QTL-seq approach identified genomic regions and diagnostic markers for rust and late leaf spot resistance in groundnut (Arachis hypogaea L.)

Identification and application of a candidate gene AhAftr1 for aflatoxin production resistance in peanut seed (Arachis hypogaea L.)

INTRODUCTION

Peanut is susceptible to infection of Aspergillus fungi and conducive to aflatoxin contamination, hence developing aflatoxin-resistant variety is highly meaningful. Identifying functional genes or loci conferring aflatoxin resistance and molecular diagnostic marker are crucial for peanut breeding.

OBJECTIVES

This work aims to (1) identify candidate gene for aflatoxin production resistance, (2) reveal the related resistance mechanism, and (3) develop diagnostic marker for resistance breeding program.

METHODS

Resistance to aflatoxin production in a recombined inbred line (RIL) population derived from a high-yielding variety Xuhua13 crossed with an aflatoxin-resistant genotype Zhonghua 6 was evaluated under artificial inoculation for three consecutive years. Both genetic linkage analysis and QTL-seq were conducted for QTL mapping. The candidate gene was further fine-mapped using a secondary segregation mapping population and validated by transgenic experiments. RNA-Seq analysis among resistant and susceptible RILs was used to reveal the resistance pathway for the candidate genes.

RESULTS

The major effect QTL qAFTRA07.1 for aflatoxin production resistance was mapped to a 1.98 Mbp interval. A gene, AhAftr1 (Arachis hypogaea Aflatoxin resistance 1), was detected structure variation (SV) in leucine rich repeat (LRR) domain of its production, and involved in disease resistance response through the effector-triggered immunity (ETI) pathway. Transgenic plants with overexpression of AhAftr1(ZH6) exhibited 57.3% aflatoxin reduction compared to that of AhAftr1(XH13). A molecular diagnostic marker AFTR.Del.A07 was developed based on the SV. Thirty-six lines, with aflatoxin content decrease by over 77.67% compared to the susceptible control Zhonghua12 (ZH12), were identified from a panel of peanut germplasm accessions and breeding lines through using AFTR.Del.A07.

CONCLUSION

Our findings would provide insights of aflatoxin production resistance mechanisms and laid meaningful foundation for further breeding programs.

Fine mapping and identification of a Fusarium wilt resistance gene FwS1 in pea

KEY MESSAGE

A Fusarium wilt resistance gene FwS1 on pea chromosome 6 was identified and mapped to a 91.4 kb region by a comprehensive genomic-based approach, and the gene Psat6g003960 harboring NB-ARC domain was identified as the putative candidate gene. Pea Fusarium wilt, incited by Fusarium oxysporum f. sp. pisi (Fop), has always been a devastating disease that causes severe yield losses and economic damage in pea-growing regions worldwide. The utilization of pea cultivars carrying resistance gene is the most efficient approach for managing this disease. In order to finely map resistance gene, F2 populations were established through the cross between Shijiadacaiwan 1 (resistant) and Y4 (susceptible). The resistance genetic analysis indicated that the Fop resistance in Shijiadacaiwan 1 was governed by a single dominant gene, named FwS1. Based on the bulked segregant analysis sequencing analyses, the gene FwS1 was initially detected on chromosome 6 (i.e., linking group II, chr6LG2), and subsequent linkage mapping with 589 F2 individuals fine-mapped the gene FwS1 into a 91.4 kb region. The further functional annotation and haplotype analysis confirmed that the gene Psat6g003960, characterized by a NB-ARC (nucleotide-binding adaptor shared by APAF-1, R proteins, and CED-4) domain, was considered as the most promising candidate gene. The encoding amino acids were altered by a "T/C" single-nucleotide polymorphism (SNP) in the first exon of the Psat6g003960, and based on this SNP locus, the molecular marker A016180 was determined to be a diagnostic marker for FwS1 by validating its specificity in both pea accessions and genetic populations with different genetic backgrounds. The FwS1 with diagnostic KASP marker A016180 could facilitate marker-assisted selection in resistance pea breeding in pea. In addition, a comparison of the candidate gene Psat6g003960 in 74SN3B and SJ1 revealed the same sequences. This finding indicated that 74SN3B carried the candidate gene for FwS1, suggesting that FwS1 and Fwf may be closely linked or an identical resistant gene against Fusarium wilt.

Validation and identification of promising gene specific markers governing foliar disease resistance in groundnut (Arachis hypogaea L.)

BACKGROUND

Groundnut is vulnerable to the major foliar fungal disease viz., late leaf spot (LLS) and rust in kharif season, which results in severe yield losses. Until now, LLS and rust resistance linked markers were developed based on GPBD 4 as a major donor source and were validated in its derivatives only, which restricted their use in marker assisted selection (MAS) involving other donors.

METHODS AND RESULTS

The current study focused to validate LLS and rust resistance linked markers employing advanced breeding lines of F6 generation, derived from nine different crosses involving nine diverse parents, to identify potential markers for marker-assisted breeding of LLS and rust resistance in groundnut. Out of 28-trait linked markers used for validation, 8 were polymorphic (28.57%). Marker-trait association (MTA) and Single Marker Analysis (SMA) revealed that the SSR marker pPGPseq5D05 is significantly associated with both LLS (15.8% PVE) and rust (17.5% PVE) resistance, whereas, the marker IPAHM103 is tightly linked with rust resistance (26.8% PVE) alone. In silico analysis revealed that the marker gene for IPAHM103 is a zinc finger protein and the marker gene for pPGPseq5D05 is an ADP-ribosylation factor GTPase-activating protein. Both these protein products impart resistance or tolerance to biotic stress in crop plants. Two other markers namely, GMLQ975 and pPGPseq13A10 were also found to be associated with LLS resistance explaining MTA up to 60%.

CONCLUSION

These gene specific markers will enable us to screen more number of germplasm lines or newly developed lines in MAS schemes for LLS and rust resistance using a wide range of resistant sources.

Celebrating Professor Rajeev K. Varshney's transformative research odyssey from genomics to the field on his induction as Fellow of the Royal Society

Professor Rajeev K. Varshney's transformative impact on crop genomics, genetics, and agriculture is the result of his passion, dedication, and unyielding commitment to harnessing the potential of genomics to address the most pressing challenges faced by the global agricultural community. Starting from a small town in India and reaching the global stage, Professor Varshney's academic and professional trajectory has inspired many scientists active in research today. His ground-breaking work, especially his effort to list orphan tropical crops to genomic resource-rich entities, has been transformative. Beyond his scientific achievements, Professor Varshney is recognized by his colleagues as an exemplary mentor, fostering the growth of future researchers, building institutional capacity, and strengthening scientific capability. His focus on translational genomics and strengthening seed system in developing countries for the improvement of agriculture has made a tangible impact on farmers' lives. His skills have been best utilized in roles at leading research centres where he has applied his expertise to deliver a new vision for crop improvement. These efforts have now been recognized by the Royal Society with the award of the Fellowship (FRS). As we mark this significant milestone in his career, we not only celebrate Professor Varshney's accomplishments but also his wider contributions that continue to transform the agricultural landscape.

Linkage Mapping and Genome-Wide Association Study Identified Two Peanut Late Leaf Spot Resistance Loci, PLLSR-1 and PLLSR-2, Using Nested Association Mapping

Identification of candidate genes and molecular markers for late leaf spot (LLS) disease resistance in peanut (Arachis hypogaea) has been a focus of molecular breeding for the U.S. industry-funded peanut genome project. Efforts have been hindered by limited mapping resolution due to low levels of genetic recombination and marker density available in traditional biparental mapping populations. To address this, a multi-parental nested association mapping population has been genotyped with the peanut 58K single-nucleotide polymorphism (SNP) array and phenotyped for LLS severity in the field for 3 years. Joint linkage-based quantitative trait locus (QTL) mapping identified nine QTLs for LLS resistance with significant phenotypic variance explained up to 47.7%. A genome-wide association study identified 13 SNPs consistently associated with LLS resistance. Two genomic regions harboring the consistent QTLs and SNPs were identified from 1,336 to 1,520 kb (184 kb) on chromosome B02 and from 1,026.9 to 1,793.2 kb (767 kb) on chromosome B03, designated as peanut LLS resistance loci, PLLSR-1 and PLLSR-2, respectively. PLLSR-1 contains 10 nucleotide-binding site leucine-rich repeat disease resistance genes. A nucleotide-binding site leucine-rich repeat disease resistance gene, Arahy.VKVT6A, was also identified on homoeologous chromosome A02. PLLSR-2 contains five significant SNPs associated with five different genes encoding callose synthase, pollen defective in guidance protein, pentatricopeptide repeat, acyl-activating enzyme, and C2 GRAM domains-containing protein. This study highlights the power of multi-parent populations such as nested association mapping for genetic mapping and marker-trait association studies in peanuts. Validation of these two LLS resistance loci will be needed for marker-assisted breeding.

Identification of candidate genes associated with peanut pod length by combined analysis of QTL-seq and RNA-seq

Pod length (PL) is one of the major traits determining pod size and yield of peanut. Discovering the quantitative trait loci (QTL) and identifying candidate genes associated with PL are essential for breeding high-yield peanut. In this study, quantitative trait loci sequencing (QTL-seq) was performed using the F2 population constructed by a short-pod variety Tifrunner (Tif) and a long-pod line Lps, and a 0.77 Mb genomic region on chromosome 07 was identified as the candidate region for PL. Then, the candidate region was narrowed to a 265.93 kb region by traditional QTL approach. RNA-seq analysis showed that there were four differentially expressed genes (DEGs) in the candidate region, among which Arahy.PF2L6F (AhCDC48) and Arahy.P4LK2T (AhTAA1) were speculated to be PL-related candidate genes. These results were informative for the elucidation of the underlying regulatory mechanism in peanut pod length and would facilitate further identification of valuable target genes.

Genetic diversity, disease resistance, and environmental adaptation of Arachis duranensis L.: New insights from landscape genomics

The genetic diversity that exists in natural populations of Arachis duranensis, the wild diploid donor of the A subgenome of cultivated tetraploid peanut, has the potential to improve crop adaptability, resilience to major pests and diseases, and drought tolerance. Despite its potential value for peanut improvement, limited research has been focused on the association between allelic variation, environmental factors, and response to early (ELS) and late leaf spot (LLS) diseases. The present study implemented a landscape genomics approach to gain a better understanding of the genetic variability of A. duranensis represented in the ex-situ peanut germplasm collection maintained at the U.S. Department of Agriculture, which spans the entire geographic range of the species in its center of origin in South America. A set of 2810 single nucleotide polymorphism (SNP) markers allowed a high-resolution genome-wide characterization of natural populations. The analysis of population structure showed a complex pattern of genetic diversity with five putative groups. The incorporation of bioclimatic variables for genotype-environment associations, using the latent factor mixed model (LFMM2) method, provided insights into the genomic signatures of environmental adaptation, and led to the identification of SNP loci whose allele frequencies were correlated with elevation, temperature, and precipitation-related variables (q < 0.05). The LFMM2 analysis for ELS and LLS detected candidate SNPs and genomic regions on chromosomes A02, A03, A04, A06, and A08. These findings highlight the importance of the application of landscape genomics in ex situ collections of peanut and other crop wild relatives to effectively identify favorable alleles and germplasm for incorporation into breeding programs. We report new sources of A. duranensis germplasm harboring adaptive allelic variation, which have the potential to be utilized in introgression breeding for a single or multiple environmental factors, as well as for resistance to leaf spot diseases.

High-throughput diagnostic markers for foliar fungal disease resistance and high oleic acid content in groundnut

BACKGROUND

Foliar diseases namely late leaf spot (LLS) and leaf rust (LR) reduce yield and deteriorate fodder quality in groundnut. Also the high oleic acid content has emerged as one of the most important traits for industries and consumers due to its increased shelf life and health benefits.

RESULTS

Genetic mapping combined with pooled sequencing approaches identified candidate resistance genes (LLSR1 and LLSR2 for LLS and LR1 for LR) for both foliar fungal diseases. The LLS-A02 locus housed LLSR1 gene for LLS resistance, while, LLS-A03 housed LLSR2 and LR1 genes for LLS and LR resistance, respectively. A total of 49 KASPs markers were developed from the genomic regions of important disease resistance genes, such as NBS-LRR, purple acid phosphatase, pentatricopeptide repeat-containing protein, and serine/threonine-protein phosphatase. Among the 49 KASP markers, 41 KASPs were validated successfully on a validation panel of contrasting germplasm and breeding lines. Of the 41 validated KASPs, 39 KASPs were designed for rust and LLS resistance, while two KASPs were developed using fatty acid desaturase (FAD) genes to control high oleic acid levels. These validated KASP markers have been extensively used by various groundnut breeding programs across the world which led to development of thousands of advanced breeding lines and few of them also released for commercial cultivation.

CONCLUSION

In this study, high-throughput and cost-effective KASP assays were developed, validated and successfully deployed to improve the resistance against foliar fungal diseases and oleic acid in groundnut. So far deployment of allele-specific and KASP diagnostic markers facilitated development and release of two rust- and LLS-resistant varieties and five high-oleic acid groundnut varieties in India. These validated markers provide opportunities for routine deployment in groundnut breeding programs.

High-density bin-based genetic map reveals a 530-kb chromosome segment derived from wild peanut contributing to late leaf spot resistance

KEY MESSAGE

Twenty-eight QTLs for LLS disease resistance were identified using an amphidiploid constructed mapping population, a favorable 530-kb chromosome segment derived from wild species contributes to the LLS resistance. Late leaf spot (LLS) is one of the major foliar diseases of peanut, causing serious yield loss and affecting the quality of kernel and forage. Some wild Arachis species possess higher resistance to LLS as compared with cultivated peanut; however, ploidy level differences restrict utilization of wild species. In this study, a synthetic amphidiploid (Ipadur) of wild peanuts with high LLS resistance was used to cross with Tifrunner to construct TI population. In total, 200 recombinant inbred lines were collected for whole-genome resequencing. A high-density bin-based genetic linkage map was constructed, which includes 4,809 bin markers with an average inter-bin distance of 0.43 cM. The recombination across cultivated and wild species was unevenly distributed, providing a novel recombination landscape for cultivated-wild Arachis species. Using phenotyping data collected across three environments, 28 QTLs for LLS disease resistance were identified, explaining 4.35-20.42% of phenotypic variation. The major QTL located on chromosome 14, qLLS14.1, could be consistently detected in 2021 Jiyang and 2022 Henan with 20.42% and 12.12% PVE, respectively. A favorable 530-kb chromosome segment derived from Ipadur was identified in the region of qLLS14.1, in which 23 disease resistance proteins were located and six of them showed significant sequence variations between Tifrunner and Ipadur. Allelic variation analysis indicating the 530-kb segment of wild species might contribute to the disease resistance of LLS. These associate genomic regions and candidate resistance genes are of great significance for peanut breeding programs for bringing durable resistance through pyramiding such multiple LLS resistance loci into peanut cultivars.

Designing future peanut: the power of genomics-assisted breeding

KEY MESSAGE

Integrating GAB methods with high-throughput phenotyping, genome editing, and speed breeding hold great potential in designing future smart peanut cultivars to meet market and food supply demands. Cultivated peanut (Arachis hypogaea L.), a legume crop greatly valued for its nourishing food, cooking oil, and fodder, is extensively grown worldwide. Despite decades of classical breeding efforts, the actual on-farm yield of peanut remains below its potential productivity due to the complicated interplay of genotype, environment, and management factors, as well as their intricate interactions. Integrating modern genomics tools into crop breeding is necessary to fast-track breeding efficiency and rapid progress. When combined with speed breeding methods, this integration can substantially accelerate the breeding process, leading to faster access of improved varieties to farmers. Availability of high-quality reference genomes for wild diploid progenitors and cultivated peanuts has accelerated the process of gene/quantitative locus discovery, developing markers and genotyping assays as well as a few molecular breeding products with improved resistance and oil quality. The use of new breeding tools, e.g., genomic selection, haplotype-based breeding, speed breeding, high-throughput phenotyping, and genome editing, is probable to boost genetic gains in peanut. Moreover, renewed attention to efficient selection and exploitation of targeted genetic resources is also needed to design high-quality and high-yielding peanut cultivars with main adaptation attributes. In this context, the combination of genomics-assisted breeding (GAB), genome editing, and speed breeding hold great potential in designing future improved peanut cultivars to meet market and food supply demands.

Genome-wide SNP discovery and genotyping delineates potential QTLs underlying major yield-attributing traits in buckwheat

Buckwheat (Fagopyrum spp.) is an important nutritional and nutraceutical-rich pseudo-cereal crop. Despite its obvious potential as a functional food, buckwheat has not been fully harnessed due to its low yield, self-incompatibility, increased seed cracking, limited seed set, lodging, and frost susceptibility. The inadequate availability of genomics resources in buckwheat is one of the major reasons for this. In the present study, genome-wide association mapping (GWAS) was conducted to identify loci associated with various morphological and yield-related traits in buckwheat. High throughput genotyping by sequencing led to the identification of 34,978 single nucleotide polymorphisms that were distributed across eight chromosomes. Population structure analysis grouped the genotypes into three sub-populations. The genotypes were also characterized for various qualitative and quantitative traits at two diverse locations, the analysis of which revealed a significant difference in the mean values. The association analysis revealed a total of 71 significant marker-trait associations across eight chromosomes. The candidate genes were identified near 100 Kb of quantitative trait loci (QTLs), providing insights into several metabolic and biosynthetic pathways. The integration of phenology and GWAS in the present study is useful to uncover the consistent genomic regions, related markers associated with various yield-related traits, and potential candidate genes having implications for being utilized in molecular breeding for the improvement of economically important traits in buckwheat. Moreover, the identified QTLs will assist in tracking the desirable alleles of target genes within the buckwheat breeding populations/germplasm.

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.

Delineation of genes for a major QTL governing heat stress tolerance in chickpea

Chickpea (Cicer arietinum) is a cool season grain legume experiencing severe yield loss during heat stress due to the intensifying climate changes and its associated gradual increase of mean temperature. Hence, understanding the genetic architecture regulating heat stress tolerance has emerged as an important trait to be addressed for enhancing yield and productivity of chickpea under heat stress. The present study is intended to identify the major genomic region(s) governing heat stress tolerance in chickpea. For this, an integrated genomics-assisted breeding strategy involving NGS-based high-resolution QTL-seq assay, QTL region-specific association analysis and molecular haplotyping was deployed in a population of 206 mapping individuals and a diversity panel of 217 germplasm accessions of chickpea. This combinatorial strategy delineated a major 156.8 kb QTL genomic region, which was subsequently narrowed-down to a functional candidate gene CaHSFA5 and its natural alleles associated strongly with heat stress tolerance in chickpea. Superior natural alleles and haplotypes delineated from the CaHSFA5 gene have functional significance in regulating heat stress tolerance in chickpea. Histochemical staining, interaction studies along with differential expression profiling of CaHSFA5 and ROS scavenging genes suggest a cross talk between CaHSFA5 with ROS homeostasis pertaining to heat stress tolerance in chickpea. Heterologous gene expression followed by heat stress screening further validated the functional significance of CaHSFA5 for heat stress tolerance. The salient outcomes obtained here can have potential to accelerate multiple translational genomic analysis including marker-assisted breeding and gene editing in order to develop high-yielding heat stress tolerant chickpea varieties.

Effects of Peanut Rust Disease (Puccinia arachidis Speg.) on Agricultural Production: Current Control Strategies and Progress in Breeding for Resistance

Peanuts play a pivotal role as an economic crop on a global scale, serving as a primary source of both edible oil and protein. Peanut rust (Puccinia arachidis Speg.) disease constitutes a significant global biotic stress, representing a substantial economic threat to the peanut industry by inducing noteworthy reductions in seed yields and compromising oil quality. This comprehensive review delves into the distinctive characteristics and detrimental symptoms associated with peanut rust, scrutinizing its epidemiology and the control strategies that are currently implemented. Notably, host resistance emerges as the most favored strategy due to its potential to surmount the limitations inherent in other approaches. The review further considers the recent advancements in peanut rust resistance breeding, integrating the use of molecular marker technology and the identification of rust resistance genes. Our findings indicate that the ongoing refinement of control strategies, especially through the development and application of immune or highly resistant peanut varieties, will have a profound impact on the global peanut industry.

Superior haplotypes of key drought-responsive genes reveal opportunities for the development of climate-resilient rice varieties

Haplotype-based breeding is an emerging and innovative concept that enables the development of designer crop varieties by exploiting and exploring superior alleles/haplotypes among target genes to create new traits in breeding programs. In this regard, whole-genome re-sequencing of 399 genotypes (landraces and breeding lines) from the 3000 rice genomes panel (3K-RG) is mined to identify the superior haplotypes for 95 drought-responsive candidate genes. Candidate gene-based association analysis reveals 69 marker-trait associations (MTAs) in 16 genes for single plant yield (SPY) under drought stress. Haplo-pheno analysis of these 16 genes identifies superior haplotypes for seven genes associated with the higher SPY under drought stress. Our study reveals that the performance of lines possessing superior haplotypes is significantly higher (p ≤ 0.05) as measured by single plant yield (SPY), for the OsGSK1-H4, OsDSR2-H3, OsDIL1-H22, OsDREB1C-H3, ASR3-H88, DSM3-H4 and ZFP182-H4 genes as compared to lines without the superior haplotypes. The validation results indicate that a superior haplotype for the DREB transcription factor (OsDREB1C) is present in all the drought-tolerant rice varieties, while it was notably absent in all susceptible varieties. These lines carrying the superior haplotypes can be used as potential donors in haplotype-based breeding to develop high-yielding drought-tolerant rice varieties.

Deploying QTL-seq rapid identification and separation of the major QTLs of tassel branch number for fine-mapping in advanced maize populations

The tassel competes with the ear for nutrients and shields the upper leaves, thereby reducing the yield of grain. The tassel branch number (TBN) is a pivotal determinant of tassel size, wherein the reduced TBN has the potential to enhance the transmission of light and reduce the consumption of nutrients, which should ultimately result in increased yield. Consequently, the TBN has emerged as a vital target trait in contemporary breeding programs that focus on compact maize varieties. In this study, QTL-seq technology and advanced population mapping were used to rapidly identify and dissect the major effects of the TBN on QTL. Advanced mapping populations (BC4F2 and BC4F3) were derived from the inbred lines 18-599 (8-11 TBN) and 3237 (0-1 TBN) through phenotypic recurrent selection. First, 13 genomic regions associated with the TBN were detected using quantitative trait locus (QTL)-seq and were located on chromosomes 2 and 5. Subsequently, validated loci within these regions were identified by QTL-seq. Three QTLs for TBN were identified in the BC4F2 populations by traditional QTL mapping, with each QTL explaining the phenotypic variation of 6.13-18.17%. In addition, for the major QTL (qTBN2-2 and qTBN5-1), residual heterozygous lines (RHLs) were developed from the BC4F2 population. These two major QTLs were verified in the RHLs by QTL mapping, with the phenotypic variation explained (PVE) of 21.57% and 30.75%, respectively. Near-isogenic lines (NILs) of qTBN2-2 and qTBN5-1 were constructed. There were significant differences between the NILs in TBN. These results will enhance our understanding of the genetic basis of TBN and provide a solid foundation for the fine-mapping of TBN.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01431-y.

Genetic mapping identified major main-effect and three co-localized quantitative trait loci controlling high iron and zinc content in groundnut

Malnutrition is a major challenge globally, and groundnut is a highly nutritious self-pollinated legume crop blessed with ample genomic resources, including the routine deployment of genomic-assisted breeding. This study aimed to identify genomic regions and candidate genes for high iron (Fe) and zinc (Zn) content, utilizing a biparental mapping population (ICGV 00440 × ICGV 06040;). Genetic mapping and quantitative trait locus (QTL) analysis (474 mapped single-nucleotide polymorphism loci; 1536.33 cM) using 2 seasons of phenotypic data together with genotypic data identified 5 major main-effect QTLs for Fe content. These QTLs exhibited log-of-odds (LOD) scores ranging from 6.5 to 7.4, explaining phenotypic variation (PVE) ranging from 22% (qFe-Ah01) to 30.0% (qFe-Ah14). Likewise, four major main effect QTLs were identified for Zn content, with LOD score ranging from 4.4 to 6.8 and PVE ranging from 21.8% (qZn-Ah01) to 32.8% (qZn-Ah08). Interestingly, three co-localized major and main effect QTLs (qFe-Ah01, qZn-Ah03, and qFe-Ah11) were identified for both Fe and Zn contents. These genomic regions harbored key candidate genes, including zinc/iron permease transporter, bZIP transcription factor, and vacuolar iron transporter which likely play pivotal roles in the accumulation of Fe and Zn contents in seeds. The findings of this study hold potential for fine mapping and diagnostic marker development for high Fe and Zn contents in groundnut.

Whole-genome sequencing based discovery of candidate genes and diagnostic markers for seed weight in groundnut

Seed weight in groundnut (Arachis hypogaea L.) has direct impact on yield as well as market price because of preference for bold seeds by consumers and industry, thereby making seed-size improvement as one of the most important objectives of groundnut breeding programs globally. Marker-based early generation selection can accelerate the process of breeding for developing large-seeded varieties. In this context, we deployed the quantitative trait locus-sequencing (QTL-seq) approach on a biparental mapping population (Chico × ICGV 02251) to identify candidate genes and develop markers for seed weight in groundnut. A total of 289.4-389.4 million reads sequencing data were generated from three libraries (ICGV 02251 and two extreme bulks) achieving 93.9-95.1% genome coverage and 8.34-9.29× average read depth. The analysis of sequencing data using QTL-seq pipeline identified five genomic regions (three on chromosome B06 and one each on chromosomes B08 and B09) for seed weight. Detailed analysis of above associated genomic regions detected 182 single-nucleotide polymorphisms (SNPs) in genic and intergenic regions, and 11 of these SNPs were nonsynonymous in the genomic regions of 10 candidate genes including Ulp proteases and BIG SEED locus genes. Kompetitive allele specific polymerase chain reaction (KASP) markers for 14 SNPs were developed, and four of these markers (snpAH0031, snpAH0033, snpAH0037, and snpAH0038) were successfully validated for deployment in breeding for large-seeded groundnut varieties.

The genus Arachis: an excellent resource for studies on differential gene expression for stress tolerance

Peanut Arachis hypogaea is a segmental allotetraploid in the section Arachis of the genus Arachis along with the Section Rhizomataceae. Section Arachis has several diploid species along with Arachis hypogaea and A. monticola. The section Rhizomataceae comprises polyploid species. Several species in the genus are highly tolerant to biotic and abiotic stresses and provide excellent sets of genotypes for studies on differential gene expression. Though there were several studies in this direction, more studies are needed to identify more and more gene combinations. Next generation RNA-seq based differential gene expression study is a powerful tool to identify the genes and regulatory pathways involved in stress tolerance. Transcriptomic and proteomic study of peanut plants under biotic stresses reveals a number of differentially expressed genes such as R genes (NBS-LRR, LRR-RLK, protein kinases, MAP kinases), pathogenesis related proteins (PR1, PR2, PR5, PR10) and defense related genes (defensin, F-box, glutathione S-transferase) that are the most consistently expressed genes throughout the studies reported so far. In most of the studies on biotic stress induction, the differentially expressed genes involved in the process with enriched pathways showed plant-pathogen interactions, phenylpropanoid biosynthesis, defense and signal transduction. Differential gene expression studies in response to abiotic stresses, reported the most commonly expressed genes are transcription factors (MYB, WRKY, NAC, bZIP, bHLH, AP2/ERF), LEA proteins, chitinase, aquaporins, F-box, cytochrome p450 and ROS scavenging enzymes. These differentially expressed genes are in enriched pathways of transcription regulation, starch and sucrose metabolism, signal transduction and biosynthesis of unsaturated fatty acids. These identified differentially expressed genes provide a better understanding of the resistance/tolerance mechanism, and the genes for manipulating biotic and abiotic stress tolerance in peanut and other crop plants. There are a number of differentially expressed genes during biotic and abiotic stresses were successfully characterized in peanut or model plants (tobacco or Arabidopsis) by genetic manipulation to develop stress tolerance plants, which have been detailed out in this review and more concerted studies are needed to identify more and more gene/gene combinations.

Simultaneously mapping loci related to two plant architecture traits by phenotypic recombination BSA/BSR in peanut (Arachis hypogaea L.)

KEY MESSAGE

We developed a new method phenotypic recombination BSA/BSR (PR-BSA/BSR), which could simultaneously identify the candidate genomic regions associated with two traits in a segregating population. Bulked segregant analysis sequencing (BSA-seq) has been widely used for identifying the genomic regions affecting a certain trait. In this study, we developed a modified BSA/bulked segregant RNA-sequencing (BSR-seq) method, which we named phenotypic recombination BSA/BSR (PR-BSA/BSR), to simultaneously identify candidate genomic regions associated with two traits in a segregating population. Lateral branch angle (LBA) and flower-branch pattern (FBP) are two important traits associated with the peanut plant architecture because they affect the planting density and light use efficiency. We generated an F₆ population (with two segregating traits) derived from a cross between the inbred lines Pingdu9616 (erect and sequential; ES-type) and Florunner (spreading and alternating; SA-type). The selection of bulks with extreme phenotypes was a key step in this study. Specifically, 30 individuals with recombinant phenotypes [i.e., spreading and sequential (SS-type) and erect and alternating (EA-type)] were selected to generate two bulks. The transcriptomes of individuals were sequenced and then the loci related to LBA and FBP were simultaneously detected via a ΔSNP-index strategy, which involved the direction of positive and negative peaks in the ∆SNP-index plot. The LBA-related locus was mapped to a 6.82 Mb region (101,743,223-108,564,267 bp) on chromosome 15, whereas the FBP-related locus was mapped to a 2.16 Mb region (117,682,534-119,846,824 bp) on chromosome 12. Furthermore, the marker-based classical QTL mapping method was used to analyze the PF-F₆ population, which confirmed our PR-BSA/BSR results. Therefore, the PR-BSA/BSR method produces accurate and reliable data.

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.

Identification of quantitative trait loci and development of diagnostic markers for growth habit traits in peanut (Arachis hypogaea L.)

KEY MESSAGE

QTLs for growth habit are identified on Arahy.15 and Arahy.06 in peanut, and diagnostic markers are developed and validated for further use in marker-assisted breeding. Peanut is a unique legume crop because its pods develop and mature underground. The pegs derive from flowers following pollination, then reach the ground and develop into pods in the soil. Pod number per plant is influenced by peanut growth habit (GH) that has been categorized into four types, including erect, bunch, spreading and prostrate. Restricting pod development at the plant base, as would be the case for peanut plants with upright lateral branches, would decrease pod yield. On the other hand, GH characterized by spreading lateral branches on the ground would facilitate pod formation on the nodes, thereby increasing yield potential. We describe herein an investigation into the GH traits of 521 peanut recombinant inbred lines grown in three distinct environments. Quantitative trait loci (QTLs) for GH were identified on linkage group (LG) 15 between 203.1 and 204.2 cM and on LG 16 from 139.1 to 139.3 cM. Analysis of resequencing data in the identified QTL regions revealed that single nucleotide polymorphism (SNP) or insertion and/or deletion (INDEL) at Arahy15.156854742, Arahy15.156931574, Arahy15.156976352 and Arahy06.111973258 may affect the functions of their respective candidate genes, Arahy.QV02Z8, Arahy.509QUQ, Arahy.ATH5WE and Arahy.SC7TJM. These SNPs and INDELs in relation to peanut GH were further developed for KASP genotyping and tested on a panel of 77 peanut accessions with distinct GH features. This study validates four diagnostic markers that may be used to distinguish erect/bunch peanuts from spreading/prostrate peanuts, thereby facilitating marker-assisted selection for GH traits in peanut breeding.

Fine mapping and causal gene identification of a novel QTL for early flowering by QTL-seq, Target-seq and RNA-seq in spring oilseed rape

A novel quantitative trait locus for early flowering in spring oilseed rape, BnaC08cqDTF, was mapped to an 86-kb region on chromosome C08, and its causal gene, CRY2, was uncovered. Days to flowering is a very important agronomic and adaptive trait of Brassica napus oilseed rape (AACC, 2n = 38). We previously identified BnaC08cqDTF as a novel candidate quantitative trait locus (QTL) for early flowering in spring oilseed rape. Here, we present fine mapping of the locus and a study of its causal gene. Initial mapping was performed by QTL sequencing of DNA pools of BC₃F₂ plants with extreme flowering times derived from crosses between the spring-type cv. No. 4512 (early flowering) and cv. No. 5246 (late flowering), along with fine mapping by target sequencing of the BC₃F₂ and BC₄F₂ populations. Fine mapping narrowed down BnaC08cqDTF to an 86-kb region on chromosome C08. The region harbored fifteen genes. After comparative analyses of the DNA sequences for mutation between A and C syntenic regions and detected by RNA-seq and qRT-PCR between the two parents, we found that BnaC08G0010400ZS harbors an A/G nonsynonymous mutation in exon 3. This single nucleotide polymorphism (SNP) haplotype was also correlated with early flowering in a 256 accession panel. BnaC08G0010400ZS is a homolog of the AT1G04400 gene (CRY2) in Arabidopsis. The analyses of transgenic Arabidopsis verified that BnaC08G0010400ZS is responsible for early flowering. Our results contribute to a better understanding of the genetic control mechanism of early flowering in spring Brassica napus and will promote the breeding for early mature varieties.

Marker-assisted introgression of wild chromosome segments conferring resistance to fungal foliar diseases into peanut (Arachis hypogaea L.)

INTRODUCTION

Fungal foliar diseases can severely affect the productivity of the peanut crop worldwide. Late leaf spot is the most frequent disease and a major problem of the crop in Brazil and many other tropical countries. Only partial resistance to fungal diseases has been found in cultivated peanut, but high resistances have been described on the secondary gene pool.

METHODS

To overcome the known compatibility barriers for the use of wild species in peanut breeding programs, we used an induced allotetraploid (Arachis stenosperma × A. magna)^4x, as a donor parent, in a successive backcrossing scheme with the high-yielding Brazilian cultivar IAC OL 4. We used microsatellite markers associated with late leaf spot and rust resistance for foreground selection and high-throughput SNP genotyping for background selection.

RESULTS

With these tools, we developed agronomically adapted lines with high cultivated genome recovery, high-yield potential, and wild chromosome segments from both A. stenosperma and A. magna conferring high resistance to late leaf spot and rust. These segments include the four previously identified as having QTLs (quantitative trait loci) for resistance to both diseases, which could be confirmed here, and at least four additional QTLs identified by using mapping populations on four generations.

DISCUSSION

The introgression germplasm developed here will extend the useful genetic diversity of the primary gene pool by providing novel wild resistance genes against these two destructive peanut diseases.

Genetic mapping identifies genomic regions and candidate genes for seed weight and shelling percentage in groundnut

Seed size is not only a yield-related trait but also an important measure to determine the commercial value of groundnut in the international market. For instance, small size is preferred in oil production, whereas large-sized seeds are preferred in confectioneries. In order to identify the genomic regions associated with 100-seed weight (HSW) and shelling percentage (SHP), the recombinant inbred line (RIL) population (Chico × ICGV 02251) of 352 individuals was phenotyped for three seasons and genotyped with an Axiom_Arachis array containing 58K SNPs. A genetic map with 4199 SNP loci was constructed, spanning a map distance of 2708.36 cM. QTL analysis identified six QTLs for SHP, with three consistent QTLs on chromosomes A05, A08, and B10. Similarly, for HSW, seven QTLs located on chromosomes A01, A02, A04, A10, B05, B06, and B09 were identified. BIG SEED locus and spermidine synthase candidate genes associated with seed weight were identified in the QTL region on chromosome B09. Laccase, fibre protein, lipid transfer protein, senescence-associated protein, and disease-resistant NBS-LRR proteins were identified in the QTL regions associated with shelling percentage. The associated markers for major-effect QTLs for both traits successfully distinguished between the small- and large-seeded RILs. QTLs identified for HSW and SHP can be used for developing potential selectable markers to improve the cultivars with desired seed size and shelling percentage to meet the demands of confectionery industries.

Genome-wide association mapping for LLS resistance in a MAGIC population of groundnut (Arachis hypogaea L.)

The identified 30 functional nucleotide polymorphisms or genic SNP markers would offer essential information for marker-assisted breeding in groundnut. A genome-wide association study (GWAS) on component traits of LLS resistance in an eight-way multiparent advance generation intercross (MAGIC) population of groundnut in the field and in a light chamber (controlled conditions) was performed via an Affymetrix 48 K single-nucleotide polymorphism (SNP) 'Axiom Arachis' array. Multiparental populations with high-density genotyping enable the detection of novel alleles. In total, five quantitative trait loci (QTLs) with marker - log10(p value) scores ranging from 4.25 to 13.77 for the incubation period (IP) and six QTLs with marker - log10(p value) scores ranging from 4.33 to 10.79 for the latent period (LP) were identified across the A- and B-subgenomes. A total of 62 markers‒trait associations (MTAs) were identified across the A- and B-subgenomes. Markers for LLS scores and the area under the disease progression curve (AUDPC) recorded for plants in the light chamber and under field conditions presented - log10 (p value) scores ranging from 4.22 to 27.30. The highest number of MTAs (six) was identified on chromosomes A05, B07 and B09. Out of a total of 73 MTAs, 37 and 36 MTAs were detected in subgenomes A and B, respectively. Taken together, these results suggest that both subgenomes have equal potential genomic regions contributing to LLS resistance. A total of 30 functional nucleotide polymorphisms or genic SNP markers were detected, among which eight genes were found to encode leucine-rich repeat (LRR) receptor-like protein kinases and putative disease resistance proteins. These important SNPs can be used in breeding programmes for the development of cultivars with improved disease resistance.

Marker assisted backcross to introgress late leaf spot and rust resistance in groundnut (Arachis hypogaea L.)

BACKGROUND

Groundnut is affected by a variety of abiotic and biotic stressors, including late leaf spot and rust, which cause significant economic loss. In this study, QTL for resistance to late leaf spot and rust from donor variety GPBD 4 were incorporated into a popular groundnut variety (ICGV 00350) through marker assisted backcross (MABC) breeding.

METHODS

Eight foreground SSR markers [AhXII (GM1009, GM1573 and Seq8D09) and AhXV (GM1536, GM2009, GM2079, GM2301 and IPAHM103)] linked with disease resistant QTLs were utilized in this study. A set of 217 SSR markers spanning the whole groundnut genome were employed for background analysis. Three backcrosses with recurrent parent and selfing were followed in the cross ICGV 00350 × GPBD 4. Background analysis was carried out in BC₃F₂; while, phenotypic confirmation for resistance was carried out in BC₃F₃ generation.

CONCLUSION

Five advanced backcross lines in BC₃F₂ were found, with more than 90% recurrent parent genome. The phenotyping of the eight ILs recorded disease scores ranging from 2.0 to 3.0 for LLS and from 1.0 to 3.0 for rust disease scores. All these lines had superior characteristics compared to the recurrent parent ICGV 00350 in terms of late leaf spot and rust resistance. The enhanced ILs will be evaluated further for commercial release.

Functional Bph14 from Rathu Heenati promotes resistance to BPH at the early seedling stage of rice (Oryza sativa L.) as revealed by QTL-seq

A QTL associated with BPH resistance at the early seedling stage was identified on chromosome 3. Functional Bph14 in Rathu Heenati was associated with BPH resistance at the early seedling stage. Brown planthopper (BPH; Nilaparvata lugens Stål) is considered the most important rice pest in many Asian countries. Several BPH resistance genes have previously been identified. However, there are few reports of genes specific for BPH resistance at the early seedling stage, a crucial stage for direct-seeding cultivation. In this study, we performed a QTL-seq analysis using two bulks (20 F₂ lines in each bulk) of the F₂ population (n = 300) derived from a cross of Rathu Heenati (RH) × HCS-1 to identify QTL/genes associated with BPH resistance at the early seedling stage. An important QTL was identified on chromosome 3 and Bph14 was identified as a potential candidate gene based on the differences in gene expression and sequence variation when compared with the two parents. All plants in the resistant bulks possessed the functional Bph14 from RH and all plants in the susceptible bulk and HCS-1 contained a large deletion (2703 bp) in Bph14. The functional Bph14 gene of RH appears to be important for BPH resistance at the early seedling stage of rice and could be used in conjunction with other BPH resistance genes in rice breeding programs that confer resistance to BPH at the early and later growth stages.

The double flower variant of yellowhorn is due to a LINE1 transposon-mediated insertion

As essential organs of reproduction in angiosperms, flowers, and the genetic mechanisms of their development have been well characterized in many plant species but not in the woody tree yellowhorn (Xanthoceras sorbifolium). Here, we focused on the double flower phenotype in yellowhorn, which has high ornamental value. We found a candidate C-class gene, AGAMOUS1 (XsAG1), through bovine serum albumin sequencing and genetics analysis with a Long Interpersed Nuclear Elements 1 (LINE1) transposable element fragment (Xsag1-LINE1-1) inserted into its second intron that caused a loss-of-C-function and therefore the double flower phenotype. In situ hybridization of XsAG1 and analysis of the expression levels of other ABC genes were used to identify differences between single- and double-flower development processes. These findings enrich our understanding of double flower formation in yellowhorn and provide evidence that transposon insertions into genes can reshape plant traits in forest trees.

Initiation of genomics-assisted breeding in Virginia-type peanuts through the generation of a de novo reference genome and informative markers

INTRODUCTION

Virginia-type peanut, Arachis hypogaea subsp. hypogaea, is the second largest market class of peanut cultivated in the United States. It is mainly used for large-seeded, in-shell products. Historically, Virginia-type peanut cultivars were developed through long-term recurrent phenotypic selection and wild species introgression projects. Contemporary genomic technologies represent a unique opportunity to revolutionize the traditional breeding pipeline. While there are genomic tools available for wild and cultivated peanuts, none are tailored specifically to applied Virginia-type cultivar development programs.

METHODS AND RESPECTIVE RESULTS

Here, the first Virginia-type peanut reference genome, "Bailey II", was assembled. It has improved contiguity and reduced instances of manual curation in chromosome arms. Whole-genome sequencing and marker discovery was conducted on 66 peanut lines which resulted in 1.15 million markers. The high marker resolution achieved allowed 34 unique wild species introgression blocks to be cataloged in the A. hypogaea genome, some of which are known to confer resistance to one or more pathogens. To enable marker-assisted selection of the blocks, 111 PCR Allele Competitive Extension assays were designed. Forty thousand high quality markers were selected from the full set that are suitable for mid-density genotyping for genomic selection. Genomic data from representative advanced Virginia-type peanut lines suggests this is an appropriate base population for genomic selection.

DISCUSSION

The findings and tools produced in this research will allow for rapid genetic gain in the Virginia-type peanut population. Genomics-assisted breeding will allow swift response to changing biotic and abiotic threats, and ultimately the development of superior cultivars for public use and consumption.

Whole genome resequencing identifies candidate genes and allelic diagnostic markers for resistance to Ralstonia solanacearum infection in cultivated peanut (Arachis hypogaea L.)

Bacterial wilt disease (BWD), caused by Ralstonia solanacearum is a major challenge for peanut production in China and significantly affects global peanut field productivity. It is imperative to identify genetic loci and putative genes controlling resistance to R. solanacearum (RRS). Therefore, a sequencing-based trait mapping approach termed "QTL-seq" was applied to a recombination inbred line population of 581 individuals from the cross of Yueyou 92 (resistant) and Xinhuixiaoli (susceptible). A total of 381,642 homozygous single nucleotide polymorphisms (SNPs) and 98,918 InDels were identified through whole genome resequencing of resistant and susceptible parents for RRS. Using QTL-seq analysis, a candidate genomic region comprising of 7.2 Mb (1.8-9.0 Mb) was identified on chromosome 12 which was found to be significantly associated with RRS based on combined Euclidean Distance (ED) and SNP-index methods. This candidate genomic region had 180 nonsynonymous SNPs and 14 InDels that affected 75 and 11 putative candidate genes, respectively. Finally, eight nucleotide binding site leucine rich repeat (NBS-LRR) putative resistant genes were identified as the important candidate genes with high confidence. Two diagnostic SNP markers were validated and revealed high phenotypic variation in the different resistant and susceptible RIL lines. These findings advocate the expediency of the QTL-seq approach for precise and rapid identification of candidate genomic regions, and the development of diagnostic markers that are applicable in breeding disease-resistant peanut varieties.

BSR and Full-Length Transcriptome Approaches Identified Candidate Genes for High Seed Ratio in Camellia vietnamensis

(1) Background: C. vietnamensis is very suitable for growth in the low hilly areas of southern subtropical regions. Under appropriate conditions, the oil yield of C. vietnamensis can reach 1125 kg/ha (the existing varieties can reach 750 kg/ha). Moreover, the fruit of C. vietnamensis is large and the pericarp is thick (>5 cm). Therefore, a high seed ratio has become the main target economic trait for the breeding of C. vietnamensis. (2) Methods: A half-sibling population of C. vietnamensis plants with a combination of high and low seed ratios was constructed by crossing a C. vietnamensis female parent. Bulked segregant RNA analysis and full-length transcriptome sequencing were performed to determine the molecular mechanisms underlying a high seed ratio. (3) Results: Seed ratio is a complex quantitative trait with a normal distribution, which is significantly associated with four other traits of fruit (seed weight, seed number, fruit diameter, and pericarp thickness). Two candidate regions related to high seed ratio (HSR) were predicted. One spanned 140.8−148.4 Mb of chromosome 2 and was associated with 97 seed-yield-related candidate genes ranging in length from 278 to 16,628 bp. The other spanned 35.3−37.3 Mb on chromosome 15 and was associated with 38 genes ranging in length from 221 to 16,928 bp. Using the full-length transcript as a template, a total of 115 candidate transcripts were obtained, and 78 transcripts were predicted to be functionally annotated. The DEGs from two set pairs of cDNA sequencing bulks were enriched to cytochrome p450 CYP76F14 (KOG0156; GO:0055114, HSR4, HSR7), the gibberellin phytohormone pathway (GO:0016787, HSR5), the calcium signaling pathway (GO:0005509, HSR6), the polyubiquitin-PPAR signaling pathway (GO:0005515, HSR2, HSR3), and several main transcription factors (bZIP transcription factor, HSR1) in C. vietnamensis.

Genetic dissection of fatty acid components in the Chinese peanut (Arachis hypogaea L.) mini-core collection under multi-environments

Peanut (Arachis hypogaea L.) is an important source of edible oil and protein for human nutrition. The quality of peanut seed oil is mainly determined by the composition of fatty acids, especially the contents of oleic acid and linoleic acid. Improving the composition of fatty acids in the seed oil is one of the main objectives for peanut breeding globally. To uncover the genetic basis of fatty acids and broaden the genetic variation in future peanut breeding programs, this study used genome-wide association studies (GWAS) to identify loci associated with target traits and developed diagnostic marker. The contents of eight fatty acid components of the Chinese peanut mini-core collection were measured under four environments. Using the phenotypic information and over one hundred thousand single nucleotide polymorphisms (SNPs), GWAS were conducted to investigate the genetics basis of fatty acids under multi-environments. Overall, 75 SNPs were identified significant trait associations with fatty acid components. Nineteen associations were repeatedly identified in multiple environments, and 13 loci were co-associated with two or three traits. Three stable major associated loci were identified, including two loci for oleic acid and linoleic acid on chromosome A09 [mean phenotypic variation explained (PVE): 38.5%, 10.35%] and one for stearic acid on B06 (mean PVE: 23%). According to functional annotations, 21 putative candidate genes related to fatty acid biosynthesis were found underlying the three associations. The allelic effect of SNP A09-114690064 showed that the base variation was highly correlated with the phenotypic variation of oleic acid and linoleic acid contents, and a cost-effective Kompetitive allele-Specific PCR (KASP) diagnostic marker was developed. Furthermore, the SNP A09-114690064 was found to change the cis-element CAAT (-) in the promoter of ahFAD2A to YACT (+), leading dozens of times higher expression level. The enhancer-like activity of ahFAD2A promoter was identified that was valuable for enriching the regulation mechanism of ahFAD2A. This study improved our understanding on the genetic architecture of fatty acid components in peanut, and the new effective diagnostic marker would be useful for marker-assisted selection of high-oleic peanut breeding.

Identification of Candidate Genes for Rind Color and Bloom Formation in Watermelon Fruits Based on a Quantitative Trait Locus-Seq

Watermelon fruit rind color (RC) and bloom formation (BF) affect product value and consumer preference. However, information on the candidate gene(s) for additional loci involved in dark green (DG) RC and the genetic control of BF and its major chemical components is lacking. Therefore, this study aimed to identify loci controlling RC and BF using QTL-seq of the F₂ population derived by crossing 'FD061129' with light-green rind and bloom and 'SIT55616RN' with DG rind and bloomless. Phenotypic evaluation of the F₁ and 219 F₂ plants indicated the genetic control of two complementary dominant loci, G₁ and G₂, for DG and a dominant locus, Bf, for BF. QTL-seq identified a genomic region on Chr.6 for G₁, Chr.8 for G₂, and Chr.1 for Bf. G₁ and G₂ helped determine RC with possible environmental effects. Chlorophyll a-b binding protein gene-based CAPS (RC-m5) at G₁ matched the highest with the RC phenotype. In the 1.4 cM Bf map interval, two additional gene-based CAPS markers were designed, and the CAPS for a nonsynonymous SNP in Cla97C01G020050, encoding a CSC1-like protein, cosegregated with the BF trait in 219 F₂ plants. Bloom powder showed a high Ca²⁺ concentration (16,358 mg·kg^-1), indicating that the CSC1-like protein gene is possibly responsible for BF. Our findings provide valuable information for marker-assisted selection for RC and BF and insights into the functional characterization of genes governing these watermelon-fruit-related traits.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Genetic and molecular analysis reveals that two major loci and their interaction confer clubroot resistance in canola introgressed from rutabaga

Clubroot disease caused by Plasmodiophora brassicae is one of the serious threats to canola (Brassica napus L. subsp. napus) production. The evolution of new pathotypes rendering available resistances ineffective compel the introgression of new resistance into canola and extend our understanding of the genetic and molecular basis of the resistance. In this paper, we report the genetic and molecular basis of clubroot resistance in canola, introgressed from a rutabaga (B. napus L. subsp. rapifera Metzg. 'Polycross'), by using a doubled-haploid (DH) mapping population. Whole-genome resequencing (WGRS)-based bulked segregant analysis followed by genetic mapping and expression analysis of the genes in resistant and susceptible DH lines at 7 and 14 d after inoculation were carried out. Following this approach, two major quantitative trait loci (QTL) located at 14.41-15.44 Mb of A03 and at 9.96-11.09 Mb of A08 chromosomes and their interaction was observed to confer resistance to pathotypes 3H, 3A, and 3D. Analysis of the genes from the two QTL regions suggested that decreased expression of sugar transporter genes (BnaA03g29290D and BnaA03g29310D) may play an important role in resistance conferred by the A03 QTL, while increased expression of the toll/interleukin-1 receptor (TIR)-nucleotide binding (NB)-leucine rich repeat (LRR) (TNL) genes (BnaA08g10100D, BnaA08g09220D, and BnaA08g10540D) could be the major determinant of the resistance conferred by the A08 QTL. Single-nucleotide polymorphism (SNP) allele-specific polymerase chain reaction (PCR)-based markers, which could be detected by agarose gel electrophoresis, were also developed from the two QTL regions for use in breeding including pyramiding of multiple clubroot resistance genes.

Harnessing the potential of bulk segregant analysis sequencing and its related approaches in crop breeding

Most plant traits are governed by polygenes including both major and minor genes. Linkage mapping and positional cloning have contributed greatly to mapping genomic loci controlling important traits in crop species. However, they are low-throughput, time-consuming, and have low resolution due to which their efficiency in crop breeding is reduced. In this regard, the bulk segregant analysis sequencing (BSA-seq) and its related approaches, viz., quantitative trait locus (QTL)-seq, bulk segregant RNA-Seq (BSR)-seq, and MutMap, have emerged as efficient methods to identify the genomic loci/QTLs controlling specific traits at high resolution, accuracy, reduced time span, and in a high-throughput manner. These approaches combine BSA with next-generation sequencing (NGS) and enable the rapid identification of genetic loci for qualitative and quantitative assessments. Many previous studies have shown the successful identification of the genetic loci for different plant traits using BSA-seq and its related approaches, as discussed in the text with details. However, the efficiency and accuracy of the BSA-seq depend upon factors like sequencing depth and coverage, which enhance the sequencing cost. Recently, the rapid reduction in the cost of NGS together with the expected cost reduction of third-generation sequencing in the future has further increased the accuracy and commercial applicability of these approaches in crop improvement programs. This review article provides an overview of BSA-seq and its related approaches in crop breeding together with their merits and challenges in trait mapping.

De novo genes in Arachis hypogaea cv. Tifrunner: systematic identification, molecular evolution, and potential contributions to cultivated peanut

De novo genes are derived from non-coding sequences, and they can play essential roles in organisms. Cultivated peanut (Arachis hypogaea) is a major oil and protein crop derived from a cross between Arachis duranensis and Arachis ipaensis. However, few de novo genes have been documented in Arachis. Here, we identified 381 de novo genes in A. hypogaea cv. Tifrunner based on comparison with five closely related Arachis species. There are distinct differences in gene expression patterns and gene structures between conserved and de novo genes. The identified de novo genes originated from ancestral sequence regions associated with metabolic and biosynthetic processes, and they were subsequently integrated into existing regulatory networks. De novo paralogs and homoeologs were identified in A. hypogaea cv. Tifrunner. De novo paralogs and homoeologs with conserved expression have mismatching cis-acting elements under normal growth conditions. De novo genes potentially have pluripotent functions in responses to biotic stresses as well as in growth and development based on quantitative trait locus data. This work provides a foundation for future research examining gene birth processes and gene function in Arachis and related taxa.

The GmSNAP11 Contributes to Resistance to Soybean Cyst Nematode Race 4 in Glycine max

Soybean cyst nematode (SCN) has devastating effects on soybean production, making it crucial to identify genes conferring SCN resistance. Here we employed next-generation sequencing-based bulked segregant analysis (BSA) to discover genomic regions, candidate genes, and diagnostic markers for resistance to SCN race 4 (SCN4) in soybean. Phenotypic analysis revealed highly significant differences among the reactions of 145 recombinant inbred lines (RILs) to SCN4. In combination with euclidean distance (ED) and Δsingle-nucleotide polymorphism (SNP)-index analyses, we identified a genomic region on Gm11 (designated as rhg1-paralog) associated with SCN4 resistance. Overexpression and RNA interference analyzes of the two candidate genes identified in this region (GmPLAC8 and GmSNAP11) revealed that only GmSNAP11 significantly contributes to SCN4 resistance. We developed a diagnostic marker for GmSNAP11. Using this marker, together with previously developed markers for SCN-resistant loci, rhg1 and Rhg4, we evaluated the relationship between genotypes and SCN4 resistance in 145 RILs and 30 soybean accessions. The results showed that all the SCN4-resistant lines harbored all the three loci, however, some lines harboring the three loci were still susceptible to SCN4. This suggests that these three loci are necessary for the resistance to SCN4, but they alone cannot confer full resistance. The GmSNAP11 and the diagnostic markers developed could be used in genomic-assisted breeding to develop soybean varieties with increased resistance to SCN4.

Development of candidate gene-based markers and map-based cloning of a dominant rust resistance gene in cultivated groundnut (Arachis hypogaea L.)

A dominant rust resistance gene, VG 9514-Rgene was isolated through map-based cloning. Sequence analysis revealed non-synonymous mutations in the TIR, NBS and LRR region of the R-protein. Candidate gene-based markers from these SNPs revealed complete co-segregation of the isolated VG 9514-Rgene with rust resistance in a RIL population and confirmed their map position in between FRS 72 and SSR_GO340445 markers in arahy03 chromosome. Blastp search of VG 9514-Rprotein detected Arahy.T6DCA5 with >80.0% identity that localized at 142,544,745.0.142,549,184 in arahy03 chromosome. K_a/K_s calculation revealed that VG 9514-Rgene had undergone positive selection compared to four homologous genes in the groundnut genome. Homology based structure modelling of this R-protein revealed a typical consensus three-dimensional folding of TIR-NBS-LRR protein. Non-synonymous mutations in susceptible version of R-protein were mapped and found E268Q mutation in hhGRExE motif, Y309F in RNBS-A motif and I579T in MHD motif of NB-ARC domain are probable candidates for loss of function.

AhNPR3 regulates the expression of WRKY and PR genes, and mediates the immune response of the peanut (Arachis hypogaea L.)

Systemic acquired resistance is an essential immune response that triggers a broad-spectrum disease resistance throughout the plant. In the present study, we identified a peanut lesion mimic mutant m14 derived from an ethyl methane sulfonate-mutagenized mutant pool of peanut cultivar "Yuanza9102." Brown lesions were observed in the leaves of an m14 mutant from seedling stage to maturity. Using MutMap together with bulked segregation RNA analysis approaches, a G-to-A point mutation was identified in the exon region of candidate gene Arahy.R60CUW, which is the homolog of AtNPR3 (Nonexpresser of PR genes) in Arabidopsis. This point mutation caused a transition from Gly to Arg within the C-terminal transactivation domain of AhNPR3A. The mutation of AhNPR3A showed no effect in the induction of PR genes when treated with salicylic acid. Instead, the mutation resulted in upregulation of WRKY genes and several PR genes, including pathogenesis-related thaumatin- and chitinase-encoding genes, which is consistent with the resistant phenotype of m14 to leaf spot disease. Further study on the AhNPR3A gene will provide valuable insights into understanding the molecular mechanism of systemic acquired resistance in peanut. Moreover, our results indicated that a combination of MutMap and bulked segregation RNA analysis is an effective method for identifying genes from peanut mutants.

BSA‑seq and genetic mapping reveals AhRt2 as a candidate gene responsible for red testa of peanut

The candidate recessive gene AhRt2 responsible for red testa of peanut was identified through combined BSA-seq and linkage mapping approaches. The testa color of peanuts (Arachis hypogaea L.) is an important trait, and those with red testa are particularly popular owing to the high-anthocyanin content. However, the identification of genes underlying the regulation of the red testa trait in peanut are rarely reported. In order to fine map red testa gene, two F_2:4 populations were constructed through the cross of YZ9102 (pink testa) with ZH12 (red testa) and ZH2 (red testa). Genetic analysis indicated that red testa was controlled by a single recessive gene named as AhRt2 (Red testa gene 2). Using BSA-seq approach, AhRt2 was preliminary identified on chromosome 12, which was further mapped to a 530-kb interval using 220 recombinant lines through linkage mapping. Furthermore, functional annotation, expression profiling, and the analyses of sequence variation confirmed that the anthocyanin reductase namely (Arahy.IK60LM) was the most likely candidate gene for AhRt2. It was found that a SNP in the third exon of AhRt2 altered the encoding amino acids, and was associated with red testa in peanut. In addition, a closely linked molecular marker linked with red testa trait in peanut was also developed for future studies. Our results provide valuable insight into the molecular mechanism underlying peanut testa color and present significant diagnostic marker resources for marker-assisted selected breeding in peanut.

Detection of a major QTL and development of KASP markers for seed weight by combining QTL-seq, QTL-mapping and RNA-seq in peanut

Combining QTL-seq, QTL-mapping and RNA-seq identified a major QTL and candidate genes, which contributed to the development of KASP markers and understanding of molecular mechanisms associated with seed weight in peanut. Seed weight, as an important component of seed yield, is a significant target of peanut breeding. However, relatively little is known about the quantitative trait loci (QTLs) and candidate genes associated with seed weight in peanut. In this study, three major QTLs on chromosomes A05, B02, and B06 were determined by applying the QTL-seq approach in a recombinant inbred line (RIL) population. Based on conventional QTL-mapping, these three QTL regions were successfully narrowed down through newly developed single nucleotide polymorphism (SNP) and simple sequence repeat markers. Among these three QTL regions, qSWB06.3 exhibited stable expression, contributing mainly to phenotypic variance across environments. Furthermore, differentially expressed genes (DEGs) were identified at the three seed developmental stages between the two parents of the RIL population. It was found that the DEGs were widely distributed in the ubiquitin-proteasome pathway, the serine/threonine-protein pathway, signal transduction of hormones and transcription factors. Notably, DEGs at the early stage were mostly involved in regulating cell division, whereas DEGs at the middle and late stages were primarily involved in cell expansion during seed development. The expression patterns of candidate genes related to seed weight in qSWB06.3 were investigated using quantitative real-time PCR. In addition, the allelic diversity of qSWB06.3 was investigated in peanut germplasm accessions. The marker Ah011475 has higher efficiency for discriminating accessions with different seed weights, and it would be useful as a diagnostic marker in marker-assisted breeding. This study provided insights into the genetic and molecular mechanisms of seed weight in peanut.

Bulk segregation analysis in the NGS era: a review of its teenage years

Bulk segregation analysis (BSA) utilizes a strategy of pooling individuals with extreme phenotypes to conduct economical and rapidly linked marker screening or quantitative trait locus (QTL) mapping. With the development of next-generation sequencing (NGS) technology in the past 10 years, BSA methods and technical systems have been gradually developed and improved. At the same time, the ever-decreasing costs of sequencing accelerate NGS-based BSA application in different species, including eukaryotic yeast, grain crops, economic crops, horticultural crops, trees, aquatic animals, and insects. This paper provides a landscape of BSA methods and reviews the BSA development process in the past decade, including the sequencing method for BSA, different populations, different mapping algorithms, associated region threshold determination, and factors affecting BSA mapping. Finally, we summarize related strategies in QTL fine mapping combining BSA.

Broadening the horizon of crop research: a decade of advancements in plant molecular genetics to divulge phenotype governing genes

Advancements in sequencing, genotyping, and computational technologies during the last decade (2011-2020) enabled new forward-genetic approaches, which subdue the impediments of precise gene mapping in varied crops. The modern crop improvement programs rely heavily on two major steps-trait-associated QTL/gene/marker's identification and molecular breeding. Thus, it is vital for basic and translational crop research to identify genomic regions that govern the phenotype of interest. Until the advent of next-generation sequencing, the forward-genetic techniques were laborious and time-consuming. Over the last 10 years, advancements in the area of genome assembly, genotyping, large-scale data analysis, and statistical algorithms have led faster identification of genomic variations regulating the complex agronomic traits and pathogen resistance. In this review, we describe the latest developments in genome sequencing and genotyping along with a comprehensive evaluation of the last 10-year headways in forward-genetic techniques that have shifted the focus of plant research from model plants to diverse crops. We have classified the available molecular genetic methods under bulk-segregant analysis-based (QTL-seq, GradedPool-Seq, QTG-Seq, Exome QTL-seq, and RapMap), target sequence enrichment-based (RenSeq, AgRenSeq, and TACCA), and mutation-based groups (MutMap, NIKS algorithm, MutRenSeq, MutChromSeq), alongside improvements in classical mapping and genome-wide association analyses. Newer methods for outcrossing, heterozygous, and polyploid plant genetics have also been discussed. The use of k-mers has enriched the nature of genetic variants which can be utilized to identify the phenotype-causing genes, independent of reference genomes. We envisage that the recent methods discussed herein will expand the repertoire of useful alleles and help in developing high-yielding and climate-resilient crops.

QTL-seq for the identification of candidate genes for days to flowering and leaf shape in pigeonpea

To identify genomic segments associated with days to flowering (DF) and leaf shape in pigeonpea, QTL-seq approach has been used in the present study. Genome-wide SNP profiling of extreme phenotypic bulks was conducted for both the traits from the segregating population (F₂) derived from the cross combination- ICP 5529 × ICP 11605. A total of 126.63 million paired-end (PE) whole-genome resequencing data were generated for five samples, including one parent ICP 5529 (obcordate leaf and late-flowering plant), early and late flowering pools (EF and LF) and obcordate and lanceolate leaf shape pools (OLF and LLS). The QTL-seq identified two significant genomic regions, one on CcLG03 (1.58 Mb region spanned from 19.22 to 20.80 Mb interval) for days to flowering (LF and EF pools) and another on CcLG08 (2.19 Mb region spanned from 6.69 to 8.88 Mb interval) for OLF and LLF pools, respectively. Analysis of genomic regions associated SNPs with days to flowering and leaf shape revealed 5 genic SNPs present in the unique regions. The identified genomic regions for days to flowering were also validated with the genotyping-by-sequencing based classical QTL mapping method. A comparative analysis of the identified seven genes associated with days to flowering on 12 Fabaceae genomes, showed synteny with 9 genomes. A total of 153 genes were identified through the synteny analysis ranging from 13 to 36. This study demonstrates the usefulness of QTL-seq approach in precise identification of candidate gene(s) for days to flowering and leaf shape which can be deployed for pigeonpea improvement.

QTL-seq approach was utilized for mapping of genomic regions/genes associated with days to flowering and leaf shape in pigeonpea. Analysis of genomic regions and associated SNPs with days to flowering and leaf shape revealed 1 and 4 non-synonymous SNPs, respectively. The study demonstrated sequencing-based trait mapping approach can accelerate trait mapping of the targeted traits.

Optimization of BSA-seq experiment for QTL mapping

Deep sequencing-based bulked segregant analysis (BSA-seq) has become a popular approach for quantitative trait loci (QTL) mapping in recent years. Effective statistical methods for BSA-seq have been developed, but how to design a suitable experiment for BSA-seq remains unclear. In this paper, we show in theory how the major experimental factors (including population size, pool proportion, pool balance, and generation) and the intrinsic factors of a QTL (including heritability and degree of dominance) affect the power of QTL detection and the precision of QTL mapping in BSA-seq. Increasing population size can improve the power and precision, depending on the QTL heritability. The best proportion of each pool in the population is around 0.25. So, 0.25 is generally applicable in BSA-seq. Small pool proportion can greatly reduce the power and precision. Imbalance of pool pair in size also causes decrease of the power and precision. Additive effect is more important than dominance effect for QTL mapping. Increasing the generation of filial population produced by selfing can significantly increase the power and precision, especially from F2 to F3. These findings enable researchers to optimize the experimental design for BSA-seq. A web-based program named BSA-seq Design Tool is available at http://124.71.74.135/BSA-seqDesignTool/ and https://github.com/huanglikun/BSA-seqDesignTool.

Combining QTL-seq and linkage mapping to uncover the genetic basis of single vs. paired spikelets in the advanced populations of two-ranked maize×teosinte

BACKGROUND

Teosinte ear bears single spikelet, whereas maize ear bears paired spikelets, doubling the number of grains in each cupulate during maize domestication. In the past 20 years, genetic analysis of single vs. paired spikelets (PEDS) has been stagnant. A better understanding of genetic basis of PEDS could help fine mapping of quantitative trait loci (QTL) and cloning of genes.

RESULTS

In this study, the advanced mapping populations (BC₃F₂ and BC₄F₂) of maize × teosinte were developed by phenotypic recurrent selection. Four genomic regions associated with PEDS were detected using QTL-seq, located on 194.64-299.52 Mb, 0-162.80 Mb, 12.82-97.17 Mb, and 125.06-157.01 Mb of chromosomes 1, 3, 6, and 8, respectively. Five QTL for PEDS were identified in the regions of QTL-seq using traditional QTL mapping. Each QTL explained 1.12-38.05% of the phenotypic variance (PVE); notably, QTL qPEDS3.1 with the average PVE of 35.29% was identified in all tests. Moreover, 14 epistatic QTL were detected, with the total PVE of 47.57-66.81% in each test. The QTL qPEDS3.1 overlapped with, or was close to, one locus of 7 epistatic QTL. Near-isogenic lines (NILs) of QTL qPEDS1.1, qPEDS3.1, qPEDS6.1, and qPEDS8.1 were constructed. All individuals of NIL-qPEDS6.1(MT1) and NIL-qPEDS8.1(MT1) showed paired spikelets (PEDS = 0), but the flowering time was 7 days shorter in the NIL-qPEDS8.1(MT1). The ratio of plants with PEDS > 0 was low (1/18 to 3/18) in the NIL-qPEDS1.1(MT1) and NIL-qPEDS3.1(MT1), maybe due to the epistatic effect.

CONCLUSION

Our results suggested that major QTL, minor QTL, epistasis and photoperiod were associated with the variation of PEDS, which help us better understand the genetic basis of PEDS and provide a genetic resource for fine mapping of QTL.

Bulk analysis by resequencing and RNA-seq identifies candidate genes for maintaining leaf water content under water deficit in maize

Drought is one of the main abiotic stresses adversely affecting maize growth and grain yield. Identifying drought tolerance-related genes and breeding varieties with enhanced tolerance are effective strategies for minimizing the effects of drought stress. In this study, the leaf relative water content (LRWC) was used for evaluating drought tolerance. QTL-seq analysis of 419 F₂ individuals from a cross between ZhengT22 (the drought-tolerant line with high LRWC) and ZhengA88 (the drought-sensitive line with low LRWC) revealed four LRWC-related QTLs (qLRWC2, qLRWC10a, qLRWC10b, and qLRWC10c) in maize seedlings under water deficit. Of these QTLs, qLRWC2 was located in a 2.03-Mb interval on chromosome 2, whereas qLRWC10a, qLRWC10b, and qLRWC10c were located in 2.85-, 3.99-, and 2.05-Mb intervals, respectively, on chromosome 10, and the 93 genes contained the variation loci locating in the four QTLs regions. To identify the candidate genes within the QTLs, an RNA-seq analysis was performed for the parents exposed to water deficit. Seven genes with effective variation loci showed significant difference in expression either in ZhengA88 or ZhengT22 in response to water deficit. Moreover, among the genes, ZmPrx64, ZmCIPK, HSP90, and ABCG34 have all been shown to be related to water stress in the previous studies. Thus, they are primary considered as the potential candidate genes controlling LRWC under water deficit at the seeding stage of maize in this study. These findings will help clarify the molecular basis of drought tolerance in maize seedlings and may be relevant for future functional analysis and for breeding drought-tolerant maize varieties.

Legacy genetics of Arachis cardenasii in the peanut crop shows the profound benefits of international seed exchange

The narrow genetics of most crops is a fundamental vulnerability to food security. This makes wild crop relatives a strategic resource of genetic diversity that can be used for crop improvement and adaptation to new agricultural challenges. Here, we uncover the contribution of one wild species accession, Arachis cardenasii GKP 10017, to the peanut crop (Arachis hypogaea) that was initiated by complex hybridizations in the 1960s and propagated by international seed exchange. However, until this study, the global scale of the dispersal of genetic contributions from this wild accession had been obscured by the multiple germplasm transfers, breeding cycles, and unrecorded genetic mixing between lineages that had occurred over the years. By genetic analysis and pedigree research, we identified A. cardenasii-enhanced, disease-resistant cultivars in Africa, Asia, Oceania, and the Americas. These cultivars provide widespread improved food security and environmental and economic benefits. This study emphasizes the importance of wild species and collaborative networks of international expertise for crop improvement. However, it also highlights the consequences of the implementation of a patchwork of restrictive national laws and sea changes in attitudes regarding germplasm that followed in the wake of the Convention on Biological Diversity. Today, the botanical collections and multiple seed exchanges which enable benefits such as those revealed by this study are drastically reduced. The research reported here underscores the vital importance of ready access to germplasm in ensuring long-term world food security.