How are SSR markers developed? Why did they become the most widely used marker system before the SNPs became the markers of choice?

SSR (Simple Sequence Repeat) markers, also known as microsatellites, are DNA sequences consisting of short, tandemly repeated motifs (typically 1-6 base pairs in length) dispersed throughout the genome. SSR markers are developed through a process of identifying, isolating, and characterizing regions of DNA containing these repetitive sequences. Here's how SSR markers are developed:

·         Genomic DNA Isolation: The first step in SSR marker development is isolating high-quality genomic DNA from the target organism or population of interest. This DNA serves as the template for identifying SSR loci within the genome.

·         SSR Loci Identification: Computational tools or laboratory techniques are used to screen genomic DNA libraries or sequence databases to identify regions containing SSR motifs. These regions are often identified based on the presence of repeated sequences with a minimum number of repeat units (e.g., di-, tri-, tetra-nucleotide repeats).

·         Primer Design: Primers are designed flanking the SSR loci to amplify the DNA region containing the repeat motif using PCR. The primers are typically designed to anneal to conserved sequences flanking the repeat region, allowing for specific amplification of the SSR locus.

·         PCR Amplification and Fragment Analysis: The designed primer pairs are used in PCR amplification reactions with genomic DNA as the template. The resulting PCR products are then analyzed using gel electrophoresis or automated capillary electrophoresis to separate DNA fragments based on size.

·         Allele Size Determination: The size of the PCR-amplified DNA fragments is determined by comparing them to size standards or reference samples. The number of repeat units in the SSR locus can be inferred based on the size difference between alleles.

·         Marker Validation and Characterization: SSR markers are validated and characterized by assessing their polymorphism, reproducibility, and Mendelian inheritance patterns across different individuals or populations. Validated SSR markers are then used for various genetic studies, including genetic mapping, diversity analysis, marker-assisted selection, and population genetics.

SSR markers became the most widely used marker system before SNPs (Single Nucleotide Polymorphisms) became the markers of choice for several reasons:

·         High Polymorphism: SSR markers are highly polymorphic, with multiple alleles segregating at each locus within a population. This high level of polymorphism makes SSRs valuable for genetic mapping, diversity analysis, and population genetics studies.

Codominant Inheritance: SSR markers exhibit codominant inheritance, meaning that both alleles at a locus are expressed in heterozygous individuals. This allows for more precise estimation of allele frequencies and heterozygosity levels within populations.

·         Ease of Detection: SSR markers can be easily detected and scored using gel electrophoresis or automated fragment analysis systems. This simplicity of detection and scoring makes SSRs accessible to researchers with basic molecular biology skills and equipment.

·         Transferability: SSR markers are often transferable across related species or populations within the same genus, facilitating comparative genomics and genetic studies in diverse organisms.

·         Information Content: SSR markers provide information on genetic diversity, population structure, and evolutionary relationships due to their high polymorphism and codominant nature.

While SSR markers were widely used and remain valuable tools in genetics and genomics, SNPs have become the markers of choice for many applications due to their abundance, genome-wide distribution, amenability to high-throughput genotyping platforms, and ease of analysis. Additionally, SNPs offer advantages such as lower mutation rates, reduced genotyping costs, and greater genomic coverage compared to SSRs, making them ideal for large-scale genetic studies and genomic applications.