Preliminary report on the construction of Hevea brasiliensis pan-genome
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TextDescription: Proceedings of the IRRDB International Rubber Conference 2023, 20-21 February 2023, IRRDB, Kuala Lumpur, Malaysia, pp. 52-60Subject(s): Summary: Hevea brasiliensis pan-genome is a resource of genomic sequences sampled from multiple cultivars of the same species. This approach is now feasible due to the current influx of draft genome sequences in the public domain. To explore the diversity within the species, four de novo-assembled Hevea cultivar draft genomes of varying contiguity and genome representation were aligned using multiple whole genome alignment. This paper describes the preliminary outcome of pan-genome construction involving genome sequences of RRIM 600, BPM 24, GT 1 and Reyan 7-33-97. Core genome generated from the four cultivars pan-genome was 4.6 Gb. From the genome alignments, a total of 13.6 million short variants (SNPs and INDELs) were called and annotated. It is evident from the growth curve of the core and variable genes, as modelled using nonlinear regression that the pan-genome would benefit from additional meta genome data to improve the accuracy of genomic structural variations, and hence increase the robustness of the predicted core and accessory genomic regions.
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Hevea brasiliensis pan-genome is a resource of genomic sequences sampled from multiple cultivars of the same species. This approach is now feasible due to the current influx of draft genome sequences in the public domain. To explore the diversity within the species, four de novo-assembled Hevea cultivar draft genomes of varying contiguity and genome representation were aligned using multiple whole genome alignment. This paper describes the preliminary outcome of pan-genome construction involving genome sequences of RRIM 600, BPM 24, GT 1 and Reyan 7-33-97. Core genome generated from the four cultivars pan-genome was 4.6 Gb. From the genome alignments, a total of 13.6 million short variants (SNPs and INDELs) were called and annotated. It is evident from the growth curve of the core and variable genes, as modelled using nonlinear regression that the pan-genome would benefit from additional meta genome data to improve the accuracy of genomic structural variations, and hence increase the robustness of the predicted core and accessory genomic regions.
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