TransAnnot: a fast transcriptome annotation pipeline

TransAnnot is a toolkit designed to predict protein functions, identify orthologous relationships, and decipher biological pathways for newly sequenced transcriptomes. Utilizing MMseqs2's fast sequence-sequence and sequence-profile search, it identifies the closest homologs from reference databases to infer essential details such as protein function, structure, and orthologous groups.

Optionally, TransAnnot can use Plass for transcriptome assembly, enabling de novo assembly of raw sequence reads at the protein level.

TransAnnot is a free and open-source (GPLv3), modular toolkit developed in C++.

Compile from source

Compiling TransAnnot from the source allows for system-specific optimization. For the compilation cmake, g++ and git are required. After the compilation, TransAnnot will be located in the build/bin directory.

git clone https://github.com/soedinglab/transannot.git
cd transannot && mkdir build && cd build
cmake -DCMAKE_BUILD_TYPE=RELEASE -DCMAKE_INSTALL_PREFIX=. ..
make -j 4
make install
export PATH=$(pwd)/bin/:$PATH

❗️ If you compile from source under macOS we recommend installing and using gcc instead of clang as a compiler. gcc can be installed with Homebrew. Force cmake to use gcc as a compiler by running:

CC="$(brew --prefix)/bin/gcc-13"
CCX="$(brew --prefix)/bin/g++-13"
cmake -DCMAKE_BUILD_TYPE=RELEASE -DCMAKE_INSTALL_PREFIX=. ..

Other dependencies for the compilation from the source are zlib and bzip.

Workflow dependencies

• Plass - should be installed separately in the current working directory, see corresponding repository, to perform de novo assembly.
• Databases - Pfam, EggNOG and UniProtKB/Swiss-Prot

Quick start

The quickest way to run TransAnnot is by using the easytransannot module:

transannot easytransannot <inputReads.fastq> Pfam-A.full eggNOG UniProtKB/Swiss-Prot <resDB> <tmp> [options]

If (one of the) target databases is already downloaded in MMseqs2 format, directly provide the path to them, otherwise simply specify their names, and the databases will be downloaded automatically. easytransannot uses Plass assembler, for more details check the descriptions for assemblereads module below.

Input

Possible inputs can be one of the following:

• translated sequences of assembled transcriptomes (obtained e.g. using Trinity followed by TransDecoder)
• raw transcriptome reads in fastq format, which will be de novo assembled by plass at the protein level

TransAnnot accepts input files from single-organism transcriptomes as well as metatranscriptomes.

Running

Modules

• assemblereads de novo assembles raw sequencing reads to large genomic fragments (contigs).
• createquerydb creates a database in a memory-efficient MMSeqs2 format for the query input sequence.
• downloaddb downloads reference databases in MMSeqs2 format on which annotations for query sequences will be searched.
• annotate performs clustering on input sequences to reduce redundancy and runs sequence-profile and sequence-sequence searches for the reference query sequences to obtain the closest homologs with the annotated function. In addition, it maps descriptions of orthologous groups and protein families to the query sequences.

• easytransannot an easy one-line command module for the complete transannot workflow, starting from input assembly, downloading reference databases to an output of sequence annotations.

assemblereads

This module uses Plass to assemble input read sequences and obtain translated protein sequences. Plass requires read length of at least 100nt, therefore assemblereads or easytransannot module is applicable only for input reads of length $\ge$ 100nt. To run, Plass must be installed and located in the current working directory. Detailed information about installation can be found here.

In this step, reads will be assembled with Plass and afterwards an MMseqs2 database will be created, you may skip this step if the transcriptome is already assembled and translated. Usage:

transannot assemblereads <inputReads.fastq[.gz|bz]> ... <inputReads.fastq[.gz|bz]> <o: fastaFile with assembly> <o: seqDB> <tmp> [options]

Since Plass has not been benchmarked for transcriptome assembly, for standard usage, we recommend using nucleotide assembler such as [Trinity] (https://github.com/trinityrnaseq/trinityrnaseq/wiki) followed by protein translator (e.g TransDecoder) (https://github.com/TransDecoder/TransDecoder/wiki) before running TransAnnot for sequence annotation. If the input query sequence is obtained from external tools, just proceed directly with createquerydb module.

createquerydb

This module creates a database for input query sequences in memory-efficient MMSeqs2 format.

To create a query database, execute the following command:

transannot createquerydb <inputFastaFile> <sequenceDB> <tmpDir> [options]

If input fasta file is obtained from external tools without using assemblereads module, this createquerydb module must be used. Otherwise, assemblereads module already provides a query sequence database in MMSeqs2 format and hence this step can be skipped.

downloaddb

This module downloads sequence databases for homology searches.

To see detailed information about databases, please use the following command:

mmseqs databases -h

and execute the below command to download the databases (Ensure the same keyword as given in mmseqs database -h):

transannot downloaddb <selection> <outDB> <tmp> [options]  

By default, transannot runs 3 searches in the subsequent annotate module against the following databases: (i) Pfam-A.full (profile database), (ii) eggNOG (profile database) and (iii) UniProtKB/SwissProt (sequence database). Hence, use the above command separately for each database to download them, for more information check MMseqs2 user guide.

annotate

This module extracts representative sequences from the query database using clustering (redundancy-free set) and uses them as search input for 3 transcriptome annotation searches (one sequence-sequence and two sequence-profile).

To run the annotate module, execute the following command:

transannot annotate <assembledQueryDB> <path to Pfam profileTargetDB> <path to eggNOG profileTargetDB> <path to SwissProt sequenceTargetDB> <o:resTsvFile> <tmp> [options]

Output

Outut is a tab-separated .tsv file containing the following columns:

queryID targetID description E-value sequenceIdentity bitScore typeOfSearch nameOfDatabase 

Important options of the annotate module

--simple-output parameter allows users to obtain simplified output for each query sequence, which only includes query and target IDs, a header of the target database and E-value. Whereas standard output contains sequence identity and bit score in addition to details provided in the --simple-output. Usage:

transannot annotate $1 $2 $3 $4 $5 $6 --simple-output 

When no tag is used, standard output will be provided.

--min-seq-id is a parameter to adjust the minimum sequence identity for the searches. The default value is set to 0.3.

--no-run-clust performs annotation without clustering. All the input query sequences will undergo annotation searches.

Use of custom database for annotation

If one is interested in annotation against a user-defined database, annotatecustom module provides such an opportunity. To run the custom annotate module execute the following command:

transannot annotatecustom <assembledQueryDB> <user-defined DB>

The user-provided database will be converted to the MMseqs2 format within the module, but it is also possible to initially provide a MMseqs2-formatted database. A limitation is that unless ID descriptors are included in the database, no mapping can be performed and no group descriptors will be retrieved.

tmp folder

tmp folder keeps temporary files. By default, all the intermediate output files from different modules will be kept in this folder. To clear tmp pass --remove-tmp-files parameter [bool], applicable for all modules except createquerydb and downloaddb.