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An improved de novo genome assembly of the common marmoset genome yields improved contiguity and increased mapping rates of sequence data
BACKGROUND: The common marmoset (Callithrix jacchus) is one of the most studied primate model organisms. However, the marmoset genomes available in the public databases are highly fragmented and filled with sequence gaps, hindering research advances related to marmoset genomics and transcriptomics....
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7114785/ https://www.ncbi.nlm.nih.gov/pubmed/32241258 http://dx.doi.org/10.1186/s12864-020-6657-2 |
Sumario: | BACKGROUND: The common marmoset (Callithrix jacchus) is one of the most studied primate model organisms. However, the marmoset genomes available in the public databases are highly fragmented and filled with sequence gaps, hindering research advances related to marmoset genomics and transcriptomics. RESULTS: Here we utilize single-molecule, long-read sequence data to improve and update the existing genome assembly and report a near-complete genome of the common marmoset. The assembly is of 2.79 Gb size, with a contig N50 length of 6.37 Mb and a chromosomal scaffold N50 length of 143.91 Mb, representing the most contiguous and high-quality marmoset genome up to date. Approximately 90% of the assembled genome was represented in contigs longer than 1 Mb, with approximately 104-fold improvement in contiguity over the previously published marmoset genome. More than 98% of the gaps from the previously published genomes were filled successfully, which improved the mapping rates of genomic and transcriptomic data on to the assembled genome. CONCLUSIONS: Altogether the updated, high-quality common marmoset genome assembly provide improvements at various levels over the previous versions of the marmoset genome assemblies. This will allow researchers working on primate genomics to apply the genome more efficiently for their genomic and transcriptomic sequence data. |
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