Comparative genome analysis to identify SNPs associated with high oleic acid and elevated protein content in soybean

Kulkarni, Krishnanand P.,Patil, Gunvant,Valliyodan, Babu,Vuong, Tri D.,Shannon, J. Grover,Nguyen, Henry T.,Lee, Jeong-Dong,Belzile, F. National Research Council of Canada, Conseil natio 2018 Genome Vol. No.

<P> The objective of this study was to determine the genetic relationship between the oleic acid and protein content. The genotypes having high oleic acid and elevated protein (HOEP) content were crossed with five elite lines having normal oleic acid and average protein (NOAP) content. The selected accessions were grown at six environments in three different locations and phenotyped for protein, oil, and fatty acid components. The mean protein content of parents, HOEP, and NOAP lines was 34.6%, 38%, and 34.9%, respectively. The oleic acid concentration of parents, HOEP, and NOAP lines was 21.7%, 80.5%, and 20.8%, respectively. The HOEP plants carried both FAD2-1A (S117N) and FAD2-1B (P137R) mutant alleles contributing to the high oleic acid phenotype. Comparative genome analysis using whole-genome resequencing data identified six genes having single nucleotide polymorphism (SNP) significantly associated with the traits analyzed. A single SNP in the putative gene Glyma.10G275800 was associated with the elevated protein content, and palmitic, oleic, and linoleic acids. The genes from the marker intervals of previously identified QTL did not carry SNPs associated with protein content and fatty acid composition in the lines used in this study, indicating that all the genes except Glyma.10G278000 may be the new genes associated with the respective traits. </P>

Mapping QTLs for 100-seed weight in an interspecific soybean cross of Williams 82 (Glycine max) and PI 366121 (Glycine soja)

Kulkarni, Krishnanand P.,Asekova, Sovetgul,Lee, Dong-Ho,Bilyeu, Kristin,Song, Jong Tae,Lee, Jeong-Dong CSIRO Publishing 2017 Crop & pasture science Vol.68 No.2

<P> Seed weight can be an important component for soybean quality and yield. The objective of the present study was to identify quantitative trait loci (QTLs) for 100-seed weight by using 169 recombinant inbred lines (RILs) derived from the cross Williams 82 × PI 366121. The parental lines and RILs were grown for four consecutive years (2012-15) in the field. The seeds were harvested after maturity, dried and used to measure 100-seed weight. Analysis of variance indicated significant differences among the RILs for 100-seed weight. The environment had significant effect on seed-weight expression as indicated by the genotype × environment interaction. QTL analysis employing inclusive composite interval mapping of additive QTLs implemented in QTL IciMapping (Version 4.1) identified nine QTLs (LOD >3) on chromosomes 1, 2, 6, 8, 13, 14, 17 and 20. The individual QTLs explained phenotypic variation in the range 6.1-12.4%. The QTLs were detected in one or two environments, indicating major influence of the growing environment on seed-weight expression. Four QTLs identified in this study, qSW-02_1, qSW-06_1, qSW-13_1 and qSW-14_1, were found to be new QTLs. The findings of the study may be helpful to reveal the molecular genetic basis of the seed-weight trait in soybean. </P>

Genetic mapping of quantitative trait loci controlling seed weight in an interspecific soybean recombinant inbred line population

Krishnanand P Kulkarni,Minsu Kim,Jeong Hwa Kim,Sovetgul Asekova,Jong Tae Song,Jeong-Dong Lee 한국육종학회 2015 한국육종학회 심포지엄 Vol.2015 No.07

Seed weight (SW), often expressed as 100-seed weight (HSW), is an important yield component in soybean and has been found to show positive correlation with seed yield. It is shown to behave as a quantitative trait controlled by many loci that are largely unclear. In this study, we represent the identification of chromosomal regions controlling the seed weight in soybean. We used a Recombinant Inbred Line (RIL) population, consisting of 188 lines derived from a cross of a wild soybean PI483463 (HSW: 0.85g) and a cultivated soybean cultivar Hutcheson (HSW: 14.05g) to identify the chromosomal regions controlling the SW trait. The population, along with parental samples and check, William82 (HSW: 21.2g) was grown for four years and phenotype data was recorded postharvest. A total of 535 SNP and 16 SSR markers, polymorphic between the parents were employed to genotype the RILs using Golden gate assay to develop the linkage map. Whole genome QTL scanning identified a total of 17 QTLs, spanning 10 chromosomes for the 100-seed weight. All these QTLs explained phenotypic variation (PV) in the range of 3.77 to 12.33%. Of the 17 QTLs, 2 QTLs qSWA1-1 and qSWD2-1, found to be the consistent QTLs, expressing in all the four environments. The QTL qSWD2-1 explained highest contribution to the total PV with 10.04 -12.23 %. The remaining 15 QTLs were identified in at least one environment with PV ranging up to 10.39%. The findings from this study will provide useful information to understand the genetic and molecular basis of SW and facilitate further genomic research leading to the yield improvements in soybean.

Genetic Improvement of the Fatty Acid Biosynthesis System to Alter the ω-6/ω-3 Ratio in the Soybean Seed

Kulkarni, Krishnanand P.,Kim, Minsu,Song, Jong Tae,Bilyeu, Kristin D.,Lee, Jeong-Dong Springer New York LLC 2017 Journal of the American Oil Chemists' Society Vol. No.

QTL Mapping for shoot fresh weight in a RIL population developed from a cross of wild and cultivated soybean

Sovetgul Asekova,Krishnanand P Kulkarni,Jeong Hwa Kim,Minsu Kim,Jiho Park,Hyun-Jee Kim,J. Grover Shannon,Jeong-Dong Lee 한국육종학회 2015 한국육종학회 심포지엄 Vol.2015 No.07

Shoot-fresh-weight (SFW) is one of the parameters, used to estimate the total plant biomass yield in soybean. Understanding the genetic and molecular basis of SFW could help increase the total biomass production. In this particular study, we identified QTLs associated with SFW in a Recombinant Inbred Line (RIL) population derived from interspecific cross of PI483463 and Hutcheson. A total of 551 (535 SNP and 16 SSR) markers, were found to be polymorphic between the parental lines and were used to screen the RILs to develop the genetic map. Linkage analysis and QTL mapping were performed using with the software QTL IciMapping version 4.0, with the minimum LOD score of 3.0 and estimating the likelihood of a QTL and its corresponding effects at every 1cM. QTLs with LOD value > threshold LOD, as determined by 1000 permutation tests at p > 0.05 were considered as significant QTLs. The analysis identified a total of 5 QTLs associated with shoot fresh weight over two environments, with the phenotypic variation (PV) ranging from 6.34 to 21.32%, and the additive effect from -0.54 to 0.33. Among these QTLs, qFW1314_19_1 had the largest LOD scores, with PV of 21.32%. Interestingly, three QTLs, qFW2013_19_1, qFW2014_19_1, and qFW1314_19_1 identified on chromosome 19(L), showed negative additive effects, indicating the contribution from the wild parent PI483463. The QTLs identified in this study can be the targets to identify the candidate genes for the SFW and can help in developing cultivars with increased biomass potential.

Environmental Stability and Correlation of Soybean Seed Starch with Protein and Oil Contents

Sanjeev K. Dhungana,Krishnanand P. Kulkarni,김민수,하보근,강성택,송종태,신동현,이정동 한국육종학회 2017 Plant Breeding and Biotechnology Vol.5 No.4

Seed starch content (SSC) is a decisive factor influencing soy food quality. Variation in SSC affects the composition of major components, oil, and protein in soybean seeds. Therefore, understanding G × E interaction of SSC is important to produce soybeans with stable SSC. In the present study, G × E interactions of 17 soybean genotypes having different SSC (0.24-1.48%) and correlation of SSC with crude protein (CP) and crude fat (CF) were investigated. The genotypes were evaluated for SSC and other traits at two planting dates across three locations over two years (2015 and 2016). The genotype × year, genotype × location, and genotype × year × location interactions were found to be significant (P ≤ 0.001) for SSC, CP, and CF. The average SSC content was found to be higher in 2015 than in 2016. Late planted soybeans contained higher SSC than the early planting soybeans. The SSC was negatively affected by the average daily mean and minimum temperatures and cloudiness during the pod-filling stage. Based on the mean rank, IT189276 (1.39%) was observed to be the most stable genotype among the high starch containing soybeans. Significant (P ≤ 0.0001) negative correlations were found between SSC and CP as well as CP and CF contents. However, a significant (P ≤ 0.05) positive correlation was observed between SSC and CF content. Results of this study showed that SSC affects the seed protein and oil contents and is significantly influenced by the growing environments.

Analysis of Molecular Variance and Population Structure of Sesame (Sesamum indicum L.) Genotypes Using Simple Sequence Repeat Markers

Sovetgul Asekova,Krishnanand P. Kulkarni,오기원,이명희,오은영,김정인,여운상,배석복,하태정,김성업 한국육종학회 2018 Plant Breeding and Biotechnology Vol.6 No.4

Sesame (Sesamum indicum L.) is an important oilseed crop grown in tropical and subtropical areas. The objective of this study was to investigate the genetic relationships among 129 sesame landraces and cultivars using simple sequence repeat (SSR) markers. Out of 70 SSRs, 23 were found to be informative and produced 157 alleles. The number of alleles per locus ranged from 3 - 14, whereas polymorphic information content ranged from 0.33 - 0.86. A distance-based phylogenetic analysis revealed two major and six minor clusters. The population structure analysis using a Bayesian model-based program in STRUCTURE 2.3.4 divided 129 sesame accessions into three major populations (K = 3). Based on pairwise comparison estimates, Pop1 was observed to be genetically close to Pop2 with FST value of 0.15, while Pop2 and Pop3 were genetically closest with FST value of 0.08. Analysis of molecular variance revealed a high percentage of variability among individuals within populations (85.84%) than among the populations (14.16%). Similarly, a high variance was observed among the individuals within the country of origins (90.45%) than between the countries of origins. The grouping of genotypes in clusters was not related to their geographic origin indicating considerable gene flow among sesame genotypes across the selected geographic regions. The SSR markers used in the present study were able to distinguish closely linked sesame genotypes, thereby showing their usefulness in assessing the potentially important source of genetic variation. These markers can be used for future sesame varietal classification, conservation, and other breeding purposes.

Physiological and Molecular Responses of Red Maple (Acer rubrum L.) Cultivars to Drought Stress

Philip Bissiwu,Krishnanand P. Kulkarni,Kalpalatha Melmaiee,Sathya Elavarthi 한국육종학회 2022 Plant Breeding and Biotechnology Vol.10 No.1

Acer rubrum (red maple) is one of the most important ornamental trees in North America. It is used in urban forestry and landscaping, as well as timber and syrup production. Drought is a major challenge that hinders the development and growth of maples and other tree species. The objective of the present study was to evaluate three red maple cultivars namely, October glory, Autumn red, and Red sunset for their physiological and molecular response to drought stress. Saplings of three cultivars of red maple were subjected to drought stress (up to 28 days unirrigated) in the summer of 2018 and 2019, and leaf samples were used to quantify physiological, biochemical, and expression changes under stress. Decrement of chlorophyll content significantly correlated with the soil moisture content observed in all three genotypes subjected to drought stress. Significant variation in proline concentration, Malondialdehyde levels, and increase in superoxide dismutase (SOD) activity at various stages of the experiments showed the ability of the maple plants to respond to drought stress. RT-qPCR analyses revealed higher and variable expression of drought-responsive genes GGAT1 encoding glutamate-glyoxylate aminotransferase, and CSD2 encoding SOD, in the red maple plants under drought stress. The results from this study indicate that the red maple plants alleviate drought stress by the possible mechanism involving decreased lipid peroxidation, and enhanced production of osmolyte and antioxidants.

Genetic analysis of shoot fresh weight in a cross of wild (G. soja) and cultivated (G. max) soybean

Asekova, Sovetgul,Kulkarni, Krishnanand P.,Patil, Gunvant,Kim, Minsu,Song, Jong Tae,Nguyen, Henry T.,Grover Shannon, J.,Lee, Jeong-Dong Springer-Verlag 2016 Molecular breeding Vol.36 No.7

Soybean Sprouts: A Review of Nutrient Composition, Health Benefits and Genetic Variation

( Mirwais Ghani ),( Krishnanand P. Kulkarni ),( Jong Tae Song ),( J. Grover Shannon ),( Jeong-dong Lee ) 한국육종학회 2016 Plant Breeding and Biotechnology Vol.4 No.4

Soybean [Glycine max (L.) Merr.] sprouts are highly digestible and a year around vegetable suitable for human consumption. Sprouting process causes a number of biochemical changes inside the seed, resulting in the accumulation of various primary and secondary metabolites. Due to such changes, sprouts contain high levels of health-promoting phytochemicals as compared to other vegetables. Sprouts are an excellent source of protein, amino acids, and vitamins, which provide numerous health benefits. Due to such advantages, soybean sprouts have been preferred as a part of daily diets in Korea and quality soybean sprouts are in high demand in the edible food market. To produce high quality soybean sprouts, several factors, including the choice of the variety, health benefits from sprout phytonutrients and inherent genetic variation for the sprout-related traits of the variety need to be considered. In this review, we have summarized literature on soybean sprout components, the health benefits, changes in nutritional factors during the sprouting process and the genetic variation among the cultivars developed for sprout usage. We have also reviewed procedures and factors like seed characteristics, temperature, chemical applications that influence the sprouting process. The information collectively presented here will be useful for understanding the progress of soybean cultivars developed for soybean sprout development and use.