scholarly journals MULTIVARIATE ANALYSIS OF 31 PHENOTYPIC TRAITS AMONG MAJOR PARENTAL LINES OF SUGARCANE BREEDING PROGRAMS IN CHINA

2020 ◽  
Vol 31 (3) ◽  
Keyword(s):  
Multivariate Analysis ◽  
Phenotypic Traits ◽  
Breeding Programs ◽  
Sugarcane Breeding ◽  
Parental Lines

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 Phenotypic diversity of horse breeds used in sports activities, employing multivariate analysis

2021 ◽  
Vol 19 (1) ◽  
pp. e0401
Author(s):  
Marcos P. G. Rezende ◽  
Julio C. Souza ◽  
Carlos H. M. Malhado ◽  
Paulo L. S. Carneiro ◽  
Johnny I. M. Araujo ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Principal Components ◽  
Phenotypic Diversity ◽  
The Body ◽  
Breeding Programs ◽  
Mato Grosso ◽  
Canonical Variables ◽  
Horse Breeding ◽  
Quarter Horse ◽  
Euclidean Distances

Aim of study: Sports involving horses have notable financial importance. Breeds are evaluated to find the best-suited ones for a specific sport category. Phenotypic diversity using biometric markers was evaluated for Quarter Horse (QH), Arabic (AR), English Thoroughbred (ET), and Brazilian Equestrian (BE) horse breeds.Area of study: Mato Grosso do Sul-Brazil.Material and methods: Lengths, widths, and circumference measures of 268 horses were collected. These measures were used to estimate conformation indexes. The size-free canonical discriminant analysis was used to remove the size effect on the animal's shape. The similarity among breeds (by sex) was evaluated employing multivariate analysis (canonical analysis, MANOVA, principal components, Euclidean distances, and grouping through complete linkage), considering all linear measures and conformation indexes (included in the analysis of principal components).Main results: Four canonical variables (CANs), each one representing an equation to interpret the morpho-functionality of breeds “sustentation”, “structure”, “frame”, and “equilibrium”, were retained. The breeds presented differences when the CANs were simultaneously considered. Differences mainly were the size and the thickness of the body as well as the ability of the animal to move. ET, QH, and BE demonstrate a well-defined biometric profile. These three breeds clustered separately from AR breed.Research highlights: Canonical variables allow to verify the functional aptitudes since the responses were close to conformation indices commonly used as horse skill estimators. The implementation of these variables as selection criteria in horse breeding programs require further studies in larger populations of horses for a confirmation of the present results.

scholarly journals Use of Highly Discriminating Morphological Characters and Isozymes in the Study of Spanish Chestnut Cultivars

2006 ◽  
Vol 131 (6) ◽  
pp. 770-779 ◽  
Author(s):  
Santiago Pereira-Lorenzo ◽  
María Belén Díaz-Hernández ◽  
Ana María Ramos-Cabrer
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Multivariate Analysis ◽  
Castanea Sativa ◽  
Principal Component ◽  
Market Value ◽  
Morphological Characters ◽  
Minor Importance ◽  
Breeding Programs ◽  
And Cluster Analysis

Morphological characters (six traits) and isozymes (four systems, five loci) were used to discriminate between Spanish chestnut cultivars (Castanea sativa Mill.) from the Iberian Peninsula. A total of 701 accessions (representing 168 local cultivars) were analyzed from collections made between 1989 and 2003 in the main chestnut growing areas: 31 were from Andalucía (12 cultivars), 293 from Asturias (65 cultivars), 25 from Castilla-León (nine cultivars), four from Extremadura (two cultivars) and 348 from Galicia (80 cultivars). Data were synthesized using multivariate analysis, principal component analysis, and cluster analysis. A total of 152 Spanish cultivars were verified: 58 cultivars of major importance and 94 of minor importance, of which 18 had high intracultivar variation. Thirty-seven cultivars were clustered into 14 synonymous groups. Six of these were from Galicia, one from Castilla-León (El Bierzo), four from Asturias, one from Asturias and Castilla-León (El Bierzo), and two from Asturias, Castilla-León (El Bierzo), and Galicia. The chestnut cultivars from Galicia and Asturias were undifferentiated in genetic terms, indicating that they are not genetically isolated. Overall, chestnut cultivars from southern Spain showed the least variation. Many (58%) of Spanish cultivars produced more than 100 nuts/kg; removing this low market-value character will be a high priority. The data obtained will be of use in chestnut breeding programs in Spain and elsewhere.

scholarly journals SSR Marker-Assisted Management of Parental Germplasm in Sugarcane (Saccharum spp. hybrids) Breeding Programs

Agronomy ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 449 ◽  
Author(s):  
Jiantao Wu ◽  
Qinnan Wang ◽  
Jing Xie ◽  
Yong-Bao Pan ◽  
Feng Zhou ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Capillary Electrophoresis ◽  
Population Structure ◽  
Ssr Markers ◽  
High Performance ◽  
Breeding Programs ◽  
Saccharum Spp ◽  
Parental Lines ◽  
Assisted Management ◽  
High Performance Capillary Electrophoresis

Sugarcane (Saccharum spp. hybrids) is an important sugar and bioenergy crop with a high aneuploidy, complex genomes and extreme heterozygosity. A good understanding of genetic diversity and population structure among sugarcane parental lines is a prerequisite for sugarcane improvement through breeding. In order to understand genetic characteristics of parental lines used in sugarcane breeding programs in China, 150 of the most popular accessions were analyzed with 21 fluorescence-labeled simple sequence repeats (SSR) markers and high-performance capillary electrophoresis (HPCE). A total of 226 SSR alleles of high-resolution capacity were identified. Among the series obtained from different origins, the YC-series, which contained eight unique alleles, had the highest genetic diversity. Based on the population structure analysis, the principal coordinate analysis (PCoA) and phylogenetic analysis, the 150 accessions were clustered into two distinct sub-populations (Pop1 and Pop2). Pop1 contained the majority of clones introduced to China (including 28/29 CP-series accessions) while accessions native to China clustered in Pop2. The analysis of molecular variance (AMOVA), fixation index (Fst) value and gene flow (Nm) value all indicated the very low genetic differentiation between the two groups. This study illustrated that fluorescence-labeled SSR markers combined with high-performance capillary electrophoresis (HPCE) could be a very useful tool for genotyping of the polyploidy sugarcane. The results provided valuable information for sugarcane breeders to better manage the parental germplasm, choose the best parents to cross, and produce the best progeny to evaluate and select for new cultivar(s).

A multivariate analysis of variation in genome size and endoreduplication in angiosperms reveals strong phylogenetic signal and association with phenotypic traits

2012 ◽  
Vol 196 (4) ◽  
pp. 1240-1250 ◽  
Author(s):  
Jillian D. Bainard ◽  
Luke D. Bainard ◽  
Thomas A. Henry ◽  
Aron J. Fazekas ◽  
Steven G. Newmaster
Keyword(s):  
Multivariate Analysis ◽  
Genome Size ◽  
Phylogenetic Signal ◽  
Phenotypic Traits ◽  
Analysis Of Variation

Genetic Relationship between Purple and Wine Testa Color in Peanut1

2001 ◽  
Vol 28 (1) ◽  
pp. 19-20 ◽  
Author(s):  
W. D. Branch
Keyword(s):  
Arachis Hypogaea ◽  
Genetic Relationship ◽  
Quality Trait ◽  
Market Quality ◽  
Breeding Programs ◽  
Arachis Hypogaea L ◽  
Parental Lines ◽  
The Relationship ◽  
Testa Color ◽  
Color Gene

Abstract A better understanding of the genetic relationship among different testa colors is needed in peanut (Arachis hypogaea L.) breeding programs. Numerous genes are involved in this important U.S. market quality trait. However, the relationship among some of these genes is not yet known. The objective of this study was to determine the interaction among the three genes (P, w1, and w2) controlling purple and wine testa color. No maternal or cytoplasmic differences were found among three reciprocal purple x wine testcrosses. The F1, F2, and F3 segregation results suggest that purple testa color of PI 331334 differs from that of wine testa color parental lines (PI 264549, Wine-Frr 1 and Wine-Frr 2) by only two genes. These findings illustrate that the dominant purple testa color gene (P) is independent from at least one of the two recessive wine genes (w1 w1 or w2w2).

scholarly journals Prediction of the importance of auxiliary traits using computational intelligence and machine learning: A simulation study

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0257213
Author(s):  
Antônio Carlos da Silva Júnior ◽  
Michele Jorge da Silva ◽  
Cosme Damião Cruz ◽  
Isabela de Castro Sant’Anna ◽  
Gabi Nunes Silva ◽  
...  
Keyword(s):  
Machine Learning ◽  
Plant Breeding ◽  
Computational Intelligence ◽  
Coefficient Of Determination ◽  
Phenotypic Traits ◽  
Linkage Groups ◽  
Breeding Programs ◽  
A Genome ◽  
Heritability Estimates ◽  
Differential Action

The present study evaluated the importance of auxiliary traits of a principal trait based on phenotypic information and previously known genetic structure using computational intelligence and machine learning to develop predictive tools for plant breeding. Data of an F2 population represented by 500 individuals, obtained from a cross between contrasting homozygous parents, were simulated. Phenotypic traits were simulated based on previously established means and heritability estimates (30%, 50%, and 80%); traits were distributed in a genome with 10 linkage groups, considering two alleles per marker. Four different scenarios were considered. For the principal trait, heritability was 50%, and 40 control loci were distributed in five linkage groups. Another phenotypic control trait with the same complexity as the principal trait but without any genetic relationship with it and without pleiotropy or a factorial link between the control loci for both traits was simulated. These traits shared a large number of control loci with the principal trait, but could be distinguished by the differential action of the environment on them, as reflected in heritability estimates (30%, 50%, and 80%). The coefficient of determination were considered to evaluate the proposed methodologies. Multiple regression, computational intelligence, and machine learning were used to predict the importance of the tested traits. Computational intelligence and machine learning were superior in extracting nonlinear information from model inputs and quantifying the relative contributions of phenotypic traits. The R2 values ranged from 44.0% - 83.0% and 79.0% - 94.0%, for computational intelligence and machine learning, respectively. In conclusion, the relative contributions of auxiliary traits in different scenarios in plant breeding programs can be efficiently predicted using computational intelligence and machine learning.

scholarly journals Application of Pedimap — a pedigree visualization tool — to facilitate the decisioning of rice breeding in Sri Lanka

2020 ◽  
Author(s):  
P.G.R.G. Rathnayake ◽  
S.M. Sahibdeen ◽  
U.A.K.S. Udawela ◽  
C.K. Weebadde ◽  
W.M.W. Weerakoon ◽  
...  
Keyword(s):  
Sri Lanka ◽  
Molecular Data ◽  
High Yield ◽  
Phenotypic Traits ◽  
Visualization Tool ◽  
Rice Breeding ◽  
Rice Varieties ◽  
Breeding Programs ◽  
Improved Varieties ◽  
Genomic Characterization

ABSTRACTThe development of rice cultivars with desirable traits is essential. The decision-making is a crucial step in rice breeding programs. The breeders can make efficient and pragmatic decisions if an organized pedigree visualization platform is available for the material of the rice breeding germplasm. The staple food in Sri Lanka is rice, and there is a great demand for improved varieties with high yield and other promising traits. In the present study, the available data of all the rice varieties released by Rice Research and Development Institute, Sri Lanka, and the related landraces and genotypes were arranged in Pedimap, a pedigree visualization tool. Pedimap can showcase pedigree relationships, phenotypic, and molecular data. The Identity by Descent (IBD) probabilities were calculated using FlexQTL software and included in the Pedimap database. The parentage selection based on the variations of phenotypic traits, selection of marker alleles for molecular breeding, and detection of the founders of genetic effects can be swiftly conducted using Pedimap. However, the power of harnessing the value of Pedimap for making breeding decisions relies on the availability of data for the traits, markers, and genomic sequences. Thus, it is imperative to characterize the breeding germplasms using standard phenomic and genomic characterization procedures before organized into Pedimap. Thereby, the worldwide breeding programs can benefit from each other to produce improved varieties to meet global challenges.

scholarly journals Direct selection for phenotypic traits in carrot genotypes

2019 ◽  
Vol 37 (3) ◽  
pp. 354-358
Author(s):  
Agnaldo DF de Carvalho ◽  
Giovani O da Silva ◽  
Gabriel E Pereira
Keyword(s):  
Agronomic Traits ◽  
Block Design ◽  
Direct Selection ◽  
Phenotypic Traits ◽  
Crop Breeding ◽  
Breeding Programs ◽  
Randomized Block Design ◽  
Increase Productivity ◽  
Abstract Selection ◽  
Selection Of

ABSTRACT Selection of more productive carrot genotypes is fundamental for crop breeding programs aiming to increase productivity and reduce cost production. Thus, the aim of this work was to evaluate gains from direct selection and to measure its effects on other agronomic traits of interest in carrots. Thirty six carrot genotypes were evaluated in two experiments: the first, sown in the second half of November 2016 and the second one in the first week of March 2017. The experimental plots covered a useful area of 1.5 m2, in transversal rows and 0.10-m double spacing between single rows x 0.20-m between double rows in a randomized block design with 3 replicates. At 90 days, the incidence of leaf blight was evaluated using a note scale and 100 days after sowing, roots were harvested measuring the number and mass of total, commercial and non-commercial roots of each plot. The direct selection of commercial root mass allowed to estimate indirect and expressive gains for most evaluated traits, allowing to select seven genotypes (populations 758, 751, 737, 736, 735, 744 and 742) which can be released as cultivar or for the formation of a broader genetic-based population.

scholarly journals A Modified Roger’s Distance Algorithm for Mixed Quantitative–Qualitative Phenotypes to Establish a Core Collection for Taiwanese Vegetable Soybeans

2021 ◽  
Vol 11 ◽  
Author(s):  
Chung-Feng Kao ◽  
Shan-Syue He ◽  
Chang-Sheng Wang ◽  
Zheng-Yuan Lai ◽  
Da-Gin Lin ◽  
...  
Keyword(s):  
Core Collection ◽  
Dietary Habits ◽  
Phenotypic Traits ◽  
Variable Rate ◽  
Vegetable Soybean ◽  
Breeding Programs ◽  
The Core ◽  
Entire Collection ◽  
Redundant Accessions ◽  
High Diversity

Vegetable soybeans [Glycine max (L.) Merr.] have characteristics of larger seeds, less beany flavor, tender texture, and green-colored pods and seeds. Rich in nutrients, vegetable soybeans are conducive to preventing neurological disease. Due to the change of dietary habits and increasing health awareness, the demand for vegetable soybeans has increased. To conserve vegetable soybean germplasms in Taiwan, we built a core collection of vegetable soybeans, with minimum accessions, minimum redundancy, and maximum representation. Initially, a total of 213 vegetable soybean germplasms and 29 morphological traits were used to construct the core collection. After redundant accessions were removed, 200 accessions were retained as the entire collection, which was grouped into nine clusters. Here, we developed a modified Roger’s distance for mixed quantitative–qualitative phenotypes to select 30 accessions (denoted as the core collection) that had a maximum pairwise genetic distance. No significant differences were observed in all phenotypic traits (p-values > 0.05) between the entire and the core collections, except plant height. Compared to the entire collection, we found that most traits retained diversities, but seven traits were slightly lost (ranged from 2 to 9%) in the core collection. The core collection demonstrated a small percentage of significant mean difference (3.45%) and a large coincidence rate (97.70%), indicating representativeness of the entire collection. Furthermore, large values in variable rate (149.80%) and coverage (92.5%) were in line with high diversity retained in the core collection. The results suggested that phenotype-based core collection can retain diversity and genetic variability of vegetable soybeans, providing a basis for further research and breeding programs.

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