Oryza nivara (Oryza_nivara_v1.0)

About Oryza nivara

Oryza nivara is a wild rice from India; one of rice species being used in the OMAP project. It belongs to the AA genome group. Breeders are interested in this organism because it exhibits resistance to grassy stunt virus. It is found in swampy areas, at edges of ponds and tanks, beside streams, in ditches, in or around rice fields. It usually grows in shallow water up to 0.3 m. seasonally dry; in open habitats. It has 12 chromosomes and a nuclear genome size of 448 Mb (flow cytometry). This work was part of the Oryza Genome Evolution project funded by NSF Award #1026200 and in collaboration with Yue-Ie Hsing.

Taxonomy ID 4536

Data source Oryza Genome Evolution Project

More information and statistics

Genome assembly: Oryza_nivara_v1.0

More information and statistics

Download DNA sequence (FASTA)

Display your data in Ensembl Plants

Gene annotation

What can I find? Protein-coding and non-coding genes, splice variants, cDNA and protein sequences, non-coding RNAs.

More about this genebuild

Download genes, cDNAs, ncRNA, proteins - FASTA - GFF3

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Comparative genomics

What can I find? Homologues, gene trees, and whole genome alignments across multiple species.

More about comparative analyses

Phylogenetic overview of gene families

Download alignments (EMF)

Variation

This species currently has no variation database. However you can process your own variants using the Variant Effect Predictor:

Variant Effect Predictor

Regulation

What can I find? Microarray annotations.

More about the Ensembl Plants microarray annotation strategy

Gramene/Ensembl Genomes Annotation

Additional annotations generated by the Gramene and Ensembl Plants project include:

  • Gene phylogenetic trees with other Gramene species.
  • LastZ Whole Genome Alignment to Arabidopsis thaliana, Oryza sativa Japonica (IRGSP v1) and other Oryza AA genomes.
  • Orthologue based DAGchainer synteny detection against other AA genomes.
  • Mapping to the genome of multiple sequence-based feature sets using Gramene BLAT pipeline.
  • Identification of various repeat features by programs such as RepeatMasker with MIPS and AGI repeat libraries, and Dust, TRF.