Determining the linkage of quantitative trait loci to RFLP markers using extreme phenotypes of recombinant inbreds of soybean (Glycine max L. Merr.)

Identification of quantitative trait loci for lodging and related agronomic traits in soybean (Glycine max [L.] Merr.)

BACKGROUND

Lodging, a crucial agronomic trait linked to soybean yield, poses a significant challenge in soybean production. Nevertheless, there has been less research on soybean lodging compared to other important agronomic traits, hindering progress in breeding high-yield soybeans. Our goals were to investigate lodging, pinpoint quantitative trait loci (QTL) linked to lodging, and forecast potential candidate genes linked to this trait. To achieve this, we employed a recombinant inbred line (RIL) population derived from a cross between Guizao 1 and B13 (GB) across various environments.

RESULTS

The lodging score of the RIL population was found to be significantly positively correlated with flowering time, maturity time, plant height, number of main stem nodes, stem diameter, and internode length, with correlation coefficients ranging from 0.457 to 0.783. A total of 84 QTLs associated with soybean lodging and related traits were identified using the GB population. The contribution of phenotypic variance ranged from 1.26 to 66.87%, with LOD scores ranging from 2.52 to 69.22. Additionally, within these QTLs, a stable major QTL associated with lodging was newly discovered in the GB population. Out of the ten major QTLs associated with other related traits, nine of them were situated within the qLD-4-1 interval of the major lodging score locus, displaying phenotypic variations ranging from 12.10 to 66.87%. Specific alterations in gene expression were revealed through the analysis of resequencing data from the two parental lines, potentially indicating their significant roles in lodging. Subsequently, it was determined through qRT-PCR that four genes are likely to be the major genes controlling soybean lodging.

CONCLUSIONS

This study's findings offer valuable insights into the genetic underpinnings of soybean lodging resistance traits. By comprehending the potential genetic factors associated with lodging, this research lays the groundwork for breeding high-yield soybeans with improved lodging resistance.

Identification of two quantitative genes controlling soybean flowering using bulked-segregant analysis and genetic mapping

Photoperiod responsiveness is important to soybean production potential and adaptation to local environments. Varieties from temperate regions generally mature early and exhibit extremely low yield when grown under inductive short-day (SD) conditions. The long-juvenile (LJ) trait is essentially a reduction and has been introduced into soybean cultivars to improve yield in tropical environments. In this study, we used next-generation sequencing (NGS)-based bulked segregant analysis (BSA) to simultaneously map qualitative genes controlling the LJ trait in soybean. We identified two genomic regions on scaffold_32 and chromosome 18 harboring loci LJ32 and LJ18, respectively. Further, we identified LJ32 on the 228.7-kb scaffold_32 as the soybean pseudo-response-regulator gene Tof11 and LJ18 on a 301-kb region of chromosome 18 as a novel PROTEIN FLOWERING LOCUS T-RELATED gene, Glyma.18G298800. Natural variants of both genes contribute to LJ trait regulation in tropical regions. The molecular identification and functional characterization of Tof11 and LJ18 will enhance understanding of the molecular mechanisms underlying the LJ trait and provide useful genetic resources for soybean molecular breeding in tropical regions.

Mapping QTL/QTN and mining candidate genes for plant height and its response to planting densities in soybean [Glycine max (L.) Merr.] through a FW-RIL population

Plant height (PH) determines the morphology and seed yield of soybean, so it is an important breeding target, which is controlled by multiple genes and affected by plant density. In this research, it was used about a four-way recombinant inbred lines (FW-RIL) with 144 families constructed by double cross (Kenfeng 14 × Kenfeng 15) × (Heinong 48 × Kenfeng 19) as experimental materials, with the purpose to map QTL/QTN associated with PH under densities of 2.2×105 plant/ha (D1) and 3×105 plant/ha (D2) in five environments. The results showed that response of PH to densities varied in accordance to genotypes among environments. A total of 26 QTLs and 13 QTNs were identified specifically in D1; 20 QTLs and 21 QTNs were identified specifically in D2. Nine QTLs and one QTN were discovered commonly in two densities. Fifteen QTLs and 9 QTNs were repeatedly detected by multiple statistical methods, densities, or environments, which could be considered stable. Eighteen QTLs were detected, as well as 7 QTNs underlying responses of PH to density increment. Six QTNs, co-located in the interval of QTL, were detected in more than two environments or methods with a longer genome length over 3000 kb. Based on gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, five genes were predicted as candidates, which were likely to be involved in growth and development of PH. The results will help elucidate the genetic basis and improve molecular assistant selection of PH.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01209-0.

Inheritance and Quantitative Trait Locus Mapping of Fusarium Wilt Resistance in Cucumber

Fusarium wilt (FW) is a very serious soil-borne disease worldwide, which usually results in huge yield losses in cucumber production. However, the inheritance and molecular mechanism of the response to FW are still unknown in cucumber (Cucumis sativus L.). In this study, two inbred cucumber lines Superina (P₁) and Rijiecheng (P₂) were used as the sensitive and resistant lines, respectively. A mixed major gene plus polygene inheritance model was used to analyze the resistance to FW in different generations of cucumber, namely, P₁, P₂, F₁ (P₁×P₂), B₁, and B₂, obtained by backcrossing F₁ plants with Superina (B₁) or Rijiecheng (B₂), and F₂, obtained by self-crossing the F₁ plants. After screening 18 genetic models, we chose the E-1 model, which included two pairs of additive-dominance-epistatic major genes and additive-dominance polygenes, as the optimal model for resistance to FW on the basis of fitness tests. The major effect quantitative trait locus (QTL) fw2.1 was detected in a 1.91-Mb-long region of chromosome 2 by bulked-segregant analysis. We used five insertion/deletion markers to fine-map the fw2.1 to a 0.60 Mb interval from 1,248,093 to 1,817,308 bp on chromosome 2 that contained 80 candidate genes. We also used the transcriptome data of Rijiecheng inoculated with Fusarium oxysporum f. sp. cucumerinum (Foc) to screen the candidate genes. Twelve differentially expressed genes were detected in fw2.1, and five of them were significantly induced by FW. The expression levels of the five genes were higher in FW-resistant Rijiecheng inoculated with Foc than in the control inoculated with water. Our results will contribute to a better understanding of the genetic basis of FW resistance in cucumber, which may help in breeding FW-resistant cucumber lines in the future.

Whole Genome Resequencing from Bulked Populations as a Rapid QTL and Gene Identification Method in Rice

Most Quantitative Trait Loci (QTL) and gene isolation approaches, such as positional- or map-based cloning, are time-consuming and low-throughput methods. Understanding and detecting the genetic material that controls a phenotype is a key means to functionally analyzing genes as well as to enhance crop agronomic traits. In this regard, high-throughput technologies have great prospects for changing the paradigms of DNA marker revealing, genotyping, and for discovering crop genetics and genomic study. Bulk segregant analysis, based on whole genome resequencing approaches, permits the rapid isolation of the genes or QTL responsible for the causative mutation of the phenotypes. MutMap, MutMap Gap, MutMap+, modified MutMap, and QTL-seq methods are among those approaches that have been confirmed to be fruitful gene mapping approaches for crop plants, such as rice, irrespective of whether the characters are determined by polygenes. As a result, in the present study we reviewed the progress made by all these methods to identify QTL or genes in rice.

Phenotypic characterization and genetic dissection of nine agronomic traits in Tokachi nagaha and its derived cultivars in soybean (Glycine max (L.) Merr.)

By using the soybean founder parent Tokachi nagaha and its 137 derived cultivars as materials, a genome-wide association analysis was performed to identify the single nucleotide polymorphisms (SNPs) underlying soybean yield and quality related traits at two planting densities. Results of ANOVA showed that genotype, environment, and genotype by environment interaction effects were all significant for each trait. The Tokachi nagaha-derived soybean population could be divided into two subpopulations based on molecular data, and accessions in each subpopulation were almost all from the same Chinese province. Relatedness was detected between pair-wise accessions within the population. Linkage disequilibrium was obvious and the level of intra-chromosome linkage disequilibrium was about 8370kb. A total of 40 SNPs with significant signal were detected and distributed across 18 chromosomes. Some SNP markers were located in or near regions where QTLs have been previously mapped by linkage analysis. Nineteen SNPs were identified both in low- and high- density planting treatments, indicating those loci were common and sTable Sixteen SNPs were co-associated with two or more different traits, suggesting that some of the QTLs/genes underlying those identified SNPs were likely to be pleiotropic.

Next-Generation Sequencing from Bulked-Segregant Analysis Accelerates the Simultaneous Identification of Two Qualitative Genes in Soybean

Next-generation sequencing (NGS)-based bulked-segregant analysis (BSA) approaches have been proven successful for rapidly mapping genes in plant species. However, most such methods are based on mutants and usually only one gene controlling the mutant phenotype is identified. In this study, NGS-based BSA was employed to map simultaneously two qualitative genes controlling cotyledon color of seed in soybean. Yellow-cotyledon (YC) and green-cotyledon (GC) bulks from progenies of a biparental population (Zhonghuang 30 × Jiyu 102) were sequenced. The SNP-index of each SNP locus in YC and GC bulks was calculated and two genomic regions on chromosomes 1 and 11 harboring, respectively, loci qCC1 and qCC2 were identified by Δ(SNP-index) analysis. These two BSA-seq-derived loci were further validated with SSR markers and fine-mapped. qCC1 was mapped to a 30.7-kb region containing four annotated genes and qCC2 was mapped to a 67.7-kb region with nine genes. These two regions contained, respectively, genes D1 and D2, which had previously been identified by homology-based cloning as being associated with cotyledon color. Sequence analysis of the NGS data also identified a frameshift deletion in the coding region of D1. These results suggested that BSA-seq could accelerate the mapping of loci controlling qualitative traits, even if a trait is controlled by more than one locus.

Genetic mapping of QTL for maize weevil resistance in a RIL population of tropical maize

A tropical RIL maize population was subjected to phenotypic and genotypic analysis for maize weevil resistance during four seasons, and three main genomic areas were detected as main QTLs. The maize weevil (Sitophilus zeamais) (MW) is a common and important pest of stored maize (Zea mays) worldwide, especially in tropical areas. Quantitative trait loci (QTLs) associated with the MW have been analyzed previously in an F2 maize population. In this work, new germplasm-based F6 recombinant inbred line (RIL) families, derived from the cross of Population 84 and Kilima, were analyzed using insect bioassays during four seasons. The parameters analyzed for MW resistance were grain weight losses (GWL), adult progeny (AP), and flour production (FP). Composite interval mapping identified a total of 15 QTLs for MW parameters located on six chromosomes, explaining between 14 and 51 % of phenotypic variation (σ p (2) ) and 27 and 81 % of genotypic variation (σ g (2) ). The QTL obtained for GWL was located in bin 2.05, which explained 15 % of σ p (2) . For AP and FP, the QTLs were located on regions 1.09 and 2.05, explaining 7 and 15 % of σ p (2) , respectively. Comparative analysis between F2 and F6 families showed similarities in QTL localization; three main regions were co-localized in chromosomes 4.08, 10.04, and 10.07, where no resistance-associated genes have been reported previously. These regions could be used for a marker-assisted selection in breeding programs for MW resistance in tropical maize.

Genetic control of soybean seed oil: II. QTL and genes that increase oil concentration without decreasing protein or with increased seed yield

Soybean [Glycine max (L.) Merrill] seed oil is the primary global source of edible oil and a major renewable and sustainable feedstock for biodiesel production. Therefore, increasing the relative oil concentration in soybean is desirable; however, that goal is complex due to the quantitative nature of the oil concentration trait and possible effects on major agronomic traits such as seed yield or protein concentration. The objectives of the present study were to study the relationship between seed oil concentration and important agronomic and seed quality traits, including seed yield, 100-seed weight, protein concentration, plant height, and days to maturity, and to identify oil quantitative trait loci (QTL) that are co-localized with the traits evaluated. A population of 203 F4:6 recombinant inbred lines, derived from a cross between moderately high oil soybean genotypes OAC Wallace and OAC Glencoe, was developed and grown across multiple environments in Ontario, Canada, in 2009 and 2010. Among the 11 QTL associated with seed oil concentration in the population, which were detected using either single-factor ANOVA or multiple QTL mapping methods, the number of QTL that were co-localized with other important traits QTL were six for protein concentration, four for seed yield, two for 100-seed weight, one for days to maturity, and one for plant height. The oil-beneficial allele of the QTL tagged by marker Sat_020 was positively associated with seed protein concentration. The oil favorable alleles of markers Satt001 and GmDGAT2B were positively correlated with seed yield. In addition, significant two-way epistatic interactions, where one of the interacting markers was solely associated with seed oil concentration, were identified for the selected traits in this study. The number of significant epistatic interactions was seven for yield, four for days to maturity, two for 100-seed weight, one for protein concentration, and one for plant height. The identified molecular markers associated with oil-related QTL in this study, which also have positive effects on other important traits such as seed yield and protein concentration, could be used in the soybean marker breeding programs aimed at developing either higher seed yield and oil concentration or higher seed protein and oil concentration per hectare. Alternatively, selecting complementary parents with greater breeding values due to positive epistatic interactions could lead to the development of higher oil soybean cultivars.

QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations

The majority of agronomically important crop traits are quantitative, meaning that they are controlled by multiple genes each with a small effect (quantitative trait loci, QTLs). Mapping and isolation of QTLs is important for efficient crop breeding by marker-assisted selection (MAS) and for a better understanding of the molecular mechanisms underlying the traits. However, since it requires the development and selection of DNA markers for linkage analysis, QTL analysis has been time-consuming and labor-intensive. Here we report the rapid identification of plant QTLs by whole-genome resequencing of DNAs from two populations each composed of 20-50 individuals showing extreme opposite trait values for a given phenotype in a segregating progeny. We propose to name this approach QTL-seq as applied to plant species. We applied QTL-seq to rice recombinant inbred lines and F2 populations and successfully identified QTLs for important agronomic traits, such as partial resistance to the fungal rice blast disease and seedling vigor. Simulation study showed that QTL-seq is able to detect QTLs over wide ranges of experimental variables, and the method can be generally applied in population genomics studies to rapidly identify genomic regions that underwent artificial or natural selective sweeps.

Genetic control of soybean seed oil: I. QTL and genes associated with seed oil concentration in RIL populations derived from crossing moderately high-oil parents

Soybean seed is a major source of oil for human consumption worldwide and the main renewable feedstock for biodiesel production in North America. Increasing seed oil concentration in soybean [Glycine max (L.) Merrill] with no or minimal impact on protein concentration could be accelerated by exploiting quantitative trait loci (QTL) or gene-specific markers. Oil concentration in soybean is a polygenic trait regulated by many genes with mostly small effects and which is negatively associated with protein concentration. The objectives of this study were to discover and validate oil QTL in two recombinant inbred line (RIL) populations derived from crosses between three moderately high-oil soybean cultivars, OAC Wallace, OAC Glencoe, and RCAT Angora. The RIL populations were grown across several environments over 2 years in Ontario, Canada. In a population of 203 F(3:6) RILs from a cross of OAC Wallace and OAC Glencoe, a total of 11 genomic regions on nine different chromosomes were identified as associated with oil concentration using multiple QTL mapping and single-factor ANOVA. The percentage of the phenotypic variation accounted for by each QTL ranged from 4 to 11 %. Of the five QTL that were tested in a population of 211 F(3:5) RILs from the cross RCAT Angora × OAC Wallace, a "trait-based" bidirectional selective genotyping analysis validated four QTL (80 %). In addition, a total of seven two-way epistatic interactions were identified for oil concentration in this study. The QTL and epistatic interactions identified in this study could be used in marker-assisted introgression aimed at pyramiding high-oil alleles in soybean cultivars to increase oil concentration for biodiesel as well as edible oil applications.

Genetic resolution and verification of quantitative trait loci for flowering and plant height with recombinant inbred lines of maize

Recombinant inbred (RI) lines offer several advantages for detecting quantitative trait loci (QTLs), including increased precision of trait measurements, power for detection of additive effects, and resolution of linked QTLs. This study was conducted to detect and characterize QTLs in maize for flowering and plant height and to compare QTL detection in an early (F2:3) generation of the same population. One hundred and eighty-six RIs from a cross between inbred lines Mo17 and H99 were evaluated in a replicated field experiment and analyzed at 101 loci detected by restriction fragment length polymorphisms. QTLs were identified by single-factor analysis of variance. A total of 59 QTLs were detected for plant height, ear height, top height, anthesis, silk emergence, and anthesis to silk interval. Individual QTLs explained 2.2-15.4% of trait variation, and multiple models including all QTLs detected for a trait explained up to 52.5% of the phenotypic variation. Comparison of QTLs detected with 150 F2:3 lines from the same population indicated that 16 (70%) of the 23 F2:3 QTLs were also observed in the F6:7 generation. Parental effects were consistent across generations. At 14 of the 16 QTLs detected in both generations, genetic effects were smaller in the F6:7. Also, some QTLs detected in the F2:3 were resolved into multiple linked QTLs in the F6:7, indicating the additional power of RI populations for mapping, with important implications for marker-assisted selection as well as map-based cloning of QTLs. Key words : Zea mays, RFLP, plant breeding, genetics, recombination.

Multi-environment mapping and meta-analysis of 100-seed weight in soybean

100-Seed weight (100-SW) of soybean is an important but complicated quantitative trait to yield. This study was focus on the quantitative trait loci (QTLs) of soybean 100-SW from 2006 to 2010, using recombination inbred lines population that was derived from a cross between Charleston and Dongnong 594. A total of 23 QTLs for 100-SW were detected in the linkage group C2, D1a, F, G and O. Nine QTLs were identified by composite interval mapping including one QTL with the minimum confidence interval (CI) of 1.3 cM, while 14 QTLs by multiple interval mapping. Furthermore, 94 reported QTLs of 100-SW were integrated with our QTL mapping results using BioMercator. As a result, 15 consensus QTLs and their corresponding markers were identified. The minimum CI was reduced to 1.52 cM by the combination of meta-analysis. These findings may merit fine-mapping of these QTL in soybean.

Mapping quantitative trait loci for seed size traits in soybean (Glycine max L. Merr.)

Seed size traits in soybean--length, width and thickness--and their corresponding ratios--length-to-width, length-to-thickness and width-to-thickness--play a crucial role in determining seed appearance, quality and yield. In this study, an attempt was made to detect quantitative trait loci (QTL) for the aforementioned seed size traits in F(2:3), F(2:4) and F(2:5) populations from the direct and reciprocal crosses of Lishuizhongzihuang with Nannong 493-1, using multi-QTL joint analysis (MJA) along with composite interval mapping (CIM). A total of 121 main-effect QTL (M-QTL), six environmental effects, eight environment-by-QTL interactions, five cytoplasmic effects and 92 cytoplasm-by-QTL interactions were detected. Fifty-two common M-QTL across MJA and CIM, 21 common M-QTL in more than two populations and 5 M-QTL in all three populations showed the stability of the results. Five M-QTL had higher heritability, greater than 20%. In addition, 28 cytoplasm-by-QTL and 4 environment-by-QTL interactions were confirmed by CIM. Most M-QTL were clustered in eight chromosomal regions. Our results provide a good foundation for fine mapping, cloning and designed molecular breeding of favorable genes related to soybean seed size traits.

A soybean mapping population specific to the early soybean production system

The objective of this research was to create a soybean [Glycine max (L.) Merr] genetic resource in the form of a publicly available, well-characterized mapping population specific to maturity groups (MG) used in the early soybean production system. A total of 568 simple sequence repeat (SSR) markers were tested for polymorphism between soybean breeding line DS97-84-1 (MG IV) and germplasm line DT97-4290 (MG IV). A 90-genotype subset of an F2 population from a cross between these lines was evaluated for genetic linkage using 162 polymorphic SSRs, plant height, pod color (L2/l2), flower color (W1/w1) and stem termination (Dt1/dt1). A 1514 cM (Kosambi) genetic map covering 65% of the soybean genome based on 157 linked SSR markers was created. Comparison with the composite soybean genetic map was used to verify map order. Loci for pod color, flower color and stem termination fell in the expected position on the map indicating this is a normally segregating mapping population. Loci for height were identified on linkage groups C2, D1a, D1b, H, L, M and O. MG IV and V soybean genotypes are critical for the early soybean production system widely used in the midsouthern US. However, only two mapping populations have been reported in Soybase for MG IV and V genotypes. Additionally, the parents used in this cross are known to differ in their response to soybean cyst nematode and charcoal rot, which constitute two major pathology threats to Midsouth soybean production. The population and map reported herein represent an important genetic resource for the early soybean production system.

Genetic mapping of seed shape in three populations of recombinant inbred lines of soybean (Glycine max L. Merr.)

Round soybean seeds are sought-after for food-type soybean. Also the genetic control of seed geometry is of scientific interest. The objectives of this study were to estimate heritability and map quantitative trait loci (QTLs) responsible for seed shape traits. Three densely mapped recombinant inbred populations each with 192 segregants were used, Minsoy x Archer, Minsoy x Noir1, and Noir1 x Archer. A two rep two location experiment was conducted in Los Andes, Chile, and East Lansing, MI, USA. Seed height (SH), width (SW), length (SL), and seed volume (SV) as width x height x length were measured to determine seed shape. Heritability was estimated by variance component analysis. A total of 19 significant QTLs (LOD >or= 3.7) in ten linkage groups (LG) were detected for all the traits. Only one QTL was stable across populations and environments and six were stable in at least two populations in both environments. The amount of phenotypic variation explained by a single QTL varied from 7.5% for SH, to 18.5% for SW and at least 30% of the genetic variation for the traits is controlled by four QTL or less. All traits were highly correlated with each other in all populations with values ranging from 0.5 to 0.9, except for SL and SW that were not significantly correlated or had a low correlation in all populations. Narrow sense heritabilities for all traits ranged from 0.42 to 0.88. We note that LG u9, u11, and u14 are hot points of the genome for QTLs for various traits. The number and genomic distribution of the QTLs confirms the complex genetic control of seed shape. Transgressive segregation was observed for all traits suggesting that careful selection of parents with similar phenotypes but different genotypes using molecular markers can result in desirable transgressive segregants.

Seed quality QTL in a prominent soybean population

Soybean [Glycine max (L.) Merr.] is a versatile crop due to its multitude of uses as a high protein meal and vegetable oil. Soybean seed traits such as seed protein and oil concentration and seed size are important quantitative traits. The objective of this study was to identify representative protein, oil, and seed size quantitative trait loci (QTL) in soybean. A recombinant inbred line (RIL) population consisting of 131 F6-derived lines was created from two prominent ancestors of North American soybeans ('Essex' and 'Williams') and the RILs were grown in six environments. One hundred simple sequence repeat (SSR) markers spaced throughout the genome were mapped in this population. There were a total of four protein, six oil, and seven seed size QTL found in this population. The QTL found in this study may assist breeders in marker-assisted selection (MAS) to retain current positive QTL in modern soybeans while simultaneously pyramiding additional QTL from new germplasm.

Identification of putative QTL that underlie yield in interspecific soybean backcross populations

Glycine soja, the wild progenitor of soybean, is a potential source of useful genetic variation in soybean improvement. The objective of our study was to map quantitative trait loci (QTL) from G. soja that could improve the crop. Five populations of BC(2)F(4)-derived lines were developed using the Glycine max cultivar IA2008 as a recurrent parent and the G. soja plant introduction (PI) 468916 as a donor parent. There were between 57 and 112 BC(2)F(4)-derived lines in each population and a total of 468 lines for the five populations. The lines were evaluated with simple sequence repeat markers and in field tests for yield, maturity, plant height, and lodging. The field testing was done over 2 years and at two locations each year. Marker data were analyzed for linkage and combined with field data to identify QTL. Using an experimentwise significance threshold of P=0.05, four yield QTL were identified across environments on linkage groups C2, E, K, and M. For these yield QTL, the IA2008 marker allele was associated with significantly greater yield than the marker allele from G. soja. In addition, one lodging QTL, four maturity QTL, and five QTL for plant height were identified across environments. Of the 14 QTL identified, eight mapped to regions where QTL with similar effects were previously mapped. Many regions carrying the yield QTL were also significant for other traits, such as plant height and lodging. When the significance threshold was reduced and the data were analyzed with simple linear regression, four QTL with a positive allele for yield from G. soja were mapped. One epistatic interaction between two genetic regions was identified for yield using an experimentwise significance threshold of P=0.05. Additional research is needed to establish whether multiple trait associations are the result of pleiotropy or genetic linkage and to retest QTL with a positive effect from G. soja.

Simple sequence repeat (SSR) markers linked to E1, E3, E4, and E7 maturity genes in soybean

Soybean near isogenic lines (NILs), contrasting for maturity and photoperiod sensitivity loci, were genotyped with approximately 430 mapped simple sequence repeats (SSRs), also known as microsatellite markers. By analysis of allele distributions across the NILs, it was possible to confirm the map location of the Dt1 indeterminate growth locus, to refine the SSR mapping of the T tawny pubescence locus, to map E1 and E3 maturity loci with molecular markers, and to map the E4 and E7 maturity loci for the first time. Molecular markers flanking these loci are now available for marker-assisted breeding for these traits. Analysis of map locations identified a putative homologous relationship among four chromosomal regions; one in the middle of linkage group (LG) C2 carrying E1 and E7, one on LG I carrying E4, one at the top of LG C2, at which there is a reproductive period quantitative trait locus (QTL), and the fourth on LG B1. Other evidence suggests that homology also exists between the E1 + E7 region on LG C2 and a region on LG L linked to a pod maturity QTL. Homology relationships predict possible locations in the soybean genome of additional maturity loci, as well as which maturity loci may share a common evolutionary origin and similar mechanism(s) of action.

A localized linkage map of the citrus tristeza virus resistance gene region

A localized genetic linkage map was developed of the region surrounding the citrus tristeza virus (CTV) resistance gene (designated Ctv) from Poncirus trifoliate L., a sexually compatible Citrus relative. Bulked segregant analysis (BSA) was used to identify potential resistance-associated RAPD fragment markers in four intergeneric backcross families that were segregating for CTV resistance. Eight RAPD fragments were found that were consistently linked to Ctv in the four families. Map distances and locus order were determined with MAPMAKER 3.0, using the results obtained from 59 individuals in the largest family. Also, a consensus map was constructed with JOINMAP 1.3, using pooled results from the four backcross families. Marker orders were identical, except for 1 marker, on these independently developed maps. Family-specific resistance-associated markers were also identified, as were numerous susceptibility-associated markers. The identification of markers tightly linked to Ctv will enable citrus breeders to identify plants likely to be CTV-resistant by indirect, marker-assisted selection, rather than by labor-intensive direct challenge with the pathogen. These markers also provide a basis for future efforts to isolate Ctv for subsequent genetic manipulation.

Quantitative trait locus analysis of a recombinant inbred line population derived from a Lycopersicon esculentum x Lycopersicon cheesmanii cross

Quantitative trait loci influencing fruit traits were identified by restriction fragment length polymorphism (RFLP) analysis in a population of recombinant inbred lines (RIL) derived from a cross of the cultivated tomato, Lycopersicon esculentum with a related wild species Lycopersicon cheesmanii. One hundred thirty-two polymorphic RFLP loci spaced throughout the tomato genome were scored for 97 F8 RIL families. Fruit weight and soluble solids were measured in replicated trials during 1991 and 1992. Seed weight was measured in 1992. Significant (P<0.01 level) quantitative trait locus (QTL) associations of marker loci were identified for each trait. A total of 73 significant marker locus-trait associations were detected for the three traits measured. Fifty-three of these associations were for fruit weight and soluble solids, many of which involved marker loci signficantly associated with both traits. QTL with large effects on all three traits were detected on chromosome 6. Greater homozygosity at many loci in the RIL population as compared to F2 populations and greater genomic coverage resulted in increased precision in the estimation of QTL effects, and large proportions of the total phenotypic variance were explained by marker class variation at significant marker loci for many traits. The RIL population was effective in detecting and discriminating among QTL for these traits previously identified in other investigations despite skewed segregation ratios at many marker loci. Large additive effects were measured at significant marker loci. Lower fruit weight, higher soluble solids, and lower seed weight were generally associated with RFLP alleles from theL. cheesmanii parent.

Recombinant inbred lines for genetic mapping in tomato

A cross between the cultivated tomato Lycopersicon esculentum and a related wild species L. cheesmanii yielded 97 recombinant inbred lines (RILs) which were used to construct a genetic map consisting of 132 molecular markers. Significant deviation from the expected 1:1 ratio between the two homozygous classes was found in 73% of the markers. In 98% of the deviating markers, L. esculentum alleles were present in greater frequency than the L. cheesmanii alleles. For most of the markers with skewed segregation, the direction of the deviation was maintained from F2 to F7 generations. The average heterozygosity in the population was 15%. This value is significantly greater than the 1.5% heterozygosity expected for RILs in the F7 generation. On average, recombination between linked markers was twice as high in the RILs than in the F2 population used to derive them. The utility of RILs for the mapping of qualitative and quantitative traits is discussed.

Epistatic expression of quantitative trait loci (QTL) in soybean [Glycine max (L.) Merr.] determined by QTL association with RFLP alleles

Quantitative trait values for seed oil and protein content or for maturity were measured in recombinant inbred lines (RIL) of soybean derived from a cross between two soybean cultivars: 'Minsoy' PI 27890 and 'Noir 1' PI 290136. Seed oil was found to be inversely correlated to protein content. By analyzing DNA from plants with extreme phenotypes, we were able to identify quantitative trait loci (QTL) for these traits as being linked to several restriction fragment length polymorphism (RFLP) loci, including R183 for oil and protein content and R79 for maturity. Cumulative distributions of trait values were graphed for those RIL with 'Minsoy' alleles and for those with 'Noir 1' alleles. As already suggested by the alleles found associated with extreme phenotypes, the distributions were consistent with an independent and additive expression of the maturity QTL linked to R79. That is, the cumulative distributions for plants with 'Minsoy' alleles and for plants with 'Noir 1' alleles were similar in shape, but the entire 'Noir 1' curve had been shifted to later maturity dates. In contrast, the trait distributions for a locus affecting oil and protein content linked to R183 were not compatible with an additive model. These results suggest that this approach can be used for rapid identification of QTLs with epistatic expression.

Interval mapping of quantitative trait loci for reproductive, morphological, and seed traits of soybean (Glycine max L.)

Quantitative trait loci (QTL) were mapped in segregating progeny from a cross between two soybean (Glycine max (L.) Merr.) cultivars: 'Minsoy' (PI 27.890) and 'Noir 1' (PI 290.136). The 15 traits analyzed included reproductive, morphological, and seed traits, seed yield and carbon isotope discrimination ratios ((13)C/(12)C). Genetic variation was detected for all of the traits, and transgressive segregation was a common phenomenon. One hundred and thirty-two linked genetic markers and 24 additional unlinked markers were used to locate QTL by interval mapping and one-way analysis of variance, respectively. Quantitative trait loci controlling 11 of the 15 traits studied were localized to intervals in 6 linkage groups. Quantitative trait loci for developmental and morphological traits (R1, R5, R8, plant height, canopy height, leaf area, etc.) tended to be clustered in three intervals, two of which were also associated with seed yield. Quantitative trait loci for seed oil were separated from all the other QTL. Major QTL for maturity and plant height were linked to RFLP markers R79 (31% variation) and G173 (53% variation). Quantitative trait loci associated with unlinked markers included possible loci for seed protein and weight. Linkage between QTL is discussed in relation to the heritability and genetic correlation of the traits.

A genetic map of soybean (Glycine max L.) using an intraspecific cross of two cultivars: 'Minosy' and 'Noir 1'

Genetic markers were mapped in segregating progeny from a cross between two soybean (Glycine max (L.) Merr.) cultivars: 'Minsoy' (PI 27.890) and 'Noir 1' (PI 290.136). A genetic linkage map was constructed (LOD [Symbol: see text] 3), consisting of 132 RFLP, isozyme, morphological, and biochemical markers. The map defined 1550cM of the soybean genome comprising 31 linkage groups. An additional 24 polymorphic markers remained unlinked. A family of RFLP markers, identified by a single probe (hybridizing to an interspersed repeated DNA sequence), extended the map, linking other markers and defining regions for which other markers were not available.