High-density linkage map construction and mapping QTL for yield and yield components in autotetraploid alfalfa using RAD-seq

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).

Accuracy of genomic selection for alfalfa biomass yield in two full-sib populations

Alfalfa (Medicago sativa) is one of the most important leguminous forages, widely planted in temperate and subtropical regions. As a homozygous tetraploid, its complex genetic background limits genetic improvement of biomass yield attributes through conventional breeding methods. Genomic selection (GS) could improve breeding efficiency by using high-density molecular markers that cover the whole genome to assess genomic breeding values. In this study, two full-sib F₁ populations, consisting of 149 and 392 individual plants (P149 and P392), were constructed using parents with differences in yield traits, and the yield traits of the F₁ populations were measured for several years in multiple environments. Comparisons of individual yields were greatly affected by environments, and the best linear unbiased prediction (BLUP) could accurately represent the original yield data. The two hybrid F₁ populations were genotyped using GBS and RAD-seq techniques, respectively, and 47,367 and 161,170 SNP markers were identified. To develop yield prediction models for a single location and across locations, genotypic and phenotypic data from alfalfa yields in multiple environments were combined with various prediction models. The prediction accuracies of the F₁ population, including 149 individuals, were 0.11 to 0.70, and those of the F₁ population, consisting of 392 individuals, were 0.14 to 0.67. The BayesC and RF models had the highest average prediction accuracy of 0.60 for two F₁ populations. The accuracy of the prediction models for P392 was higher than that of P149. By analyzing multiple prediction models, moderate prediction accuracies are obtained, although accuracies will likely decline across multiple locations. Our study provided evidence that GS can accelerate the improvement of alfalfa yield traits.

Combining QTL mapping and RNA-Seq Unravels candidate genes for Alfalfa (Medicago sativa L.) leaf development

BACKGROUND

Leaf size affects crop canopy morphology and photosynthetic efficiency, which can influence forage yield and quality. It is of great significance to mine the key genes controlling leaf development for breeding new alfalfa varieties. In this study, we mapped leaf length (LL), leaf width (LW), and leaf area (LA) in an F1 mapping population derived from a cultivar named ZhongmuNo.1 with larger leaf area and a landrace named Cangzhou with smaller leaf area.

RESULTS

This study showed that the larger LW was more conducive to increasing LA. A total of 24 significant quantitative trait loci (QTL) associated with leaf size were identified on both the paternal and maternal linkage maps. Among them, nine QTL explained about 11.50-22.45% phenotypic variation. RNA-seq analysis identified 2,443 leaf-specific genes and 3,770 differentially expressed genes. Combining QTL mapping, RNA-seq alalysis, and qRT-PCR, we identified seven candidate genes associated with leaf development in five major QTL regions.

CONCLUSION

Our study will provide a theoretical basis for marker-assisted breeding and lay a foundation for further revealing molecular mechanism of leaf development in alfalfa.

Application of machine learning to explore the genomic prediction accuracy of fall dormancy in autotetraploid alfalfa

Fall dormancy (FD) is an essential trait to overcome winter damage and for alfalfa (Medicago sativa) cultivar selection. The plant regrowth height after autumn clipping is an indirect way to evaluate FD. Transcriptomics, proteomics, and quantitative trait locus mapping have revealed crucial genes correlated with FD; however, these genes cannot predict alfalfa FD very well. Here, we conducted genomic prediction of FD using whole-genome SNP markers based on machine learning-related methods, including support vector machine (SVM) regression, and regularization-related methods, such as Lasso and ridge regression. The results showed that using SVM regression with linear kernel and the top 3000 genome-wide association study (GWAS)-associated markers achieved the highest prediction accuracy for FD of 64.1%. For plant regrowth height, the prediction accuracy was 59.0% using the 3000 GWAS-associated markers and the SVM linear model. This was better than the results using whole-genome markers (25.0%). Therefore, the method we explored for alfalfa FD prediction outperformed the other models, such as Lasso and ElasticNet. The study suggests the feasibility of using machine learning to predict FD with GWAS-associated markers, and the GWAS-associated markers combined with machine learning would benefit FD-related traits as well. Application of the methodology may provide potential targets for FD selection, which would accelerate genetic research and molecular breeding of alfalfa with optimized FD.

Construction of a high-density genetic map and localization of grazing-tolerant QTLs in Medicago falcata L

BACKGROUND

Using genomic DNA from 79 F1 plants resulted from a crossing between parents with strong and weak grazing tolerance in Medicago falcata L., we generated an EcoRI restriction site-associated DNA (RAD) sequencing library. After sequencing and assembly, a high-density genetic map with high-quality SNP markers was constructed, with a total length of 1312.238 cM and an average density of 0.844 SNP/cM.

METHODS

The phenotypic traits of 79 F1 families were observed and the QTLS of 6 traits were analyzed by interval mapping.

RESULTS

Sixty three QTLs were identified for seven traits with LOD values from 3 to 6 and the contribution rates from 15% to 30%. Among the 63 QTLs, 17 were for natural shoot height, 12 for rhizome Length, 10 for Shoot canopy diameter, 9 for Basal plant diameter, 6 for stem number, 5 for absolute shoot height, and 4 for rhizome width. These QTLs were concentrated on LG2, LG4, LG5, LG7, and LG8. LG6 had only 6 QTLs. According to the results of QTL mapping, comparison of reference genomes, and functional annotation, 10 candidate genes that may be related to grazing tolerance were screened. qRT-PCR analysis showed that two candidate genes (LOC11412291 and LOC11440209) may be the key genes related to grazing tolerance of M. falcata.

CONCLUSION

The identified trait-associated QTLs and candidate genes in this study will provide a solid foundation for future molecular breeding for enhanced grazing-tolerance in M. falcata.

Assessing the sensitivity of alfalfa yield potential to climate impact under future scenarios in Iran

Alfalfa is a major forage crop in Iran. To quantify the impact of climate change on its yield and water application for irrigation in Iran, the SSM-iCrop2 simulation model and two GCMs of IPSL and HadGEM were used under RCP4.5 and RCP8.5 for the 2050s. Despite increased temperatures, alfalfa forage yield will increase in most of the regions across the country due to acceleration of spring regrowth, a higher number of cuttings, increased incident and received photosynthetically active radiation because of increased growing season length due to increased temperatures, and positive effect of CO₂ on photosynthesis and radiation use efficiency. Changes in climatic conditions have had a significant impact on alfalfa net irrigation water, and the sum of net irrigation water has a direct relationship with alfalfa yield. Due to increased temperature, changes in rainfall, and improved concentration of atmospheric CO₂, the forage yield of alfalfa will fluctuate highly under all climatic scenarios. The highest increase and decrease in the average yield using the HadGEM model under RCP8.5 was 32 and - 33%, respectively. The average net irrigation water of alfalfa increased by 36% in the HadGEM model under RCP8.5 and decreased by - 41% in the IPSL model under RCP8.5. Therefore, to improve alfalfa yield in Iran in the future, strategies compatible such as high temperature-tolerant cultivars may be the most reasonable approaches.

RAD-Seq-Based High-Density Linkage Maps Construction and Quantitative Trait Loci Mapping of Flowering Time Trait in Alfalfa (Medicago sativa L.)

Alfalfa (Medicago sativa L.) is a perennial forage crop known as the "Queen of Forages." To dissect the genetic mechanism of flowering time (FT) in alfalfa, high-density linkage maps were constructed for both parents of an F1 mapping population derived from a cross between Cangzhou (P1) and ZhongmuNO.1 (P2), consisting of 150 progenies. The FT showed a transgressive segregation pattern in the mapping population. A total of 13,773 single-nucleotide polymorphism markers was obtained by using restriction-site associated DNA sequencing and distributed on 64 linkage groups, with a total length of 3,780.49 and 4,113.45 cM and an average marker interval of 0.58 and 0.59 cM for P1 and P2 parent, respectively. Quantitative trait loci (QTL) analyses were performed using the least square means of each year as well as the best linear unbiased prediction values across 4 years. Sixteen QTLs for FT were detected for P1 and 22 QTLs for P2, accounting for 1.40-16.04% of FT variation. RNA-Seq analysis at three flowering stages identified 5,039, 7,058, and 7,996 genes that were differentially expressed between two parents, respectively. Based on QTL mapping, DEGs analysis, and functional annotation, seven candidate genes associated with flowering time were finally detected. This study discovered QTLs and candidate genes for alfalfa FT, making it a useful resource for breeding studies on this essential crop.

Forage Yield, Canopy Characteristics, and Radiation Interception of Ten Alfalfa Varieties in an Arid Environment

An increasing demand for new and improved livestock forage products is driving the development of forage systems in arid regions. Our study evaluated the productivity of 10 alfalfa (Medicago sativa L.) varieties and the relationship between forage yield and canopy structure traits, such as plant height, branch number, stem/leaf ratio, and leaf area index in the arid Hexi Corridor, north-west China. Here, plant height, primary branch number per plant, and stem/leaf ratio were positively correlated with forage yield. In terms of a two-year total yield, Gannong No. 5 produced the highest value (13,923 kg ha⁻¹), followed by the WL342HQ (12,409 kg ha⁻¹), Phabulous (11,928 kg ha⁻¹), and Xinjiang Daye (11,416 kg ha⁻¹) varieties. Therefore, these four alfalfa varieties are suitable for large-scale cultivation in the Hexi Corridor region and other arid areas where the effect of precipitation is even larger than that of temperature. These results provide valuable information for the selection and cultivation of alfalfa varieties, which could improve forage yield and the production of livestock in arid regions.

Silencing of MsD14 Resulted in Enhanced Forage Biomass through Increasing Shoot Branching in Alfalfa (Medicago sativa L.)

Branching is one of the key determinants of plant architecture that dramatically affects crop yield. As alfalfa is the most important forage crop, understanding the genetic basis of branching in this plant can facilitate breeding for a high biomass yield. In this study, we characterized the strigolactone receptor gene MsD14 in alfalfa and demonstrated that MsD14 was predominantly expressed in flowers, roots, and seedpods. Furthermore, we found that MsD14 expression could significantly respond to strigolactone in alfalfa seedlings, and its protein was located in the nucleus, cytoplasm, and cytomembrane. Most importantly, transformation assays demonstrated that silencing of MsD14 in alfalfa resulted in increased shoot branching and forage biomass. Significantly, MsD14 could physically interact with AtMAX2 and MsMAX2 in the presence of strigolactone, suggesting a similarity between MsD14 and AtD14. Together, our results revealed the conserved D14-MAX2 module in alfalfa branching regulation and provided candidate genes for alfalfa high-yield molecular breeding.

Genome assembly of alfalfa cultivar zhongmu-4 and identification of SNPs associated with agronomic traits

Alfalfa (Medicago sativa L.) is the most important legume forage crop worldwide with high nutritional value and yield. For a long time, the breeding of alfalfa was hampered by lacking reliable information on the autotetraploid genome and molecular markers linked to important agronomic traits. We herein reported the de novo assembly of the allele-aware chromosome-level genome of Zhongmu-4, a cultivar widely cultivated in China, and a comprehensive database of genomic variations based on resequencing of 220 germplasms. Approximate 2.74 Gb contigs (N50 of 2.06 Mb), accounting for 88.39% of the estimated genome, were assembled, and 2.56 Gb contigs were anchored to 32 pseudo-chromosomes. A total of 34,922 allelic genes were identified from the allele-aware genome. We observed the expansion of gene families, especially those related to the nitrogen metabolism, and the increase of repetitive elements including transposable elements, which probably resulted in the increase of Zhongmu-4 genome compared with Medicago truncatula. Population structure analysis revealed that the accessions from Asia and South America had relatively lower genetic diversity than those from Europe, suggesting that geography may influence alfalfa genetic divergence during local adaption. Genome-wide association studies identified 101 single nucleotide polymorphisms (SNPs) associated with 27 agronomic traits. Two candidate genes were predicted to be correlated with fall dormancy and salt response. We believe that the allele-aware chromosome-level genome sequence of Zhongmu-4 combined with the resequencing data of the diverse alfalfa germplasms will facilitate genetic research and genomics-assisted breeding in variety improvement of alfalfa.

Genotyping Analysis by RAD-Seq Reads Is Useful to Assess the Genetic Identity and Relationships of Breeding Lines in Lavender Species Aimed at Managing Plant Variety Protection

Lavender species are widely distributed in their wild forms around the Mediterranean Basin and they are also cultivated worldwide as improved and registered clonal varieties. The economic interest of the species belonging to the Lavandula genus is determined by their use as ornamental plants and important source of essential oils that are destinated to the production of cosmetics, pharmaceuticals and foodstuffs. Because of the increasing number of cases of illegal commercialization of selected varieties, the protection of plant breeders’ rights has become of main relevance for the recognition of breeding companies’ royalties. With this aim, genomic tools based on molecular markers have been demonstrated to be very reliable and transferable among laboratories, and also much more informative than morphological descriptors. With the rising of the next-generation sequencing (NGS) technologies, several genotyping-by-sequencing approaches are now available. This study deals with a deep characterization of 15 varietal clones, belonging to two distinct Lavandula species, by means of restriction-site associated DNA sequencing (RAD-Seq). We demonstrated that this technology screens single nucleotide variants that enable to assess the genetic identity of individual accessions, to reconstruct genetic relationships among related breeding lines, to group them into genetically distinguishable main subclusters, and to assign their molecular lineages to distinct ancestors. Moreover, a number of polymorphic sites were identified within genes putatively involved in biosynthetic pathways related to both tissue pigmentation and terpene production, useful for breeding and/or protecting newly registered varieties. Overall, the results highlighted the presence of pure ancestries and interspecific hybrids for the analyzed Lavandula species, and demonstrated that RAD-Seq analysis is very informative and highly reliable for characterizing Lavandula clones and managing plant variety protection.

Uncovering phylogenetic relationships and genetic diversity of water dropwort using phenotypic traits and SNP markers

The water dropworts Oenanthe linearis Wall. ex DC. and O. javanica (Blume) DC. are aquatic perennial herbs that have been used in China as vegetables and traditional medicines. However, their phylogenetic relationships and genetic diversity are poorly understood. Here, we presented the phenotypic traits and genome-wide DNA marker-based analysis of 158 water dropwort accessions representing both species. The analysis revealed that Oenanthe linearis was readily segregated into linear-leaf and deep-cleft leaf water dropworts according to their leaf shapes at flowering. Oenanthe javanica was classified by clustering analysis into two clusters based mainly on the morphological characteristics of their ultimate segments (leaflets). A set of 11 493 high-quality single-nucleotide polymorphisms was identified and used to construct a phylogenetic tree. There was strong discrimination between O. linearis and O. javanica, which was consistent with their phenotype diversification. The population structure and phylogenetic tree analyses suggested that the O. linearis accessions formed two major groups, corresponding to the linear-leaf and deep-cleft leaf types. The most obvious phenotypic differences between them were fully expressed at the reproductive growth stage. A single-nucleotide polymorphism-based analysis revealed that the O. javanica accessions could be categorized into groups I andII. However, this finding did not entirely align with the clusters revealed by morphological classification. Landraces were clustered into one group along with the remaining wild accessions. Hence, water dropwort domestication was short in duration. The level of genetic diversity for O. linearis (π = 0.1902) was slightly lower than that which was estimated for O. javanica (π = 0.2174). There was a low level of genetic differentiation between O. linearis and O. javanica (Fst = 0.0471). The mean genetic diversity among accessions ranged from 0.1818 for the linear-leaf types to 0.2318 for the groupII accessions. The phenotypic traits and the single-nucleotide polymorphism markers identified here lay empirical foundation for future genomic studies on water dropwort.

Identification and Validation of Major QTLs, Epistatic Interactions, and Candidate Genes for Soybean Seed Shape and Weight Using Two Related RIL Populations

Understanding the genetic mechanism underlying seed size, shape, and weight is essential for enhancing soybean cultivars. High-density genetic maps of two recombinant inbred line (RIL) populations, LM6 and ZM6, were evaluated across multiple environments to identify and validate M-QTLs as well as identify candidate genes behind major and stable quantitative trait loci (QTLs). A total of 239 and 43 M-QTLs were mapped by composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM) approaches, from which 180 and 18, respectively, are novel QTLs. Twenty-two QTLs including four novel major QTLs were validated in the two RIL populations across multiple environments. Moreover, 18 QTLs showed significant AE effects, and 40 pairwise of the identified QTLs exhibited digenic epistatic effects. Thirty-four QTLs associated with seed flatness index (FI) were identified and reported here for the first time. Seven QTL clusters comprising several QTLs for seed size, shape, and weight on genomic regions of chromosomes 3, 4, 5, 7, 9, 17, and 19 were identified. Gene annotations, gene ontology (GO) enrichment, and RNA-seq analyses of the genomic regions of those seven QTL clusters identified 47 candidate genes for seed-related traits. These genes are highly expressed in seed-related tissues and nodules, which might be deemed as potential candidate genes regulating the seed size, weight, and shape traits in soybean. This study provides detailed information on the genetic basis of the studied traits and candidate genes that could be efficiently implemented by soybean breeders for fine mapping and gene cloning, and for marker-assisted selection (MAS) targeted at improving these traits individually or concurrently.

Genetic Mapping by Sequencing More Precisely Detects Loci Responsible for Anaerobic Germination Tolerance in Rice

Direct seeded rice (DSR) is a mainstay for planting rice in the Americas, and it is rapidly becoming more popular in Asia. It is essential to develop rice varieties that are suitable for this type of production system. ASD1, a landrace from India, possesses several traits desirable for direct-seeded fields, including tolerance to anaerobic germination (AG). To map the genetic basis of its tolerance, we examined a population of 200 F_2:3 families derived from a cross between IR64 and ASD1 using the restriction site-associated DNA sequencing (RAD-seq) technology. This genotyping platform enabled the identification of 1921 single nucleotide polymorphism (SNP) markers to construct a high-resolution genetic linkage map with an average interval of 0.9 cM. Two significant quantitative trait loci (QTLs) were detected on chromosomes 7 and 9, qAG7 and qAG9, with LOD scores of 7.1 and 15.0 and R² values of 15.1 and 29.4, respectively. Here, we obtained more precise locations of the QTLs than traditional simple sequence repeat and low-density SNP genotyping methods and may help further dissect the genetic factors of these QTLs.

Identification of Genetic Loci Associated With Crude Protein Content and Fiber Composition in Alfalfa (Medicago sativa L.) Using QTL Mapping

Forage quality determined mainly by protein content and fiber composition has a crucial influence on digestibility and nutrition intake for animal feeding. To explore the genetic basis of quality traits, we conducted QTL mapping based on the phenotypic data of crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and lignin of an F1 alfalfa population generated by crossing of two alfalfa parents with significant difference in quality. In total, 83 QTLs were identified with contribution to the phenotypic variation (PVE) ranging from 1.45 to 14.35%. Among them, 47 QTLs interacted significantly with environment and 12 QTLs were associated with more than one trait. Epistatic effect was also detected for 73 pairs of QTLs with PVE of 1.08-14.06%. The results suggested that the inheritance of quality-related traits was jointly affected by additive, epistasis and environment. In addition, 83.33% of the co-localized QTLs were shared by ADF and NDF with the same genetic direction, while the additive effect of crude protein-associated QTLs was opposite to that fiber composition on the same locus, suggesting that the loci may antagonistically contribute to protein content and fiber composition. Further analysis of a QTL related to all the three traits of fiber composition (qNDF1C, qADF1C-2, and qlignin1C-2) showed that five candidate genes were homologs of cellulose synthase-like protein A1 in Medicago truncatula, indicating the potential role in fiber synthesis. For the protein-associated loci we identified, qCP4C-1 was located in the shortest region (chr 4.3 39.3-39.4 Mb), and two of the seven corresponding genes in this region were predicted to be E3 ubiquitin-protein ligase in protein metabolism. Therefore, our results provide some reliable regions significantly associated with alfalfa quality, and identification of the key genes would facilitate marker-assisted selection for favorable alleles in breeding program of alfalfa quality improvement.

Development of EST-SSR markers and association mapping with floral traits in Syringa oblata

BACKGROUND

Lilac (Syringa oblata) is an important woody plant with high ornamental value. However, very limited genetic marker resources are currently available, and little is known about the genetic architecture of important ornamental traits for S. oblata, which is hindering its genetic studies. Therefore, it is of great significance to develop effective molecular markers and understand the genetic architecture of complex floral traits for the genetic research of S. oblata.

RESULTS

In this study, a total of 10,988 SSRs were obtained from 9864 unigene sequences with an average of one SSR per 8.13 kb, of which di-nucleotide repeats were the dominant type (32.86%, 3611). A set of 2042 primer pairs were validated, out of which 932 (45.7%) exhibited successful amplifications, and 248 (12.1%) were polymorphic in eight S. oblata individuals. In addition, 30 polymorphic EST-SSR markers were further used to assess the genetic diversity and the population structure of 192 cultivated S. oblata individuals. Two hundred thirty-four alleles were detected, and the PIC values ranged from 0.23 to 0.88 with an average of 0.51, indicating a high level of genetic diversity within this cultivated population. The analysis of population structure showed two major subgroups in the association population. Finally, 20 significant associations were identified involving 17 markers with nine floral traits using the mixed linear model. Moreover, marker SO104, SO695 and SO790 had significant relationship with more than one trait.

CONCLUSION

The results showed newly developed markers were valuable resource and provided powerful tools for genetic breeding of lilac. Beyond that, our study could serve an efficient foundation for further facilitate genetic improvement of floral traits for lilac.