Armillaria solidipes str. 28-4 (Armost1)

About Armillaria solidipes str. 28-4 (GCA_002307675)

Armillaria ostoyae (sometimes called Armillaria solidipes) is a species of plant pathogenic fungus in the Physalacriaceae family. It is the most common variant in the western U.S., of the group of species that all used to share the name Armillaria mellea. Armillaria ostoyae is quite common on both hardwood and conifer wood in forests west of the Cascade crest. The mycelium attacks the sapwood and is able to travel great distances under the bark or between trees in the form of black rhizomorphs (
"shoestrings
").

In most areas of North America, Armillaria ostoyae can be separated from other species by its physical features. Its brown colors, fairly prominent scales featured on its cap, and the well-developed ring on its stem sets it apart from any Armillaria. (Herink, 1973)

It is known to be one of the largest living organisms, where scientists have estimated a single specimen found in Malheur National Forest in Oregon to be 2,400 years old, covering and colloquially named the
"Humongous Fungus
". Armillaria ostoyae grows and spreads primarily underground and the bulk of the organism lies in the ground, out of sight. Hence, the organism is invisible from the surface. In the autumn this organism blooms
"honey mushrooms
", evidence of the organism beneath. Low competition for land and nutrients have allowed this organism to grow so huge; it possibly covers more geographical area than any other living organism.

(Text and image from Wikipedia, the free encyclopaedia.)

Taxonomy ID 1076256

Data source DOE Joint Genome Institute

More information and statistics

Genome assembly: Armost1

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Gene annotation

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

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Comparative genomics

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

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Phylogenetic overview of gene families

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Variation

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

Variant Effect Predictor