Tag Archives: database

The C is for Catalog

It seems intuitive enough that the size of an organism’s genome should be related to its evolutionary complexity. As a general rule, this tends to be true. But look within a class of organisms and you’ll find a great deal of genome size – also known as a C-value – variation. A newt’s genome, for example, is ten times the size of a frog’s.

This discrepancy between genome size and evolutionary complexity is known as the C-value paradox and it has long captured the imagination of biologists. Genome sequencing and annotation have revealed that a great amount of an organism’s genome is non-coding, suggesting that a great deal of genetic content may be gained or lost without affecting the so-called “evolutionary complexity” of the organism (though whether this non-coding DNA is truly “junk” is still up for debate).

In a recent Nucleic Acids Research paper, Gregory et al introduce another toolset to aid in our understand of genome size: the genome size databases. Three separate databases catalog the genome size statistics for various Plants, Animals and Fungi respectively, collectively covering >10,000 species. While various methods of estimating genome size may produce conflicting estimates of genome size (caveat emptor!), these tools should serve to help guide analyses and experiments of genome size evolution. Specifically, by enabling comparisons of genome size across multiple phylogenetic levels, these datasets should facilitate a better understanding of where the genome size/complexity relationship falls off.

As an interesting side note, the authors mention a few particular findings in fungi. The histogram of genome size in Fungi (see the figure) tends to be tighter than in Plants and Animals, with almost all taxa within the range of 1C or 10-60 Mb of DNA. That said, a few species appear to exhibit considerable intraspecific variation. While this may be due to the aforementioned methodological errors, the authors consider that dikaryotic hybrids and heterokaryotes may contribute to this observation. It seems that we may only be scratching the surface of genome size variation in Fungi and if genome size is indeed rapidly evolving in Fungi, they may serve to as good models to study this evolutionary phenomenon.

Making the Revolution Work for You

In a recent Microbiology Mini-Review, Meriel Jones catalogs both the potential benefits and problems that arise from fungal genome sequencing. Using the nine genomes (being) sequenced from the Aspergillus clade, Jones addresses several issues tied to a singular theme: if we are to unlock the potential that fungal genome sequencing holds, both academically and entrepreneurially, then a more robust infrastructure that enables comparative and functional annotation of genomes must be established.

Fortunately, like any good awareness advocate, Jones points us in the direction of e-Fungi, a UK based virtual project aimed at setting up such an infrastructure. Anyone can navigate this database to either compare the stored genomic information or evaluate any fungus of interest in the light of the e-Fungi genomic data. The data appears to be precomputed, similar to IMG from JGI, so there are inherent limitations on the data that one can obtain. However, tools such as these put important data in the hands of expert mycologists that can turn the information into something biologically meaningful.

As Jones points out, this is just the beginning. If fungal genomes are to live up to their promise, they must engage more than just experts at reading genomes.