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基于 SLAF-seq 技术的石斛兰 SNP 标记开发及亲缘 关系分析.

Authors :
崔学强
黄昌艳
邓杰玲
李先民
李秀玲
张自斌
Source :
Biotechnology Bulletin. 2023, Vol. 39 Issue 6, p141-148. 8p.
Publication Year :
2023

Abstract

The genetic relationship of the collected Dendrobium germplasm resources was analyzed by SNP marker technology to provide theoretical basis for the selection of new varieties breeding parents. Total 60 Dendrobium germplasm resources were used for SNP marker development and genetic relationship analysis using specific-locus amplified fragment sequencing technology(SLAF-seq). The sequencing data of each sample were statistically analyzed, and 157.34 Mb Clean Reads data were obtained. The Reads data of each sample ranged from 576 195 to 5 359 710. The average sequencing quality value(Q30)and GC content of samples was 93.85% and 40.16%. Through sequencing data analysis, a total of 1 337 217 SLAF tags and 1 049 638 polymorphic SLAF tags were obtained. The average sequencing depth of the tags was 9.63×.A total of 11 248 186 population SNP markers were developed. The number of SNP markers in each sample ranged from 694 015 to 6 367 379. The integrity ratio was 2.71% to 24.89%, and the hetloci ratio was 1.13% to 5.74%. The population SNPs were filtered, and a total of 31 499 highly consistent and effective SNP markers were obtained. The phylogenetic tree was constructed by using the SNP markers obtained. The 60 Dendrobium germplasm resources were divided into 3 subgroups. These three subgroups contained germplasm resources: Q1(3), Q2(21), and Q3(36). The results of germplasm clustering were basically consistent with the morphological classification. Using SLAF-seq technology can efficiently and accurately develop SNP markers suitable for the genetic analysis of Dendrobium. The SNP markers developed may provide molecular basis for Dendrobium breeding, genetic map construction, variety identification and association analysis of agronomic traits. [ABSTRACT FROM AUTHOR]

Details

Language :
Chinese
ISSN :
10025464
Volume :
39
Issue :
6
Database :
Academic Search Index
Journal :
Biotechnology Bulletin
Publication Type :
Academic Journal
Accession number :
164973183
Full Text :
https://doi.org/10.13560/j.cnki.biotech.bull.1985.2022-1386