Genome-wide identification of markers for selecting higher oil content in oil palm

Genotyping by sequencing for the construction of oil palm (Elaeis guineensis Jacq.) genetic linkage map and mapping of yield related quantitative trait loci

Background

Oil palm (Elaeis guineensis Jacq.) is one of the major oil-producing crops. Improving the quality and increasing the production yield of oil palm have been the primary focuses of both conventional and modern breeding approaches. However, the conventional breeding approach for oil palm is very challenging due to its longevity, which results in a long breeding cycle. Thus, the establishment of marker assisted selection (MAS) for oil palm breeding programs would speed up the breeding pipeline by generating new oil palm varieties that possess high commercial traits. With the decreasing cost of sequencing, Genotyping-by-sequencing (GBS) is currently feasible to many researchers and it provides a platform to accelerate the discovery of single nucleotide polymorphism (SNP) as well as insertion and deletion (InDel) markers for the construction of a genetic linkage map. A genetic linkage map facilitates the identification of significant DNA regions associated with the trait of interest via quantitative trait loci (QTL) analysis.

Methods

A mapping population of 112 F1 individuals from a cross of Deli dura and Serdang pisifera was used in this study. GBS libraries were constructed using the double digestion method with HindIII and TaqI enzymes. Reduced representation libraries (RRL) of 112 F1 progeny and their parents were sequenced and the reads were mapped against the E. guineensis reference genome. To construct the oil palm genetic linkage map, informative SNP and InDel markers were used to discover significant DNA regions associated with the traits of interest. The nine traits of interest in this study were fresh fruit bunch (FFB) yield, oil yield (OY), oil to bunch ratio (O/B), oil to dry mesocarp ratio (O/DM) ratio, oil to wet mesocarp ratio (O/WM), mesocarp to fruit ratio (M/F), kernel to fruit ratio (K/F), shell to fruit ratio (S/F), and fruit to bunch ratio (F/B).

Results

A total of 2.5 million SNP and 153,547 InDel markers were identified. However, only a subset of 5,278 markers comprising of 4,838 SNPs and 440 InDels were informative for the construction of a genetic linkage map. Sixteen linkage groups were produced, spanning 2,737.6 cM for the maternal map and 4,571.6 cM for the paternal map, with average marker densities of one marker per 2.9 cM and one per 2.0 cM respectively, were produced. A QTL analysis was performed on nine traits; however, only QTL regions linked to M/F, K/F and S/F were declared to be significant. Of those QTLs were detected: two for M/F, four for K/F and one for S/F. These QTLs explained 18.1-25.6% of the phenotypic variance and were located near putative genes, such as casein kinase II and the zinc finger CCCH domain, which are involved in seed germination and growth. The identified QTL regions for M/F, K/F and S/F from this study could be applied in an oil palm breeding program and used to screen palms with desired traits via marker assisted selection (MAS).

A Chromosome-level Reference Genome of African Oil Palm Provides Insights into Its Divergence and Stress Adaptation

The palm family (Arecaceae), consisting of ∼ 2600 species, is the third most economically important family of plants. The African oil palm (Elaeis guineensis) is one of the most important palms. However, the genome sequences of palms that are currently available are still limited and fragmented. Here, we report a high-quality chromosome-level reference genome of an oil palm, Dura, assembled by integrating long reads with ∼ 150× genome coverage. The assembled genome was 1.7 Gb in size, covering 94.5% of the estimated genome, of which 91.6% was assigned into 16 pseudochromosomes and 73.7% was repetitive sequences. Relying on the conserved synteny with oil palm, the existing draft genome sequences of both date palm and coconut were further assembled into chromosomal level. Transposon burst, particularly long terminal repeat retrotransposons, following the last whole-genome duplication, likely explains the genome size variation across palms. Sequence analysis of the VIRESCENS gene in palms suggests that DNA variations in this gene are related to fruit colors. Recent duplications of highly tandemly repeated pathogenesis-related proteins from the same tandem arrays play an important role in defense responses to Ganoderma. Whole-genome resequencing of both ancestral African and introduced oil palms in Southeast Asia reveals that genes under putative selection are notably associated with stress responses, suggesting adaptation to stresses in the new habitat. The genomic resources and insights gained in this study could be exploited for accelerating genetic improvement and understanding the evolution of palms.

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.

Construction of the first high-density SNP genetic map and identification of QTLs for the natural rubber content in Taraxacum kok-saghyz Rodin

BACKGROUND

Taraxacum kok-saghyz Rodin (TKS) is a promising commercial alternative natural rubber (NR) yielding plant. Cultivating TKS with a high NR content is an important breeding target, and developing molecular markers related to NR content can effectively accelerate the breeding process of TKS.

RESULTS

To construct a high-density SNP genetic map and uncover genomic regions related to the NR content in TKS, an F₁ mapping population of TKS was constructed by crossing two parents (l66 and X51) with significant differences in NR contents. The NR content of the F₁ plants ranged from 0.30 to 15.14% and was distributed normally with a coefficient of variation of 47.61%, indicating quantitative trait inheritance. Then, employing whole-genome resequencing (WGR), a TKS genetic linkage map of 12,680 bin markers comprising 322,439 SNPs was generated. Based on the genetic map and NR content of the F₁ population, six quantitative trait loci (QTLs) for NR content with LOD > 4.0 were identified on LG01/Chr01 and LG06/Chr06. Of them, the 2.17 Mb genomic region between qHRC-C6-1 and qHRC-C6-2 on ChrA06, with 65.62% PVE in total, was the major QTL region. In addition, the six QTLs have significant additive genetic effects on NR content and could be used to develop markers for marker-assisted selection (MAS) in TKS with a high NR content.

CONCLUSION

This work constructed the first high-density TKS genetic map and identified the QTLs and genomic regions controlling the NR content, which provides useful information for fine mapping, map-based cloning, and MAS in TKS.

Genomic selection for morphological and yield-related traits using genome-wide SNPs in oil palm

Oil palm is the most important oil crop worldwide. Colombia is the fourth largest producer, primarily relying on production from interspecific hybrids, derived from crosses between Elaeis oleifera and Elaeis guineensis (OxG). However, conventional breeding can take up to 20 years to generate a new variety. Therefore, reducing the breeding cycle while improving the genetic gain for complex traits is desirable. Genomic selection (GS) is an approach with the potential to achieve this goal. In this study, we evaluated 431 F1 interspecific hybrids (OxG) and 444 backcrosses (BC1) for morphological and yield-related traits. Genomic predictions were performed with the G-BLUP model using three different population datasets for training the model: the same population (TRN1), the other population (TRN2), and both populations (TRN1+2). Higher multi-family prediction accuracies were obtained for foliar area (0.3 in OxG) and trunk height (0.47 in BC1) when the model was trained with TRN1. Single-family prediction accuracies were lower in the OxG compared to BC1 families for traits such as trunk diameter, trunk height, bunch number, and yield using TRN1. Conversely, lower prediction accuracies were obtained for most traits when the model was trained using TRN2 (< 0.1). Multi-trait models showed a substantial increase of the predictions for traits such as yield (0.22 for OxG and 0.44 for BC1), because of the genetic correlations between traits. The results herein highlighted the potential of GS for parental selection in OxG and BC1 populations, but further studies are required to improve the models to select individuals by their genetic value.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01341-5.

A bulked segregant analysis tool for out-crossing species (BSATOS) and QTL-based genomics-assisted prediction of complex traits in apple

INTRODUCTION

Genomic heterozygosity, self-incompatibility, and rich-in somatic mutations hinder the molecular breeding efficiency of outcrossing plants.

OBJECTIVES

We attempted to develop an efficient integrated strategy to identify quantitative trait loci (QTLs) and trait-associated genes, to develop gene markers, and to construct genomics-assisted prediction (GAP) modes.

METHODS

A novel protocol, bulked segregant analysis tool for out-crossing species (BSATOS), is presented here, which is characterized by taking full advantage of all segregation patterns (including AB × AB markers) and haplotype information. To verify the effectiveness of the protocol in dealing with the complex traits of outbreeding species, three apple cross populations with 9,654 individuals were adopted.

RESULTS

By using BSATOS, 90, 60, and 77 significant QTLs were identified successfully and candidate genes were predicted for apple fruit weight (FW), fruit ripening date (FRD), and fruit soluble solid content (SSC), respectively. The gene-based markers were developed and genotyped for 1,396 individuals in a training population, including 145 Malus accessions and 1,251 F1 plants of the three full-sib families. GAP models were trained using marker genotype effect estimates of the training population. The prediction accuracy was 0.7658, 0.6455, and 0.3758 for FW, FRD, and SSC, respectively.

CONCLUSION

The BSATOS and GAP models provided a convenient and efficient methodology for candidate gene mining and molecular breeding in out-crossing plant species. The BSATOS pipeline can be freely downloaded from: https://github.com/maypoleflyn/BSATOS.

Predicting Heritability of Oil Palm Breeding Using Phenotypic Traits and Machine Learning

Oil palm is one of the main crops grown to help achieve sustainability in Malaysia. The selection of the best breeds will produce quality crops and increase crop yields. This study aimed to examine machine learning (ML) in oil palm breeding (OPB) using factors other than genetic data. A new conceptual framework to adopt the ML in OPB will be presented at the end of this paper. At first, data types, phenotype traits, current ML models, and evaluation technique will be identified through a literature survey. This study found that the phenotype and genotype data are widely used in oil palm breeding programs. The average bunch weight, bunch number, and fresh fruit bunch are the most important characteristics that can influence the genetic improvement of progenies. Although machine learning approaches have been applied to increase the productivity of the crop, most studies focus on molecular markers or genotypes for plant breeding, rather than on phenotype. Theoretically, the use of phenotypic data related to offspring should predict high breeding values by using ML. Therefore, a new ML conceptual framework to study the phenotype and progeny data of oil palm breeds will be discussed in relation to achieving the Sustainable Development Goals (SDGs).

Insights on Genetic Diversity, Population Structure, and Linkage Disequilibrium in Globally Diverse Coconut Accessions Using Genotyping-by-Sequencing

Genotyping-by-sequencing (GBS) has emerged as a cost-effective approach for genome-wide discovery of single-nucleotide polymorphism (SNP) markers and high-throughput genotyping. In this study, 96 coconut palms, representing 16 accessions from globally diverse origins, were genotyped using the GBS strategy. A total of 10,835 high-quality SNPs, which were identified after stringent filtering, were utilized to assess genetic diversity, population structure, and linkage disequilibrium (LD) analyses. The polymorphism information content (PIC) values of SNPs ranged from 0.1 to 0.4, with a large proportion of SNPs (8633 nos.; 79.7%) having a higher PIC in the range of 0.3-0.4. The genetic diversity analysis revealed the existence of a high level of variation in coconut accessions, with an average expected heterozygosity (H_e) value of 0.43. Unweighted neighbor-joining phylogenetic tree and Bayesian-based model population structure grouped coconut genotypes into four main clusters. The accessions are generally clustered based on their height (tall or dwarf), with a few accession clusterings based on geographical origins. Investigation of LD pattern in coconut indicated a relatively rapid LD decay with a short range (9 kb). The results obtained in this study will contribute to enhancing the capacity of coconut researchers to utilize genetic diversity for further genetic improvement. In addition, it would open up possibilities for performing genomic studies such as genome-wide association studies and genomic selection to accelerate the efficiency and speed of coconut genetic improvement.

Genome-wide association study (GWAS) of major QTLs for bunch and oil yield related traits in Elaeis guineensis L

Oil palm (Elaeis guineensis Jacq.) is a long breeding cycle perennial crop with a genome size of 1.8 Gb. This is the first report of GWAS on large number of 310 African germplasm using 400 SSR markers till date. Highly significant correlation was found between leaf area (LA) and rachis length (RL) (0.75) followed by bunch weight (BW) and bunch index (BI) (0.65), whereas negative correlation was observed between bunch number (BN) and average bunch weight (ABW). First two principal component analysis (PCA) together explained maximum amount of variation (84.5 %). The PCA1 revealed that group 2 (Guinea Bissau and Cameroon) and group 4 (Zambia and Cameroon) genotypes are best suitable for BN, BI and BW traits. GWAS of six bunch yield and seven bunch oil yield traits with SSRs resulted in the identification 43 significant quantitative trait loci (QTLs) by mixed linear model (MLM) approach. Seven SSR loci were found to be linked to oil to dry mesocarp (ODM) on chromosomes 1,4,7,10,12 and 15. The SSR locus mEgCIR1753 for ODM was significantly linked at a p of ≤0.05 which explained 34.6 % of phenotypic variance. The important parameters like ODM, OWM and OB were located on 4, 10, 11 and 15 chromosomes. The leaf area and ODM were associated with candidate genes representing of low-temperature-induced 65 kDa proteins. The identified markers can be effectively used for marker assisted selection of high yielding oil palm genotypes.

Phenomics, genomics of oil palm (Elaeis guineensis Jacq.): way forward for making sustainable and high yielding quality oil palm

Oil palm (Elaeis guineensis Jacq.) is a heterogeneous, perennial crop having long breeding cycle with a genome size of 1.8 Gb. The demand for vegetable oil is steadily increasing, and expected that nearly 240-250 million tons of vegetable oil may be required by 2050. Genomics and next generation technologies plays crucial role in achieving the sustainable availability of oil palm with good yield and high quality. A successful breeding programme in oil palm depends on the availability of diverse gene pool, ex-situ conservation and their proper utilization for generating elite planting material. The major breeding methods adopted in oil palm are either modified recurrent selection or the modified reciprocal recurrent selection method. The QTLs of yield and related traits are chiefly located on chromosome 4, 10, 12 and 15 which is discussed in the current review. The probable chromosomal regions influencing the less height increment is observed to be on chromosomes 4, 10, 14 and 15. Advanced genomic approaches together with bioinformatics tools were discussed thoroughly for achieving sustainable oil palm where more efforts are needed. Major emphasis is given on oil palm crop improvement using holistic approaches of various genomic tools. Also a road map given on the milestones in the genomics and way forward for making oil palm to high yielding quality oil palm.

Molecular approaches for improving oil palm for oil

The oil palm, originating from Africa, is the most productive oil crop species. Palm oil is an important source of edible oil. Its current global plantation area is over 23 million ha. The theoretical oil yield potential of the oil palm is 18.2 tons/ha/year. However, current average oil yield is only 3.8 tons/ha/year. In the past 100 years, conventional breeding and improvement of field management played important roles in increasing oil yield. However, conventional breeding for trait improvement was limited by its very long (10-20 years) phenotypic selection cycle, although it improved oil yield by ~10-20% per generation. Molecular breeding using novel molecular technologies will accelerate genetic improvement and may reduce the need to deforest and to use arable land for expanding oil palm plantations, which in turn makes palm oil more sustainable. Here, we comprehensively synthesize information from relevant literature of the technologies, achievements, and challenges of molecular approaches, including tissue culture, haploid breeding, mutation breeding, marker-assisted selection (MAS), genomic selection (GS), and genome editing (GE). We propose the characteristics of ideal palms and suggest a road map to breed ideal palms for sustainable palm oil.

Genes, pathways and networks responding to drought stress in oil palm roots

Oil palm is the most productive oilseed crop and its oil yield is seriously affected by frequent drought stress. However, little is known about the molecular responses of oil palm to drought stress. We studied the root transcriptomic responses of oil palm seedlings under 14-day drought stress. We identified 1293 differentially expressed genes (DEGs), involved in several molecular processes, including cell wall biogenesis and functions, phenylpropanoid biosynthesis and metabolisms, ion transport and homeostasis and cellular ketone metabolic process, as well as small molecule biosynthetic process. DEGs were significantly enriched into two categories: hormone regulation and metabolism, as well as ABC transporters. In addition, three protein–protein interaction networks: ion transport, reactive nitrogen species metabolic process and nitrate assimilation, were identified to be involved in drought stress responses. Finally, 96 differentially expressed transcription factors were detected to be associated with drought stress responses, which were classified into 28 families. These results provide not only novel insights into drought stress responses, but also valuable genomic resources to improve drought tolerance of oil palm by both genetic modification and selective breeding.

Intricate genetic variation networks control the adventitious root growth angle in apple

Background

The root growth angle (RGA) typically determines plant rooting depth, which is significant for plant anchorage and abiotic stress tolerance. Several quantitative trait loci (QTLs) for RGA have been identified in crops. However, the underlying mechanisms of the RGA remain poorly understood, especially in apple rootstocks. The objective of this study was to identify QTLs, validate genetic variation networks, and develop molecular markers for the RGA in apple rootstock.

Results

Bulked segregant analysis by sequencing (BSA-seq) identified 25 QTLs for RGA using 1955 hybrids of the apple rootstock cultivars ‘Baleng Crab’ (Malus robusta Rehd., large RGA) and ‘M9’ (M. pumila Mill., small RGA). With RNA sequencing (RNA-seq) and parental resequencing, six major functional genes were identified and constituted two genetic variation networks for the RGA. Two single nucleotide polymorphisms (SNPs) of the MdLAZY1 promoter damaged the binding sites of MdDREB2A and MdHSFB3, while one SNP of MdDREB2A and MdIAA1 affected the interactions of MdDREB2A/MdHSFB3 and MdIAA1/MdLAZY1, respectively. A SNP within the MdNPR5 promoter damaged the interaction between MdNPR5 and MdLBD41, while one SNP of MdLBD41 interrupted the MdLBD41/MdbHLH48 interaction that affected the binding ability of MdLBD41 on the MdNPR5 promoter. Twenty six SNP markers were designed on candidate genes in each QTL interval, and the marker effects varied from 0.22°-26.11°.

Conclusions

Six diagnostic markers, SNP592, G122, b13, Z312, S1272, and S1288, were used to identify two intricate genetic variation networks that control the RGA and may provide new insights into the accuracy of the molecular markers. The QTLs and SNP markers can potentially be used to select deep-rooted apple rootstocks.

Quantitative trait loci-based genomics-assisted prediction for the degree of apple fruit cover color

Apple fruit cover color is an important appearance trait determining fruit quality, high degree of fruit cover color or completely red fruit skin is also the ultimate breeding goal. MdMYB1 has repeatedly been reported as a major gene controlling apple fruit cover color. There are also multiple minor-effect genes affecting degree of fruit cover color (DFC). This study was to identify genome-wide quantitative trait loci (QTLs) and to develop genomics-assisted prediction for apple DFC. The DFC phenotype data of 9,422 hybrids from five full-sib families of Malus asiatica 'Zisai Pearl', M. domestica 'Red Fuji', 'Golden Delicious', and 'Jonathan' were collected in 2014-2017. The phenotype varied considerably among hybrids with the same MdMYB1 genotype. Ten QTLs for DFC were identified using MapQTL and bulked segregant analysis via sequencing. From these QTLs, ten candidate genes were predicted, including MdMYB1 from a year-stable QTL on chromosome 9 of 'Zisai Pearl' and 'Red Fuji'. Then, kompetitive allele-specific polymerase chain reaction (KASP) markers were designed on these candidate genes and 821 randomly selected hybrids were genotyped. The genotype effects of the markers were estimated. MdMYB1-1 (represented by marker H162) exhibited a partial dominant allelic effect on MdMYB1-2 and showed non-allelic epistasis on markers H1245 and G6. Finally, a non-additive QTL-based genomics assisted prediction model was established for DFC. The Pearson's correlation coefficient between the genomic predicted value and the observed phenotype value was 0.5690. These results can be beneficial for apple genomics-assisted breeding and may provide insights for understanding the mechanism of fruit coloration.

Development of High-Density Genetic Linkage Maps and Identification of Loci for Chestnut Gall Wasp Resistance in Castanea spp

Castanea sativa is an important multipurpose species in Europe for nut and timber production as well as for its role in the landscape and in the forest ecosystem. This species has low tolerance to chestnut gall wasp (Dryocosmus kuriphilus Yasumatsu), which is a pest that was accidentally introduced into Europe in early 2000 and devastated forest and orchard trees. Resistance to the gall wasp was found in the hybrid cultivar ‘Bouche de Bétizac’ (C. sativa × C. crenata) and studied by developing genetic linkage maps using a population derived from a cross between ‘Bouche de Bétizac’ and the susceptible cultivar ‘Madonna’ (C. sativa). The high-density genetic maps were constructed using double-digest restriction site-associated DNA-seq and simple sequence repeat markers. The map of ‘Bouche de Bétizac’ consisted of 1459 loci and spanned 809.6 cM; the map of ‘Madonna’ consisted of 1089 loci and spanned 753.3 cM. In both maps, 12 linkage groups were identified. A single major QTL was recognized on the ‘Bouche de Bétizac’ map, explaining up to 67–69% of the phenotypic variance of the resistance trait (Rdk1). The Rdk1 quantitative trait loci (QTL) region included 11 scaffolds and two candidate genes putatively involved in the resistance response were identified. This study will contribute to C. sativa breeding programs and to the study of Rdk1 genes.

Detection of significant SNP associated with production and oil quality traits in interspecific oil palm hybrids using RARSeq

A RARSeq based Association mapping study was performed in a population of 104 Elaeis oleifera x E. guineensis hybrids of five origins with the aim of finding functional markers associated to six productive and 19 oil quality traits. For this purpose mRNA of each genotype was isolated and double stranded cDNA was synthesized. Following digestion with two restriction enzymes and adapter ligation, a size selected pool of barcoded amplicons was produced and sequenced using Illumina MiSeq. The obtained sequences were processed with a "snakemake" pipeline, filtered and missing values were imputed. For all traits except two significant effects of the origin was observed. Genetic diversity analyses revealed high variability within origins and an excess of heterozygosity in the population. Two GLM models with Q matrix or PCA matrix as covariates and two MLM models incorporating in addition a Kinship matrix were tested for genotype-phenotype associations using GAPIT software. Using unadjusted p values (< 0.01) 78 potential associations were detected involving 25 SNP and 20 traits. When applying FDR multiple testing with p <  0.05, 25 significant associations remained involving eight SNP and six quality traits. Four SNP were located in genes with a potential relevant biological meaning.

Genome-wide association study for leaf area, rachis length and total dry weight in oil palm (Eleaeisguineensis) using genotyping by sequencing

The marker-trait association for complex traits using genotyping by sequencing (GBS) method is being widely spread in plants. The study aimed to identify significant single nucleotide polymorphism (SNP) associations for rachis length (RL), leaf area (LA) and total dry weight (TrDW) in oil palm among diverse African germplasm. The Illumina NextSeq platform has been used for SNP genotyping and retained 4031 fully informative SNPs after applying the filter criterion. These 4031 SNPs were used for genome wide association study for the above three traits. The LD decay rates of the African germplasm using GBS data of SNP is observed to be 25 Kb at 0.45 of average pair wise correlation coefficient (r²). Association mapping led to the identification of seven significant associations for three traits using MLM approach at a P value of ≤ 0.001. Three associations were identified for total dry weight, two each for leaf area index and rachis length. The qtlLA1 was found to be highly significant at a P value of 7.39E^-05 (18.4% phenotypic variance) which is located on chromosome 4. Two QTLs (qtlLA2 and qtlRL1) were located on chromosome 1, which explained 11.9% and 12.4% of phenotypic variance respectively. Three QTLs for total dry weight were located on chromosome 2, 14 and 16, all-together explained 40% phenotypic variance. The results showed that the SNP-trait associations identified in the present study could be used in selection of elite oil palm germplasm for higher yields.

Genome-wide association study (GWAS) of leaf cuticular wax components in Camelina sativa identifies genetic loci related to intracellular wax transport

BACKGROUND

It is important to explore renewable alternatives (e.g. biofuels) that can produce energy sources to help reduce reliance on fossil oils, and reduce greenhouse gases and waste solids resulted from fossil oils consumption. Camelina sativa is an oilseed crop which has received increasing attention due to its short life cycle, broader adaptation regions, high oil content, high level of omega-3 unsaturated fatty acids, and low-input requirements in agriculture practices. To expand its Camelina production areas into arid regions, there is a need to breed for new drought-tolerant cultivars. Leaf cuticular wax is known to facilitate plant development and growth under water-limited conditions. Dissecting the genetic loci underlying leaf cuticular waxes is important to breed for cultivars with improved drought tolerance.

RESULTS

Here we combined phenotypic data and single nucleotide polymorphism (SNP) data from a spring C. sativa diversity panel using genotyping-by-sequencing (GBS) technology, to perform a large-scale genome-wide association study (GWAS) on leaf wax compositions. A total of 42 SNP markers were significantly associated with 15 leaf wax traits including major wax components such as total primary alcohols, total alkanes, and total wax esters as well as their constituents. The vast majority of significant SNPs were associated with long-chain carbon monomers (carbon chain length longer than C28), indicating the important effects of long-chain carbon monomers on leaf total wax biosynthesis. These SNP markers are located on genes directly or indirectly related to wax biosynthesis such as maintaining endoplasmic reticulum (ER) morphology and enabling normal wax secretion from ER to plasma membrane or Golgi network-mediated transport.

CONCLUSIONS

These loci could potentially serve as candidates for the genetic control involved in intracellular wax transport that might directly or indirectly facilitate leaf wax accumulation in C. sativa and can be used in future marker-assisted selection (MAS) to breed for the cultivars with high wax content to improve drought tolerance.

Progress in plant genome sequencing: research directions

Since the first plant genome of Arabidopsis thaliana has been sequenced and published, genome sequencing technologies have undergone significant changes. New algorithms, sequencing technologies and bioinformatic approaches were adopted to obtain genome, transcriptome and exome sequences for model and crop species, which have permitted deep inferences into plant biology. As a result of an improved genome assembly and analysis methods, genome sequencing costs plummeted and the number of high-quality plant genome sequences is constantly growing. Consequently, more than 300 plant genome sequences have been published over the past twenty years. Although many of the published genomes are considered incomplete, they proved to be a valuable tool for identifying genes involved in the formation of economically valuable plant traits, for marker-assisted and genomic selection and for comparative analysis of plant genomes in order to determine the basic patterns of origin of various plant species. Since a high coverage and resolution of a genome sequence is not enough to detect all changes in complex samples, targeted sequencing, which consists in the isolation and sequencing of a specific region of the genome, has begun to develop. Targeted sequencing has a higher detection power (the ability to identify new differences/variants) and resolution (up to one basis). In addition, exome sequencing (the method of sequencing only protein-coding genes regions) is actively developed, which allows for the sequencing of non-expressed alleles and genes that cannot be found with RNA-seq. In this review, an analysis of sequencing technologies development and the construction of “reference” genomes of plants is performed. A comparison of the methods of targeted sequencing based on the use of the reference DNA sequence is accomplished.

Mapping of Quantitative Trait Loci for Growth and Carcass-Related Traits in Chickens Using a Restriction-Site Associated DNA Sequencing Method

In the present study, quantitative trait loci (QTLs) analysis was performed to identify the chromosomal positions of growth and carcass-related trait QTLs using 319 F₂ chickens obtained from intercrosses of an Oh-Shamo male and four White Plymouth Rock females. Body weight was measured weekly until the birds were 7 weeks old. Carcass-related traits were also measured at this timepoint. A genetic linkage map was constructed using 545 single nucleotide polymorphism (SNP) markers that were developed using a restriction-site associated DNA sequencing method. The linkage map included the 23 autosomes and the Z chromosome. Using simple interval QTL mapping, we were able to identify 10 significant and suggestive main-effect QTLs for growth and carcass-related traits present on chromosomes 1, 2, 3, 5, 8, 19, 24, and Z. These loci explained 5.60–16.52% of the phenotypic variances. The chromosomal positions of the 10 QTLs overlapped with those of previously reported QTLs, whereas the targeted traits varied. Our QTLs will aid future breeding programs in improving growth and meat yield of chickens (e.g., via marker-assisted selection), particularly in the Japanese brand chicken industry.

Cloning and characterization of EgGDSL, a gene associated with oil content in oil palm

Oil palm (Elaeis guineensis, Jacq.) is a key tropical oil crop, which provides over one third of the global vegetable oil production, but few genes related to oil yield have been characterized. In this study, a GDSL esterase/lipase gene, which was significantly associated with oil content, was isolated from oil palm and designated as EgGDSL. Its functional characterization was carried out through ectopic expression in Arabidopsis ecotype Col-0. It was shown that expression of EgGDSL in Arabidopsis led to the increased total fatty acid content by 9.5% compared with the wild type. Further analysis of the fatty acid composition revealed that stearic acid (18:0) increased in the seeds of the transgenic lines, but the levels of linoleic acid (18:2) plus 11-eicosenoic acid drastically declined. Quantitative real-time PCR (qPCR) revealed that in oil palm, EgGDSL was highly expressed in mesocarp followed by leaf, and the expression level was very low in the root. The expression level of EgGDSL gene began to increase at two months after flowering (MAF) and reached its peak by four MAF, then declined rapidly, and reached its lowest level during the mature period (6 MAF). The EgGDSL gene was more highly expressed in oil palm trees with high oil content than that with low oil content, demonstrating that the transcription level of EgGDSL correlated with the amount of oil accumulation. The gene may be valuable for engineering fatty acid metabolism in crop improvement programmes and for marker-assisted breeding.

Developing genome-wide SNPs and constructing an ultrahigh-density linkage map in oil palm

Oil palm (Elaeis guineensis Jacq.) is the leading oil-producing crops and the most important edible oil resource worldwide. DNA markers and genetic linkage maps are essential resources for marker-assisted selection to accelerate genetic improvement. We conducted RAD-seq on an Illumina NextSeq500 to discover genome-wide SNPs, and used the SNPs to construct a linkage map for an oil palm (Tenera) population derived from a cross between a Deli Dura and an AVROS Pisifera. The RAD-seq produced 1,076 million single-end reads across the breeding population containing 155 trees. Mining this dataset detected 510,251 loci. After filtering out loci with low accuracy and more than 20% missing data, 11,394 SNPs were retained. Using these SNPs, in combination with 188 anchor SNPs and 123 microsatellites, we constructed a linkage map containing 10,023 markers covering 16 chromosomes. The map length is 2,938.2 cM with an average marker space of 0.29 cM. The large number of SNPs will supply ample choices of DNA markers in analysing the genetic diversity, population structure and evolution of oil palm. This high-density linkage map will contribute to mapping quantitative trait loci (QTL) for important traits, thus accelerating oil palm genetic improvement.