Pod and Seed Trait QTL Identification To Assist Breeding for Peanut Market Preferences

Fine mapping and candidate gene analysis of major QTLs for number of seeds per pod in Arachis hypogaea L

BACKGROUND

Peanut (Arachis hypogaea L., 2n = 2x = 20) is an important industrial and oil crop that is widely grown in more than 100 countries. In recent years, breeders have focused on increasing the seed number per pod to improve their yield in addition to other breeding for other key components of yield, including the pod number, seeds per pod, and 100-seed weight.

RESULTS

In this study, a secondary population of 1,114 BC1F2 lines was derived from a cross between the parents R45 and JNH3. Two stable major-effect quantitative trait loci of qRMPA09.1 and qRMPA09.2 were detected simultaneously and mapped within chromosomal intervals of approximately 400 Kb and 600 Kb on chromosome A09. Additionally, combined whole-genome and RNA sequencing analyses showed the differential expression of the Arahy.04JNDX gene that belongs to a MYB transcription factor (TF) between the two parents. The AhMYB51 gene was also inferred to influence the number of seeds per pod in peanuts. An examination of the backcross lines L2/L4 showed that AhMYB51 increases the rate of multiple pods per plant (RMSP) primarily by affecting brassinosteroids in the flowers, while its overexpression promotes the length of siliques in Arabidopsis thaliana.

CONCLUSIONS

Our findings provide valuable insights for the cloning of favorable alleles for RMSP in peanuts. The qRMSPA09.1 and qRMSPA09.2 are two novel QTL associated with the RMSP trait, with AhMYB51 predicted as its candidate gene. Moreover, the closely linked polymorphic SNP markers for loci of two significant QTLs may be useful in accelerating marker-assisted breeding in peanuts.

High-resolution genetic and physical mapping reveals a peanut spotted wilt disease resistance locus, PSWDR-1, to Tomato spotted wilt virus (TSWV), within a recombination cold-spot on chromosome A01

BACKGROUND

Peanut (Arachis hypogaea L.) is a vital global crop, frequently threatened by both abiotic and biotic stresses. Among the most damaging biotic stresses is Tomato spotted wilt virus (TSWV), which causes peanut spotted wilt disease resulting in significant yield loss. Developing TSWV-resistant cultivars is crucial to new cultivar release. Previous studies have used a subset of the "S" recombinant inbred line (RIL) population derived from SunOleic 97R and NC94022 and identified quantitative trait loci (QTLs) for resistance to TSWV. These studies utilized different genotyping techniques and found large consistent genomic regions on chromosome A01. The objective of this study was to fine map the QTL and identify candidate genes using the entire population of 352 RILs and high-density, high-quality peanut SNP arrays.

RESULTS

We used both versions of the peanut SNP arrays with five years of disease ratings, and successfully mapped the long-sought peanut spotted wilt disease resistance locus, PSWDR-1. QTL analyses identified two major QTLs, explaining 41.43% and 43.69% of the phenotypic variance within 3.6 cM and 0.28 cM intervals using the peanut Axiom_Arachis-v1 and Axiom_Arachis-v2 SNP arrays, respectively, on chromosome A01. These QTLs corresponded to 295 kb and 235 kb physical intervals. The unique overlap region of these two QTLs was 488 kb. A comparison of the genetic linkage map with the reference genome revealed a 1.3 Mb recombination "cold spot" (11.325-12.646 Mb) with only two recombination events of RIL-S1 and RIL-S17, which displayed contrasting phenotypes. Sequencing of these two recombinants confirmed the cold spot with only five SNPs detected within this region.

CONCLUSIONS

This study successfully identified a peanut spotted wilt disease resistance locus, PSWDR-1, on chromosome A01 within a recombination "cold spot". The PSWDR-1 locus contains three candidate genes, a TIR-NBS-LRR gene (Arahy.1PK53M), a glutamate receptor-like gene (Arahy.RI1BYW), and an MLO-like protein (Arahy.FX71XI). These findings provide a foundation for future functional studies to validate the roles of these candidate genes in resistance and application in breeding TSWV-resistant peanut cultivars.

Integrated RNA-Seq and Metabolomics Analyses of Biological Processes and Metabolic Pathways Involved in Seed Development in Arachis hypogaea L

In peanut cultivation, fertility and seed development are essential for fruit quality and yield, while pod number per plant, seed number per pod, kernel weight, and seed size are indicators of peanut yield. In this study, metabolomic and RNA-seq analyses were conducted on the flowers and aerial pegs (aerpegs) of two peanut cultivars JNH3 (Jinonghei) and SLH (Silihong), respectively. Compared with SLH, JNH3 had 3840 up-regulated flower-specific differentially expressed genes (DEGs) and 5890 up-regulated aerpeg-specific DEGs. Compared with the JNH3 aerpegs, there were 4079 up-regulated variety-specific DEGs and 18 up-regulated differentially accumulated metabolites (DAMs) of JNH3 flowers, while there were 3732 up-regulated variety-specific DEGs and 48 up-regulated DAMs in SLH flowers. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that the DEGs of JNH3 were associated with pollen germination and phenylalanine metabolism in flower and aerpeg tissues, respectively. In contrast, the DEGs of SLH were associated with protein degradation, amino acid metabolism, and DNA repair. However, there were significant differences in the lipids and lipid-like molecules between JNH3 flowers and SLH flowers. This investigation provides candidate genes and an experimental basis for the further improvement of high-quality and high-yield peanut varieties.

Mapping QTLs for early leaf spot resistance and yield component traits using an interspecific AB-QTL population in peanut

Early leaf spot (ELS), caused by Passalora personata (syn. Cercospora arachidicola), is a highly damaging peanut disease worldwide. While there are limited sources of resistance in cultivated peanut cultivars, wild relatives carry alleles for strong resistance, making them a valuable strategic resource for peanut improvement. So far, only a few wild diploid species have been utilized to transfer resistant alleles to cultivars. To mitigate the risk of resistance breakdown by pathogens, it is important to diversify the sources of resistance when breeding for disease resistance. In this study, we created an AB-QTL population by crossing an induced allotetraploid (IpaCor1), which combines the genomes of the diploid species Arachis ipaënsis and A. correntina, with the susceptible cultivar Fleur11. A. correntina has been reported to possess strong resistance to leaf spot diseases. The AB-QTL population was genotyped with the Axiom-Arachis 48K SNPs and evaluated for ELS resistance under natural infestation over three years in Senegal. Marker/trait associations enabled the mapping of five QTLs for ELS resistance on chromosomes A02, A03, A08, B04, and B09. Except for the QTL on chromosome B09, the wild species contributed favorable alleles at all other QTLs. One genomic region on chromosome A02 contained several relevant QTLs, contributing to ELS resistance, earliness, and increased biomass yield, potentially allowing marker-assisted selection to introduce this region into elite cultivars. This study's findings have aided in diversifying the sources of resistance to ELS disease and other important agronomic traits, providing another compelling example of the value of peanut wild species in improving cultivated peanut.

Using cross-country datasets for association mapping in Arachis hypogaea L

Groundnut (Arachis hypogaea L.) is one of the most important climate-resilient oil crops in sub-Saharan Africa. There is a significant yield gap for groundnut in Africa because of poor soil fertility, low agricultural inputs, biotic and abiotic stresses. Cross-country evaluations of promising breeding lines can facilitate the varietal development process. The objective of our study was to characterize popular test environments in Uganda (Serere and Nakabango) and Malawi (Chitala and Chitedze) and identify genotypes with stable superior yields for potential future release. Phenotypic data were generated for 192 breeding lines for yield-related traits, while genotypic data were generated using skim-sequencing. We observed significant variation (p < 0.001; p < 0.01; p < 0.05) across genotypes for all yield-related traits: days to flowering (DTF), pod yield (PY), shelling percentage, 100-seed weight, and grain yield within and across locations. Nakabango, Chitedze, and Serere were clustered as one mega-environment with the top five most stable genotypes being ICGV-SM 01709, ICGV-SM 15575, ICGV-SM 90704, ICGV-SM 15576, and ICGV-SM 03710, all Virginia types. Population structure analysis clustered the genotypes in three distinct groups based on market classes. Eight and four marker-trait associations (MTAs) were recorded for DTF and PY, respectively. One of the MTAs for DTF was co-localized within an uncharacterized protein on chromosome 13, while another one (TRv2Chr.11_3476885) was consistent across the two countries. Future studies will need to further characterize the candidate genes as well as confirm the stability of superior genotypes across seasons before recommending them for release.

Genetic characterization and mapping of the shell-strength trait in peanut

BACKGROUND

Shell strength is an important trait in peanuts that impacts shell breakage and yield. Despite its significance, the genetic basis of shell strength in peanuts remains largely unknown, and the current methods for rating this trait are qualitative and subjective. This study aimed to investigate the genetics of shell strength using a segregating recombinant-inbred-line (RIL) population derived from the hard-shelled cultivar 'Hanoch' and the soft-shelled cultivar 'Harari'.

RESULTS

Initially, a quantitative method was developed using a texture analyzer, focusing on the proximal part of isolated shells with a P/5 punching probe. This method revealed significant differences between Hanoch and Harari. Shell strength was then measured in 235 RILs across two distinct environments, revealing a normal distribution with some RILs exhibiting shell strength values beyond those of the parental lines, indicating transgressive segregation. Analysis of variance indicated significant effects for the RILs, with no effects of block or year, and a broad-sense heritability estimate of 0.675, indicating a substantial genetic component. Using an existing genetic map, we identified three QTLs for shell strength, with one major QTL (qSSB02) explaining 18.7% of the phenotypic variation. The allelic status of qSSB02 corresponded significantly with cultivar designation for in-shell or shelled types over four decades of Israeli peanut breeding. Physical and compositional analyses revealed that Hanoch has a higher shell density than Harari, rather than any difference in shell thickness, and is associated with increased levels of lignin, cellulose, and crude fiber.

CONCLUSIONS

These findings provide valuable insights into the genetic and compositional factors that influence shell strength in peanut, laying a foundation for marker-assisted selection in breeding programs focused on improving pod hardness in peanuts.

Genome-Wide Association Analysis Identified Quantitative Trait Loci (QTLs) Underlying Drought-Related Traits in Cultivated Peanut (Arachis hypogaea L.)

Drought is a destructive abiotic stress that affects all critical stages of peanut growth such as emergence, flowering, pegging, and pod filling. The development of a drought-tolerant variety is a sustainable strategy for long-term peanut production. The U.S. mini-core peanut germplasm collection was evaluated for drought tolerance to the middle-season drought treatment phenotyping for pod weight, pod count, relative water content (RWC), specific leaf area (SLA), leaf dry matter content (LDMC), and drought rating. A genome-wide association study (GWAS) was performed to identify minor and major QTLs. A total of 144 QTLs were identified, including 18 significant QTLs in proximity to 317 candidate genes. Ten significant QTLs on linkage groups (LGs) A03, A05, A06, A07, A08, B04, B05, B06, B09, and B10 were associated with pod weight and pod count. RWC stages 1 and 2 were correlated with pod weight, pod count, and drought rating. Six significant QTLs on LGs A04, A07, B03, and B04 were associated with RWC stages 1 and 2. Drought rating was negatively correlated with pod yield and pod count and was associated with a significant QTL on LG A06. Many QTLs identified in this research are novel for the evaluated traits, with verification that the pod weight shared a significant QTL on chromosome B06 identified in other research. Identified SNP markers and the associated candidate genes provide a resource for molecular marker development. Verification of candidate genes surrounding significant QTLs will facilitate the application of marker-assisted peanut breeding for drought tolerance.

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.

Molecular tagging of seed size using MITE markers in an induced large seed mutant with higher cotyledon cell size in groundnut

A large seed mutant, TG 89 having a 76.7% increment in hundred kernel weight in comparison to its parent TG 26, was isolated from an electron beam-induced mutagenized population. Studies based on environmental scanning electron microscopy of both parent and mutant revealed that the mutant seed cotyledon had significantly bigger cell size than parent. A mapping population with 122 F2 plants derived from the mutant and a distant normal seed genotype (ICGV 15007) was utilized to map the QTL associated with higher HKW. Bulk segregant analysis revealed putative association of three markers with this mutant large seed trait. Further, genotyping of F2 individuals with polymorphic markers detected 14 linkage groups with a map distance of 1053 cM. QTL analysis revealed a significant additive major QTL for the mutant large seed trait on linkage group A05 explaining 12.7% phenotypic variation for the seed size. This QTL was located between flanking markers AhTE333 and AhTE810 having a map interval of 4.7 cM which corresponds to 90.65 to 107.24 Mbp in A05 chromosome, respectively. Within this genomic fragment, an ortholog of the BIG SEEDS 1 gene was found at 102,476,137 bp. Real-time PCR revealed down-regulation of this BIG SEEDS 1 gene in the mutant indicating a loss of function mutation giving rise to a large seed phenotype. This QTL was validated in 11 advanced breeding lines having large seed size from this mutant but with varied genetic backgrounds. This validation showcased a highly promising selection accuracy of 90.9% for the marker-assisted selection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03909-0.

QTL analysis of traits related to seed size and shape in sesame (Sesamum indicum L.)

Seed size and shape are important traits that determine seed yield in sesame. Understanding the genetic basis of seed size and shape is essential for improving the yield of sesame. In this study, F2 and BC1 populations were developed by crossing the Yuzhi 4 and Bengal small-seed (BS) lines for detecting the quantitative trait loci (QTLs) of traits related to seed size and shape. A total of 52 QTLs, including 13 in F2 and 39 in BC1 populations, for seed length (SL), seed width (SW), and length to width ratio (L/W) were identified, explaining phenotypic variations from 3.68 to 21.64%. Of these QTLs, nine stable major QTLs were identified in the two populations. Notably, three major QTLs qSL-LG3-2, qSW-LG3-2, and qSW-LG3-F2 that accounted for 4.94-16.34% of the phenotypic variations were co-localized in a 2.08 Mb interval on chromosome 1 (chr1) with 279 candidate genes. Three stable major QTLs qSL-LG6-2, qLW-LG6, and qLW-LG6-F2 that explained 8.14-33.74% of the phenotypic variations were co-localized in a 3.27 Mb region on chr9 with 398 candidate genes. In addition, the stable major QTL qSL-LG5 was co-localized with minor QTLs qLW-LG5-3 and qSW-LG5 to a 1.82 Mb region on chr3 with 195 candidate genes. Gene annotation, orthologous gene analysis, and sequence analysis indicated that three genes are likely involved in sesame seed development. These results obtained herein provide valuable in-formation for functional gene cloning and improving the seed yield of sesame.

PSW1, an LRR receptor kinase, regulates pod size in peanut

Pod size is a key agronomic trait that greatly determines peanut yield, the regulatory genes and molecular mechanisms that controlling peanut pod size are still unclear. Here, we used quantitative trait locus analysis to identify a peanut pod size regulator, POD SIZE/WEIGHT1 (PSW1), and characterized the associated gene and protein. PSW1 encoded leucine-rich repeat receptor-like kinase (LRR-RLK) and positively regulated pod stemness. Mechanistically, this allele harbouring a 12-bp insertion in the promoter and a point mutation in the coding region of PSW1 causing a serine-to-isoleucine (S618I) substitution substantially increased mRNA abundance and the binding affinity of PSW1 for BRASSINOSTEROID INSENSITIVE1-ASSOCIATED RECEPTOR KINASE 1 (BAK1). Notably, PSW1HapII (super-large pod allele of PSW1) expression led to up-regulation of a positive regulator of pod stemness PLETHORA 1 (PLT1), thereby resulting in larger pod size. Moreover, overexpression of PSW1HapII increased seed/fruit size in multiple plant species. Our work thus discovers a conserved function of PSW1 that controls pod size and provides a valuable genetic resource for breeding high-yield crops.

Identification of QTL for kernel weight and size and analysis of the pentatricopeptide repeat (PPR) gene family in cultivated peanut (Arachis hypogaea L.)

Peanut (Arachis hypogaea L.) is an important oilseed crop worldwide. Improving its yield is crucial for sustainable peanut production to meet increasing food and industrial requirements. Deciphering the genetic control underlying peanut kernel weight and size, which are essential components of peanut yield, would facilitate high-yield breeding. A high-density single nucleotide polymorphism (SNP)-based linkage map was constructed using a recombinant inbred lines (RIL) population derived from a cross between the variety Yuanza9102 and a germplasm accession wt09-0023. Kernel weight and size quantitative trait loci (QTLs) were co-localized to a 0.16 Mb interval on Arahy07 using inclusive composite interval mapping (ICIM). Analysis of SNP, and Insertion or Deletion (INDEL) markers in the QTL interval revealed a gene encoding a pentatricopeptide repeat (PPR) superfamily protein as a candidate closely linked with kernel weight and size in cultivated peanut. Examination of the PPR gene family indicated a high degree of collinearity of PPR genes between A. hypogaea and its diploid progenitors, Arachis duranensis and Arachis ipaensis. The candidate PPR gene, Arahy.JX1V6X, displayed a constitutive expression pattern in developing seeds. These findings lay a foundation for further fine mapping of QTLs related to kernel weight and size, as well as validation of candidate genes in cultivated peanut.

An Overview of Mapping Quantitative Trait Loci in Peanut (Arachis hypogaea L.)

Quantitative Trait Loci (QTL) mapping has been thoroughly used in peanut genetics and breeding in spite of the narrow genetic diversity and the segmental tetraploid nature of the cultivated species. QTL mapping is helpful for identifying the genomic regions that contribute to traits, for estimating the extent of variation and the genetic action (i.e., additive, dominant, or epistatic) underlying this variation, and for pinpointing genetic correlations between traits. The aim of this paper is to review the recently published studies on QTL mapping with a particular emphasis on mapping populations used as well as traits related to kernel quality. We found that several populations have been used for QTL mapping including interspecific populations developed from crosses between synthetic tetraploids and elite varieties. Those populations allowed the broadening of the genetic base of cultivated peanut and helped with the mapping of QTL and identifying beneficial wild alleles for economically important traits. Furthermore, only a few studies reported QTL related to kernel quality. The main quality traits for which QTL have been mapped include oil and protein content as well as fatty acid compositions. QTL for other agronomic traits have also been reported. Among the 1261 QTL reported in this review, and extracted from the most relevant studies on QTL mapping in peanut, 413 (~33%) were related to kernel quality showing the importance of quality in peanut genetics and breeding. Exploiting the QTL information could accelerate breeding to develop highly nutritious superior cultivars in the face of climate change.

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.

A first insight into the genetics of maturity trait in Runner × Virginia types peanut background

'Runner' and 'Virginia', the two main market types of Arachis hypogaea subspecies hypogaea, differ in several agricultural and industrial characteristics. One such trait is time to maturation (TTM), contributing to the specific environmental adaptability of each subspecies. However, little is known regarding TTM's genetic and molecular control in peanut in general, and particularly in the Runner/Virginia background. Here, a recombinant inbred line population, originating from a cross between an early-maturing Virginia and a late-maturing Runner type, was used to detect quantitative trait loci (QTL) for maturity. An Arachis SNP-array was used for genotyping, and a genetic map with 1425 SNP loci spanning 24 linkage groups was constructed. Six significant QTLs were identified for the maturity index (MI) trait on chromosomes A04, A08, B02 and B04. Two sets of stable QTLs in the same loci were identified, namely qMIA04a,b and qMIA08_2a,b with 11.5%, 8.1% and 7.3%, 8.2% of phenotypic variation explained respectively in two environments. Interestingly, one consistent QTL, qMIA04a,b, overlapped with the previously reported QTL in a Virginia × Virginia population having the same early-maturing parent ('Harari') in common. The information and materials generated here can promote informed targeting of peanut idiotypes by indirect marker-assisted selection.

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.

Identification of a major locus for flowering pattern sheds light on plant architecture diversification in cultivated peanut

A major gene controls flowering pattern in peanut, possibly encoding a TFL1-like. It was subjected to gain/loss events of a deletion and changes in mRNA expression levels, partly explaining the evolution of flowering pattern in Arachis. Flowering pattern (FP) is a major characteristic differentiating the two subspecies of cultivated peanut (Arachis hypogaea L.). Subsp. fastigiata possessing flowers on the mainstem (MSF) and a sequential FP, whereas subsp. hypogaea lacks MSF and exhibits an alternate FP. FP is considered the main contributor to plant adaptability, and evidence indicates that its diversification occurred during the several thousand years of domestication. However, the genetic mechanism that controls FP in peanut is unknown. We investigated the genetics of FP in a recombinant inbred population, derivatives of an A. hypogaea by A. fastigiata cross. Lines segregated 1:1 for FP, indicating a single gene effect. Using Axiom_Arachis2 SNP-array, FP was mapped to a small segment in chromosome B02, wherein a Terminal Flowering 1-like (AhTFL1) gene with a 1492 bp deletion was found in the fastigiata line, leading to a truncated protein. Remapping FP in the RIL population with the AhTFL1 indel as a marker increased the LOD score from 53.3 to 158.8 with no recombination in the RIL population. The same indel was found co-segregating with the phenotype in two independent EMS-mutagenized M2 families, suggesting a hotspot for gene conversion. Also, AhTFL1 was significantly less expressed in the fastigiata line compared to hypogaea and in flowering than non-flowering branches. Sequence analysis of the AhTFL1 in peanut world collections indicated significant conservation, supporting the putative role of AhTFL1 in peanut speciation during domestication and modern cultivation.

Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut

With an objective of identifying the genomic regions for productivity and quality traits in peanut, a recombinant inbred line (RIL) population developed from an elite variety, TMV 2 and its ethyl methane sulfonate (EMS)-derived mutant was phenotyped over six seasons and genotyped with genotyping-by-sequencing (GBS), Arachis hypogaea transposable element (AhTE) and simple sequence repeats (SSR) markers. The genetic map with 700 markers spanning 2,438.1 cM was employed for quantitative trait loci (QTL) analysis which identified a total of 47 main-effect QTLs for the productivity and oil quality traits with the phenotypic variance explained (PVE) of 10-52% over the seasons. A common QTL region (46.7-50.1 cM) on Ah02 was identified for the multiple traits, such as a number of pods per plant (NPPP), pod weight per plant (PWPP), shelling percentage (SP), and test weight (TW). Similarly, a QTL (7.1-18.0 cM) on Ah16 was identified for both SP and protein content (PC). Epistatic QTL (epiQTL) analysis revealed intra- and inter-chromosomal interactions for the main-effect QTLs and other genomic regions governing these productivity traits. The markers identified by a single marker analysis (SMA) mapped to the QTL regions for most of the traits. Among the five potential candidate genes identified for PC, SP and oil quality, two genes (Arahy.7A57YA and Arahy.CH9B83) were affected by AhMITE1 transposition, and three genes (Arahy.J5SZ1I, Arahy.MZJT69, and Arahy.X7PJ8H) involved functional single nucleotide polymorphisms (SNPs). With major and consistent effects, the genomic regions, candidate genes, and the associated markers identified in this study would provide an opportunity for gene cloning and genomics-assisted breeding for increasing the productivity and enhancing the quality of peanut.

Genetic mapping and QTL analysis for peanut smut resistance

BACKGROUND

Peanut smut is a disease caused by the fungus Thecaphora frezii Carranza & Lindquist to which most commercial cultivars in South America are highly susceptible. It is responsible for severely decreased yield and no effective chemical treatment is available to date. However, smut resistance has been identified in wild Arachis species and further transferred to peanut elite cultivars. To identify the genome regions conferring smut resistance within a tetraploid genetic background, this study evaluated a RIL population {susceptible Arachis hypogaea subsp. hypogaea (JS17304-7-B) × resistant synthetic amphidiploid (JS1806) [A. correntina (K 11905) × A. cardenasii (KSSc 36015)] × A. batizocoi (K 9484)^4×} segregating for the trait.

RESULTS

A SNP based genetic map arranged into 21 linkage groups belonging to the 20 peanut chromosomes was constructed with 1819 markers, spanning a genetic distance of 2531.81 cM. Two consistent quantitative trait loci (QTLs) were identified qSmIA08 and qSmIA02/B02, located on chromosome A08 and A02/B02, respectively. The QTL qSmIA08 at 15.20 cM/5.03 Mbp explained 17.53% of the phenotypic variance, while qSmIA02/B02 at 4.0 cM/3.56 Mbp explained 9.06% of the phenotypic variance. The combined genotypic effects of both QTLs reduced smut incidence by 57% and were stable over the 3 years of evaluation. The genome regions containing the QTLs are rich in genes encoding proteins involved in plant defense, providing new insights into the genetic architecture of peanut smut resistance.

CONCLUSIONS

A major QTL and a minor QTL identified in this study provide new insights into the genetic architecture of peanut smut resistance that may aid in breeding new varieties resistant to peanut smut.

Identification of consistent QTL for time to maturation in Virginia-type Peanut (Arachis hypogaea L.)

BACKGROUND

Time-to-maturation (TTM) is an important trait contributing to adaptability, yield and quality in peanut (Arachis hypogaea L). Virginia market-type peanut belongs to the late-maturing A. hypogaea subspecies with considerable variation in TTM within this market type. Consequently, planting and harvesting schedule of peanut cultivars, including Virginia market-type, need to be optimized to maximize yield and grade. Little is known regarding the genetic control of TTM in peanut due to the challenge of phenotyping and limited DNA polymorphism. Here, we investigated the genetic control of TTM within the Virginia market-type peanut using a SNP-based high-density genetic map. A recombinant inbred line (RIL) population, derived from a cross between two Virginia-type cultivars 'Hanoch' and 'Harari' with contrasting TTM (12-15 days on multi-years observations), was phenotyped in the field for 2 years following a randomized complete block design. TTM was estimated by maturity index (MI). Other agronomic traits like harvest index (HI), branching habit (BH) and shelling percentage (SP) were recorded as well.

RESULTS

MI was highly segregated in the population, with 13.3-70.9% and 28.4-80.2% in years 2018 and 2019. The constructed genetic map included 1833 SNP markers distributed on 24 linkage groups, covering a total map distance of 1773.5 cM corresponding to 20 chromosomes on the tetraploid peanut genome with 1.6 cM mean distance between the adjacent markers. Thirty QTL were identified for all measured traits. Among the four QTL regions for MI, two consistent QTL regions (qMIA04a,b and qMIB03a,b) were identified on chromosomes A04 (118680323-125,599,371; 6.9Mbp) and B03 (2839591-4,674,238; 1.8Mbp), with LOD values of 5.33-6.45 and 5-5.35 which explained phenotypic variation of 9.9-11.9% and 9.3-9.9%, respectively. QTL for HI were found to share the same loci as MI on chromosomes B03, B05, and B06, demonstrating the possible pleiotropic effect of HI on TTM. Significant but smaller effects on MI were detected for BH, pod yield and SP.

CONCLUSIONS

This study identified consistent QTL regions conditioning TTM for Virginia market-type peanut. The information and materials generated here can be used to further develop molecular markers to select peanut idiotypes suitable for diverse growth environments.

Fine-Mapping of a Wild Genomic Region Involved in Pod and Seed Size Reduction on Chromosome A07 in Peanut (Arachis hypogaea L.)

Fruit and seed size are important yield component traits that have been selected during crop domestication. In previous studies, Advanced Backcross Quantitative Trait Loci (AB-QTL) and Chromosome Segment Substitution Line (CSSL) populations were developed in peanut by crossing the cultivated variety Fleur11 and a synthetic wild allotetraploid (Arachis ipaensis × Arachis duranensis)^4x. In the AB-QTL population, a major QTL for pod and seed size was detected in a ~5 Mb interval in the proximal region of chromosome A07. In the CSSL population, the line 12CS_091, which carries the QTL region and that produces smaller pods and seeds than Fleur11, was identified. In this study, we used a two-step strategy to fine-map the seed size QTL region on chromosome A07. We developed new SSR and SNP markers, as well as near-isogenic lines (NILs) in the target QTL region. We first located the QTL in ~1 Mb region between two SSR markers, thanks to the genotyping of a large F₂ population of 2172 individuals and a single marker analysis approach. We then used nine new SNP markers evenly distributed in the refined QTL region to genotype 490 F₃ plants derived from 88 F₂, and we selected 10 NILs. The phenotyping of the NILs and marker/trait association allowed us to narrowing down the QTL region to a 168.37 kb chromosome segment, between the SNPs Aradu_A07_1148327 and Aradu_A07_1316694. This region contains 22 predicted genes. Among these genes, Aradu.DN3DB and Aradu.RLZ61, which encode a transcriptional regulator STERILE APETALA-like (SAP) and an F-box SNEEZY (SNE), respectively, were of particular interest. The function of these genes in regulating the variation of fruit and seed size is discussed. This study will contribute to a better knowledge of genes that have been targeted during peanut domestication.