gene alignment (microsynteny)

Question

[gubrins]

Hi all,

I have two reference genomes already annotated and I want to study several genes that are found in a tandem array, to see if they are orthologous or not and if a specific gene in species A originated several others in species B. I am not finding any tool for doing that, as the ones I found are specifically focused on macrosynteny (as chromosomal rearrengements).

I tried to align the genomic sequences containing those genes, but the genomic sequences are in fasta files, so they are missing the gene information. How could I add the gene information (for both species) to that alignment if there is no tool that can do it?

Thanks in advance!

Answer 1

[cmdcolin]

I am not an expert in these methods, but this is a random list of ideas

you can look at this guide for mcscan which performs a protein-alignment of all genes https://github.com/tanghaibao/jcvi/wiki/MCscan-(Python-version)#microsynteny-visualization

this gives you just a gene-level view of microsynteny. I sometimes see the mcscan method called gene based or marker based alignment

if you want to see the per-base level alignment, that is often a "whole genome alignment". minimap2 is a common example of this

then there are perhaps hybrid methods, like AnchorWave. you can see that the steps of anchorwave uses first marker/gene based alignment, then uses those to extend the whole genome alignment. this was i believe successfully used in plants especially

https://github.com/baoxingsong/AnchorWave

then you can try to visualize results, which i think is a very interesting challenge. many tools do large scale visualizations like circos and syri but indeed, zooming in and getting microsynteny visualizations is useful

I develop jbrowse 2, which i think has some unique capabilities for zooming in and viewing alignments. you can follow the quickstart guide that includes loading a PAF file from minimap2 here https://jbrowse.org/jb2/docs/quickstart_web/#adding-a-synteny-track-from-a-paf-file

I also know there are lots of other tools, depending on your interest and I catalog them here https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&tag=Comparative