An international reference consensus genetic map with 897 marker loci based on 11 mapping populations for tetraploid groundnut (Arachis hypogaea L.)

Marker-assisted introgression to improve the oleic acid content in the TMV 7 groundnut (Arachis hypogaea L.) variety suitable for the oil industry

BACKGROUND

Improving the quality and shelf life of groundnut oil is one of the foremost objectives of groundnut breeding programmes. This can be achieved by marker-assisted introgression, a technique that efficiently and precisely enables breeders to develop plants with enhanced qualities. This study focused on improving the oleic acid content of an elite groundnut variety, TMV 7, by introgressing a recessive mutation responsible for the increase in oleic acid from ICG 15419. Hybridization was performed between the donor and recurrent parents to develop the F1, BC1F1, BC2F1 and BC2F2 populations. Introgressed lines with increased oleic acid in the genetic background of TMV 7 were identified using allele-specific marker, F435-F, F435SUB-R and a set of SSR markers were employed to recover the genome of the recurrent parent.

RESULTS

With two backcrosses, a total of ten homozygous plants in the BC2F2 population were identified with oleic acid content ranging from 54.23 to 57.72% causing an increase of 36% over the recurrent parent. Among the ten lines, the line IL-23 exhibited the highest level of recurrent parent genome recovery of 91.12%.

CONCLUSIONS

The phenotypic evaluation of 10 homozygous introgressed lines indicated fewer differences for all other traits under study compared to the recurrent parent, except for oleic acid and linoleic acid content confirming the genetic background of the recurrent parent. The identified lines will be subjected to multilocation trials before their commercial release.

Does improved oleic acid content due to marker-assisted introgression of ahFAD2 mutant alleles in peanuts alter its mineral and vitamin composition?

Peanuts (Arachis hypogaea L.) with high oleic acid content have extended shelf life and several health benefits. Oleic, linoleic, and palmitic acid contents in peanuts are regulated by ahFAD2A and ahFAD2B mutant alleles. In the present study, ahFAD2A and ahFAD2B mutant alleles from SunOleic 95R were introgressed into two popular peanut cultivars, GG-7 and TKG19A, followed by markers-assisted selection (MAS) and backcrossing (MABC). A total of 22 MAS and three MABC derived lines were developed with increased oleic acid (78-80%) compared to those of GG 7 (40%) and TKG 19A (50%). Peanut kernel mineral and vitamin composition remained unchanged, while potassium content was altered in high oleic ingression lines. Two introgression lines, HOMS Nos. 37 and 113 had over 10% higher pooled pod yield than respective best check varieties. More than 70% recurrent parent genome recovery was observed in HOMS-37 and HOMS-113 through recombination breeding. However, the absence of recombination in the vicinity of the target locus resulted in its precise introgression along with ample background genome recovery. Selected introgression lines could be released for commercial cultivation based on potential pod yield and oleic acid content.

Insights into the Genomic Architecture of Seed and Pod Quality Traits in the U.S. Peanut Mini-Core Diversity Panel

Traits such as seed weight, shelling percent, percent sound mature kernels, and seed dormancy determines the quality of peanut seed. Few QTL (quantitative trait loci) studies using biparental mapping populations have identified QTL for seed dormancy and seed grade traits. Here, we report a genome-wide association study (GWAS) to detect marker–trait associations for seed germination, dormancy, and seed grading traits in peanut. A total of 120 accessions from the U.S. peanut mini-core collection were evaluated for seed quality traits and genotyped using Axiom SNP (single nucleotide polymorphism) array for peanut. We observed significant variation in seed quality traits in different accessions and different botanical varieties. Through GWAS, we were able to identify multiple regions associated with sound mature kernels, seed weight, shelling percent, seed germination, and dormancy. Some of the genomic regions that were SNP associated with these traits aligned with previously known QTLs. For instance, QTL for seed dormancy has been reported on chromosome A05, and we also found SNP on the same chromosome associated with seed dormancy, explaining around 20% of phenotypic variation. In addition, we found novel genomic regions associated with seed grading, seed germination, and dormancy traits. SNP markers associated with seed quality and dormancy identified here can accelerate the selection process. Further, exploring the function of candidate genes identified in the vicinity of the associated marker will assist in understanding the complex genetic network that governs seed quality.

Improved Genetic Map Identified Major QTLs for Drought Tolerance- and Iron Deficiency Tolerance-Related Traits in Groundnut

A deep understanding of the genetic control of drought tolerance and iron deficiency tolerance is essential to hasten the process of developing improved varieties with higher tolerance through genomics-assisted breeding. In this context, an improved genetic map with 1205 loci was developed spanning 2598.3 cM with an average 2.2 cM distance between loci in the recombinant inbred line (TAG 24 × ICGV 86031) population using high-density 58K single nucleotide polymorphism (SNP) “Axiom_Arachis” array. Quantitative trait locus (QTL) analysis was performed using extensive phenotyping data generated for 20 drought tolerance- and two iron deficiency tolerance-related traits from eight seasons (2004–2015) at two locations in India, one in Niger, and one in Senegal. The genome-wide QTL discovery analysis identified 19 major main-effect QTLs with 10.0–33.9% phenotypic variation explained (PVE) for drought tolerance- and iron deficiency tolerance- related traits. Major main-effect QTLs were detected for haulm weight (20.1% PVE), SCMR (soil plant analytical development (SPAD) chlorophyll meter reading, 22.4% PVE), and visual chlorosis rate (33.9% PVE). Several important candidate genes encoding glycosyl hydrolases; malate dehydrogenases; microtubule-associated proteins; and transcription factors such as MADS-box, basic helix-loop-helix (bHLH), NAM, ATAF, and CUC (NAC), and myeloblastosis (MYB) were identified underlying these QTL regions. The putative function of these genes indicated their possible involvement in plant growth, development of seed and pod, and photosynthesis under drought or iron deficiency conditions in groundnut. These genomic regions and candidate genes, after validation, may be useful to develop molecular markers for deploying genomics-assisted breeding for enhancing groundnut yield under drought stress and iron-deficient soil conditions.

Transcriptome Analysis Identified Coordinated Control of Key Pathways Regulating Cellular Physiology and Metabolism upon Aspergillus flavus Infection Resulting in Reduced Aflatoxin Production in Groundnut

Aflatoxin-affected groundnut or peanut presents a major global health issue to both commercial and subsistence farming. Therefore, understanding the genetic and molecular mechanisms associated with resistance to aflatoxin production during host–pathogen interactions is crucial for breeding groundnut cultivars with minimal level of aflatoxin contamination. Here, we performed gene expression profiling to better understand the mechanisms involved in reduction and prevention of aflatoxin contamination resulting from Aspergillus flavus infection in groundnut seeds. RNA sequencing (RNA-Seq) of 16 samples from different time points during infection (24 h, 48 h, 72 h and the 7th day after inoculation) in U 4-7-5 (resistant) and JL 24 (susceptible) genotypes yielded 840.5 million raw reads with an average of 52.5 million reads per sample. A total of 1779 unique differentially expressed genes (DEGs) were identified. Furthermore, comprehensive analysis revealed several pathways, such as disease resistance, hormone biosynthetic signaling, flavonoid biosynthesis, reactive oxygen species (ROS) detoxifying, cell wall metabolism and catabolizing and seed germination. We also detected several highly upregulated transcription factors, such as ARF, DBB, MYB, NAC and C2H2 in the resistant genotype in comparison to the susceptible genotype after inoculation. Moreover, RNA-Seq analysis suggested the occurrence of coordinated control of key pathways controlling cellular physiology and metabolism upon A. flavus infection, resulting in reduced aflatoxin production.

Genome-based trait prediction in multi- environment breeding trials in groundnut

KEY MESSAGE

Comparative assessment identified naïve interaction model, and naïve and informed interaction GS models suitable for achieving higher prediction accuracy in groundnut keeping in mind the high genotype × environment interaction for complex traits. Genomic selection (GS) can be an efficient and cost-effective breeding approach which captures both small- and large-effect genetic factors and therefore promises to achieve higher genetic gains for complex traits such as yield and oil content in groundnut. A training population was constituted with 340 elite lines followed by genotyping with 58 K 'Axiom_Arachis' SNP array and phenotyping for key agronomic traits at three locations in India. Four GS models were tested using three different random cross-validation schemes (CV0, CV1 and CV2). These models are: (1) model 1 (M1 = E + L) which includes the main effects of environment (E) and line (L); (2) model 2 (M2 = E + L + G) which includes the main effects of markers (G) in addition to E and L; (3) model 3 (M3 = E + L + G + GE), a naïve interaction model; and (4) model 4 (E + L + G + LE + GE), a naïve and informed interaction model. Prediction accuracy estimated for four models indicated clear advantage of the inclusion of marker information which was reflected in better prediction accuracy achieved with models M2, M3 and M4 as compared to M1 model. High prediction accuracies (> 0.600) were observed for days to 50% flowering, days to maturity, hundred seed weight, oleic acid, rust@90 days, rust@105 days and late leaf spot@90 days, while medium prediction accuracies (0.400-0.600) were obtained for pods/plant, shelling  %, and total yield/plant. Assessment of comparative prediction accuracy for different GS models to perform selection for untested genotypes, and unobserved and unevaluated environments provided greater insights on potential application of GS breeding in groundnut.

Identification of novel QTLs for late leaf spot resistance and validation of a major rust QTL in peanut (Arachis hypogaea L.)

Co-occurrence of two devastating foliar-fungal diseases of peanut, viz., late leaf spot (LLS), and rust may cause heavy yield loss besides adversely affecting the quality of kernel and fodder. This study reports the mapping of seven novel stress-related candidate EST-SSRs in a region having major QTLs for LLS and rust diseases using an F₂ mapping population (GJG17 × GPBD4) consisting of 328 individuals. The parental polymorphism using 1311 SSRs revealed 84 SSRs (6.4%) as polymorphic and of these 70 SSRs could be mapped on 14 linkage groups (LG). QTL analysis has identified a common QTL (LLS_QTL1/Rust_QTL) for LLS and rust diseases in the map interval of 1.41 cM on A03 chromosome, explaining 47.45% and 70.52% phenotypic variations, respectively. Another major QTL for LLS (LLS_QTL1), explaining a 29.06% phenotypic variation was also found on LG_A03. A major rust QTL has been validated which was found harboring R-gene and resistance-related genes having a role in inducing hypersensitive response (HR). Further, 23 linked SSRs including seven novel EST-SSRs were also validated in 177 diverse Indian groundnut genotypes. Twelve genotypes resistant to both LLS and rust were found carrying the common (rust and LLS) QTL region, LLS QTL region, and surrounding regions. These identified and validated candidate EST-SSR markers would be of great use for the peanut breeding groups working for the improvement of foliar-fungal disease resistance.

Review: Climate change impacts on food security- focus on perennial cropping systems and nutritional value

Anthropogenic increases in fossil fuel emissions have been a primary driver of increased concentrations of atmospheric carbon dioxide ([CO₂]) and other greenhouse gases resulting in warmer temperatures, alterations in precipitation patterns, and increased occurrence of extreme weather events in terrestrial areas across the globe. In agricultural growing regions, alterations in climate can challenge plant productivity in ways that impact the ability of the world to sustain adequate food production for a growing and increasingly affluent population with shifting access to affordable and nutritious food. While the knowledge gap that exists regarding potential climate change impacts is large across agriculture, it is especially large in specialty cropping systems. This includes fruit and vegetable crops, and perennial cropping systems which also contribute (along with row crops) to our global diet. In order to obtain a comprehensive view of the true impact of climate change on our global food supply, we must expand our narrow focus from improving yield and plant productivity to include the impact of climate change on the nutritional value of these crops. In order to address these questions, we need a multi-faceted approach that integrates physiology and genomics tools and conducts comprehensive experiments under realistic depictions of future projected climate. This review describes gaps in our knowledge in relation to these responses, and future questions and actions that are needed to develop a sustainable future food supply in light of global climate change.

Steady expression of high oleic acid in peanut bred by marker-assisted backcrossing for fatty acid desaturase mutant alleles and its effect on seed germination along with other seedling traits

Peanut (Arachis hypogaea L.) is an important nutrient-rich food legume and valued for its good quality cooking oil. The fatty acid content is the major determinant of the quality of the edible oil. The oils containing higher monounsaturated fatty acid are preferred for improved shelf life and potential health benefits. Therefore, a high oleic/linoleic fatty acid ratio is the target trait in an advanced breeding program. The two mutant alleles, ahFAD2A (on linkage group a09) and ahFAD2B (on linkage group b09) control fatty acid composition for higher oleic/linoleic ratio in peanut. In the present study, marker-assisted backcrossing was employed for the introgression of two FAD2 mutant alleles from SunOleic95R into the chromosome of ICGV06100, a high oil content peanut breeding line. In the marker-assisted backcrossing-introgression lines, a 97% increase in oleic acid, and a 92% reduction in linoleic acid content was observed in comparison to the recurrent parent. Besides, the oleic/linoleic ratio was increased to 25 with respect to the recurrent parent, which was only 1.2. The most significant outcome was the stable expression of oil-content, oleic acid, linoleic acid, and palmitic acid in the marker-assisted backcrossing-introgression lines over the locations. No significant difference was observed between high oleic and normal oleic in peanuts for seedling traits except germination percentage. In addition, marker-assisted backcrossing-introgression lines exhibited higher yield and resistance to foliar fungal diseases, i.e., late leaf spot and rust.

A new source of root-knot nematode resistance from Arachis stenosperma incorporated into allotetraploid peanut (Arachis hypogaea)

Root-knot nematode is a very destructive pathogen, to which most peanut cultivars are highly susceptible. Strong resistance is present in the wild diploid peanut relatives. Previously, QTLs controlling nematode resistance were identified on chromosomes A02, A04 and A09 of Arachis stenosperma. Here, to study the inheritance of these resistance alleles within the genetic background of tetraploid peanut, an F₂ population was developed from a cross between peanut and an induced allotetraploid that incorporated A. stenosperma, [Arachis batizocoi x A. stenosperma]^4×. This population was genotyped using a SNP array and phenotyped for nematode resistance. QTL analysis allowed us to verify the major-effect QTL on chromosome A02 and a secondary QTL on A09, each contributing to a percentage reduction in nematode multiplication up to 98.2%. These were validated in selected F_2:3 lines. The genome location of the large-effect QTL on A02 is rich in genes encoding TIR-NBS-LRR protein domains that are involved in plant defenses. We conclude that the strong resistance to RKN, derived from the diploid A. stenosperma, is transferrable and expressed in tetraploid peanut. Currently it is being used in breeding programs for introgressing a new source of nematode resistance and to widen the genetic basis of agronomically adapted peanut lines.

Genetics, genomics and breeding of groundnut (Arachis hypogaea L.)

Groundnut is an important food and oil crop in the semiarid tropics, contributing to household food consumption and cash income. In Asia and Africa, yields are low attributed to various production constraints. This review paper highlights advances in genetics, genomics and breeding to improve the productivity of groundnut. Genetic studies concerning inheritance, genetic variability and heritability, combining ability and trait correlations have provided a better understanding of the crop's genetics to develop appropriate breeding strategies for target traits. Several improved lines and sources of variability have been identified or developed for various economically important traits through conventional breeding. Significant advances have also been made in groundnut genomics including genome sequencing, marker development and genetic and trait mapping. These advances have led to a better understanding of the groundnut genome, discovery of genes/variants for traits of interest and integration of marker-assisted breeding for selected traits. The integration of genomic tools into the breeding process accompanied with increased precision of yield trialing and phenotyping will increase the efficiency and enhance the genetic gain for release of improved groundnut varieties.

Marker-assisted backcrossing to improve seed oleic acid content in four elite and popular peanut (Arachis hypogaea L.) cultivars with high oil content

High oleic acid composition is an important determinant of seed quality in peanut (Arachis hypogaea) in regard to its nutritional benefits for human health and prolonged shelf-life for peanut products. To improve the oleic acid content of popular peanut cultivars in China, four peanut cultivars of different market types were hybridized with high-oleic-acid donors and backcrossed for four generations as recurrent parents using fad2 marker-assisted backcross selection. Seed quality traits in advanced generations derived by selfing were assessed using near-infrared reflectance spectroscopy for detection of oleic acid and Kompetitive allele-specific PCR (KASP) screening of fad2 mutant markers. Twenty-four high-oleic-acid lines of BC₄F₄ and BC₄F₅ populations, with morphological features and agronomic traits similar to those of the recurrent parents, were obtained within 5 years. The genetic backgrounds of BC₄F₅ lines were estimated using the KASP assay, which revealed the genetic background recovery rate was 79.49%-92.31%. The superior lines raised are undergoing a multi-location test for cultivar registration and release. To our knowledge, this is the first application of single nucleotide polymorphism markers based on the high-throughput and cost-effective KASP assay for detection of fad2 mutations and genetic background evaluation in a peanut breeding program.

Mapping of a dominant rust resistance gene revealed two R genes around the major Rust_QTL in cultivated peanut (Arachis hypogaea L.)

A consensus rust QTL was identified within a 1.25 cM map interval of A03 chromosome in cultivated peanut. This map interval contains a TIR-NB-LRR R gene and four pathogenesis-related genes. Disease resistance in plants is manifested due to the specific interaction between the R gene product and its cognate avirulence gene product (AVR) in the pathogen. Puccinia arachidis Speg. causes rust disease and inflicts economic damages to peanut. Till now, no experimental evidence is known for the action of R gene in peanut for rust resistance. A fine mapping approach towards the development of closely linked markers for rust resistance gene was undertaken in this study. Phenotyping of an RIL population at five environments for field rust score and subsequent QTL analysis has identified a 1.25 cM map interval that harbored a consensus major Rust_QTL in A03 chromosome. This Rust_QTL is flanked by two SSR markers: FRS72 and SSR_GO340445. Both the markers clearly identified strong association of the mapped region with rust reaction in both resistant and susceptible genotypes from a collection of 95 cultivated peanut germplasm. This 1.25 cM map interval contained 331.7 kb in the physical map of A. duranensis and had a TIR-NB-LRR category R gene (Aradu.Z87JB) and four glucan endo-1,3 β glucosidase genes (Aradu.RKA6 M, Aradu.T44NR, Aradu.IWV86 and Aradu.VG51Q). Another resistance gene analog was also found in the vicinity of mapped Rust_QTL. The sequence between SSR markers, FRS72 and FRS49, contains an LRR-PK (Aradu.JG217) which is equivalent to RHG4 in soybean. Probably, the protein kinase domain in AhRHG4 acts as an integrated decoy for the cognate AVR from Puccinia arachidis and helps the TIR-NB-LRR R-protein to initiate a controlled program cell death in resistant peanut plants.

High-Density Genetic Map Construction and Identification of QTLs Controlling Oleic and Linoleic Acid in Peanut using SLAF-seq and SSRs

The cultivated peanut, A. hypogaea L., is an important oil and food crop globally.High-density genetic linkage mapping is a valuable and effective method for exploring complex quantitative traits. In this context, a recombinant inbred line (RIL) of 146 lines was developed by crossing Huayu28 and P76. We developed 433,679 high-quality SLAFs, of which 29,075 were polymorphic. 4,817 SLAFs were encoded and grouped into different segregation patterns. A high-resolution genetic map containing 2,334 markers (68 SSRs and 2,266 SNPs) on 20 linkage groups (LGs) spanning 2586.37 cM was constructed for peanut. The average distance between adjacent markers was 2.25 cM. Based on phenotyping in seven environments, QTLs for oleic acid (C18:1), linoleic acid (C18:2) and the ratio of oleic acid to linoleic acid (O/L) were identified and positioned on linkage groups A03, A04, A09, B09 and B10. Marker2575339 and Marker2379598 in B09 were associated with C18:1, C18:2 and O/L in seven environments, Marker4391589 and Marker4463600 in A09 were associated with C18:1, C18:2 and O/L in six environments. This map exhibits high resolution and accuracy, which will facilitate QTL discovery for essential agronomic traits in peanut.

A consensus linkage map of lentil based on DArT markers from three RIL mapping populations

Background

Lentil (Lens culinaris ssp. culinaris Medikus) is a diploid (2n = 2x = 14), self-pollinating grain legume with a haploid genome size of about 4 Gbp and is grown throughout the world with current annual production of 4.9 million tonnes.

Materials and methods

A consensus map of lentil (Lens culinaris ssp. culinaris Medikus) was constructed using three different lentils recombinant inbred line (RIL) populations, including “CDC Redberry” x “ILL7502” (LR8), “ILL8006” x “CDC Milestone” (LR11) and “PI320937” x “Eston” (LR39).

Results

The lentil consensus map was composed of 9,793 DArT markers, covered a total of 977.47 cM with an average distance of 0.10 cM between adjacent markers and constructed 7 linkage groups representing 7 chromosomes of the lentil genome. The consensus map had no gap larger than 12.67 cM and only 5 gaps were found to be between 12.67 cM and 6.0 cM (on LG3 and LG4). The localization of the SNP markers on the lentil consensus map were in general consistent with their localization on the three individual genetic linkage maps and the lentil consensus map has longer map length, higher marker density and shorter average distance between the adjacent markers compared to the component linkage maps.

Conclusion

This high-density consensus map could provide insight into the lentil genome. The consensus map could also help to construct a physical map using a Bacterial Artificial Chromosome library and map based cloning studies. Sequence information of DArT may help localization of orientation scaffolds from Next Generation Sequencing data.

Unraveling the molecules hidden in the gray shadows of quantitative disease resistance to pathogens

Una de las preguntas más desafiantes del fitomejoramiento y de la fitopatología molecular es ¿cuáles son las bases genéticas y moleculares de la resistencia cuantitativa a enfermedades?. El escaso conocimiento de cómo este tipo de resistencia funciona ha obstaculizado que los fitomejoradores la aprovecharlo plenamente. Para superar estos obstáculos se han desarrollado nuevas metodologías para el estudio de rasgos cuantitativos. Los enfoques como el mapeo genético, la identificación de loci de rasgos cuantitativos (QTL) y el mapeo por asociaciones, incluyendo el enfoque de genes candidatos y los estudios de asociación amplia del genoma, se han llevado a cabo históricamente para describir rasgos cuantitativos y por lo tanto para estudiar QDR. Además, se han proporcionado grandes avances en la obtención de datos fenotípicos cuantitativos para mejorar estos análisis. Recientemente, algunos genes asociados a QDR han sido clonados, lo que conduce a nuevas hipótesis sobre las bases moleculares de este tipo de resistencia. En esta revisión presentamos los avances más recientes sobre QDR y la correspondiente aplicación, que han permitido postular nuevas ideas que pueden ayudar a construir nuevos modelos. Algunas de las hipótesis presentadas aquí como posibles explicaciones para QDR están relacionadas con el nivel de expresión y el splicing alternativo de algunos genes relacionados con la defensa, la acción de "alelos débiles" de genes R, la presencia de variantes alélicas en los genes implicados en la respuesta de defensa y un papel central de quinasas o pseudoqinasas. Con la información recapitulada en esta revisión es posible concluir que la distinción conceptual entre resistencia cualitativa y cuantitativa puede ser cuestionada ya que ambos comparten importantes componentes.

Genome-wide SNP Genotyping Resolves Signatures of Selection and Tetrasomic Recombination in Peanut

Peanut (Arachis hypogaea; 2n = 4x = 40) is a nutritious food and a good source of vitamins, minerals, and healthy fats. Expansion of genetic and genomic resources for genetic enhancement of cultivated peanut has gained momentum from the sequenced genomes of the diploid ancestors of cultivated peanut. To facilitate high-throughput genotyping of Arachis species, 20 genotypes were re-sequenced and genome-wide single nucleotide polymorphisms (SNPs) were selected to develop a large-scale SNP genotyping array. For flexibility in genotyping applications, SNPs polymorphic between tetraploid and diploid species were included for use in cultivated and interspecific populations. A set of 384 accessions was used to test the array resulting in 54 564 markers that produced high-quality polymorphic clusters between diploid species, 47 116 polymorphic markers between cultivated and interspecific hybrids, and 15 897 polymorphic markers within A. hypogaea germplasm. An additional 1193 markers were identified that illuminated genomic regions exhibiting tetrasomic recombination. Furthermore, a set of elite cultivars that make up the pedigree of US runner germplasm were genotyped and used to identify genomic regions that have undergone positive selection. These observations provide key insights on the inclusion of new genetic diversity in cultivated peanut and will inform the development of high-resolution mapping populations. Due to its efficiency, scope, and flexibility, the newly developed SNP array will be very useful for further genetic and breeding applications in Arachis.

Genetic mapping of yield traits using RIL population derived from Fuchuan Dahuasheng and ICG6375 of peanut (Arachis hypogaea L.)

The genetic architecture determinants of yield traits in peanut (Arachis hypogaea L.) are poorly understood. In the present study, an effort was made to map quantitative trait loci (QTLs) for yield traits using recombinant inbred lines (RIL). A genetic linkage map was constructed containing 609 loci, covering a total of 1557.48 cM with an average distance of 2.56 cM between adjacent markers. The present map exhibited good collinearity with the physical map of diploid species of Arachis. Ninety-two repeatable QTLs were identified for 11 traits including height of main stem, total branching number, and nine pod- and seed-related traits. Of the 92 QTLs, 15 QTLs were expressed across three environments and 65 QTLs were newly identified. Twelve QTLs for the height of main stem and the pod- and seed-related traits explaining more than 10 % of phenotypic variation showed a great potential for marker-assisted selection in improving these traits. The trait-by-trait meta-analysis revealed 33 consensus QTLs. The consensus QTLs and other QTLs were further integrated into 29 pleiotropic unique QTLs with the confidence interval of 1.86 cM on average. The significant co-localization of QTLs was consistent with the significant phenotypic correlations among these traits. The complexity of the genetic architecture of yield traits was demonstrated. The present QTLs for pod- and seed-related traits could be the most fundamental genetic factors contributing to the yield traits in peanut. The results provide a good foundation for fine mapping, cloning and designing molecular breeding of favorable genes in peanut.

Development and deployment of a high-density linkage map identified quantitative trait loci for plant height in peanut (Arachis hypogaea L.)

Plant height is one of the most important architecture traits in crop plants. In peanut, the genetic basis of plant height remains ambiguous. In this context, we genotyped a recombinant inbred line (RIL) population with 140 individuals developed from a cross between two peanut varieties varying in plant height, Zhonghua 10 and ICG 12625. Genotyping data was generated for 1,175 SSR and 42 transposon polymorphic markers and a high-density genetic linkage map was constructed with 1,219 mapped loci covering total map length of 2,038.75 cM i.e., accounted for nearly 80% of the peanut genome. Quantitative trait locus (QTL) analysis using genotyping and phenotyping data for three environments identified 8 negative-effect QTLs and 10 positive-effect QTLs for plant height. Among these QTLs, 8 QTLs had a large contribution to plant height that explained ≥10% phenotypic variation. Two major-effect consensus QTLs namely cqPHA4a and cqPHA4b were identified with stable performance across three environments. Further, the allelic recombination of detected QTLs proved the existence of the phenomenon of transgressive segregation for plant height in the RIL population. Therefore, this study not only successfully reported a high-density genetic linkage map of peanut and identified genomic region controlling plant height but also opens opportunities for further gene discovery and molecular breeding for plant height in peanut.

Target Amplicon Sequencing for Genotyping Genome-Wide Single Nucleotide Polymorphisms Identified by Whole-Genome Resequencing in Peanut

Genome-wide genotyping data regarding breeding materials are essential resources for improving breeding efficiency, especially in plants with complex genomes with a high degree of polyploidy. Several current breeding efforts in cultivated peanut ( L.), which has a tetraploid genome, are devoted to developing high oleic acid cultivars. Genetic maps for such breeding programs have been developed using simple-sequence repeat (SSR) markers, the use of which requires time-consuming electrophoretic analyses. Next-generation sequencing (NGS) technology can overcome this technical hurdle. Initially, we attempted double-digest restriction site-associated DNA sequencing on peanut breeding materials used to develop high oleic acid cultivars. However, this method was not effective because few single nucleotide polymorphism (SNPs) were available because of low genetic diversity of the lines. The genome sequences of the probable diploid ancestors of cultivated peanut, Krapov. & W. C. Greg. and Krapov. & W. C. Greg., are available. Therefore, we next employed whole-genome resequencing analysis to obtain genome-wide SNP data. In this analysis, we observed large biases in the numbers and genomic positions of interspecific and intraspecific SNPs. For genome-wide genotyping, we selected a subset of SNPs covering the peanut genome as the targets of amplicon sequencing analysis. Using this technique, genome-wide genotypes of the breeding materials were easily and rapidly determined. The SNP information and analytic methods developed in this study should accelerate genetics, genomics, and breeding in peanut.

Identification of major QTLs underlying tomato spotted wilt virus resistance in peanut cultivar Florida-EP(TM) '113'

BACKGROUND

Spotted wilt caused by tomato spotted wilt virus (TSWV) is one of the major peanut (Arachis hypogaea L.) diseases in the southeastern United States. Occurrence, severity, and symptoms of spotted wilt disease are highly variable from season to season, making it difficult to efficiently evaluate breeding populations for resistance. Molecular markers linked to spotted wilt resistance could overcome this problem and allow selection of resistant lines regardless of environmental conditions. Florida-EP(TM) '113' is a spotted wilt resistant cultivar with a significantly lower infection frequency. However, the genetic basis is still unknown. The objective of this study is to map the major quantitative trait loci (QTLs) linked to spotted wilt resistance in Florida-EP(TM) '113'.

RESULTS

Among 2,431 SSR markers located across the whole peanut genome screened between the two parental lines, 329 were polymorphic. Those polymorphic markers were used to further genotype a representative set of individuals in a segregating population. Only polymorphic markers on chromosome A01 showed co-segregation between genotype and phenotype. Genotyping by sequencing (GBS) of the representative set of individuals in the segregating population also depicted a strong association between several SNPs on chromosome A01 and the trait, indicating a major QTL on chromosome A01. Therefore marker density was enriched on the A01 chromosome. A linkage map with 23 makers on chromosome A01 was constructed, showing collinearity with the physical map. Combined with phenotypic data, a major QTL flanked by marker AHGS4584 and GM672 was identified on chromosome A01, with up to 22.7 % PVE and 9.0 LOD value.

CONCLUSION

A major QTL controlling the spotted wilt resistance in Florida-EP(TM) '113' was identified. The resistance is most likely contributed by PI 576638, a hirsuta botanical-type line, introduced from Mexico with spotted wilt resistance. The flanking markers of this QTL can be used for further fine mapping and marker assisted selection in peanut breeding programs.

Genomic survey sequencing for development and validation of single-locus SSR markers in peanut (Arachis hypogaea L.)

BACKGROUND

Single-locus markers have many advantages compared with multi-locus markers in genetic and breeding studies because their alleles can be assigned to particular genomic loci in diversity analyses. However, there is little research on single-locus SSR markers in peanut. Through the de novo assembly of DNA sequencing reads of A. hypogaea, we developed single-locus SSR markers in a genomic survey for better application in genetic and breeding studies of peanut.

RESULTS

In this study, DNA libraries with four different insert sizes were used for sequencing with 150 bp paired-end reads. Approximately 237 gigabases of clean data containing 1,675,631,984 reads were obtained after filtering. These reads were assembled into 2,102,446 contigs with an N50 length of 1,782 bp, and the contigs were further assembled into 1,176,527 scaffolds with an N50 of 3,920 bp. The total length of the assembled scaffold sequences was 2.0 Gbp, and 134,652 single-locus SSRs were identified from 375,180 SSRs. Among these developed single-locus SSRs, trinucleotide motifs were the most abundant, followed by tetra-, di-, mono-, penta- and hexanucleotide motifs. The most common motif repeats for the various types of single-locus SSRs have a tendency to be A/T rich. A total of 1,790 developed in silico single-locus SSR markers were chosen and used in PCR experiments to confirm amplification patterns. Of them, 1,637 markers that produced single amplicons in twelve inbred lines were considered putative single-locus markers, and 290 (17.7 %) showed polymorphisms. A further F2 population study showed that the segregation ratios of the 97 developed SSR markers, which showed polymorphisms between the parents, were consistent with the Mendelian inheritance law for single loci (1:2:1). Finally, 89 markers were assigned to an A. hypogaea linkage map. A subset of 100 single-locus SSR markers was shown to be highly stable and universal in a collection of 96 peanut accessions. A neighbor-joining tree of this natural population showed that genotypes have obviously correlation with botanical varieties.

CONCLUSIONS

We have shown that the detection of single-locus SSR markers from a de novo genomic assembly of a combination of different-insert-size libraries is highly efficient. This is the first report of the development of genome-wide single-locus markers for A. hypogaea, and the markers developed in this study will be useful for gene tagging, sequence scaffold assignment, linkage map construction, diversity analysis, variety identification and association mapping in peanut.

Analytical and Decision Support Tools for Genomics-Assisted Breeding

To successfully implement genomics-assisted breeding (GAB) in crop improvement programs, efficient and effective analytical and decision support tools (ADSTs) are 'must haves' to evaluate and select plants for developing next-generation crops. Here we review the applications and deployment of appropriate ADSTs for GAB, in the context of next-generation sequencing (NGS), an emerging source of massive genomic information. We discuss suitable software tools and pipelines for marker-based approaches (markers/haplotypes), including large-scale genotypic and phenotypic, data management, and molecular breeding approaches. Although phenotyping remains expensive and time consuming, prediction of allelic effects on phenotypes opens new doors to enhance genetic gain across crop cycles, building on reliable phenotyping approaches and good crop information systems, including pedigree information and target haplotypes.

The genome sequences of Arachis duranensis and Arachis ipaensis, the diploid ancestors of cultivated peanut

Cultivated peanut (Arachis hypogaea) is an allotetraploid with closely related subgenomes of a total size of ∼2.7 Gb. This makes the assembly of chromosomal pseudomolecules very challenging. As a foundation to understanding the genome of cultivated peanut, we report the genome sequences of its diploid ancestors (Arachis duranensis and Arachis ipaensis). We show that these genomes are similar to cultivated peanut's A and B subgenomes and use them to identify candidate disease resistance genes, to guide tetraploid transcript assemblies and to detect genetic exchange between cultivated peanut's subgenomes. On the basis of remarkably high DNA identity of the A. ipaensis genome and the B subgenome of cultivated peanut and biogeographic evidence, we conclude that A. ipaensis may be a direct descendant of the same population that contributed the B subgenome to cultivated peanut.

Exciting journey of 10 years from genomes to fields and markets: Some success stories of genomics-assisted breeding in chickpea, pigeonpea and groundnut

Legume crops such as chickpea, pigeonpea and groundnut, mostly grown in marginal environments, are the major source of nutrition and protein to the human population in Asia and Sub-Saharan Africa. These crops, however, have a low productivity, mainly due to their exposure to several biotic and abiotic stresses in the marginal environments. Until 2005, these crops had limited genomics resources and molecular breeding was very challenging. During the last decade (2005-2015), ICRISAT led demand-driven innovations in genome science and translated the massive genome information in breeding. For instance, large-scale genomic resources including draft genome assemblies, comprehensive genetic and physical maps, thousands of SSR markers, millions of SNPs, several high-throughput as well as low cost marker genotyping platforms have been developed in these crops. After mapping several breeding related traits, several success stories of translational genomics have become available in these legumes. These include development of superior lines with enhanced drought tolerance in chickpea, enhanced and pyramided resistance to Fusarium wilt and Ascochyta blight in chickpea, enhanced resistance to leaf rust in groundnut, improved oil quality in groundnut and utilization of markers for assessing purity of hybrids/parental lines in pigeonpea. Some of these stories together with future prospects have been discussed.

Application of genomics-assisted breeding for generation of climate resilient crops: progress and prospects

Climate change affects agricultural productivity worldwide. Increased prices of food commodities are the initial indication of drastic edible yield loss, which is expected to increase further due to global warming. This situation has compelled plant scientists to develop climate change-resilient crops, which can withstand broad-spectrum stresses such as drought, heat, cold, salinity, flood, submergence and pests, thus helping to deliver increased productivity. Genomics appears to be a promising tool for deciphering the stress responsiveness of crop species with adaptation traits or in wild relatives toward identifying underlying genes, alleles or quantitative trait loci. Molecular breeding approaches have proven helpful in enhancing the stress adaptation of crop plants, and recent advances in high-throughput sequencing and phenotyping platforms have transformed molecular breeding to genomics-assisted breeding (GAB). In view of this, the present review elaborates the progress and prospects of GAB for improving climate change resilience in crops, which is likely to play an ever increasing role in the effort to ensure global food security.

A high-density, SNP-based consensus map of tetraploid wheat as a bridge to integrate durum and bread wheat genomics and breeding

Consensus linkage maps are important tools in crop genomics. We have assembled a high-density tetraploid wheat consensus map by integrating 13 data sets from independent biparental populations involving durum wheat cultivars (Triticum turgidum ssp. durum), cultivated emmer (T. turgidum ssp. dicoccum) and their ancestor (wild emmer, T. turgidum ssp. dicoccoides). The consensus map harboured 30 144 markers (including 26 626 SNPs and 791 SSRs) half of which were present in at least two component maps. The final map spanned 2631 cM of all 14 durum wheat chromosomes and, differently from the individual component maps, all markers fell within the 14 linkage groups. Marker density per genetic distance unit peaked at centromeric regions, likely due to a combination of low recombination rate in the centromeric regions and even gene distribution along the chromosomes. Comparisons with bread wheat indicated fewer regions with recombination suppression, making this consensus map valuable for mapping in the A and B genomes of both durum and bread wheat. Sequence similarity analysis allowed us to relate mapped gene-derived SNPs to chromosome-specific transcripts. Dense patterns of homeologous relationships have been established between the A- and B-genome maps and between nonsyntenic homeologous chromosome regions as well, the latter tracing to ancient translocation events. The gene-based homeologous relationships are valuable to infer the map location of homeologs of target loci/QTLs. Because most SNP and SSR markers were previously mapped in bread wheat, this consensus map will facilitate a more effective integration and exploitation of genes and QTL for wheat breeding purposes.

Quantitative trait locus analysis of agronomic and quality-related traits in cultivated peanut (Arachis hypogaea L.)

SSR-based QTL mapping provides useful information for map-based cloning of major QTLs and can be used to improve the agronomic and quality traits in cultivated peanut by marker-assisted selection. Cultivated peanut (Arachis hypogaea L.) is an allotetraploid species (AABB, 2n = 4× = 40), valued for its edible oil and digestible protein. Linkage mapping has been successfully conducted for most crops, and it has been applied to detect the quantitative trait loci (QTLs) of biotic and abiotic traits in peanut. However, the genetic basis of agronomic and quality-related traits remains unclear. In this study, high levels of phenotypic variation, broad-sense heritability and significant correlations were observed for agronomic and quality-related traits in an F 2:3 population. A genetic linkage map was constructed for cultivated peanut containing 470 simple sequence repeat (SSR) loci, with a total length of 1877.3 cM and average distance of 4.0 cM between flanking markers. For 10 agronomic traits, 24 QTLs were identified and each QTL explained 1.69-18.70 % of the phenotypic variance. For 8 quality-related traits, 12 QTLs were identified that explained 1.72-20.20 % of the phenotypic variance. Several QTLs for multiple traits were overlapped, reflecting the phenotypic correlation between these traits. The majority of QTLs exhibited obvious dominance or over-dominance effects on agronomic and quality traits, highlighting the importance of heterosis for breeding. A comparative analysis revealed genomic duplication and arrangement of peanut genome, which aids the assembly of scaffolds in genomic sequencing of Arachis hypogaea. Our QTL analysis results enabled us to clearly understand the genetic base of agronomic and quality traits in cultivated peanut, further accelerating the progress of map-based cloning of major QTLs and marker-assisted selection in future breeding.

Identification of QTLs for Rust Resistance in the Peanut Wild Species Arachis magna and the Development of KASP Markers for Marker-Assisted Selection

Rust is a major pathogen of the peanut crop. Development and adoption of rust-resistant cultivars is the most cost efficient and effective way to control the spread of the disease and reduce yield losses. Some cultivated peanut germplasm accessions have a degree of resistance, but the secondary gene pool is a source of much stronger resistance alleles. Wild species, however, have undesirable agronomic traits that are a disincentive to their use in breeding. The identification of genomic regions that harbor disease resistance in wild species is the first step in the implementation of marker-assisted selection that can speed the introgression of wild disease resistances and the elimination of linkage drag. In this work, we identify genome regions that control different components of rust resistance in a recombinant inbred line population developed from a cross between two Arachis species, the susceptible most probable B genome ancestor of cultivated peanut, Arachis ipaënsis, and an accession of its closest relative, Arachis magna, which is resistant to rust. Quantitative trait loci for several components of resistance were placed in the same position on linkage group B08. Single-nucleotide polymorphism Kompetitive allele-specific polymerase chain reaction markers for rust resistance region were designed and validated for marker function in both diploid and tetraploid contexts.

Tetrasomic recombination is surprisingly frequent in allotetraploid Arachis

Arachis hypogaea L. (cultivated peanut) is an allotetraploid (2n = 4x = 40) with an AABB genome type. Based on cytogenetic studies it has been assumed that peanut and wild-derived induced AABB allotetraploids have classic allotetraploid genetic behavior with diploid-like disomic recombination only between homologous chromosomes, at the exclusion of recombination between homeologous chromosomes. Using this assumption, numerous linkage map and quantitative trait loci studies have been carried out. Here, with a systematic analysis of genotyping and gene expression data, we show that this assumption is not entirely valid. In fact, autotetraploid-like tetrasomic recombination is surprisingly frequent in recombinant inbred lines generated from a cross of cultivated peanut and an induced allotetraploid derived from peanut’s most probable ancestral species. We suggest that a better, more predictive genetic model for peanut is that of a “segmental allotetraploid” with partly disomic, partly tetrasomic genetic behavior. This intermediate genetic behavior has probably had a previously overseen, but significant, impact on the genome and genetics of cultivated peanut.

Next-generation transcriptome sequencing, SNP discovery and validation in four market classes of peanut, Arachis hypogaea L

Single-nucleotide polymorphisms, which can be identified in the thousands or millions from comparisons of transcriptome or genome sequences, are ideally suited for making high-resolution genetic maps, investigating population evolutionary history, and discovering marker-trait linkages. Despite significant results from their use in human genetics, progress in identification and use in plants, and particularly polyploid plants, has lagged. As part of a long-term project to identify and use SNPs suitable for these purposes in cultivated peanut, which is tetraploid, we generated transcriptome sequences of four peanut cultivars, namely OLin, New Mexico Valencia C, Tamrun OL07 and Jupiter, which represent the four major market classes of peanut grown in the world, and which are important economically to the US southwest peanut growing region. CopyDNA libraries of each genotype were used to generate 2 × 54 paired-end reads using an Illumina GAIIx sequencer. Raw reads were mapped to a custom reference consisting of Tifrunner 454 sequences plus peanut ESTs in GenBank, compromising 43,108 contigs; 263,840 SNP and indel variants were identified among four genotypes compared to the reference. A subset of 6 variants was assayed across 24 genotypes representing four market types using KASP chemistry to assess the criteria for SNP selection. Results demonstrated that transcriptome sequencing can identify SNPs usable as selectable DNA-based markers in complex polyploid species such as peanut. Criteria for effective use of SNPs as markers are discussed in this context.

Development and Utilization of InDel Markers to Identify Peanut (Arachis hypogaea) Disease Resistance

Peanut diseases, such as leaf spot and spotted wilt caused by Tomato Spotted Wilt Virus, can significantly reduce yield and quality. Application of marker assisted plant breeding requires the development and validation of different types of DNA molecular markers. Nearly 10,000 SSR-based molecular markers have been identified by various research groups around the world, but less than 14.5% showed polymorphism in peanut and only 6.4% have been mapped. Low levels of polymorphism limit the application of marker assisted selection (MAS) in peanut breeding programs. Insertion/deletion (InDel) markers have been reported to be more polymorphic than SSRs in some crops. The goals of this study were to identify novel InDel markers and to evaluate the potential use in peanut breeding. Forty-eight InDel markers were developed from conserved sequences of functional genes and tested in a diverse panel of 118 accessions covering six botanical types of cultivated peanut, of which 104 were from the U.S. mini-core. Results showed that 16 InDel markers were polymorphic with polymorphic information content (PIC) among InDels ranged from 0.017 to 0.660. With respect to botanical types, PICs varied from 0.176 for fastigiata var., 0.181 for hypogaea var., 0.306 for vulgaris var., 0.534 for aequatoriana var., 0.556 for peruviana var., to 0.660 for hirsuta var., implying that aequatoriana var., peruviana var., and hirsuta var. have higher genetic diversity than the other types and provide a basis for gene functional studies. Single marker analysis was conducted to associate specific marker to disease resistant traits. Five InDels from functional genes were identified to be significantly correlated to tomato spotted wilt virus (TSWV) infection and leaf spot, and these novel markers will be utilized to identify disease resistant genotype in breeding populations.

High-resolution linkage map and chromosome-scale genome assembly for cassava (Manihot esculenta Crantz) from 10 populations

Cassava (Manihot esculenta Crantz) is a major staple crop in Africa, Asia, and South America, and its starchy roots provide nourishment for 800 million people worldwide. Although native to South America, cassava was brought to Africa 400-500 years ago and is now widely cultivated across sub-Saharan Africa, but it is subject to biotic and abiotic stresses. To assist in the rapid identification of markers for pathogen resistance and crop traits, and to accelerate breeding programs, we generated a framework map for M. esculenta Crantz from reduced representation sequencing [genotyping-by-sequencing (GBS)]. The composite 2412-cM map integrates 10 biparental maps (comprising 3480 meioses) and organizes 22,403 genetic markers on 18 chromosomes, in agreement with the observed karyotype. We used the map to anchor 71.9% of the draft genome assembly and 90.7% of the predicted protein-coding genes. The chromosome-anchored genome sequence will be useful for breeding improvement by assisting in the rapid identification of markers linked to important traits, and in providing a framework for genomic selection-enhanced breeding of this important crop.

Gene-based SNP discovery and genetic mapping in pea

KEY MESSAGE

Gene-based SNPs were identified and mapped in pea using five recombinant inbred line populations segregating for traits of agronomic importance. Pea (Pisum sativum L.) is one of the world's oldest domesticated crops and has been a model system in plant biology and genetics since the work of Gregor Mendel. Pea is the second most widely grown pulse crop in the world following common bean. The importance of pea as a food crop is growing due to its combination of moderate protein concentration, slowly digestible starch, high dietary fiber concentration, and its richness in micronutrients; however, pea has lagged behind other major crops in harnessing recent advances in molecular biology, genomics and bioinformatics, partly due to its large genome size with a large proportion of repetitive sequence, and to the relatively limited investment in research in this crop globally. The objective of this research was the development of a genome-wide transcriptome-based pea single-nucleotide polymorphism (SNP) marker platform using next-generation sequencing technology. A total of 1,536 polymorphic SNP loci selected from over 20,000 non-redundant SNPs identified using deep transcriptome sequencing of eight diverse Pisum accessions were used for genotyping in five RIL populations using an Illumina GoldenGate assay. The first high-density pea SNP map defining all seven linkage groups was generated by integrating with previously published anchor markers. Syntenic relationships of this map with the model legume Medicago truncatula and lentil (Lens culinaris Medik.) maps were established. The genic SNP map establishes a foundation for future molecular breeding efforts by enabling both the identification and tracking of introgression of genomic regions harbouring QTLs related to agronomic and seed quality traits.

Construction of a SNP-based genetic linkage map in cultivated peanut based on large scale marker development using next-generation double-digest restriction-site-associated DNA sequencing (ddRADseq)

BACKGROUND

Cultivated peanut, or groundnut (Arachis hypogaea L.), is an important oilseed crop with an allotetraploid genome (AABB, 2n=4x=40). In recent years, many efforts have been made to construct linkage maps in cultivated peanut, but almost all of these maps were constructed using low-throughput molecular markers, and most show a low density, directly influencing the value of their applications. With advances in next-generation sequencing (NGS) technology, the construction of high-density genetic maps has become more achievable in a cost-effective and rapid manner. The objective of this study was to establish a high-density single nucleotide polymorphism (SNP)-based genetic map for cultivated peanut by analyzing next-generation double-digest restriction-site-associated DNA sequencing (ddRADseq) reads.

RESULTS

We constructed reduced representation libraries (RRLs) for two A. hypogaea lines and 166 of their recombinant inbred line (RIL) progenies using the ddRADseq technique. Approximately 175 gigabases of data containing 952,679,665 paired-end reads were obtained following Solexa sequencing. Mining this dataset, 53,257 SNPs were detected between the parents, of which 14,663 SNPs were also detected in the population, and 1,765 of the obtained polymorphic markers met the requirements for use in the construction of a genetic map. Among 50 randomly selected in silico SNPs, 47 were able to be successfully validated. One linkage map was constructed, which was comprised of 1,685 marker loci, including 1,621 SNPs and 64 simple sequence repeat (SSR) markers. The map displayed a distribution of the markers into 20 linkage groups (LGs A01-A10 and B01-B10), spanning a distance of 1,446.7 cM. The alignment of the LGs from this map was shown in comparison with a previously integrated consensus map from peanut.

CONCLUSIONS

This study showed that the ddRAD library combined with NGS allowed the rapid discovery of a large number of SNPs in the cultivated peanut. The first high density SNP-based linkage map for A. hypogaea was generated that can serve as a reference map for cultivated Arachis species and will be useful in genetic mapping. Our results contribute to the available molecular marker resources and to the assembly of a reference genome sequence for the peanut.

The use of SNP markers for linkage mapping in diploid and tetraploid peanuts

Single nucleotide polymorphic markers (SNPs) are attractive for use in genetic mapping and marker-assisted breeding because they can be scored in parallel assays at favorable costs. However, scoring SNP markers in polyploid plants like the peanut is problematic because of interfering signal generated from the DNA bases that are homeologous to those being assayed. The present study used a previously constructed 1536 GoldenGate SNP assay developed using SNPs identified between two A. duranensis accessions. In this study, the performance of this assay was tested on two RIL mapping populations, one diploid (A. duranensis × A. stenosperma) and one tetraploid [A. hypogaea cv. Runner IAC 886 × synthetic tetraploid (A. ipaënsis × A. duranensis)^4×]. The scoring was performed using the software GenomeStudio version 2011.1. For the diploid, polymorphic markers provided excellent genotyping scores with default software parameters. In the tetraploid, as expected, most of the polymorphic markers provided signal intensity plots that were distorted compared to diploid patterns and that were incorrectly scored using default parameters. However, these scorings were easily corrected using the GenomeStudio software. The degree of distortion was highly variable. Of the polymorphic markers, approximately 10% showed no distortion at all behaving as expected for single-dose markers, and another 30% showed low distortion and could be considered high-quality. The genotyped markers were incorporated into diploid and tetraploid genetic maps of Arachis and, in the latter case, were located almost entirely on A genome linkage groups.

A reference consensus genetic map for molecular markers and economically important traits in faba bean (Vicia faba L.)

BACKGROUND

Faba bean (Vicia faba L.) is among the earliest domesticated crops from the Near East. Today this legume is a key protein feed and food worldwide and continues to serve an important role in culinary traditions throughout Middle East, Mediterranean region, China and Ethiopia. Adapted to a wide range of soil types, the main faba bean breeding objectives are to improve yield, resistance to biotic and abiotic stresses, seed quality and other agronomic traits. Genomic approaches aimed at enhancing faba bean breeding programs require high-quality genetic linkage maps to facilitate quantitative trait locus analysis and gene tagging for use in a marker-assisted selection. The objective of this study was to construct a reference consensus map in faba bean by joining the information from the most relevant maps reported so far in this crop.

RESULTS

A combination of two approaches, increasing the number of anchor loci in diverse mapping populations and joining the corresponding genetic maps, was used to develop a reference consensus map in faba bean. The map was constructed from three main recombinant inbreed populations derived from four parental lines, incorporates 729 markers and is based on 69 common loci. It spans 4,602 cM with a range from 323 to 1041 loci in six main linkage groups or chromosomes, and an average marker density of one locus every 6 cM. Locus order is generally well maintained between the consensus map and the individual maps.

CONCLUSION

We have constructed a reliable and fairly dense consensus genetic linkage map that will serve as a basis for genomic approaches in faba bean research and breeding. The core map contains a larger number of markers than any previous individual map, covers existing gaps and achieves a wider coverage of the large faba bean genome as a whole. This tool can be used as a reference resource for studies in different genetic backgrounds, and provides a framework for transferring genetic information when using different marker technologies. Combined with syntenic approaches, the consensus map will increase marker density in selected genomic regions and will be useful for future faba bean molecular breeding applications.

The Value of Diploid Peanut Relatives for Breeding and Genomics

Collection, evaluation, and introgression research has been conducted with Arachis species for more than 60 years. Eighty species in the genus have been described and additional species will be named in the future. Extremely high levels of disease and insect resistances to immunity have been observed in many species of the genus as compared to the cultivated peanut, which makes them extremely important for crop improvement. Many thousands of interspecific hybrids have been produced in the genus, but introgression has been slow because of genomic incompatibilities and sterility of hybrids. Genomics research was initiated during the late 1980s to characterize species relationships and investigate more efficient methods to introgress genes from wild species to A. hypogaea. Relatively low density genetic maps have been created from inter- and intra-specific crosses, several of which have placed disease resistance genes into limited linkage groups. Of particular interest is associating molecular markers with traits of interest to enhance breeding for disease and insect resistances. Only recently have sufficiently large numbers of markers become available to effectively conduct marker assisted breeding in peanut. Future analyses of the diploid ancestors of the cultivated peanut, A. duranensis and A. ipaensis, will allow more detailed characterization of peanut genetics and the effects of Arachis species alleles on agronomic traits. Extensive efforts are being made to create populations for genomic analyses of peanut, and introgression of genes from wild to cultivated genotypes should become more efficient in the near future.

Recent Advances in Molecular Genetic Linkage Maps of Cultivated Peanut

The competitiveness of peanuts in domestic and global markets has been threatened by losses in productivity and quality that are attributed to diseases, pests, environmental stresses and allergy or food safety issues. Narrow genetic diversity and a deficiency of polymorphic DNA markers severely hindered construction of dense genetic maps and quantitative trait loci (QTL) mapping in order to deploy linked markers in marker-assisted peanut improvement. The U.S. Peanut Genome Initiative (PGI) was launched in 2004, and expanded to a global effort in 2006 to address these issues through coordination of international efforts in genome research beginning with molecular marker development and improvement of map resolution and coverage. Ultimately, a peanut genome sequencing project was launched in 2012 by the Peanut Genome Consortium (PGC). We reviewed the progress for accelerated development of peanut genomic resources in peanut, such as generation of expressed sequenced tags (ESTs) (252,832 ESTs as December 2012 in the public NCBI EST database), development of molecular markers (over 15,518 SSRs), and construction of peanut genetic linkage maps, in particular for cultivated peanut. Several consensus genetic maps have been constructed, and there are examples of recent international efforts to develop high density maps. An international reference consensus genetic map was developed recently with 897 marker loci based on 11 published mapping populations. Furthermore, a high-density integrated consensus map of cultivated peanut and wild diploid relatives also has been developed, which was enriched further with 3693 marker loci on a single map by adding information from five new genetic mapping populations to the published reference consensus map.

Integrated consensus map of cultivated peanut and wild relatives reveals structures of the A and B genomes of Arachis and divergence of the legume genomes

The complex, tetraploid genome structure of peanut (Arachis hypogaea) has obstructed advances in genetics and genomics in the species. The aim of this study is to understand the genome structure of Arachis by developing a high-density integrated consensus map. Three recombinant inbred line populations derived from crosses between the A genome diploid species, Arachis duranensis and Arachis stenosperma; the B genome diploid species, Arachis ipaënsis and Arachis magna; and between the AB genome tetraploids, A. hypogaea and an artificial amphidiploid (A. ipaënsis × A. duranensis)(4×), were used to construct genetic linkage maps: 10 linkage groups (LGs) of 544 cM with 597 loci for the A genome; 10 LGs of 461 cM with 798 loci for the B genome; and 20 LGs of 1442 cM with 1469 loci for the AB genome. The resultant maps plus 13 published maps were integrated into a consensus map covering 2651 cM with 3693 marker loci which was anchored to 20 consensus LGs corresponding to the A and B genomes. The comparative genomics with genome sequences of Cajanus cajan, Glycine max, Lotus japonicus, and Medicago truncatula revealed that the Arachis genome has segmented synteny relationship to the other legumes. The comparative maps in legumes, integrated tetraploid consensus maps, and genome-specific diploid maps will increase the genetic and genomic understanding of Arachis and should facilitate molecular breeding.

Genome-wide characterization and linkage mapping of simple sequence repeats in mei (Prunus mume Sieb. et Zucc.)

Because of its popularity as an ornamental plant in East Asia, mei (Prunus mume Sieb. et Zucc.) has received increasing attention in genetic and genomic research with the recent shotgun sequencing of its genome. Here, we performed the genome-wide characterization of simple sequence repeats (SSRs) in the mei genome and detected a total of 188,149 SSRs occurring at a frequency of 794 SSR/Mb. Mononucleotide repeats were the most common type of SSR in genomic regions, followed by di- and tetranucleotide repeats. Most of the SSRs in coding sequences (CDS) were composed of tri- or hexanucleotide repeat motifs, but mononucleotide repeats were always the most common in intergenic regions. Genome-wide comparison of SSR patterns among the mei, strawberry (Fragaria vesca), and apple (Malus×domestica) genomes showed mei to have the highest density of SSRs, slightly higher than that of strawberry (608 SSR/Mb) and almost twice as high as that of apple (398 SSR/Mb). Mononucleotide repeats were the dominant SSR motifs in the three Rosaceae species. Using 144 SSR markers, we constructed a 670 cM-long linkage map of mei delimited into eight linkage groups (LGs), with an average marker distance of 5 cM. Seventy one scaffolds covering about 27.9% of the assembled mei genome were anchored to the genetic map, depending on which the macro-colinearity between the mei genome and Prunus T×E reference map was identified. The framework map of mei constructed provides a first step into subsequent high-resolution genetic mapping and marker-assisted selection for this ornamental species.

Achievements and prospects of genomics-assisted breeding in three legume crops of the semi-arid tropics

Advances in next-generation sequencing and genotyping technologies have enabled generation of large-scale genomic resources such as molecular markers, transcript reads and BAC-end sequences (BESs) in chickpea, pigeonpea and groundnut, three major legume crops of the semi-arid tropics. Comprehensive transcriptome assemblies and genome sequences have either been developed or underway in these crops. Based on these resources, dense genetic maps, QTL maps as well as physical maps for these legume species have also been developed. As a result, these crops have graduated from 'orphan' or 'less-studied' crops to 'genomic resources rich' crops. This article summarizes the above-mentioned advances in genomics and genomics-assisted breeding applications in the form of marker-assisted selection (MAS) for hybrid purity assessment in pigeonpea; marker-assisted backcrossing (MABC) for introgressing QTL region for drought-tolerance related traits, Fusarium wilt (FW) resistance and Ascochyta blight (AB) resistance in chickpea; late leaf spot (LLS), leaf rust and nematode resistance in groundnut. We critically present the case of use of other modern breeding approaches like marker-assisted recurrent selection (MARS) and genomic selection (GS) to utilize the full potential of genomics-assisted breeding for developing superior cultivars with enhanced tolerance to various environmental stresses. In addition, this article recommends the use of advanced-backcross (AB-backcross) breeding and development of specialized populations such as multi-parents advanced generation intercross (MAGIC) for creating new variations that will help in developing superior lines with broadened genetic base. In summary, we propose the use of integrated genomics and breeding approach in these legume crops to enhance crop productivity in marginal environments ensuring food security in developing countries.