Evidence-based gene models for structural and functional annotations of the oil palm genome

Multi-Omics Approaches in Oil Palm Research: A Comprehensive Review of Metabolomics, Proteomics, and Transcriptomics Based on Low-Temperature Stress

Oil palm (Elaeis guineensis Jacq.) is a typical tropical oil crop with a temperature of 26-28 °C, providing approximately 35% of the total world's vegetable oil. Growth and productivity are significantly affected by low-temperature stress, resulting in inhibited growth and substantial yield losses. To comprehend the intricate molecular mechanisms underlying the response and acclimation of oil palm under low-temperature stress, multi-omics approaches, including metabolomics, proteomics, and transcriptomics, have emerged as powerful tools. This comprehensive review aims to provide an in-depth analysis of recent advancements in multi-omics studies on oil palm under low-temperature stress, including the key findings from omics-based research, highlighting changes in metabolite profiles, protein expression, and gene transcription, as well as including the potential of integrating multi-omics data to reveal novel insights into the molecular networks and regulatory pathways involved in the response to low-temperature stress. This review also emphasizes the challenges and prospects of multi-omics approaches in oil palm research, providing a roadmap for future investigations. Overall, a better understanding of the molecular basis of the response of oil palm to low-temperature stress will facilitate the development of effective breeding and biotechnological strategies to improve the crop's resilience and productivity in changing climate scenarios.

Functional characterization of the MSP-C6 promoter as a potential tool for mesocarp-preferential expression of transgenes

Modification of lipid composition in the mesocarp tissue of oil palm involves genetic manipulation of multiple genes. More than one mesocarp-preferential promoter is necessary for the expression of individual transgenes in the same plant to obviate transcriptional gene silencing. This study aimed to identify genes that are preferentially expressed in the mesocarp tissue and characterize selected candidate mesocarp-preferential promoters. Ten transcripts that were preferentially expressed in the mesocarp tissue were identified from the analysis of 82 transcriptome datasets of 12 different oil palm tissues. The expression of two candidate genes, MSP-C1 and MSP-C6, was verified to be preferentially expressed in the mesocarp tissues and shown to have a low expression level in non-mesocarp tissues by reverse transcription quantitative real-time PCR (RT-qPCR). MSP-C6 promoter fragments of different lengths were transformed into tomato plants for further characterization. Both unripe and ripe fruits of transgenic tomato plants transformed with a construct harboring the MSP-C6-F1 (2014 bp) promoter were shown to have high beta-glucuronidase (GUS) activities. The findings of this study suggest the potential applications of the MSP-C6 promoter as a molecular tool for genetic engineering of novel traits in fruit crops.

High-resolution genetic linkage map and height-related QTLs in an oil palm (Elaeis guineensis) family planted across multiple sites

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.

Integrated consensus genetic map and genomic scaffold re-ordering of oil palm (Elaeis guineensis) genome

A high-quality reference genome is an important resource that can help decipher the genetic basis of traits in combination with linkage or association analyses. The publicly available oil palm draft genome sequence of AVROS pisifera (EG5) accounts for 1.535 Gb of the 1.8 Gb oil palm genome. However, the assemblies are fragmented, and the earlier assembly only had 43% of the sequences placed on pseudo-chromosomes. By integrating a number of SNP and SSR-based genetic maps, a consensus map (AM_EG5.1), comprising of 828.243 Mb genomic scaffolds anchored to 16 pseudo-chromosomes, was generated. This accounted for 54% of the genome assembly, which is a significant improvement to the original assembly. The total length of N50 scaffolds anchored to the pseudo-chromosomes increased by ∼18% compared to the previous assembly. A total of 139 quantitative trait loci for agronomically important quantitative traits, sourced from literature, were successfully mapped on the new pseudo-chromosomes. The improved assembly could also be used as a reference to identify potential errors in placement of specific markers in the linkage groups of the genetic maps used to assemble the consensus map. The 3422 unique markers from five genetic maps, anchored to the pseudo-chromosomes of AM_EG5.1, are an important resource that can be used preferentially to either construct new maps or fill gaps in existing genetic maps. Synteny analysis further revealed that the AM_EG5.1 had high collinearity with the date palm genome cultivar 'Barhee BC4' and shared most of its segmental duplications. This improved chromosomal-level genome is a valuable resource for genetic research in oil palm.

A Review of an Artificial Intelligence Framework for Identifying the Most Effective Palm Oil Prediction

Machine Learning (ML) offers new precision technologies with intelligent algorithms and robust computation. This technology benefits various agricultural industries, such as the palm oil sector, which possesses one of the most sustainable industries worldwide. Hence, an in-depth analysis was conducted, which is derived from previous research on ML utilisation in the palm oil in-dustry. The study provided a brief overview of widely used features and prediction algorithms and critically analysed current the state of ML-based palm oil prediction. This analysis is extended to the ML application in the palm oil industry and a comparison of related studies. The analysis was predicated on thoroughly examining the advantages and disadvantages of ML-based palm oil prediction and the proper identification of current and future agricultural industry challenges. Potential solutions for palm oil prediction were added to this list. Artificial intelligence and ma-chine vision were used to develop intelligent systems, revolutionising the palm oil industry. Overall, this article provided a framework for future research in the palm oil agricultural industry by highlighting the importance of ML.

Genome-Wide Prediction of Transcription Start Sites in Conifers

The identification of promoters is an essential step in the genome annotation process, providing a framework for gene regulatory networks and their role in transcription regulation. Despite considerable advances in the high-throughput determination of transcription start sites (TSSs) and transcription factor binding sites (TFBSs), experimental methods are still time-consuming and expensive. Instead, several computational approaches have been developed to provide fast and reliable means for predicting the location of TSSs and regulatory motifs on a genome-wide scale. Numerous studies have been carried out on the regulatory elements of mammalian genomes, but plant promoters, especially in gymnosperms, have been left out of the limelight and, therefore, have been poorly investigated. The aim of this study was to enhance and expand the existing genome annotations using computational approaches for genome-wide prediction of TSSs in the four conifer species: loblolly pine, white spruce, Norway spruce, and Siberian larch. Our pipeline will be useful for TSS predictions in other genomes, especially for draft assemblies, where reliable TSS predictions are not usually available. We also explored some of the features of the nucleotide composition of the predicted promoters and compared the GC properties of conifer genes with model monocot and dicot plants. Here, we demonstrate that even incomplete genome assemblies and partial annotations can be a reliable starting point for TSS annotation. The results of the TSS prediction in four conifer species have been deposited in the Persephone genome browser, which allows smooth visualization and is optimized for large data sets. This work provides the initial basis for future experimental validation and the study of the regulatory regions to understand gene regulation in gymnosperms.

Prediction of Rice Transcription Start Sites Using TransPrise: A Novel Machine Learning Approach

As the interest in genetic resequencing increases, so does the need for effective mathematical, computational, and statistical approaches. One of the difficult problems in genome annotation is determination of precise positions of transcription start sites. In this paper, we present TransPrise-an efficient deep learning tool for predicting positions of eukaryotic transcription start sites. TransPrise offers significant improvement over existing promoter-prediction methods. To illustrate this, we compared predictions of TransPrise with the TSSPlant approach for well-annotated genome of Oryza sativa. Using a computer with a graphics processing unit, the run time of TransPrise is 250 min on a genome of 374 Mb long.We provide the full basis for the comparison and encourage users to freely access a set of our computational tools to facilitate and streamline their own analyses. The ready-to-use Docker image with all the necessary packages, models, and code as well as the source code of the TransPrise algorithm are available at http://compubioverne.group/ . The source code is ready to use and to be customized to predict TSS in any eukaryotic organism.

Expression of fatty acid and triacylglycerol synthesis genes in interspecific hybrids of oil palm

Evaluation of transcriptome data in combination with QTL information has been applied in many crops to study the expression of genes responsible for specific phenotypes. In oil palm, the mesocarp oil extracted from E. oleifera × E. guineensis interspecific hybrids is known to have lower palmitic acid (C16:0) content compared to pure African palms. The present study demonstrates the effectiveness of transcriptome data in revealing the expression profiles of genes in the fatty acid (FA) and triacylglycerol (TAG) biosynthesis processes in interspecific hybrids. The transcriptome assembly yielded 43,920 putative genes of which a large proportion were homologous to known genes in the public databases. Most of the genes encoding key enzymes involved in the FA and TAG synthesis pathways were identified. Of these, 27, including two candidate genes located within the QTL associated with C16:0 content, showed differential expression between developmental stages, populations and/or palms with contrasting C16:0 content. Further evaluation using quantitative real-time PCR revealed that differentially expressed patterns are generally consistent with those observed in the transcriptome data. Our results also suggest that different isoforms are likely to be responsible for some of the variation observed in FA composition of interspecific hybrids.

DNA methylation changes in clonally propagated oil palm

Several hypomethylated sites within the Karma region of EgDEF1 and hotspot regions in chromosomes 1, 2, 3, and 5 may be associated with mantling. One of the main challenges faced by the oil palm industry is fruit abnormalities, such as the "mantled" phenotype that can lead to reduced yields. This clonal abnormality is an epigenetic phenomenon and has been linked to the hypomethylation of a transposable element within the EgDEF1 gene. To understand the epigenome changes in clones, methylomes of clonal oil palms were compared to methylomes of seedling-derived oil palms. Whole-genome bisulfite sequencing data from seedlings, normal, and mantled clones were analyzed to determine and compare the context-specific DNA methylomes. In seedlings, coding and regulatory regions are generally hypomethylated while introns and repeats are extensively methylated. Genes with a low number of guanines and cytosines in the third position of codons (GC₃-poor genes) were increasingly methylated towards their 3' region, while GC₃-rich genes remain demethylated, similar to patterns in other eukaryotic species. Predicted promoter regions were generally hypomethylated in seedlings. In clones, CG, CHG, and CHH methylation levels generally decreased in functionally important regions, such as promoters, 5' UTRs, and coding regions. Although random regions were found to be hypomethylated in clonal genomes, hypomethylation of certain hotspot regions may be associated with the clonal mantling phenotype. Our findings, therefore, suggest other hypomethylated CHG sites within the Karma of EgDEF1 and hypomethylated hotspot regions in chromosomes 1, 2, 3 and 5, are associated with mantling.

CRISPR/Cas mediated base editing: a practical approach for genome editing in oil palm

The improvement of the yield and quality of oil palm via precise genome editing has been indispensable goal for oil palm breeders. Genome editing via the CRISPR/Cas9 (CRISPR-associated protein 9) system, ZFN (zinc finger nucleases) and TALEN (transcription activator-like effector nucleases) has flourished as an efficient technology for precise target modifications in the genomes of various crops. Among the genome editing technologies, base editing approach has emerged as novel technology that could generate single base changes i.e. irreversible conversion of one target base in to other in a programmable manner. A base editor (adenine or cytosine) is a fusion of catalytically inactive CRISPR-Cas9 domain (Cas9 variants) and cytosine or adenosine deaminase domain that introduces desired point mutations. However, till date no such genetic modifications have ever been developed in oil palm via base editing technology. Precise genome editing via base editing approach can be a challenging task in oil palm due to its complex genome as well as difficulties in tissue culture and genetic transformation methods. However, availability of whole genome sequencing data in oil palm provides a platform for developing the base editing technology. Here, we briefly review the potential application and future implications of base editing technology for the genetic improvement of oil palm.

Characterization of Oil Palm Acyl-CoA-Binding Proteins and Correlation of Their Gene Expression with Oil Synthesis

Acyl-CoA-binding proteins (ACBPs) are involved in binding and trafficking acyl-CoA esters in eukaryotic cells. ACBPs contain a well-conserved acyl-CoA-binding domain. Their various functions have been characterized in the model plant Arabidopsis and, to a lesser extent, in rice. In this study, genome-wide detection and expression analysis of ACBPs were performed on Elaeis guineensis (oil palm), the most important oil crop in the world. Seven E. guineensis ACBPs were identified and classified into four groups according to their deduced amino acid domain organization. Phylogenetic analysis showed conservation of this family with other higher plants. All seven EgACBPs were expressed in most tissues while their differential expression suggests various functions in specific tissues. For example, EgACBP3 had high expression in inflorescences and stalks while EgACBP1 showed strong expression in leaves. Because of the importance of E. guineensis as an oil crop, expression of EgACBPs was specifically examined during fruit development. EgACBP3 showed high expression throughout mesocarp development, while EgACBP1 had enhanced expression during rapid oil synthesis. In endosperm, both EgACBP1 and EgACBP3 exhibited increased expression during seed development. These results provide important information for further investigations on the biological functions of EgACBPs in various tissues and, in particular, their roles in oil synthesis.

TransPrise: a novel machine learning approach for eukaryotic promoter prediction

As interest in genetic resequencing increases, so does the need for effective mathematical, computational, and statistical approaches. One of the difficult problems in genome annotation is determination of precise positions of transcription start sites. In this paper we present TransPrise-an efficient deep learning tool for prediction of positions of eukaryotic transcription start sites. Our pipeline consists of two parts: the binary classifier operates the first, and if a sequence is classified as TSS-containing the regression step follows, where the precise location of TSS is being identified. TransPrise offers significant improvement over existing promoter-prediction methods. To illustrate this, we compared predictions of TransPrise classification and regression models with the TSSPlant approach for the well annotated genome of Oryza sativa. Using a computer equipped with a graphics processing unit, the run time of TransPrise is 250 minutes on a genome of 374 Mb long. The Matthews correlation coefficient value for TransPrise is 0.79, more than two times larger than the 0.31 for TSSPlant classification models. This represents a high level of prediction accuracy. Additionally, the mean absolute error for the regression model is 29.19 nt, allowing for accurate prediction of TSS location. TransPrise was also tested in Homo sapiens, where mean absolute error of the regression model was 47.986 nt. We provide the full basis for the comparison and encourage users to freely access a set of our computational tools to facilitate and streamline their own analyses. The ready-to-use Docker image with all necessary packages, models, code as well as the source code of the TransPrise algorithm are available at (http://compubioverne.group/). The source code is ready to use and customizable to predict TSS in any eukaryotic organism.

MIGREW: database on molecular identification of genes for resistance in wheat

Population structure of fungal infections in wheat differs between wheat varieties and environments. Taking into account evolution of host-pathogen interactions, genetic diversity of both wheat and fungus must be a monitored. In order to catalogue information to support need of wheat pathologists and breeders, who use conventional methods and Molecular Assisted Selection (MAS) techniques, we have developed the Molecular Identification of Genes for Resistance in Wheat (MIGREW) database. The main goal of this database is to support wheat breeding efforts to develop immunity to rusts and powdery mildew. MIGREW is also focused on effectiveness of wheat resistance genes in different regions of Russia to provide users relevant information on the rapidly changing population structure of pathogens.

In silico characterization and expression profiling of the diacylglycerol acyltransferase gene family (DGAT1, DGAT2, DGAT3 and WS/DGAT) from oil palm, Elaeis guineensis

The diacylglycerol acyltransferases (DGAT) (diacylglycerol:acyl-CoA acyltransferase, EC 2.3.1.20) are a key group of enzymes that catalyse the final and usually the most important rate-limiting step of triacylglycerol biosynthesis in plants and other organisms. Genes encoding four distinct functional families of DGAT enzymes have been characterised in the genome of the African oil palm, Elaeis guineensis. The contrasting features of the various isoforms within the four families of DGAT genes, namely DGAT1, DGAT2, DGAT3 and WS/DGAT are presented both in the oil palm itself and, for comparative purposes, in 12 other oil crop or model/related plants, namely Arabidopsis thaliana, Brachypodium distachyon, Brassica napus, Elaeis oleifera, Glycine max, Gossypium hirsutum, Helianthus annuus, Musa acuminata, Oryza sativa, Phoenix dactylifera, Sorghum bicolor, and Zea mays. The oil palm genome contains respectively three, two, two and two distinctly expressed functional copies of the DGAT1, DGAT2, DGAT3 and WS/DGAT genes. Phylogenetic analyses of the four DGAT families showed that the E. guineensis genes tend to cluster with sequences from P. dactylifera and M. acuminata rather than with other members of the Commelinid monocots group, such as the Poales which include the major cereal crops such as rice and maize. Comparison of the predicted DGAT protein sequences with other animal and plant DGATs was consistent with the E. guineensis DGAT1 being ER located with its active site facing the lumen while DGAT2, although also ER located, had a predicted cytosol-facing active site. In contrast, DGAT3 and some (but not all) WS/DGAT in E. guineensis are predicted to be soluble, cytosolic enzymes. Evaluation of E. guineensis DGAT gene expression in different tissues and developmental stages suggests that the four DGAT groups have distinctive physiological roles and are particularly prominent in developmental processes relating to reproduction, such as flowering, and in fruit/seed formation especially in the mesocarp and endosperm tissues.

Comparative genomic and transcriptomic analysis of selected fatty acid biosynthesis genes and CNL disease resistance genes in oil palm

Comparative genomics and transcriptomic analyses were performed on two agronomically important groups of genes from oil palm versus other major crop species and the model organism, Arabidopsis thaliana. The first analysis was of two gene families with key roles in regulation of oil quality and in particular the accumulation of oleic acid, namely stearoyl ACP desaturases (SAD) and acyl-acyl carrier protein (ACP) thioesterases (FAT). In both cases, these were found to be large gene families with complex expression profiles across a wide range of tissue types and developmental stages. The detailed classification of the oil palm SAD and FAT genes has enabled the updating of the latest version of the oil palm gene model. The second analysis focused on disease resistance (R) genes in order to elucidate possible candidates for breeding of pathogen tolerance/resistance. Ortholog analysis showed that 141 out of the 210 putative oil palm R genes had homologs in banana and rice. These genes formed 37 clusters with 634 orthologous genes. Classification of the 141 oil palm R genes showed that the genes belong to the Kinase (7), CNL (95), MLO-like (8), RLK (3) and Others (28) categories. The CNL R genes formed eight clusters. Expression data for selected R genes also identified potential candidates for breeding of disease resistance traits. Furthermore, these findings can provide information about the species evolution as well as the identification of agronomically important genes in oil palm and other major crops.

PalmXplore: oil palm gene database

A set of Elaeis guineensis genes had been generated by combining two gene prediction pipelines: Fgenesh++ developed by Softberry and Seqping by the Malaysian Palm Oil Board. PalmXplore was developed to provide a scalable data repository and a user-friendly search engine system to efficiently store, manage and retrieve the oil palm gene sequences and annotations. Information deposited in PalmXplore includes predicted genes, their genomic coordinates, as well as the annotations derived from external databases, such as Pfam, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Information about genes related to important traits, such as those involved in fatty acid biosynthesis (FAB) and disease resistance, is also provided. The system offers Basic Local Alignment Search Tool homology search, where the results can be downloaded or visualized in the oil palm genome browser (MYPalmViewer). PalmXplore is regularly updated offering new features, improvements to genome annotation and new genomic sequences. The system is freely accessible at http://palmxplore.mpob.gov.my.

Identification of Ganoderma Disease Resistance Loci Using Natural Field Infection of an Oil Palm Multiparental Population

Multi-parental populations are promising tools for identifying quantitative disease resistance loci. Stem rot caused by Ganoderma boninense is a major threat to palm oil production, with yield losses of up to 80% prompting premature replantation of palms. There is evidence of genetic resistance sources, but the genetic architecture of Ganoderma resistance has not yet been investigated. This study aimed to identify Ganoderma resistance loci using an oil palm multi-parental population derived from nine major founders of ongoing breeding programs. A total of 1200 palm trees of the multi-parental population was planted in plots naturally infected by Ganoderma, and their health status was assessed biannually over 25 yr. The data were treated as survival data, and modeled using the Cox regression model, including a spatial effect to take the spatial component in the spread of Ganoderma into account. Based on the genotypes of 757 palm trees out of the 1200 planted, and on pedigree information, resistance loci were identified using a random effect with identity-by-descent kinship matrices as covariance matrices in the Cox model. Four Ganoderma resistance loci were identified, two controlling the occurrence of the first Ganoderma symptoms, and two the death of palm trees, while favorable haplotypes were identified among a major gene pool for ongoing breeding programs. This study implemented an efficient and flexible QTL mapping approach, and generated unique valuable information for the selection of oil palm varieties resistant to Ganoderma disease.