Download or read book Seed and Leaf Trait Correlations and Identification of Underlying Loci in Soybean Glycine Max L Merr written by Charles R. Yesudas and published by . This book was released on 2008 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soybean [Glycine max (L.) Merill] is a major crop due to high seed protein, isoflavone and oil contents. The aim here was to find loci underlying agronomic traits with new markers and new trait data. Genetic analyses of these traits were carried out in field experiments of 100 'Essex' x 'Forrest' (ExF) recombinant inbred lines. Trait data analysis for insect leaf herbivory, yield, seed protein, oil, water and isoflavone content and mapping the underlying QTL identified candidate genes. Seed protein content was positively correlated with seed yield but negatively correlated with seed oil. Seed isoflavone content did not correlate with herbivory but did negatively correlate with seed yield. Two measures of herbivory; pest incidence and pest severity, showed a strong genetic component but did not correlate with any other trait. QTL associations ranged from 5 loci for total glycitein to 1 for many other traits. Sixty eight QTL were found in this study, including 10 new QTL underlying 9 previously characterized traits derived for the 27 new markers added to the existing ExF mapping file.

Download or read book Identification and Localization of Quantitative Trait Loci QTL and Genes Associated with Oil Concentration in Soybean Glycine Max L Merrill Seed written by Mehrzad Eskandari and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Quantitative Trait Loci Associated with Protein Oil and Carbohydrates in Soybean Glycine Max L Merr Seeds written by Ravi V. Mural and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soybean is mainly cultivated for its oil and high quality protein meal for feed, fuel and food uses. Achieving an improved balance of protein and oil in the seed, along with yield will enhance crop value. In practice, this has been difficult to achieve due to significant negative correlations of oil and protein, and the mostly negative relationship reported between seed protein concentration and yield. Most previous studies have focused on increasing seed oil concentration (SOC) or seed protein concentration (SPC) individually, and a few focused on decreasing raffinosacharides to improve digestibility and metabolizable energy of the feed for monogastric animals. None of the studies to date have considered improving the balance of SOC and SPC by also considering variation in total soluble sugars, which comprise the third largest component in soybean seed. Three related bi-parental recombinant inbred line (RIL) populations were developed by crossing two plant introduction lines that have lower total sugar concentration with two high-yielding soybean lines having higher SOC resulting in two pairs of half-sib populations. The objectives of this study were to identify genomic regions that influence oil, protein and carbohydrate concentrations in the seed in three uniquely structured bi-parental RIL populations using Molecular Inversion Probes (MIPs) markers, and evaluate relationships among seed composition traits and seed yield, seed weight and plant maturity from multiple environments. In total, 51 QTLs for seed, seed composition and plant traits were mapped on 17 chromosomes. All populations showed transgressive segregation for the sum of seed oil+protein concentration (SUM) in both directions but showed little transgressive segregation for SOC or SPC in two populations. There was a positive correlation of SOC and SPC with the SUM in two populations and a near to zero relationship of SUM with plot yield. Over the three populations, about 85% of the lines met processor targets of 10-12 pounds of oil per bushel and would produce 48% protein meal. The selected lines from this study could be further evaluated for yield and desirable agronomic traits in multi-location trials, which could lead to higher yielding soybean lines with improved seed composition. This work will ultimately lead to higher profitability for both the processors and farmers.

Download or read book Characterization of the Genetic and Environmental Effects Underlying Soybean Seed Protein Concentration in Two Recombinant Inbred Populations written by Rachel Whaley and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Soybean (Glycine max (L.) Merrill) is a significant source of high-quality plant-based protein. An increased awareness of soybean health benefits has spurred a greater demand for soy-based food products, which has attracted attention from researchers, soybean growers and food processors. Soybean seed protein concentration is a complex trait that is influenced by genotype, environment and genotype-by-environment interaction effects, and is negatively associated with seed yield. The main objectives of this study were to: (i) determine the effects of genotype and genotype-by-environment interaction on seed protein concentration; and (ii) identify quantitative trait loci (QTL) associated with seed protein concentration suitable for marker-assisted selection. Genotypic and phenotypic data were collected from multi-environment trials of two recombinant inbred line (RIL) populations, derived from the high-protein cultivar, AC X790P (49%, dry weight basis), and low protein commercial cultivars, S18-R6 (41%) and S23-T5 (42%). Genotype, environment and genotype-by-environment interaction effects significantly affected seed protein concentration and seed yield. Significant correlations between seed protein concentration and seed yield were not observed in either population, and GGE biplots made it possible to identify for competitive high-protein genotypes. Seventy-nine QTL associated with seed protein concentration (with R2 ranging from 4.1% to 24.4%) were identified, 14 of which (with R2 ranging from 10.0% to 20.7%) were deemed desirable for marker-assisted selection.

Download or read book Mendelizing Quantitative Trait Loci that Underlie Resistance to Soybean Sudden Death Syndrome written by Yi-Chen Lee and published by . This book was released on 2016 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soybean (Glycine max [L.] Merr.) cultivars differ in their resistance to sudden death syndrome (SDS). The syndrome is caused by root colonization by Fusarium virguliforme (ex. F. solani f. sp. glycines). Breeding for improve SDS response has proven challenging, possible due to interactions among the 18 known loci for resistance. Four loci for resistance to SDS (cq Rfs to cqRfs3) were found clustered within 20 cM of the rhg1 locus underlying resistance to soybean cyst nematode (SCN) on chromosome 18. Another locus on chromosome 20 (cqRfs5) was reported to interact with this cluster. The aims of this study were to compare the inheritance of resistance to SDS in a near isogenic line (NIL) population that was fixed for resistance to SCN but still segregated at 2 of the 4 loci (cqRfs1 and cqRfs) for resistance to SDS on chromosome 18; to examine the interaction with the locus on chromosome 20; and to identify candidate regions underlying quantitative trait loci (QTL). Used were a near isogenic line population derived from residual heterozygosity in an F5:7 recombinant inbred line EF60 1-40; SDS response data from 2 locations and years; four microsatellite markers and six thousand SNP markers. Polymorphic regions were found from 2,788 to 8,938 Kbp on chromosome 18 and 33,100 to 34,943 Kbp on chromosome 20. Both regions were significantly (0.005 P 0.0001) associated with resistance to SDS. A fine map was constructed that Mendelized the three loci. Substitution maps suggested the two loci on chromosome 18 were actually 3 loci (cqRfs, cq Rfs1 and cqRfs19). Candidate genes for cq Rfs19 were identified in a small region of the genome sequence of soybean. An epistatic interaction was inferred where the allele of loci on chromosome 18 determined the value of the locus on chromosome 20. It was concluded that SDS loci are both complex and interacting which may explain the slow progress in breeding for resistance to SDS.

Download or read book Genetic Analysis of Quality Traits for Food grade Soybean Glycine Max L Merr in a Breeding Population written by Mao Huang and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Food-grade soybeans are a specialty crop with unique chemical and physical seed quality requirements. The tofu production market requires large, round soybean seed with a clear hilum and high protein content. The aim of this project was to detect QTL responsible for traits important in food-grade soybeans, and to provide information for the selection of food-grade soybeans in a breeding program. This study assessed seed shape, size, density, weight, protein content, and oil content in two independent populations of breeding lines and cultivars as well as textural traits of the tofu produced from a subset of those. By identifying the relationship between seed traits and tofu texture, the previously established positive correlation between seed protein content and the stiffness and gel strength of tofu were confirmed. Little to no correlations between seed size and shape measurements and the texture of tofu were detected, indicating that this consumer preference for large, round seeds may not relate to tofu quality. The effects of selection for specialty traits on the genetic differentiation within a breeding program were assessed, results shown that both parental and progeny selection contributed to genetic differentiation and population structure. Association mapping was conducted with 504 markers in a population of 242 breeding lines and cultivars, leading to the identification of 50 significant marker-trait associations. Of the 27 significant associations tested in another independent confirmation population consisting of 152 lines or cultivars, 12 were confirmed. These results can be directly applied to increase selection efficiency in a breeding program.

Download or read book Genomic Regions Involved in Seed Protein Oil and Carbohydrate Concentration in Soybean written by Samantha J. McConaughy and published by . This book was released on 2017 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soybeans [Glycine max (L.) Merr.] are processed for their high-quality vegetable oil and protein meal for feed, food, and industrial applications but, because of the high negative correlations between seed protein and oil concentration, it has been difficult to develop soybean lines with concomitant increases in both protein and oil. Previous studies considered only seed protein or oil concentration. This study is unique in that populations were developed using parental lines that differed in their protein, oil, and total carbohydrate concentrations in the mature seed. Two soybean populations were developed using soybean accession PI 547827 with lower total sugars as a common parent, crossed to two different soybean lines with modified protein and oil concentrations. The objectives were to identify quantitative trait loci (QTL) related to seed protein, oil, and carbohydrate concentration as well as for individual sugars sucrose, raffinose, and stachyose. For each of the two crosses, F4-derived recombinant inbred lines (RIL) were developed through single seed descent resulting in 526 and 404 RILs, respectively. Genotypes were determined for F4 plants by genotyping-by-sequence (GbS), resulting in 1,650 to 2,850 polymorphic SNPs used for QTL analyses. Populations were grown in an augmented design in two Nebraska and one Puerto Rico environment to evaluate seed composition, yield, and maturity. The QTL analyses identified 23 novel QTL across all seed composition traits, protein, oil, sum(p+o) or carbohydrate concentration, and each of the sugars on 17 different linkage groups. Ninety nine percent of the lines in the high protein cross, and 100% of the lines in the high oil cross exceeded processor targets of 11 pounds of oil per bushel and a soybean meal with greater than 47.5% protein. Correlations between yield and the sum(p+o) were either zero or slightly positive, indicating that it should be possible to identify high-yielding lines with increased seed protein and oil concentration. Populations like these, and the QTL identified here, will be useful in achieving those objectives to provide more value for both the processor and producer.

Download or read book Marker Assisted Selection for Seed Yield in Soybean Glycine Max L Merr Plant Row Yield Trials written by Jason D. Neus and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative trait loci (QTL) controlling seed yield in soybean [Glycine max (L.) Merr.] have been difficult to confirm among populations. Our objective was to determine whether a method of marker-assisted selection (MAS) for seed yield in elite lines would be applicable to selection in soybean plant row yield trials (PRYTs). Lines from two populations with elite parents were grown in PRYTs in 2008 and tested with markers to identify quantitative trait loci (QTL) associated with seed yield. The first population was tested with 53 single nucleotide polymorphism (SNP) markers and the second population with 26 SNP markers. F-tests were conducted to determine which loci were significantly associated with seed yield in the PRYTs. Lines from each population were then selected from the PRYTs to form five groups from each population: high and low seed yield phenotypes, high and low seed yield genotypes, and random. The five groups from each population were planted at eight diverse locations in 2009. In one population, the mean of the genotypic high group was not statistically different than the phenotypic high group. In the other population, the mean of the genotypic high group was within 90 kg/ha-1 of the mean of the phenotypic high group and was superior to the random group for seed yield. Even with the limited marker coverage, the genotypic selection method used in this study successfully identified lines in PRYTs that would not have been selected due to poor seed yield performance in 2008.

Download or read book The Soybean Genome written by Henry T. Nguyen and published by Springer. This book was released on 2017-09-20 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the application of soybean genome sequences to comparative, structural, and functional genomics. Since the availability of the soybean genome sequence has revolutionized molecular research on this important crop species, the book also describes how the genome sequence has shaped research on transposon biology and applications for gene identification, tilling and positional gene cloning. Further, the book shows how the genome sequence influences research in the areas of genetic mapping, marker development, and genome-wide association mapping for identifying important trait genes and soybean breeding. In closing, the economic and botanical aspects of the soybean are also addressed.

Download or read book Identification of Quantitative Trait Loci QTL Associated with Seed Soyasaponin I Concentration in Soybean Glycine Max L Merril written by Edward MacDonell and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Soybean (Glycine max [L.] Merr.) is the world's largest oilseed crop and also produces soyasaponins, which have nutraceutical properties. Soyasaponin I is the major soyasaponin derived from soybean seeds. Seed soyasaponin I concentration is a quantitative trait, which can be improved through marker-assisted selection. A population of 186 F4-derived recombinant inbred lines from the cross of 'OAC Wallace' and 'OAC Glencoe' and a trial of 40 soybean cultivars were used in this study. Six QTL associated with soyasaponin I were identified through simple and composite interval mapping. Genotype, environment, and genotype-by-environment interactions for soyasaponin I were significant in the cultivar trial and genotype was significant in the mapping population. These results contribute to a better understanding of the genetics of soyasaponin I, the influence of environment and genotype-by-environment interactions on the trait, and provide molecular markers to facilitate marker-assisted selection for soybean cultivars with improved soyasaponin I profiles.

Download or read book Soybean Improvement written by Shabir Hussain Wani and published by Springer Nature. This book was released on 2022-10-17 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soybean (Glycine max L. (Merr)) is one of the most important crops worldwide. Soybean seeds are vital for both protein meal and vegetable oil. Soybean was domesticated in China, and since last 4-5 decades it has become one of the most widely grown crops around the globe. The crop is grown on an anticipated 6% of the world’s arable land, and since the 1970s, the area in soybean production has the highest percentage increase compared to any other major crop. It is a major crop in the United States, Brazil, China and Argentina and important in many other countries. The cultivated soybean has one wild annual relative, G. soja, and 23 wild perennial relatives. Soybean has spread to many Asian countries two to three thousand years ago, but was not known in the West until the 18th century. Among the various constraints responsible for decrease in soybean yields are the biotic and abiotic stresses which have recently increased as a result of changing climatic scenarios at global level. A lot of work has been done for cultivar development and germplasm enhancement through conventional plant breeding. This has resulted in development of numerous high yielding and climate resilient soybean varieties. Despite of this development, plant breeding is long-term by nature, resource dependent and climate dependent. Due to the advancement in genomics and phenomics, significant insights have been gained in the identification of genes for yield improvement, tolerance to biotic and abiotic stress and increased quality parameters in soybean. Molecular breeding has become routine and with the advent of next generation sequencing technologies resulting in SNP based molecular markers, soybean improvement has taken a new dimension and resulted in mapping of genes for various traits that include disease resistance, insect resistance, high oil content and improved yield. This book includes chapters from renowned potential soybean scientists to discuss the latest updates on soybean molecular and genetic perspectives to elucidate the complex mechanisms to develop biotic and abiotic stress resilience in soybean. Recent studies on the improvement of oil quality and yield in soybean have also been incorporated.

Download or read book Identification of Quantitative Trait Loci QTL and Genes Associated with Seed Isoflavone Concentration in Soybean Glycine Max L Merril written by Adam Carter and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Isoflavones are plant secondary metabolites produced by soybean (Glycine-max-[L.] Merr.) that function as phytoalexins in plants and have positive human health benefits. Breeding for soybeans with high seed isoflavones has attracted considerable attention. Soybean seed isoflavones are quantitatively inherited and may be involved in disease resistance. The objectives of this thesis were to: identify quantitative-trait-loci (QTL) and genes associated with seed isoflavones and study the effects of genotype, environment, and genotype-by-environment interaction (GEI) on isoflavones. A population of 109 recombinant inbred lines was developed from the cross RCAT 1004 x DH 4202 and evaluated in four Ontario locations in 2015 and 2016. Significant genotype, environment, and GEI effects were found. Single marker analyses and interval mapping identified 10 and four QTL associated with isoflavones, respectively. Gene expression analyses revealed the importance of the chalcone synthase 7 and 8 (CHS7 and CHS8) genes on isoflavone biosynthesis. The identified QTL and genes can be used in marker assisted selection.

Download or read book Soybean molecular breeding and genetics written by Guo-Liang Jiang and published by Frontiers Media SA. This book was released on 2023-03-29 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Genetics and Genomics of Soybean written by Gary Stacey and published by Springer Science & Business Media. This book was released on 2008-05-07 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soybean genomics is of great interest as one of the most economically important crops and a major food source. This book covers recent advances in soybean genome research, including classical, RFLP, SSR, and SNP markers; genomic and cDNA libraries; functional genomics platforms; genetic and physical maps; and gene expression profiles. The book is for researchers and students in plant genetics and genomics, plant biology and pathology, agronomy, and food sciences.

Download or read book Genetic Validation and its Role in Crop Improvement written by Ahmed Sallam and published by Frontiers Media SA. This book was released on 2022-11-08 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Soybean Breeding written by Felipe Lopes da Silva and published by Springer. This book was released on 2017-06-10 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book was written by soybean experts to cluster in a single publication the most relevant and modern topics in soybean breeding. It is geared mainly to students and soybean breeders around the world. It is unique since it presents the challenges and opportunities faced by soybean breeders outside the temperate world.

Download or read book Identification of Quantitative Trait Loci for Partial Resistance to Phytophthora Sojae in Six Soybean glycine Max L Merr Plant Introductions written by Sungwoo Lee and published by . This book was released on 2013 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: In soybean [Glycine max (L.) Merr.], Phytophthora root and stem rot caused by Phytophthora sojae is one of the destructive diseases that result in economic losses around the world. However, changes in P. sojae populations emphasize the integrated use of Rps gene-mediated resistance with partial resistance for more durable and effective defense. Quantitative trait loci (QTL) for partial resistance to P. sojae have been identified in several studies albeit in only a few genetic sources, primarily the cultivar Conrad. The first objective was to characterize six soybean plant introductions originating from East Asia for QTL conditioning partial resistance to P. sojae. The second objective was to evaluate joint-population QTL analysis (via joint inclusive composite interval mapping, JICIM) for the effectiveness of combining multiple populations with heterogeneous experimental conditions. Four populations were F7:8 and two were F4:6 generations, and they were mapped with partially overlapping sets of molecular markers. Resistance was measured either by lesion length in tray tests, or by root colonization, plant weight, root fresh weight, and root dry weight in layer tests. Conventional bi-parental QTL analysis identified ~12 QTL for a measurement in each population via composite interval mapping (CIM) using MapQTL5, which explained ~58% of total phenotypic variance (PV) in each population. Individually, most QTL explained less than 10% of PV. Interestingly, most of the QTL identified in this study mapped closely to other resistance QTL associated with resistance to other pests or pathogens or R-gene clusters. Joint-population QTL analysis (JICIM) detected the same QTL which were identified in each single-population analysis (Inclusive composite interval mapping, ICIM). In one pair of two populations with the fewest confounding factors, joint-population analysis detected an additional QTL; however this was not identified when all six of the populations were combined. In another population which had 128 RILs, no QTL were identified using the ICIM method compared to 1 QTL identified with MapQTL5. When populations were combined that were evaluated with different phenotypic methods, the same QTL were identified in the combined analysis compared to each population analyzed independently. Thus differences in phenotypic analysis did not largely affect the detection of these QTL. This study identified some limits in the use of joint linkage analysis and parameters for combining populations to detect additional QTL. Detection of additional QTL with this analysis will be enhanced if the populations are advanced beyond the F4, markers are fully integrated into large chromosome segments, and populations are sufficiently large. More importantly, populations which were evaluated with different phenotypic methods can be combined, provided common checks were used and data were normalized with the checks’ values. Many of the QTL identified in these six populations through both analyses overlapped at multiple genomic positions, while many were distinct from QTL identified in Conrad. This suggests that the QTL identified in this study will be useful in diversifying the US soybean cultivars and providing new genes to enhance resistance to P. sojae through breeding.