Gene content homoplasy

We just published an article, in collaboration with the laboratory of Gabriela Olmedo-Alvarez, trying to solve the phylogeny of Bacillus, which started with a special focus on Bacillus isolated from aquatic environments. The work required solving several little problems just to get those phylogenies, choosing the appropriate genes/proteins for the analyses, thinking of distance measures, etc. All of which I’ll be delighted to write about in later posts. For now, I’ll concentrate on the main finding.

In a previous article, also in collaboration with Gabriela, we had presented several phylogenies all showing that aquatic Bacillus clustered together into a single clade. Given the continuous growth of the public genome databases (see the previous two posts for example), and that Gabriela’s lab continues sequencing aquatic and other interesting Bacillus, we wondered whether the aquatic group would stand to this avalanche of new data. So there we were, choosing Bacillus and checking the data about their places of isolation. As in the previous work, we built a phylogenetic tree based on the 16S rRNA genes, a second one based on the proteins encoded by genes present in all of the genomes under analysis (a core tree), a third tree based on marker genes for phylogenomics published by Jonathan Eisen‘s group, and a hierarchical cluster based on the [dis]similarity of shared proteins between each pair of genomes that we call the Genomic Similarity Score (GSS).

The phylogenetic trees showed a clade of aquatic Bacillus, but several other aquatic Bacillus landed in other clades, thus breaking the pattern previously found. However, the GSS analysis placed the aquatic Bacillus closer together than any of the phylogenetic trees. We were surprised because, in the previous work, the GSS cluster reflected the results of the phylogenetic trees. We therefore started looking for an explanation for this discrepancy.

The phylogenetic trees are restricted to using genes or proteins shared by all the genomes under analysis, while the GSS is not limited, as it uses the similarity of all of the proteins encoded by the genes shared by each pair of genomes. Thus, we thought that there might be more genes shared between organisms of similar environments, than would be expected from their different vertical origins. After all, it is not rare for Bacteria to receive genes via horizontal gene transfer (HGT).

To test for this possibility, we proceeded to make analyses based on gene content as reflected by the classification of their encoded proteins into protein families, and the comparison of such content across organisms. We produced clusters based on gene content and, again, aquatic Bacillus were clustered better than in the phylogenetic trees. Further analyses showed some genes prevailing in groups from each environment. Most of these “environmentally-related” genes were found in strains isolated from soil, and therefore every group had some interesting genes for future studies. Among them we found genes described in previous works as being related to the appropriate environments where we found them to be enriched.

We call this apparent tendency to share more genes than expected from vertical inheritance, perhaps due to environmental constraints, gene content homoplasy.

Main reference:

  1. Hernández-González IL, Moreno-Hagelsieb G, Olmedo-Álvarez G (2018) Environmentally-driven gene content convergence and the Bacillus phylogeny. BMC Evol Biol 18: 148.

OK, more updates 2017

Well, the last post was about updates, but it was more about 2016 than 2017. Here a couple graphs for your delight. One before filtering, the other after, with the counts of prokaryotic genomes in each NCBI category as of July 2017.

The four categories are: Complete, Chromosome, Scaffold, and Contigs. My filtering used to include redundant TaxIDs, but I learned that TaxIDs wasn’t a good idea. Now I filter only by strain, substrain, etc, as provided by the NCBI list of features. Not perfect, but I seem to keep most genomes.


Updates 2017

You might already know, but if you didn’t, NCBI changed the organization of its genome database. They used to have a BACTERIA directory containing all the complete genomes (with a few caveats), and a DRAFT_BACTERIA containing, well, draft genomes. Today, the genomes are scattered and organized somewhat taxonomically, so you have to look at some files to figure out if the genomes are drafty or not so drafty. Now they have four categories: Complete, Chromosome, Scaffold, and Contig. I think that’s the order of completeness, though I’m still not sure how Chromosome


Growth of genome data at NCBI

differs from Complete, but I suspect that’s what used to be the caveats (maybe only one replicon, of many, was sequenced). Anyway, last December I finished some BLASTP comparisons of a Complete genomes dataset that I downloaded by August (2016). The dataset contains 4085 complete prokaryotic genomes (I eliminated genomes from the same strains or the same taxid). Updates are thus starting to appear in the data I offer through this web site and my server at Laurier. Check frequently if you need newer data than what you found previously.

Happy new year!

Undergrad theses!

This term I have three students working on their undergrad theses, plus one working on directed studies. I am very proud of these students. Lots of initiative, reading articles, trying the computer (except for one, they hadn’t worked under unix before!), now having lots of success running their commands, and looking at results!

What are they doing? Two of them are working with protein domains in transporter proteins (from the TCDB), one on sorting prokaryotic genomes into taxonomically-coherent groups, one more on the divergence of orthologs and paralogs.


Half Sabbatical 2015!

I spent four great months working with Milton Saier at UCSD. Milton built a very useful database on transporter proteins, The Transporter Classification database (TCDB), and his lab has developed several pieces of software to play and analyze the database looking for such things as homologs that have diverged beyond the limits of detection by common sequence comparison tools. It was my privilege and honor to help Milton’s lab update and improve some of these tools, and develop a couple new ones. The tasks also gave me a lesson about sharing software, no matter how complex or simple.

In any event,  I’m still working on some specific projects that we started during my visit, and feel full of new ideas, for example about detection of protein domains. I expect that these ideas will complement work that’s been going on in my lab on assignment of functions to homologs with highly divergent sequences.

In short, this was a sabbatical as they should be. I learned a lot and got inspiration for new projects that I would have never thought about before this visit.


The whole 2015 Spring/Summer group

lab-photo-2015-reducedHere the whole group in the lab of Computational conSequences during the Spring/Summer of 2015. I’d say that this is the best group ever.

Gustavo leaves today, going back to Michoacán, Mexico after spending his sabbatical here. Julie left a few weeks ago, also back to Michoacán. She might come back for the Spring/Summer 2016.

The only locals are Brigitte, Kissa, Thomas, César and me. Brigitte and Kissa being honorary members who have been in the lab for collaborative reasons, but work for their M.Sc. degrees with other faculty members at Laurier (Michael Suits and Geoff Horsman, respectively).

We’ve been working on phages, plant-growth promoting bacteria, 16S rRNA gene analyses, metabolic annotations, gene neighborhoods, predicting gene functions, and predicting metabolism and transcriptional regulation networks. Lots of fun.

Summer 2015 group

group-2015-reducedThis is [most of] the group in the lab of Computational conSequences this summer. Several visitors from Mexico! Julie, Gustavo, and Ramiro from Michoacán, and Adrián from Mexico City.

What we’re doing?

In no particular order:

  • Julie is working with 16S rRNA genes
  • Gustavo is on sabbatical doing all kinds of reviews and such on plant growth promoting bacteria
  • Ramiro is working on the genome of a plant growth promoting bacteria
  • Adrián is working on Phage
  • Kissa is working with adjacent genes (gene neighborhoods)
  • Harold is working on genome annotations
  • Thomas is working on predicted functions (metabolism and such)
  • César is working on regulatory networks in prokaryotes, and on metagenome annotations
%d bloggers like this: