An integrated genetic linkage map of cultivated peanut (Arachis hypogaea L.) constructed from two RIL populations

Detection of two homologous major QTLs and development of diagnostic molecular markers for sucrose content in peanut

KEY MESSAGE

We identified two stable and homologous major QTLs for sucrose content in peanut, and developed breeder-friendly molecular markers for marker-assisted selection breeding. Sucrose content is a crucial quality trait for edible peanuts, and increasing sucrose content is a key breeding objective. However, the genetic basis of sucrose content in peanut remains unclear, and major quantitative trait loci (QTLs) for sucrose content have yet to be identified. In this study, a high-density genetic map was constructed based on whole-genome re-sequencing data from a peanut RIL population. This map consisted of 2,042 bins and 24,142 SNP markers, making it one of the most comprehensive maps to date in terms of marker density. Two major QTLs (qSCA06.2 and qSCB06.2) were identified, explaining 31.41% and 24.13% of the phenotypic variance, respectively. Notably, these two QTLs were located in homologous genomic regions between the A and B subgenomes. The elite allele of qSCA06.2 was exclusive to Valencia-type, while the elite allele of qSCB06.2 existed in other peanut types. Importantly, the distribution of alleles from two homologous QTLs in the RIL population and diverse germplasm accessions consistently demonstrated that only the combination of elite allelic genotypes from both QTLs/genes resulted in a significantly dominant phenotype, accompanied by a substantial increase in sucrose content. The newly developed diagnostic markers for these QTLs were confirmed to be reliable and could facilitate future breeding efforts to enhance sucrose content using marker-assisted selection techniques. Overall, this study highlights the co-regulation of sucrose content by two major homologous QTLs/genes and provides valuable insights into the genetic basis of sucrose in peanuts.

Advances in omics research on peanut response to biotic stresses

Peanut growth, development, and eventual production are constrained by biotic and abiotic stresses resulting in serious economic losses. To understand the response and tolerance mechanism of peanut to biotic and abiotic stresses, high-throughput Omics approaches have been applied in peanut research. Integrated Omics approaches are essential for elucidating the temporal and spatial changes that occur in peanut facing different stresses. The integration of functional genomics with other Omics highlights the relationships between peanut genomes and phenotypes under specific stress conditions. In this review, we focus on research on peanut biotic stresses. Here we review the primary types of biotic stresses that threaten sustainable peanut production, the multi-Omics technologies for peanut research and breeding, and the recent advances in various peanut Omics under biotic stresses, including genomics, transcriptomics, proteomics, metabolomics, miRNAomics, epigenomics and phenomics, for identification of biotic stress-related genes, proteins, metabolites and their networks as well as the development of potential traits. We also discuss the challenges, opportunities, and future directions for peanut Omics under biotic stresses, aiming sustainable food production. The Omics knowledge is instrumental for improving peanut tolerance to cope with various biotic stresses and for meeting the food demands of the exponentially growing global population.

Construction of ddRADseq-Based High-Density Genetic Map and Identification of Quantitative Trait Loci for Trans-resveratrol Content in Peanut Seeds

Resveratrol (trans-3,4',5-trihydroxystilbene) is a natural stilbene phytoalexin which is also found to be good for human health. Cultivated peanut (Arachis hypogaea L.), a worldwide important legume crop, is one of the few sources of human's dietary intake of resveratrol. Although the variations of resveratrol contents among peanut varieties were observed, the variations across environments and its underlying genetic basis were poorly investigated. In this study, the resveratrol content in seeds of a recombination inbred line (RIL) population (Zhonghua 6 × Xuhua 13, 186 progenies) were quantified by high performance liquid chromatography (HPLC) method across four environments. Genotypes, environments and genotype × environment interactions significantly influenced the resveratrol contents in the RIL population. A total of 8,114 high-quality single nucleotide polymorphisms (SNPs) were identified based on double-digest restriction-site-associated DNA sequencing (ddRADseq) reads. These SNPs were clustered into bins using a reference-based method, which facilitated the construction of high-density genetic map (2,183 loci with a total length of 2,063.55 cM) and the discovery of several chromosome translocations. Through composite interval mapping (CIM), nine additive quantitative trait loci (QTL) for resveratrol contents were identified on chromosomes A01, A07, A08, B04, B05, B06, B07, and B10 with 5.07-8.19% phenotypic variations explained (PVE). Putative genes within their confidential intervals might play roles in diverse primary and secondary metabolic processes. These results laid a foundation for the further genetic dissection of resveratrol content as well as the breeding and production of high-resveratrol peanuts.

High-density SNP map facilitates fine mapping of QTLs and candidate genes discovery for Aspergillus flavus resistance in peanut (Arachis hypogaea)

Two novel resistant QTLs mapped and candidate genes identified for Aspergillus flavus resistance in cultivated peanut using SLAF-seq. Aflatoxin contamination in peanuts caused by Aspergillus flavus is a serious food safety issue for human health around the world. Host plant resistance to fungal infection and reduction in aflatoxin are crucial for mitigating this problem. Identification of the resistance-linked markers can be used in marker-assisted breeding for varietal development. Here we report construction of two high-density genetic linkage maps with 1975 SNP loci and 5022 SNP loci, respectively. Two consistent quantitative trait loci (QTL) were identified as qRAF-3-1 and qRAF-14-1, which located on chromosomes A03 and B04, respectively. QTL qRAF-3-1 was mapped within 1.67 cM and had more than 19% phenotypic variance explained (PVE), while qRAF-14-1 was located within 1.34 cM with 5.15% PVE. While comparing with the reference genome, the mapped QTLs, qRAF-3-1 and qRAF-14-1, were located within a physical distance of 1.44 Megabase pair (Mbp) and 2.22 Mbp, harboring 67 and 137 genes, respectively. Among the identified candidate genes, six genes with the same function were found within both QTLs regions. In addition, putative disease resistance RPP13-like protein 1 (RPP13), lipoxygenase (Lox), WRKY transcription factor (WRKY) and cytochrome P450 71B34 genes were also identified. Using microarray analysis, genes responded to A. flavus infection included coding for RPP13, pentatricopeptide repeat-containing-like protein, and Lox which may be possible candidate genes for resistance to A. flavus. The QTLs and candidate genes will further facilitate marker development and validation of genes for deployment in the molecular breeding programs against A. flavus in peanuts.

A recombination bin-map identified a major QTL for resistance to Tomato Spotted Wilt Virus in peanut (Arachis hypogaea)

Tomato spotted wilt virus (TSWV) is a devastating disease to peanut growers in the South-eastern region of the United States. Newly released peanut cultivars in recent years are crucial as they have some levels of resistance to TSWV. One mapping population of recombinant inbred line (RIL) used in this study was derived from peanut lines of SunOleic 97R and NC94022. A whole genome re-sequencing approach was used to sequence these two parents and 140 RILs. A recombination bin-based genetic map was constructed, with 5,816 bins and 20 linkage groups covering a total length of 2004 cM. Using this map, we identified three QTLs which were colocalized on chromosome A01. One QTL had the largest effect of 36.51% to the phenotypic variation and encompassed 89.5 Kb genomic region. This genome region had a cluster of genes, which code for chitinases, strictosidine synthase-like, and NBS-LRR proteins. SNPs linked to this QTL were used to develop Kompetitive allele specific PCR (KASP) markers, and the validated KASP markers showed expected segregation of alleles coming from resistant and susceptible parents within the population. Therefore, this bin-map and QTL associated with TSWV resistance made it possible for functional gene mapping, map-based cloning, and marker-assisted breeding. This study identified the highest number of SNP makers and demonstrated recombination bin-based map for QTL identification in peanut. The chitinase gene clusters and NBS-LRR disease resistance genes in this region suggest the possible involvement in peanut resistance to TSWV.

QTL identification for seed weight and size based on a high-density SLAF-seq genetic map in peanut (Arachis hypogaea L.)

BACKGROUND

The cultivated peanut is an important oil and cash crop grown worldwide. To meet the growing demand for peanut production each year, genetic studies and enhanced selection efficiency are essential, including linkage mapping, genome-wide association study, bulked-segregant analysis and marker-assisted selection. Specific locus amplified fragment sequencing (SLAF-seq) is a powerful tool for high density genetic map (HDGM) construction and quantitative trait loci (QTLs) mapping. In this study, a HDGM was constructed using SLAF-seq leading to identification of QTL for seed weight and size in peanut.

RESULTS

A recombinant inbred line (RIL) population was advanced from a cross between a cultivar 'Huayu36' and a germplasm line '6-13' with contrasting seed weight, size and shape. Based on the cultivated peanut genome, a HDGM was constructed with 3866 loci consisting of SLAF-seq and simple sequence repeat (SSR) markers distributed on 20 linkage groups (LGs) covering a total map distance of 1266.87 cM. Phenotypic data of four seed related traits were obtained in four environments, which mostly displayed normal distribution with varied levels of correlation. A total of 27 QTLs for 100 seed weight (100SW), seed length (SL), seed width (SW) and length to width ratio (L/W) were identified on 8 chromosomes, with LOD values of 3.16-31.55 and explaining phenotypic variance (PVE) from 0.74 to 83.23%. Two stable QTL regions were identified on chromosomes 2 and 16, and gene content within these regions provided valuable information for further functional analysis of yield component traits.

CONCLUSIONS

This study represents a new HDGM based on the cultivated peanut genome using SLAF-seq and SSRs. QTL mapping of four seed related traits revealed two stable QTL regions on chromosomes 2 and 16, which not only facilitate fine mapping and cloning these genes, but also provide opportunity for molecular breeding of new peanut cultivars with improved seed weight and size.

Evolutionary balance between LRR domain loss and young NBS-LRR genes production governs disease resistance in Arachis hypogaea cv. Tifrunner

BACKGROUND

Cultivated peanut (Arachis hypogaea L.) is an important oil and protein crop, but it has low disease resistance; therefore, it is important to reveal the number, sequence features, function, and evolution of genes that confer resistance. Nucleotide-binding site-leucine-rich repeats (NBS-LRRs) are resistance genes that are involved in response to various pathogens.

RESULTS

We identified 713 full-length NBS-LRRs in A. hypogaea cv. Tifrunner. Genetic exchange events occurred on NBS-LRRs in A. hypogaea cv. Tifrunner, which were detected in the same subgenomes and also found in different subgenomes. Relaxed selection acted on NBS-LRR proteins and LRR domains in A. hypogaea cv. Tifrunner. Using quantitative trait loci (QTL), we found that NBS-LRRs were involved in response to late leaf spot, tomato spotted wilt virus, and bacterial wilt in A. duranensis (2 NBS-LRRs), A. ipaensis (39 NBS-LRRs), and A. hypogaea cv. Tifrunner (113 NBS-LRRs). In A. hypogaea cv. Tifrunner, 113 NBS-LRRs were classified as 75 young and 38 old NBS-LRRs, indicating that young NBS-LRRs were involved in response to disease after tetraploidization. However, compared to A. duranensis and A. ipaensis, fewer LRR domains were found in A. hypogaea cv. Tifrunner NBS-LRR proteins, partly explaining the lower disease resistance of the cultivated peanut.

CONCLUSIONS

Although relaxed selection acted on NBS-LRR proteins and LRR domains, LRR domains were preferentially lost in A. hypogaea cv. Tifrunner compared to A. duranensis and A. ipaensis. The QTL results suggested that young NBS-LRRs were important for resistance against diseases in A. hypogaea cv. Tifrunner. Our results provid insight into the greater susceptibility of A. hypogaea cv. Tifrunner to disease compared to A. duranensis and A. ipaensis.

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.

A Major and Stable QTL for Bacterial Wilt Resistance on Chromosome B02 Identified Using a High-Density SNP-Based Genetic Linkage Map in Cultivated Peanut Yuanza 9102 Derived Population

Bacterial wilt (BW) is one of the important diseases limiting the production of peanut (Arachis hypogaea L.) worldwide. The sufficient precise information on the quantitative trait loci (QTL) for BW resistance is essential for facilitating gene mining and applying in molecular breeding. Cultivar Yuanza 9102 is BW resistant, bred from wide cross between cultivated peanut Baisha 1016 and a wild diploid peanut species A. chacoense with BW resistance. In this study, we aim to map the major QTLs related to BW-resistance in Yuanza 9102. A high density SNP-based genetic linkage map was constructed through double-digest restriction-site-associated DNA sequencing (ddRADseq) technique based on Yuanza 9102 derived recombinant inbred lines (RILs) population. The map contained 2,187 SNP markers distributed on 20 linkage groups (LGs) spanning 1566.10 cM, and showed good synteny with AA genome from A. duranensis and BB genome from A. ipaensis. Phenotypic frequencies of BW resistance among RIL population showed two-peak distribution in four environments. Four QTLs explaining 5.49 to 23.22% phenotypic variance were identified to be all located on chromosome B02. The major QTL, qBWB02.1 (12.17–23.33% phenotypic variation explained), was detected in three environments showing consistent and stable expression. Furthermore, there was positive additive effect among these major and minor QTLs. The major QTL region was mapped to a region covering 2.3 Mb of the pseudomolecule B02 of A. ipaensis which resides in 21 nucleotide-binding site -leucine-rich repeat (NBS-LRR) encoding genes. The result of the major stable QTL (qBWB02.1) not only offers good foundation for discovery of BW resistant gene but also provide opportunity for deployment of the QTL in marker-assisted breeding in peanut.

High-density genetic map using whole-genome resequencing for fine mapping and candidate gene discovery for disease resistance in peanut

Whole-genome resequencing (WGRS) of mapping populations has facilitated development of high-density genetic maps essential for fine mapping and candidate gene discovery for traits of interest in crop species. Leaf spots, including early leaf spot (ELS) and late leaf spot (LLS), and Tomato spotted wilt virus (TSWV) are devastating diseases in peanut causing significant yield loss. We generated WGRS data on a recombinant inbred line population, developed a SNP-based high-density genetic map, and conducted fine mapping, candidate gene discovery and marker validation for ELS, LLS and TSWV. The first sequence-based high-density map was constructed with 8869 SNPs assigned to 20 linkage groups, representing 20 chromosomes, for the 'T' population (Tifrunner × GT-C20) with a map length of 3120 cM and an average distance of 1.45 cM. The quantitative trait locus (QTL) analysis using high-density genetic map and multiple season phenotyping data identified 35 main-effect QTLs with phenotypic variation explained (PVE) from 6.32% to 47.63%. Among major-effect QTLs mapped, there were two QTLs for ELS on B05 with 47.42% PVE and B03 with 47.38% PVE, two QTLs for LLS on A05 with 47.63% and B03 with 34.03% PVE and one QTL for TSWV on B09 with 40.71% PVE. The epistasis and environment interaction analyses identified significant environmental effects on these traits. The identified QTL regions had disease resistance genes including R-genes and transcription factors. KASP markers were developed for major QTLs and validated in the population and are ready for further deployment in genomics-assisted breeding in peanut.

A SNP-Based Linkage Map Revealed QTLs for Resistance to Early and Late Leaf Spot Diseases in Peanut (Arachis hypogaea L.)

Cultivated peanut (Arachis hypogaea L.) is an important oilseed crop that is grown extensively in Africa, Asia and America. The diseases early and late leaf spot severely constrains peanut production worldwide. Because multiple genes control resistance to leaf spot diseases, conventional breeding is a time-consuming approach for pyramiding resistance genes into a single genotype. Marker-assisted selection (MAS) would complement and accelerate conventional breeding once molecular markers tightly associated with the resistance genes are identified. In this study, we have generated a large number of SNPs through genotyping by sequencing (GBS) and constructed a high-resolution map with an average distance of 1.34 cM among 2,753 SNP markers distributed on 20 linkage groups. QTL mapping has revealed that major QTL within a confidence interval could provide an efficient way to detect putative resistance genes. Analysis of the interval sequences has indicated that a major QTL for resistance to late leaf spot anchored by two NBS-LRR resistance genes on chromosome B05. Two major QTLs located on chromosomes A03 and B04 were associated with resistance genes for early leaf spot. Sequences within the confidence interval would facilitate identifying resistance genes and applying marker-assisted selection for resistance.

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.

Refining a major QTL controlling spotted wilt disease resistance in cultivated peanut (Arachis hypogaea L.) and evaluating its contribution to the resistance variations in peanut germplasm

BACKGROUND

Spotted wilt, caused by tomato spotted wilt virus (TSWV), has been one of major diseases in cultivated peanut grown in the southeastern United States (US) since 1990. Previously a major quantitative trait locus (QTL) controlling spotted wilt disease resistance was mapped to an interval of 2.55 cM genetic distance corresponding to a physical distance of 14.4 Mb on chromosome A01 of peanut by using a segregating F₂ population. The current study focuses on refining this major QTL region and evaluating its contributions in the US peanut mini-core germplasm.

RESULTS

Two simple sequence repeat (SSR) markers associated with the major QTL were used to genotype F₅ individuals, and 25 heterozygous individuals were selected and developed into an F₆ segregating population. Based on visual evaluation in the field, a total of 194 susceptible F₆ individuals were selected and planted into F₇ generation for phenotyping. Nine SSR markers were used to genotype the 194 F₆ individuals, and QTL analysis revealed that a confidence interval of 15.2 Mb region had the QTL with 22.8% phenotypic variation explained (PVE). This QTL interval was further genotyped using the Amplicon-seq method. A total of 81 non-redundant single nucleotide polymorphism (SNP) and eight InDel markers were detected. No recombinant was detected among the F₆ individuals. Two InDel markers were integrated into the linkage group and helped to refine the confidence interval of this QTL into a 0.8 Mb region. To test the QTL contributes to the resistance variance in US peanut mini-core germplasm, two flanking SSR markers were used to genotype 107 mini-core germplasm accessions. No statistically significant association was observed between the genotype at the QTL region and spotted wilt resistance in the mini-core germplasm, which indicated that the resistance allelic region at this QTL didn't contribute to the resistance variance in the US peanut mini-core germplasm, thus was a unique resistance source.

CONCLUSION

A major QTL related to spotted wilt disease resistance in peanut was refined to a 0.8 Mb region on A01 chromosome, which didn't relate to spotted wilt disease resistance in the US peanut mini-core germplasm and might be a unique genetic source.

Chromosomes A07 and A05 associated with stable and major QTLs for pod weight and size in cultivated peanut (Arachis hypogaea L.)

Co-localized intervals and candidate genes were identified for major and stable QTLs controlling pod weight and size on chromosomes A07 and A05 in an RIL population across four environments. Cultivated peanut (Arachis hypogaea L.) is an important legume crops grown in > 100 countries. Hundred-pod weight (HPW) is an important yield trait in peanut, but its underlying genetic mechanism was not well studied. In this study, a mapping population (Xuhua 13 × Zhonghua 6) with 187 recombinant inbred lines (RILs) was developed to map quantitative trait loci (QTLs) for HPW together with pod length (PL) and pod width (PW) by both unconditional and conditional QTL analyses. A genetic map covering 1756.48 cM was constructed with 817 markers. Additive effects, epistatic interactions, and genotype-by-environment interactions were analyzed using the phenotyping data generated across four environments. Twelve additive QTLs were identified on chromosomes A05, A07, and A08 by unconditional analysis, and five of them (qPLA07, qPLA05.1, qPWA07, qHPWA07.1, and qHPWA05.2) showed major and stable expressions in all environments. Conditional QTL mapping found that PL had stronger influences on HPW than PW. Notably, qHPWA07.1, qPLA07, and qPWA07 that explained 17.93-43.63% of the phenotypic variations of the three traits were co-localized in a 5 cM interval (1.48 Mb in physical map) on chromosome A07 with 147 candidate genes related to catalytic activity and metabolic process. In addition, qHPWA05.2 and qPLA05.1 were co-localized with minor QTL qPWA05.2 to a 1.3 cM genetic interval (280 kb in physical map) on chromosome A05 with 12 candidate genes. This study provides a comprehensive characterization of the genetic components controlling pod weight and size as well as candidate QTLs and genes for improving pod yield in future peanut breeding.

Development of a High-Density Genetic Map Based on Specific Length Amplified Fragment Sequencing and Its Application in Quantitative Trait Loci Analysis for Yield-Related Traits in Cultivated Peanut

High-density genetic maps (HDGMs) are very useful for genomic studies and quantitative trait loci (QTL) mapping. However, the low frequency of DNA polymorphisms in peanut has limited the quantity of available markers and hindered the construction of a HDGM. This study generated a peanut genetic map with the highest number of high-quality SNPs based on specific locus amplified fragment sequencing (SLAF-seq) technology and a newly constructed RIL population ("ZH16" × "sd-H1"). The constructed HDGM included 3,630 SNP markers belonging to 2,636 bins on 20 linkage groups (LGs), and it covers 2,098.14 cM in length, with an average marker distance of 0.58 cM. This HDGM was applied for the following collinear comparison, scaffold anchoring and analysis of genomic characterization including recombination rates and segregation distortion in peanut. For QTL mapping of investigated 14 yield-related traits, a total of 62 QTLs were detected on 12 chromosomes across 3 environments, and the co-localization of QTLs was observed for these traits which were significantly correlated on phenotype. Two stable co-located QTLs for seed- and pod-related traits were significantly identified in the chromosomal end of B06 and B07, respectively. The construction of HDGM and QTL analysis for yield-related traits in this study provide useful information for fine mapping and functional analysis of genes as well as molecular marker-assisted breeding.

Haplotype-Based Genotyping in Polyploids

Accurate identification of polymorphisms from sequence data is crucial to unlocking the potential of high throughput sequencing for genomics. Single nucleotide polymorphisms (SNPs) are difficult to accurately identify in polyploid crops due to the duplicative nature of polyploid genomes leading to low confidence in the true alignment of short reads. Implementing a haplotype-based method in contrasting subgenome-specific sequences leads to higher accuracy of SNP identification in polyploids. To test this method, a large-scale 48K SNP array (Axiom Arachis2) was developed for Arachis hypogaea (peanut), an allotetraploid, in which 1,674 haplotype-based SNPs were included. Results of the array show that 74% of the haplotype-based SNP markers could be validated, which is considerably higher than previous methods used for peanut. The haplotype method has been implemented in a standalone program, HAPLOSWEEP, which takes as input bam files and a vcf file and identifies haplotype-based markers. Haplotype discovery can be made within single reads or span paired reads, and can leverage long read technology by targeting any length of haplotype. Haplotype-based genotyping is applicable in all allopolyploid genomes and provides confidence in marker identification and in silico-based genotyping for polyploid genomics.

Development of SSR markers and identification of major quantitative trait loci controlling shelling percentage in cultivated peanut (Arachis hypogaea L.)

A total of 204,439 SSR markers were developed in diploid genomes, and 25 QTLs for shelling percentage were identified in a RIL population across 4 years including five consistent QTLs. Cultivated peanut (Arachis hypogaea L.) is an important grain legume providing edible oil and protein for human nutrition. Genome sequences of its diploid ancestors, Arachis duranensis and A. ipaensis, were reported, but their SSRs have not been well exploited and utilized hitherto. Shelling percentage is an important economic trait and its improvement has been one of the major objectives in peanut breeding programs. In this study, the genome sequences of A. duranensis and A. ipaensis were used to develop SSR markers, and a mapping population (Yuanza 9102 × Xuzhou 68-4) with 195 recombinant inbred lines was used to map QTLs controlling shelling percentage. The numbers of newly developed SSR markers were 84,383 and 120,056 in the A. duranensis and A. ipaensis genomes, respectively. Genotyping of the mapping population was conducted with both newly developed and previously reported markers. QTL analysis using the phenotyping data generated in Wuhan across four consecutive years and genotyping data of 830 mapped loci identified 25 QTLs with 4.46-17.01% of phenotypic variance explained in the four environments. Meta-analysis revealed five consistent QTLs that could be detected in at least two environments. Notably, the consistent QTL cqSPA09 was detected in all four environments and explained 10.47-17.01% of the phenotypic variance. The segregation in the progeny of a residual heterozygous line confirmed that the cpSPA09 locus had additive effect in increasing shelling percentage. These consistent and major QTL regions provide opportunity not only for further gene discovery, but also for the development of functional markers for breeding.

Genotypic Regulation of Aflatoxin Accumulation but Not Aspergillus Fungal Growth upon Post-Harvest Infection of Peanut (Arachis hypogaea L.) Seeds

Aflatoxin contamination is a major economic and food safety concern for the peanut industry that largely could be mitigated by genetic resistance. To screen peanut for aflatoxin resistance, ten genotypes were infected with a green fluorescent protein (GFP)-expressing Aspergillus flavus strain. Percentages of fungal infected area and fungal GFP signal intensity were documented by visual ratings every 8 h for 72 h after inoculation. Significant genotypic differences in fungal growth rates were documented by repeated measures and area under the disease progress curve (AUDPC) analyses. SICIA (Seed Infection Coverage and Intensity Analyzer), an image processing software, was developed to digitize fungal GFP signals. Data from SICIA image analysis confirmed visual rating results validating its utility for quantifying fungal growth. Among the tested peanut genotypes, NC 3033 and GT-C20 supported the lowest and highest fungal growth on the surface of peanut seeds, respectively. Although differential fungal growth was observed on the surface of peanut seeds, total fungal growth in the seeds was not significantly different across genotypes based on a fluorometric GFP assay. Significant differences in aflatoxin B levels were detected across peanut genotypes. ICG 1471 had the lowest aflatoxin level whereas Florida-07 had the highest. Two-year aflatoxin tests under simulated late-season drought also showed that ICG 1471 had reduced aflatoxin production under pre-harvest field conditions. These results suggest that all peanut genotypes support A. flavus fungal growth yet differentially influence aflatoxin production.

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 Dissection of Novel QTLs for Resistance to Leaf Spots and Tomato Spotted Wilt Virus in Peanut (Arachis hypogaea L.)

Peanut is an important crop, economically and nutritiously, but high production cost is a serious challenge to peanut farmers as exemplified by chemical spray to control foliar diseases such as leaf spots and thrips, the vectors of tomato spotted wilt virus (TSWV). The objective of this research was to map the quantitative trait loci (QTLs) for resistance to leaf spots and TSWV in one recombinant inbred line (RIL) mapping population of "Tifrunner × GT-C20" for identification of linked markers for marker-assisted breeding. Here, we report the improved genetic linkage map with 418 marker loci with a marker density of 5.3 cM/loci and QTLs associated with multi-year (2010-2013) field phenotypes of foliar disease traits, including early leaf spot (ELS), late leaf spot (LLS), and TSWV. A total of 42 QTLs were identified with phenotypic variation explained (PVE) from 6.36 to 15.6%. There were nine QTLs for resistance to ELS, 22 QTLs for LLS, and 11 QTLs for TSWV, including six, five, and one major QTLs with PVE higher than 10% for resistance to each disease, respectively. Of the total 42 QTLs, 34 were mapped on the A sub-genome and eight mapped on the B sub-genome suggesting that the A sub-genome harbors more resistance genes than the B sub-genome. This genetic linkage map was also compared with two diploid peanut physical maps, and the overall co-linearity was 48.4% with an average co-linearity of 51.7% for the A sub-genome and 46.4% for the B sub-genome. The identified QTLs associated markers and potential candidate genes will be studied further for possible application in molecular breeding in peanut genetic improvement for disease resistance.

Co-localization of major quantitative trait loci for pod size and weight to a 3.7 cM interval on chromosome A05 in cultivated peanut (Arachis hypogaea L.)

Background

Cultivated peanut (Arachis hypogaea L.), an important source of edible oil and protein, is widely grown in tropical and subtropical areas of the world. Genetic improvement of yield-related traits is essential for improving yield potential of new peanut varieties. Genomics-assisted breeding (GAB) can accelerate the process of genetic improvement but requires linked markers for the traits of interest. In this context, we developed a recombinant inbred line (RIL) mapping population (Yuanza 9102 × Xuzhou 68-4) with 195 individuals and used to map quantitative trait loci (QTLs) associated with three important pod features, namely pod length, pod width and hundred-pod weight.

Results

QTL analysis using the phenotyping data generated across four environments in two locations and genotyping data on 743 mapped loci identified 15 QTLs for pod length, 11 QTLs for pod width and 16 QTLs for hundred-pod weight. The phenotypic variation explained (PVE) ranged from 3.68 to 27.84%. Thirteen QTLs were consistently detected in at least two environments and three QTLs (qPLA05.7, qPLA09.3 and qHPWA05.6) were detected in all four environments indicating their consistent and stable expression. Three major QTLs, detected in at least three environments, were found to be co-localized to a 3.7 cM interval on chromosome A05, and they were qPLA05.7 for pod length (16.89–27.84% PVE), qPWA05.5 for pod width (13.73–14.12% PVE), and qHPWA05.6 for hundred-pod weight (13.75–26.82% PVE). This 3.7 cM linkage interval corresponds to ~2.47 Mb genomic region of the pseudomolecule A05 of A. duranensis, including 114 annotated genes related to catalytic activity and metabolic process.

Conclusions

This study identified three major consistent and stable QTLs for pod size and weight which were co-localized in a 3.7 cM interval on chromosome A05. These QTL regions not only offer further investigation for gene discovery and development of functional markers but also provide opportunity for deployment of these QTLs in GAB for improving yield in peanut.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3456-x) contains supplementary material, which is available to authorized users.

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.

Genetic Variation and Association Mapping of Seed-Related Traits in Cultivated Peanut (Arachis hypogaea L.) Using Single-Locus Simple Sequence Repeat Markers

Cultivated peanut (Arachis hypogaea L.) is an allotetraploid (AABB, 2n = 4x = 40), valued for its edible oil and digestible protein. Seed size and weight are important agronomical traits significantly influence the yield and nutritional composition of peanut. However, the genetic basis of seed-related traits remains ambiguous. Association mapping is a powerful approach for quickly and efficiently exploring the genetic basis of important traits in plants. In this study, a total of 104 peanut accessions were used to identify molecular markers associated with seed-related traits using 554 single-locus simple sequence repeat (SSR) markers. Most of the accessions had no or weak relationship in the peanut panel. The linkage disequilibrium (LD) decayed with the genetic distance of 1cM at the genome level and the LD of B subgenome decayed faster than that of the A subgenome. Large phenotypic variation was observed for four seed-related traits in the association panel. Using mixed linear model with population structure and kinship, a total of 30 significant SSR markers were detected to be associated with four seed-related traits (P < 1.81 × 10^-3) in different environments, which explained 11.22-32.30% of the phenotypic variation for each trait. The marker AHGA44686 was simultaneously and repeatedly associated with seed length and hundred-seed weight in multiple environments with large phenotypic variance (26.23 ∼ 32.30%). The favorable alleles of associated markers for each seed-related trait and the optimal combination of favorable alleles of associated markers were identified to significantly enhance trait performance, revealing a potential of utilization of these associated markers in peanut breeding program.

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.

Evidence of Genomic Exchanges between Homeologous Chromosomes in a Cross of Peanut with Newly Synthetized Allotetraploid Hybrids

Cultivated peanut and synthetics are allotetraploids (2n = 4x = 40) with two homeologous sets of chromosomes. Meiosis in allotetraploid peanut is generally thought to show diploid-like behavior. However, a recent study pointed out the occurrence of recombination between homeologous chromosomes, especially when synthetic allotetraploids are used, challenging the view of disomic inheritance in peanut. In this study, we investigated the meiotic behavior of allotetraploid peanut using 380 SSR markers and 90 F2 progeny derived from the cross between Arachis hypogaea cv Fleur 11 (AABB) and ISATGR278-18 (AAKK), a synthetic allotetraploid that harbors a K-genome that was reported to pair with the cultivated B-genome during meiosis. Segregation analysis of SSR markers showed 42 codominant SSRs with unexpected null bands among some progeny. Chi-square tests for these loci deviate from the expected 1:2:1 Mendelian ratio under disomic inheritance. A linkage map of 357 codominant loci aligned on 20 linkage groups (LGs) with a total length of 1728 cM, averaging 5.1 cM between markers, was developed. Among the 10 homeologous sets of LGs, one set consisted of markers that all segregated in a polysomic-like pattern, six in a likely disomic pattern and the three remaining in a mixed pattern with disomic and polysomic loci clustered on the same LG. Moreover, we reported a substitution of homeologous chromosomes in some progeny. Our results suggest that the homeologous recombination events occurred between the A and K genomes in the newly synthesized allotetraploid and have been highlighted in the progeny. Homeologous exchanges are rarely observed in tetraploid peanut and have not yet been reported for AAKK and AABB genomes. The implications of these results on peanut breeding are discussed.

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.

Mapping Quantitative Trait Loci of Resistance to Tomato Spotted Wilt Virus and Leaf Spots in a Recombinant Inbred Line Population of Peanut (Arachis hypogaea L.) from SunOleic 97R and NC94022

Peanut is vulnerable to a range of diseases, such as Tomato spotted wilt virus (TSWV) and leaf spots which will cause significant yield loss. The most sustainable, economical and eco-friendly solution for managing peanut diseases is development of improved cultivars with high level of resistance. We developed a recombinant inbred line population from the cross between SunOleic 97R and NC94022, named as the S-population. An improved genetic linkage map was developed for the S-population with 248 marker loci and a marker density of 5.7 cM/loci. This genetic map was also compared with the physical map of diploid progenitors of tetraploid peanut, resulting in an overall co-linearity of about 60% with the average co-linearity of 68% for the A sub-genome and 47% for the B sub-genome. The analysis using the improved genetic map and multi-season (2010-2013) phenotypic data resulted in the identification of 48 quantitative trait loci (QTLs) with phenotypic variance explained (PVE) from 3.88 to 29.14%. Of the 48 QTLs, six QTLs were identified for resistance to TSWV, 22 QTLs for early leaf spot (ELS) and 20 QTLs for late leaf spot (LLS), which included four, six, and six major QTLs (PVE larger than 10%) for each disease, respectively. A total of six major genomic regions (MGR) were found to have QTLs controlling more than one disease resistance. The identified QTLs and resistance gene-rich MGRs will facilitate further discovery of resistance genes and development of molecular markers for these important diseases.

Homoeologs: What Are They and How Do We Infer Them?

The evolutionary history of nearly all flowering plants includes a polyploidization event. Homologous genes resulting from allopolyploidy are commonly referred to as 'homoeologs', although this term has not always been used precisely or consistently in the literature. With several allopolyploid genome sequencing projects under way, there is a pressing need for computational methods for homoeology inference. Here we review the definition of homoeology in historical and modern contexts and propose a precise and testable definition highlighting the connection between homoeologs and orthologs. In the second part, we survey experimental and computational methods of homoeolog inference, considering the strengths and limitations of each approach. Establishing a precise and evolutionarily meaningful definition of homoeology is essential for understanding the evolutionary consequences of polyploidization.

Analysis of genetic diversity and population structure of peanut cultivars and breeding lines from China, India and the US using simple sequence repeat markers

Cultivated peanut is grown worldwide as rich-source of oil and protein. A broad genetic base is needed for cultivar improvement. The objectives of this study were to develop highly informative simple sequence repeat (SSR) markers and to assess the genetic diversity and population structure of peanut cultivars and breeding lines from different breeding programs in China, India and the US. A total of 111 SSR markers were selected for this study, resulting in a total of 472 alleles. The mean values of gene diversity and polymorphic information content (PIC) were 0.480 and 0.429, respectively. Country-wise analysis revealed that alleles per locus in three countries were similar. The mean gene diversity in the US, China and India was 0.363, 0.489 and 0.47 with an average PIC of 0.323, 0.43 and 0.412, respectively. Genetic analysis using the STRUCTURE divided these peanut lines into two populations (P1, P2), which was consistent with the dendrogram based on genetic distance (G1, G2) and the clustering of principal component analysis. The groupings were related to peanut market types and the geographic origin with a few admixtures. The results could be used by breeding programs to assess the genetic diversity of breeding materials to broaden the genetic base and for molecular genetics studies.

Genomic Tools in Groundnut Breeding Program: Status and Perspectives

Groundnut, a nutrient-rich food legume, is cultivated world over. It is valued for its good quality cooking oil, energy and protein rich food, and nutrient-rich fodder. Globally, groundnut improvement programs have developed varieties to meet the preferences of farmers, traders, processors, and consumers. Enhanced yield, tolerance to biotic and abiotic stresses and quality parameters have been the target traits. Spurt in genetic information of groundnut was facilitated by development of molecular markers, genetic, and physical maps, generation of expressed sequence tags (EST), discovery of genes, and identification of quantitative trait loci (QTL) for some important biotic and abiotic stresses and quality traits. The first groundnut variety developed using marker assisted breeding (MAB) was registered in 2003. Since then, USA, China, Japan, and India have begun to use genomic tools in routine groundnut improvement programs. Introgression lines that combine foliar fungal disease resistance and early maturity were developed using MAB. Establishment of marker-trait associations (MTA) paved way to integrate genomic tools in groundnut breeding for accelerated genetic gain. Genomic Selection (GS) tools are employed to improve drought tolerance and pod yield, governed by several minor effect QTLs. Draft genome sequence and low cost genotyping tools such as genotyping by sequencing (GBS) are expected to accelerate use of genomic tools to enhance genetic gains for target traits in groundnut.

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.

QTL mapping for bacterial wilt resistance in peanut (Arachis hypogaea L.)

Bacterial wilt (BW) caused by Ralstonia solanacearum is a serious, global, disease of peanut (Arachis hypogaea L.), but it is especially destructive in China. Identification of DNA markers linked to the resistance to this disease will help peanut breeders efficiently develop resistant cultivars through molecular breeding. A F₂ population, from a cross between disease-resistant and disease-susceptible cultivars, was used to detect quantitative trait loci (QTL) associated with the resistance to this disease in the cultivated peanut. Genome-wide SNPs were identified from restriction-site-associated DNA sequencing tags using next-generation DNA sequencing technology. SNPs linked to disease resistance were determined in two bulks of 30 resistant and 30 susceptible plants along with two parental plants using bulk segregant analysis. Polymorphic SSR and SNP markers were utilized for construction of a linkage map and for performing the QTL analysis, and a moderately dense linkage map was constructed in the F₂ population. Two QTL (qBW-1 and qBW-2) detected for resistance to BW disease were located in the linkage groups LG1 and LG10 and account for 21 and 12 % of the bacterial wilt phenotypic variance. To confirm these QTL, the F₈ RIL population with 223 plants was utilized for genotyping and phenotyping plants by year and location as compared to the F₂ population. The QTL qBW-1 was consistent in the location of LG1 in the F₈ population though the QTL qBW-2 could not be clarified due to fewer markers used and mapped in LG10. The QTL qBW-1, including four linked SNP markers and one SSR marker within 14.4-cM interval in the F₈, was closely related to a disease resistance gene homolog and was considered as a candidate gene for resistance to BW. QTL identified in this study would be useful to conduct marker-assisted selection and may permit cloning of resistance genes. Our study shows that bulk segregant analysis of genome-wide SNPs is a useful approach to expedite the identification of genetic markers linked to disease resistance traits in the allotetraploidy species peanut.

Quantitative trait locus analysis for pod- and kernel-related traits in the cultivated peanut (Arachis hypogaea L.)

BACKGROUND

The cultivated peanut (Arachis hypogaea L.) is an important oil and food crop in the world. Pod- and kernel-related traits are direct factors involved in determining the yield of the peanut. However, the genetic basis underlying pod- and kernel-related traits in the peanut remained largely unknown, which hampered the improvement of peanut through marker-assisted selection. To understand the genetic basis underlying pod- and kernel-related traits in the peanut and provide more useful information for marker-assisted breeding, we conducted quantitative trait locus (QTL) analysis for pod length and width and seed length and width by use of two F2:3 populations derived from cultivar Fuchuan Dahuasheng × ICG 6375 (FI population) and cultivar Xuhua 13 × cultivar Zhonghua 6 (XZ population) in this study.

RESULTS

Two genetic maps containing 347 and 228 polymorphic markers were constructed for FI and XZ populations respectively. In total, 39 QTLs explaining 1.25-26.11% of the phenotypic variations were detected in two populations. For the FI population, 26 QTLs were detected between the two environments, among which twelve were not mapped before. For the XZ population, thirteen QTLs were detected, among which eight were not reported before. One QTL for pod width was repeatedly mapped between the two populations.

CONCLUSION

The QTL analyses for pod length and width and seed length and width were conducted in this study using two mapping populations. Novel QTLs were identified, which included two for pod length, four for pod width, five for seed length and one for seed width in the FI population, and three for pod length, three for pod width and two for seed width in the XZ population. Our results will be helpful for improving pod- and seed-related traits in peanuts through marker-assisted selection.

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.

Tropical food legumes: virus diseases of economic importance and their control

Diverse array of food legume crops (Fabaceae: Papilionoideae) have been adopted worldwide for their protein-rich seed. Choice of legumes and their importance vary in different parts of the world. The economically important legumes are severely affected by a range of virus diseases causing significant economic losses due to reduction in grain production, poor quality seed, and costs incurred in phytosanitation and disease control. The majority of the viruses infecting legumes are vectored by insects, and several of them are also seed transmitted, thus assuming importance in the quarantine and in the epidemiology. This review is focused on the economically important viruses of soybean, groundnut, common bean, cowpea, pigeonpea, mungbean, urdbean, chickpea, pea, faba bean, and lentil and begomovirus diseases of three minor tropical food legumes (hyacinth bean, horse gram, and lima bean). Aspects included are geographic distribution, impact on crop growth and yields, virus characteristics, diagnosis of causal viruses, disease epidemiology, and options for control. Effectiveness of selection and planting with virus-free seed, phytosanitation, manipulation of crop cultural and agronomic practices, control of virus vectors and host plant resistance, and potential of transgenic resistance for legume virus disease control are discussed.

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.

Genetic mapping of QTLs controlling fatty acids provided insights into the genetic control of fatty acid synthesis pathway in peanut (Arachis hypogaea L.)

Peanut, a high-oil crop with about 50% oil content, is either crushed for oil or used as edible products. Fatty acid composition determines the oil quality which has high relevance to consumer health, flavor, and shelf life of commercial products. In addition to the major fatty acids, oleic acid (C18:1) and linoleic acid (C18:2) accounting for about 80% of peanut oil, the six other fatty acids namely palmitic acid (C16:0), stearic acid (C18:0), arachidic acid (C20:0), gadoleic acid (C20:1), behenic acid (C22:0), and lignoceric acid (C24:0) are accounted for the rest 20%. To determine the genetic basis and to improve further understanding on effect of FAD2 genes on these fatty acids, two recombinant inbred line (RIL) populations namely S-population (high oleic line 'SunOleic 97R' × low oleic line 'NC94022') and T-population (normal oleic line 'Tifrunner' × low oleic line 'GT-C20') were developed. Genetic maps with 206 and 378 marker loci for the S- and the T-population, respectively were used for quantitative trait locus (QTL) analysis. As a result, a total of 164 main-effect (M-QTLs) and 27 epistatic (E-QTLs) QTLs associated with the minor fatty acids were identified with 0.16% to 40.56% phenotypic variation explained (PVE). Thirty four major QTLs (>10% of PVE) mapped on five linkage groups and 28 clusters containing more than three QTLs were also identified. These results suggest that the major QTLs with large additive effects would play an important role in controlling composition of these minor fatty acids in addition to the oleic and linoleic acids in peanut oil. The interrelationship among these fatty acids should be considered while breeding for improved peanut genotypes with good oil quality and desired fatty acid composition.

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.

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.

Identification of QTLs associated with oil content and mapping FAD2 genes and their relative contribution to oil quality in peanut (Arachis hypogaea L.)

BACKGROUND

Peanut is one of the major source for human consumption worldwide and its seed contain approximately 50% oil. Improvement of oil content and quality traits (high oleic and low linoleic acid) in peanut could be accelerated by exploiting linked markers through molecular breeding. The objective of this study was to identify QTLs associated with oil content, and estimate relative contribution of FAD2 genes (ahFAD2A and ahFAD2B) to oil quality traits in two recombinant inbred line (RIL) populations.

RESULTS

Improved genetic linkage maps were developed for S-population (SunOleic 97R × NC94022) with 206 (1780.6 cM) and T-population (Tifrunner × GT-C20) with 378 (2487.4 cM) marker loci. A total of 6 and 9 QTLs controlling oil content were identified in the S- and T-population, respectively. The contribution of each QTL towards oil content variation ranged from 3.07 to 10.23% in the S-population and from 3.93 to 14.07% in the T-population. The mapping positions for ahFAD2A (A sub-genome) and ahFAD2B (B sub-genome) genes were assigned on a09 and b09 linkage groups. The ahFAD2B gene (26.54%, 25.59% and 41.02% PVE) had higher phenotypic effect on oleic acid (C18:1), linoleic acid (C18:2), and oleic/linoleic acid ratio (O/L ratio) than ahFAD2A gene (8.08%, 6.86% and 3.78% PVE). The FAD2 genes had no effect on oil content. This study identified a total of 78 main-effect QTLs (M-QTLs) with up to 42.33% phenotypic variation (PVE) and 10 epistatic QTLs (E-QTLs) up to 3.31% PVE for oil content and quality traits.

CONCLUSIONS

A total of 78 main-effect QTLs (M-QTLs) and 10 E-QTLs have been detected for oil content and oil quality traits. One major QTL (more than 10% PVE) was identified in both the populations for oil content with source alleles from NC94022 and GT-C20 parental genotypes. FAD2 genes showed high effect for oleic acid (C18:1), linoleic acid (C18:2), and O/L ratio while no effect on total oil content. The information on phenotypic effect of FAD2 genes for oleic acid, linoleic acid and O/L ratio, and oil content will be applied in breeding selection.

Construction of a high-quality genomic BAC library for Chinese peanut cultivar Zhonghua 8 with high oil content

BACKGROUND

Arachis hypogaea L. (2n = 4× = 40, AABB) is one of the most important oil and economic crop plants in the word. This species has the largest genome size of about 2,813 Mb among the oil crop species. Zhonghua 8 is a peanut cultivar planted widely in central China and has several superior traits including high oil content, high yield and disease resistance. A high-quality BAC library of Zhonghua 8 was constructed for future researches on the genomics of Chinese peanut cultivars.

RESULTS

A Hin d III-digested genomic BAC (bacterial artificial chromosome) library was constructed with the genomic DNA from leaves of Zhonghua 8. This BAC library consists of 160,512 clones and the average insert is estimated about 102 kb ranging from 30 to 150 kb. The library represents about 5.55× haploid genome equivalents, and provides a 99.71% probability of finding specific genes. The empty-vector rate is under 5 percent detected from 200 randomly selected clones. Probing of 384 clones with the psbA gene of barley chloroplast and the atp6 gene of rice mitochondrion indicated that the contamination with organellar DNA is insignificant. Successive subculture of three clones showed that the inserts are stable in one hundred generations.

CONCLUSIONS

This study presented the construction of a high-quality BAC library for the genome of Chinese cultivated peanut. Many essential experiences were summarized in the present study. This BAC library can serve as a substantial platform for development of molecular marker, isolation of genes and further genome research.

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.

Use of EST-SSR markers for evaluating genetic diversity and fingerprinting celery (Apium graveolens L.) cultivars

Celery (Apium graveolens L.) is one of the most economically important vegetables worldwide, but genetic and genomic resources supporting celery molecular breeding are quite limited, thus few studies on celery have been conducted so far. In this study we made use of simple sequence repeat (SSR) markers generated from previous celery transcriptome sequencing and attempted to detect the genetic diversity and relationships of commonly used celery accessions and explore the efficiency of the primers used for cultivars identification. Analysis of molecular variance (AMOVA) of Apium graveolens L. var. dulce showed that approximately 43% of genetic diversity was within accessions, 45% among accessions, and 22% among horticultural types. The neighbor-joining tree generated by unweighted pair group method with arithmetic mean (UPGMA), and population structure analysis, as well as principal components analysis (PCA), separated the cultivars into clusters corresponding to the geographical areas where they originated. Genetic distance analysis suggested that genetic variation within Apium graveolens was quite limited. Genotypic diversity showed any combinations of 55 genic SSRs were able to distinguish the genotypes of all 30 accessions.

Genetic diversity and population structure of the major peanut (Arachis hypogaea L.) cultivars grown in China by SSR markers

One hundred and forty-six highly polymorphic simple sequence repeat (SSR) markers were used to assess the genetic diversity and population structure of 196 peanut (Arachis Hypogaea L.) cultivars which had been extensively planted in different regions in China. These SSR markers amplified 440 polymorphic bands with an average of 2.99, and the average gene diversity index was 0.11. Eighty-six rare alleles with a frequency of less than 1% were identified in these cultivars. The largest Fst or genetic distance was found between the cultivars that adapted to the south regions and those to the north regions in China. A neighbor-joining tree of cultivars adapted to different ecological regions was constructed based on pairwise Nei's genetic distances, which showed a significant difference between cultivars from the south and the north regions. A model-based population structure analysis divided these peanut cultivars into five subpopulations (P1a, P1b, P2, P3a and P3b). P1a and P1b included most the cultivars from the southern provinces including Guangdong, Guangxi and Fujian. P2 population consisted of the cultivars from Hubei province and parts from Shandong and Henan. P3a and P3b had cultivars from the northern provinces including Shandong, Anhui, Henan, Hebei, Jiangsu and the Yangtze River region including Sichuan province. The cluster analysis, PCoA and PCA based on the marker genotypes, revealed five distinct clusters for the entire population that were related to their germplasm regions. The results indicated that there were obvious genetic variations between cultivars from the south and the north, and there were distinct genetic differentiation among individual cultivars from the south and the north. Taken together, these results provided a molecular basis for understanding genetic diversity of Chinese peanut cultivars.

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.

Identification of expressed resistance gene analogs from peanut (Arachis hypogaea L.) expressed sequence tags

Low genetic diversity makes peanut (Arachis hypogaea L.) very vulnerable to plant pathogens, causing severe yield loss and reduced seed quality. Several hundred partial genomic DNA sequences as nucleotide-binding-site leucine-rich repeat (NBS-LRR) resistance genes (R) have been identified, but a small portion with expressed transcripts has been found. We aimed to identify resistance gene analogs (RGAs) from peanut expressed sequence tags (ESTs) and to develop polymorphic markers. The protein sequences of 54 known R genes were used to identify homologs from peanut ESTs from public databases. A total of 1,053 ESTs corresponding to six different classes of known R genes were recovered, and assembled 156 contigs and 229 singletons as peanut-expressed RGAs. There were 69 that encoded for NBS-LRR proteins, 191 that encoded for protein kinases, 82 that encoded for LRR-PK/transmembrane proteins, 28 that encoded for Toxin reductases, 11 that encoded for LRR-domain containing proteins and four that encoded for TM-domain containing proteins. Twenty-eight simple sequence repeats (SSRs) were identified from 25 peanut expressed RGAs. One SSR polymorphic marker (RGA121) was identified. Two polymerase chain reaction-based markers (Ahsw-1 and Ahsw-2) developed from RGA013 were homologous to the Tomato Spotted Wilt Virus (TSWV) resistance gene. All three markers were mapped on the same linkage group AhIV. These expressed RGAs are the source for RGA-tagged marker development and identification of peanut resistance genes.

Development of COS-SNP and HRM markers for high-throughput and reliable haplotype-based detection of Lr14a in durum wheat (Triticum durum Desf.)

Leaf rust (Puccinia triticina Eriks. & Henn.) is a major disease affecting durum wheat production. The Lr14a-resistant gene present in the durum wheat cv. Creso and its derivative cv. Colosseo is one of the best characterized leaf-rust resistance sources deployed in durum wheat breeding. Lr14a has been mapped close to the simple sequence repeat markers gwm146, gwm344 and wmc10 in the distal portion of the chromosome arm 7BL, a gene-dense region. The objectives of this study were: (1) to enrich the Lr14a region with single nucleotide polymorphisms (SNPs) and high-resolution melting (HRM)-based markers developed from conserved ortholog set (COS) genes and from sequenced Diversity Array Technology (DArT(®)) markers; (2) to further investigate the gene content and colinearity of this region with the Brachypodium and rice genomes. Ten new COS-SNP and five HRM markers were mapped within an 8.0 cM interval spanning Lr14a. Two HRM markers pinpointed the locus in an interval of <1.0 cM and eight COS-SNPs were mapped 2.1-4.1 cM distal to Lr14a. Each marker was tested for its capacity to predict the state of Lr14a alleles (in particular, Lr14-Creso associated to resistance) in a panel of durum wheat elite germplasm including 164 accessions. Two of the most informative markers were converted into KASPar(®) markers. Single assay markers ubw14 and wPt-4038-HRM designed for agarose gel electrophoresis/KASPar(®) assays and high-resolution melting analysis, respectively, as well as the double-marker combinations ubw14/ubw18, ubw14/ubw35 and wPt-4038-HRM-ubw35 will be useful for germplasm haplotyping and for molecular-assisted breeding.