Evidence map›Paper›PMID 22227928›Full record

ArticleJournal of genetics2011

Wheat kernel dimensions: how do they contribute to kernel weight at an individual QTL level?

Fa Cui, Anming Ding, Jun Li, Chunhua Zhao, Xingfeng Li, Deshun Feng, Xiuqin Wang, Lin Wang, Jurong Gao, Honggang Wang

Abstract read
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In one paragraph

Article in Journal of genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
4.1field-weighted citation impact, top 7% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 74 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Fine mapping of a major QTL, qKl-1BL controlling kernel length in common wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
  7. Review
  8. Review
  9. Fine mapping of KLW1 that conditions kernel weight mainly through regulating kernel length in wheat (Triticum aestivum L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023
    Article
  10. Article
  11. Article
  12. Article
  13. Quick mapping and characterization of a co-located kernel length and thousand-kernel weight-related QTL in wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. QTL detection for wheat kernel size and quality and the responses of these traits to low nitrogen stress.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2016
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Fa CuiState Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, Taian Subcenter of National Wheat Improvement Center, College of Agronomy, Shandong Agricultural University, Taian 271018, People's Republic of China.
Anming Ding
Jun Li
Chunhua Zhao
Xingfeng Li
Deshun Feng
Xiuqin Wang
Lin Wang
Jurong Gao
Honggang Wang
Shandong Agricultural University · CNState Key Laboratory of Crop BiologyNingbo Academy of Agricultural Sciences · CNShandong Academy of Agricultural Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kernel dimensions (KD) contribute greatly to thousand-kernel weight (TKW) in wheat. In the present study, quantitative trait loci (QTL) for TKW, kernel length (KL), kernel width (KW) and kernel diameter ratio (KDR) were detected by both conditional and unconditional QTL mapping methods. Two related F(8:9) recombinant inbred line (RIL) populations, comprising 485 and 229 lines, respectively, were used in this study, and the trait phenotypes were evaluated in four environments. Unconditional QTL mapping analysis detected 77 additive QTL for four traits in two populations. Of these, 24 QTL were verified in at least three trials, and five of them were major QTL, thus being of great value for marker assisted selection in breeding programmes. Conditional QTL mapping analysis, compared with unconditional QTL mapping analysis, resulted in reduction in the number of QTL for TKW due to the elimination of TKW variations caused by its conditional traits; based on which we first dissected genetic control system involved in the synthetic process between TKW and KD at an individual QTL level. Results indicated that, at the QTL level, KW had the strongest influence on TKW, followed by KL, and KDR had the lowest level contribution to TKW. In addition, the present study proved that it is not all-inclusive to determine genetic relationships of a pairwise QTL for two related/causal traits based on whether they were co-located. Thus, conditional QTL mapping method should be used to evaluate possible genetic relationships of two related/causal traits.

Indexed as

Quantitative Trait LociChromosome MappingChromosomes, PlantEnvironmentGenetic LinkageGenetic MarkersGenotypeInbreedingPhenotypeSeedsTriticumGenetic Markers

Identifiers

PMID22227928
OpenAlexW2092364066

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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.