Double-digest restriction-associated DNA sequencing-based genotyping and its applications in sesame germplasm management.

Sesame (Sesamum indicum L.) is an ancient oilseed crop belonging to the family Pedaliaceae and a globally cultivated crop for its use as oil and food. In this study, 2496 sesame accessions, being conserved at the National Genebank of ICAR-National Bureau of Plant Genetic Resources (NBPGR), were genotyped using genomics-assisted double-digest restriction-associated DNA sequencing (ddRAD-seq) approach. A total of 64,910 filtered single-nucleotide polymorphisms (SNPs) were utilized to assess the genome-scale diversity. Applications of this genome-scale information (reduced representation using restriction enzymes) are demonstrated through the development of a molecular core collection (CC) representing maximal SNP diversity. This information is also applied in developing a mid-density panel (MDP) comprising 2515 hyper-variable SNPs, representing almost equally the genic and non-genic regions. The sesame CC comprising 384 accessions, a representative set of accessions with maximal diversity, was identified using multiple criteria such as k-mer (subsequence of length "k" in a sequence read) diversity, observed heterozygosity, CoreHunter3, GenoCore, and genetic differentiation. The coreset constituted around 15% of the total accessions studied, and this small subset had captured >60% SNP diversity of the entire population. In the coreset, the admixture analysis shows reduced genetic complexity, increased nucleotide diversity (π), and is geographically distributed without any repetitiveness in the CC germplasm. Within the CC, India-originated accessions exhibit higher diversity (as expected based on the center of diversity concept), than those accessions that were procured from various other countries. The identified CC set and the MDP will be a valuable resource for genomics-assisted accelerated sesame improvement program.

A genomic toolkit for winged bean Psophocarpus tetragonolobus.

A sustainable supply of plant protein is critical for future generations and needs to be achieved while reducing green house gas emissions from agriculture and increasing agricultural resilience in the face of climate volatility. Agricultural diversification with more nutrient-rich and stress tolerant crops could provide the solution. However, this is often hampered by the limited availability of genomic resources and the lack of understanding of the genetic structure of breeding germplasm and the inheritance of important traits. One such crop with potential is winged bean (Psophocarpus tetragonolobus), a high seed protein tropical legume which has been termed 'the soybean for the tropics'. Here, we present a chromosome level winged bean genome assembly, an investigation of the genetic diversity of 130 worldwide accessions, together with two linked genetic maps and a trait QTL analysis (and expression studies) for regions of the genome with desirable ideotype traits for breeding, namely architecture, protein content and phytonutrients.

The Progression in Developing Genomic Resources for Crop Improvement.

Sequencing technologies have rapidly evolved over the past two decades, and new technologies are being continually developed and commercialized. The emerging sequencing technologies target generating more data with fewer inputs and at lower costs. This has also translated to an increase in the number and type of corresponding applications in genomics besides enhanced computational capacities (both hardware and software). Alongside the evolving DNA sequencing landscape, bioinformatics research teams have also evolved to accommodate the increasingly demanding techniques used to combine and interpret data, leading to many researchers moving from the lab to the computer. The rich history of DNA sequencing has paved the way for new insights and the development of new analysis methods. Understanding and learning from past technologies can help with the progress of future applications. This review focuses on the evolution of sequencing technologies, their significant enabling role in generating plant genome assemblies and downstream applications, and the parallel development of bioinformatics tools and skills, filling the gap in data analysis techniques.

A pilot-scale comparison between single and double-digest RAD markers generated using GBS strategy in sesame (Sesamum indicum L.).

To reduce the genome sequence representation, restriction site-associated DNA sequencing (RAD-seq) protocols is being widely used either with single-digest or double-digest methods. In this study, we genotyped the sesame population (48 sample size) in a pilot scale to compare single and double-digest RAD-seq (sd and ddRAD-seq) methods. We analysed the resulting short-read data generated from both protocols and assessed their performance impacting the downstream analysis using various parameters. The distinct k-mer count and gene presence absence variation (PAV) showed a significant difference between the sesame samples studied. Additionally, the variant calling from both datasets (sdRAD-seq and ddRAD-seq) exhibits a significant difference between them. The combined variants from both datasets helped in identifying the most diverse samples and possible sub-groups in the sesame population. The most diverse samples identified from each analysis (k-mer, gene PAV, SNP count, Heterozygosity, NJ and PCA) can possibly be representative samples holding major diversity of the small sesame population used in this study. The best possible strategies with suggested inputs for modifications to utilize the RAD-seq strategy efficiently on a large dataset containing thousands of samples to be subjected to molecular analysis like diversity, population structure and core development studies were discussed.

Deciphering the molecular basis for photosynthetic parameters in Bambara groundnut (Vigna subterranea L. Verdc) under drought stress.

BACKGROUND: Assessment of segregating populations for their ability to withstand drought stress conditions is one of the best approaches to develop breeding lines and drought tolerant varieties. Bambara groundnut (Vigna subterranea L. Verdc.) is a leguminous crop, capable of growing in low-input agricultural systems in semi-arid areas. An F4 bi-parental segregating population obtained from S19-3 × DodR was developed to evaluate the effect of drought stress on photosynthetic parameters and identify QTLs associated with these traits under drought-stressed and well-watered conditions in a rainout shelter. RESULTS: Stomatal conductance (gs), photosynthesis rate (A), transpiration rate (E) and intracellular CO2 (Ci) were significantly reduced (p < 0.05) while water use efficiency (WUE) was significantly increased (p < 0.05) under drought-stressed conditions. A strong linear correlation was observed between gs, WUE, A, E and Ci under both water regimes. The variability between different water treatment, among individual lines and the interaction between lines and environment for photosynthetic parameters provides resources for superior lines selection and drought resistant variety improvement. Significant QTL for gs and FV/FM under well-watered conditions were mapped on LG5 and LG3, respectively, with more than 20% of the PVE, which could be considered as the major QTL to control these traits. Five clustered QTLs for photosynthetic traits under drought-stressed and well-watered conditions were mapped on LG5, LG6A, LG10 and LG11, respectively. CONCLUSIONS: Significant and putative QTLs associated with photosynthetic parameters and the effect of drought stress on these traits have been revealed by QTL linkage mapping and field experiment in the F4 segregating population derived from S19-3 × DodR in bambara groundnut. The study provides fundamental knowledge of how photosynthetic traits response to drought stress and how genetic features control these traits under drought-stressed and well-watered conditions in bambara groundnut.

Exploring the sorghum race level diversity utilizing 272 sorghum accessions genomic resources.

Due to evolutionary divergence, sorghum race populations exhibit significant genetic and morphological variation. A k-mer-based sorghum race sequence comparison identified the conserved k-mers of all 272 accessions from sorghum and the race-specific genetic signatures identified the gene variability in 10,321 genes (PAVs). To understand sorghum race structure, diversity and domestication, a deep learning-based variant calling approach was employed in a set of genotypic data derived from a diverse panel of 272 sorghum accessions. The data resulted in 1.7 million high-quality genome-wide SNPs and identified selective signature (both positive and negative) regions through a genome-wide scan with different (iHS and XP-EHH) statistical methods. We discovered 2,370 genes associated with selection signatures including 179 selective sweep regions distributed over 10 chromosomes. Co-localization of these regions undergoing selective pressure with previously reported QTLs and genes revealed that the signatures of selection could be related to the domestication of important agronomic traits such as biomass and plant height. The developed k-mer signatures will be useful in the future to identify the sorghum race and for trait and SNP markers for assisting in plant breeding programs.

A multiscale mathematical model describing the growth and development of bambara groundnut.

A principal objective in agriculture is to maximise food production; this is particularly relevant with the added demands of an ever increasing population, coupled with the unpredictability that climate change brings. Further improvements in productivity can only be achieved with an increased understanding of plant and crop processes. In this respect, mathematical modelling of plants and crops plays an important role. In this paper we present a two-scale mathematical model of crop yield that accounts for plant growth and canopy interactions. A system of nonlinear ordinary differential equations (ODEs) is formulated to describe the growth of each individual plant, where equations are coupled via a term that describes plant competition via canopy-canopy interactions. A crop of greenhouse plants is then modelled via an agent based modelling approach in which the growth of each plant is described via our system of ODEs. The model is formulated for the African drought tolerant legume bambara groundnut (Vigna subterranea), which is currently being investigated as a food source in light of climate change and food insecurity challenges. Our model allows us to account for plant diversity and also investigate the effect of individual plant traits (e.g. plant canopy size and planting distance) on the yield of the overall crop. Informed with greenhouse data, model results show that plant positioning relative to other plants has a large impact on individual plant yield. Variation in physiological plant traits from genetic diversity and the environmental effects lead to experimentally observed variations in crop yield. These traits include plant height, plant carrying capacity, leaf accumulation rate and canopy spread. Of these traits plant height and ground cover growth rates are found to have the greatest impact on crop yield. We also consider a range of different planting arrangements (uniform grid, staggered grid, circular rings and random allocation) and find that the staggered grid leads to the greatest crop yield (6% more compared to uniform grid). Whilst formulated specifically for bambara groundnut, the generic formulation of our model means that with changes to certain parameter's, it may be extended to other crop species that form a canopy.

Genomic selection strategies to increase genetic gain in tea breeding programs.

Tea [Camellia sinensis (L.) O. Kuntze] is mainly grown in low- to middle-income countries (LMIC) and is a global commodity. Breeding programs in these countries face the challenge of increasing genetic gain because the accuracy of selecting superior genotypes is low and resources are limited. Phenotypic selection (PS) is traditionally the primary method of developing improved tea varieties and can take over 16 yr. Genomic selection (GS) can be used to improve the efficiency of tea breeding by increasing selection accuracy and shortening the generation interval and breeding cycle. Our main objective was to investigate the potential of implementing GS in tea-breeding programs to speed up genetic progress despite the low cost of PS in LMIC. We used stochastic simulations to compare three GS-breeding programs with a Pedigree and PS program. The PS program mimicked a practical commercial tea-breeding program over a 40-yr breeding period. All the GS programs achieved at least 1.65 times higher genetic gains than the PS program and 1.4 times compared with Seed-Ped program. Seed-GSc was the most cost-effective strategy of implementing GS in tea-breeding programs. It introduces GS at the seedlings stage to increase selection accuracy early in the program and reduced the generation interval to 2 yr. The Seed-Ped program outperformed PS by 1.2 times and could be implemented where it is not possible to use GS. Our results indicate that GS could be used to improve genetic gain per unit time and cost even in cost-constrained tea-breeding programs.

Genetic diversity analysis and marker-trait associations in Amaranthus species.

Amaranth (Amaranthus spp.) is a highly nutritious, underutilized vegetable and pseudo-cereal crop. It possesses diverse abiotic stress tolerance traits, is genetically diverse and highly phenotypically plastic, making it an ideal crop to thrive in a rapidly changing climate. Despite considerable genetic diversity there is a lack of detailed characterization of germplasm or population structures. The present study utilized the DArTSeq platform to determine the genetic relationships and population structure between 188 amaranth accessions from 18 agronomically important vegetable, grain, and weedy species. A total of 74, 303 SNP alleles were generated of which 63, 821 were physically mapped to the genome of the grain species A. hypochondriacus. Population structure was inferred in two steps. First, all 188 amaranth accessions comprised of 18 species and second, only 120 A. tricolor accessions. After SNP filtering, a total of 8,688 SNPs were generated on 181 amaranth accessions of 16 species and 9,789 SNPs generated on 118 A. tricolor accessions. Both SNP datasets produced three major sub-populations (K = 3) and generate consistent taxonomic classification of the amaranth sub-genera (Amaranthus Amaranthus, Amaranthus Acnida and Amaranthus albersia), although the accessions were poorly demarcated by geographical origin and morphological traits. A. tricolor accessions were well discriminated from other amaranth species. A genome-wide association study (GWAS) of 10 qualitative traits revealed an association between specific phenotypes and genetic variants within the genome and identified 22 marker trait associations (MTAs) and 100 MTAs (P≤0.01, P≤0.001) on 16 amaranth species and 118 A.tricolor datasets, respectively. The release of SNP markers from this panel has produced invaluable preliminary genetic information for phenotyping and cultivar improvement in amaranth species.

Natural Genotypic Variation Underpins Root System Response to Drought Stress in Bambara Groundnut [Vigna subterranea (L.) Verdc.].

Bambara groundnut [Vigna subterranea (L.) Verdc.] is grown in rainfed production systems and suffers from periodic drought stress (DS), leading to yield reductions. Natural genotypic variation for root traits is essential for adaptation to water deficit conditions. However, root traits have not been fully utilised as selection criteria to improve DS in bambara groundnut. The present study explored the natural genotypic variation found in single genotypes of bambara groundnut derived from landraces to identify adaptive differences in tap root length (TRL) and root length density (RLD) in response to DS. A diverse core collection of eight bambara groundnut genotypes from various locations (namely, Gresik, LunT, IITA-686, DodR, S19-3, Tiga nicuru, and Ankpa-4, DipC1), were grown for two seasons (2018 and 2019) in polyvinyl chloride (PVC) columns with well-watered (WW) and 30-day DS treatments. Plant samples were collected at 55 days after emergence (DAE) (30 days of DS) and at 105 DAE (30 days of DS plus 50 days of recovery). Under DS, differential TRL among genotypes at 55 DAE was observed, with DodR recording the longest among genotypes with an increase (1% in 2018) in TRL under DS compared to WW, whereas LunT and IITA-686 showed significant (p < 0.001) decrease in TRL (27 and 25%, respectively, in 2018). Average RLD was observed to have the highest reduction under DS in the 90-110 cm layer (42 and 58%, respectively, in 2018 and 2019). Rainy habitat LunT had limited roots in 2018 and recorded the least (0.06 ± 0.013 cm-3) RLD in 2019. However, dry-habitat DodR showed an increase in the RLD (60-90 cm) under DS compared to WW, while dry-habitat S19-3 densely occupied all depths with RLD of 0.16 ± 0.05 and 0.18 ± 0.01 cm cm-3 in the deepest layer in both seasons, respectively. Reduced RLD under DS showed recovery when the plants were re-watered. These plants were additionally observed to have RLD that surpasses the density in WW at all soil depths at 105 DAE. Also, recovery was shown in Tiga nicuru and DodR (0-30 cm) and IITA-686 (90-110 cm) in 2019. Average RLD under DS treatment was associated with substantial grain yield advantage (R 2 = 0.27 and R 2 = 0.49, respectively) in 2018 and 2019. An increase in TRL allowed DodR to quickly explore water at a deeper soil depth in response to gradually declining soil water availability. High RLD in genotypes such as DodR, DipC1 and S19-3 also offered adaptive advantage over other genotypes under DS. Variation in intrinsic RLD in deeper soil depths in the studied genotypes determines root foraging capacity when facing DS. This suggests that different agroecological environments to which bambara groundnut is subjected in its natural habitat have promoted a phenotypic differentiation in root systems to adapt to ecotypic conditions, which may help offset the impact of DS. The natural genotypic variation exhibited, especially by DodR, could be exploited to identify potential quantitative trait loci (QTLs) that control deep rooting and root length density.

Out of Africa: characterizing the natural variation in dynamic photosynthetic traits in a diverse population of African rice (Oryza glaberrima).

African rice (Oryza glaberrima) has adapted to challenging environments and is a promising source of genetic variation. We analysed dynamics of photosynthesis and morphology in a reference set of 155 O. glaberrima accessions. Plants were grown in an agronomy glasshouse to late tillering stage. Photosynthesis induction from darkness and the decrease in low light was measured by gas exchange and chlorophyll fluorescence along with root and shoot biomass, stomatal density, and leaf area. Steady-state and kinetic responses were modelled. We describe extensive natural variation in O. glaberrima for steady-state, induction, and reduction responses of photosynthesis that has value for gene discovery and crop improvement. Principal component analyses indicated key clusters of plant biomass, kinetics of photosynthesis (CO2 assimilation, A), and photoprotection induction and reduction (measured by non-photochemical quenching, NPQ), consistent with diverse adaptation. Accessions also clustered according to countries with differing water availability, stomatal conductance (gs), A, and NPQ, indicating that dynamic photosynthesis has adaptive value in O. glaberrima. Kinetics of NPQ, A, and gs showed high correlation with biomass and leaf area. We conclude that dynamic photosynthetic traits and NPQ are important within O. glaberrima, and we highlight NPQ kinetics and NPQ under low light.

Challenges for FAIR-compliant description and comparison of crop phenotype data with standardized controlled vocabularies.

Crop phenotypic data underpin many pre-breeding efforts to characterize variation within germplasm collections. Although there has been an increase in the global capacity for accumulating and comparing such data, a lack of consistency in the systematic description of metadata often limits integration and sharing. We therefore aimed to understand some of the challenges facing findable, accesible, interoperable and reusable (FAIR) curation and annotation of phenotypic data from minor and underutilized crops. We used bambara groundnut (Vigna subterranea) as an exemplar underutilized crop to assess the ability of the Crop Ontology system to facilitate curation of trait datasets, so that they are accessible for comparative analysis. This involved generating a controlled vocabulary Trait Dictionary of 134 terms. Systematic quantification of syntactic and semantic cohesiveness of the full set of 28 crop-specific COs identified inconsistencies between trait descriptor names, a relative lack of cross-referencing to other ontologies and a flat ontological structure for classifying traits. We also evaluated the Minimal Information About a Phenotyping Experiment and FAIR compliance of bambara trait datasets curated within the CropStoreDB schema. We discuss specifications for a more systematic and generic approach to trait controlled vocabularies, which would benefit from representation of terms that adhere to Open Biological and Biomedical Ontologies principles. In particular, we focus on the benefits of reuse of existing definitions within pre- and post-composed axioms from other domains in order to facilitate the curation and comparison of datasets from a wider range of crops. Database URL: https://www.cropstoredb.org/cs_bambara.html.

Development of Selection Indices for Improvement of Seed Yield and Lipid Composition in Bambara Groundnut (Vigna subterranea (L.) Verdc.).

The underutilised grain legume bambara groundnut (Vigna subterranea) has the potential to contribute significantly to nutritional security. However, the lack of commercial cultivars has hindered its wider adoption and utilisation as a food source. The development of competitive cultivars is impeded by (1) lack of systematic data describing variation in nutritional composition within the gene pool, and (2) a poor understanding of how concentrations of different nutritional components interact. In this study, we analysed seed lipid and protein concentration and lipid composition within a collection of 100 lines representing the global gene pool. Seed protein and lipid varied over twofold with a normal distribution, but no significant statistical correlation was detected between the two components. Seed lipid concentration (4.2-8.8 g/100 g) is primarily determined by the proportion of oleic acid (r2 = 0.45). Yield and composition data for a subset of 40 lines were then used to test selection parameters for high yielding, high lipid breeding lines. From five selection indices tested using 15 scenarios, an index based on the seed number, seed weight, and oleic acid yielded a >50% expected increase in each of the mean values of seed number, pod dry weight, seed dry weight, and seed size, as well as an expected 7% increase in seed lipid concentration.

Bambara Groundnut: An Underutilized Leguminous Crop for Global Food Security and Nutrition.

Rapid population growth, climate change, intensive monoculture farming, and resource depletion are among the challenges that threaten the increasingly vulnerable global agri-food system. Heavy reliance on a few major crops is also linked to a monotonous diet, poor dietary habits, and micronutrient deficiencies, which are often associated with diet-related diseases. Diversification-of both agricultural production systems and diet-is a practical and sustainable approach to address these challenges and to improve global food and nutritional security. This strategy is aligned with the recommendations from the EAT-Lancet report, which highlighted the urgent need for increased consumption of plant-based foods to sustain population and planetary health. Bambara groundnut (Vigna subterranea (L.) Verdc.), an underutilized African legume, has the potential to contribute to improved food and nutrition security, while providing solutions for environmental sustainability and equity in food availability and affordability. This paper discusses the potential role of Bambara groundnut in diversifying agri-food systems and contributing to enhanced dietary and planetary sustainability, with emphasis on areas that span the value chain: from genetics, agroecology, nutrition, processing, and utilization, through to its socioeconomic potential. Bambara groundnut is a sustainable, low-cost source of complex carbohydrates, plant-based protein, unsaturated fatty acids, and essential minerals (magnesium, iron, zinc, and potassium), especially for those living in arid and semi-arid regions. As a legume, Bambara groundnut fixes atmospheric nitrogen to improve soil fertility. It is resilient to adverse environmental conditions and can yield on poor soil. Despite its impressive nutritional and agroecological profile, the potential of Bambara groundnut in improving the global food system is undermined by several factors, including resource limitation, knowledge gap, social stigma, and lack of policy incentives. Multiple research efforts to address these hurdles have led to a more promising outlook for Bambara groundnut; however, there is an urgent need to continue research to realize its full potential.

An Improved Oil Palm Genome Assembly as a Valuable Resource for Crop Improvement and Comparative Genomics in the Arecoideae Subfamily.

Oil palm (Elaeis guineensis Jacq.) is the most traded crop among the economically important palm species. Here, we report an extended version genome of E. guineensis that is 1.2 Gb in length, an improvement of the physical genome coverage to 79% from the previous 43%. The improvement was made by assigning an additional 1968 originally unplaced scaffolds that were available publicly into the physical genome. By integrating three ultra-dense linkage maps and using them to place genomic scaffolds, the 16 pseudomolecules were extended. As we show, the improved genome has enhanced the mapping resolution for genome-wide association studies (GWAS) and permitted further identification of candidate genes/protein-coding regions (CDSs) and any non-coding RNA that may be associated with them for further studies. We then employed the new physical map in a comparative genomics study against two other agriculturally and economically important palm species-date palm (Phoenix dactylifera L.) and coconut palm (Cocos nucifera L.)-confirming the high level of conserved synteny among these palm species. We also used the improved oil palm genome assembly version as a palm genome reference to extend the date palm physical map. The improved genome of oil palm will enable molecular breeding approaches to expedite crop improvement, especially in the largest subfamily of Arecoideae, which consists of 107 species belonging to Arecaceae.

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.

A mini foxtail millet with an Arabidopsis-like life cycle as a C4 model system.

Foxtail millet (Setaria italica) is an important crop species and an emerging model plant for C4 grasses. However, functional genomics research on foxtail millet is challenging because of its long generation time, relatively large stature and recalcitrance to genetic transformation. Here we report the development of xiaomi, a rapid-cycling mini foxtail millet mutant as a C4 model system. Five to six generations of xiaomi can be grown in a year in growth chambers due to its short life cycle and small plant size, similar to Arabidopsis. A point mutation in the Phytochrome C (PHYC) gene was found to be causal for these characteristics. PHYC encodes a light receptor essential for photoperiodic flowering. A reference-grade xiaomi genome comprising 429.94 Mb of sequence was assembled and a gene-expression atlas from 11 different tissues was developed. These resources, together with an established highly efficient transformation system and a multi-omics database, make xiaomi an ideal model system for functional studies of C4 plants.

Major QTLs for Trunk Height and Correlated Agronomic Traits Provide Insights into Multiple Trait Integration in Oil Palm Breeding.

Superior oil yield is always the top priority of the oil palm industry. Short trunk height (THT) and compactness traits have become increasingly important to improve harvesting efficiency since the industry started to suffer yield losses due to labor shortages. Breeding populations with low THT and short frond length (FL) are actually available, such as Dumpy AVROS pisifera (DAV) and Gunung Melayu dura (GM). However, multiple trait stacking still remains a challenge for oil palm breeding, which usually requires 12-20 years to complete a breeding cycle. In this study, yield and height increment in the GM × GM (GM-3341) and the GM × DAV (GM-DAV-3461) crossing programs were evaluated and palms with good yield and smaller height increment were identified. In the GM-3341 family, non-linear THT growth between THT_2008 (seven years old) and THT_2014 (13 years old) was revealed by a moderate correlation, suggesting that inter-palm competition becomes increasingly important. In total, 19 quantitative trait loci (QTLs) for THT_2008 (8), oil per palm (O/P) (7) and FL (4) were localized on the GM-3341 linkage map, with an average mapping interval of 2.01 cM. Three major QTLs for THT_2008, O/P and FL are co-located on chromosome 11 and reflect the correlation of THT_2008 with O/P and FL. Multiple trait selection for high O/P and low THT (based on the cumulative effects of positive alleles per trait) identified one palm from 100 palms, but with a large starting population of 1000-1500 seedling per cross, this low frequency could be easily compensated for during breeding selection.

Transcriptome-wide identification and characterization of the Rab GTPase family in mango.

The Rab GTPase family plays a vital role in several plant physiological processes including fruit ripening. Fruit softening during ripening involves trafficking of cell wall polymers and enzymes between cellular compartments. Mango, an economically important fruit crop, is known for its delicious taste, exotic flavour and nutritional value. So far, there is a paucity of information on the mango Rab GTPase family. In this study, 23 genes encoding Rab proteins were identified in mango by a comprehensive in silico approach. Sequence alignment and similarity tree analysis with the model plant Arabidopsis as a reference enabled the bona fide assignment of the deduced mango proteins to classify into eight subfamilies. Expression analysis by RNA-Sequencing (RNA-Seq) showed that the Rab genes were differentially expressed in ripe and unripe mangoes suggesting the involvement of vesicle trafficking during ripening. Interaction analysis showed that the proteins involved in vesicle trafficking and cell wall softening were interconnected providing further evidence of the involvement of the Rab GTPases in fruit softening. Correlation analyses showed a significant relationship between the expression level of the RabA3 and RabA4 genes and fruit firmness at the unripe stage of the mango varieties suggesting that the differences in gene expression level might be associated with the contrasting firmness of these varieties. This study will not only provide new insights into the complexity of the ripening-regulated molecular mechanism but also facilitate the identification of potential Rab GTPases to address excessive fruit softening.