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Gene Set Functional Analysis

Genomic Loci Functional Analysis

MARACAS, MicroAlgae RnA-seq and Chip-seq AnalysiS

PharaohFUN, PHylogenomic Analysis foR plAnt prOtein History and FUNction elucidation

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ALGAEFUN with MARACAS

microALGAE FUNctional enrichment tool for MicroAlgae RnA-seq and Chip-seq AnalysiS

Welcome to ALGAEFUN with MARACAS a microalgae web based tool for the analysis of RNA-seq and ChIP-seq data and the functional annotation of the resulting gene sets and genomic loci. ALGAEFUN with MARACAS supports the analysis for a wide collection of microalgae that includes Chlamydomonas reinhardtii, Ostreococcus tauri, Phaeodactylum tricornutum and Nannochloropsis gaditana. Please select from the navigation bar on the left the type of analysis you want to perform. You can also see our video tutorials on how to analyse RNA-seq and ChIP-seq data as well as on how to functionally annotate gene sets and genomic loci. Our code is freely available at Github. Please cite our work if you find it useful in your research.

Below you can find the phylogenetic relationship between the different microalgae species supported in ALGAEFUN with MARACAS:

AlgaeFUN allows researchers to perform functional annotation over gene sets. Gene Ontology (GO) enrichment analysis as well as KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis are supported. The gene set of interest can be obtained, for example, as the result of a differential expression analysis carried out using MARACAS. See our video tutorial for details or follow the next steps to perform your analysis:

In the left panel choose your microalgae of interest, the type of enrichment analysis to perform and the p-value threshold.
Insert your gene set in the text box or load it from a file using the Browse … button. An example can be loaded by clicking on the Example button. Click on Clear button to remove the loaded gene set.
Users can choose between the default background gene provided by AlgaeFUN of a custom one that can be specified.
Click on the Have Fun button to perform the specified functional enrichment analysis. The results will be shown in the different tabs below.

PharaohFUN allows researchers to explore orthologous proteins across different evolutionally distant species given a target protein. To perform the analysis, please follow the next instructions:

Select the model which better fits your data. Currently supported models are Viridiplantae (comprising the clades Chlorophyta and Streptophyta) and Global (including species from the whole Archaeplastida clade, as well as examples of Stramenopiles and Cryptophytes). Note that although both models contain the green lineage, their results may vary because the common ancestors of the groups are very distant in time, so for a more accurate analysis it is recommended to use the Viridiplantae model, while for a more generalist one the Global model should yield more information.
Press the Have fun button.
In the lower panel choose as many species as you wish to include in the tree. The species order follows an evolutionary criterion, grouping species belonging to the same clade.
Then write the ID of your gene of interest in the textbox, which has to correspond to one of the organisms selected in the previous step. If not, please select it before continuing. An example for Marchantia polymorpha appears in the text box.
If the objective of the study is to map the evolutionary history of a gene considering the species involved, choose Resolved Gene Trees, which shows the reconciliation of gene trees with the species tree. If, on the other hand, you only want to obtain a cladogram of similar proteins, choose Gene Trees, as it does not consider the evolutionary history of the species during the calculation.
Finally, click the Have Fun! button to construct the tree. Each organism appears with an specific color detailed in legend and the target gene is highlighted in red. Also, a text box allows user to copy the names of all the detected orthologs in a simple way. The generated tree can be downloaded as an image and in Newick format for use by other phylogenetic analysis tools. In addition, both the names of the genes contained in the tree and the sequences of the proteins encoded by its primary transcript can be downloaded using the respective buttons.
After generating the tree, navigate through the rest of the tabs and follow the instructions to perform different analyses on the genes listed in the tree.
Exceptions are the Download Genomes, Literature Annotation and Identify Sequences tabs. After choosing the model, these tabs can be used without defining species or generating the tree. Particularly useful is the Identify Sequences tab, which allows the user to enter sequences to return the ID of the most similar protein in the dataset. The Download Genomes tab allows for the download of the genomes used in the development of PharaohFUN. The Literature Annotation tab implements a connection to PlantConnectome, allowing to quickly extract associations of a search term with different biological entities based on scientific literature.
To change the model, refresh the page.

Select the type of tree to plot

AlgaeFUN allows researchers to perform annotation analysis of genomic loci or regions. These are typically generated from ChIP-seq studies of the genome-wide distribution of epigenetic marks or transcription factor binding sites. Our tool MARACAS can be used to perform this type of analysis. The set of marked genes can be obtained as well as the distribution of the genomic loci overlapping specific genes parts. Also, individual marked genes and the average signal level around the TSS (Transcription Start Site) and TES (Transcription End Site) over the complete set of marked genes can be visualized. See our video tutorial for details or follow the next steps to perform your analysis:

In the left panel choose your microalgae of interest, the gene promoter length and the gene parts that will be considered when determining the marked genes.
Insert in the text box your set of genomic regions as a table consisting of three tab-separated columns representing the chromosome, the start and end position of the regions. An example can be loaded by clicking on the Example button. Click on Clear button to remove the loaded gene set. Alternatively, using the Browse... button, the genomic regions can be uploaded from a file in BED format as described previously containing as least three columns. This file can be obained using our tool MARACAS.
Optionally, users can upload the genome wide signal level of a epigenetic mark or transcription factor binding in a BigWig file. This file can be obained using our tool MARACAS.
Click on the Have Fun button to perform the specified analysis. The results will be shown in the different tabs below.

MARACAS (MicroAlgae RnA-seq and Chip-seq AnalysiS) is an automatic computational pipeline specifically designed for the analysis of microalgae RNA-seq and ChIP-seq data . MARACAS starts processing raw fastq files and generates lists of differentially expressed genes for RNA-seq data and lists of genomic loci in bed format for ChIP-seq data. BigWig files containing normalized mapping signal are also generated. The analysis are performed according to user specified parameters. Reports in html and pdf format are produced for easy exploration of the results.
Differential expressed gene lists and genomic loci lists can be further analyzed using this online tool AlgaeFUN for functional analysis.
MARACAS supports a wide range of microalge including:

Ostreococcus tauri
Micromonas pusilla CCMP1545
Bathycoccus prasinos
Coccomyxa subellipsoidea
Chlamydomonas reinhardtii
Volvox Carteri
Dunaliella salina
Haematococcus lacustris
Chlomochloris zofingiensis
Klebsormidium nitens
Mesotaenium endlicherianum
Spirogloea muscicola
Phaeodactylum tricornutum
Nannochloropsis gaditana

MARACAS can be executed in a sequential mode in a laptop or server and in a distributed/parallel mode in a computer cluster.

Click here for instructions on how to download, install and execute MARACAS.

AlgaeFUN, is entirely developed using the R package shiny. The source code is released under GNU General Public License v3.0 and is hosted at GitHub. If you experience any problem using AlgaeFUN please create an issue in GitHub and we will address it.

AlgaeFUN at GitHub

MARACAS, is developed using bash scripting and several bioconductor R packages. The source code is released under GNU General Public License v3.0 and is hosted at GitHub. If you experience any problem using AlgaeFUN please create an issue in GitHub and we will address it.

MARACAS at GitHub

We are strongly committed to open access software and open science. Following our philosophy we have deposited our GitHub code into Zenodo , a general-purpose open-access repository developed under the European OpenAIRE program. Meanwhile we publish our work in a journal if you find AlgaeFUN with MARACAS useful in your research we would be most grateful if you cite our GitHub repository with a, DOI as follows:

Romero-Losada, A.B., Arvanitidou, C., de los Reyes, P., García-González, M., Romero-Campero, F.J. (2021) AlgaeFUN with MARACAS, microAlgae FUNctional enrichment tool for MicroAlgae RnA-seq and Chip-seq AnalysiS v1.0, Zenodo, doi:10.5381/zenodo.4754516 doi:10.5381/zenodo.4752818

Above you can find a video tutorial on how to use the different tools implemented in AlgaeFUN with MARACAS.

To watch the tutorial for PharaohFUN please press here

Please be patient, computing GO enrichment ...

Your GO enrichment is ready!

Please be patient, computing KEGG pathway enrichment ...

Your KEGG enrichment is ready!

Please be patient, computing common IDs conversion ...

Your common IDs conversion is ready!

Please be patient, computing tree ...

Press the Show Orthogroup Evolution button to visualize the expansions and contractions in orthogroup size across the different branches of the species tree. Only orthogroups that have significantly undergone these processes are shown. Note that only orthogroups present at the root of the tree are analyzed. Orthogroups present in less than 10 species or with a great difference in gene copies between species are also excluded.

Please be patient, reconstructing ancestors ...

Next, click on the Show Gene Selection for Pfam button, select the desired proteins from the tree and click on the Show Pfam Domains button to determine their PFAM domains. A table with the domains of each protein and their positions will be displayed, as well as a plot showing the same information. Warning: this process may take a long time in the case of selecting many proteins.

Please be patient, identifying domains ...

Next, click on the Show Gene Selection for MSA button, select the desired proteins from the tree and click on the Compute MSA button to show the alignment. The alignment is shown as text, including the consensus sequence. For a graphical representation with the different aminoacids colored according to their chemical nature, click on the download button. The aligned sequences can also be download as a FASTA file. Warning: This process (specially the colored download) may take a long time in the case of selecting many proteins.

Please be patient, aligning sequences ...

Click on the button to select the genes of interest from the tree and select the ontology type to display the GO terms associated with those genes. After pressing the Show GO terms button, the results are displayed in tabular form and are accompanied by a GO association plot (each node is a GO and an edge is drawn between two nodes if a gene has both terms) and a treeplot showing the hierarchy of the identified terms and their summary.

Please be patient, computing GO terms ...

Click on the button to select the genes of interest from the tree and press the Show KEGG information button to show the results. These include a table showing the KEGG Orthology IDs, indicating how many and which of the selected proteins correspond to each ID. In addition, the application performs an enrichment in KEGG pathways from the identified KOs and allows for the plotting of these pathways with the genes mapped onto them, using a selector to choose the pathway in case several enriched ones exist. Warning: this process may take a long time in the case of selecting many proteins. Attempts to plot large pathways will produce an error, only more specific ones are supported i.e. Carbon metabolism will return an error while Biotin metabolism will not

Please be patient, exploring pathways ...

In the text box, type the search term to query your bibliographic information, i.e., CCA1. Then select one of the 4 search modes: Normal returns the entities containing the term, Exact returns those that are identical, Alias returns all aliases associated with the term and Substring returns all those containing a given string. Associations found in the literature are returned in tabular form, with links to the papers from which the information was extracted. This functionality is based on PlantConnectome, to extend this analysis, it is recommended to use https://connectome.plant.tools/.

Select the search mode

Please be patient, searching literature ...

Select the desired organism and press the button to choose a genome (the amino acid sequences corresponding o the main transcript of each gene) used in the development of the tool with the ID considered for each sequence. Then press the download button to download it. To change the organism, select the new one and press again the Acess genome files button to update the genome before downloading.

Select the organism

To avoid mismatches between theentered gene IDs and those used by the application, in this tab you can paste the sequence of the protein to be analyzed and select the working species. The result will be a single-element table with the best identity result, indicating the similarity of the protein entered with the protein used by the application. The ID shown in the table can be then used for performing the analysis.