QTL analyses of drought tolerance and growth for a Salix dasyclados × Salix viminalis hybrid in contrasting water regimes

Quantitative trait loci (QTL) for growth traits and water-use efficiency have been identified in two water regimes (normal and drought-treated) and for a treatment index. A tetraploid hybrid F₂ population originating from a cross between a Salix dasyclados clone (SW901290) and a Salix viminalis clone (Jorunn) was used in the study. The growth response of each individual including both above and below ground dry-matter production (i.e. shoot length, shoot diameter, aboveground and root dry weight, internode length, root dry weight/total dry weight, relative growth rate and leaf nitrogen content) was analysed in a replicated block experiment with two water treatments. A composite interval mapping approach was used to estimate number of QTL, the magnitude of the QTL and their position on genetic linkage maps. QTL specific for each treatment and for the treatment index were found, but QTL common across the treatments and the treatment index were also detected. Each QTL explained from 8% to 29% of the phenotypic variation, depending on trait and treatment. Clusters of QTL for different traits were mapped close to each other at several linkage groups, indicating either a common genetic base or tightly linked QTL. Common QTL identified between treatments and treatment index in the complex trait dry weight can be useful tools in the breeding and selection for drought stress tolerance in Salix.     

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

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

Comparative QTL analysis of early short-time drought tolerance in Polish fodder and malting spring barleys

Key message

An effective approach for the further evolution of QTL markers, may be to create mapping populations for locally adapted gene pools, and to phenotype the studied trait under local conditions.

Abstract

Mapping populations of Polish fodder and malting spring barleys (Hordeum vulgare L.) were used to analyze traits describing short-time drought response at the seedlings stage. High-throughput genotyping (Diversity Array Technology (DArT) markers) and phenotyping techniques were used. The results showed high genetic diversity of the studied populations which allowed the creation of high-density linkage maps. There was also high diversity in the physiological responses of the barleys. Quantitative trait locus (QTL) analysis revealed 18 QTLs for nine physiological traits on all chromosomes except 1H in malting barley and 15 QTLs for five physiological traits on chromosomes 2H, 4H, 5H and 6H in fodder barley. Chromosomes 4H and 5H contained QTLs which explained most of the observed phenotypic variations in both populations. There was a major QTL for net photosynthetic rate in the malting barley located on chromosome 5H and two major QTLs for overall photochemical performance (PI) located on 5H and 7H. One major QTL related to photochemical quenching of chlorophyll fluorescence was located on chromosome 4H in fodder barley. Three QTL regions were common to both mapping populations but the corresponding regions explained different drought-induced traits. One region was for QTLs related to PSII photosynthetic activity stress index in malting barley, and the corresponding region in fodder barley was related to the water content stress index. These results are in accordance with previous studies which showed that different traits were responsible for drought tolerance variations in fodder and malting barleys.     

Quantitative trait loci (QTL) mapping of blush skin and flowering time in a European pear (<Emphasis Type="Italic">Pyrus communis</Emphasis>) progeny of ‘Flamingo’ × ‘Abate Fetel’

Blush skin and flowering time are agronomic traits of interest to the Agricultural Research Council (ARC) Infruitec-Nietvoorbij pear breeding programme. The genetic control of these traits was investigated in the pear progeny derived from ‘Flamingo’ (blush cultivar) × ‘Abate Fetel’ (slightly blush) made up of 121 seedlings. Blush skin was scored phenotypically over three seasons and flowering time was scored over two seasons. A total of 160 loci from 137 simple sequence repeat (SSR) markers were scored in the progeny and used to construct parental genetic linkage maps. Quantitative trait loci (QTL) analysis revealed two QTLs for blush skin, a major QTL on linkage group (LG) 5 in ‘Flamingo’, and a major QTL on LG9 in ‘Abate Fetel’. Two SSR markers, NB101a and SAmsCO865954, were closely linked with the major QTL on LG5 in ‘Flamingo’, with alleles 139 bp and 462 bp in coupling, respectively. These markers were present in approximately 90% of the seedlings scored as good blush (class 4) based on the average data set. These two markers were used to genotype other pear accessions to validate the QTL on LG5 with the view of marker-assisted selection. Two candidate genes, MYB86 and UDP-glucosyl transferase, were associated with the QTL on LG5 and MYB21 and MYB39 were associated with the QTL on LG9. QTL analysis for flowering time revealed a major QTL located on LG9 in both parents. Marker GD142 with allele 161 bp from ‘Flamingo’ was present in approximately 88% of the seedlings that flowered earlier than either parent, based on the average data set. The QTLs and linked markers will facilitate marker-assisted selection for the improvement of these complex traits.     

Genetic mapping of QTLs controlling horticultural traits in diploid roses

A segregating progeny set of 96 F₁ diploid hybrids (2n=2x=14) between Blush Noisette (D10), one of the first seedlings from the original Champneys Pink Cluster, and Rosa wichurana (E15), was used to construct a genetic linkage map of the rose genome following a pseudo-testcross mapping strategy. A total of 133 markers (130 RAPD, one morphological and two microsatellites) were located on the 14 linkage groups (LGs) of the D10 and E15 maps, covering total map lengths of 388 and 260 cM, respectively. Due to the presence of common biparental markers the homology of four LGs between parental maps (D10-1/E15-1 to D10-4/E15-4) could be inferred. Four horticulturally interesting quantitative traits, flower size (FS), days to flowering (DF), leaf size (LS), and resistance to powdery mildew (PM) were analysed in the progeny in order to map quantitative trait loci (QTLs) controlling these traits. A total of 13 putative QTLs (LOD>3.0) were identified, four for FS, two for flowering time, five for LS, and two for resistance to PM. Possible homologies between QTLs detected in the D10 and E15 maps could be established between Fs1 and Fs3, Fs2 and Fs4, and Ls1 and Ls3. Screening for pairwise epistatic interactions between loci revealed additional, epistatic QTLs (EQTLs) for DF and LS that were not detected in the original QTL analysis. The genetic maps developed in this study will be useful to add new markers and locate genes for important traits in the genus providing a practical resource for marker-assisted selection programs in roses.     

Genetic dissection of powdery mildew resistance in interspecific half-sib grapevine families using SNP-based maps

Quantitative trait locus (QTL) identification in perennial fruit crops is impeded largely by their lengthy generation time, resulting in costly and labor-intensive maintenance of breeding programs. In a grapevine (genus Vitis) breeding program, although experimental families are typically unreplicated, the genetic backgrounds may contain similar progenitors previously selected due to their contribution of favorable alleles. In this study, we investigated the utility of joint QTL identification provided by analyzing half-sib families. The genetic control of powdery mildew was studied using two half-sib F₁ families, namely GE0711/1009 (MN1264 × MN1214; N = 147) and GE1025 (MN1264 × MN1246; N = 125) with multiple species in their ancestry. Maternal genetic maps consisting of 1077 and 1641 single nucleotide polymorphism (SNP) markers, respectively, were constructed using a pseudo-testcross strategy. Ratings of field resistance to powdery mildew were obtained based on whole-plant evaluation of disease severity. This 2-year analysis uncovered two QTLs that were validated on a consensus map in these half-sib families with improved precision relative to the parental maps. Examination of haplotype combinations based on the two QTL regions identified strong association of haplotypes inherited from ‘Seyval blanc’, through MN1264, with powdery mildew resistance. This investigation also encompassed the use of microsatellite markers to establish a correlation between 206-bp (UDV-015b) and 357-bp (VViv67) fragment sizes with resistance-carrying haplotypes. Our work is one of the first reports in grapevine demonstrating the use of SNP-based maps and haplotypes for QTL identification and tagging of powdery mildew resistance in half-sib families.     

Association mapping of quantitative resistance for <Emphasis Type="Italic">Leptosphaeria maculans</Emphasis> in oilseed rape (<Emphasis Type="Italic">Brassica napus</Emphasis> L.)

Stem canker caused by the fungus Leptosphaeria maculans is a major disease of Brassica napus. Quantitative resistance factors appear to be important components for effective and durable control of this pathogen. Quantitative trait loci (QTL) for stem canker resistance have previously been identified in the Darmor variety. However, before these QTL can be used in marker-assisted selection (MAS) to breed resistant varieties, they must be validated in a wide range of genetic backgrounds. We used an association mapping approach to confirm the markers located within the QTL previously identified in Darmor and establish their usefulness in MAS. For this, we characterized the molecular diversity of an oilseed rape collection of 128 lines showing a large spectrum of responses to infection by L. maculans, using 72 pairs of primers for simple sequence repeat and other markers. We used different association mapping models which either do or do not take into account the population structure and/or family relatedness. In all, 61 marker alleles were found to be associated with resistance to stem canker. Some of these markers were associated with previously identified QTL, which confirms their usefulness in MAS. Markers located in regions not harbouring previously identified QTL were also associated with resistance, suggesting that new QTL or allelic variants are present in the collection. All of these markers associated with stem canker resistance will help identify accessions carrying desirable alleles and facilitate QTL introgression.     

Genetic mapping in (<Emphasis Type="Italic">Populus tomentosa</Emphasis> ×<Emphasis Type="Italic"> Populus bolleana</Emphasis>) and<Emphasis Type="Italic"> P. tomentosa</Emphasis> Carr. using AFLP markers

The AFLP genetic linkage maps for two poplar cultivars were constructed with the pseudo-test-cross mapping strategy. The hybrids were derived from an interspecific backcross between the female hybrid clone TB01 (Populus tomentosa × Populus bolleana) and the male clone LM50 (P. tomentosa). A total of 782 polymorphic fragments were obtained with a PCR-based strategy using 49 enzyme-nested (EcoRI/MseI) primer combinations. Six hundred and thirty two of these fragments segregated in a 1:1 ratio (P<0.01), indicating that these DNA polymorphisms are heterozygous in one parent and null in the other. The linkage analysis was performed using Mapmaker version 3.0 with LOD 5.0 and a maximum recombination fraction () of 0.3. Map distances were estimated using the Kosambi mapping function. In the framework map for LM50 (P. tomentosa), 218 markers were aligned in 19 major linkage groups. The linked loci spanned approximately 2,683 cM of the poplar genome, with an average distance of 12.3 cM between adjacent markers. For TB01 (P. tomentosa × P. bolleana), the analysis revealed 144 loci, which were mapped to 19 major linkage groups and covered about 1,956 cM, with an average distance of 13.6 cM between adjacent markers. These maps covered about 87% and 77% of the estimated genome size of parents LM50 and TB01, respectively. The maps developed in this study lay an important foundation for future genomics research in poplar, providing a means for localizing genes controlling economically important traits in P. tomentosa.Communicated by O. Savolainen     

Detection and mapping of QTL for earliness components in a bread wheat recombinant inbred lines population

Earliness, an adaptative trait and factor of variation for agronomic characters, is a major trait in plant breeding. Its constituent traits, photoperiod sensitivity (PS), vernalization requirement (VR) and intrinsic earliness (IE), are largely under independent genetic controls. Mapping of major genes and quantitative trait loci (QTL) controlling these components is in progress. Most of the studies focusing on earliness considered it as a whole or through one (or two) of its components. The purpose of this study was to detect and map QTL for the three traits together through an experimental design combining field trials and controlled growth conditions. QTL were mapped in a population of F₇ recombinant inbred lines derived by single-seed descent from a cross between two French varieties, Renan and Récital. A map was previously constructed, based on 194 lines and 254 markers, covering about 77% of the genome. Globally, 13 QTL with a LOD>2.5 were detected, of which four control PS, five control VR and four control IE. Two major photoperiod sensitive QTL, together explaining more than 31% of the phenotypic variation, were mapped on chromosomes 2B and 2D, at the same position as the two major genes Ppd-B1 and Ppd-D1. One major VR QTL explaining (depending on the year) 21.8–39.6% of the phenotypic variation was mapped on 5A. Among the other QTL, two QTL of PS and VR not referenced so far were detected on 5A and 6D, respectively. A VR QTL already detected on 2B in a connected population was confirmed.     

Genomic regions influencing resistance to the parasitic weed <Emphasis Type="Italic">Striga hermonthica</Emphasis> in two recombinant inbred populations of sorghum

Molecular markers for resistance of sorghum to the hemi-parasitic weed Striga hermonthica were mapped in two recombinant inbred populations (RIP-1, -2) of F_3:5 lines developed from the crosses IS9830 × E36-1 (1) and N13 × E36-1 (2). The resistant parental lines were IS9830 and N13; the former is characterized by a low stimulation of striga seed germination, the latter by mechanical resistance. The genetic maps of RIP-1 and RIP-2 spanned 1,498 cM and 1,599 cM, respectively, with 137 and 157 markers distributed over 11 linkage groups. To evaluate striga resistance, we divided each RIP into set 1 (116 lines tested in 1997) and set 2 (110 lines evaluated in 1998). Field trials were conducted in five environments per year in Mali and Kenya. Heritability estimates for area under the striga number progress curve (ASNPC) in sets 1 and 2 were respectively 0.66 and 0.74 in RIP-1 and 0.81 and 0.82 in RIP-2. Across sites, composite interval mapping detected 11 QTL (quantitative trait loci) and nine QTL in sets 1 and 2 of RIP-1, explaining 77% and 80% of the genetic variance for ASNPC, respectively. The most significant RIP-1 QTL corresponded to the major-gene locus lgs (low stimulation of striga seed germination) in linkage group I. In RIP-2, 11 QTL and nine QTL explained 79% and 82% of the genetic variance for ASNPC in sets 1 and 2, respectively. Five QTL were common to both sets of each RIP, with the resistance alleles deriving from IS9830 or N13. Since their effects were validated across environments, years and independent RIP samples, these QTL are excellent candidates for marker-assisted selection.     

Location of genes involved in ear compactness in wheat (Triticum aestivum) by means of molecular markers

Quantitative trait loci (QTLs) for three traits related to ear morphology (spike length, number of spikelets, and compactness as the ratio between number of spikelets and spike length) in wheat (Triticum aestivum L.) were mapped in a doubled-haploid (DH) population derived from the cross between the cultivars Courtot and Chinese Spring. A molecular marker linkage map of this cross that had previously been constructed based on 187 DH lines and 380 markers was used for QTL mapping. The genome was well covered (85%) except chromosomes 1D and 4D and a set of anchor loci regularly spaced (one marker each 15.5 cM) were chosen for marker regression analysis. The presence of a QTL was declared at a significance threshold = 0.001. The population was grown in one location under field conditions during three years (1994, 1995 and 1998). For each trait, 4 to 6 QTLs were identified with individual effects ranging between 6.9% and 21.8% of total phenotypic variation. Several QTLs were detected that affected more than one trait. Of the QTLs 50% were detected in more than one year and two of them (number of spikelets on chromosome 2B, and compactness on chromosome 2D) emerged from the data from the three years. Only one QTL co-segregated with the gene Q known to be involved in ear morphology, namely the speltoid phenotype. However, this chromosome region explained only a minor part of the variation (7.5–11%). Other regions had a stronger effect, especially two previously unidentified regions located on chromosomes 1A and 2B. The region on the long arm of chromosome 1A was close to the locus XksuG34-1A and explained 12% of variation in spike length and 10% for compactness. On chromosome 2B, the QTL was detected for the three traits near the locus Xfbb121-2B. This QTL explained 9% to 22% of variation for the traits and was located in the same region as the gene involved in photoperiod response (Ppd2). Other regions were located at homoeologous positions on chromosomes 2A and 2D.     

Genetic linkage analysis of X-ray hypersensitivity in the LEC mutant rat

The LEC rat has been reported to exhibit X-ray hypersensitivity and deficiency in DNA double-strand break (DSB) repair. The present study was performed to map the locus responsible for this phenotype, the xhs (X-ray hypersensitivity), as the first step in identifying the responsible gene. Analysis of the progeny of (BN × LEC)F₁× LEC backcrosses indicated that the X-ray hypersensitive phenotype was controlled by multiple genetic loci in contrast to the results reported previously. Quantitative trait loci (QTL) linkage analysis revealed two responsible loci located on Chromosomes (Chr) 4 and 1. QTL on Chr 4 exhibited very strong linkage to the X-ray hypersensitive phenotype, while QTL on Chr 1 showed weak linkage. The Rad52 locus, mutation of which results in hypersensitivity to ionizing radiation and impairment of DNA DSB repair in yeast, was reported to be located on the synteneic regions of mouse Chr 6 and human Chr 12. However, mapping of the rat Rad52 locus indicated that it was located 23 cM distal to the QTL on Chr 4. Furthermore, none of the radio-sensitivity-related loci mapped previously in the rat chromosome were identical to the QTL on Chrs 4 and 1 in the LEC rat. Thus, it seems that X-ray hypersensitivity in the LEC rat is caused by mutation(s) in as-yet-undefined genes. Received: 14 February 2000 / Accepted: 17 May 2000     

Quantitative trait loci that control the oil content variation of rapeseed (Brassica napus L.)

Key message

This report describes an integrative analysis of seed-oil-content quantitative trait loci (QTL) in Brassica napus , using a high-density genetic map to align QTL among different populations.

Abstract

Rapeseed (Brassica napus) is an important source of edible oil and sustainable energy. Given the challenge involved in using only a few genes to substantially increase the oil content of rapeseed without affecting the fatty acid composition, exploitation of a greater number of genetic loci that regulate the oil content variation among rapeseed germplasm is of fundamental importance. In this study, we investigated variation in the seed-oil content among two related genetic populations of Brassica napus, the TN double-haploid population and its derivative reconstructed-F₂ population. Each population was grown in multiple experiments under different environmental conditions. Mapping of quantitative trait loci (QTL) identified 41 QTL in the TN populations. Furthermore, of the 20 pairs of epistatic interaction loci detected, approximately one-third were located within the QTL intervals. The use of common markers on different genetic maps and the TN genetic map as a reference enabled us to project QTL from an additional three genetic populations onto the TN genetic map. In summary, we used the TN genetic map of the B. napus genome to identify 46 distinct QTL regions that control seed-oil content on 16 of the 19 linkage groups of B. napus. Of these, 18 were each detected in multiple populations. The present results are of value for ongoing efforts to breed rapeseed with high oil content, and alignment of the QTL makes an important contribution to the development of an integrative system for genetic studies of rapeseed.     

Quantitative trait locus effects and environmental interaction in a sample of North American barley germ plasm

Quantitative trait locus (QTL) and QTL x environment (E) interaction effects for agronomic and malting quality traits were measured using a 123-point linkage map and multi-environment phenotype data from an F₁-derived doubled haploid population of barley (Hordeum vulgare). The QTL × E interactions were due to differences in magnitude of QTL effects. Highly significant QTL effects were found for all traits at multiple sites in the genome. Yield QTL peaks and support intervals often coincided with plant height and lodging QTL peaks and support intervals. QTL were detected in the vicinity of a previously mapped Mendelian maturity locus and known function probes for- and-amylase genes. The average map density (9.6 cM) should be adequate for molecular marker-assisted selection, particularly since there were few cases of alternative favorable alleles for different traits mapping to the same or adjacent intervals.Oreg Agric Exp Stn J No. 10150     

Comparative genome-wide mapping versus extreme pool-genotyping and development of diagnostic SNP markers linked to QTL for adult plant resistance to stripe rust in common wheat

Key message

A major stripe rust resistance QTL on chromosome 4BL was localized to a 4.5-Mb interval using comparative QTL mapping methods and validated in 276 wheat genotypes by haplotype analysis.

Abstract

CYMMIT-derived wheat line P10103 was previously identified to have adult plant resistance (APR) to stripe rust in the greenhouse and field. The conventional approach for QTL mapping in common wheat is laborious. Here, we performed QTL detection of APR using a combination of genome-wide scanning and extreme pool-genotyping. SNP-based genetic maps were constructed using the Wheat55 K SNP array to genotype a recombinant inbred line (RIL) population derived from the cross Mingxian 169?×?P10103. Five stable QTL were detected across multiple environments. After comparing SNP profiles from contrasting, extreme DNA pools of RILs six putative QTL were located to approximate chromosome positions. A major QTL on chromosome 4B was identified in F_2:4 contrasting pools from cross Zhengmai 9023?×?P10103. A consensus QTL (LOD?=?26–40, PVE?=?42–55%), named QYr.nwafu-4BL, was defined and localized to a 4.5-Mb interval flanked by SNP markers AX-110963704 and AX-110519862 in chromosome arm 4BL. Based on stripe rust response, marker genotypes, pedigree analysis and mapping data, QYr.nwafu-4BL is likely to be a new APR QTL. The applicability of the SNP-based markers flanking QYr.nwafu-4BL was validated on a diversity panel of 276 wheat lines. The additional minor QTL on chromosomes 4A, 5A, 5B and 6A enhanced the level of resistance conferred by QYr.nwafu-4BL. Marker-assisted pyramiding of QYr.nwafu-4BL and other favorable minor QTL in new wheat cultivars should improve the level of APR to stripe rust.

     

QTL analysis of flowering time inArabidopsis thaliana

Quantitative trait loci (QTL) analyses based on restriction fragment length polymorphism maps have been used to resolve the genetic control of flowering time in a cross between twoArabidopsis thaliana ecotypes H51 and Landsbergerecta, differing widely in flowering time. Five quantitative trait loci affecting flowering time were identified in this cross (RLN1-5), four of which are located in regions containing mutations or loci previously identified as conferring a late-flowering phenotype. One of these loci is coincident with theFRI locus identified as the major determinant for late flowering and vernalization responsiveness in theArabidopsis ecotype Stockholm.RLN5, which maps to the lower half of chromosome five (between markers mi69 and m233), only affected flowering time significantly under short day conditions following a vernalization period. The late-flowering phenotype of H51 compared to Landsbergerecta was due to alleles conferring late flowering at only two of the five loci. At the three other loci, H51 possessed alleles conferring early flowering in comparison to those of Landsbergerecta. Combinations of alleles conferring early and late flowering from both parents accounted for the transgressive segregation of flowering time observed within the F₂ population. Three QTL,RLN1,RLN2 andRLN3 displayed significant genotype-by-environment interactions for flowering time. A significant interaction between alleles atRLN3 andRLN4 was detected.     

Pheno2Geno - High-throughput generation of genetic markers and maps from molecular phenotypes for crosses between inbred strains

Background

Genetic markers and maps are instrumental in quantitative trait locus (QTL) mapping in segregating populations. The resolution of QTL localization depends on the number of informative recombinations in the population and how well they are tagged by markers. Larger populations and denser marker maps are better for detecting and locating QTLs. Marker maps that are initially too sparse can be saturated or derived de novo from high-throughput omics data, (e.g. gene expression, protein or metabolite abundance). If these molecular phenotypes are affected by genetic variation due to a major QTL they will show a clear multimodal distribution. Using this information, phenotypes can be converted into genetic markers.

Results

The Pheno2Geno tool uses mixture modeling to select phenotypes and transform them into genetic markers suitable for construction and/or saturation of a genetic map. Pheno2Geno excludes candidate genetic markers that show evidence for multiple possibly epistatically interacting QTL and/or interaction with the environment, in order to provide a set of robust markers for follow-up QTL mapping.We demonstrate the use of Pheno2Geno on gene expression data of 370,000 probes in 148 A. thaliana recombinant inbred lines. Pheno2Geno is able to saturate the existing genetic map, decreasing the average distance between markers from 7.1 cM to 0.89 cM, close to the theoretical limit of 0.68 cM (with 148 individuals we expect a recombination every 100/148=0.68 cM); this pinpointed almost all of the informative recombinations in the population.

Conclusion

The Pheno2Geno package makes use of genome-wide molecular profiling and provides a tool for high-throughput de novo map construction and saturation of existing genetic maps. Processing of the showcase dataset takes less than 30 minutes on an average desktop PC. Pheno2Geno improves QTL mapping results at no additional laboratory cost and with minimum computational effort. Its results are formatted for direct use in R/qtl, the leading R package for QTL studies. Pheno2Geno is freely available on CRAN under “GNU GPL v3”. The Pheno2Geno package as well as the tutorial can also be found at: http://pheno2geno.nl.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0475-6) contains supplementary material, which is available to authorized users.     

RFLP mapping of the sugary enhancer1 gene in maize

RFLP marker data from an F₂₃ population derived from a cross between a sugary1 (su1) and a sugary enhancer1 (su1, sel) inbred were used to construct a genetic linkage map of maize. This map includes 93 segregating marker loci distributed throughout the maize genome, providing a saturated linkage map that is suitable for linkage analysis with quantitative trait loci (QTL). This population, which has been immortalized in the form of sibbed F₂₃ families, was derived from each of the 214 F₂ plants and along with probe data are available to the scientific community. QTL analysis for kernel sucrose (the primary form of sugar) concentration at 20 days after pollination (DAP) uncovered the segregation of seven major QTL influencing sucrose concentration; a locus linked to umc36a described the greatest proportion of the variation (24.7%). Since maltose concentration has previously been reported to be associated with the se1 phenotype, an analysis of probe associations with maltose concentration at 40 DAP was also conducted. The highly significant association of umc36a with maltose and sucrose concentrations provided evidence that this probe is linked to se1. Phenotypic evaluation for the se1 genotype in each F₂₃ family enabled us to map the gene 12.1 cM distal to umc36a. In contrast to previous work where se1 was reported to be located on chromosome four, our data strongly suggest that the sugary enhancer1 locus maps on the the distal portion of the long arm of chromosome 2 in the maize genome.     

QTL consistency and meta-analysis for grain yield components in three generations in maize

Grain yield is the most important and complex trait in maize. In this study, a total of 258 F₉ recombinant inbred lines (RIL), derived from a cross between dent corn inbred Dan232 and popcorn inbred N04, were evaluated for eight grain yield components under four environments. Quantitative trait loci (QTL) and their epistatic interactions were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL across three generations (RIL, F_2:3 and BC₂F₂) derived from the same cross. In total, 103 QTL, 42 pairs of epistatic interactions and 16 meta-QTL (mQTL) were detected. Twelve out of 13 QTL with contributions (R ²) over 15% were consistently detected in 3–4 environments (or in combined analysis) and integrated in mQTL. Only q100GW-7-1 was detected in all four environments and in combined analysis. 100qGW-1-1 had the largest R ² (19.3–24.6%) in three environments and in combined analysis. In contrast, 35 QTL for 6 grain yield components were detected in the BC₂F₂ and F_2:3 generations, no common QTL across three generations were located in the same marker intervals. Only 100 grain weight (100GW) QTL on chromosome 5 were located in adjacent marker intervals. Four common QTL were detected across the RIL and F_2:3 generations, and two between the RIL and BC₂F₂ generations. Each of five important mQTL (mQTL7-1, mQTL10-2, mQTL4-1, mQTL5-1 and mQTL1-3) included 7–12 QTL associated with 2–6 traits. In conclusion, we found evidence of strong influence of genetic structure and environment on QTL detection, high consistency of major QTL across environments and generations, and remarkable QTL co-location for grain yield components. Fine mapping for five major QTL (q100GW-1-1, q100GW-7-1, qGWP-4-1, qERN-4-1 and qKR-4-1) and construction of single chromosome segment lines for genetic regions of five mQTL merit further studies and could be put into use in marker-assisted breeding.     

Phosphorus deficiency-induced root elongation and its QTL in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

A significant level of root elongation was induced in rice (Oryza sativa) grown under phosphorus-deficient conditions. The root elongation clearly varied among a total of 62 varieties screened under two different phosphorus levels. Two contrasting varieties, Gimbozu, with a low elongating response and Kasalath, with a high elongating response, were chosen and crossed to produce a hybrid population for QTL analyses. QTLs for the phosphorus deficiency-induced root elongation were detected by two linkage maps, i.e., one with 82 F₃ families constructed by 97 simple sequence repeat (SSR) and sequence-tag site markers and another with 97 F₈ lines by 790 amplified fragment length polymorphism and SSR markers. A single QTL for the elongation response was detected on chromosome 6, with a LOD score of 4.5 in both maps and explained about 20% of total phenotypic variance. In addition, this QTL itself, or a region tightly linked with it, partly explained an ability to reduce accumulation of excess iron in the shoots. The identified QTL will be useful to improve rice varieties against a complex nutritional disorder caused by phosphorus deficiency and iron toxicity.Electronic Supplementary Material Supplementary material is available for this article at