In silico EST-SSR Identification and Development through EST Sequences from Metroxylon sagu Rottb. for Genetic Diversity Analysis

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Devit Purwoko
Siti Zulaeha
Teuku Tajuddin
Farida Rosana Mira
Maharani Dewi Solikhah
Gemilang Rahmadara
Nurul Fitri Hanifah
Rusmanto

Abstract

Sago plant (Metroxylon sagu Rottb.) is one of the most carbohydrate-producing plants in the world. Microsatellites or simple sequence repeats (SSRs) play an important role in the genome and are used extensively compared to other molecular markers. For the first time, we are exploiting data expressed sequence tags (EST) of sago plants to identify and characterise markers in this species. EST data about sago plants are obtained through the EST database on the National Center for Biotechnology Information (NCBI) website. We obtained data of 458 Kb (412 contig) with a maximum and minimum length of 1,138 and 124 nucleotides, respectively. We successfully identified 820 perfectly patterned SSR using Phobos 3.3.12 software. The type characterisation of EST-SSR was dominated by tri-nucleotides 36% (294), followed by hexa-nucleotides 24% (202), tetra-nucleotides 15% (120), penta-nucleotides 13% (108) and di-nucleotides 12% (96). The most frequency of SSR motifs in each type is AG, AAG and AAAG. Analysis of synteny on the EST sequence with the online application Phytozome found that sequences were distributed on 12 Oryza sativa chromosomes with a likeness percentage between 63% to 100% and e-value between 0 to 0.094. We developed the primer and generated 19 primers. Furthermore, we validated 7 primers that all generated polymorphic alleles. To our knowledge, this report is the first identification and characterisation of EST-SSR for sago species and these markers can be used for genetic diversity analysis, marker assisted selection (MAS), cultivar identification, kinship analysis and genetic mapping analysis.

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In silico EST-SSR Identification and Development through EST Sequences from Metroxylon sagu Rottb. for Genetic Diversity Analysis. (2024). Tropical Life Sciences Research, 35(1), 13–32. https://doi.org/10.21315/tlsr2024.35.1.2
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References

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