Quantitative Trait Loci For Grain Yield Research Articles

Analysis of Genetic Diversity and Survey of QTLs for Grain Yield under Drought Stress in Drought Tolerant Rice Landraces Using DTY QTL-linked Markers

Genetic diversity in a set of 60 rice genotypes were analyzed using 27 random and 13 grain yield under drought (DTY) quantitative trait loci (QTLs)-linked simple sequence repeats (SSR) markers. The average gene diversity polymorphism information content were 0.53 and 0.46, respectively. The presence of DTY QTLs for grain yield under drought stress was predicted using peak marker in comparison to the positive checks. The DTY QTL qDTY12.1, amplified by the peak marker RM 28048, was found in 43.3% of genotypes, and qDTY2.2 was detected in only 6.67 % of genotypes using peak marker RM279. Two germplasm accessions, IC389895 and DT 2, possessed maximum number of DTY QTLs and absent is IC525099. Phylogenetic analysis revealed four distinct clusters within the germplasm. Overall, the evaluated genotypes presented a rich source of diversity and contain valuable DTY QTLs which can be utilized in rice genetic enhancement program for drought tolerance.

Detection of drought tolerance-related QTL in the Plainsman V./Cappelle Desprez doubled haploid wheat population

Drought stress is one of the major abiotic factors that significantly reduces wheat grain yield. Improving drought tolerance is a challenge that plant breeders are facing nowadays. In this study, our goal was to identify quantitative trait loci (QTL) in the Plainsman V./Cappelle Desprez doubled haploid (DH) population under drought induced as decreased irrigation (ds) and well-watered (ww) conditions in glasshouse. In total, 54 QTL were detected across the three years in two water regimes linked to 10 drought tolerance-related agronomic traits. Out of the detected QTL regions several have been previously reported. The QTL on chromosome 1A (wPt-744613-wPt-8016) related to thousand grain weight was detected in both ds and ww conditions, explaining the 12.7–17.4% of the phenotypic variance. QTL for grain yield was detected on chromosomes 1A, and 6B in the ds treatment. Numerous QTL was identified under both irrigation levels.

Identification of QTLs for grain yield and other traits in tropical maize under Striga infestation.

Striga is an important biotic factor limiting maize production in sub-Saharan Africa and can cause yield losses as high as 100%. Marker-assisted selection (MAS) approaches hold a great potential for improving Striga resistance but requires identification and use of markers associated with Striga resistance for adequate genetic gains from selection. However, there is no report on the discovery of quantitative trait loci (QTL) for resistance to Striga in maize under artificial field infestation. In the present study, 198 BC1S1 families obtained from a cross involving TZEEI 29 (Striga resistant inbred line) and TZEEI 23 (Striga susceptible inbred line) plus the two parental lines were screened under artificial Striga-infested conditions at two Striga-endemic locations in Nigeria in 2018, to identify QTL associated with Striga resistance indicator traits, including grain yield, ears per plant, Striga damage and number of emerged Striga plants. Genetic map was constructed using 1,386 DArTseq markers distributed across the 10 maize chromosomes, covering 2076 cM of the total genome with a mean spacing of 0.11 cM between the markers. Using composite interval mapping (CIM), fourteen QTL were identified for key Striga resistance/tolerance indicator traits: 3 QTL for grain yield, 4 for ears per plant and 7 for Striga damage at 10 weeks after planting (WAP), across environments. Putative candidate genes which encode major transcription factor families WRKY, bHLH, AP2-EREBPs, MYB, and bZIP involved in plant defense signaling were detected for Striga resistance/tolerance indicator traits. The QTL detected in the present study would be useful for rapid transfer of Striga resistance/tolerance genes into Striga susceptible but high yielding maize genotypes using MAS approaches after validation. Further studies on validation of the QTL in different genetic backgrounds and in different environments would help verify their reproducibility and effective use in breeding for Striga resistance/tolerance.

The genetic associations between yield component traits and bacterial leaf blight resistance in rice (O. sativa L.)

Bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae (Xoo) is highly destructive to high-yielding susceptible rice cultivars. In severe epidemics, yield losses up to 75% have been reported. Considerable information on BLB resistant genes is available; however, genetic overlaps between BLB resistant and yield related traits largely remain unclear. Using two sets of backcross introgression inbred lines and one set of recombinant inbred lines, genetic associations between bacterial leaf blight resistance and yield component traits in three Xoo races were analyzed using Single Nucleotide polymorphism (SNP) markers. Fifteen quantitative trait loci conferring BLB resistant and 112 QTLs for yield and yield related traits were detected. Among 15 QTLs conferring bacteria leaf blight resistance, 14 QTLs overlapped with 39 QTLs for yield and yield related traits. The total resistance variation explained by additive QTLs (R2) ranged between 5-76% and epistasis QTLs ranged between 1-26%. Quantitative trait loci (QTLs) with the highest additive effects for BLB resistance were detected at positions os04-17305294 (on chr.4), os05-07310209 (on chr.5), os09-15240130 (on chr.9), os11-28421947 (on chr.11) and os12-25291547(on chr.12). The BLB resistance QTL at position os05-07310209 (on chr.5) overlapped with QTLs for 1000-grain weight, grain number per panicle, days to heading, grain length width ratio and grain yield per plant. The BLB resistance QTL at position os09-15240130 (on chr.9) overlapped with QTLs for grain yield per plant, panicle number, grain width and 1000-grain weight. The BLB resistance QTL at position os12-25291547-(on chr.12) overlapped with QTLs for 1000-grain weight, panicle number, grain yield per plant, filled grain number and grain width. Eleven percent of the 717 plants in this study were resistant to at least two Xoo races and had higher grain yield compared to both recurrent parents. Overlapping regions especially with already cloned genes and epistasis detected in this study offer opportunity to develop rice varieties which combine high yield and resistance to bacteria leaf blight.

A QTL hot spot region on chromosome 1B for nine important traits under terminal drought stress conditions in wheat

Drought tolerance is a polygenic trait and is considered as one of the most important limiting factors to productivity of wheat and other crops around the world. Identifying drought-responsive genes using quantitative trait loci (QTL) and association analysis is one of the ways of developing drought tolerance cultivars. In order to detect QTLs for terminal drought tolerance in wheat, QTL analyses were conducted using an F12 recombinant inbred line population. A total of 53 main effects QTLs on 15 different chromosomes and 12 QTL by QTL (QQ) interactions on 13 different chromosomes were detected for yield, yield components and some agronomic traits using composite interval mapping and mixed-model based composite interval mapping analysis. The most significant QTL for grain yield was QYld.1A1 on 1A1, explaining 19.7% of the phenotypic variance under terminal drought stress. In addition, a QTL hot-spot region including important QTLs for grain yield, biological yield, grain number per spike, thousand grain weight, spike length, spike weight, stem weight and plant height was identified in the same region on chromosome 1B and clustered within the marker interval between wpt-3465 and wpt-2019. The DArT marker Wpt-5801 at the position of 67.7 cM showed linkage with all traits using single marker regression analysis. The BLAST search of markers sequences on the wheat genome identified 390 gene stable identifiers. Gene ontology analysis showed that the most dominant terms were ‘binding’ and ‘single-organism catabolic process’ for molecular function and biological process categories, respectively. This QTL hot-spot region with nine important QTLs could be used to improve drought tolerance after validation.

QTL mapping for yield-related traits in wheat based on four RIL populations.

Eight environmentally stable QTL for grain yield-related traits were detected by four RIL populations, and two of them were validated by a natural wheat population containing 580 diverse varieties or lines. Yield and yield-related traits are important factors in wheat breeding. In this study, four RIL populations derived from the cross of one common parent Yanzhan 1 (a Chinese domesticated cultivar) and four donor parents including Hussar (a British domesticated cultivar) and three semi-wild wheat varieties in China were phenotyped for 11 yield-related traits in eight environments. An integrated genetic map containing 2009 single-nucleotide polymorphism (SNP) markers generated from a 90K SNP array was constructed to conduct quantitative trait loci (QTL) analysis. A total of 161 QTL were identified, including ten QTL for grain yield per plant (GYP) and yield components, 49 QTL for spike-related traits, 43 QTL for flag leaf-related traits, 22 QTL for plant height (PH), and 37 QTL for heading date and flowering date. Eight environmentally stable QTL were validated in individual RIL population where the target QTL was notably detected, and six of them had a significant effect on GYP. Furthermore, Two QTL, QSPS-2A.4 and QSL-4A.1, were also validated in a natural wheat population containing 580 diverse varieties or lines, which provided valuable resources for further fine mapping and genetic improvement in yield in wheat.

Mapping of Quantitative Trait Loci (QTL) Related to Drought Tolerance in Common Bean (Phaseolus vulgaris L.) Using F2 Population from (KATB1 Χ GLP2)

Many of the common bean growing regions around the world are prone to drought stress, making drought the major challenge to production and yield stability in rainfed environments. Mapping of yield-associated loci under drought stress will offer a better understanding of the genetics of drought tolerance to the plant breeders and therefore, will accelerate the selection of drought tolerant crop varieties through marker assisted selection (MAS).The current study reports identification of quantitative trait loci (QTL) linked to physiological, phenological, yield and yield related traits using 120 F2 population derived from a cross between two common bean genotypes, KAT B1 (drought tolerant) and GLP2 (drought susceptible) evaluated under drought stress and well-watered conditions. The research was conducted at the Agricultural and Mechanization Institute, Machakos, Kenya. The F2 population showed significant variation in traits under drought stress. From the 374 polymorphic SNP markers surveyed, 20 genomic regions were identified for various traits under drought stress, individually explaining 2.6 to 21.3% of phenotypic variation. The number of QTLs identified per trait were: 2-grain/seed yield (GY); 1-number of branches (NBP); 2-stem biomass (SB); 1-leaf biomass (LB); 1-pod biomass (PB); 3-days to flowering; 2-days to maturity (DM); 4- number of pods per plant (NPP); 1-seed weight (SW); 2-stomatal conductance (SMTL) and 1-leaf water potential (LWP). QTLs for number of pods per plant, number of grains/seeds per pod, days to flowering, leaf biomass and stem biomass were found co-locating with QTLs for grain yield on chromosome Pv02 under drought stress treatment. The cumulative effects of these QTLs on chromosomes 2 resulted in higher grain/seed yield. This study has provided information on QTLs in common bean that could be used in selection purpose for grain yield under drought conditions.

QTL mapping for resistance to and tolerance for the rice root-knot nematode, Meloidogyne graminicola

BackgroundThe root-knot nematode Meloidogyne graminicola is an obligate biotrophic pathogen considered to be the most damaging nematode species that causes significant yield losses to upland and rainfed lowland rice production in South and Southeast Asia. Mapping and identification of quantitative trait loci (QTL) for resistance to and tolerance for M. graminicola may offer a safe and economic management option to farmers. In this study, resistance to and tolerance for M. graminicola in Asian rice (Oryza sativa L.) were studied in a mapping population consisting of 300 recombinant inbred lines (RILs) derived from IR78877–208-B-1-2, an aerobic rice genotype with improved resistance to and tolerance for M. graminicola, and IR64, a popular, high-yielding rice mega-variety susceptible to M. graminicola. RILs were phenotyped for resistance and tolerance in the dry seasons of 2012 and 2013. QTL analysis was performed using 131 single nucleotide polymorphism (SNP) and 33 simple sequence repeat (SSR) markers.ResultsThree QTLs with main effects on chromosomes 4 (qMGR4.1), 7 (qMGR7.1) and 9 (qMGR9.1) and two epistatic interactions (qMGR3.1/ qMGR11.1 and qMGR4.2/ qMGR8.1) associated with nematode reproduction that were consistent in the two seasons were detected. A QTL affecting root galling was found on chromosomes 4 (qGR4.1) and 8 (qGR8.1), and QTLs for nematode tolerance were found on chromosomes 5 (qYR5.1) and 11 (qYR11.1). These QTLs were consistent in both seasons. A QTL for grain yield was found on chromosome 10 (qGYLD10.1), a QTL affecting filled grains per panicle was detected on chromosome 11 (qFG11.1) and a QTL for fresh root weight was found on chromosomes 2 (qFRWt2.1), 8 (qFRWt8.1) and 12 (qFRWt12.1) in both seasons. The donor of the alleles for qMGR4.1, qMGR7.1, qMGR9.1, qGR4.1, qGR8.1, qYR5.1 and qFRWt2.1 was IR78877–208-B-1-2, whereas for qYR11.1, qGYLD10.1 and qFG11.1, qFRWt8.1 and qFRWt12.1 was IR64. Lines having favorable alleles for resistance, tolerance and yield provided better yield under nematode-infested conditions and could be a starting point of marker-assisted breeding (MAB) for the improvement of M. graminicola resistance and tolerance in Asian rice.ConclusionThis study identified a total of 12 QTLs with main effects and two epistatic interactions in the 1st season and 2nd season related to M. graminicola resistance and tolerance, and other agronomic traits such as plant yield, percentage of filled grains, and fresh and dry root weight. Rice genotypes that have the favorable alleles for resistance (qMGR4.1, qMGR7.1, qMGR9.1, qGR4.1, qGR8.1) and tolerance (qYR5.1, and qYR11.1,) QTLs, and which are either resistant or partially resistant and tolerant, were also selected. These selected genotypes and the identified QTLs are vital information in designing MAB for the improvement of high-yielding rice genotypes but are susceptible to M. graminicola infection.

Mapping Quantitative Trait Loci for Agronomic Traits in Winter Wheat under Different Soil Moisture Levels

Due to variable moisture conditions in the U.S. Great Plains, it is important to understand genetic control of crop traits under a range of soil moisture levels. Our objective was to identify quantitative trait loci (QTL) for yield, phenology, and morphological traits in wheat (Triticum aestivum L.) under different soil moisture conditions. Field evaluation of a winter wheat doubled haploid population (n = 185) derived from a cross between CO940610 and ‘Platte’ was carried out in Fort Collins and Greeley, Colorado, USA in 2007–2008 and 2008–2009, respectively. At each location, trials were grown under moderate drought stress and fully irrigated conditions. A total of 33 QTL for 11 traits was detected in two or more environments. A cluster of QTL for nine traits was found on chromosome 2B in the vicinity of the photoperiod response gene Ppd-B1. Other stable QTL clusters were detected on chromosome 6A and near the vernalization response gene Vrn-D3 on chromosome 7D. A QTL for grain yield on chromosome 5A was detected in three environments. With minor exceptions, the large-effect QTL were detected in both the water limited and fully irrigated environments, rather than being detected only under specific moisture levels.

QTL Analysis for Grain Iron and Zinc Concentrations in Two O. nivara Derived Backcross Populations

Identification of quantitative trait loci (QTLs) for grain mineral elements can assist in faster and more precise development of micronutrient dense rice varieties through marker-assisted breeding. In the present study, QTLs were mapped for Fe and Zn concentrations in two BC2F3 mapping populations derived from the crosses of O. sativa cv Swarna with two different accessions of O. nivara. In all, 10 and 8 QTLs were identified for grain Fe and Zn concentrations in population 1, and 7 and 5 QTLs were identified in population 2, respectively. Eighty percent of the QTLs detected in both populations were derived from O. nivara. Five QTLs for Fe and three QTLs for Zn explained more than 15% phenotypic variance either in interval or composite interval mapping. The locations of O. nivara derived QTLs such as qFe2.1, qFe3.1, qFe8.2 and qZn12.1 were consistently identified in both the populations. Epistatic interaction was observed only between RM106 and RM6 on chromosome 2 and between RM22 and RM7 on chromosome 3 for Fe concentration in population 1. Sixteen candidate genes for metal homeostasis were found to co-locate with 10 QTLs for Fe and Zn concentrations in both the populations. Most of the Fe and Zn QTLs were found to co-locate with QTLs for grain yield and grain quality traits. Some of the major effect QTLs identified can be used to improve rice grain Fe and Zn concentrations.

Genetic Loci Governing Grain Yield and Root Development under Variable Rice Cultivation Conditions.

Drought is the major abiotic stress to rice grain yield under unpredictable changing climatic scenarios. The widely grown, high yielding but drought susceptible rice varieties need to be improved by unraveling the genomic regions controlling traits enhancing drought tolerance. The present study was conducted with the aim to identify quantitative trait loci (QTLs) for grain yield and root development traits under irrigated non-stress and reproductive-stage drought stress in both lowland and upland situations. A mapping population consisting of 480 lines derived from a cross between Dular (drought-tolerant) and IR64-21 (drought susceptible) was used. QTL analysis revealed three major consistent-effect QTLs for grain yield (qDTY1.1, qDTY1.3, and qDTY8.1) under non-stress and reproductive-stage drought stress conditions, and 2 QTLs for root traits (qRT9.1 for root-growth angle and qRT5.1 for multiple root traits, i.e., seedling-stage root length, root dry weight and crown root number). The genetic locus qDTY1.1 was identified as hotspot for grain yield and yield-related agronomic and root traits. The study identified significant positive correlations among numbers of crown roots and mesocotyl length at the seedling stage and root length and root dry weight at depth at later stages with grain yield and yield-related traits. Under reproductive stage drought stress, the grain yield advantage of the lines with QTLs ranged from 24.1 to 108.9% under upland and 3.0–22.7% under lowland conditions over the lines without QTLs. The lines with QTL combinations qDTY1.3+qDTY8.1 showed the highest mean grain yield advantage followed by lines having qDTY1.1+qDTY8.1 and qDTY1.1+qDTY8.1+qDTY1.3, across upland/lowland reproductive-stage drought stress. The identified QTLs for root traits, mesocotyl length, grain yield and yield-related traits can be immediately deployed in marker-assisted breeding to develop drought tolerant high yielding rice varieties.

Development of a High-Density SNP-Based Linkage Map and Detection of QTL for β-Glucans, Protein Content, Grain Yield per Spike and Heading Time in Durum Wheat.

High-density genetic linkage maps of crop species are particularly useful in detecting qualitative and quantitative trait loci for important agronomic traits and in improving the power of classical approaches to identify candidate genes. The aim of this study was to develop a high-density genetic linkage map in a durum wheat recombinant inbred lines population (RIL) derived from two elite wheat cultivars and to identify, characterize and correlate Quantitative Trait Loci (QTL) for β-glucan, protein content, grain yield per spike and heading time. A dense map constructed by genotyping the RIL population with the wheat 90K iSelect array included 5444 single nucleotide polymorphism (SNP) markers distributed in 36 linkage groups. Data for β-glucan and protein content, grain yield per spike and heading time were obtained from replicated trials conducted at two locations in southern Italy. A total of 19 QTL were detected in different chromosome regions. In particular, three QTL for β-glucan content were detected on chromosomes 2A and 2B (two loci); eight QTL controlling grain protein content were detected on chromosomes 1B, 2B, 3B (two loci), 4A, 5A, 7A and 7B; seven QTL for grain yield per spike were identified on chromosomes 1A, 2B, 3A (two loci), 3B (two loci) and 6B; and one marker-trait association was detected on chromosome 2A for heading time. The last was co-located with a β-glucan QTL, and the two QTL appeared to be negatively correlated. A genome scan for genomic regions controlling the traits and SNP annotated sequences identified five putative candidate genes involved in different biosynthesis pathways (β-glucosidase, GLU1a; APETALA2, TaAP2; gigantea 3, TaGI3; 14-3-3 protein, Ta14A; and photoperiod sensitivity, Ppd-A1). This study provides additional information on QTL for important agronomic traits that could be useful for marker-assisted breeding to obtain new genotypes with commercial and nutritional relevance.

Association Mapping of Yield and Yield-related Traits Under Reproductive Stage Drought Stress in Rice (Oryza sativa L.)

BackgroundThe identification and introgression of major-effect QTLs for grain yield under drought are some of the best and well-proven approaches for improving the drought tolerance of rice varieties. In the present study, we characterized Malaysian rice germplasm for yield and yield-related traits and identified significant trait marker associations by structured association mapping.ResultsThe drought screening was successful in screening germplasm with a yield reduction of up to 60% and heritability for grain yield under drought was up to 78%. There was a wider phenotypic and molecular diversity within the panel, indicating the suitability of the population for quantitative trait loci (QTL) mapping. Structure analyses clearly grouped the accessions into three subgroups with admixtures. Linkage disequilibrium (LD) analysis revealed that LD decreased with an increase in distance between marker pairs and the LD decay varied from 5–20 cM. The Mixed Linear model-based structured association mapping identified 80 marker trait associations (MTA) for grain yield (GY), plant height (PH) and days to flowering (DTF). Seven MTA were identified for GY under drought stress, four of these MTA were consistently identified in at least two of the three analyses. Most of these MTA identified were on chromosomes 2, 5, 10, 11 and 12, and their phenotypic variance (PV) varied from 5% to 19%. The in silico analysis of drought QTL regions revealed the association of several drought-responsive genes conferring drought tolerance. The major-effect QTLs are useful in marker-assisted QTL pyramiding to improve drought tolerance.ConclusionThe results have clearly shown that structured association mapping is one of the feasible options to identify major-effect QTLs for drought tolerance-related traits in rice.

QTLs for stomatal and photosynthetic traits related to salinity tolerance in barley

BackgroundStomata regulate photosynthesis and transpiration, and these processes are critical for plant responses to abiotic stresses such as salinity. A barley double haploid population with 108 lines derived from a cross between CM72 (salt-tolerant) and Gairdner (salt-sensitive) was used to detect quantitative trait loci (QTLs) associated with stomatal and photosynthetic traits related to salinity tolerance.ResultsA total of 11 significant QTLs (LOD > 3.0) and 11 tentative QTLs (2.5 < LOD < 3.0) were identified. These QTLs are distributed on all the seven chromosomes, except 5H and explain 9.5–17.3% of the phenotypic variation. QTLs for biomass, intercellular CO2 concentration, transpiration rate and stomatal conductance under control conditions co-localised together. A QTL for biomass also co-located with one for transpiration rate under salinity stress. A linkage was found between stomatal pore area and gas exchange. A QTL for salinity tolerance also co-localised with QTLs for grain yield and biomass on chromosome 3H. Based on the draft barley genome, the candidate genes for salinity tolerance at this locus are proposed.ConclusionsThe lack of major QTLs for gas exchange and stomatal traits under control and saline conditions indicates a complex relationship between salinity and leaf gas exchange due to the fact that these complex quantitative traits are under the control of multiple genes.

Application of a library of near isogenic lines to understand context dependent expression of QTL for grain yield and adaptive traits in bread wheat.

BackgroundPrevious quantitative trait loci (QTLs) studies using the Avalon × Cadenza doubled haploid (DH) population identified eleven QTLs determining plant height, heading date and grain yield. The objectives of this study were: (i) to provide insight into the effects of these QTLs using reciprocal multiple near isogenic lines (NILs) with each pair of alleles compared in both parental backgrounds (Avalon or Cadenza), (ii) quantifying epistasis by looking at the background effects and (iii) predict favourable allelic combinations to develop superior genotypes adapted to a target environment.ResultsTo this aim, a library of 553 BC2 NILs and their recurrent parents were tested over two growing seasons (2012/2013 and 2013/2014). The results obtained in the present study validated the plant height, heading date and grain yield QTLs previously identified. Epistatic interactions were detected for the 6B QTL for plant height and heading date, 3A QTL for heading date and grain yield and 2A QTL for grain yield.ConclusionThe marker assisted backcrossing strategy used provided an efficient method of resolving QTL for key agronomic traits in wheat as Mendelian factors determining possible epistatic interactions. The study shows that these QTLs are amenable to marker assisted selection, fine mapping, future positional cloning, and physiological trait dissection.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-016-0849-6) contains supplementary material, which is available to authorized users.

Identifying Quantitative Trait Loci for Economic Traits in an Elite Soft Red Winter Wheat Population

Genotyping‐by‐sequencing (GBS), reduces genotyping costs and allows breeders to genotype large populations with thousands of markers. Genome‐wide association studies with GBS markers can be used to identify quantitative trait loci (QTL) for important traits in elite populations of soft red winter wheat (SRWW; Triticum aestivum L.). Our objective was to identify potential QTL for grain yield (GY), Fusarium head blight resistance (FHB), flour yield (FY), and softness equivalence (SE) in a set of 470 elite SWRR wheat lines that were genotyped with 33,169 GBS markers and phenotyped in multiple environments. For all traits, we found lines that were phenotypically superior to the elite checks. We identified four FHB QTL, nine QTL for quality, and 14 QTL for with R2 values ranging from 1.6 to 3.5%. The QTL with the largest effect for FHB resistance reduced disease by 1.76%. For quality, the largest‐effect QTL increased FY and SE by 0.37 and 0.67%, respectively. For GY the QTL with the largest effect in Wooster, OH, increased GY by 129.6 kg ha−1, for northwest Ohio, the largest‐effect QTL increased GY by 67.2 kg ha−1, and the largest‐effect QTL for GY over all environments increased GY by 48.8 kg ha−1. While marker‐assisted selection (MAS) for these QTL could be used to improve these traits, the preponderance of genetic variation appeared to be controlled by genes with small effect, suggesting that MAS should be used as a supplement to genomic selection.

Identification of quantitative trait loci for agronomic traits contributed by a barley (Hordeum vulgare) Mediterranean landrace

Some Spanish barley (Hordeum vulgare L.) landraces perform better than modern cultivars at low-production sites. The objective of this study was to identify favourable quantitative trait loci (QTLs) for interesting agronomic traits contributed by the landrace SBCC073. To achieve this objective, a population of 100 BC1F5 lines was derived from the cross between the elite cultivar Orria, with high productivity, and the Spanish landrace SBCC073, which was the best performer in low-production trials. The population was evaluated in field trials for 3 years (2011, 2013, and 2014) in Zaragoza, Spain. The population was genotyped with a DArTseq genotyping-by-sequencing assay. A genetic linkage map was developed by using markers of four flowering-time genes and 1227 single-nucleotide polymorphisms of good quality. The genetic map resulted in 11 linkage groups, covering a total distance of 871.1 cM. Five QTLs for grain yield were detected on 2H.1, 4H, 5H and 6H.2. Alleles from SBCC073 contributed to increased yield in three of them. A region at the end of chromosome 5H contains favourable alleles for early vigour, higher grain yield and earlier flowering, all derived from SBCC073. Alleles from Orria contributed to increasing grain yield and simultaneously to reducing plant height on the same region of 6H.2, and to increasing 1000-kernel weight on chromosomes 3H and 5H.

Genetic properties of the MAGIC maize population: a new platform for high definition QTL mapping in Zea mays.

BackgroundMaize (Zea mays) is a globally produced crop with broad genetic and phenotypic variation. New tools that improve our understanding of the genetic basis of quantitative traits are needed to guide predictive crop breeding. We have produced the first balanced multi-parental population in maize, a tool that provides high diversity and dense recombination events to allow routine quantitative trait loci (QTL) mapping in maize.ResultsWe produced 1,636 MAGIC maize recombinant inbred lines derived from eight genetically diverse founder lines. The characterization of 529 MAGIC maize lines shows that the population is a balanced, evenly differentiated mosaic of the eight founders, with mapping power and resolution strengthened by high minor allele frequencies and a fast decay of linkage disequilibrium. We show how MAGIC maize may find strong candidate genes by incorporating genome sequencing and transcriptomics data. We discuss three QTL for grain yield and three for flowering time, reporting candidate genes. Power simulations show that subsets of MAGIC maize might achieve high-power and high-definition QTL mapping.ConclusionsWe demonstrate MAGIC maize’s value in identifying the genetic bases of complex traits of agronomic relevance. The design of MAGIC maize allows the accumulation of sequencing and transcriptomics layers to guide the identification of candidate genes for a number of maize traits at different developmental stages. The characterization of the full MAGIC maize population will lead to higher power and definition in QTL mapping, and lay the basis for improved understanding of maize phenotypes, heterosis included. MAGIC maize is available to researchers.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0716-z) contains supplementary material, which is available to authorized users.

Mapping QTL, Selection Differentials, and the Effect of Rht‐B1 under Organic and Conventionally Managed Systems in the Attila × CDC Go Spring Wheat Mapping Population

ABSTRACTA randomly derived recombinant inbred line (RIL) population (n = 163) from a cross between CIMMYT spring wheat ‘Attila’ and the Canadian ‘CDC Go’ was used to map quantitative trait loci (QTL) affecting various agronomic and quality traits. The experiment was also designed to investigate the feasibility of organic wheat breeding by determining selection differentials and the effect of Rht‐B1 in paired organic and conventional management systems. Heritability estimates differed between systems for five of nine traits measured; including grain yield, number of tillers, plant height, kernel weight, and grain protein content. Direct selection in each management system resulted in 50% or fewer selected individuals in common between the two systems, for eight of the nine (except for flowering time) studied traits. Most QTL were specific to either the organic or the conventional management system. However, consistent QTL for grain yield, grain volume weight, kernel weight, and days to flowering were mapped in both systems on chromosomes 6A, 1B, 3A, and 5B, respectively. The effect of Rht‐B1 was more pronounced in organic systems, where RILs carrying the wild‐type allele were taller, produced more grain yield with higher grain protein content, and suppressed weed biomass to a greater extent than those carrying dwarfing alleles. Results of the present study suggest that differences exist between the two management systems for QTL effects. Indirect selection of superior genotypes from one system to another will not result in the advancement of the best possible genotypes. Therefore, selection of spring wheat cultivars for organic systems should be conducted on organically managed lands.

Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat.

Seedling root traits of wheat (Triticum aestivum L.) have been shown to be important for efficient establishment and linked to mature plant traits such as height and yield. A root phenotyping pipeline, consisting of a germination paper-based screen combined with image segmentation and analysis software, was developed and used to characterize seedling traits in 94 doubled haploid progeny derived from a cross between the winter wheat cultivars Rialto and Savannah. Field experiments were conducted to measure mature plant height, grain yield, and nitrogen (N) uptake in three sites over 2 years. In total, 29 quantitative trait loci (QTLs) for seedling root traits were identified. Two QTLs for grain yield and N uptake co-localize with root QTLs on chromosomes 2B and 7D, respectively. Of the 29 root QTLs identified, 11 were found to co-localize on 6D, with four of these achieving highly significant logarithm of odds scores (>20). These results suggest the presence of a major-effect gene regulating seedling root vigour/growth on chromosome 6D.