MétaCan
Menu
Back to cohort
Record W2919920622

Genetic analysis of carotenoid biosynthesis in chickpea (Cicer arietinum L.) seeds

2018· dissertation· en· W2919920622 on OpenAlexaboutno aff
Mohammad Rezaei

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsnot available
Fundersnot available
KeywordsCarotenoidBiosynthesisBiologyHorticultureNull (SQL)BotanyBiotechnologyGeneGeneticsComputer scienceData mining
DOInot available

Abstract

fetched live from OpenAlex

Vitamin A deficiency is a worldwide problem especially in the third world countries. Improvement of carotenoid levels in the edible parts of the crops has been one of the major objectives of many plant breeding programs. Chickpea (Cicer arietinum L.) is an important source of carotenoids. The availability of diverse germplasm resources along with the availability of its genome sequence, makes chickpea an ideal object for studying carotenogenesis in pulses. The objectives of this research were: 1) to identify the genomic regions associated with carotenoid concentration in diverse chickpea accessions and in populations derived from biparental crosses, 2) to examine the effects of environment on carotenogenesis, 3) to examine the relationship between cotyledon colour and carotenoid concentration, and 4) to examine the expression patterns of the genes involved in carotenoid biosynthesis during seed development. A genotypic panel of 172 chickpea accessions was evaluated in 2015 and 2016 with one location per year in Saskatchewan, Canada. The effects of genotype and environment were significant on the concentration of each carotenoid component. The mean and range for the concentration of each component based on the average of two-years data are as follows: 10.14 and 3.5-28.2 µg g-1 for lutein, 0.37 and 0-3.04 µg g-1 for violaxanthin, 1.65 and 0.27-2.84 µg g-1 for zeaxanthin, 0.09 and 0-2.5 µg g-1 for β-carotene respectively.\nThe chickpea genotypic panel consisted of two major subpopulations, kabuli and desi groups, along with an admixture group. Genome-wide association analysis revealed that the genes in the primary steps of carotenoid biosynthesis and those involved in apo-carotenoid production had significant associations with carotenoid concentration in chickpea. Three F2 populations derived from crossing cultivars with green and yellow cotyledons were used to identify QTL associated with carotenoids. Five to eight QTLs responsible for different carotenoid components were identified in each population. In all three populations, the highest phenotypic variation explained by QTL was found for the β-carotene concentration. Cotyledon colour (CotCol) was mapped on linkage group 8 in each population. A positive and significant relationship between cotyledon colour and carotenoid concentration was identified in this experiment. The structure, genomic location, and copy number of 29 genes involved in carotenoid and isoprenoid pathways were retrieved in the chickpea genome. Two missense mutations were found in zeta carotene isomerase (ZISO2) in CDC Verano, a green cotyledon kabuli cultivar, which might explain the higher carotenoid concentration in this cultivar. The expression patterns of 19 genes from the carotenoid pathway were analyzed in five chickpea cultivars at different seed developmental stages. The highest expression level from all the genes was observed at eight and 16 days post-anthesis across the five cultivars. The highest carotenoid concentration and expression levels of the carotenoid genes were found in CDC Jade, a desi cultivar with green cotyledons. Based on gene expression analysis, the desaturation and isomerisation reactions positively affected the carotenoid concentration, while hydroxylation adversely affected the carotenoid concentration. The results from this research could help breeders to develop chickpea cultivars with improved carotenoid/provitamin A levels through molecular breeding.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.229
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicPhytase and its ApplicationsFrench-language works237,207