Selective Genotyping for Marker Assisted Selection Strategies for Soybean Yield Improvement

The relatively low genomic variation of current U.S. soybean [Glycine max (L.) Merill] cultivars constrains the improvement of grain yield, seed quality, and other agronomic traits within soybean breeding programs. Recently, a substantial effort has been undertaken to introduce novel genetic diversity present in wild soybean (Glycine soja Siebold and Zucc.) into new elite cultivars, in both public and private applied soybean breeding programs. The objectives of this research were to evaluate the phenotypic diversity within a core collection of 80 G. soja plant introductions (PIs) in the United States Department of Agriculture National Genetic Resources Program that were collected in China, Japan, Russia, and South Korea, and to analyze the correlations between agronomic and seed composition traits. Field tests were conducted in Missouri and North Carolina during three years, 2013, 2014, and 2015, in a randomized complete block design (n=3). The phenotypic data collected included plant maturity date, seed weight, and the seed concentration of protein, oil, essential amino acid, fatty acid, and soluble carbohydrates. Analyzing the data from six environments, we found genotype was a significant (p less than 0.0001) source of variation for maturity date, seed weight, seed protein and amino acids, seed oil and fatty acids, and seed carbohydrates. Significant correlations were observed between numerous traits. The core collection had lower seed weight, higher seed content of protein, linolenic acid, raffinose and stachyose but lower seed content of oil and oleic acid than those of the cultivated soybean lines that were used as checks. The amino acid profile of the core collection was significantly different from that of the checks. An association analysis revealed 19 SNP that were significantly associated with maturity, seed weight, and seed contents of aspartic acid, glutamine, palmitic acid, oleic acid, and linoleic acid. The information and data collected in this study will be invaluable in guiding soybean breeders and geneticists in selecting promising Glycine soja plant introductions for research and cultivar improvement. In addition the identification of quantitative trait loci (QTLs) associated with the contents of seed protein and oil, maturity, branching traits, height, lodging, and yield in a recombinant inbred line (RIL) population developed from one single F2 plant from the cross between Osage and PI593983 was carried out. The mapping population in this study included 164 F4:6 recombinant inbred lines (RILs) derived from a cross between Osage, a cultivated soybean variety, and PI593983, a wild soybean accession. Field tests were carried out in Missouri for two years during 2016 and 2017, in a randomized complete block design (n=2). Both protein and oil contents showed high heritabilities. Seed protein and seed oil were negatively correlated (-0.77). A total of 4,374 polymorphic markers were used to construct a genetic linkage map, and nine QTLs for protein content, explained 7.6 to 36.7% of variance, and seven QTLs for oil content, explained for 7.8 to 29.7% of variance, were detected using composite interval mapping. addition we identified eight novel QTLs and confirmed sixteen QTLs associated with maturity (R2 = 6.4 to 26.3%), plant height (R2 = 7.4 to 15.5%), and total branch length (R2 = 9.3% and 14.5%) in individual and across environments, and the ratio of total branch length to plant height (R2 = 11.8%), yield (R2 =12.8 and 15.7), and lodging (R2 = 12.1 and 13.4) in individual studied environments. Sixteen QTLs for maturity, yield, and plant height confirmed previously reported QTLs, and eight QTLs have not been reported before. The results of this study will facilitate the identification of the causative genes for seed protein and oil, maturity, height, lodging, and branching traits, and will help soybean breeder improve soybean performance by developing markers for marker-assisted selection.

BackgroundMany large-effect quantitative trait loci (QTLs) for yield and disease resistance related traits have been identified in different mapping populations of peanut (Arachis hypogaea L.) under multiple environments. However, only a limited number of QTLs have been used in marker-assisted selection (MAS) because of unfavorable epistatic interactions between QTLs in different genetic backgrounds. Thus, it is essential to identify consensus QTLs across different environments and genetic backgrounds for use in MAS. Here, we used QTL meta-analysis to identify a set of consensus QTLs for yield and disease resistance related traits in peanut.ResultsA new integrated consensus genetic map with 5874 loci was constructed. The map comprised 20 linkage groups (LGs) and was up to a total length of 2918.62 cM with average marker density of 2.01 loci per centimorgan (cM). A total of 292 initial QTLs were projected on the new consensus map, and 40 meta-QTLs (MQTLs) for yield and disease resistance related traits were detected on four LGs. The genetic intervals of these consensus MQTLs varied from 0.20 cM to 7.4 cM, which is narrower than the genetic intervals of the initial QTLs, meaning they may be suitable for use in MAS. Importantly, a region of the map that previously co-localized multiple major QTLs for pod traits was narrowed from 3.7 cM to 0.7 cM using an overlap region of four MQTLs for yield related traits on LG A05, which corresponds to a physical region of about 630.3 kb on the A05 pseudomolecule of peanut, including 38 annotated candidate genes (54 transcripts) related to catalytic activity and metabolic process. Additionally, one major MQTL for late leaf spot (LLS) was identified in a region of about 0.38 cM. BLAST searches identified 26 candidate genes (30 different transcripts) in this region, some of which were annotated as related to regulation of disease resistance in different plant species.ConclusionsCombined with the high-density marker consensus map, all the detected MQTLs could be useful in MAS. The biological functions of the 64 candidate genes should be validated to unravel the molecular mechanisms of yield and disease resistance in peanut.

Yield under drought stress is a highly complex trait with large influence to even a minor fluctuation in the environmental conditions. Genomics-assisted breeding holds great promise for improving such complex traits more efficiently in less time, but requires markers associated with the trait of interest. In this context, a recombinant inbred line mapping population (TAG 24 × ICGV 86031) was used to identify markers associated with quantitative trait loci (QTLs) for yield and yield related traits at two important locations of West Africa under well watered and water stress conditions. Among the traits analyzed under WS condition, the harvest index (HI) and the haulm yield (HYLD) were positively correlated with the pod yield (PYLD) and showed intermediate broad sense heritability. QTL analysis using phenotyping and genotyping data resulted in identification of 52 QTLs. These QTLs had low phenotypic variance (<12 %) for all the nine traits namely plant height, primary branching, SPAD chlorophyll meter reading, percentage of sound mature kernels, 100 kernel weight, shelling percentage, HI, HYLD and PYLD. Interestingly, few QTLs identified in this study were also overlapped with previously reported QTLs detected for drought tolerance related traits identified earlier in Indian environmental conditions using the same mapping population. Accumulating these many small-effect QTLs into a single genetic background is nearly impossible through marker-assisted backcrossing and even marker-assisted recurrent selection. Under such circumstances, the deployment of genomic selection is the most appropriate approach for improving such complex traits with more precision and in less time.Electronic supplementary materialThe online version of this article (doi:10.1007/s10681-015-1472-6) contains supplementary material, which is available to authorized users.

White mold disease (WM) of common bean (Phaseolus vulgaris L.), caused by Sclerotinia sclerotiorum (Lib.) de Bary, reduces crop yield and quality throughout the United States. The development of cultivars with resistance to WM would be facilitated by the identification and use of molecular markers linked to resistance genes. The objectives of this research were (i) to characterize WM reaction in a recombinant inbred line (RIL) population derived from a cross between resistant and susceptible germplasm, (ii) to validate the effect of a previously reported quantitative trait locus (QTL) for WM resistance, and (iii) to locate additional QTL associated with WM resistance. A RIL population that consisted of 94 lines was derived from a cross between G122 (resistant) and CO72548 (susceptible). The population was evaluated for WM reaction in three greenhouse tests and one field environment, and for molecular markers throughout the genome. Two RIL were identified with higher resistance levels (P &lt; 0.05) than the resistant parent G122. A previously reported QTL on linkage group B7 was significant (P &lt; 0.01) in single‐factor analysis of variance, but not with composite interval mapping. Five QTL for resistance to WM were found (likelihood odds ratio [LOD] &gt; 2.7) on linkage groups B1, B2b, B8, and B9. The QTL were contributed from both parents and together accounted for 48% of the phenotypic variation (R2). For field resistance, one QTL (R2 = 12%) on linkage group B8 was detected. These results confirm polygenic resistance to WM in common bean.

ABSTRACTIn order to breed efficiently, it is necessary to identify individual quantitative trait loci (QTLs) as well as interactions between these loci and to determine which QTLs produce phenotypes that are environment specific. This can be done by linking QTLs to molecular markers. The objective of this research was to carry out such an analysis for yield, one of the most complex agronomic traits. To do this, recombinant inbred lines of soybean [Glycine max (L.) Merrill] were characterized for molecular genetic markers and analyzed for yield in different environments. Interactions between QTLs were identified by subdividing the segregants into four sub‐populations defined by molecular alleles at pairs of unlinked loci. Differences in the mean yields of these sub‐populations defined interactions between QTLs. Measurements of yield in genotyped, recombinant inbred populations derived from crosses of ‘Minsoy’ with ‘Archer’ (MA population) and ‘Noir 1’ with Archer (NA population) have identified a pair of interacting yield QTLs whose effect was independent of environment as well as a pair of loci whose interaction was environment specific. Each example of epistasis, involved an allele specific interaction between the two QTLs. In the NA population, a pair of QTLs was identified in which Noir 1 alleles interact to specify a significant increase in yield that is not environment specific. These loci, located on linkage groups (LG) U3 and U9, do not affect either height or maturity. In all environments, the interaction between the QTLs was significant. In the MA population, a pair of QTLs was identified in which the Minsoy alleles interact to specify a significant increase in yield. However, this significant interaction is environment specific. One of the loci (on LG U14) is also associated with effects on height, seed weight, and maturity that are found in other environments, but these latter effects do not appear to involve any interactions with other loci. The data from the MA population support the concept that interactions between QTLs also can result in location‐specific effects on quantitative traits.

An F1 derived doubled haploid (DH) population of 402 lines from the adapted spring wheat cross Superb (high yielding)/BW278 (low yielding) was developed to identify quantitative trait loci (QTL) associated with yield and yield components. A subset of the population (186 lines) was evaluated in replicated field trials in 2001 and 2002 at six locations in Manitoba and Saskatchewan, Canada. Agronomic parameters, grain yield and yield components including 1,000 grain weight, harvest index, average seed weight spike(-1), seed number spike(-1) and spikes number m(-2) were measured. A genetic map was constructed with 268 microsatellite marker loci and included two morphological genes, reduced plant height, Rht-B1b, and the presence/absence of awns, B1. Composite interval mapping was conducted to estimate the location and effect of QTL associated with the evaluated traits. A total of 53 QTL were identified on 12 chromosomes for the 9 evaluated traits with the coefficient of determination ranging from 0.03 to 0.21 of the total variation. The increase in yield and yield components ranged from 4.5 to 17.1% over the population mean. The five grain yield QTL were detected on chromosomes 1A, 2D, 3B, and 5A and showed a combined increase of 34.4%, over the population mean. The alleles from Superb were associated with increased yield for four of the five QTL. This study identified potential chromosome segments for use in marker-assisted selection to improve yield and yield components in spring wheat.

Plant height (PH) is an important agronomic trait that is closely related to soybean yield and quality. However, it is a complex quantitative trait governed by multiple genes and is influenced by environment. Unraveling the genetic mechanism involved in PH, and developing soybean cultivars with desirable PH is an imperative goal for soybean breeding. In this regard, the present study used high-density linkage maps of two related recombinant inbred line (RIL) populations viz., MT and ZM evaluated in three different environments to detect additive and epistatic effect quantitative trait loci (QTLs) as well as their interaction with environments for PH in Chinese summer planting soybean. A total of eight and 12 QTLs were detected by combining the composite interval mapping (CIM) and mixed-model based composite interval mapping (MCIM) methods in MT and ZM populations, respectively. Among these QTLs, nine QTLs viz., QPH-2, qPH-6-2MT, QPH-6, qPH-9-1ZM, qPH-10-1ZM, qPH-13-1ZM, qPH-16-1MT, QPH-17 and QPH-19 were consistently identified in multiple environments or populations, hence were regarded as stable QTLs. Furthermore, Out of these QTLs, three QTLs viz., qPH-4-2ZM, qPH-15-1MT and QPH-17 were novel. In particular, QPH-17 could detect in both populations, which was also considered as a stable and major QTL in Chinese summer planting soybean. Moreover, eleven QTLs revealed significant additive effects in both populations, and out of them only six showed additive by environment interaction effects, and the environment-independent QTLs showed higher additive effects. Finally, six digenic epistatic QTLs pairs were identified and only four additive effect QTLs viz., qPH-6-2MT, qPH-19-1MT/QPH-19, qPH-5-1ZM and qPH-17-1ZM showed epistatic effects. These results indicate that environment and epistatic interaction effects have significant influence in determining genetic basis of PH in soybean. These results would not only increase our understanding of the genetic control of plant height in summer planting soybean but also provide support for implementing marker assisted selection (MAS) in developing cultivars with ideal plant height as well as gene cloning to elucidate the mechanisms of plant height.

Grain yield and associated agronomic traits are important factors in wheat (Triticum aestivum L.) improvement. Knowledge regarding the number, genomic location, and effect of quantitative trait loci (QTL) would facilitate marker-assisted selection and the development of cultivars with desirable characteristics. Our objectives were to identify QTLs directly and indirectly affecting grain yield expression. A population of 132 F12 recombinant inbred lines (RILs) was derived by single-seed descent from a cross between the Chinese facultative wheat Ning7840 and the US soft red winter wheat Clark. Phenotypic data were collected for 15 yield and other agronomic traits in the RILs and parental lines from three locations in Oklahoma from 2001 to 2003. Twenty-nine linkage groups, consisting of 363 AFLP and 47 SSR markers, were identified. Using composite interval mapping (CIM) analysis, 10, 16, 30, and 14 QTLs were detected for yield, yield components, plant adaptation (shattering and lodging resistance, heading date, and plant height), and spike morphology traits, respectively. The QTL effects ranged from 7 to 23%. Marker alleles from Clark were associated with a positive effect for the majority of QTLs for yield and yield components, but gene dispersion was the rule rather than the exception for this RIL population. Often, QTLs were detected in proximal positions for different traits. Consistent, co-localized QTLs were identified in linkage groups 1AL, 1B, 4B, 5A, 6A, and 7A, and less consistent but unique QTLs were identified on 2BL, 2BS, 2DL, and 6B. Results of this study provide a benchmark for future efforts on QTL identification for yield traits.

The productivity of sorghum is mainly determined by quantitative traits such as grain yield and stem sugar-related characteristics. Substantial crop improvement has been achieved by breeding in the last decades. Today, genetic mapping and characterization of quantitative trait loci (QTLs) is considered a valuable tool for trait enhancement. We have investigated QTL associated with the sugar components (Brix, glucose, sucrose, and total sugar content) and sugar-related agronomic traits (flowering date, plant height, stem diameter, tiller number per plant, fresh panicle weight, and estimated juice weight) in four different environments (two locations) using a population of 188 recombinant inbred lines (RILs) from a cross between grain (M71) and sweet sorghum (SS79). A genetic map with 157 AFLP, SSR, and EST-SSR markers was constructed, and several QTLs were detected using composite interval mapping (CIM). Further, additive x additive interaction and QTL x environmental interaction were estimated. CIM identified more than five additive QTLs in most traits explaining a range of 6.0-26.1% of the phenotypic variation. A total of 24 digenic epistatic locus pairs were identified in seven traits, supporting the hypothesis that QTL analysis without considering epistasis can result in biased estimates. QTLs showing multiple effects were identified, where the major QTL on SBI-06 was significantly associated with most of the traits, i.e., flowering date, plant height, Brix, sucrose, and sugar content. Four out of ten traits studied showed a significant QTL x environmental interaction. Our results are an important step toward marker-assisted selection for sugar-related traits and biofuel yield in sorghum.

It is of significance to discover genes related to fiber quality and yield traits and tightly linked markers for marker-assisted selection (MAS) in cotton breeding. In this study, 188 F8 recombinant inbred lines (RILs), derived from a intraspecific cross between HS46 and MARCABUCAG8US-1-88 were genotyped by the cotton 63K single nucleotide polymorphism (SNP) assay. Field trials were conducted in Sanya, Hainan Province, during the 2014–2015 cropping seasons under standard conditions. Results revealed significant differences (P < 0.05) among RILs, environments and replications for fiber quality and yield traits. Broad-sense heritabilities of all traits including fiber length, fiber uniformity, micronaire, fiber elongation, fiber strength, boll weight, and lint percentage ranged from 0.26 to 0.66. A 1784.28 cM (centimorgans) linkage map, harboring 2618 polymorphic SNP markers, was constructed, which had 0.68 cM per marker density. Seventy-one quantitative trait locus (QTLs) for fiber quality and yield traits were detected on 21 chromosomes, explaining 4.70∼32.28% phenotypic variance, in which 16 were identified as stable QTLs across two environments. Meanwhile, 12 certain regions were investigated to be involved in the control of one (hotspot) or more (cluster) traits, mainly focused on Chr05, Chr09, Chr10, Chr14, Chr19, and Chr20. Nineteen pairs of epistatic QTLs (e-QTLs) were identified, of which two pairs involved in two additive QTLs. These additive QTLs, e-QTLs, and QTL clusters were tightly linked to SNP markers, which may serve as target regions for map-based cloning, gene discovery, and MAS in cotton breeding.

Wheat cultivar Madsen has a new gene on the short arm of chromosome 1A and two QTL for all-stage resistance and three QTL for high-temperature adult-plant resistance that in combination confer high-level, durable resistance to stripe rust. Wheat cultivar Madsen has maintained a high-level resistance to stripe rust over 30years. To map quantitative trait loci (QTL) underlying the high-level, durable resistance, 156 recombinant inbred lines (RILs) developed from cross Avocet S × Madsen were phenotyped with selected races of Puccinia striiformis f. sp. tritici in the greenhouse seedling tests, and in naturally infected fields during 2015-2017. The RILs were genotyped by SSR and SNP markers from genotyping by sequencing and the 90K wheat SNP chip. Three QTL for all-stage resistance were mapped on chromosomes 1AS, 1BS and 2AS, and two QTL for high-temperature adult-plant (HTAP) resistance were mapped on 3BS and 6BS. The most effective QTL on 2AS, explaining 8.97-23.10% of the phenotypic variation in seedling tests and 8.60-71.23% in field tests, contained Yr17 for all-stage resistance and an additional gene for HTAP resistance. The 6BS QTL, detected in all field tests, was identified as Yr78. The 1AS QTL, conferring all-stage resistance, was identified as a new gene, which explained 20.45 and 30.23% of variation in resistance to races PSTv-37 and PSTv-40, respectively, and contributed significantly to field resistance at Pullman in 2015-2017, but was not detected at Mount Vernon. The interactions among QTL were mostly additive, and RILs with all five QTL had the highest level of resistance in the field, similar to Madsen. Genotyping 148 US Pacific Northwest wheat cultivars with markers for the 1AS, 2AS and 6BS QTL validated the genes and markers, and indicated their usefulness for marker-assisted selection.

Saturation mapping of consistent QTLs for yield and days to flowering under drought using locally adapted landrace in rice (Oryza sativa L.)

ABSTRACTTerminal and intermittent drought limits dry bean (Phaseolus vulgaris L.) production worldwide. Tolerance to drought exists but is difficult to breed for because of inconsistent expression across environments. Our objective was to identify quantitative trait loci (QTL) conditioning yield in a recombinant inbred line (RIL) population with consistent expression across multiple drought‐stress environments. We tested 140 RILs from ‘Buster’ pinto (susceptible)/‘Roza’ pink (tolerant) for yield under multiple stresses (intermittent drought, compaction, and low fertility) across 3 yr and terminal drought across four location‐years. A genetic linkage map (953 cM) was generated using single nucleotide polymorphism (SNP) markers. Two major‐effect QTL were detected on Pv01 and Pv02. The Pv01 QTL, defined by the closest marker SNP50809 (47.7 Mb), explained up to 37% of the phenotypic variance for seed yield under multiple stress (including intermittent drought) and was consistently expressed each year. The Pv02 QTL, nearest SNP40055 (11.8 Mb), was detected under drought stress (R2 = 33%) in addition to multiple stress (R2 = 17–23%). Phenological traits cosegregated with the yield QTL and affirmed the importance of phenological plasticity in adaptation to drought stress. Late maturity contributed to increased yield under multiple and nonstress and early maturity to increased yield under terminal drought. Given major and consistent effect, further investigation of the potential for the Pv01 and Pv02 QTL in breeding for multiple abiotic stress and drought tolerance in dry bean is warranted.

Quantitative traits, seed size, yield and days to flowering were studied in a chickpea intraspecific recombinant inbred line (RIL) population (F6:7) derived from a Kabuli × Desi cross. The population was evaluated in two locations over 2 years. Days to flowering was also evaluated in the greenhouse under short‐day conditions. Seed size was the most heritable trait (0.90), followed by days to flowering (0.36) and yield (0.14). Negative and significant correlation was found between yield and seed size in the second year where environmental homogeneity was tested by analysing the controls included in each assay. During the first year, the environment was not considered homogeneous for yield in either location. Quantitative trait loci (QTLs) for the three characters were detected in linkage group (LG) 4. In relation to seed size, two QTLs were located in LG4 (QTLSW1) and LG8 (QTLSW2). QTLSW1 accounted 20.3% of the total phenotypic variation and QTLSW2 explained 10.1%. A QTL for yield (QTLYD) was located in LG4 explaining around 13% of variation. QTLYD might be pleiotropic with QTLSW1. For days to flowering, a QTL (QTLDF1) was located in LG4 for all environments analysed explaining around 20% of variation. QTLDF1 was closely linked to QTLSW1 and QTLYD in LG4.

Salinity is one of the most serious factors limiting the productivity of rice crops, with adverse effects on germination, plant vigor and crop yield. A population of 300 F 5:6 recombinant inbred lines (RILs), which was derived from a cross between IR29 (indica sensitive to salinity) and Hasawi (Saudi cultivar showing salt tolerance), was evaluated at a young seedling stage under hydroponic conditions at an EC of 12 dsm -1 . Such RIL population when fixed can be repeatedly used for investigating QTLs of various phenotypes under different environments. Transgressive segregation was noted for all traits in the RILs; In all 31 RILs (10% of the 300 RILs) had tolerance level similar or better than Hasawi as determined by their standard evaluation system (SES) score of 4 or less, performance under both saline and non-saline conditions for plant height, root length, shoot dry weight and shoot fresh weight; suggesting these RILs can be rated as tolerant to salinity and are been advanced in our breeding program Quantitative trait loci (QTL) related to salt tolerance were detected using 142 F 5 RILs and single nucleotide polymorphisms (SNPs) chip composed of 384 SNP markers for indica x indica background. There were seven significant QTL related to 4 different traits associated to salt tolerance at young seedling stage. They were mapped on chromosomes 1, 2 and 6. The QTL qDW1.1, qDW2.1, qDW2.2 and qDW6.1 co-segregated with shoot dry weight and accounted between 10.6 and 42.3% of its phenotypic variation, while qPH1.1 and qPH1.2 were associated with plant height (explaining between 12.7 and 13.8% of its phenotypic variation), and qF2.1 co-segregated with shoot fresh weight (10.6% of trait variation) was accounted by SNP marker (id2007526). These QTLs had positive additive effects confirming that Hasawi alleles contributed to enhance traits related to salt tolerance at young seedling stage. The SNP markers associated with the QTLs identified in this study could be useful for further marker-aided breeding aiming at developing new rice cultivars for saline-prone agro-ecosystems