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In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Results
  • Discussion
  • Disclosures
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

The protocol described here provides detailed instructions on how to analyze genomic regions of interest for microprotein-coding potential using PhyloCSF on the user-friendly UCSC Genome Browser. Additionally, several tools and resources are recommended to further investigate sequence characteristics of identified microproteins to gain insight into their putative functions.

Abstract

Next-generation sequencing (NGS) has propelled the field of genomics forward and produced whole genome sequences for numerous animal species and model organisms. However, despite this wealth of sequence information, comprehensive gene annotation efforts have proven challenging, especially for small proteins. Notably, conventional protein annotation methods were designed to intentionally exclude putative proteins encoded by short open reading frames (sORFs) less than 300 nucleotides in length to filter out the exponentially higher number of spurious noncoding sORFs throughout the genome. As a result, hundreds of functional small proteins called microproteins (<100 amino acids in length) have been incorrectly classified as noncoding RNAs or overlooked entirely.

Here we provide a detailed protocol to leverage free, publicly available bioinformatic tools to query genomic regions for microprotein-coding potential based on evolutionary conservation. Specifically, we provide step-by-step instructions on how to examine sequence conservation and coding potential using Phylogenetic Codon Substitution Frequencies (PhyloCSF) on the user-friendly University of California Santa Cruz (UCSC) Genome Browser. Additionally, we detail steps to efficiently generate multiple species alignments of identified microprotein sequences to visualize amino acid sequence conservation and recommend resources to analyze microprotein characteristics, including predicted domain structures. These powerful tools can be used to help identify putative microprotein-coding sequences in noncanonical genomic regions or to rule out the presence of a conserved coding sequence with translational potential in a noncoding transcript of interest.

Introduction

The identification of the complete set of coding elements in the genome has been a major goal since the initiation of the Human Genome Project, and remains a central objective toward the understanding of biological systems and the etiology of genetic-based diseases1,2,3,4. Advances in NGS techniques have led to the production of whole genome sequences for an extensive number of organisms, including vertebrates, invertebrates, yeast, and plants5. Additionally, high-throughput transcriptional sequencing methods have further revealed the complexity of the cellular transcriptome, and identified thousands of novel RNA molecules with both protein-coding and noncoding functions6,7. Decoding this vast amount of sequence information is an ongoing process, and challenges remain with comprehensive gene annotation efforts8.

The recent development of translational profiling methods, including ribosome profiling9,10 and poly-ribosome sequencing11, have provided evidence indicating that hundreds of noncanonical translation events map to currently unannotated sORFs throughout the genome, with the potential to generate small proteins called microproteins or micropeptides12,13,14,15,16,17. Microproteins have emerged as a novel class of versatile proteins previously overlooked by standard gene annotation methods due to their small size (<100 amino acids) and lack of classical protein-coding gene characteristics8,12,18,19,20. Microproteins have been described in virtually all organisms, including yeast21,22, flies17,23,24, and mammals25,26,27,28, and have been shown to play critical roles in diverse processes, including development, metabolism, and stress signaling19,20,29,30,31,32,33,34. Thus, it is imperative to continue to mine the genome for additional members of this long-overlooked class of functional small proteins.

Despite the widespread recognition of the biological importance of microproteins, this class of genes remains vastly underrepresented in genome annotations, and their accurate identification continues to be an ongoing challenge that has hindered progress in the field. Various computational tools and experimental methods have recently been developed to overcome the difficulties associated with identifying microprotein-coding sequences (discussed extensively in several comprehensive reviews8,35,36,37). Many recent microprotein identification studies38,39,40,41,42,43,44,45,46,47 have relied heavily on the use of one such algorithm called PhyloCSF48,49, a powerful comparative genomics approach that can be leveraged to distinguish conserved protein-coding regions of the genome from those that are noncoding.

PhyloCSF compares codon substitution frequencies (CSF) using multi-species nucleotide alignments and phylogenetic models to detect evolutionary signatures of protein-coding genes. This empirical model-based approach relies on the premise that proteins are primarily conserved at the amino acid level rather than the nucleotide sequence. Therefore, synonymous codon substitutions, which encode the same amino acid, or codon substitutions to amino acids with conserved properties (i.e., charge, hydrophobicity, polarity) are scored positively, while non-synonymous substitutions, including missense and nonsense substitutions, score negatively. PhyloCSF is trained on whole-genome data and has proven to be effective in scoring short portions of a coding sequence (CDS) in isolation from the full sequence, which is necessary when analyzing microproteins or individual exons of standard protein-coding genes48,49.

Notably, the recent integration of the PhyloCSF track hubs in the University of California Santa Cruz (UCSC) Genome Browser49,50,51 enables investigators of all backgrounds to easily access a user-friendly interface to query genomic regions of interest for protein-coding potential. The protocol outlined below provides detailed instruction on how to load the PhyloCSF track hubs on the UCSC Genome Browser and subsequently interrogate genomic regions of interest to probe for high-confidence protein-coding regions (or the lack thereof). Additionally, in the case where a positive PhyloCSF score is observed, steps are delineated to further analyze microprotein-coding potential and efficiently generate multiple species alignments of the identified amino acid sequences to illustrate cross-species sequence conservation. Lastly, several additional publicly available resources and tools are introduced in the discussion to survey identified microprotein characteristics, including predicted domain structures and insight into putative microprotein function.

Protocol

The protocol outlined below details steps to load and navigate the PhyloCSF browser tracks on the UCSC Genome Browser (generated by Mudge et al.49). For general questions regarding the UCSC Genome Browser, an extensive Genome Browser User's Guide can be found here: https://genome.ucsc.edu/goldenPath/help/hgTracksHelp.html.

1. Loading the PhyloCSF Track Hub to the UCSC Genome Browser

  1. Open an internet browser window and navigate to the UCSC Genome Browser (https://genome.ucsc.edu/).
  2. Under the Our tools heading, select the Track Hubs option.
    NOTE: The Track Hubs option can also be found under the My Data tab.
  3. In the Public Hubs tab, type PhyloCSF into the Search terms box. Click on the Search Public Hubs button.
  4. Connect to PhyloCSF by clicking on the Connect button for the Hub Name PhyloCSF (Description: Evolutionary protein-coding potential as measured by PhyloCSF).
    ​NOTE: This Track Hub will load to numerous assemblies, including human (hg19 and hg38) and mouse (mm10 and mm39).
  5. After clicking on connect, wait to be redirected to the UCSC Genome Browser Gateway page (https://genome.ucsc.edu/cgi-bin/hgGateway).

2. Navigating to genes of interest using Gene Identifiers

  1. Select the species and genome assembly to query. To query a different species (e.g., mouse), select the species of interest under the Browse/Select Species heading by clicking on the appropriate icon, or type the species into the text box that says, Enter species, common name or assembly ID.
    NOTE: The assembly is listed directly under the Find Position heading. Typically, the default is the Human Assembly (e.g., Dec. 2009 [GRCh37/hg19]).
  2. Choose the assembly to search under the Find Position heading using the dropdown menu.
  3. Enter the position, gene symbol, or search terms in the Position/Search Term box and click on Go to navigate to a gene of interest on the Genome Browser.
  4. If the search resulted in multiple matches, wait to be redirected to a page that requires the selection of a position of interest. Click on the appropriate gene of interest.

3. Navigating to genomic regions of interest using sequence information

  1. Navigate to the UCSC Genome Browser (https://genome.ucsc.edu/) and select the BLAST-Like Alignment Tool (BLAT) under the Our tools heading to query a specific DNA or protein sequence. Alternatively, hover the cursor over the Tools tab and select the Blat option or follow this link: https://genome.ucsc.edu/cgi-bin/hgBlat.
  2. Select the species (Genome) and Assembly of interest using the dropdown menus.
  3. Define the Query type using the dropdown menu.
  4. Paste the sequence of interest into the BLAT Search Genome text box and click Submit.
  5. Click on the browser link under the ACTIONS heading to navigate to the genomic region of interest.

4. Identifying conserved sORFs using PhyloCSF Track Data

  1. Visually scan the genomic area of interest for positively scoring PhyloCSF regions (Figure 1).
    NOTE: For a detailed explanation of how to visually interpret PhyloCSF scores on the UCSC Genome Browser, see the representative results section below.
  2. Use the zoom feature to magnify regions of interest to examine sequence characteristics and search for start/stop codons. To zoom in manually, hold the shift key and click and hold the mouse button while dragging along the region of interest. Alternatively, use the zoom in and zoom out buttons at the top of the page to navigate (1.5x, 3x, 10x, or base zoom options are available).
    NOTE: Before using the zoom in/zoom out buttons, it is necessary to reposition the gene so that the region of interest is in the middle of the screen. To perform this action, click on the image and drag it left or right to move the genomic region horizontally as desired or use the move arrows at the top of the page.
  3. Zoom in until the nucleotide (base) sequence is visible.
    NOTE: The nucleotide sequence will appear directly above the +1 Smoothed PhyloCSF score.
  4. Visually scan the nucleotide sequence near the beginning and end of the positively scoring PhyloCSF regions to identify putative start (ATG) and stop (TGA/TAA/TAG) codons.
    NOTE: If the gene of interest is on the minus strand of DNA, the start and stop codons will be the reverse complement (i.e., CAT for the start codon and TCA/TTA/CTA for the stop codon).

5. Viewing homologous regions in other genomes

  1. Hover the mouse over the View heading at the top of the page and click on the In Other Genomes (Convert) option.
  2. Define the genome of interest using the dropdown menu below the New Genome heading.
  3. Select the genomic assembly of interest using the dropdown menu under the New Assembly heading, then click the Submit button.
  4. Once the browser returns a list of regions in the new assembly with similarity, click on the chromosome position link to navigate to the homologous region of interest.
    NOTE: The percentage of total bases (nucleotides) and the span that are covered by the region will be defined for each region listed. The higher the percentage of matching bases, the higher the conservation is for the region of interest.
  5. Follow the same navigational strategies detailed in Section 4 to analyze the sequence.

6. Generating multi-species sequence alignments for microproteins of interest

  1. Click on the gene of interest in the GENCODE track on the UCSC Genome Browser (indicated in Figure 1A with a blue box) to navigate to the gene description page.
  2. Under the Sequence and Links to Tools and Databases heading, click on the link in the table that reads Other Species FASTA.
  3. Click on the boxes associated with the species of interest to select them. Click on Submit. Copy and paste the sequences appearing at the bottom of the page in FASTA format into a word processing document.
  4. Open a second browser window and navigate to the Clustal Omega Multiple Sequence Alignment tool52 on the European Bioinformatics Institute (EMBL-EBI) website53,54: https://www.ebi.ac.uk/Tools/msa/clustalo/.
  5. Paste the sequence files that are still on the clipboard into the box in STEP 1 that reads sequences in any supported format. Scroll to the bottom of the page and click on Submit. Look below the aligned results (in black font) for symbols that indicate the degree of conservation of each amino acid (symbols are defined in Table 1).
    NOTE: It may take several minutes to generate the alignment.
  6. To view the amino acid properties in color, click on the Show Colors link directly above the sequences to color the amino acids according to their properties (defined in Table 2).
  7. Copy and paste the sequence alignment into a word processing or slideshow program to generate a figure or illustration file (e.g., Figure 2).
    NOTE: Use a monospaced font for the alignment such as Courier.
  8. To view other outputs from the Clustal Omega results page, click on the appropriate tabs (i.e., Guide Tree or Phylogenetic Tree).
  9. Click on the Results Viewers tab for options to view the sequence information using Jalview, a free program that specializes in multiple sequence alignment editing, visualization, and analysis55, or to access direct links to MView and Simple Phylogeny56.

Results

Here we will use the validated microprotein mitoregulin (Mtln) as an example to demonstrate how a conserved sORF will generate a positive PhyloCSF score that can be easily visualized and analyzed on the UCSC Genome Browser. Mitoregulin was previously annotated as a noncoding RNA (formerly human gene ID LINC00116 and mouse gene ID 1500011K16Rik). Comparative genomics and sequence conservation analysis methods played a critical role in its initial discovery40,

Discussion

The protocol presented here provides detailed instructions on how to interrogate genomic regions of interest for microprotein-coding potential using PhyloCSF on the user-friendly UCSC Genome Browser48,49,50,51. As detailed above, PhyloCSF is a powerful comparative genomics algorithm that integrates phylogenetic models and codon substitution frequencies to identify evolutionary signatures that a...

Disclosures

The authors declare that they have no competing financial interests.

Acknowledgements

This work was supported by grants from the National Institutes of Health (HL-141630 and HL-160569) and Cincinnati Children's Research Foundation (Trustee Award).

Materials

NameCompanyCatalog NumberComments
WebsiteWebsite AddressRequirements
Clustal Omega Multiple Sequence Alignment Toolhttps://www.ebi.ac.uk/Tools/msa/clustalo/Web browserMultiple sequence alignment program for the efficient alignment of FASTA sequences (i.e. for cross-species comparison of identified microproteins)
COXPRESSdbhttps://coxpresdb.jpWeb browserProvides co-regulated gene relationships to estimate gene functions
EMBL-EBI Bioinformatics Tools FAQshttps://www.ebi.ac.uk/seqdb/confluence/display/JDSAT/Bioinformatics+Tools+FAQWeb browserFrequently Asked Questions (FAQs) for EMBL-EBI tools. Includes the color coding key for protein sequence alignments
European Bioinformatics Institute (EMBL-EBI),
Tools and Data Resources		https://www.ebi.ac.uk/services/allWeb browserComprehensive list of freely available websites, tools and data resources
Expasy - Swiss Bioinformatics Resource Portalhttps://www.expasy.orgWeb browserSuite of bioinformatic tools and resources for protein sequence analysis that is maintained by the Swiss Institute of Bioinformatics (SIB)
National Center for Biotechnology Information (NCBI)
Conserved Domain Search		https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgiWeb browserSearch tool to identify conserved domains within protein or coding nucleotide sequences
Pfam 35http://pfam.xfam.orgWeb browserProtein family (Pfam) database, provides alignments and classification of protein families and domains
PhyloCSF Track Hub Description https://genome.ucsc.edu/cgi-bin/hgTrackUi?hgsid=1267045267_TEc99h2oW5Q
edaCd4ir8aZ65ryaD&db=mm10
&c=chr2&g=hub_109801_
PhyloCSF_smooth		Web browserDetailed description of the Smoothed PhyloCSF tracks and PhyloCSF Track Hub
   
   
   
   
   
SignalP 6.0https://services.healthtech.dtu.dk/service.php?SignalP-6.0Web browserPredicts the presence of signal peptides and the location of their cleavage sites
TMHMM - 2.0https://services.healthtech.dtu.dk/service.php?TMHMM-2.0Web browserPrediction of transmembrane helices in proteins
UCSC Genome Browser BLAT Searchhttps://genome.ucsc.edu/cgi-bin/hgBlatWeb browserTool used to find genomic regions using DNA or protein sequence information
UCSC Genome Browser Gatewayhttps://genome.ucsc.edu/cgi-bin/hgGatewayWeb browserDirect link to the UCSC Genome Browser Gateway
UCSC Genome Browser Homehttps://genome.ucsc.edu/Web browserHome website for the UCSC Genome Browser
UCSC Genome Browser Track Data Hubshttps://genome.ucsc.edu/cgi-bin/hgHubConnect#publicHubsWeb browserDirect link to Track Data Hubs/Public Hubs database to search for and load the PhyloCSF Tracks
UCSC Genome Browser User Guidehttps://genome.ucsc.edu/goldenPath/help/hgTracksHelp.htmlWeb browserComprehensive user guide detailing how to navigate the UCSC Genome Browser
WoLF PSORThttps://wolfpsort.hgc.jpWeb browserProtein subcellular localization prediction tool

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