QTL mapping in three tropical maize populations reveals a set of constitutive and adaptive genomic regions for drought tolerance

Despite numerous published reports of quantitative trait loci (QTL) for drought-related traits, practical applications of such QTL in maize improvement are scarce. Identifying QTL of sizeable effects that express more or less uniformly in diverse genetic backgrounds across contrasting water regimes could significantly complement conventional breeding efforts to improve drought tolerance. We evaluated three tropical bi-parental populations under water-stress (WS) and well-watered (WW) regimes in Mexico, Kenya and Zimbabwe to identify genomic regions responsible for grain yield (GY) and anthesis-silking interval (ASI) across multiple environments and diverse genetic backgrounds. Across the three populations, on average, drought stress reduced GY by more than 50 % and increased ASI by 3.2 days. We identified a total of 83 and 62 QTL through individual environment analyses for GY and ASI, respectively. In each population, most QTL consistently showed up in each water regime. Across the three populations, the phenotypic variance explained by various individual QTL ranged from 2.6 to 17.8 % for GY and 1.7 to 17.8 % for ASI under WS environments and from 5 to 19.5 % for GY under WW environments. Meta-QTL (mQTL) analysis across the three populations and multiple environments identified seven genomic regions for GY and one for ASI, of which six mQTL on chr.1, 4, 5 and 10 for GY were constitutively expressed across WS and WW environments. One mQTL on chr.7 for GY and one on chr.3 for ASI were found to be ‘adaptive’ to WS conditions. High throughput assays were developed for SNPs that delimit the physical intervals of these mQTL. At most of the QTL, almost equal number of favorable alleles was donated by either of the parents within each cross, thereby demonstrating the potential of drought tolerant × drought tolerant crosses to identify QTL under contrasting water regimes.     

Identification of QTL for maize grain yield and kernel-related traits

Grain yield (GY) is one of the most important and complex quantitative traits in maize (Zea mays L.) breeding practice. Quantitative trait loci (QTLs) for GY and three kernel-related traits were detected in a set of recombinant inbred lines (RILs). One hundred and seven simple sequence repeats (SSRs) and 168 insertion/deletion polymorphism markers (Indels) were used to genotype RILs. Eight QTLs were found to be associated with four yield-related traits: GY, 100-kernel weight (HKW), 10-kernel length (KL), and 10-kernel length width (KW). Each QTL explained between 5.96 (qKL2-1) and 13.05 (qKL1-1) per cent of the phenotypic variance. Notably, one common QTL, located at the marker interval between bnlg1893 and chr2-236477 (chromosomal bin 2.09) simultaneously controlled GY and HKW; another common QTL, at bin 2.03 was simultaneously responsible for HKW and KW. Of the QTLs identified, only one pair of significant epistatic interaction involved in chromosomal region at bin 2.03 was detected for HKW; no significant QTL × environment interactions were observed. These results provide the common QTLs and for marker-assisted breeding.     

Simultaneous improvement and genetic dissection of grain yield and its related traits in a backbone parent of hybrid rice (Oryza sativa L.) using selective introgression

Three populations with a total of 125 BC2F3:4 introgression lines (ILs) selected for high yields from three BC2F2 populations were used for genetic dissection of rice yield and its related traits. The progeny testing in replicated phenotyping across two environments and genotyping with 140 polymorphic simple sequence repeat markers allowed the identification of 21 promising ILs that had significantly higher yields than the recurrent parent Shuhui527 (SH527). A total of 94 quantitative trait loci (QTL) were identified using the selective introgression method based on Chi-squared (χ ²) and multi-locus probability tests and the RSTEP-LRT method based on stepwise regression. These QTL were mostly mapped to 12 clusters on seven rice chromosomes. Several important properties of the QTL affecting grain yield (GY) and its related traits were revealed. The first one was the presence of strong and frequent non-random associations between or among QTL that affect low-heritability traits (GY and spikelet number per panicle, SN) in the ILs with high trait values. Second, beneficial alleles at 88.9 % GY and 75 % SN QTL for increased productivity were from the donors, suggesting that direct phenotypic selection for high yield in our introgression breeding program was a powerful way to transfer beneficial alleles at many loci from the donors into SH527. Third, most QTL were in clusters with large effects on multiple traits, which should be the focal points in further investigations and marker-assisted selection in rice. The majority of the QTL identified were expressed only in one of the environments, suggesting that differential expression of QTL in different environments is the primary genetic basis of genotype × environment interaction. Finally, a large variation in both the direction and magnitude of QTL effects was detected for different donor alleles at seven QTL in the same genetic background and environments. This finding suggests the possible presence of functional diversity among the donor alleles at these loci. The promising ILs and QTL identified provide valuable materials and genetic information for further improving the yield potential of SH527, which is a backbone restorer of hybrid rice in China.     

Meta-analysis of quantitative trait loci for grain yield and component traits under reproductive-stage drought stress in an upland rice population

A recombinant inbred population developed from a cross between high-yielding lowland rice (Oryza sativa L.) subspecies indica cv. IR64 and upland tropical rice subspecies japonica cv. Cabacu was used to identify quantitative trait loci (QTLs) for grain yield (GY) and component traits under reproductive-stage drought stress. One hundred fifty-four lines were grown in field trials in Indonesia under aerobic conditions by giving surface irrigation to field capacity every 4 days. Water stress was imposed for a period of 15 days during pre-flowering by withholding irrigation at 65 days after seeding. Leaf rolling was scored at the end of the stress period and eight agronomic traits were evaluated after recovery. The population was also evaluated for root pulling force, and a total of 201 single nucleotide polymorphism markers were used to construct the molecular genetic linkage map and QTL mapping. A QTL for GY under drought stress was identified in a region close to the sd1 locus on chromosome 1. QTL meta-analysis across diverse populations showed that this QTL was conserved across genetic backgrounds and co-localized with QTLs for leaf rolling and osmotic adjustment (OA). A QTL for percent seed set and grains per panicle under drought stress was identified on chromosome 8 in the same region as a QTL for OA previously identified in three different populations.     

Genetic basis of soybean adaptation to North American vs. Asian mega-environments in two independent populations from Canadian × Chinese crosses

One of the goals of plant breeding is to increase yield with improved quality characters. Plant introductions (PI) are a rich source of favorable alleles that could improve different characters in modern soybean [Glycine max (L.) Merril] including yield. The objectives of this study were to identify yield QTL underlying the genetic basis for differential adaptation of soybeans to the Canadian, United States or Chinese mega-environments (ME) and to evaluate the relationship and colocalization between yield and agronomic traits QTL. Two crosses between high-yielding Canadian cultivars and elite Chinese cultivars, OAC Millennium × Heinong 38 and Pioneer 9071 × #8902, were used to develop two recombinant inbred line (RIL) populations. Both populations were evaluated at different locations in Ontario, Canada; Minnesota, United States (US), Heilongjiang and Jilin, China, in 2009 and 2010. Significant variation for yield was observed among the RILs of both populations across the three hypothetical ME. Two yield QTL (linked to the interval Satt364–Satt591 and Satt277) and one yield QTL (linked to marker Sat_341) were identified by single-factor ANOVA and interval mapping across all ME in populations 1 and 2, respectively. The most frequent top ten high-yielding lines across all ME carried most of the high-yielding alleles of the QTL that were identified in two and three ME. Both parents contributed favorable alleles, which suggests that not only the adapted parent but also the PI parents are potential sources of beneficial alleles in reciprocal environments. Other QTL were detected also at two and one ME. Most of the yield QTL were co-localized with a QTL associated with an agronomic trait in one, two, or three ME in just one or in both populations. Results suggested that most of the variation observed in seed yield can be explained by the variation of different agronomic traits such a maturity, lodging and height. Novel alleles coming from PI can favorably contribute, directly or indirectly, to seed yield and the utilization of QTL detected across one, two or three ME would facilitate the new allele introgression into breeding populations in both North America and China.     

Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers

Key message

We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay.

Abstract

Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai?×?Shi 4185 (D?×?S), Gaocheng 8901?×?Zhoumai 16 (G?×?Z) and Linmai 2?×?Zhong 892 (L?×?Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5–32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

     

Identification of QTL for agronomic traits of importance for olive breeding

Development of methodologies for early selection is one of the most important goals of olive breeding programs at present. In this context, the identification of molecular markers associated with beneficial alleles could allow the development of marker-assisted selection (MAS) strategies in olive breeding programs. Fruit-related and plant vigor traits, which are of key importance for olive selection and breeding, were analyzed during two seasons in a progeny derived from the cross ‘Picual’ × ‘Arbequina.’ Quantitative trait loci (QTL) analyses were performed using MapQTL 4.0. A total of 22 putative QTLs were identified in the map of ‘Arbequina.’ QTLs clustered in linkage groups (LG) 1, 10 and 17. QTLs for oil-related traits located in LG 1 and 10 explained around 20–30 % of the phenotypic variability depending on the season and the trait. QTL for moisture-related traits were detected in LG 1, 10 and 17, and QTLs for the ratio pulp to stone were identified in LG 10 and 17 explaining around 15–20 %. Interaction between QTLs for the same trait was investigated. The significance of these results was discussed considering the co-localization of QTLs and Pearson correlations among traits. Five additional QTLs were detected in the map of ‘Picual.’ Four of them clustered in LG 17 indicating the presence of a QTL for fruit weight explaining around 12.7–15.2 % of the variability. Additionally, a QTL for trunk diameter was detected in LG 14 explaining 16 % of the variation. These results represent an important step toward the application of MAS in olive breeding programs.     

Identification of germplasm with stacked QTL underlying seed traits in an inbred soybean population from cultivars Essex and Forrest

Soybean (Glycine max (L.) Merr.) seed provides valuable oil (~200 g/kg) and protein (~400 g/kg) co-products. Seed composition variations result from several quantitative trait loci (QTL) that act through development. The objectives here were to identify loci underlying seed traits in the Essex × Forrest (EF94)-derived recombinant inbred line (RIL) population which has low frequencies of marker polymorphisms. Seed weight, protein, and oil were measured over 3 years: 2001, 2003, and 2005. Essex’s seeds were larger (141 mg/seed), higher in protein (406 g/kg), and lower in oil (190 g/kg) than Forrest’s (115 mg/seed, 395 g protein/kg, and 203 g oil/kg). Marker analysis included 413 markers for trait associations used for ANOVA, interval mapping, and composite interval mapping. Eleven QTL in nine genomic regions were associated (LOD >2; P < 0.0077) with seed traits. Two QTL, for mean protein and seed size, were clustered on linkage group (LG) E (chromosome Gm16). QTL for protein content alone were found on LG C2 (Gm6), LG D1b (Gm2), LG H (Gm12), and LG I (Gm20). The alleles from Essex, the high-protein parent, underlay higher protein (4–10 g/kg) at four of five loci. A QTL for mean oil was found on LG A2 (Gm18) and on LG I (Gm 20). The alleles from Forrest underlay higher oil (3–4 g/kg). Five separate QTL for mean seed weight were found on LG A1 (Gm05), LG N (Gm15), two on LG B1 (Gm11) and one on LG N (Gm3). The alleles from Essex underlay greater seed weight (0.4–0.66 g/100 seeds). The QTL positions were consistent with reported loci. Germplasm that contained all five beneficial alleles at the QTL underlying protein was significantly higher in protein and yield than Essex (409.7–412.3 g/kg) and included RILs 49 and 62. The germplasm identified can be useful for further breeding of the many traits and QTL measured in each line.     

The Sweet Passion Fruit (<Emphasis Type="Italic">Passiflora alata</Emphasis>) Crop: Genetic and Phenotypic Parameter Estimates and QTL Mapping for Fruit Traits

Despite their economic importance, some tropical crop species are largely neglected when it comes to conducting genetic studies characterizing target traits for breeding. Herein, genetic and phenotypic parameters as well quantitative trait loci (QTL) are described for the first time in a full-sib progeny of sweet passion fruit (Passiflora alata). A hundred F₁ individuals were evaluated in two locations for seven fruit traits: diameter of fruit (DF, in mm), length of fruit (LF, in mm), weight of fruit (WF, in g), thickness of fruit skin (TS, in mm), weight of fruit skin (WS, in g), weight of fruit pulp (WP, in g) and soluble solids (SS, in °Brix). Mixed models fitted complex, unstructured genetic variance-covariance matrices for all traits in phenotypic analysis. Because of important genetic correlations among skin and pulp traits, multiplicative index selection to select the most promising individuals was successfully applied. A previously reported integrated map supported composite interval mapping (CIM) analyses. In total, we found 22 QTLs mapped in seven out of nine linkage groups. Heritabilities (from 59.8 % to 82.7 %) and proportion of phenotypic variance explained by the QTLs (from 42.0 % to 64.3 %) were comparable for each trait. Principal component analysis on TS, WS and WP showed that the first two principal components (PCs) accounted for 93.6 % of the total variability. CIM analyses on these two PCs revealed five putative QTLs controlling variation for these three traits simultaneously. Thus, genetic improvement for sweet passion fruit should be based on correlations between traits and QTL-related information can be a useful tool.     

Identifying wheat genomic regions for improving grain protein concentration independently of grain yield using multiple inter-related populations

Grain yield (GY) and grain protein concentration (GPC) are two major traits contributing to the economic value of the wheat crop. These are, consequently, major targets in wheat breeding programs, but their simultaneous improvement is hampered by the negative correlation between GPC and GY. Identifying the genetic determinants of GPC and GY through quantitative trait loci (QTL) analysis would be one way to identify chromosomal regions, allowing improvement of GPC without reducing GY using marker-assisted selection. Therefore, QTL detection was carried out for GY and GPC using three inter-connected doubled haploid populations grown in a large multi-environment trial network. Chromosomes 2A, 2D, 3B, 7B and 7D showed co-location of QTL for GPC and GY with antagonistic effects, thus contributing to the negative GPC–GY relationship. Nonetheless, genomic regions determining GPC independently of GY across experiments were found on chromosomes 3A and 5D and could help breeders to move the GPC–GY relationship in a desirable direction.     

Comparison of three QTL detection models on biochemical,sensory, and yield characters in Coffea canephora

Coffea canephora is subject to enormous competitive challenges from other crops, especially for farmer sustainability and consumer requirements. Coffee breeding programs have to focus on specific traits linked to these two key targets, such as quality character, largely depending on the bean’s biochemical composition and field yield. Two segregating populations A and B, from crosses between a hybrid (Congolese?×?Guinean) FRT58 parental clone and a Congolese FRT51 genotype and between two Congolese parents FRT67 and FRT51, respectively, were used to characterize the quantitative trait loci (QTL) involved in agronomic and biochemical traits. A consensus genetic map was established using 249 SSRs covering 1,201 cM. Three QTL detection models per population with MapQTL (model I) and MCQTL (model II) followed by a connected population approach with MCQTL (model III) were compared based on their efficiency, precision for QTL detection, and their genetic effect assessment (additive, dominance, and parental-favorable allele). The analysis detected a total of 143 QTLs, 60 of which were shared between the three models; 28 found with two models; and two, 13, and 40 specific from models I, II, and III, respectively. The last model III based on connected populations is much more efficient in detecting QTLs with low variance explained and led to the genetic characterization of favorable allele. Thanks to this comparison of three QTL detection models on our quantitative genetic study, we will give a new insight for coffee breeding programs dedicated to managing complex agronomic or qualitative traits.     

Identification of QTL for Early Vigor and Stay-Green Conferring Tolerance to Drought in Two Connected Advanced Backcross Populations in Tropical Maize (Zea mays L.)

We aimed to identify quantitative trait loci (QTL) for secondary traits related to grain yield (GY) in two BC₁F_2:3 backcross populations (LPSpop and DTPpop) under well-watered (4 environments; WW) and drought stressed (6; DS) conditions to facilitate breeding efforts towards drought tolerant maize. GY reached 5.6 and 5.8 t/ha under WW in the LPSpop and the DTPpop, respectively. Under DS, grain yield was reduced by 65% (LPSpop) to 59% (DTPpop) relative to WW. GY was strongly associated with the normalized vegetative index (NDVI; r ranging from 0.61 to 0.96) across environmental conditions and with an early flowering under drought stressed conditions (r ranging from -0.18 to -0.25) indicative of the importance of early vigor and drought escape for GY. Out of the 105 detected QTL, 53 were overdominant indicative of strong heterosis. For 14 out of 18 detected vigor QTL, as well as for eight flowering time QTL the trait increasing allele was derived from CML491. Collocations of early vigor QTL with QTL for stay green (bin 2.02, WW, LPSpop; 2.07, DS, DTPpop), the number of ears per plant (bins 2.02, 2.05, WW, LPSpop; 5.02, DS, LPSpop) and GY (bin 2.07, WW, DTPpop; 5.04, WW, LPSpop), reinforce the importance of the observed correlations. LOD scores for early vigor QTL in these bins ranged from 2.2 to 11.25 explaining 4.6 (additivity: +0.28) to 19.9% (additivity: +0.49) of the observed phenotypic variance. A strong flowering QTL was detected in bin 2.06 across populations and environmental conditions explaining 26–31.3% of the observed phenotypic variation (LOD: 13–17; additivity: 0.1–0.6d). Improving drought tolerance while at the same time maintaining yield potential could be achieved by combining alleles conferring early vigor from the recurrent parent with alleles advancing flowering from the donor. Additionally bin 8.06 (DTPpop) harbored a QTL for GY under WW (additivity: 0.27 t/ha) and DS (additivity: 0.58 t/ha). R² ranged from 0 (DTPpop, WW) to 26.54% (LPSpop, DS) for NDVI, 18.6 (LPSpop, WW) to 42.45% (LPSpop, DS) for anthesis and from 0 (DTPpop, DS) to 24.83% (LPSpop, WW) for GY. Lines out-yielding the best check by 32.5% (DTPpop, WW) to 60% (DTPpop, DS) for all population-by-irrigation treatment combination (except LPSpop, WW) identified are immediately available for the use by breeders.     

Molecular mapping in tropical maize (Zea mays L.) using microsatellite markers. 2. Quantitative trait loci (QTL) for grain yield, plant height, ear height and grain moisture

A previous genetic map containing 117 microsatellite loci and 400 F(2) plants was used for quantitative trait loci (QTL) mapping in tropical maize. QTL were characterized in a population of 400 F(2:3) lines, derived from selfing the F(2) plants, and were evaluated with two replications in five environments. QTL determinations were made from the mean of these five environments. Grain yield (GY), plant height (PH), ear height (EH) and grain moisture (GM) were measured. Variance components for genotypes (G), environments (E) and GxE interaction were highly significant for all traits. Heritability was 0.69 for GY, 0.66 for PH, 0.67 for EH and 0.23 for GM. Using composite interval mapping (CIM), a total of 13 distinct QTLs were identified: four for GY, four for PH and five for EH. No QTL was detected for GM. The QTL explained 32.73 % of the phenotypic variance of GY, 24.76 % of PH and 20.91 % of EH. The 13 QTLs displayed mostly partial dominance or overdominance gene action and mapped to chromosomes 1, 2, 7, 8 and 9. Most QTL alleles conferring high values for the traits came from line L-14-4B. Mapping analysis identified genomic regions associated with two or more traits in a manner that was consistent with correlation among traits, supporting either pleiotropy or tight linkage among QTL. The low number of QTLs found, can be due to the great variation that exists among tropical environments.     

Quantitative trait analysis of seed yield and other complex traits in hybrid spring rapeseed (Brassica napus L.): 2. Identification of alleles from unadapted germplasm

Unadapted germplasm may contain alleles that could improve hybrid cultivars of spring oilseed Brassica napus. Quantitative trait loci (QTL) mapping was used to identify potentially useful alleles from two unadapted germplasm sources, a Chinese winter cultivar and a re-synthesized B. napus, that increase seed yield when introgressed into a B. napus spring hybrid combination. Two populations of 160 doubled haploid (DH) lines were created from crosses between the unadapted germplasm source and a genetically engineered male-fertility restorer line (P1804). A genetically engineered male-sterile tester line was used to create hybrids with each DH line (testcrosses). The two DH line populations were evaluated in two environments and the two testcross populations were evaluated in three or four environments for seed yield and other agronomic traits. Several genomic regions were found in the two testcross populations which contained QTL for seed yield. The map positions of QTL for days to flowering and resistance to a bacterial leaf blight disease coincided with QTL for seed yield and other agronomic traits, suggesting the occurrence of pleiotropic or linked effects. For two hybrid seed yield QTL, the favorable alleles increasing seed yield originated from the unadapted parents, and one of these QTL was detected in multiple environments and in both populations. In this QTL region, a chromosome rearrangement was identified in P1804, which may have affected seed yield.Electronic Supplementary Material Supplementary material is available to authorised users in the online version of this article at .     

Genome-wide association study for agronomic and physiological traits in spring wheat evaluated in a range of heat prone environments

Key message

We identified 27 stable loci associated with agronomic traits in spring wheat using genome-wide association analysis, some of which confirmed previously reported studies. GWAS peaks identified in regions where no QTL for grain yield per se has been mapped to date, provide new opportunities for gene discovery and creation of new cultivars with desirable alleles for improving yield and yield stability in wheat.

Abstract

We undertook large-scale genetic analysis to determine marker-trait associations (MTAs) underlying agronomic and physiological performance in spring wheat using genome-wide association studies (GWAS). Field trials were conducted at seven sites in three countries (Sudan, Egypt, and Syria) over 2–3 years in each country. Twenty-five agronomic and physiological traits were measured on 188 wheat genotypes. After correcting for population structure and relatedness, a total of 245 MTAs distributed over 66 loci were associated with agronomic traits in individual and mean performance across environments respectively; some of which confirmed previously reported loci. Of these, 27 loci were significantly associated with days to heading, thousand kernel weight, grain yield, spike length, and leaf rolling for mean performance across environments. Despite strong QTL by environment interactions, eight of the loci on chromosomes 1A, 1D, 5A, 5D, 6B, 7A, and 7B had pleiotropic effects on days to heading and yield components (TKW, SM^?2, and SNS). The winter-type alleles at the homoeologous VRN1 loci significantly increased days to heading and grain yield in optimal environments, but decreased grain yield in heat prone environments. Top 20 high-yielding genotypes, ranked by additive main effects and multiplicative interaction (AMMI), had low kinship relationship and possessed 4–5 favorable alleles for GY MTAs except two genotypes, Shadi-4 and Qafzah-11/Bashiq-1–2. This indicated different yield stability mechanisms due to potentially favorable rare alleles that are uncharacterized. Our results will enable wheat breeders to effectively introgress several desirable alleles into locally adapted germplasm in developing wheat varieties with high yield stability and enhanced heat tolerance.

     

On the use of mathematically-derived traits in QTL mapping

Mathematically-derived traits from two or more component traits, either by addition, subtraction, multiplication, or division, have been frequently used in genetics and breeding. When used in quantitative trait locus (QTL) mapping, derived traits sometimes show discrepancy with QTL identified for the component traits. We used three QTL distributions and three genetic effects models, and an actual maize mapping population, to investigate the efficiency of using derived traits in QTL mapping, and to understand the genetic and biological basis of derived-only QTL, i.e., QTL identified for a derived trait but not for any component trait. Results indicated that the detection power of the four putative QTL was consistently greater than 90% for component traits in simulated populations, each consisting of 200 recombinant inbred lines. Lower detection power and higher false discovery rate (FDR) were observed when derived traits were used. In an actual maize population, simulations were designed based on the observed QTL distributions and effects. When derived traits were used, QTL detected for both component and derived traits had comparable power, but those detected for component traits but not for derived traits had low detection power. The FDR from subtraction and division in the maize population were higher than the FDR from addition and multiplication. The use of derived traits increased the gene number, caused higher-order gene interactions than observed in component traits, and possibly complicated the linkage relationship between QTL as well. The increased complexity of the genetic architecture with derived traits may be responsible for the reduced detection power and the increased FDR. Derived-only QTL identified in practical genetic populations can be explained either as minor QTL that are not significant in QTL mapping of component traits, or as false positives.     

Verification of marker–trait associations in biparental winter barley (<Emphasis Type="Italic">Hordeum vulgare</Emphasis> L.) DH populations

In previous genome-wide association studies, marker–trait associations for grain yield and additional traits of agronomic importance were identified in the German winter barley (Hordeum vulgare L.) breeding gene pool. In the present study, seven doubled haploid populations segregating for the relevant alleles at the associated loci were used to get information whether these marker–trait associations can be verified in biparental populations and reliably used in applied barley breeding. The doubled haploid populations were phenotyped in field trials at two to five locations each in 1 year and genotyped by 40 trait-associated single nucleotide polymorphisms using an Illumina VeraCode GoldenGate assay. Large phenotypic variation was observed for all traits within at least one doubled haploid population. For 19 out of 58 marker–trait associations tested, the phenotypic means of both marker classes were significantly (p ≤ 0.005) different, thus confirming the association of the respective marker and the quantitative trait locus detected. For example, doubled haploid lines derived from a cross of ‘Malta’ × ‘Goldmine’ carrying different marker alleles differed by 0.41 t/ha in mean grain yield. The 19 (out of 58) marker–trait associations verified correspond to 10 (out of 27) genomic regions. Markers that were verified to be associated with a quantitative trait locus can be implemented directly in winter barley breeding for the selection of parental lines and marker-assisted pedigree selection.     

Identification of quantitative trait loci (QTL) for fruit-quality traits and number of weeks of flowering in the cultivated strawberry

Fruit quality and repeat flowering are two major foci of several strawberry breeding programs. The identification of quantitative trait loci (QTL) and molecular markers linked to these traits could improve breeding efficiency. In this work, an F₁ population derived from the cross ‘Delmarvel’ × ‘Selva’ was used to develop a genetic linkage map for QTL analyses of fruit-quality traits and number of weeks of flowering. Some QTL for fruit-quality traits were identified on the same homoeologous groups found in previous studies, supporting trait association in multiple genetic backgrounds and utility in multiple breeding programs. None of the QTL for soluble solids colocated with a QTL for titratable acids, and, although the total soluble solid contents were significantly and positively correlated with titratable acids, the correlation coefficient value of 0.2452 and independence of QTL indicate that selection for high soluble solids can be practiced independently of selection for low acidity. One genomic region associated with the total number of weeks of flowering was identified quantitatively on LG IV-S-1. The most significant marker, FxaACAO2I8C-145S, explained 43.3 % of the phenotypic variation. The repeat-flowering trait, scored qualitatively, mapped to the same region as the QTL. Dominance of the repeat-flowering allele was demonstrated by the determination that the repeat-flowering parent was heterozygous. This genomic region appears to be the same region identified in multiple mapping populations and testing environments. Markers linked in multiple populations and testing environments to fruit-quality traits and repeat flowering should be tested widely for use in marker-assisted breeding.     

QTL mapping and phenotypic variation for root architectural traits in maize (Zea mays L.)

Key message

QTL were identified for root architectural traits in maize.

Abstract

Root architectural traits, including the number, length, orientation, and branching of the principal root classes, influence plant function by determining the spatial and temporal domains of soil exploration. To characterize phenotypic patterns and their genetic control, three recombinant inbred populations of maize were grown for 28 days in solid media in a greenhouse and evaluated for 21 root architectural traits, including length, number, diameter, and branching of seminal, primary and nodal roots, dry weight of embryonic and nodal systems, and diameter of the nodal root system. Significant phenotypic variation was observed for all traits. Strong correlations were observed among traits in the same root class, particularly for the length of the main root axis and the length of lateral roots. In a principal component analysis, relationships among traits differed slightly for the three families, though vectors grouped together for traits within a given root class, indicating opportunities for more efficient phenotyping. Allometric analysis showed that trajectories of growth for specific traits differ in the three populations. In total, 15 quantitative trait loci (QTL) were identified. QTL are reported for length in multiple root classes, diameter and number of seminal roots, and dry weight of the embryonic and nodal root systems. Phenotypic variation explained by individual QTL ranged from 0.44 % (number of seminal roots, NyH population) to 13.5 % (shoot dry weight, OhW population). Identification of QTL for root architectural traits may be useful for developing genotypes that are better suited to specific soil environments.