*** Supplementary Dataset 2 from the paper "Syntenic cell wall QTLs as versatile breeding tools: intraspecific allelic variability and predictability of biomass quality loci in target plant species" ***
Authors: F. Pancaldi, E.N. van Loo, S. Senio, M. Al Hassan, K. van der Cruijsen, M.J. Paulo, O. Dolstra, M.E. Schranz, L.M. Trindade
Laboratory of Plant Breeding, Wageningen University
Biosystematics, Wageningen University
Biometris, Wageningen University
Corresponding author: L.M. Trindade

***General Introduction***
This dataset reports 100 sets of random QTL regions from the genome of Miscanthus sinensis that were used for a co-localization analysis in the paper attached to the dataset itself
The dataset was created during the PhD project of Francesco Pancaldi (2018-2022)
10.4121/22068593
It is being made public both to act as supplementary data for publications and the PhD
thesis of Francesco Pancaldi, and in order for other researchers to use this data in their own work.
The research of which this dataset is part of was made possible by a grant from EU Horizon 2020 scheme.

***Data structure***
This dataset contains 100 sets of 91 random QTL regions each, identified from the genome of Miscanthus sinensis.
Each of these 100 sets mirrors the basepair size distribution of 91 QTLs that were found in Miscanthus sinensis through genome-wide association analysis (GWAS) for multiple traits related to biomass (cell wall) quality.
The 100 sets of random QTL regions were used in the publication attached to this dataset to perform a permutation analysis to test for co-localization between a set of syntenic QTLs for cell wall quality previously mapped in Miscanthus and QTLs detected by GWAS within this research (see the paper attached).

The dataset contains 9 columns:
-1: QTL_ID: a numeric ID (QTL_1-QTL_91) for each random QTL within each set
-2: Chrom: Miscanthus sinensis chromosome
-2: Start: bp starting position of each random QTL region within the Miscanthus genome, on the respective chromosome
-2: End: bp ending position of each random QTL region within the Miscanthus genome, on the respective chromosome
-2: Length: bp length of each random QTL region
-2: Overlaps_with_SQTL: YES/NO, depending on QTL co-localization for >50% of QTL length with a syntenic QTL
-2: Overlap_perc: percentage of QTL region (bp length) co-localizing with a syntenic QTL
-2: SQTL_IDs: ID of the co-localizing syntenic QTL
-2: Iteration: Number of QTLs set (1-100)

***Methodology***
The 100 sets of random QTL regions have been produced in R, by applying the size distribution of GWAS QTLs as constraint for determining the size of random QTLs.
Random QTLs could be picked across the whole miscanthus genome, to ensure complete randomness of region selection. 
Detailed explanation of the research can be found in the paper "Syntenic cell wall QTLs as versatile breeding tools: intra-specific allelic variability and predictability of biomass quality loci in target plant species" (https://doi.org/10.3390/plants12040779).

