Dataset Information

Characterizing microsatellite polymorphisms using assembly-based and mapping-based tools.

ABSTRACT: Microsatellite polymorphism has always been a challenge for genome assembly and sequence alignment due to sequencing errors, short read lengths, and high incidence of polymerase slippage in microsatellite regions. Despite the information they carry being very valuable, microsatellite variations have not gained enough attention to be a routine step in genome sequence analysis pipelines. After the completion of the 1000 Genomes Project, which aimed to establish the most detailed genetic variation catalog for humans, the consortium released only two microsatellite prediction sets generated by two tools. Many other large research efforts have failed to shed light on microsatellite variations. We evaluated the performance of three different local assembly methods on three different experimental settings, focusing on genotype-based performance, coverage impact, and preprocessing including flanking regions. All these experiments supported our initial expectations on assembly. We also demonstrate that overlap-layout-consensus (OLC)-basedassembly methods show higher sensitivity to microsatellite variant calling when compared to a de Bruijn graph-based approach. We conclude that assembly with OLC is the better method for genotyping microsatellites. Our pipeline is available at https://github.com/gulfemd/STRAssembly.

SUBMITTER: Demir G

PROVIDER: S-EPMC6710001 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Characterizing microsatellite polymorphisms using assembly-based and mapping-based tools.

Demir Gülfem G Alkan Can C

Turkish journal of biology = Turk biyoloji dergisi 20190805 4

Microsatellite polymorphism has always been a challenge for genome assembly and sequence alignment due to sequencing errors, short read lengths, and high incidence of polymerase slippage in microsatellite regions. Despite the information they carry being very valuable, microsatellite variations have not gained enough attention to be a routine step in genome sequence analysis pipelines. After the completion of the 1000 Genomes Project, which aimed to establish the most detailed genetic variation ...[more]

PMID: 31496881

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Project description:BACKGROUND: Eggplant (Solanum melongena L.) is a member of the Solanaceae family. In spite of its widespread cultivation and nutritional and economic importance, its genome has not as yet been extensively investigated. Few analyses have been carried out to determine the genetic diversity of eggplant at the DNA level, and linkage relationships have not been well characterised. As for the other Solanaceae crop species (potato, tomato and pepper), the level of intra-specific polymorphism appears to be rather limited, and so it is important that an effort is made to develop more informative DNA markers to make progress in understanding the genetics of eggplant and to advance its breeding. The aim of the present work was to develop a set of functional microsatellite (SSR) markers, via an in silico analysis of publicly available DNA sequence. RESULTS: From >3,300 genic DNA sequences, 50 SSR-containing candidates suitable for primer design were recovered. Of these, 39 were functional, and were then applied to a panel of 44 accessions, of which 38 were cultivated eggplant varieties, and six were from related Solanum species. The usefulness of the SSR assays for diversity analysis and taxonomic discrimination was demonstrated by constructing a phylogeny based on SSR polymorphisms, and by the demonstration that most were also functional when tested with template from tomato, pepper and potato. As a results of BLASTN analyses, several eggplant SSRs were found to have homologous counterparts in the phylogenetically related species, which carry microsatellite motifs in the same position. CONCLUSION: The set of eggplant EST-SSR markers was informative for phylogenetic analysis and genetic mapping. Since EST-SSRs lie within expressed sequence, they have the potential to serve as perfect markers for genes determining variation in phenotype. Their high level of transferability to other Solanaceae species can be used to provide anchoring points for the integration of genetic maps across species.

Project description:BACKGROUND: Wheat (Triticum aestivum L.) is a staple food crop worldwide. The wheat genome has not yet been sequenced due to its huge genome size (approximately 17,000 Mb) and high levels of repetitive sequences; the whole genome sequence may not be expected in the near future. Available linkage maps have low marker density due to limitation in available markers; therefore new technologies that detect genome-wide polymorphisms are still needed to discover a large number of new markers for construction of high-resolution maps. A high-resolution map is a critical tool for gene isolation, molecular breeding and genomic research. Single feature polymorphism (SFP) is a new microarray-based type of marker that is detected by hybridization of DNA or cRNA to oligonucleotide probes. This study was conducted to explore the feasibility of using the Affymetrix GeneChip to discover and map SFPs in the large hexaploid wheat genome. RESULTS: Six wheat varieties of diverse origins (Ning 7840, Clark, Jagger, Encruzilhada, Chinese Spring, and Opata 85) were analyzed for significant probe by variety interactions and 396 probe sets with SFPs were identified. A subset of 164 unigenes was sequenced and 54% showed polymorphism within probes. Microarray analysis of 71 recombinant inbred lines from the cross Ning 7840/Clark identified 955 SFPs and 877 of them were mapped together with 269 simple sequence repeat markers. The SFPs were randomly distributed within a chromosome but were unevenly distributed among different genomes. The B genome had the most SFPs, and the D genome had the least. Map positions of a selected set of SFPs were validated by mapping single nucleotide polymorphism using SNaPshot and comparing with expressed sequence tags mapping data. CONCLUSION: The Affymetrix array is a cost-effective platform for SFP discovery and SFP mapping in wheat. The new high-density map constructed in this study will be a useful tool for genetic and genomic research in wheat.

Dataset Information

Characterizing microsatellite polymorphisms using assembly-based and mapping-based tools.

Publications

Characterizing microsatellite polymorphisms using assembly-based and mapping-based tools.

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