Dataset Information

Development of SSR markers in Paeonia based on De Novo transcriptomic assemblies.

ABSTRACT: Peony is a famous ornamental and medicinal plant in China, and peony hybrid breeding is an important means of germplasm innovation. However, research on the genome of this species is limited, thereby hindering the genetic and breeding research on peony. In the present study, simple sequence repeat (SSR) locus analysis was performed on expressed sequence tags obtained by the transcriptome sequencing of Paeonia using Microsatellite software. Primers with polymorphism were obtained via polymerase chain reaction amplification and electrophoresis. As a result, a total of 86,195 unigenes were obtained by assembling the transcriptome data of Paeonia. Functional annotations were obtained in seven functional databases including 49,172 (Non-Redundant Protein Sequence Database: 57.05%), 38,352 (Nucleotide Sequence Database: 44.49%), 36,477 (Swiss Prot: 42.32%), 38,905 (Clusters of Orthologous Groups for Eukaryotic Complete Genomes: 45.14%), 37,993 (Kyoto Encyclopedia of Genes and Genomes: 44.08%), 26,832 (Gene Ontology: 31.13%) and 37,758 (Pfam: 43.81%) unigenes. Meanwhile, 21,998 SSR loci were distributed in 17,567 unigenes containing SSR sequences, and the SSR distribution frequency was 25.52%, with an average of one SSR sequence per 4.66 kb. Mononucleotide, dinucleotide, and trinucleotide were the main repeat types, accounting for 55.74%, 25.58%, and 13.21% of the total repeat times, respectively. Forty-five pairs of the 100 pairs of primers selected randomly could amplify clear polymorphic bands. The polymorphic primers of these 45 pairs were used to cluster and analyze 16 species of peony. The new SSR molecular markers can be useful for the study of genetic diversity and marker-assisted breeding of peony.

SUBMITTER: He D

PROVIDER: S-EPMC6991952 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Development of SSR markers in Paeonia based on De Novo transcriptomic assemblies.

He Dan D Zhang Jiaorui J Zhang Xuefeng X He Songlin S Xie Dongbo D Liu Yang Y Li Chaomei C Wang Zheng Z Liu Yiping Y

PloS one 20200130 1

Peony is a famous ornamental and medicinal plant in China, and peony hybrid breeding is an important means of germplasm innovation. However, research on the genome of this species is limited, thereby hindering the genetic and breeding research on peony. In the present study, simple sequence repeat (SSR) locus analysis was performed on expressed sequence tags obtained by the transcriptome sequencing of Paeonia using Microsatellite software. Primers with polymorphism were obtained via polymerase c ...[more]

PMID: 31999761

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Project description:BackgroundThe medicinal legume Mucuna pruriens (L.) DC. has attracted attention worldwide as a source of the anti-Parkinson's drug L-Dopa. It is also a popular green manure cover crop that offers many agronomic benefits including high protein content, nitrogen fixation and soil nutrients. The plant currently lacks genomic resources and there is limited knowledge on gene expression, metabolic pathways, and genetics of secondary metabolite production. Here, we present transcriptomic resources for M. pruriens, including a de novo transcriptome assembly and annotation, as well as differential transcript expression analyses between root, leaf, and pod tissues. We also develop microsatellite markers and analyze genetic diversity and population structure within a set of Indian germplasm accessions.ResultsOne-hundred ninety-one million two hundred thirty-three thousand two hundred forty-two bp cleaned reads were assembled into 67,561 transcripts with mean length of 626 bp and N50 of 987 bp. Assembled sequences were annotated using BLASTX against public databases with over 80% of transcripts annotated. We identified 7,493 simple sequence repeat (SSR) motifs, including 787 polymorphic repeats between the parents of a mapping population. 134 SSRs from expressed sequenced tags (ESTs) were screened against 23?M. pruriens accessions from India, with 52 EST-SSRs retained after quality control. Population structure analysis using a Bayesian framework implemented in fastSTRUCTURE showed nearly similar groupings as with distance-based (neighbor-joining) and principal component analyses, with most of the accessions clustering per geographical origins. Pair-wise comparison of transcript expression in leaves, roots and pods identified 4,387 differentially expressed transcripts with the highest number occurring between roots and leaves. Differentially expressed transcripts were enriched with transcription factors and transcripts annotated as belonging to secondary metabolite pathways.ConclusionsThe M. pruriens transcriptomic resources generated in this study provide foundational resources for gene discovery and development of molecular markers. Polymorphic SSRs identified can be used for genetic diversity, marker-trait analyses, and development of functional markers for crop improvement. The results of differential expression studies can be used to investigate genes involved in L-Dopa synthesis and other key metabolic pathways in M. pruriens.

Project description:The current revolution in genomics has been made possible by software tools called genome assemblers, which stitch together DNA fragments "read" by sequencing machines into complete or nearly complete genome sequences. Despite decades of research in this field and the development of dozens of genome assemblers, assessing and comparing the quality of assembled genome sequences still relies on the availability of independently determined standards, such as manually curated genome sequences, or independently produced mapping data. These "gold standards" can be expensive to produce and may only cover a small fraction of the genome, which limits their applicability to newly generated genome sequences. Here we introduce a de novo? probabilistic measure of assembly quality which allows for an objective comparison of multiple assemblies generated from the same set of reads. We define the quality of a sequence produced by an assembler as the conditional probability of observing the sequenced reads from the assembled sequence. A key property of our metric is that the true genome sequence maximizes the score, unlike other commonly used metrics.We demonstrate that our de novo? score can be computed quickly and accurately in a practical setting even for large datasets, by estimating the score from a relatively small sample of the reads. To demonstrate the benefits of our score, we measure the quality of the assemblies generated in the GAGE and Assemblathon 1 assembly "bake-offs" with our metric. Even without knowledge of the true reference sequence, our de novo? metric closely matches the reference-based evaluation metrics used in the studies and outperforms other de novo? metrics traditionally used to measure assembly quality (such as N50). Finally, we highlight the application of our score to optimize assembly parameters used in genome assemblers, which enables better assemblies to be produced, even without prior knowledge of the genome being assembled.Likelihood-based measures, such as ours proposed here, will become the new standard for de novo? assembly evaluation.

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Development of SSR markers in Paeonia based on De Novo transcriptomic assemblies.

Publications

Development of SSR markers in Paeonia based on De Novo transcriptomic assemblies.

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