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  1. High-resolution genetic linkage map and height-related QTLs in an oil palm (Elaeis guineensis) family planted across multiple sites
    Ting NC, Chan PL, Buntjer J, Ordway JM, Wischmeyer C, Ooi LC, et al.
    Physiol Mol Biol Plants, 2023 Sep;29(9):1301-1318.
    PMID: 38024957 DOI: 10.1007/s12298-023-01360-2
    A refined SNP array containing 92,459 probes was developed and applied for chromosome scanning, construction of a high-density genetic linkage map and QTL analysis in a selfed Nigerian oil palm family (T128). Genotyping of the T128 mapping family generated 76,447 good quality SNPs for detailed scanning of aberration and homozygosity in the individual pseudo-chromosomes. Of them, 25,364 polymorphic SNPs were used for linkage analysis resulting in an 84.4% mapping rate. A total of 21,413 SNPs were mapped into 16 linkage groups (LGs), covering a total map length of 1364.5 cM. This genetic map is 16X denser than the previous version used to establish pseudo-chromosomes of the oil palm reference genome published in 2013. The QTLs associated with height, height increment and rachis length were identified in LGs TT05, 06, 08, 15 and 16. The present QTLs as well as those published previously were tagged to the reference genome to determine their chromosomal locations. Almost all the QTLs identified in this study were either close to or co-located with those reported in other populations. Determining the QTL position on chromosomes was also helpful in mining for the underlying candidate genes. In total, 55 putative genes and transcription factors involved in the biosynthesis, conjugation and signalling of the major phytohormones, especially for gibberellins and cell wall morphogenesis were found to be present in the identified genomic QTL regions, and their potential roles in plant dwarfism are discussed.

    SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-023-01360-2.

  2. Transcriptional effects of carbon and nitrogen starvation on Ganoderma boninense, an oil palm phytopathogen
    Nagappan J, Ooi SE, Chan KL, Kadri F, Nurazah Z, Halim MAA, et al.
    Mol Biol Rep, 2024 Jan 25;51(1):212.
    PMID: 38273212 DOI: 10.1007/s11033-023-09054-4
    BACKGROUND: Ganoderma boninense is a phytopathogen of oil palm, causing basal and upper stem rot diseases.

    METHODS: The genome sequence was used as a reference to study gene expression during growth in a starved carbon (C) and nitrogen (N) environment with minimal sugar and sawdust as initial energy sources. This study was conducted to mimic possible limitations of the C-N nutrient sources during the growth of G. boninense in oil palm plantations.

    RESULTS: Genome sequencing of an isolate collected from a palm tree in West Malaysia generated an assembly of 67.12 Mb encoding 19,851 predicted genes. Transcriptomic analysis from a time course experiment during growth in this starvation media identified differentially expressed genes (DEGs) that were found to be associated with 29 metabolic pathways. During the active growth phase, 26 DEGs were related to four pathways, including secondary metabolite biosynthesis, carbohydrate metabolism, glycan metabolism and mycotoxin biosynthesis. G. boninense genes involved in the carbohydrate metabolism pathway that contribute to the degradation of plant cell walls were up-regulated. Interestingly, several genes associated with the mycotoxin biosynthesis pathway were identified as playing a possible role in pathogen-host interaction. In addition, metabolomics analysis revealed six metabolites, maltose, xylobiose, glucooligosaccharide, glycylproline, dimethylfumaric acid and arabitol that were up-regulated on Day2 of the time course experiment.

    CONCLUSIONS: This study provides information on genes expressed by G. boninense in metabolic pathways that may play a role in the initial infection of the host.

  3. Detection of ploidy and chromosomal aberrations in commercial oil palm using high-throughput SNP markers
    Ngoot-Chin T, Zulkifli MA, van de Weg E, Zaki NM, Serdari NM, Mustaffa S, et al.
    Planta, 2021 Feb 05;253(2):63.
    PMID: 33544231 DOI: 10.1007/s00425-021-03567-7
    MAIN CONCLUSION: Karyotyping using high-density genome-wide SNP markers identified various chromosomal aberrations in oil palm (Elaeis guineensis Jacq.) with supporting evidence from the 2C DNA content measurements (determined using FCM) and chromosome counts. Oil palm produces a quarter of the world's total vegetable oil. In line with its global importance, an initiative to sequence the oil palm genome was carried out successfully, producing huge amounts of sequence information, allowing SNP discovery. High-capacity SNP genotyping platforms have been widely used for marker-trait association studies in oil palm. Besides genotyping, a SNP array is also an attractive tool for understanding aberrations in chromosome inheritance. Exploiting this, the present study utilized chromosome-wide SNP allelic distributions to determine the ploidy composition of over 1,000 oil palms from a commercial F1 family, including 197 derived from twin-embryo seeds. Our method consisted of an inspection of the allelic intensity ratio using SNP markers. For palms with a shifted or abnormal distribution ratio, the SNP allelic frequencies were plotted along the pseudo-chromosomes. This method proved to be efficient in identifying whole genome duplication (triploids) and aneuploidy. We also detected several loss of heterozygosity regions which may indicate small chromosomal deletions and/or inheritance of identical by descent regions from both parents. The SNP analysis was validated by flow cytometry and chromosome counts. The triploids were all derived from twin-embryo seeds. This is the first report on the efficiency and reliability of SNP array data for karyotyping oil palm chromosomes, as an alternative to the conventional cytogenetic technique. Information on the ploidy composition and chromosomal structural variation can help to better understand the genetic makeup of samples and lead to a more robust interpretation of the genomic data in marker-trait association analyses.
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