微卫星
生物
基因分型
植物
树(集合论)
序列(生物学)
生态学
遗传学
基因型
基因
数学
数学分析
等位基因
作者
Alejandra Lorena Goncalves,María Victoria García,Emilie Chancerel,Olivier Lepais,Myriam Heuertz
标识
DOI:10.5091/plecevo.138834
摘要
Background and aims – Anadenanthera colubrina is a Neotropical native forest tree species with significant ecological importance in Seasonally Dry Tropical Forests. Developing genetic markers for this species is relevant for conservation, breeding, and evolutionary studies. Previously available genetic markers for A. colubrina consisted of a few microsatellites. Next-generation sequencing (NGS) strategies allow simple and cost-effective development of new SSR loci from low-coverage whole genome shotgun sequencing. The main aim was to develop microsatellite markers for sequence-based high-throughput genotyping (SSRseq) in the species and to characterize their information content against traditional capillary electrophoresis-based microsatellite data by estimating the amount of molecularly accessible size homoplasy of each locus. Additionally, the reliability of these markers for population genetic analysis was assessed by genotyping two age classes (reproductively mature trees and seedlings) in a typical location in Argentina. Key results – Sixty primer pairs targeting microsatellites were designed, of which 25 were validated with allelic error rates < 3% and genotype missingness < 20%. A significantly higher number of alleles per locus and heterozygosity was detected for SSRseq considering sequence polymorphisms compared to analysing the same data based on sequence size (length) only. Size homoplasy, calculated as the proportion of mismatches between datasets relative to the number of alleles differing in length, averaged 97.85% over all SSR loci. High levels of population genetic diversity were detected in adults and seedlings from Paranaense forests, exceeding those reported in previous studies of A. colubrina using traditional SSRs. The generated datasets increase the resolution of capillary-based microsatellite genotyping, allowing for more accurate inference of eco-evolutionary processes in non-model tree species.
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