scholarly journals Combined linkage and association mapping of putative QTLs controlling black tea quality and drought tolerance traits

2018 ◽  
Author(s):  
Robert. K. Koech ◽  
Richard Mose ◽  
Samson M. Kamunya ◽  
Zeno Apostolides
Keyword(s):  
Association Mapping ◽  
Carbon Fixation ◽  
Black Tea ◽  
Interval Mapping ◽  
Phenotypic Traits ◽  
Phenotypic Variance ◽  
Quality Traits ◽  
Putative Qtls ◽  
Tea Quality ◽  
Population Structure Analysis

AbstractThe advancements in genotyping have opened new approaches for identification and precise mapping of Quantitative Trait Loci (QTLs) in plants, particularly by combining linkage and association mapping (AM) analysis. In this study, a combination of linkage and the AM approach was used to identify and authenticate putative QTLs associated with black tea quality traits and percent relative water content (%RWC). The population structure analysis clustered two parents and their respective 261 F1 progenies from the two reciprocal crosses into two clusters with 141 tea accessions in cluster one and 122 tea accessions in cluster two. The two clusters were of mixed origin with tea accessions in population TRFK St. 504 clustering together with tea accessions in population TRFK St. 524. A total of 71 putative QTLs linked to black tea quality traits and %RWC were detected in interval mapping (IM) method and were used as cofactors in multiple QTL model (MQM) mapping where 46 putative QTLs were detected. The phenotypic variance for each QTL ranged from 2.8–23.3% in IM and 4.1–23% in MQM mapping. Using Q-model and Q+K-model in AM, a total of 49 DArTseq markers were associated with 16 phenotypic traits. Significant marker-trait association in AM were similar to those obtained in IM, and MQM mapping except for six more putative QTLs detected in AM which are involved in biosynthesis of secondary metabolites, carbon fixation and abiotic stress. The combined linkage and AM approach appears to have great potential to improve the selection of desirable traits in tea breeding.

scholarly journals Combined linkage and association mapping of putative QTLs controlling black tea quality and drought tolerance traits

Euphytica ◽  
2019 ◽  
Vol 215 (10) ◽  
Author(s):  
Robert. K. Koech ◽  
Richard Mose ◽  
Samson M. Kamunya ◽  
Zeno Apostolides
Keyword(s):  
Drought Tolerance ◽  
Association Mapping ◽  
Black Tea ◽  
Putative Qtls ◽  
Tea Quality

Identification of novel QTL for black tea quality traits and drought tolerance in tea plants (Camellia sinensis)

2018 ◽  
Vol 14 (1) ◽  
Author(s):  
Robert K. Koech ◽  
Pelly M. Malebe ◽  
Christopher Nyarukowa ◽  
Richard Mose ◽  
Samson M. Kamunya ◽  
...  
Keyword(s):  
Drought Tolerance ◽  
Camellia Sinensis ◽  
Black Tea ◽  
Quality Traits ◽  
Tea Quality ◽  
Tea Plants

Candidate gene-based association genetics analysis of herbage quality traits in perennial ryegrass (Lolium perenne L.)

2013 ◽  
Vol 64 (3) ◽  
pp. 244 ◽  
Author(s):  
L. W. Pembleton ◽  
J. Wang ◽  
N. O. I. Cogan ◽  
J. E. Pryce ◽  
G. Ye ◽  
...  
Keyword(s):  
Association Mapping ◽  
Candidate Gene ◽  
Perennial Ryegrass ◽  
Association Studies ◽  
Phenotypic Variance ◽  
Genome Wide Association Studies ◽  
Quality Traits ◽  
Near Infrared Reflectance ◽  
Genome Wide ◽  
Herbage Quality

Due to the complex genetic architecture of perennial ryegrass, based on an obligate outbreeding reproductive habit, association-mapping approaches to genetic dissection offer the potential for effective identification of genetic marker–trait linkages. Associations with genes for agronomic characters, such as components of herbage nutritive quality, may then be utilised for accelerated cultivar improvement using advanced molecular breeding practices. The objective of the present study was to evaluate the presence of such associations for a broad range of candidate genes involved in pathways of cell wall biosynthesis and carbohydrate metabolism. An association-mapping panel composed from a broad range of non-domesticated and varietal sources was assembled and assessed for genome-wide sequence polymorphism. Removal of significant population structure obtained a diverse meta-population (220 genotypes) suitable for association studies. The meta-population was established with replication as a spaced-plant field trial. All plants were genotyped with a cohort of candidate gene-derived single nucleotide polymorphism (SNP) markers. Herbage samples were harvested at both vegetative and reproductive stages and were measured for a range of herbage quality traits using near infrared reflectance spectroscopy. Significant associations were identified for ~50% of the genes, accounting for small but significant components of phenotypic variance. The identities of genes with associated SNPs were largely consistent with detailed knowledge of ryegrass biology, and they are interpreted in terms of known biochemical and physiological processes. Magnitudes of effect of observed marker–trait gene association were small, indicating that future activities should focus on genome-wide association studies in order to identify the majority of causal mutations for complex traits such as forage quality.

scholarly journals Genome-enabled prediction models for black tea (Camellia sisnesnsis) quality and drought tolerance traits

2019 ◽  
Author(s):  
Robert. K. Koech ◽  
Pelly M. Malebe ◽  
Christopher Nyarukowa ◽  
Richard Mose ◽  
Samson M. Kamunya ◽  
...  
Keyword(s):  
Drought Tolerance ◽  
Genomic Selection ◽  
Prediction Models ◽  
Black Tea ◽  
Future Application ◽  
Phenotypic Traits ◽  
List Type ◽  
Putative Qtls ◽  
Validation Population ◽  
Prediction Approach

SummaryGenomic selection in tea (Camellia sinensis) breeding has the potential to accelerate efficiency of choosing parents with desirable traits at the seedling stage.The study evaluated different genome-enabled prediction models for black tea quality and drought tolerance traits in discovery and validation populations. The discovery population comprised of two segregating tea populations (TRFK St. 504 and TRFK St. 524) with 255 F1 progenies and 56 individual tea cultivars in validation population genotyped using 1 421 DArTseq markers.Two-fold cross-validation was used for training the prediction models in discovery population, and the best prediction models were consequently, fitted to the validation population.Of all the four based prediction approaches, putative QTLs (Quantitative Trait Loci) + annotated proteins + KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathway-based prediction approach, showed robustness and usefulness in prediction of phenotypes.Extreme Learning Machine model had better prediction ability for catechin, astringency, brightness, briskness, and colour based on putative QTLs + annotated proteins + KEGG pathway approach.The percent variables of importance of putatively annotated proteins and KEGG pathways were associated with the phenotypic traits. The findings has for the first time opened up a new avenue for future application of genomic selection in tea breeding.

scholarly journals Phenotypic and genetic variation of ultraviolet–visible-infrared spectral wavelengths of bovine meat

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giovanni Bittante ◽  
Simone Savoia ◽  
Alessio Cecchinato ◽  
Sara Pegolo ◽  
Andrea Albera
Keyword(s):  
Meat Quality ◽  
Genetic Improvement ◽  
Near Infrared ◽  
Infrared Region ◽  
Phenotypic Variance ◽  
Quality Traits ◽  
Meat Quality Traits ◽  
Infrared Spectral ◽  
Portable Spectrometers ◽  
Absorbance Spectra

AbstractSpectroscopic predictions can be used for the genetic improvement of meat quality traits in cattle. No information is however available on the genetics of meat absorbance spectra. This research investigated the phenotypic variation and the heritability of meat absorbance spectra at individual wavelengths in the ultraviolet–visible and near-infrared region (UV–Vis-NIR) obtained with portable spectrometers. Five spectra per instrument were taken on the ribeye surface of 1185 Piemontese young bulls from 93 farms (13,182 Herd-Book pedigree relatives). Linear animal model analyses of 1481 single-wavelengths from UV–Vis-NIRS and 125 from Micro-NIRS were carried out separately. In the overlapping regions, the proportions of phenotypic variance explained by batch/date of slaughter (14 ± 6% and 17 ± 7%,), rearing farm (6 ± 2% and 5 ± 3%), and the residual variances (72 ± 10% and 72 ± 5%) were similar for the UV–Vis-NIRS and Micro-NIRS, but additive genetics (7 ± 2% and 4 ± 2%) and heritability (8.3 ± 2.3% vs 5.1 ± 0.6%) were greater with the Micro-NIRS. Heritability was much greater for the visible fraction (25.2 ± 11.4%), especially the violet, blue and green colors, than for the NIR fraction (5.0 ± 8.0%). These results allow a better understanding of the possibility of using the absorbance of visible and infrared wavelengths correlated with meat quality traits for the genetic improvement in beef cattle.

Assessing black tea quality based on visible–near infrared spectra and kernel-based methods

2021 ◽  
Vol 98 ◽  
pp. 103810
Author(s):  
Guangxin Ren ◽  
Ying Liu ◽  
Jingming Ning ◽  
Zhengzhu Zhang
Keyword(s):  
Infrared Spectra ◽  
Near Infrared ◽  
Black Tea ◽  
Near Infrared Spectra ◽  
Tea Quality

scholarly journals Determination of the Chemical Composition of Tea by Chromatographic Methods: A Review

2015 ◽  
Vol 4 (3) ◽  
pp. 56 ◽  
Author(s):  
Alexandr Ya Yashin ◽  
Boris V. Nemzer ◽  
Emilie Combet ◽  
Yakov I. Yashin
Keyword(s):  
Chemical Composition ◽  
Volatile Compounds ◽  
Black Tea ◽  
Storage Conditions ◽  
Organoleptic Evaluation ◽  
Chromatographic Methods ◽  
Tea Quality ◽  
Processing And Storage ◽  
And Storage

<p>Despite the fact that mankind has been drinking tea for more than 5000 years, its chemical composition has been studied only in recent decades. These studies are primarily carried out using chromatographic methods. This review summarizes the latest information regarding the chemical composition of different tea grades by different chromatographic methods, which has not previously been reviewed in the same scope. Over the last 40 years, the qualitative and quantitative analyses of high volatile compounds were determined by GC and GC/MS. The main components responsible for aroma of green and black tea were revealed, and the low volatile compounds basically were determined by HPLC and LC/MS methods. Most studies focusing on the determination of catechins and caffeine in various teas (green, oolong, black and pu-erh) involved HPLC analysis.</p> <p>Knowledge of tea chemical composition helps in assessing its quality on the one hand, and helps to monitor and manage its growing, processing, and storage conditions on the other. In particular, this knowledge has enabled to establish the relationships between the chemical composition of tea and its properties by identifying the tea constituents which determine its aroma and taste. Therefore, assessment of tea quality does not only rely on subjective organoleptic evaluation, but also on objective physical and chemical methods, with extra determination of tea components most beneficial to human health. With this knowledge, the nutritional value of tea may be increased, and tea quality improved by providing via optimization of the growing, processing, and storage conditions.</p>

A Novel Technique of Black Tea Quality Prediction Using Electronic Tongue Signals

2014 ◽  
Vol 63 (10) ◽  
pp. 2472-2479 ◽  
Author(s):  
Pradip Saha ◽  
Santanu Ghorai ◽  
Bipan Tudu ◽  
Rajib Bandyopadhyay ◽  
Nabarun Bhattacharyya
Keyword(s):  
Electronic Tongue ◽  
Black Tea ◽  
Quality Prediction ◽  
Novel Technique ◽  
Tea Quality

scholarly journals Identification of quantitative trait loci for leaf traits in rice

Genetika ◽  
2016 ◽  
Vol 48 (2) ◽  
pp. 643-652 ◽  
Author(s):  
Baoyan Jia ◽  
Xinhua Zhao ◽  
Yang Qin ◽  
Muhammad Irfan ◽  
Tae-Heon Kim ◽  
...  
Keyword(s):  
Recombinant Inbred Lines ◽  
Leaf Traits ◽  
Rice Cultivar ◽  
Interval Mapping ◽  
Mapping Method ◽  
Japonica Rice ◽  
Phenotypic Variance ◽  
Simple Sequence ◽  
Variance Explained ◽  
Map Distance

A recombinant inbred lines (RILs) population of 90 lines were developed from a subspecies cross between an indica type cultivar, ?Cheongcheong?, and a japonica rice cultivar, ?Nagdong? was evaluated for leaf traits in 2009. A genetic linkage map consisting of 154 simple sequence repeat (SSR) markers was constructed, covering 1973.6 cM of 12 chromosomes with an average map distance of 13.9 cM between markers. By composite interval mapping method a total of 19 QTLs were identified for the leaf traits on 5 chromosomes (Chr.1, Chr.3, Chr.6, Chr.8 and Chr.11). The percentage of phenotypic variance explained by each QTL varied from 8.1% to 29.4%. Five pleiotropic effects loci were identified on chromosomes 1,6.

scholarly journals Dissection of the genetic basis of oil content in Chinese peanut cultivars through association mapping

2020 ◽  
Author(s):  
Nian Liu ◽  
Li Huang ◽  
Weigang Chen ◽  
Bei Wu ◽  
Manish K. Pandey ◽  
...  
Keyword(s):  
Association Mapping ◽  
Ssr Markers ◽  
Oil Content ◽  
Genetic Basis ◽  
Principal Component ◽  
Primary Sources ◽  
Phenotypic Variance ◽  
Mapping Panel ◽  
Stable Association ◽  
Faster Development

Abstract Background: Peanut is one of the primary sources for vegetable oil worldwide, and enhancing oil content is the main objective in several peanut breeding programs of the world. Tightly linked markers are required for faster development of high oil content peanut varieties through genomics-assisted breeding (GAB), and association mapping is one of the promising approaches for discovery of such associated markers. Results: An association mapping panel consisting of 292 peanut varieties extensively distributed in China was phenotyped for oil content and genotyped with 583 polymorphic SSR markers. These markers amplified 3663 alleles with an average of 6.28 alleles per locus. The structure, phylogenetic relationship, and principal component analysis (PCA) indicated two subgroups majorly differentiating based on geographic regions. Genome-wide association analysis identified 12 associated markers including one (AGGS1014_2) highly stable association controlling up to 9.94% phenotypic variance explained (PVE) across multiple environments. Interestingly, the frequency of the favorable alleles for 12 associated markers showed a geographic difference. Two associated markers (AGGS1014_2 and AHGS0798) with 6.90-9.94% PVE were verified to enhance oil content in an independent RIL population and also indicated selection during the breeding program. Conclusion: This study provided insights into the genetic basis of oil content in peanut and verified highly associated two SSR markers to facilitate marker-assisted selection for developing high-oil content breeding peanut varieties.

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