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

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

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 QTLs associated with very-long chain fatty acid (VLCFA) content via linkage mapping and BSA-seq in peanut

KEY MESSAGE

Three major QTLs qA01, qB04.1 and qB05 for VLCFA content and their corresponding allele-specific markers will benefit peanut low VLCFA breeding, and a candidate gene Arahy.IF1JV3 was predicted. Peanut is a globally significant oilseed crop worldwide, and contains a high content (20%) of saturated fatty acid (SFA) in its seeds. As high level SFA intake in human dietary may increase the cardiovascular disease risk, reducing the SFA content in peanut is crucial for improving its nutritional quality. Half of the SFAs in peanut are very long-chain fatty acids (VLCFA), so reducing the VLCFA content is a feasible strategy to decrease the total SFA content. Luoaowan with extremely low VLCFA (4.80%) was crossed with Jihua16 (8.00%) to construct an F2:4 population. Three major QTLs including qA01, qB04.1 and qB05 for VLCFA content were detected with 4.43 ~ 14.32% phenotypic variation explained through linkage mapping. Meanwhile, three genomic regions on chromosomes B03, B04 and B05 were identified via BSA-seq approach. Two co-localized intervals on chromosomes B04 (100.10 ~ 103.97 Mb) and B05 (6.39 ~ 10.90 Mb) were identified. With markers developed based on SNP/InDel variations in qA01 between the two parents, the remaining interval was refined to 103.58 ~ 111.14 Mb. A candidate gene Arahy.IF1JV3 encoding a β-ketoacyl-CoA synthase was found in qA01, and its expression level in Luoaowan was significantly lower than that in Jihua16. Allele-specific markers targeting qA01, qB04.1 and qB05 were developed and validated in F4 population, and an elite line with high oleic, low VLCFA (5.05%) and low SFA (11.48%) contents was selected. This study initially revealed the genetic mechanism of VLCFA content, built a marker-assisted selection system for low VLCFA breeding, and provided an effective method to decrease the SFA content in peanut.

Identification of Putative Quantitative Trait Loci for Improved Seed Oil Quality in Peanuts

Improving seed oil quality in peanut (Arachis hypogaea) has long been an aim of breeding programs worldwide. The genetic resources to achieve this goal are limited. We used an advanced recombinant inbred line (RIL) population derived from JH5 × KX01-6 to explore quantitative trait loci (QTL) affecting peanut oil quality and their additive effects, epistatic effects, and QTL × environment interactions. Gas chromatography (GC) analysis suggested seven fatty acids components were obviously detected in both parents and analyzed in a follow-up QTL analysis. The major components, palmitic acid (C16:0), oleic acid (C18:1), and linoleic acid (C18:2), exhibited considerable phenotypic variation and fit the two major gene and minor gene mixed-inheritance model. Seventeen QTL explained 2.57-38.72% of the phenotypic variation in these major components, with LOD values of 4.12-37.56 in six environments, and thirty-five QTL explained 0.94-32.21% of the phenotypic variation, with LOD values of 5.99-150.38 in multiple environments. Sixteen of these QTL were detected in both individual and multiple environments. Among these, qFA_08_1 was a novel QTL with stable, valuable and major effect. Two other major-effect QTL, qFA_09_2 and qFA_19_3, share the same physical position as FAD2A and FAD2B, respectively. Eleven stable epistatic QTL involving nine loci explained 1.30-34.97% of the phenotypic variation, with epistatic effects ranging from 0.09 to 6.13. These QTL could be valuable for breeding varieties with improved oil quality.

Effects of Peanuts and Pistachios on Gut Microbiota and Metabolic Syndrome: A Review

There is growing evidence that the gut microbiota is associated with various aspects of human health, including immune system regulation, vitamin synthesis, short-chain fatty acid production, etc. Peanuts and pistachios are foods rich in protein, unsaturated fatty acids, vitamins, polyphenols, and other dietary components that have been shown to benefit the gut microbiota. Therefore, this review aims to describe the effects of consuming peanuts and pistachios on the gut microbiota and the potential role of these microbiota in human health. This review suggests that the consumption of peanuts or pistachios can demonstrate the potential to exert a beneficial effect on the gut microbiota by promoting the growth of beneficial gut bacteria that produce, for example, short-chain fatty acids that are beneficial for human health. In the case of peanuts, in particular, the possible modulation of the microbiota is associated with an improvement in the risk factors of metabolic syndrome and the inflammatory process triggered by a high-fat diet.

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 analysis and exploration of major effect QTLs underlying oil content in peanut

KEY MESSAGE

AhyHOF1, likely encoding a WRI1 transcription factor, plays critical roles in peanut oil synthesis. Although increasing the oil content of peanut to meet growing demand has long been a primary aim of breeding programs worldwide, the mining of genetic resources to achieve this objective has obviously lagged behind that of other oil crops. In the present study, we developed an advanced recombinant inbred line population containing 192 F9:11 families derived from parents JH5 and KX01-6. We then constructed a high-resolution genetic map covering 3,706.382 cM, with an average length of 185.32 cM per linkage group, using 2840 polymorphic SNPs. Two stable QTLs, qCOA08_1 and qCOA08_2 having the highest contributions to genetic variation (16.1% and 20.7%, respectively), were simultaneously detected in multiple environments and closely mapped within physical intervals of approximately 2.9 Mb and 1.7 Mb, respectively, on chromosome A08. In addition, combined analysis of whole-genome and transcriptome resequencing data uncovered a strong candidate gene encoding a WRI1 transcription factor and differentially expressed between the two parents. This gene, designated as High Oil Favorable gene 1 in Arachis hypogaea (AhyHOF1), was hypothesized to play roles in oil accumulation. Examination of near-inbred lines of #AhyHOF1/#Ahyhof1 provided further evidence that AhyHOF1 increases oil content, mainly by affecting the contents of several fatty acids. Taken together, our results provide valuable information for cloning the favorable allele for oil content in peanut. In addition, the closely linked polymorphic SNP markers within qCOA08_1 and qCOA08_2 loci may be useful for accelerating marker-assisted selection breeding of peanut.

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.

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

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

QTL identification, fine mapping, and marker development for breeding peanut (Arachis hypogaea L.) resistant to bacterial wilt

A major QTL, qBWA12, was fine mapped to a 216.68 kb physical region, and A12.4097252 was identified as a useful KASP marker for breeding peanut varieties resistant to bacterial wilt. Bacterial wilt, caused by Ralstonia solanacearum, is a major disease detrimental to peanut production in China. Breeding disease-resistant peanut varieties is the most economical and effective way to prevent the disease and yield loss. Fine mapping the QTLs for bacterial wilt resistance is critical for the marker-assisted breeding of disease-resistant varieties. A recombinant inbred population comprising 521 lines was used to construct a high-density genetic linkage map and to identify QTLs for bacterial wilt resistance following restriction-site-associated DNA sequencing. The genetic map, which included 5120 SNP markers, covered a length of 3179 cM with an average marker distance of 0.6 cM. Four QTLs for bacterial wilt resistance were mapped on four chromosomes. One major QTL, qBWA12, with LOD score of 32.8-66.0 and PVE of 31.2-44.8%, was stably detected in all four development stages investigated over the 3 trial years. Additionally, qBWA12 spanned a 2.7 cM region, corresponding to approximately 0.4 Mb and was fine mapped to a 216.7 kb region by applying KASP markers that were polymorphic between the two parents based on whole-genome resequencing data. In a large collection of breeding and germplasm lines, it was proved that KASP marker A12.4097252 can be applied for the marker-assisted breeding to develop peanut varieties resistant to bacterial wilt. Of the 19 candidate genes in the region covered by qBWA12, nine NBS-LRR genes should be further investigated regarding their potential contribution to the resistance of peanut against bacterial wilt.

Genome-wide approaches delineate the additive, epistatic, and pleiotropic nature of variants controlling fatty acid composition in peanut (Arachis hypogaea L.)

The fatty acid composition of seed oil is a major determinant of the flavor, shelf-life, and nutritional quality of peanuts. Major QTLs controlling high oil content, high oleic content, and low linoleic content have been characterized in several seed oil crop species. Here, we employ genome-wide association approaches on a recently genotyped collection of 787 plant introduction accessions in the USDA peanut core collection, plus selected improved cultivars, to discover markers associated with the natural variation in fatty acid composition, and to explain the genetic control of fatty acid composition in seed oils. Overall, 251 single nucleotide polymorphisms (SNPs) had significant trait associations with the measured fatty acid components. Twelve SNPs were associated with two or three different traits. Of these loci with apparent pleiotropic effects, 10 were associated with both oleic (C18:1) and linoleic acid (C18:2) content at different positions in the genome. In all 10 cases, the favorable allele had an opposite effect-increasing and lowering the concentration, respectively, of oleic and linoleic acid. The other traits with pleiotropic variant control were palmitic (C16:0), behenic (C22:0), lignoceric (C24:0), gadoleic (C20:1), total saturated, and total unsaturated fatty acid content. One hundred (100) of the significantly associated SNPs were located within 1000 kbp of 55 genes with fatty acid biosynthesis functional annotations. These genes encoded, among others: ACCase carboxyl transferase subunits, and several fatty acid synthase II enzymes. With the exception of gadoleic (C20:1) and lignoceric (C24:0) acid content, which occur at relatively low abundance in cultivated peanuts, all traits had significant SNP interactions exceeding a stringent Bonferroni threshold (α = 1%). We detected 7682 pairwise SNP interactions affecting the relative abundance of fatty acid components in the seed oil. Of these, 627 SNP pairs had at least one SNP within 1000 kbp of a gene with fatty acid biosynthesis functional annotation. We evaluated 168 candidate genes underlying these SNP interactions. Functional enrichment and protein-to-protein interactions supported significant interactions (P-value < 1.0E-16) among the genes evaluated. These results show the complex nature of the biology and genes underlying the variation in seed oil fatty acid composition and contribute to an improved genotype-to-phenotype map for fatty acid variation in peanut seed oil.

Metabolomic Markers of Southern Dietary Patterns in the Jackson Heart Study

SCOPE

New biomarkers are needed that are representative of dietary intake.

METHODS AND RESULTS

We assess metabolites associated with Southern dietary patterns in 1401 Jackson Heart Study participants. Three dietary patterns are empirically derived using principal component analysis: meat and fast food, fish and vegetables, and starchy foods. We randomly select two subsets of the study population: two-third sample for discovery (n = 934) and one-third sample for replication (n = 467). Among the 327 metabolites analyzed, 14 are significantly associated with the meat and fast food dietary pattern, four are significantly associated with the fish and vegetables dietary pattern, and none are associated with the starchy foods dietary pattern in the discovery sample. In the replication sample, nine remain associated with the meat and fast food dietary pattern [indole-3-propanoic acid, C24:0 lysophosphatidylcholine (LPC), N-methyl proline, proline betaine, C34:2 phosphatidylethanolamine (PE) plasmalogen, C36:5 PE plasmalogen, C38:5 PE plasmalogen, cotinine, hydroxyproline] and three remain associated with the fish and vegetables dietary pattern [1,7-dimethyluric acid, C22:6 lysophosphatidylethanolamine, docosahexaenoic acid (DHA)].

CONCLUSION

Twelve metabolites are discovered and replicated in association with dietary patterns detected in a Southern U.S. African-American population, which could be useful as biomarkers of Southern dietary patterns.

Enhancing the Nutritional Quality of Major Food Crops Through Conventional and Genomics-Assisted Breeding

Nutritional stress is making over two billion world population malnourished. Either our commercially cultivated varieties of cereals, pulses, and oilseed crops are deficient in essential nutrients or the soils in which these crops grow are becoming devoid of minerals. Unfortunately, our major food crops are poor sources of micronutrients required for normal human growth. To overcome the problem of nutritional deficiency, greater emphasis should be laid on the identification of genes/quantitative trait loci (QTLs) pertaining to essential nutrients and their successful deployment in elite breeding lines through marker-assisted breeding. The manuscript deals with information on identified QTLs for protein content, vitamins, macronutrients, micro-nutrients, minerals, oil content, and essential amino acids in major food crops. These QTLs can be utilized in the development of nutrient-rich crop varieties. Genome editing technologies that can rapidly modify genomes in a precise way and will directly enrich the nutritional status of elite varieties could hold a bright future to address the challenge of malnutrition.

Combining High Oleic Acid Trait and Resistance to Late Leaf Spot and Rust Diseases in Groundnut (Arachis hypogaea L.)

High oleic trait, resistance to rust and late leaf spot (LLS) are important breeding objectives in groundnut. Rust and LLS cause significant economic loss, and high oleic trait is an industry preferred trait that enhances economic returns. This study reports marker-assisted selection to introgress high oleic content, resistance to LLS and rust into Kadiri 6 (K 6), a popular cultivar. The alleles for target traits were selected using linked allele-specific, simple sequence repeats and single nucleotide polymorphic markers. The F₁s (384), intercrossed F₁s (441), BC₁F₁s (380), BC₁F₂s (195), and BC₁F₃s (343) were genotyped to obtain desired allelic combination. Sixteen plants were identified with homozygous high oleic, LLS and rust resistance alleles in BC₁F₂, which were advanced to BC₁F₃ and evaluated for disease resistance, yield governing and nutritional quality traits. Phenotyping with Near-Infrared Reflectance Spectroscopy identified three lines (BC₁F₃-76, BC₁F₃-278, and BC₁F₃-296) with >80% oleic acid. The identified lines exhibit high levels of resistance to LLS and rust diseases (score of 3.0-4.0) with preferred pod and kernel features. The selected lines are under yield testing trials in multi-locations for release and commercialization. The lines reported here demonstrated combining high oleic trait with resistance to LLS and rust diseases.

High-resolution mapping of a major and consensus quantitative trait locus for oil content to a ~ 0.8-Mb region on chromosome A08 in peanut (Arachis hypogaea L.)

KEY MESSAGE: ddRAD-seq-based high-density genetic map comprising 2595 loci identified a major and consensus QTL with a linked marker in a 0.8-Mb physical interval for oil content in peanut. Enhancing oil content is an important breeding objective in peanut. High-resolution mapping of quantitative trait loci (QTLs) with linked markers could facilitate marker-assisted selection in breeding for target traits. In the present study, a recombined inbred line population (Xuhua 13 × Zhonghua 6) was used to construct a genetic map based on double-digest restriction-site-associated DNA sequencing (ddRAD-seq). The resulting high-density genetic map contained 2595 loci, and spanned a length of 2465.62 cM, with an average distance of 0.95 cM/locus. Seven QTLs for oil content were identified on five linkage groups, including the major and stable QTL qOCA08.1 on chromosome A08 with 10.14-27.19% phenotypic variation explained. The physical interval of qOCA08.1 was further delimited to a ~ 0.8-Mb genomic region where two genes affecting oil synthesis had been annotated. The marker SNPOCA08 was developed targeting the SNP loci associated with oil content and validated in peanut cultivars with diverse oil contents. The major and stable QTL identified in the present study could be further dissected for gene discovery. Furthermore, the tightly linked marker for oil content would be useful in marker-assisted breeding in peanut.

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

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

A novel quantitative trait locus on chromosome A9 controlling oleic acid content in Brassica napus

One of the most important goals in the breeding of oilseed crops, including Brassica napus, is to improve the quality of edible vegetable oil, which is mainly determined by the seed fatty acid composition, particularly the C18:1 content. Previous studies have indicated that the C18:1 content is a polygenic trait, and no stable quantitative trait loci (QTLs) except for FAD2 have been reported. By performing a GWAS using 375 low erucic acid B. napus accessions genotyped with the Brassica 60K SNP array and constructing a high-density SNP-based genetic map of a 150 DH population, we identified a novel QTL on the A9 chromosome. The novel locus could explain 11.25%, 5.72% and 6.29% of phenotypic variation during three consecutive seasons and increased the C18:1 content by approximately 3%-5%. By fine mapping and gene expression analysis, we found three potential candidate genes and verified the fatty acids in a homologous gene mutant of Arabidopsis. A metal ion-binding protein was found to be the most likely candidate gene in the region. Thus, the C18:1 content can be further increased to about 80% with this novel locus together with FAD2 mutant allele without compromise of agronomic performance. A closely linked marker, BnA129, for this novel QTL (OLEA9) was developed so that we can effectively identify materials with high C18:1 content at an early growth stage by marker-assisted selection. Our results may also provide new insight for understanding the complex genetic mechanism of fatty acid metabolism.

Identification of Climate and Genetic Factors That Control Fat Content and Fatty Acid Composition of Theobroma cacao L. Beans

The main ingredients of chocolate are usually cocoa powder, cocoa butter, and sugar. Both the powder and the butter are extracted from the beans of the cacao tree (Theobroma cacao L.). The cocoa butter represents the fat in the beans and possesses a unique fatty acid profile that results in chocolate's characteristic texture and mouthfeel. Here, we used a linkage mapping population and phenotypic data of 3,292 samples from 420 progeny which led to the identification of 27 quantitative trait loci (QTLs) for fatty acid composition and six QTLs for fat content. Progeny showed extensive variation in fat levels and composition, with the level of palmitic acid negatively correlated to the sum of stearic acid, oleic acid, and linoleic acid. A major QTL explaining 24% of the relative level of palmitic acid was mapped to the distal end of chromosome 4, and those higher levels of palmitic acid were associated with the presence of a haplotype from the "TSH 1188" parent in the progeny. Within this region of chromosome 4 is the Thecc1EG017405 gene, an orthologue and isoform of the stearoyl-acyl carrier protein (ACP) desaturase (SAD) gene in plants, which is involved in fatty acid biosynthesis. Besides allelic differences, we also show that climate factors can change the fatty acid composition in the beans, including a significant positive correlation between higher temperatures and the higher level of palmitic acid. Moreover, we found a significant pollen donor effect from the variety "SIAL 70" which was associated with decreased palmitic acid levels.

Mapping and Validating QTL for Fatty Acid Compositions and Growth Traits in Asian Seabass

Asian seabass is an important food fish species. While improving growth, increasing the nutritional value is important, omega-3 fatty acids are indispensable to human health. Identifying and validating DNA markers associated with traits is the first step towards marker-assisted selection (MAS). We quantified 13 different fatty acids and three growth traits in 213 F₂ Asian seabass from a family at the age 270 days post hatch, and screened QTL for these traits. The content of total fatty acids in 100 g flesh was 2.57 ± 0.80 g, while the proportions of docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) were 16.96 ± 2.20% and 5.42 ± 0.90%, respectively. A linkage map with 2424 SNPs was constructed and used for QTL mapping. For fatty acid compositions, 14 significant QTL were identified on three linkage groups (LG5, LG11 and LG14), with phenotypic variance explained (PVE) from 12.8 to 24.6%. Thirty-nine suggestive QTL were detected on 16 LGs. Two significant QTL for EPA were identified on LG5 and LG14, with PVE of 15.2% and 15.1%, respectively. No significant QTL was identified for DHA. For growth traits, six significant and 13 suggestive QTL were identified on two and seven LGs, respectively. Only a few significant QTL for fatty acids overlapped with previously mapped QTL for these traits, suggesting that most QTL detected in a family are family-specific and could only be used in MAS in the family per se. To facilitate population-wide molecular breeding, more powerful methods (e.g. GWAS) should be used to identify SNPs for genomic selection.

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

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

Development of high oleic peanut lines through marker-assisted introgression of mutant ahFAD2 alleles and its fatty acid profiles under open-field and controlled conditions

Peanut is one of the most important oilseed crops grown worldwide. In this study, the mutant ahFAD2 alleles conferring high oleic (HO) content are introgressed into an elite Indian cultivar GPBD4 which is also resistant to the foliar fungal diseases like rust and late leaf spot (LLS). The allele-specific PCR (AS-PCR) and cleaved amplified polymorphic sequences (CAPS) assays were used for the marker-assisted backcross (MABC) approach and 64 HO introgression lines (ILs) were generated. These ILs were tested for the FA compositions under the glasshouse and field conditions. The oleic acid and linoleic acid contents in the ILs were recorded to be between 68.94-82.33% and 1.74-10.87%, respectively, under glasshouse and 67.04-81.71% and 2.00-15.66%, respectively, under field conditions. The increase in the oleic acid content of the ILs over its recurrent parent (RP) was recorded to the tune of 28.78-53.80% and 33.70-62.96% under glasshouse and field conditions, respectively, indicating the stable expression of ahFAD2B gene in two different environments. On the contrary, linoleic acid showed 56.47-93.03% and 40.02-92.34% reduction in the ILs over its RP under glasshouse and field conditions, respectively. These ILs with a healthy FA profile can meet not only the nutritional requirements of a health-conscious society but also the industrial demands for better shelf life of oil and its products.

The genome of cultivated peanut provides insight into legume karyotypes, polyploid evolution and crop domestication

High oil and protein content make tetraploid peanut a leading oil and food legume. Here we report a high-quality peanut genome sequence, comprising 2.54 Gb with 20 pseudomolecules and 83,709 protein-coding gene models. We characterize gene functional groups implicated in seed size evolution, seed oil content, disease resistance and symbiotic nitrogen fixation. The peanut B subgenome has more genes and general expression dominance, temporally associated with long-terminal-repeat expansion in the A subgenome that also raises questions about the A-genome progenitor. The polyploid genome provided insights into the evolution of Arachis hypogaea and other legume chromosomes. Resequencing of 52 accessions suggests that independent domestications formed peanut ecotypes. Whereas 0.42-0.47 million years ago (Ma) polyploidy constrained genetic variation, the peanut genome sequence aids mapping and candidate-gene discovery for traits such as seed size and color, foliar disease resistance and others, also providing a cornerstone for functional genomics and peanut improvement.

Genetic imprints of domestication for disease resistance, oil quality, and yield component traits in groundnut (Arachis hypogaea L.)

Ploidy difference between wild Arachis species and cultivated genotypes hinder transfer of useful alleles for agronomically important traits. To overcome this genetic barrier, two synthetic tetraploids, viz., ISATGR 1212 (A. duranensis ICG 8123 × A. ipaensis ICG 8206) and ISATGR 265-5A (A. kempff-mercadoi ICG 8164 × A. hoehnei ICG 8190), were used to generate two advanced backcross (AB) populations. The AB-populations, namely, AB-pop1 (ICGV 91114 × ISATGR 1212) and AB-pop2, (ICGV 87846 × ISATGR 265-5A) were genotyped with DArT and SSR markers. Genetic maps were constructed for AB-pop1 and AB-pop2 populations with 258 loci (1415.7 cM map length and map density of 5.5 cM/loci) and 1043 loci (1500.8 cM map length with map density of 1.4 cM/loci), respectively. Genetic analysis identified large number of wild segments in the population and provided a good source of diversity in these populations. Phenotyping of these two populations identified several introgression lines with good agronomic, oil quality, and disease resistance traits. Quantitative trait locus (QTL) analysis showed that the wild genomic segments contributed favourable alleles for foliar disease resistance while cultivated genomic segments mostly contributed favourable alleles for oil quality and yield component traits. These populations, after achieving higher stability, will be useful resource for genetic mapping and QTL discovery for wild species segments in addition to using population progenies in breeding program for diversifying the gene pool of cultivated groundnut.

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

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

Molecular Mapping of Oil Content and Fatty Acids Using Dense Genetic Maps in Groundnut (Arachis hypogaea L.)

Enhancing seed oil content with desirable fatty acid composition is one of the most important objectives of groundnut breeding programs globally. Genomics-assisted breeding facilitates combining multiple traits faster, however, requires linked markers. In this context, we have developed two different F₂ mapping populations, one for oil content (OC-population, ICGV 07368 × ICGV 06420) and another for fatty acid composition (FA-population, ICGV 06420 × SunOleic 95R). These two populations were phenotyped for respective traits and genotyped using Diversity Array Technology (DArT) and DArTseq genotyping platforms. Two genetic maps were developed with 854 (OC-population) and 1,435 (FA-population) marker loci with total map distance of 3,526 and 1,869 cM, respectively. Quantitative trait locus (QTL) analysis using genotyping and phenotyping data identified eight QTLs for oil content including two major QTLs, qOc-A10 and qOc-A02, with 22.11 and 10.37% phenotypic variance explained (PVE), respectively. For seven different fatty acids, a total of 21 QTLs with 7.6-78.6% PVE were identified and 20 of these QTLs were of major effect. Two mutant alleles, ahFAD2B and ahFAD2A, also had 18.44 and 10.78% PVE for palmitic acid, in addition to oleic (33.8 and 17.4% PVE) and linoleic (41.0 and 19.5% PVE) acids. Furthermore, four QTL clusters harboring more than three QTLs for fatty acids were identified on the three LGs. The QTLs identified in this study could be further dissected for candidate gene discovery and development of diagnostic markers for breeding improved groundnut varieties with high oil content and desirable oil quality.

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

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

Quantitative Trait Locus Analysis of Late Leaf Spot Resistance and Plant-Type-Related Traits in Cultivated Peanut (Arachis hypogaea L.) under Multi-Environments

Late leaf spot (LLS) is one of the most serious foliar diseases affecting peanut worldwide leading to huge yield loss. To understand the genetic basis of LLS and assist breeding in the future, we conducted quantitative trait locus (QTL) analysis for LLS and three plant-type-related traits including height of main stem (HMS), length of the longest branch (LLB) and total number of branches (TNB). Significant negative correlations were observed between LLS and the plant-type-related traits in multi-environments of a RIL population from the cross Zhonghua 5 and ICGV 86699. A total of 20 QTLs were identified for LLS, of which two QTLs were identified in multi-environments and six QTLs with phenotypic variation explained (PVE) more than 10%. Ten, seven, fifteen QTLs were identified for HMS, LLB and TNB, respectively. Of these, one, one, two consensus QTLs and three, two, three major QTLs were detected for HMS, LLB and TNB, respectively. Of all 52 unconditional QTLs for LLS and plant-type-related traits, 10 QTLs were clustered in five genetic regions, of which three clusters including five robust major QTLs overlapped between LLS and one of the plant-type-related traits, providing evidence that the correlation could be genetically constrained. On the other hand, conditional mapping revealed different numbers and different extent of additive effects of QTLs for LLS conditioned on three plant-type-related traits (HMS, LLB and TNB), which improved our understanding of interrelationship between LLS and plant-type-related traits at the QTL level. Furthermore, two QTLs, qLLSB6-7 and qLLSB1 for LLS resistance, were identified residing in two clusters of NB-LRR—encoding genes. This study not only provided new favorable QTLs for fine-mapping, but also suggested that the relationship between LLS and plant-type-related traits of HMS, LLB and TNB should be considered while breeding for improved LLS resistance in peanut.

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

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

Characterization and Transferable Utility of Microsatellite Markers in the Wild and Cultivated Arachis Species

Microsatellite or simple sequence repeat (SSR) is one of the most widely distributed molecular markers that have been widely utilized to assess genetic diversity and genetic mapping for important traits in plants. However, the understanding of microsatellite characteristics in Arachis species and the currently available amount of high-quality SSR markers remain limited. In this study, we identified 16,435 genome survey sequences SSRs (GSS-SSRs) and 40,199 expressed sequence tag SSRs (EST-SSRs) in Arachis hypogaea and its wild relative species using the publicly available sequence data. The GSS-SSRs had a density of 159.9–239.8 SSRs/Mb for wild Arachis and 1,015.8 SSR/Mb for cultivated Arachis, whereas the EST-SSRs had the density of 173.5–384.4 SSR/Mb and 250.9 SSRs/Mb for wild and cultivated Arachis, respectively. The trinucleotide SSRs were predominant across Arachis species, except that the dinucleotide accounted for most in A. hypogaea GSSs. From Arachis GSS-SSR and EST-SSR sequences, we developed 2,589 novel SSR markers that showed a high polymorphism in six diverse A. hypogaea accessions. A genetic linkage map that contained 540 novel SSR loci and 105 anchor SSR loci was constructed by case of a recombinant inbred lines F₆ population. A subset of 82 randomly selected SSR markers were used to screen 39 wild and 22 cultivated Arachis accessions, which revealed a high transferability of the novel SSRs across Arachis species. Our results provided informative clues to investigate microsatellite patterns across A. hypogaea and its wild relative species and potentially facilitate the germplasm evaluation and gene mapping in Arachis species.

Insights into the Indian Peanut Genotypes for ahFAD2 Gene Polymorphism Regulating Its Oleic and Linoleic Acid Fluxes

In peanut (Arachis hypogaea L.), the customization of fatty acid profile is an evolving area to fulfill the nutritional needs in the modern market. A total of 174 peanut genotypes, including 167 Indian cultivars, 6 advanced breeding lines and "SunOleic95R"-a double mutant line, were investigated using AS-PCRs, CAPS and gene sequencing for the ahFAD2 allele polymorphism, along with its fatty acid compositions. Of these, 80 genotypes were found having substitution (448G>A) mutation only in ahFAD2A gene, while none recorded 1-bp insertion (441_442insA) mutation in ahFAD2B gene. Moreover, 22 wild peanut accessions found lacking both the mutations. Among botanical types, the ahFAD2A mutation was more frequent in ssp. hypogaea (89%) than in ssp. fastigiata (17%). This single allele mutation, found affecting not only oleic to linoleic acid fluxes, but also the composition of other fatty acids in the genotypes studied. Repeated use of a few selected genotypes in the Indian varietal development programs were also eminently reflected in its ahFAD2 allele polymorphism. Absence of known mutations in the wild-relatives indicated the possible origin of these mutations, after the allotetraploidization of cultivated peanut. The SNP analysis of both ahFAD2A and ahFAD2B genes, revealed haplotype diversity of 1.05% and 0.95%, while Ka/Ks ratio of 0.36 and 0.39, respectively, indicating strong purifying selection pressure on these genes. Cluster analysis, using ahFAD2 gene SNPs, showed presence of both mutant and non-mutant genotypes in the same cluster, which might be due the presence of ahFAD2 gene families. This investigation provided insights into the large number of Indian peanut genotypes, covering various aspects related to O/L flux regulation and ahFAD2 gene polymorphism.

Molecular breeding for introgression of fatty acid desaturase mutant alleles (ahFAD2A and ahFAD2B) enhances oil quality in high and low oil containing peanut genotypes

High oleate peanuts have two marketable benefits, health benefits to consumers and extended shelf life of peanut products. Two mutant alleles present on linkage group a09 (ahFAD2A) and b09 (ahFAD2B) control composition of three major fatty acids, oleic, linoleic and palmitic acids which together determine peanut oil quality. In conventional breeding, selection for fatty acid composition is delayed to advanced generations. However by using DNA markers, breeders can reject large number of plants in early generations and therefore can optimize time and resources. Here, two approaches of molecular breeding namely marker-assisted backcrossing (MABC) and marker-assisted selection (MAS) were employed to transfer two FAD2 mutant alleles from SunOleic 95R into the genetic background of ICGV 06110, ICGV 06142 and ICGV 06420. In summary, 82 MABC and 387 MAS derived introgression lines (ILs) were developed using DNA markers with elevated oleic acid varying from 62 to 83%. Oleic acid increased by 0.5-1.1 folds, with concomitant reduction of linoleic acid by 0.4-1.0 folds and palmitic acid by 0.1-0.6 folds among ILs compared to recurrent parents. Finally, high oleate ILs, 27 with high oil (53-58%), and 28 ILs with low oil content (42-50%) were selected that may be released for cultivation upon further evaluation.