Elucidating the process of SNPs identification in non-reference genome crops

Area of Science:

• Genomics
• Bioinformatics
• Crop Science

Background:

• Next-generation sequencing (NGS) and bioinformatics tools accelerate genome-wide single nucleotide polymorphism (SNP) identification in crops.
• SNP discovery is particularly difficult in orphan crops or those lacking a reference genome.
• Existing bioinformatics pipelines require adaptation for non-model organisms.

Purpose of the Study:

• To present a sequential methodology for *in silico* SNP identification.
• To propose and validate novel mapping strategies for SNP discovery in crops without a reference genome.
• To offer alternative bioinformatics solutions for orphan crop genetic research.

Main Methods:

• Utilized CLC Genomics software for sequence analysis and SNP identification.
• Developed and tested three mapping approaches: Common Reference Map from Progenitor Genomes (CRMPG), Step-wise Use of Progenitor Genomes (SWPG), and *de novo* Assembly of Sequence Read (DASR).
• Validated the proposed methods using dd-RAD sequencing data from two *Brassica juncea* genotypes.

Main Results:

• The proposed mapping approaches demonstrated feasibility for *in silico* SNP identification in a non-reference genome context.
• Comparative analysis of CRMPG, SWPG, and DASR provided insights into their efficacy for SNP discovery.
• Successful SNP identification was achieved in *Brassica juncea*, highlighting the potential of these methods for other orphan crops.

Conclusions:

• The developed *in silico* SNP identification strategies offer viable alternatives for crops lacking a reference genome.
• CLC Genomics software and the proposed mapping approaches can significantly aid genetic improvement in orphan crops.
• This research contributes to advancing genomic resources for understudied crop species.