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.

Genetic mapping identified three hotspot genomic regions and candidate genes controlling heat tolerance-related traits in groundnut.

Groundnut productivity and quality have been impeded by rising temperatures in semi-arid environments. Hence, understanding the effects and molecular mechanisms of heat stress tolerance will aid in tackling yield losses. In this context, a recombinant inbred line (RIL) population was developed and phenotyped for eight seasons at three locations for agronomic, phenological, and physiological traits under heat stress. A genetic map was constructed using genotyping-by-sequencing with 478 single-nucleotide polymorphism (SNP) loci spanning a map distance of 1,961.39 cM. Quantitative trait locus (QTL) analysis using phenotypic and genotypic data identified 45 major main-effect QTLs for 21 traits. Intriguingly, three QTL clusters (Cluster-1-Ah03, Cluster-2-Ah12, and Cluster-3-Ah20) harbor more than half of the major QTLs (30/45, 66.6%) for various heat tolerant traits, explaining 10.4%-38.6%, 10.6%-44.6%, and 10.1%-49.5% of phenotypic variance, respectively. Furthermore, important candidate genes encoding DHHC-type zinc finger family protein (arahy.J0Y6Y5), peptide transporter 1 (arahy.8ZMT0C), pentatricopeptide repeat-containing protein (arahy.4A4JE9), Ulp1 protease family (arahy.X568GS), Kelch repeat F-box protein (arahy.I7X4PC), FRIGIDA-like protein (arahy.0C3V8Z), and post-illumination chlorophyll fluorescence increase (arahy.92ZGJC) were the underlying three QTL clusters. The putative functions of these genes suggested their involvement in seed development, regulating plant architecture, yield, genesis and growth of plants, flowering time regulation, and photosynthesis. Our results could provide a platform for further fine mapping, gene discovery, and developing markers for genomics-assisted breeding to develop heat-tolerant groundnut varieties.

Corrosion inhibition study of 6061 aluminium alloy in the presence of ethyl 5-methyl-1-(4-nitrophenyl)-1H-1,2,3-triazole-4-carboxylate (NTE) in hydrochloric acid.

The inhibitory effect of an ethyl 5-methyl-1-(4-nitrophenyl)-1H-1,2,3-triazole-4-carboxylate (NTE) was investigated on the corrosion of Al (AA6061) alloy at different temperatures (303-333 K) by Electrochemical impedance spectroscopy (EIS), Potentiodynamic polarization (PDP), and weight loss techniques. It was found that NTE molecules protect the aluminium against corrosion and its ability increases with increasing concentrations, and temperature resulting in better inhibitory performance. At all concentrations and temperature ranges, NTE exhibited mixed inhibitor action and complied with the Langmuir isotherm. At 100 ppm and 333 K, NTE demonstrated the highest inhibition efficiency (94%). The EIS results and the PDP results had a good level of concordance. A suitable mechanism for the corrosion prevention of AA6061 alloy was proposed. Atomic force microscopy (AFM) and scanning electron microscopy (SEM) were used to confirm the adsorption of an inhibitor onto the aluminium alloy surface. The electrochemical results were validated by morphological examination, which demonstrated that NTE prevents uniform corrosion of aluminium alloy in acid chloride solutions. The activation energy and thermodynamic parameters were computed, and the results were discussed.

Genome-wide structural and functional features of single nucleotide polymorphisms revealed from the whole genome resequencing of 179 accessions of Arachis.

Peanut being an important food, oilseed and fodder crop worldwide, its genetic improvement currently relies on genomics-assisted breeding (GAB). Since the level of marker polymorphism is limited in peanut, the availability of a large number of DNA markers is the prerequisite for GAB. Therefore, we detected 4,309,724 single nucleotide polymorphisms (SNPs) from the whole genome re-sequencing (WGRS) data of 178 peanut accessions along with the reference genome sequence of Tifrunner. SNPs were analyzed for their structural and functional features to conclude on their utility and employability in genetic and genomic studies. ISATGR278-18, a synthetic amphidiploid, showed the highest number of SNPs (2,505,266), while PI_628538 recorded the lowest number (19,058) of SNPs. A03 showed the highest number of SNPs, while B08 recorded the lowest number of SNPs. The number of accessions required to record 50% of the total SNPs varied from 11 to 13 across the chromosomes. The rate of transitions was more than that of transversions. Among the various chromosomal contexts, intergenic and intronic regions carried more SNPs than the exonic regions. SNP impact analysis indicated 2488 SNPs with high impact due to gain of stop codons, variations in splice acceptors and splice donors, and loss of start codons. Of the 4,309,723 SNPs, 46,087 had the highest polymorphic information content (PIC) of 0.375. As an illustration of application, the drought-tolerant accession C76-16 was compared with A72 (an accession with high-stress rating) to identify 637,833 SNPs, of which 418 had high impact substitutions. Overall, these structural and functional features of the SNPs will be of immense importance for their utility in genetic and genomic studies in peanut.

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.

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

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

Profiling of Nutraceuticals and Proximates in Peanut Genotypes Differing for Seed Coat Color and Seed Size.

A total of 60 genotypes of peanut comprising 46 genotypes selected from ICRISAT mini core collection and 14 elite cultivars with differing kernel color and size were used to profile the nutritional parameters such as proximates (moisture, fat, ash, crude protein, crude fiber, carbohydrate content) and nutraceuticals (total polyphenol content and total antioxidant activity). The genotypes showed varied kernel color ranging from white to purple. Kernel skin color was quantified using colorimetry, and the color parameters were expressed as CIELAB color parameters. In total, nine morphological traits, six yield related traits, eight nutritional traits and eleven color parameters were observed across 60 genotypes. The sixty genotypes were grouped into ten clusters based on the color strength. Among them, Cluster-III with dark red seeds had the maximum fat content and total polyphenol content (TPC). Cluster-VI with light pink colored seeds had high antioxidant activity (AOA) and Cluster-X with white colored seeds had highest moisture and crude protein content. Color strength (K/S) was found to be positively correlated with TPC. Another color parameter, redness/greenness (a*) was found to be positively correlated with AOA. However, seed size was positively correlated with the crude protein content, but not with any other nutritional traits under study. The population studies based on the genotypic data indicated two distinct groups pertaining to botanical types of peanut. The marker-trait association (MTA) using single marker analysis indicated 75 major MTAs for most of the nutritional traits except for moisture content. The markers associated with nutritional parameters and other important yield related traits can further be utilized for genomics-assisted breeding for nutrient-rich peanuts.

Translational genomics for achieving higher genetic gains in groundnut.

KEY MESSAGE: Groundnut has entered now in post-genome era enriched with optimum genomic and genetic resources to facilitate faster trait dissection, gene discovery and accelerated genetic improvement for developing climate-smart varieties. Cultivated groundnut or peanut (Arachis hypogaea), an allopolyploid oilseed crop with a large and complex genome, is one of the most nutritious food. This crop is grown in more than 100 countries, and the low productivity has remained the biggest challenge in the semiarid tropics. Recently, the groundnut research community has witnessed fast progress and achieved several key milestones in genomics research including genome sequence assemblies of wild diploid progenitors, wild tetraploid and both the subspecies of cultivated tetraploids, resequencing of diverse germplasm lines, genome-wide transcriptome atlas and cost-effective high and low-density genotyping assays. These genomic resources have enabled high-resolution trait mapping by using germplasm diversity panels and multi-parent genetic populations leading to precise gene discovery and diagnostic marker development. Furthermore, development and deployment of diagnostic markers have facilitated screening early generation populations as well as marker-assisted backcrossing breeding leading to development and commercialization of some molecular breeding products in groundnut. Several new genomics applications/technologies such as genomic selection, speed breeding, mid-density genotyping assay and genome editing are in pipeline. The integration of these new technologies hold great promise for developing climate-smart, high yielding and more nutritious groundnut varieties in the post-genome era.

Genotype × Environment Studies on Resistance to Late Leaf Spot and Rust in Genomic Selection Training Population of Peanut (Arachis hypogaea L.).

Foliar fungal diseases especially late leaf spot (LLS) and rust are the important production constraints across the peanut growing regions of the world. A set of 340 diverse peanut genotypes that includes accessions from gene bank of International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), elite breeding lines from the breeding program, and popular cultivars were screened for LLS and rust resistance and yield traits across three locations in India under natural and artificial disease epiphytotic conditions. The study revealed significant variation among the genotypes for LLS and rust resistance at different environments. Combined analysis of variance revealed significant environment (E) and genotype × environment (G×E) interactions for both the diseases indicating differential response of genotypes in different environments. The present study reported 31 genotypes as resistant to LLS and 66 to rust across the locations at 90 DAS with maturity duration 103 to 128 days. Twenty-eight genotypes showed resistance to both the diseases across the locations, of which 19 derived from A. cardenasii, five from A. hypogaea, and four from A. villosa. Site regression and Genotype by Genotype x Environment (GGE) biplot analysis identified eight genotypes as stable for LLS, 24 for rust and 14 for pod yield under disease pressure across the environments. Best performing environment specific genotypes were also identified. Nine genotypes resistant to LLS and rust showed 77% to 120% increase in pod yield over control under disease pressure with acceptable pod and kernel features that can be used as potential parents in LLS and rust resistance breeding. Pod yield increase as a consequence of resistance offered to foliar fungal diseases suggests the possibility of considering 'foliar fungal disease resistance' as a must-have trait in all the peanut cultivars that will be released for cultivation in rainfed ecologies in Asia and Africa. The phenotypic data of the present study will be used for designing genomic selection prediction models in peanut.

Remusatia vivipara lectin and Sclerotium rolfsii lectin interfere with the development and gall formation activity of Meloidogyne incognita in transgenic tomato.

Root knot nematodes are serious threats to growth and yield of solaneous crops including tomato. In this study, a binary vector carrying Remusatia vivipara (rvl1) and Sclerotium rolfsii (srl1) lectin genes were introduced independently into Lycopersicon esculentum cv. Pusa Ruby via Agrobacterium tumefaciens for resistance against root knot nematode, Meloidogyne incognita. In total, one hundred and one rvl1 and srl1-transformed plants exhibiting kanamycin resistance were confirmed to carry transgenes as detected by polymerase chain reaction (PCR) with 4.59% transformation efficiency. Genetic analysis of T1 progeny confirmed Mendelian segregation of the introduced genes. Three events each of rvl1 and srl1 transgenic tomato were randomly selected for further confirmation by Southern and TAIL-PCR analyses. All three events of srl1 transgenics showed single copy transgene, whereas two rvl1 transgenic events showed single copy of transgene, while remaining event showed two copies of transgenes. Site of integration obtained for rvl1 and srl1 transgenic events by TAIL-PCR revealed that all the three events of rvl1 and srl1 transgenics differed for their site of integration and insertion sites did not contain any predicted gene. Moreover, expression of the rvl1 and srl1 transgenes was detected by haemagglutination assay in all three events of rvl1 and srl1, but not in non-transgenic tomato plant. Homozygous progenies of these events were grown and inoculated with M. incognita. Development and reproduction of M. incognita was severely affected in transgenic tomato plants expressing RVL1 and SRL1 exhibiting the high levels of resistance compared to non-transgenic plants. Therefore, these transgenic lines demonstrate a promising potential for variety development of tomato lines with enhanced resistance against M. incognita.

Sequencing Analysis of Genetic Loci for Resistance for Late Leaf Spot and Rust in Peanut (Arachis hypogaea L.).

The aim of this study was to identify candidate resistance genes for late leaf spot (LLS) and rust diseases in peanut (Arachis hypogaea L.). We used a double-digest restriction-site associated DNA sequencing (ddRAD-Seq) technique based on next-generation sequencing (NGS) for genotyping analysis across the recombinant inbred lines (RILs) derived from a cross between a susceptible line, TAG 24, and a resistant line, GPBD 4. A total of 171 SNPs from the ddRAD-Seq together with 282 markers published in the previous studies were mapped on a genetic map covering 1510.1 cM. Subsequent quantitative trait locus (QTL) analysis revealed major genetic loci for LLS and rust resistance on chromosomes A02 and A03, respectively. Heterogeneous inbred family-derived near isogenic lines and the pedigree of the resistant gene donor, A. cardenasii Krapov. & W.C. Greg., including the resistant derivatives of ICGV 86855 and VG 9514 as well as GPBD 4, were employed for whole-genome resequencing analysis. The results indicated the QTL candidates for LLS and rust resistance were located in 1.4- and 2.7-Mb genome regions on A02 and A03, respectively. In these regions, four and six resistance-related genes with deleterious mutations were selected as candidates for LLS and rust resistance, respectively. These delimited genomic regions may be beneficial in breeding programs aimed at improving disease resistance and enhancing peanut productivity.

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

Rust and late leaf spot (LLS) are the two major foliar fungal diseases in groundnut, and their co-occurrence leads to significant yield loss in addition to the deterioration of fodder quality. To identify candidate genomic regions controlling resistance to rust and LLS, whole-genome resequencing (WGRS)-based approach referred as 'QTL-seq' was deployed. A total of 231.67 Gb raw and 192.10 Gb of clean sequence data were generated through WGRS of resistant parent and the resistant and susceptible bulks for rust and LLS. Sequence analysis of bulks for rust and LLS with reference-guided resistant parent assembly identified 3136 single-nucleotide polymorphisms (SNPs) for rust and 66 SNPs for LLS with the read depth of ≥7 in the identified genomic region on pseudomolecule A03. Detailed analysis identified 30 nonsynonymous SNPs affecting 25 candidate genes for rust resistance, while 14 intronic and three synonymous SNPs affecting nine candidate genes for LLS resistance. Subsequently, allele-specific diagnostic markers were identified for three SNPs for rust resistance and one SNP for LLS resistance. Genotyping of one RIL population (TAG 24 × GPBD 4) with these four diagnostic markers revealed higher phenotypic variation for these two diseases. These results suggest usefulness of QTL-seq approach in precise and rapid identification of candidate genomic regions and development of diagnostic markers for breeding applications.

Genomewide association studies for 50 agronomic traits in peanut using the 'reference set' comprising 300 genotypes from 48 countries of the semi-arid tropics of the world.

Peanut is an important and nutritious agricultural commodity and a livelihood of many small-holder farmers in the semi-arid tropics (SAT) of world which are facing serious production threats. Integration of genomics tools with on-going genetic improvement approaches is expected to facilitate accelerated development of improved cultivars. Therefore, high-resolution genotyping and multiple season phenotyping data for 50 important agronomic, disease and quality traits were generated on the 'reference set' of peanut. This study reports comprehensive analyses of allelic diversity, population structure, linkage disequilibrium (LD) decay and marker-trait association (MTA) in peanut. Distinctness of all the genotypes can be established by using either an unique allele detected by a single SSR or a combination of unique alleles by two or more than two SSR markers. As expected, DArT features (2.0 alleles/locus, 0.125 PIC) showed lower allele frequency and polymorphic information content (PIC) than SSRs (22.21 alleles /locus, 0.715 PIC). Both marker types clearly differentiated the genotypes of diploids from tetraploids. Multi-allelic SSRs identified three sub-groups (K = 3) while the LD simulation trend line based on squared-allele frequency correlations (r2) predicted LD decay of 15-20 cM in peanut genome. Detailed analysis identified a total of 524 highly significant MTAs (p value > 2.1 × 10-6) with wide phenotypic variance (PV) range (5.81-90.09%) for 36 traits. These MTAs after validation may be deployed in improving biotic resistance, oil/ seed/ nutritional quality, drought tolerance related traits, and yield/ yield components.

Transposon insertional mutagenesis in rice.

Insertion mutants offer one of the direct ways to relate a gene to its function by employing forward or reverse genetics approaches. Both T-DNA and transposon insertional mutants are being produced in several crops, including rice, the first cereal with its complete genome sequenced. Transposons have several advantages over T-DNA including the ability to produce multiple independent insertion lines from individual starter lines, as well as producing revertants by remobilization. With our new gene constructs, and a two-component transposon iAc/Ds mutagenesis protocol, we have improved both gene trapping and screening efficiencies in rice.

Purification, characterization and molecular cloning of a monocot mannose-binding lectin from Remusatia vivipara with nematicidal activity.

A mannose-binding lectin (RVL) was purified from the tubers of Remusatia vivipara, a monocot plant by single-step affinity chromatography on asialofetuin-Sepharose 4B. RVL agglutinated only rabbit erythrocytes and was inhibited by mucin, asialomucin, asialofetuin and thyroglobulin. Lectin activity was stable up to 80 degrees C and under wide range of pH (2.0-9.3). SDS-PAGE and gel filtration results showed the lectin is a homotetramer of Mr 49.5 kDa, but MALDI analysis showed two distinct peaks corresponding to subunit mass of 12 kDa and 12.7 kDa. Also the N-terminal sequencing gave two different sequences indicating presence of two polypeptide chains. Cloning of RVL gene indicated posttranslational cleavage of RVL precursor into two mature polypeptides of 116 and 117 amino-acid residues. Dynamic light scattering (DLS) and gel filtration studies together confirmed the homogeneity of the purified lectin and supported RVL as a dimer with Mr 49.5 kDa derived from single polypeptide precursor of 233 amino acids. Purified RVL exerts potent nematicidal activity on Meloidogyne incognita, a root knot nematode. Fluorescent confocal microscopic studies demonstrated the binding of RVL to specific regions of the alimentary-tract and exhibited a potent toxic effect on M. incognita. RVL-mucin complex failed to interact with the gut confirming the receptor mediated lectin interaction. Very high mortality (88%) rate was observed at lectin concentration as low as 30 microg/ml, suggesting its potential application in the development of nematode resistant transgenic-crops.