Construction of a high density linkage map in Oil Palm using SPET markers

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).

Analysis of >3400 worldwide eggplant accessions reveals two independent domestication events and multiple migration-diversification routes

Eggplant (Solanum melongena) is an important Solanaceous crop, widely cultivated and consumed in Asia, the Mediterranean basin, and Southeast Europe. Its domestication centers and migration and diversification routes are still a matter of debate. We report the largest georeferenced and genotyped collection to this date for eggplant and its wild relatives, consisting of 3499 accessions from seven worldwide genebanks, originating from 105 countries in five continents. The combination of genotypic and passport data points to the existence of at least two main centers of domestication, in Southeast Asia and the Indian subcontinent, with limited genetic exchange between them. The wild and weedy eggplant ancestor S. insanum shows admixture with domesticated S. melongena, similar to what was described for other fruit-bearing Solanaceous crops such as tomato and pepper and their wild ancestors. After domestication, migration and admixture of eggplant populations from different regions have been less conspicuous with respect to tomato and pepper, thus better preserving 'local' phenotypic characteristics. The data allowed the identification of misclassified and putatively duplicated accessions, facilitating genebank management. All the genetic, phenotypic, and passport data have been deposited in the Open Access G2P-SOL database, and constitute an invaluable resource for understanding the domestication, migration and diversification of this cosmopolitan vegetable.

Development and application of Single Primer Enrichment Technology (SPET) SNP assay for population genomics analysis and candidate gene discovery in lettuce

Single primer enrichment technology (SPET) is a novel high-throughput genotyping method based on short-read sequencing of specific genomic regions harboring polymorphisms. SPET provides an efficient and reproducible method for genotyping target loci, overcoming the limits associated with other reduced representation library sequencing methods that are based on a random sampling of genomic loci. The possibility to sequence regions surrounding a target SNP allows the discovery of thousands of closely linked, novel SNPs. In this work, we report the design and application of the first SPET panel in lettuce, consisting of 41,547 probes spanning the whole genome and designed to target both coding (~96%) and intergenic (~4%) regions. A total of 81,531 SNPs were surveyed in 160 lettuce accessions originating from a total of 10 countries in Europe, America, and Asia and representing 10 horticultural types. Model ancestry population structure clearly separated the cultivated accessions (Lactuca sativa) from accessions of its presumed wild progenitor (L. serriola), revealing a total of six genetic subgroups that reflected a differentiation based on cultivar typology. Phylogenetic relationships and principal component analysis revealed a clustering of butterhead types and a general differentiation between germplasm originating from Western and Eastern Europe. To determine the potentiality of SPET for gene discovery, we performed genome-wide association analysis for main agricultural traits in L. sativa using six models (GLM naive, MLM, MLMM, CMLM, FarmCPU, and BLINK) to compare their strength and power for association detection. Robust associations were detected for seed color on chromosome 7 at 50 Mbp. Colocalization of association signals was found for outer leaf color and leaf anthocyanin content on chromosome 9 at 152 Mbp and on chromosome 5 at 86 Mbp. The association for bolting time was detected with the GLM, BLINK, and FarmCPU models on chromosome 7 at 164 Mbp. Associations were detected in chromosomal regions previously reported to harbor candidate genes for these traits, thus confirming the effectiveness of SPET for GWAS. Our findings illustrated the strength of SPET for discovering thousands of variable sites toward the dissection of the genomic diversity of germplasm collections, thus allowing a better characterization of lettuce collections.

Genetic dissection of fruit maturity date in apricot (P. armeniaca L.) through a Single Primer Enrichment Technology (SPET) approach

Background

Single primer enrichment technology (SPET) is an emerging and increasingly popular solution for high-throughput targeted genotyping in plants. Although SPET requires a priori identification of polymorphisms for probe design, this technology has potentially higher reproducibility and transferability compared to other reduced representation sequencing (RRS) approaches, also enabling the discovery of closely linked polymorphisms surrounding the target one.

Results

The potential for SPET application in fruit trees was evaluated by developing a 25K target SNPs assay to genotype a panel of apricot accessions and progenies. A total of 32,492 polymorphic sites were genotyped in 128 accessions (including 8,188 accessory non-target SNPs) with extremely low levels of missing data and a significant correlation of allelic frequencies compared to whole-genome sequencing data used for array design. Assay performance was further validated by estimating genotyping errors in two biparental progenies, resulting in an overall 1.8% rate. SPET genotyping data were used to infer population structure and to dissect the architecture of fruit maturity date (MD), a quantitative reproductive phenological trait of great agronomical interest in apricot species. Depending on the year, GWAS revealed loci associated to MD on several chromosomes. The QTLs on chromosomes 1 and 4 (the latter explaining most of the phenotypic variability in the panel) were the most consistent over years and were further confirmed by linkage mapping in two segregating progenies.

Conclusions

Besides the utility for marker assisted selection and for paving the way to in-depth studies to clarify the molecular bases of MD trait variation in apricot, the results provide an overview of the performance and reliability of SPET for fruit tree genetics.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08901-1.

Genome properties of key oil palm (Elaeis guineensis Jacq.) breeding populations

A good knowledge of the genome properties of the populations makes it possible to optimize breeding methods, in particular genomic selection (GS). In oil palm (Elaeis guineensis Jacq), the world's main source of vegetable oil, this would provide insight into the promising GS results obtained so far. The present study considered two complex breeding populations, Deli and La Mé, with 943 individuals and 7324 single-nucleotide polymorphisms (SNPs) from genotyping-by-sequencing. Linkage disequilibrium (LD), haplotype sharing, effective size (N_e), and fixation index (F_st) were investigated. A genetic linkage map spanning 1778.52 cM and with a recombination rate of 2.85 cM/Mbp was constructed. The LD at r²=0.3, considered the minimum to get reliable GS results, spanned over 1.05 cM/0.22 Mbp in Deli and 0.9 cM/0.21 Mbp in La Mé. The significant degree of differentiation existing between Deli and La Mé was confirmed by the high F_st value (0.53), the pattern of correlation of SNP heterozygosity and allele frequency among populations, and the decrease of persistence of LD and of haplotype sharing among populations with increasing SNP distance. However, the level of resemblance between the two populations over short genomic distances (correlation of r values between populations >0.6 for SNPs separated by <0.5 cM/1 kbp and percentage of common haplotypes >40% for haplotypes <3600 bp/0.20 cM) likely explains the superiority of GS models ignoring the parental origin of marker alleles over models taking this information into account. The two populations had low N_e (<5). Population-specific genetic maps and reference genomes are recommended for future studies.

Targeted genome-wide SNP genotyping in feral horses using non-invasive fecal swabs

The development of high-throughput sequencing has prompted a transition in wildlife genetics from using microsatellites toward sets of single nucleotide polymorphisms (SNPs). However, genotyping large numbers of targeted SNPs using non-invasive samples remains challenging due to relatively large DNA input requirements. Recently, target enrichment has emerged as a promising approach requiring little template DNA. We assessed the efficacy of Tecan Genomics’ Allegro Targeted Genotyping (ATG) for generating genome-wide SNP data in feral horses using DNA isolated from fecal swabs. Total and host-specific DNA were quantified for 989 samples collected as part of a long-term individual-based study of feral horses on Sable Island, Nova Scotia, Canada, using dsDNA fluorescence and a host-specific qPCR assay, respectively. Forty-eight samples representing 44 individuals containing at least 10 ng of host DNA (ATG’s recommended minimum input) were genotyped using a custom multiplex panel targeting 279 SNPs. Genotyping accuracy and consistency were assessed by contrasting ATG genotypes with those obtained from the same individuals with SNP microarrays, and from multiple samples from the same horse, respectively. 62% of swabs yielded the minimum recommended amount of host DNA for ATG. Ignoring samples that failed to amplify, ATG recovered an average of 88.8% targeted sites per sample, while genotype concordance between ATG and SNP microarrays was 98.5%. The repeatability of genotypes from the same individual approached unity with an average of 99.9%. This study demonstrates the suitability of ATG for genome-wide, non-invasive targeted SNP genotyping, and will facilitate further ecological and conservation genetics research in equids and related species.

Newly Developed MAGIC Population Allows Identification of Strong Associations and Candidate Genes for Anthocyanin Pigmentation in Eggplant

Multi-parent advanced generation inter-cross (MAGIC) populations facilitate the genetic dissection of complex quantitative traits in plants and are valuable breeding materials. We report the development of the first eggplant MAGIC population (S3 Magic EGGplant InCanum, S3MEGGIC; 8-way), constituted by the 420 S3 individuals developed from the intercrossing of seven cultivated eggplant (Solanum melongena) and one wild relative (S. incanum) parents. The S3MEGGIC recombinant population was genotyped with the eggplant 5k probes SPET platform and phenotyped for anthocyanin presence in vegetative plant tissues (PA) and fruit epidermis (FA), and for the light-insensitive anthocyanic pigmentation under the calyx (PUC). The 7,724 filtered high-confidence single-nucleotide polymorphisms (SNPs) confirmed a low residual heterozygosity (6.87%), a lack of genetic structure in the S3MEGGIC population, and no differentiation among subpopulations carrying a cultivated or wild cytoplasm. Inference of haplotype blocks of the nuclear genome revealed an unbalanced representation of the founder genomes, suggesting a cryptic selection in favour or against specific parental genomes. Genome-wide association study (GWAS) analysis for PA, FA, and PUC detected strong associations with two myeloblastosis (MYB) genes similar to MYB113 involved in the anthocyanin biosynthesis pathway, and with a COP1 gene which encodes for a photo-regulatory protein and may be responsible for the PUC trait. Evidence was found of a duplication of an ancestral MYB113 gene with a translocation from chromosome 10 to chromosome 1 compared with the tomato genome. Parental genotypes for the three genes were in agreement with the identification of the candidate genes performed in the S3MEGGIC population. Our new eggplant MAGIC population is the largest recombinant population in eggplant and is a powerful tool for eggplant genetics and breeding studies.

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).

Oil palm in the 2020s and beyond: challenges and solutions

BACKGROUND

Oil palm, Elaeis guineensis, is by far the most important global oil crop, supplying about 40% of all traded vegetable oil. Palm oils are key dietary components consumed daily by over three billion people, mostly in Asia, and also have a wide range of important non-food uses including in cleansing and sanitizing products.

MAIN BODY

Oil palm is a perennial crop with a > 25-year life cycle and an exceptionally low land footprint compared to annual oilseed crops. Oil palm crops globally produce an annual 81 million tonnes (Mt) of oil from about 19 million hectares (Mha). In contrast, the second and third largest vegetable oil crops, soybean and rapeseed, yield a combined 84 Mt oil but occupy over 163 Mha of increasingly scarce arable land. The oil palm crop system faces many challenges in the 2020s. These include increasing incidence of new and existing pests/diseases and a general lack of climatic resilience, especially relating to elevated temperatures and increasingly erratic rainfall patterns, plus downstream issues relating to supply chains and consumer sentiment. This review surveys the oil palm sector in the 2020s and beyond, its major challenges and options for future progress.

CONCLUSIONS

Oil palm crop production faces many future challenges, including emerging threats from climate change and pests and diseases. The inevitability of climate change requires more effective international collaboration for its reduction. New breeding and management approaches are providing the promise of improvements, such as much higher yielding varieties, improved oil profiles, enhanced disease resistance, and greater climatic resilience.

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.