Evidence map›Paper›PMID 34925418›Full record

ReviewFrontiers in plant science2021

Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value.

Tinashe Zenda, Songtao Liu, Anyi Dong, Jiao Li, Yafei Wang, Xinyue Liu, Nan Wang, Huijun Duan

Abstract readReview
In one paragraph

Review in Frontiers in plant science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
–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

33 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. Structural Variation and Its Roles in Plant Genomes.Plants (Basel, Switzerland) · 2026
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  20. Integrating omics databases for enhanced crop breeding.Journal of integrative bioinformatics · 2023
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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

8 authors.

Tinashe ZendaState Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China.
Songtao LiuAcademy of Agriculture and Forestry Sciences, Hebei North University, Zhangjiakou, China.
Anyi DongState Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China.
Jiao LiState Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China.
Yafei WangState Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China.
Xinyue LiuState Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China.
Nan WangState Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China.
Huijun DuanState Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Novel crop improvement approaches, including those that facilitate for the exploitation of crop wild relatives and underutilized species harboring the much-needed natural allelic variation are indispensable if we are to develop climate-smart crops with enhanced abiotic and biotic stress tolerance, higher nutritive value, and superior traits of agronomic importance. Top among these approaches are the "omics" technologies, including genomics, transcriptomics, proteomics, metabolomics, phenomics, and their integration, whose deployment has been vital in revealing several key genes, proteins and metabolic pathways underlying numerous traits of agronomic importance, and aiding marker-assisted breeding in major crop species. Here, citing several relevant examples, we appraise our understanding on the recent developments in omics technologies and how they are driving our quest to breed climate resilient crops. Large-scale genome resequencing, pan-genomes and genome-wide association studies are aiding the identification and analysis of species-level genome variations, whilst RNA-sequencing driven transcriptomics has provided unprecedented opportunities for conducting crop abiotic and biotic stress response studies. Meanwhile, single cell transcriptomics is slowly becoming an indispensable tool for decoding cell-specific stress responses, although several technical and experimental design challenges still need to be resolved. Additionally, the refinement of the conventional techniques and advent of modern, high-resolution proteomics technologies necessitated a gradual shift from the general descriptive studies of plant protein abundances to large scale analysis of protein-metabolite interactions. Especially, metabolomics is currently receiving special attention, owing to the role metabolites play as metabolic intermediates and close links to the phenotypic expression. Further, high throughput phenomics applications are driving the targeting of new research domains such as root system architecture analysis, and exploration of plant root-associated microbes for improved crop health and climate resilience. Overall, coupling these multi-omics technologies to modern plant breeding and genetic engineering methods ensures an all-encompassing approach to developing nutritionally-rich and climate-smart crops whose productivity can sustainably and sufficiently meet the current and future food, nutrition and energy demands.

Indexed as

abiotic stressbiotic stressgenomics assisted breeding (GAB)multi-omics technologiesnutritive traitspan-genomessingle cell transcriptomicssystems biology approach

Identifiers

PMID34925418
PMCPMC8672198

What OpenQuestion holds

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LicenceCC BY
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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.