CucurQTL Documentation

Welcome to the comprehensive documentation for CucurQTL - a specialized database for Quantitative Trait Loci (QTL) data across cucurbit species. This documentation will guide you through all features and functionalities of the database.

1.1 What are QTLs?

A Quantitative Trait Locus (QTL) is a region of DNA associated with a particular phenotypic trait that varies in degree. Unlike simple Mendelian traits controlled by single genes, quantitative traits (like fruit size, yield, or disease resistance) are influenced by multiple genes and environmental factors.

QTL analysis helps researchers:

• Identify genomic regions controlling important agricultural traits
• Understand the genetic architecture of complex traits
• Develop markers for marker-assisted selection (MAS)
• Accelerate crop breeding programs

1.2 Database Purpose

CucurQTL serves as a comprehensive repository for QTL data across multiple cucurbit species, including cucumber, watermelon, melon, pumpkin, and other economically important gourds. The database aims to:

1.3 Key Features

• QTL Search: Filter and search QTLs by species, trait, sub-trait, and parameters
• JBrowse2 Integration: Interactive genome browser for visualizing genomic features
• Functional Annotation: Search gene annotations within specific genomic regions
• Genome Downloads: Access reference genomes, GFF annotations, and protein sequences
• Data Export: Download search results in CSV and Excel formats
• Contributor System: Submit QTL data for review and approval by administrators
• Admin Dashboard: Comprehensive admin panel for data management and user approvals

2. Application Features

2.1 QTL Database Search

The QTL search interface provides powerful filtering capabilities to find relevant QTL data:

Search Filters

• Species: Select from 10 cucurbit species (Cucumber, Watermelon, Melon, etc.)
• Trait Category: Major trait categories (Fruit Quality, Disease Resistance, Vegetative, etc.)
• Sub-trait: Specific traits within categories (Fruit Length, Powdery Mildew Resistance)
• Parameter: Measured parameters (Brix content, Length in cm, etc.)

Results Display

Search results include:

• QTL name and associated linkage group
• Position interval on the chromosome
• LOD score and phenotypic variance explained (PVE/R²)
• Associated markers and mapping method
• Reference publication with DOI links

2.2 JBrowse2 Genome Browser

CucurQTL integrates JBrowse2, a modern genome browser that allows interactive visualization of genomic data:

Available Tracks

• Reference Sequence: View nucleotide sequences at any zoom level
• Gene Annotations: Browse gene models, exons, and UTRs
• GFF Tracks: Visualize genomic features from annotation files

Navigation Features

• Search by gene name or genomic coordinates
• Zoom in/out with mouse scroll or controls
• Pan by clicking and dragging
• Switch between species assemblies

2.3 Functional Annotation Search

The Functional Annotation tool allows you to search for genes and genomic features within specific regions:

Search Parameters

• Species: Select the species of interest
• Chromosome: Specify the chromosome number
• Start Position: Beginning of the genomic region (bp)
• End Position: End of the genomic region (bp)

Available Annotation Fields

2.4 Reference Genome Resources

Download reference genomes and annotation files for all 10 cucurbit species:

Available Downloads

• Genome FASTA: Complete reference genome sequences (.fa.gz)
• GFF Annotations: Gene and feature annotations (.gff3.gz)
• Protein Sequences: Predicted protein sequences (.fa.gz)

2.5 Contributor System

CucurQTL features a comprehensive data submission system allowing researchers to contribute QTL data:

For Contributors

• Registration: Create an account with your institutional details and ORCID ID
• CSV Upload: Submit QTL data in standardized CSV format
• Upload Tracking: Monitor the status of your submissions
• Email Notifications: Receive updates when your data is approved

CSV Format Requirements

Upload files must include these columns:

Species, Trait, Sub-Trait, Parameter, Cross, Population type,
Method/Model, Qtl Name, Linkage Group (LG), Position/interval (cM/Mb),
Associated Marker, LOD, PVE/R2, Reference, Doi

Admin Review Process

• New registrations require admin approval before access is granted
• Uploaded data is staged for review before being added to the main database
• Admins can approve, reject, or request revisions
• Approved data is automatically imported with proper foreign key relationships

3. User Guide

3.1 Searching QTLs

1. Navigate to QTL from the main navigation menu
2. Use the cascading dropdown filters:
   • First, select a Species (e.g., Cucumber)
   • Choose a Trait Category (e.g., Fruit Quality)
   • Select a Sub-trait (e.g., Fruit Length)
   • Optionally filter by Parameter
3. Click "Search" to retrieve matching QTLs
4. Browse results in the interactive data table
5. Click "Download CSV" or "Download Excel" to export results

3.2 Using JBrowse2 Genome Browser

1. Navigate to Tools → JBrowse2 from the menu
2. Select a species/assembly from the dropdown
3. Enter a genomic location in the search box (e.g., Chr1:1000000-2000000)
4. Use the track selector to enable/disable annotation tracks
5. Click on features to view detailed information
6. Use mouse scroll to zoom, click-drag to pan

3.3 Searching Functional Annotations

1. Navigate to Tools → Functional Annotation
2. Select a Species from the dropdown
3. Enter genomic coordinates:
   • Chromosome: Enter chromosome number (e.g., 3)
   • Start Position: Start of region in base pairs
   • End Position: End of region in base pairs
4. Click "Add More" to search multiple regions simultaneously
5. Select which annotation columns to display using checkboxes
6. Click "Search" to retrieve annotations
7. Export results using the download button

3.4 Downloading Reference Genomes

1. Navigate to Tools → Genomes
2. Browse the species cards to find your organism of interest
3. Each species card provides three download options:
   • Download Genome: Reference FASTA sequence
   • Download GFF: Gene annotations
   • Download Protein: Predicted protein sequences
4. Click the button to start download (files are gzip compressed)

4. Database Schema

4.1 Core QTL Tables

The database uses a normalized relational structure to organize QTL data efficiently:

species

Stores cucurbit species information.

traits

Major trait categories.

sub_traits

Specific traits within categories.

parameters

Measurable parameters for each sub-trait.

qtls

Main QTL data table containing all QTL records.

4.2 Contributor System Tables

Tables supporting the data submission and approval workflow:

contributors

Registered data contributors/curators.

data_uploads

Tracks all data upload submissions.

staged_qtl_data

Temporary storage for uploaded QTL data awaiting approval.

admin_users

Administrative users with approval permissions.

4.3 Genomic Annotation Table

genomic_sequences

Stores functional annotation data for genes and genomic features.

5. Technical Implementation

5.1 Technologies Used

Database Indexes

Optimized indexes for common query patterns:

-- QTL table indexes
CREATE INDEX idx_species_trait ON qtls(species_id, trait_id);
CREATE INDEX idx_qtl_name ON qtls(qtl_name);
CREATE INDEX idx_linkage_group ON qtls(linkage_group);

-- Reference table indexes  
CREATE INDEX idx_reference_year ON reference_list(publication_year);
CREATE INDEX idx_reference_authors ON reference_list(authors(255));

-- Contributor system indexes
CREATE INDEX idx_contributor_status ON contributors(status);
CREATE INDEX idx_contributor_email ON contributors(email);
CREATE INDEX idx_upload_status ON data_uploads(status);
CREATE INDEX idx_upload_contributor ON data_uploads(contributor_id);
CREATE INDEX idx_staged_upload ON staged_qtl_data(upload_id);

-- Genomic sequences indexes
CREATE INDEX idx_genomic_species ON genomic_sequences(genomic_species);
CREATE INDEX idx_genomic_chromosome ON genomic_sequences(chromosome);
CREATE INDEX idx_genomic_position ON genomic_sequences(start_position, end_position);

5.2 Query Examples

Example 1: Find QTLs for Cucumber Fruit Length

SELECT q.qtl_name, q.linkage_group, q.position_interval, 
       q.lod, q.pve_r2, r.authors, r.publication_year
FROM qtls q
JOIN species s ON q.species_id = s.species_id
JOIN sub_traits st ON q.sub_trait_id = st.sub_trait_id
JOIN reference_list r ON q.reference_id = r.reference_id
WHERE s.species_name = 'Cucumis sativus'
  AND st.sub_trait_name LIKE '%fruit length%';

Example 2: Get Annotations in a Genomic Region

SELECT sequence, feature, name, symbol, 
       start_position, end_position, strand,
       go_ids, go_names, hit_desc
FROM genomic_sequences
WHERE genomic_species = 'Cucumis sativus'
  AND chromosome = 3
  AND start_position >= 10000000
  AND end_position <= 15000000
ORDER BY start_position;

Example 3: Count QTLs by Species

SELECT s.species_name, COUNT(*) as qtl_count
FROM qtls q
JOIN species s ON q.species_id = s.species_id
GROUP BY s.species_name
ORDER BY qtl_count DESC;

6. Available Cucurbit Species

CucurQTL currently includes data for 10 economically important cucurbit species:

7. Glossary of Terms

8. Future Development

Planned enhancements for upcoming releases:

Recent Updates

• Contributor Portal: Full registration and data submission system
• Admin Dashboard: Comprehensive management interface for approvals
• CSV Upload: Flexible header mapping with auto-extraction of authors/year
• Email Notifications: Automated approval notifications via EmailJS
• Direct Admin Upload: Admins can upload QTL data directly without staging

9. Contact Information

For questions, feedback, or data submission inquiries: