Dataset Information

A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data.

ABSTRACT: Traditional methods for developing polymorphic microsatellite loci without reference sequences are time-consuming and labor-intensive, and the polymorphisms of simple sequence repeat (SSR) loci developed from expressed sequence tag (EST) databases are generally poor. To address this issue, in this study, we developed a new software (PSSRdt) and established an effective method for directly obtaining polymorphism details of SSR loci by analyzing diverse transcriptome data. The new method includes three steps, raw data processing, PSSRdt application, and loci extraction and verification. To test the practicality of the method, we successfully obtained 1940 potential polymorphic SSRs from the transcript dataset combined with 44 pea aphid transcriptomes. Fifty-two SSR loci obtained by the new method were selected for validating the polymorphic characteristics by genotyping in pea aphid individuals. The results showed that over 92% of SSR loci were polymorphic and 73.1% of loci were highly polymorphic. Our new software and method provide an innovative approach to microsatellite development based on RNA-seq data, and open a new path for the rapid mining of numerous loci with polymorphism to add to the body of research on microsatellites.

SUBMITTER: Tian R

PROVIDER: S-EPMC6895799 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Publications

A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data.

Tian Ruizheng R Zhang Cunhuan C Huang Yixiao Y Guo Xin X Chen Maohua M

Genes 20191111 11

Traditional methods for developing polymorphic microsatellite loci without reference sequences are time-consuming and labor-intensive, and the polymorphisms of simple sequence repeat (SSR) loci developed from expressed sequence tag (EST) databases are generally poor. To address this issue, in this study, we developed a new software (PSSRdt) and established an effective method for directly obtaining polymorphism details of SSR loci by analyzing diverse transcriptome data. The new method includes ...[more]

PMID: 31717904

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Project description:In this study, we aimed to develop novel genic simple sequence repeat (eSSR) markers and to study phylogenetic relationship among Pistacia species. Transcriptome sequencing was performed in different tissues of Siirt and Atl cultivars of pistachio (Pistacia vera). A total of 37.5-Gb data were used in the assembly. The number of total contigs and unigenes was calculated as 98,831, and the length of N50 was 1,333 bp after assembly. A total of 14,308 dinucleotide, trinucleotide, tetranucleotide, pentanucleotide, and hexanucleotide SSR motifs (4-17) were detected, and the most abundant SSR repeat types were trinucleotide (29.54%), dinucleotide (24.06%), hexanucleotide (20.67%), pentanucleotide (18.88%), and tetranucleotide (6.85%), respectively. Overall 250 primer pairs were designed randomly and tested in eight Pistacia species for amplification. Of them, 233 were generated polymerase chain reaction products in at least one of the Pistacia species. A total of 55 primer pairs that had amplifications in all tested Pistacia species were used to characterize 11 P. vera cultivars and 78 wild Pistacia genotypes belonging to nine Pistacia species (P. khinjuk, P. eurycarpa, P. atlantica, P. mutica, P. integerrima, P. chinensis, P. terebinthus, P. palaestina, and P. lentiscus). A total of 434 alleles were generated from 55 polymorphic eSSR loci with an average of 7.89 alleles per locus. The mean number of effective allele was 3.40 per locus. Polymorphism information content was 0.61, whereas observed (Ho) and expected heterozygosity (He) values were 0.39 and 0.65, respectively. UPGMA (unweighted pair-group method with arithmetic averages) and STRUCTURE analysis divided 89 Pistacia genotypes into seven populations. The closest species to P. vera was P. khinjuk. P. eurycarpa was closer P. atlantica than P. khinjuk. P. atlantica-P. mutica and P. terebinthus-P. palaestina pairs of species were not clearly separated from each other, and they were suggested as the same species. The present study demonstrated that eSSR markers can be used in the characterization and phylogenetic analysis of Pistacia species and cultivars, as well as genetic linkage mapping and QTL (quantitative trait locus) analysis.

Dataset Information

A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data.

Publications

A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data.

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