Evidence map›Paper›PMID 31889880›Full record

ReviewSaudi journal of biological sciences2020

Legume genomics and transcriptomics: From classic breeding to modern technologies.

Muhammad Afzal, Salem S Alghamdi, Hussein H Migdadi, Muhammad Altaf Khan, Nurmansyah, Shaher Bano Mirza, Ehab El-Harty

Abstract readReview
In one paragraph

Review in Saudi journal of biological sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

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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

7 authors.

Muhammad AfzalDepartment of Plant Production, College of Food and Agricultural Sciences, King Saud University, Riyadh, Saudi Arabia.
Salem S AlghamdiDepartment of Plant Production, College of Food and Agricultural Sciences, King Saud University, Riyadh, Saudi Arabia.
Hussein H MigdadiDepartment of Plant Production, College of Food and Agricultural Sciences, King Saud University, Riyadh, Saudi Arabia.
Muhammad Altaf KhanDepartment of Plant Production, College of Food and Agricultural Sciences, King Saud University, Riyadh, Saudi Arabia.
NurmansyahDepartment of Plant Production, College of Food and Agricultural Sciences, King Saud University, Riyadh, Saudi Arabia.
Shaher Bano MirzaComputational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahcesehir University (BAU), Istanbul, Turkey.
Ehab El-HartyDepartment of Plant Production, College of Food and Agricultural Sciences, King Saud University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Legumes are essential and play a significant role in maintaining food standards and augmenting physiochemical soil properties through the biological nitrogen fixation process. Biotic and abiotic factors are the main factors limiting legume production. Classical breeding methodologies have been explored extensively about the problem of truncated yield in legumes but have not succeeded at the desired rate. Conventional breeding improved legume genotypes but with more resources and time. Recently, the invention of next-generation sequencing (NGS) and high-throughput methods for genotyping have opened new avenues for research and developments in legume studies. During the last decade, genome sequencing for many legume crops documented. Sequencing and re-sequencing of important legume species have made structural variation and functional genomics conceivable. NGS and other molecular techniques such as the development of markers; genotyping; high density genetic linkage maps; quantitative trait loci (QTLs) identification, expressed sequence tags (ESTs), single nucleotide polymorphisms (SNPs); and transcription factors incorporated into existing breeding technologies have made possible the accurate and accelerated delivery of information for researchers. The application of genome sequencing, RNA sequencing (transcriptome sequencing), and DNA sequencing (re-sequencing) provide considerable insights for legume development and improvement programs. Moreover, RNA-Seq helps to characterize genes, including differentially expressed genes, and can be applied for functional genomics studies, especially when there is limited information available for the studied genomes. Genome-based crop development studies and the availability of genomics data as well as decision-making gears look be specific for breeding programs. This review mainly presents an overview of the path from classical breeding to new emerging genomics tools, which will trigger and accelerate genomics-assisted breeding for recognition of novel genes for yield and quality characters for sustainable legume crop production.

Indexed as

Classical breedingImprovementLegumesRNA sequencingTranscriptome

Identifiers

PMID31889880
PMCPMC6933173

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.