Omics: a tool for resilient rice genetic improvement strategies

  • Muhammad Naeem
  • , Zeeshan Ali
  • , Anzal Khan
  • , Sami-Ul-Allah
  • , Hassan Javed Chaudhary
  • , Javeria Ashraf
  • , Faheem Shahzad Baloch

Research output: Contribution to journalReview articlepeer-review

4 Citations (Scopus)

Abstract

Rice is pivotal pyramid of about half of the world population. Bearing small genome size and worldwide utmost food crop rice has been known as ideal cereal crop for genome research. Currently, decreasing water table and soil fatigue are big challenges and intense consequences in changing climate. Whole sequenced genome of rice sized 389 Mb of which 95% is covered with excellent mapping order. Sequenced rice genome helps in molecular biology and transcriptomics of cereals as it provides whole genome sequence of indica and japonica sub species. Through rice genome sequencing and functional genomics, QTLs or genes, genetic variability and halophyte blocks for agronomic characters were identified which have proved much more useful in molecular breeding and direct selection. There are different numbers of genes or QTLs identified for yield related traits i.e., 6 QTLs/genes for plant architecture, 6 for panicle characteristics, 4 for grain number, 1 gene/QTL for tiller, HGW, grain filling and shattering. QTLS/genes for grain quality, biotic stresses and for abiotic stresses are 7, 23 and 13 respectively. Low yield, inferior quality and susceptibility to biotic and abiotic stresses of a crop is due to narrow genetic background of new evolving rice verities. Wild rice provides genetic resources for improvement of these characters, molecular and genomics tool at different stages can overcome these stresses and improve yield and quality of rice crop.

Original languageEnglish (UK)
Pages (from-to)5075-5088
Number of pages14
JournalMolecular Biology Reports
Volume49
Issue number6
DOIs
Publication statusPublished - Jun 2022
Externally publishedYes

Keywords

  • Abiotic stress
  • Drought stress
  • Genomics
  • Metabolomics
  • Proteomics

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