ArticleBMC plant biology2022
Association mapping for protein, total soluble sugars, starch, amylose and chlorophyll content in rice.
Article in BMC plant biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 25 citations in OpenAlex.
- Article
- Pyramiding QTLs for durable sheath blight resistance in the popular rice variety 'Maudamani'.Scientific reports · 2026Article
- Mapping and identification of QTLs for low light tolerance traits in grapevine.BMC plant biology · 2025Article
- From Gene to Plate: Molecular Insights into and Health Implications of Rice (International journal of molecular sciences · 2025Review
- Mapping Genomic Regions for Grain Protein Content and Quality Traits in Milled Rice (Plants (Basel, Switzerland) · 2025Article
- Influence of Exogenous Melatonin on the Physiological Traits ofPlants (Basel, Switzerland) · 2025Article
- Study on the rooting promotion of chrysanthemum cuttings byFrontiers in plant science · 2025Article
- Fantastic genes: where and how to find them? Exploiting rice genetic resources for the improvement of yield, tolerance, and resistance to a wide array of stresses in rice.Functional & integrative genomics · 2023Review
- Transfer of Stress Resilient QTLs and Panicle Traits into the Rice Variety, Reeta through Classical and Marker-Assisted Breeding Approaches.International journal of molecular sciences · 2023Article
- Mapping the Genomic Regions Controlling Germination Rate and Early Seedling Growth Parameters in Rice.Genes · 2023Article
- Molecular Breeding for Incorporation of Submergence Tolerance and Durable Bacterial Blight Resistance into the Popular Rice Variety 'Ranidhan'.Biomolecules · 2023Article
- LcNAC72-LcDREB1 Regulatory Module Mediates Low-Temperature Stress Response by Enhancing ROS Scavenging Capacity in Lonicera caerulea.Physiologia plantarumArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundProtein, starch, amylose and total soluble sugars are basic metabolites of seed that influence the eating, cooking and nutritional qualities of rice. Chlorophyll is responsible for the absorption and utilization of the light energy influencing photosynthetic efficiency in rice plant. Mapping of these traits are very important for detection of more number of robust markers for improvement of these traits through molecular breeding approaches.
resultsA representative panel population was developed by including 120 germplasm lines from the initial shortlisted 274 lines for mapping of the six biochemical traits using 136 microsatellite markers through association mapping. A wide genetic variation was detected for the traits, total protein, starch, amylose, total soluble sugars, chlorophyll a, and chlorophyll b content in the population. Specific allele frequency, gene diversity, informative markers and other diversity parameters obtained from the population indicated the effectiveness of utilization of the population and markers for mapping of these traits. The fixation indices values estimated from the population indicated the existence of linkage disequilibrium for the six traits. The population genetic structure at K = 3 showed correspondence with majority of the members in each group for the six traits. The reported QTL, qProt1, qPC6.2, and qPC8.2 for protein content; qTSS8.1 for total soluble sugar; qAC1.2 for amylose content; qCH2 and qSLCHH for chlorophyll a (Chl. a) while qChl5D for chlorophyll b (Chl. b) were validated in this population. The QTL controlling total protein content qPC1.2; qTSS7.1, qTSS8.2 and qTSS12.1 for total soluble sugars; qSC2.1, qSC2.2, qSC6.1 and qSC11.1 for starch content; qAC11.1, qAC11.2 and qAC11.3 for amylose content; qChla8.1 for Chl. a content and qChlb7.1 and qChlb8.1 for Chl. b identified by both Generalized Linear Model and Mixed Linear Model were detected as novel QTL. The chromosomal regions on chromosome 8 at 234 cM for grain protein content and total soluble sugars and at 363 cM for Chl. a and Chl. b along with the position at 48 cM on chromosome 11 for starch and amylose content are genetic hot spots for these traits.
conclusionThe validated, co-localized and the novel QTL detected in this study will be useful for improvement of protein, starch, amylose, total soluble sugars and chlorophyll content in rice.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.