bioRxivPlant Biology
A K-mer based Bulked Segregant Analysis approach to map seed traits in unphased heterozygous potato genomes
P. Sonsungsan, M. L. Nganga, M. Lieberman, K. Amundson, V. Steward, K. Plaimas, L. Comai, I. M. Henry
Abstract
High-throughput sequencing-based methods for bulked segregant analysis (BSA) allow for the rapid identification of genetic markers associated with traits of interest. BSA studies have successfully identified qualitative (binary) and quantitative trait loci using QTL mapping. However, most traditional QTL mapping approaches require a reference genome. Here, we combine high throughput short read sequencing with bulk segregant analysis of k-mers (BSA-k-mer). This method can be applied to any organism and is particularly useful for species with genomes too different from the closest sequenced genome. It is also instrumental when dealing with highly heterozygous and polyploid genomes without phased haplotype assemblies and for which a single haplotype can control a trait. Finally, it is flexible in terms of population structure. Here, we present the application of the BSA-k-mer method for the rapid identification of candidate regions related to seed spot and seed size in diploid potato. While conventional QTL mapping of parental genotypes did not generate any signal, candidate loci were identified for each trait using the BSA-k-mer approach. The seed spot loci match with previously identified loci associated with pigmentation in potato. The loci associated with seed size are novel. Both sets of loci are potentially instrumental in future breeding towards true seeds in potato. Article SummaryIdentifying genes linked to agronomic traits in potatoes is challenging because potato genomes are complex and variable. We are investigating the genetic basis of seed size and color. Seeds were categorized as large or small, or spotted or not, based on simple visual observation. Next, DNA sequences from each individual were mined for association between random short sequences (k-mers) and those two traits. This more flexible method allowed us to identify regions of the potato genome associated with both traits.
- organism: plant (other)
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- approach: deep learning
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