SNPs vs. microhaplotypes: challenges and advantages in alfalfa breeding

Authors: MEDINA, CESAR - University Of Minnesota; Heuschele, Deborah; ZHAO, DONGYAN - Cornell University; LIN, MENG - Cornell University; BEIL, CRAIG - Cornell University; SHEEHAN, MOIRA - Cornell University; Xu, Zhanyou

Submitted to: Plant and Animal Genome Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 1/10/2025
Publication Date: 1/15/2025
Citation: Medina, C.M., Heuschele, D.J., Zhao, D., Lin, M., Beil, C.T., Sheehan, M.J., Xu, Z. 2025. SNPs vs. microhaplotypes: challenges and advantages in alfalfa breeding. Plant and Animal Genome Conference. San Diego, California, January 10-15, 2025.

Interpretive Summary:

Technical Abstract: With the advent of high-throughput targeted sequencing, SNPs have become the most widely used markers due to their abundance in the genome. Specifically, biallelic SNP markers are commonly applied in genomic association and genomic prediction approaches. However, the binary nature of biallelic SNPs limits the information captured, affecting diversity studies and the identification of rare alleles. In this study, we present a methodology for generating multiallelic markers, named as “microhaplotypes”, from a DArTag genotyping panel, and we compare the genetic diversity and genomic association results obtained using target SNPs and microhaplotype markers for four root system architecture traits (taproot diameter [TD], first lateral root distance [LD], lateral root number [LN], and fibrous score [FS]) across seven populations under divergent selection. We demonstrate that the use of microhaplotypes reduces the number of monomorphic markers by 10%, increases detection rate of genetic diversity by 50%, and enables the identification of multiple private alleles by population. Moreover, genomic association studies identified four markers using target SNPs and 11 markers using microhaplotype markers for TD, LD, and LN. The main challenge with using microhaplotype markers is the lack of specialized software to handle multiallelic markers, which restricts genomic prediction analyses to target SNPs. However, we foresee that in the future, new models will accommodate multiallelic markers in polyploid crops like alfalfa. Overall, we demonstrate that microhaplotypes capture more genetic information, exhibiting higher diversity values and identifying more associated markers compared to target SNPs.