High-quality genetic mapping with ddRADseq in the non-model tree Quercus rubra

Area of Science:

• Genomics
• Forestry
• Population Genetics

Background:

• Restriction site associated DNA sequencing (RADseq) is a cost-effective method for genetic linkage mapping in forest trees lacking a reference genome.
• Accurate genetic maps are crucial for ordering sequence scaffolds and identifying genes related to stress resistance in forest trees.
• This study focused on optimizing ddRADseq for genetic mapping in Quercus rubra.

Purpose of the Study:

• To develop and optimize a ddRADseq approach for high-quality genetic linkage mapping in Quercus rubra.
• To assess the impact of sequencing depth on the quality and density of the genetic map.
• To evaluate the utility of ddRADseq for organisms without a reference genome.

Main Methods:

• Utilized ddRADseq technology for genetic mapping in Quercus rubra.
• Employed a digital normalization method for de novo reference generation and SAMtools for SNP calling.
• Optimized bioinformatics pipelines and premapping filters, including rigorous quality control for missing data and Mendelian deviation.

Main Results:

• Achieved high sequencing depth in parents (248×) and moderate depth in progeny (15×), yielding 78,725 SNP calls.
• Identified map inflation primarily due to multiple SNPs within the same sequence (77%).
• Generated a high-quality map with 849 SNP markers using low missing data (5%) and a 0.025 deviation threshold, but lower progeny sequencing depth proved insufficient.

Conclusions:

• ddRADseq successfully produced a moderately dense, high-quality genetic map for Quercus rubra.
• Key factors for success included high parent/progeny sequencing depth, a robust framework map, optimized bioinformatics, and stringent filters.
• Sufficient sequencing depth is critical for ddRADseq utility in organisms lacking reference genomes; improvements in reduced representation sequencing are needed to minimize missing data.