DOI: 10.5061/dryad.0cfxpnw7p
title: Finding orthologs for aminoacyl tRNA synthetases in parasitic plants

description: Eukaryotic nuclear genomes often encode distinct sets of protein
 translation machinery for function in the cytosol vs. organelles
 (mitochondria and plastids). This phenomenon raises questions about why
 multiple translation systems are maintained even though they are capable
 of comparable functions, and whether they evolve differently depending on
 the compartment where they operate. These questions are particularly
 interesting in land plants because translation machinery, including
 aminoacyl-tRNA synthetases (aaRS), is often dual-targeted to both the
 plastids and mitochondria. These two organelles have quite different
 metabolisms, with much higher rates of translation in plastids to supply
 the abundant, rapid-turnover proteins required for photosynthesis.
 Previous studies have indicated that plant organellar aaRS evolve more
 slowly compared to mitochondrial aaRS in other eukaryotes that lack
 plastids. Thus, we investigated the evolution of nuclear-encoded
 organellar and cytosolic translation machinery across a broad sampling of
 angiosperms, including non-photosynthetic (heterotrophic) plant species
 with reduced rates of plastid gene expression to test the hypothesis that
 translational demands associated with photosynthesis constrain the
 evolution of bacterial-like enzymes involved in organellar tRNA
 metabolism. Remarkably, heterotrophic plants exhibited wholesale loss of
 many organelle-targeted aaRS and other enzymes, even though translation
 still occurs in their mitochondria and plastids. These losses were often
 accompanied by apparent retargeting of cytosolic enzymes and tRNAs to the
 organelles, sometimes preserving aaRS-tRNA charging relationships but
 other times creating surprising mismatches between cytosolic aaRS and
 mitochondrial tRNA substrates. Our findings indicate that the presence of
 a photosynthetic plastid drives the retention of specialized systems for
 organellar tRNA metabolism.
description: Output of Orthofinder run on protein models from parasitic and
 autotrophic plant species. 
description: # Finding orthologs of Aminoacyl tRNA synthetases in parasitic plants. ---
 Here is the relevant output from Orthofinder run on parasitic and
 autotrophic plants. Additionally there are some scripts used in the
 analysis downstream, including finding all orthogroups with aminoacyl tRNA
 synthetases, running reciprocal best hit (RBH) searches in BLAST, and
 sorting and plotting orthologs based on length of sequence relative to
 Arabidopsis thaliana reference. ## Description of the data and file
 structure This submission has the initial output from Orthofinder:
 Orthogroups.tsv This submission also has downstream code for analysis (see
 code section for more details) Required metadata files to run code: *
 aaRS_tRNAprocessing.txt - metadata about genes of interest, including
 Arabidopsis thaliana ortholog TAIR identifiers, and description of
 sub-cellular targeting and target amino acid. - psuedogenes.txt - A list
 of known amino-acyl tRNA psuedogenes in Arabidopsis thaliana, based on
 Duchenne et. al., 2005. - aaRS_tRNAprocessing_Athal_query.txt - Just the
 TAIR identifiers for genes of interest, for use in Reciprocal Best Hit via
 BLAST+. - orthogroups_geneID.txt - metadata about genes of interest,
 including subcellular targeting, description, and orthogroup identifier
 from Orthofinder analysis. - orthogroup_sequences.zip - contains amino
 acid sequences for each orthogroup with target genes. ## Sharing/Access
 information Data was derived from many publicly available datasets. See
 publication for details. Orthofinder was used to find orthologous protein
 sequences across all species. References: *Emms DM, Kelly S, 2015.
 OrthoFinder: solving fundamental biases in whole genome comparisons
 dramatically improves orthogroup inference accuracy. Genome Biology 16.*
 *Emms DM, Kelly S, 2019. OrthoFinder: Phylogenetic orthology inference for
 comparative genomics. Genome Biology 20.* *Blast+ was used for Reciprocal
 Best Hit analysis:* *Camacho C, Coulouris G, Avagyan V et al., 2009.
 BLAST+: Architecture and applications. BMC Bioinformatics 10.* ##
 Code/Software Includes python scripts and a bash script used for
 downstream analysis and data visualization. 1. Extract orthogroups of
 interest based on list: `python3 individualfind_orthogroups.py
 aaRS_tRNAprocessing_Athal_query.txt Orthogroups.tsv orthogroups_ind.xlsx`
 2. Obtain Reciprocal Best Hit (RBH) using blast against A. thaliana.
 Requires BLAST+ installed locally, and databases generated from protein
 annotations for each species including Arabidopsis. `for fa in
 ~/blastdb/_prot.fa; do blast_RBH_noE.sh
 aaRS_tRNAprocessing_Athal_query.txt blastdb/A_thaliana_prot.fa $fa
 ${fa#////} A_thaliana_prot.fa; done` 3. Merge Orthogroups and RBH hits:
 `for f in $(ls blast_RBH*); do merge_orthofinder_blastRBH.py
 orthogroups_ind.xlsx $f; done` 4. Extract sequences for each gene in each
 orthogroup and generate new fasta file. Use command line to remove
 psuedogenes in psuedogenes.txt Then generate multiple sequence alignments
 for each orthogroup in via MAFFT and put into folder alignments/ 5. Use
 script to parse output- determine ortholog length relative to A. thaliana
 model `parse_absencepresence.py orthogroup_sequences/
 presence_absence_seperateoldnewmodels.xlsx` 6. Plot using jupyter notebook
 plot_presenceabsence.ipynb *python packages required include:* pandas
 numpy seaborn scipy.stats matplotlib re os datetime math # Version changes
 As of October 2024: **20240528**: Re-did analysis but added two new sets
 of gene models (old models run in parallel), resulting in an entirely new
 Orthogroups.tsv file. Metadata file with list of aaRS/tRNA modifying
 enzymes is included as an example of format. For lists of other proteins
 from the study (i.e. riboproteins, targeting controls, organelle import
 machinery), please see linked publication. * *Balanophora fungosa*:
 Genome-based models from China National GeneBank (CNGB) Sequence Archive
 (CNSA) accession number CNP0003054 * *Sapria himalayana*: Protein models
 directly from author of DOI: 10.1186/s12915-023-01620-3. **20240811:**
 Altered tablemash_blast_RBH.py so species name is added to name of output
 excel file **20240820:** Altered scripts for parsing sequences by length
 and plotting * Removed MAFFT alignment step (parse_after*_*mafft.py),
 replaced with new script parse_absencepresence.py which just assesses
 length of putative ortholog relative to *A. thaliana *model without
 multiple sequence alignment. * Removed analysis/ plotting of of
 tetrapyrole pathway, added analysis/ plotting of organelle protein import
 machinery- see plot_presenceabsence.ipynb