Surendra S. Manohar

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.

Genomic Tools in Groundnut Breeding Program: Status and Perspectives

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

Iron and zinc concentrations in peanut ( Arachis hypogaea L.) seeds and their relationship with other nutritional and yield parameters

Biofortification (delivery of micronutrients via micronutrient-dense crops) can be achieved through plant breeding and offers a cost-effective and sustainable approach to fighting micronutrient malnutrition. The present study was conducted to facilitate the initiation of a breeding programme to improve the concentration of iron (Fe) and zinc (Zn) in peanut (Arachis hypogaea L.) seeds. The experiment was conducted with 64 diverse peanut genotypes for 2 years in eight different environments at the International Crops Research Institute for the Semi-Arid Tropics, Patancheru, India to assess the genetic variation for Fe and Zn concentrations in peanut seeds and their heritability and correlations with other traits. Significant differences were observed among the genotypes and environments for Fe (33–68 mg/kg), Zn (44–95 mg/kg), protein (150–310 mg/g) and oil (410–610 mg/g) concentration in seeds and their heritability was high, thus indicating the possibility of improving them through breeding. As seen in other plants, a significant positive association between concentrations of Fe and Zn was observed. Trade-offs between pod yield and Fe and Zn concentrations were not observed and the same was also true for oil content. Besides being high yielding, genotypes ICGV 06099 (57 mg/kg Fe and 81 mg/kg Zn) and ICGV 06040 (56 mg/kg Fe and 80 mg/kg Zn) had stable performance for Fe and Zn concentrations across environments. These are the ideal choices for use as parents in a breeding programme and in developing mapping populations.

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.

Selections data of high-oil-yielding stables Groundnut genotypes based on genotype X environment interactions

Peanut (Arachis hypogaea L.) genotypes with superior and stable agronomic performance and high oil content were identified from testing of 160 advanced breeding lines over six seasons (three rainy and three post rainy seasons). The study revealed significant genotype and genotype X environment interaction determining oil and protein content; shelling out-turn; and pod, kernel, and oil yield in peanut. The variability among genotypes was high across the environments for pod yield (546- 7382 kg per ha), oil yield (301-2742 kg per ha), oil content (37-60%), 100-seed weight (21-127 g), and protein content (19-31%). The GGE bi-plot technique revealed that ICGV 05155 is a stable genotype for oil yield with an average oil yield of 1886 kg per ha. ICGV 05155 recorded highest average pod yield of 4928 kg per ha, kernel yield of 3420 kg per ha, and oil content of 55%. ICGV 06049, ICGV 06041, ICGV 06420, and ICGV 03043 were other genotypes with stable oil yield. Simple regression showed significant contributions of oil content (18-54%), and kernel yield (92-99%) to oil yield across the environments. Simultaneous improvement of kernel yield and oil content is feasible in breeding programs, as kernel yield had no negative association with oil content. The high oil content genotypes, ICGV 05155, ICGV 06049, ICGV 06041, ICGV 06420, and ICGV 03043, with stable oil yield were promoted to multilocation adaptive trials required for their release for cultivation and used as parents in breeding programs and development of mapping population to identify quantitative trait loci (QTL) governing oil content. Experiment location on Google Map

Groundnut genotypes data based on analysis for high oil trails in post rainy season

Peanut (Arachis hypogaea L.) genotypes with superior and stable agronomic performance and high oil content were identified from testing of 160 advanced breeding lines over six seasons (three rainy and three post rainy seasons). The study revealed significant genotype and genotype X environment interaction determining oil and protein content; shelling out-turn; and pod, kernel, and oil yield in peanut. The variability among genotypes was high across the environments for pod yield (546- 7382 kg per ha), oil yield (301-2742 kg per ha), oil content (37-60%), 100-seed weight (21-127 g), and protein content (19-31%). The GGE bi-plot technique revealed that ICGV 05155 is a stable genotype for oil yield with an average oil yield of 1886 kg per ha. ICGV 05155 recorded highest average pod yield of 4928 kg per ha, kernel yield of 3420 kg per ha, and oil content of 55%. ICGV 06049, ICGV 06041, ICGV 06420, and ICGV 03043 were other genotypes with stable oil yield. Simple regression showed significant contributions of oil content (18-54%), and kernel yield (92-99%) to oil yield across the environments. Simultaneous improvement of kernel yield and oil content is feasible in breeding programs, as kernel yield had no negative association with oil content. The high oil content genotypes, ICGV 05155, ICGV 06049, ICGV 06041, ICGV 06420, and ICGV 03043, with stable oil yield were promoted to multilocation adaptive trials required for their release for cultivation and used as parents in breeding programs and development of mapping population to identify quantitative trait loci (QTL) governing oil content. Experiment location on Google Map

Data on identified foliar fungal disease-resistant introgression lines with higher pod and haulm yield testing of Groundnut in MABC rainy 2013

Introgression lines (ILs) of groundnut with enhanced resistance to rust recorded increased pod and haulm yield in testing. Marker-assisted backcrossing (MABC) approach was used to introgress a genomic region containing a major QTL that explains >80% of phenotypic variance (PV) for rust resistance. ILs in the genetic background of TAG-24, ICGV 91114 and JL 24 were evaluated for two seasons (Rainy 2013 and 2014) to select 20 best ILs based on resistance, productivity parameters and maturity duration. selected ILs was conducted in locations including disease hot spots.The incidence of rust is severe during the season. In all the locations, infector rows of susceptible variety around the experimental plot and in between test entries ensured uniform spread of disease. Only the disease scores at ICRISAT, Patancheru. Background genotype, environment and genotype X environment interactions are important for expression of resistance governed by the QTL region. Six best ILs namely ICGV13192, ICGV 13193, ICGV 13200, ICGV 13206, ICGV 13228 and ICGV 13229 were selected with 39–79% higher mean pod yield and 25-89% higher mean haulm yield over their respective recurrent parents. Pod yield increase was contributed by increase in seed mass and number of pods per plant. Experiment location on Google Map

Identified foliar fungal disease-resistant introgression lines with higher pod and haulm yield testing of Groundnut in MABC Post rainy 2013-14

Introgression lines (ILs) of groundnut with enhanced resistance to rust and late leaf spot (LLS) recorded increased pod and haulm yield testing. Marker-assisted backcrossing (MABC) approach was used to introgress a genomic region containing a major QTL that explains >80% of phenotypic variance (PV) for rust resistance and67.98% PV for LLS resistance. ILs in the genetic background of TAG-24, ICGV 91114 and JL 24 were evaluated for two seasons (Rainy 2013 and 2014) to select 20best ILs based on resistance, productivity parameters and maturity duration. Both late leaf spot and rust occur together. while LLS is moderate. In all the locations, infector rows of susceptible variety around the experimental plot and in between test entries ensured uniform spread of disease. Only the disease scores at ICRISAT, Patancheru . Background genotype, environment and genotype X environment interactions are important for expression of resistance governed by the QTL region. Six best ILs namely ICGV13192, ICGV 13193, ICGV 13200, ICGV 13206, ICGV 13228 and ICGV 13229 were selected with 39–79% higher mean pod yield and 25-89% higher mean haulm yield over their respective recurrent parents. Pod yield increase was contributed by increase in seed mass and number of pods per plant. Experiment location on Google Map

Data on identified foliar fungal disease-resistant introgression lines with higher pod and haulm yield testing of LLS and RUST

Introgression lines (ILs) of groundnut with enhanced resistance to rust and late leaf spot (LLS) recorded increased pod and haulm yield testing. Marker-assisted backcrossing (MABC) approach was used to introgress a genomic region containing a major QTL that explains >80% of phenotypic variance (PV) for rust resistance and 67.98% PV for LLS resistance. ILs in the genetic background of TAG-24, ICGV 91114 and JL 24 were evaluated for two seasons (Rainy 2013 and 2014) to select 20 best ILs based on resistance, productivity parameters and maturity duration. Both late leaf spot and rust occur together. while LLS is moderate. infector rows of susceptible variety around the experimental plot and in between test entries ensured uniform spread of disease. The disease scores at ICRISAT, Patancheru . Background genotype, environment and genotype X environment interactions are important for expression of resistance governed by the QTL region. Six best ILs namely ICGV13192, ICGV 13193, ICGV 13200, ICGV 13206, ICGV 13228 and ICGV 13229 were selected with 39–79% higher mean pod yield and 25-89% higher mean haulm yield over their respective recurrent parents. Pod yield increase was contributed by increase in seed mass and number of pods per plant. Experiment location on Google Map

Identified foliar fungal disease-resistant introgression lines with higher pod and haulm yield data in multilocation testing of Groundnut in Dharwad and Aliyar Nagar

Introgression lines (ILs) of groundnut with enhanced resistance to rust and late leaf spot (LLS) recorded increased pod and haulm yield in multilocation testing. Marker-assisted backcrossing (MABC) approach was used to introgress a genomic region containing a major QTL that explains >80% of phenotypic variance (PV) for rust resistance and 67.98% PV for LLS resistance. ILs in the genetic background of TAG-24, ICGV 91114 and JL 24 were evaluated for two seasons (Rainy 2013 and 2014) to select 20 best ILs based on resistance, productivity parameters and maturity duration. Multilocation evaluation of the selected ILs was conducted including disease hot spots. Disease incidence at these two locations is by natural infection wherein, both late leaf spot and rust occur together. The incidence of rust is severe at Aliyarnagar during the season, while LLS is moderate. In all the locations, infector rows of susceptible variety around the experimental plot and in between test entries ensured uniform spread of disease. Only the disease scores at Aliyarnagar, were considered for ANOVA as the scoring at Dharwad-Karnataka was recorded on single replication. Background genotype, environment and genotype X environment interactions are important for expression of resistance governed by the QTL region. Six best ILs namely ICGV13192, ICGV 13193, ICGV 13200, ICGV 13206, ICGV 13228 and ICGV 13229 were selected with 39–79% higher mean pod yield and 25-89% higher mean haulm yield over their respective recurrent parents. Pod yield increase was contributed by increase in seed mass and number of pods per plant. Experiment location on Google Map - Dharwad Experiment location on Google Map - Aliyar Nagar