Gaurav Diwan

- Placing new #Biodiversity #Genomics genomes (e.g.) in this framework gives context to which gene functions already exist in that clade and what is new/unknown for the new one

Big thanks to Rob Russell, Paschalis, JC, Mu-en, @maxjtelford.bsky.social @guigolab.bsky.social John Colbourne!

10/10

So take home messages:
- Overlaying function onto gene evolutionary history captures the specific biology of species without #morphology
- Phylogeny can be perfected & annotations can be perfected but if one fuses them together as they are, one could get deep #Evolution insights

9/10

And when we look inside the clusters, we can check the exact genes that have the analogous functions leading to the adaptation to the new environment. N.B. these genes are not from the same HOG. So, they're not related by sequence but by #function...

8/10

Comparison level of enrichment in clustered GO terms at the transition nodes versus their parent nodes. The genes inside the cluster were then checked for the source of the terms.

For the water to land nodes, terms inside a GO cluster were
Bone development in tetrapods 🦴
Open tracheal system in arthropods
Seed/Leaf development in plants 🍀
These were all anatomical structures which organisms needed to survive on land.

Again... these were captured from gene annotations!
7/10

Next we analyzed the functions emerging at nodes that underwent large phenotypic transitions. In our tree, we had 3 nodes where species moved from water to land and 5 nodes where organisms became multicellular.

We enriched GO terms at transition nodes and clustered them by semantic similarity

6/10

Above: GO enrichment of genes from HOGs gained at each node of the eukaryote --> tetrapod lineage. Below: average % of KEGG pathway categories gained at the same nodes.

Eukaryotes = splicing + cell cycle + transcription/translation
Metazoa = differentiation + embryo development + nervous systems
Vertebrates = immune response + digestive systems + circulatory systems

So we are recovering characteristic #traits from gene annotations!

5/10

Instead of focusing on which exact genes were gained or to avoid over-interpreting the ancestral reconstruction of our sets, we analysed the enriched GO terms and categories of pathways gained at these nodes. We found interesting specificity here
#genomebiology

4/10

Nodes with the largest HOG + pathway component gains were the ancestors of:
- All Eukaryotes
- Flowering plants 🌻
- Slime molds (!)
- Metazoans 🦐
- Vertebrates 🚶‍♂️
#EvoBio #evolbio

3/10

We sorted all genes into HOGs (at the root of the species tree) and traced the history of each HOG on the species tree. We also did the same for the orthologs of each gene.
We used:
Each HOG = one gene that duplicated/diverged
Each ortholog = KEGG/Reactome pathway component
#phylogenomics
2/10

Number of genes, domains and pathways gained at every node of a cladogram of 508 species

Pleased to announce that our #preprint on the evolutionary history of gene functions is now online at #bioRxiv! We overlayed functional annotations on the evolutionary history of ~4.5M genes from 508 species across the tree of life and found some very cool stuff!

tinyurl.com/FuncEvol

🧵 1/10

Good morning people at #ESEB2025

Come check out my poster P03.068 today to know about

- The evolutionary history of genes and gene functions from >500 species across the tree of life 🪾

- How that helps us reveal widespread parallelisms in the move from water to land and multicellularity 🧬

Fantastic day 1 @eseb2025.bsky.social ! Talks showing how incorrect orthology and hidden paralogy could affect phylogenetic tree structures; species tree inference from WGA; and how pre-LUCA protein sequences tell you the order in which amino acids emerged!
Super cool stuff #ESEB2025

Checked in @eseb2025.bsky.social in Barcelona. Come check out my poster on Thursday if you want to know the evolutionary history of any gene or its function! #ESEB2025