Comments (3)
Hi Cyan,
What workflow have you tried?
agora-basic? agora-vertebrate? agora-plants?
Are the genomes well assembled (chromosome level)?
Do you have the possibility to add an outgroup to the studied species?
Regards,
Alex
from agora.
Hi Alex,
Thanks for the quick reply. I used agora-vertebrate, and all genomes are chr-level. About outgroup, do you mean I’ d better use N1 rather than N0 as the ancestor to draw karyotype or is there any other parameters in Agora to do this? Indeed, I found N0 is always more fragmented than N1, but the number of CARS in N1 is still too much to deduce the real ancestral chr number for my data. Hope that you could help me with this problem, and feel free to contact me if anything unclear.
Best,
Cyan
from agora.
Hi Cyan,
The number of CARs inferred by AGORA will depend on many variables related to your data. The reconstruction will depend on the number of extant genomes you provide, the phylogenetic distance between species, the quality of genome annotations, the specific structure of each genome, and the quality of the orthologous assignments you performed.
AGORA is not the tool to “infer the true ancestral chromosome number.” The algorithm will do its best to reconstruct an ancestral gene order but it is not its purpose to infer the exact number of ancestral chromosomes.
For example:
As shown in the publication (Figure 4), even though zoofish studies infer 12 chromosomes for the Poaceae ancestor in grasses, AGORA infers 19 larger CARs (and more), which can be mapped to the 12 chromosomes of rice (used as a proxy for the ancestral grass karyotype). The links between scaffolds cannot be inferred by the algorithm, likely due to the lack of conserved synteny between species in centromeric regions.
However, for your data, you may want to try the “agora-generic” script to attempt scaffolding in order to improve the size of the CARs. Results, however, should be carefully analyzed to check for potential over-assembly.
I hope this helps.
best regards,
Alex
from agora.
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