The genomics and genetic information of Malaysian rice (Oryza sativa L.) is currently limited. It was necessary to conduct genome resequencing of these rice accessions exhibiting different responses to salinity stress. The sequencing was carried out using the Illumina NovaSeq X platform with 30× sequencing coverage to pinpoint variants between salinity tolerant and sensitive rice accessions. The discovery of single nucleotide polymorphisms (SNPs) is crucial for the development of DNA markers associated with salinity tolerance traits. The genome sequence data (FASTQ format) for these accessions have been deposited to the European Nucleotide Archive (ENA) database under the accession number PRJEB71716.
The genomics and genetic data of pigmented and non-pigmented Malaysian rice varieties are still limited. Hence, we performed the genome resequencing of two black rice varieties (Bali, Pulut Hitam 9), two red rice varieties (MRM16, MRQ100) and two white rice varieties (MR297 and MRQ76) using Illumina HiSeq 4000 platform with 30x sequencing coverage. We aimed to identify and annotate single nucleotide polymorphisms (SNPs) from the genome of these four pigmented and two non-pigmented rice varieties. The potential SNPs will be used in developing the functional SNP markers related to nutritional (i.e. antioxidant, folate, amylose) and quality (i.e. aromatic) traits. Raw data of the pigmented and non-pigmented rice varieties have been deposited into the European Nucleotide Archive (ENA) database with accession number PRJEB29070 and PRJEB32344, respectively.
The trend of microsatellite marker discovery and development revolved as a result of the advancement of next generation sequencing (NGS) technology as it has developed numerous microsatellites within a short period of time at a low cost. This study generated microsatellite markers using RAD sequencing technologies for the understudied Nephelium lappaceum. A total of 1403 microsatellite markers were successfully designed, which consisted of 853 di-, 525 tri-, 17 tetra-, 5 penta-, and 3 hexanucleotide microsatellite markers. Subsequently, selection of 39 microsatellites was made for the evaluation of genetic diversity of the selected 22 rambutan varieties. Twelve microsatellites, which exhibited high call rates across the samples, were used to assess the diversity of the aforementioned rambutan varieties. The analysis of 12 microsatellites revealed the presence of 72 alleles and six alleles per locus in average. Furthermore, the polymorphic information content (PIC) value ranged from 0.326 (NlaSSR20) to 0.832 (NlaSSR32), which included an average of 0.629 per locus, while the generated Neighbour Joining dendrogram showed two major clusters. The pairwise genetic distance of shared alleles exhibited a range of values from 0.046 (R134↔R170) to 0.818 (R5↔R170), which suggested highest dissimilarity detected between R5 and R170. Notably, these research findings would useful for varietal identification, proper management and conservation of the genetic resources, and exploitation and utilization in future breeding programs.
Universiti Sains Malaysia has started the Big Brain Data Initiative project since the last two years as brain mapping techniques have proven to be important in understanding the molecular, cellular and functional mechanisms of the brain. This Big Brain Data Initiative can be a platform for neurophysicians and neurosurgeons, psychiatrists, psychologists, cognitive neuroscientists, neurotechnologists and other researchers to improve brain mapping techniques. Data collection from a cohort of multiracial population in Malaysia is important for present and future research and finding cure for neurological and mental illness. Malaysia is one of the participant of the Global Brain Consortium (GBC) supported by the World Health Organization. This project is a part of its contribution via the third GBC goal which is influencing the policy process within and between high-income countries and low- and middle-income countries, such as pathways for fair data-sharing of multi-modal imaging data, starting with electroencephalographic data.