Evidence map›Paper›PMID 41461981›Full record

ReviewRice (New York, N.Y.)2025

Engineering non-coding DNA Elements in Rice: an Elegant Approach To fine-tune Agronomical Advantageous Traits.

Tilak Chandra, Sarika Jaiswal, Kutubuddin A Molla, Deependra Pratap Singh, Mir Asif Iquebal, Dinesh Kumar

Abstract readReview
In one paragraph

Review in Rice (New York, N.Y.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Review
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

6 authors.

Tilak ChandraDivision of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, 110012, India.
Sarika JaiswalDivision of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, 110012, India.
Kutubuddin A MollaCrop Improvement Division, ICAR-National Rice Research Institute, Cuttack, 753006, Odisha, India.
Deependra Pratap SinghDepartment of Biotechnology, Graphic Era (Deemed to be University), Dehradun, 248002, Uttarakhand, India.
Mir Asif IquebalDivision of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, 110012, India. ma.iquebal@icar.gov.in.
Dinesh KumarDivision of Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, 110012, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rice serves as a fundamental staple crop, supporting the dietary needs of nearly one-third of the global population. This critical role necessitates immediate and strategic efforts to develop multi-attribute genotypes to ensure sustainable food and nutritional security for the burgeoning population. The augmentation of rice production is not only vital for addressing immediate food demands but also crucial for fostering long-term sustainability, thereby supporting livelihoods and driving economic development. Achieving this transformation necessitates a holistic and systems-level understanding of the molecular and regulatory networks that govern phenotypic plasticity and agronomic performance. While coding regions are pivotal for expression, non-coding elements play an even more prominent role in regulating transcriptional activity and orchestrating essential biological processes. Natural allelic variation within these non-coding elements serves as an evolutionary substrate for regulatory rewiring, contributing to adaptive plasticity, domestication traits, and intraspecific diversification. Therefore, the precise modulation of desirable agronomic traits could be facilitated by targeted engineering of such elements, which often allows for the fine-tuning of allelic effects in terms of the attenuation and partial restoration of alleles to impact desirable traits over coding components, which often results in complete exclusion or lethality. Therefore, we attempted to provide a comprehensive synthesis of functionally characterized non-coding elements exclusively for rice, highlight their functional roles, and emphasize how natural variation within these elements is critical for selecting traits associated with domestication and the breeding of elite genotypes. Notably, the potential of engineered non-coding RNA elements for the enhancement of agronomically advantageous traits is critically discussed. The future roadmap of non-coding element editing in rice is expected to be significantly shaped by continuous technological innovations in the editing toolbox, coupled with breakthrough discoveries for non-coding elements influencing agronomical traits. These advances have the potential to revolutionize the development of superior rice genotypes, ultimately contributing to the global effort to ensure food and nutritional security.

Indexed as

CRISPR/Cas9Natural variationsNon-coding elementsNon-coding RNAsRiceSingle nucleotide polymorphism

Identifiers

PMID41461981
PMCPMC12748393

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.