ArticleBMC genetics2016
Dissection of the qTGW1.1 region into two tightly-linked minor QTLs having stable effects for grain weight in rice.
Article in BMC genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed.
- Article
- Dissection and Fine-Mapping of Two QTL Controlling Grain Size Linked in a 515.6-kb Region on Chromosome 10 of Rice.Plants (Basel, Switzerland) · 2024Article
- Dissecting the Genetic Basis of Yield Traits and Validation of a Novel Quantitative Trait Locus for Grain Width and Weight in Rice.Plants (Basel, Switzerland) · 2024Article
- Identification ofMolecular breeding : new strategies in plant improvement · 2024Article
- Gene based markers improve precision of genome-wide association studies and accuracy of genomic predictions in rice breeding.Heredity · 2023Article
- Identification, Fine Mapping and Application of Quantitative Trait Loci for Grain Shape Using Single-Segment Substitution Lines in Rice (Plants (Basel, Switzerland) · 2023Article
- Control of Grain Weight and Size in Rice (Oryza sativa L.) by OsPUB3 Encoding a U-Box E3 Ubiquitin Ligase.Rice (New York, N.Y.) · 2022Article
- Fine Mapping ofInternational journal of molecular sciences · 2022Article
- Identifying Quantitative Trait Loci for Thousand Grain Weight in Eggplant by Genome Re-Sequencing Analysis.Frontiers in genetics · 2022Article
- Control of Thousand-Grain Weight byInternational journal of molecular sciences · 2021Article
- Verification and dissection of one quantitative trait locus for grain size and weight on chromosome 1 in rice.Scientific reports · 2021Article
- Article
- Identification through fine mapping and verification using CRISPR/Cas9-targeted mutagenesis for a minor QTL controlling grain weight in rice.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
- Article
- Fine-mapping ofPeerJ · 2020Article
- A novel quantitative trait locus on chromosome A9 controlling oleic acid content in Brassica napus.Plant biotechnology journal · 2019Article
- Identification of a candidate gene underlying qKRN5b for kernel row number in Zea mays L.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2019Article
- Importance of the Interaction between Heading Date GenesInternational journal of molecular sciences · 2019Article
- Dissection of three quantitative trait loci for grain size on the long arm of chromosome 10 in rice (PeerJ · 2019Article
- Dissection and fine-mapping of two QTL for grain size linked in a 460-kb region on chromosome 1 of rice.Rice (New York, N.Y.) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMost agronomical traits of crop species are complex traits controlled by multiple genes and affected by environmental factors. While considerable efforts have been made to fine-map and clone major quantitative trait loci (QTLs) for yield-related traits in rice, it is not until recently that the attention has been paid to minor QTLs. Following previous dissection of QTLs for grain weight and grain size in a 12-Mb interval on the long arm of chromosome 1 in rice, this study targeted at one putative QTL region for a more precise mapping and for analyzing the genotype-by-environment interaction of minor QTLs.
resultsFour BC2F10 plants of the indica rice cross ZS97///ZS97//ZS97/MY46 were selected. They carried overlapped heterozygous segments that jointly covered the entire putative region for qTGW1.1 detected previously. Four sets of near isogenic lines (NILs) were developed from selfing progenies of the four plants. Each NIL set consisted of 32 ZS97 homozygous lines and 32 MY46 homozygous lines that differed in the corresponding heterozygous region. They were grown in two locations having distinct ecological conditions and measured for 1000-grain weight, grain length and grain width. Two QTLs were separated in an 835.2-kb interval flanked by DNA markers Wn28447 and RM11569. They both showed consistent effects across the two environments. The qTGW1.1a located within the 120.4-kb interval Wn28447 - RM11543 significantly affect all the three traits with the enhancing allele derived from ZS97, showing a stronger influence on grain weight than on grain length and width. The qTGW1.1b located in the 521.8-kb interval RM11554 - RM11569 significantly affect grain weight and length with the enhancing allele derived from MY46, having a stronger influence on grain length than on grain weight. Consistent performance of the two QTLs was confirmed in a validation experiment using five NIL-F2 populations segregated for either qTGW1.1a or qTGW1.1b.
conclusionSeparation of closely-linked QTLs having small effects is achievable in the absence of major-QTL segregation. Minor QTLs for complex traits could act consistently in diverse environments, offering the potential of pyramiding beneficial alleles of multiple minor QTLs through marker-assisted selection.
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.