ELIANE CRISTINA ARCELINO ◽  
SILVAN GOMES DE BRITO ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Breeding Cycle ◽  
Prediction Methods ◽  
Best Linear Unbiased Predictor ◽  
Entire Genome ◽  
Genomic Breeding ◽  
Breeding Values ◽  
Genome Wide ◽  
Best Linear Unbiased

ABSTRACT Genome-wide selection (GWS) uses simultaneously the effect of the thousands markers covering the entire genome to predict genomic breeding values for individuals under selection. The possible benefits of GWS are the reduction of the breeding cycle, increase in gains per unit of time, and decrease of costs. However, the success of the GWS is dependent on the choice of the method to predict the effects of markers. Thus, the objective of this work was to predict genomic breeding values (GEBV) through artificial neural networks (ANN), based on the estimation of the effect of the markers, compared to the Ridge Regression-Best Linear Unbiased Predictor/Genome Wide Selection (RR-BLUP/GWS). Simulations were performed by software R to provide correlations concerning ANN and RR-BLUP/GWS. The prediction methods were evaluated using correlations between phenotypic and genotypic values and predicted GEBV. The results showed the superiority of the ANN in predicting GEBV in simulations with higher and lower marker densities, with higher levels of linkage disequilibrium and heritability.

scholarly journals Applying the Spatial EBLUP to Place-Based Policing. Simulation Study and Application to Confidence in Police Work

2020 ◽  
Vol 13 (4) ◽  
pp. 901-924
Author(s):  
David Buil-Gil ◽  
Angelo Moretti ◽  
Natalie Shlomo ◽  
Juanjo Medina
Keyword(s):  
Spatial Autocorrelation ◽  
Random Effects ◽  
Simulation Study ◽  
Small Area ◽  
Police Work ◽  
Best Linear Unbiased Predictor ◽  
Spatial Random Effects ◽  
Area Estimation ◽  
Best Linear Unbiased ◽  
Estimation Models

Abstract There is growing need for reliable survey-based small area estimates of crime and confidence in police work to design and evaluate place-based policing strategies. Crime and confidence in policing are geographically aggregated and police resources can be targeted to areas with the most problems. High levels of spatial autocorrelation in these variables allow for using spatial random effects to improve small area estimation models and estimates’ reliability. This article introduces the Spatial Empirical Best Linear Unbiased Predictor (SEBLUP), which borrows strength from neighboring areas, to place-based policing. It assesses the SEBLUP under different scenarios of number of areas and levels of spatial autocorrelation and provides an application to confidence in policing in London. The SEBLUP should be applied for place-based policing strategies when the variable’s spatial autocorrelation is medium/high, and the number of areas is large. Confidence in policing is higher in Central and West London and lower in Eastern neighborhoods.

Sign in / Sign up

Export Citation Format

Share Document