QTL Mapping in New Arabidopsis thaliana Advanced Intercross-Recombinant Inbred Lines

Background

Even when phenotypic differences are large between natural or domesticated strains, the underlying genetic basis is often complex, and causal genomic regions need to be identified by quantitative trait locus (QTL) mapping. Unfortunately, QTL positions typically have large confidence intervals, which can, for example, lead to one QTL being masked by another, when two closely linked loci are detected as a single QTL. One strategy to increase the power of precisely localizing small effect QTL, is the use of an intercross approach before inbreeding to produce Advanced Intercross RILs (AI-RILs).

Methodology/Principal Findings

We present two new AI-RIL populations of Arabidopsis thaliana genotyped with an average intermarker distance of 600 kb. The advanced intercrossing design led to expansion of the genetic map in the two populations, which contain recombination events corresponding to 50 kb/cM in an F₂ population. We used the AI-RILs to map QTL for light response and flowering time, and to identify segregation distortion in one of the AI-RIL populations due to a negative epistatic interaction between two genomic regions.

Conclusions/Significance

The two new AI-RIL populations, EstC and KendC, derived from crosses of Columbia (Col) to Estland (Est-1) and Kendallville (Kend-L) provide an excellent resource for high precision QTL mapping. Moreover, because they have been genotyped with over 100 common markers, they are also excellent material for comparative QTL mapping.     

Joint QTL linkage mapping for multiple-cross mating design sharing one common parent

Background

Nested association mapping (NAM) is a novel genetic mating design that combines the advantages of linkage analysis and association mapping. This design provides opportunities to study the inheritance of complex traits, but also requires more advanced statistical methods. In this paper, we present the detailed algorithm of a QTL linkage mapping method suitable for genetic populations derived from NAM designs. This method is called joint inclusive composite interval mapping (JICIM). Simulations were designed on the detected QTL in a maize NAM population and an Arabidopsis NAM population so as to evaluate the efficiency of the NAM design and the JICIM method.

Principal Findings

Fifty-two QTL were identified in the maize population, explaining 89% of the phenotypic variance of days to silking, and nine QTL were identified in the Arabidopsis population, explaining 83% of the phenotypic variance of flowering time. Simulations indicated that the detection power of these identified QTL was consistently high, especially for large-effect QTL. For rare QTL having significant effects in only one family, the power of correct detection within the 5 cM support interval was around 80% for 1-day effect QTL in the maize population, and for 3-day effect QTL in the Arabidopsis population. For smaller-effect QTL, the power diminished, e.g., it was around 50% for maize QTL with an effect of 0.5 day. When QTL were linked at a distance of 5 cM, the likelihood of mapping them as two distinct QTL was about 70% in the maize population. When the linkage distance was 1 cM, they were more likely mapped as one single QTL at an intermediary position.

Conclusions

Because it takes advantage of the large genetic variation among parental lines and the large population size, NAM is a powerful multiple-cross design for complex trait dissection. JICIM is an efficient and specialty method for the joint QTL linkage mapping of genetic populations derived from the NAM design.     

An SNP-based second-generation genetic map of Daphnia magna and its application to QTL analysis of phenotypic traits

Background

Although Daphnia is increasingly recognized as a model for ecological genomics and biomedical research, there is, as of yet, no high-resolution genetic map for the genus. Such a map would provide an important tool for mapping phenotypes and assembling the genome. Here we estimate the genome size of Daphnia magna and describe the construction of an SNP array based linkage map. We then test the suitability of the map for life history and behavioural trait mapping. The two parent genotypes used to produce the map derived from D. magna populations with and without fish predation, respectively and are therefore expected to show divergent behaviour and life-histories.

Results

Using flow cytometry we estimated the genome size of D. magna to be about 238 mb. We developed an SNP array tailored to type SNPs in a D. magna F2 panel and used it to construct a D. magna linkage map, which included 1,324 informative markers. The map produced ten linkage groups ranging from 108.9 to 203.6 cM, with an average distance between markers of 1.13 cM and a total map length of 1,483.6 cM (Kosambi corrected). The physical length per cM is estimated to be 160 kb. Mapping infertility genes, life history traits and behavioural traits on this map revealed several significant QTL peaks and showed a complex pattern of underlying genetics, with different traits showing strongly different genetic architectures.

Conclusions

The new linkage map of D. magna constructed here allowed us to characterize genetic differences among parent genotypes from populations with ecological differences. The QTL effect plots are partially consistent with our expectation of local adaptation under contrasting predation regimes. Furthermore, the new genetic map will be an important tool for the Daphnia research community and will contribute to the physical map of the D. magna genome project and the further mapping of phenotypic traits. The clones used to produce the linkage map are maintained in a stock collection and can be used for mapping QTLs of traits that show variance among the F2 clones.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1033) contains supplementary material, which is available to authorized users.     

A gene-derived SNP-based high resolution linkage map of carrot including the location of QTL conditioning root and leaf anthocyanin pigmentation

Background

Purple carrots accumulate large quantities of anthocyanins in their roots and leaves. These flavonoid pigments possess antioxidant activity and are implicated in providing health benefits. Informative, saturated linkage maps associated with well characterized populations segregating for anthocyanin pigmentation have not been developed. To investigate the genetic architecture conditioning anthocyanin pigmentation we scored root color visually, quantified root anthocyanin pigments by high performance liquid chromatography in segregating F₂, F₃ and F₄ generations of a mapping population, mapped quantitative trait loci (QTL) onto a dense gene-derived single nucleotide polymorphism (SNP)-based linkage map, and performed comparative trait mapping with two unrelated populations.

Results

Root pigmentation, scored visually as presence or absence of purple coloration, segregated in a pattern consistent with a two gene model in an F₂, and progeny testing of F₃-F₄ families confirmed the proposed genetic model. Purple petiole pigmentation was conditioned by a single dominant gene that co-segregates with one of the genes conditioning root pigmentation. Root total pigment estimate (RTPE) was scored as the percentage of the root with purple color.All five anthocyanin glycosides previously reported in carrot, as well as RTPE, varied quantitatively in the F₂ population. For the purpose of QTL analysis, a high resolution gene-derived SNP-based linkage map of carrot was constructed with 894 markers covering 635.1 cM with a 1.3 cM map resolution. A total of 15 significant QTL for all anthocyanin pigments and for RTPE mapped to six chromosomes. Eight QTL with the largest phenotypic effects mapped to two regions of chromosome 3 with co-localized QTL for several anthocyanin glycosides and for RTPE. A single dominant gene conditioning anthocyanin acylation was identified and mapped.Comparative mapping with two other carrot populations segregating for purple color indicated that carrot anthocyanin pigmentation is controlled by at least three genes, in contrast to monogenic control reported previously.

Conclusions

This study generated the first high resolution gene-derived SNP-based linkage map in the Apiaceae. Two regions of chromosome 3 with co-localized QTL for all anthocyanin pigments and for RTPE, largely condition anthocyanin accumulation in carrot roots and leaves. Loci controlling root and petiole anthocyanin pigmentation differ across diverse carrot genetic backgrounds.

Electronic supplementary material

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Combining two Meishan F2 crosses improves the detection of QTL on pig chromosomes 2, 4 and 6

Background

In pig, a number of experiments have been set up to identify QTL and a multitude of chromosomal regions harbouring genes influencing traits of interest have been identified. However, the mapping resolution remains limited in most cases and the detected QTL are rather inaccurately located. Mapping accuracy can be improved by increasing the number of phenotyped and genotyped individuals and/or the number of informative markers. An alternative approach to overcome the limited power of individual studies is to combine data from two or more independent designs.

Methods

In the present study we report a combined analysis of two independent design (a French and a Dutch F2 experimental designs), with 2000 F2 individuals. The purpose was to further map QTL for growth and fatness on pig chromosomes 2, 4 and 6. Using QTL-map software, uni- and multiple-QTL detection analyses were applied separately on the two pedigrees and then on the combination of the two pedigrees.

Results

Joint analyses of the combined pedigree provided (1) greater significance of shared QTL, (2) exclusion of false suggestive QTL and (3) greater mapping precision for shared QTL.

Conclusions

Combining two Meishan x European breeds F2 pedigrees improved the mapping of QTL compared to analysing pedigrees separately. Our work was facilitated by the access to raw phenotypic data and DNA of animals from both pedigrees and the combination of the two designs with the addition of new markers allowed us to fine map QTL without phenotyping additional animals.     

Genetic dynamics underlying phenotypic development of biomass yield in triticale

Background

The nature of dynamic traits with their phenotypic plasticity suggests that they are under the control of a dynamic genetic regulation. We employed a precision phenotyping platform to non-invasively assess biomass yield in a large mapping population of triticale at three developmental stages.

Results

Using multiple-line cross QTL mapping we identified QTL for each of these developmental stages which explained a considerable proportion of the genotypic variance. Some QTL were identified at each developmental stage and thus contribute to biomass yield throughout the studied developmental phases. Interestingly, we also observed QTL that were only identified for one or two of the developmental stages illustrating a temporal contribution of these QTL to the trait. In addition, epistatic QTL were detected and the epistatic interaction landscape was shown to dynamically change with developmental progression.

Conclusions

In summary, our results reveal the temporal dynamics of the genetic architecture underlying biomass accumulation in triticale and emphasize the need for a temporal assessment of dynamic traits.

Electronic supplementary material

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Fine mapping and replication of QTL in outbred chicken advanced intercross lines

Background

Linkage mapping is used to identify genomic regions affecting the expression of complex traits. However, when experimental crosses such as F₂ populations or backcrosses are used to map regions containing a Quantitative Trait Locus (QTL), the size of the regions identified remains quite large, i.e. 10 or more Mb. Thus, other experimental strategies are needed to refine the QTL locations. Advanced Intercross Lines (AIL) are produced by repeated intercrossing of F₂ animals and successive generations, which decrease linkage disequilibrium in a controlled manner. Although this approach is seen as promising, both to replicate QTL analyses and fine-map QTL, only a few AIL datasets, all originating from inbred founders, have been reported in the literature.

Methods

We have produced a nine-generation AIL pedigree (n = 1529) from two outbred chicken lines divergently selected for body weight at eight weeks of age. All animals were weighed at eight weeks of age and genotyped for SNP located in nine genomic regions where significant or suggestive QTL had previously been detected in the F₂ population. In parallel, we have developed a novel strategy to analyse the data that uses both genotype and pedigree information of all AIL individuals to replicate the detection of and fine-map QTL affecting juvenile body weight.

Results

Five of the nine QTL detected with the original F₂ population were confirmed and fine-mapped with the AIL, while for the remaining four, only suggestive evidence of their existence was obtained. All original QTL were confirmed as a single locus, except for one, which split into two linked QTL.

Conclusions

Our results indicate that many of the QTL, which are genome-wide significant or suggestive in the analyses of large intercross populations, are true effects that can be replicated and fine-mapped using AIL. Key factors for success are the use of large populations and powerful statistical tools. Moreover, we believe that the statistical methods we have developed to efficiently study outbred AIL populations will increase the number of organisms for which in-depth complex traits can be analyzed.     

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.     

Construction of a high-density genetic map based on large-scale markers developed by specific length amplified fragment sequencing (SLAF-seq) and its application to QTL analysis for isoflavone content in Glycine max

Background

Quantitative trait locus (QTL) mapping is an efficient approach to discover the genetic architecture underlying complex quantitative traits. However, the low density of molecular markers in genetic maps has limited the efficiency and accuracy of QTL mapping. In this study, specific length amplified fragment sequencing (SLAF-seq), a new high-throughput strategy for large-scale SNP discovery and genotyping based on next generation sequencing (NGS), was employed to construct a high-density soybean genetic map using recombinant inbred lines (RILs, Luheidou2 × Nanhuizao, F_5:8). With this map, the consistent QTLs for isoflavone content across various environments were identified.

Results

In total, 23 Gb of data containing 87,604,858 pair-end reads were obtained. The average coverage for each SLAF marker was 11.20-fold for the female parent, 12.51-fold for the male parent, and an average of 3.98-fold for individual RILs. Among the 116,216 high-quality SLAFs obtained, 9,948 were polymorphic. The final map consisted of 5,785 SLAFs on 20 linkage groups (LGs) and spanned 2,255.18 cM in genome size with an average distance of 0.43 cM between adjacent markers. Comparative genomic analysis revealed a relatively high collinearity of 20 LGs with the soybean reference genome. Based on this map, 41 QTLs were identified that contributed to the isoflavone content. The high efficiency and accuracy of this map were evidenced by the discovery of genes encoding isoflavone biosynthetic enzymes within these loci. Moreover, 11 of these 41 QTLs (including six novel loci) were associated with isoflavone content across multiple environments. One of them, qIF20-2, contributed to a majority of isoflavone components across various environments and explained a high amount of phenotypic variance (8.7% - 35.3%). This represents a novel major QTL underlying isoflavone content across various environments in soybean.

Conclusions

Herein, we reported a high-density genetic map for soybean. This map exhibited high resolution and accuracy. It will facilitate the identification of genes and QTLs underlying essential agronomic traits in soybean. The novel major QTL for isoflavone content is useful not only for further study on the genetic basis of isoflavone accumulation, but also for marker-assisted selection (MAS) in soybean breeding in the future.

Electronic supplementary material

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Genetic architecture of hybrid male sterility in Drosophila: analysis of intraspecies variation for interspecies isolation

Background

The genetic basis of postzygotic isolation is a central puzzle in evolutionary biology. Evolutionary forces causing hybrid sterility or inviability act on the responsible genes while they still are polymorphic, thus we have to study these traits as they arise, before isolation is complete.

Methodology/Principal Findings

Isofemale strains of D. mojavensis vary significantly in their production of sterile F₁ sons when females are crossed to D. arizonae males. We took advantage of the intraspecific polymorphism, in a novel design, to perform quantitative trait locus (QTL) mapping analyses directly on F₁ hybrid male sterility itself. We found that the genetic architecture of the polymorphism for hybrid male sterility (HMS) in the F₁ is complex, involving multiple QTL, epistasis, and cytoplasmic effects.

Conclusions/Significance

The role of extensive intraspecific polymorphism, multiple QTL, and epistatic interactions in HMS in this young species pair shows that HMS is arising as a complex trait in this system. Directional selection alone would be unlikely to maintain polymorphism at multiple loci, thus we hypothesize that directional selection is unlikely to be the only evolutionary force influencing postzygotic isolation.     

QTL analysis of root traits as related to phosphorus efficiency in soybean

Background and Aims

Low phosphorus (P) availability is a major constraint to soybean growth and production, especially in tropical and subtropical areas. Root traits have been shown to play critical roles in P efficiency in crops. Identification of the quantitative trait loci (QTLs) conferring superior root systems could significantly enhance genetic improvement in soybean P efficiency.

Methods

A population of 106 F₉ recombinant inbred lines (RILs) derived from a cross between BD2 and BX10, which contrast in both P efficiency and root architecture, was used for mapping and QTL analysis. Twelve traits were examined in acid soils. A linkage map was constructed using 296 simple sequence repeat (SSR) markers with the Kosambi function, and the QTLs associated with these traits were detected by composite interval mapping and multiple-QTL mapping.

Key Results

The first soybean genetic map based on field data from parental genotypes contrasting both in P efficiency and root architecture was constructed. Thirty-one putative QTLs were detected on five linkage groups, with corresponding contribution ratios of 9·1–31·1 %. Thirteen putative QTLs were found for root traits, five for P content, five for biomass and five for yield traits. Three clusters of QTLs associated with the traits for root and P efficiency at low P were located on the B1 linkage group close to SSR markers Satt519 and Satt519-Sat_128, and on the D2 group close to Satt458; and one cluster was on the B1 linkage group close to Satt519 at high P.

Conclusions

Most root traits in soybean were conditioned by more than two minor QTLs. The region closer to Satt519 on the B1 linkage group might have great potential for future genetic improvement for soybean P efficiency through root selection.     

Genetic architecture is more complex for resistance to Septoria tritici blotch than to Fusarium head blight in Central European winter wheat

Background

Fusarium head blight (FHB) and Septoria tritici blotch (STB) severely impair wheat production. With the aim to further elucidate the genetic architecture underlying FHB and STB resistance, we phenotyped 1604 European wheat hybrids and their 135 parental lines for FHB and STB disease severities and determined genotypes at 17,372 single-nucleotide polymorphic loci.

Results

Cross-validated association mapping revealed the absence of large effect QTL for both traits. Genomic selection showed a three times higher prediction accuracy for FHB than STB disease severity for test sets largely unrelated to the training sets.

Conclusions

Our findings suggest that the genetic architecture is less complex and, hence, can be more properly tackled to perform accurate prediction for FHB than STB disease severity. Consequently, FHB disease severity is an interesting model trait to fine-tune genomic selection models exploiting beyond relatedness also knowledge of the genetic architecture.

Electronic supplementary material

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Overlapping mouse subcongenic strains successfully separate two linked body fat QTL on distal MMU 2

Background

Mouse chromosome 2 is linked to growth and body fat phenotypes in many mouse crosses. With the goal to identify the underlying genes regulating growth and body fat on mouse chromosome 2, we developed five overlapping subcongenic strains that contained CAST/EiJ donor regions in a C57BL/6J^hg/hg background (hg is a spontaneous deletion of 500 Kb on mouse chromosome 10). To fine map QTL on distal mouse chromosome 2 a total of 1,712 F2 mice from the five subcongenic strains, plus 278 F2 mice from the HG2D founder congenic strain were phenotyped and analyzed. Interval mapping (IM) and composite IM (CIM) were performed on body weight and body fat traits on a combination of SNP and microsatellite markers, which generated a high-density genotyping panel.

Results

Phenotypic analysis and interval mapping of total fat mass identified two QTL on distal mouse chromosome 2. One QTL between 150 and 161 Mb, Fatq2a, and the second between 173.3 and 175.6 Mb, Fatq2b. The two QTL reside in different congenic strains with significant total fat differences between homozygous cast/cast and b6/b6 littermates. Both of these QTL were previously identified only as a single QTL affecting body fat, Fatq2. Furthermore, through a novel approach referred here as replicated CIM, Fatq2b was mapped to the Gnas imprinted locus.

Conclusions

The integration of subcongenic strains, high-density genotyping, and CIM succesfully partitioned two previously linked QTL 20 Mb apart, and the strongest QTL, Fatq2b, was fine mapped to a ~2.3 Mb region interval encompassing the Gnas imprinted locus.

Electronic supplementary material

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Genetic Analysis of Central Carbon Metabolism Unveils an Amino Acid Substitution That Alters Maize NAD-Dependent Isocitrate Dehydrogenase Activity

Background

Central carbon metabolism (CCM) is a fundamental component of life. The participating genes and enzymes are thought to be structurally and functionally conserved across and within species. Association mapping utilizes a rich history of mutation and recombination to achieve high resolution mapping. Therefore, applying association mapping in maize (Zea mays ssp. mays), the most diverse model crop species, to study the genetics of CCM is a particularly attractive system.

Methodology/Principal Findings

We used a maize diversity panel to test the CCM functional conservation. We found heritable variation in enzyme activity for every enzyme tested. One of these enzymes was the NAD-dependent isocitrate dehydrogenase (IDH, E.C. 1.1.1.41), in which we identified a novel amino-acid substitution in a phylogenetically conserved site. Using candidate gene association mapping, we identified that this non-synonymous polymorphism was associated with IDH activity variation. The proposed mechanism for the IDH activity variation includes additional components regulating protein level. With the comparison of sequences from maize and teosinte (Zea mays ssp. Parviglumis), the maize wild ancestor, we found that some CCM genes had also been targeted for selection during maize domestication.

Conclusions/Significance

Our results demonstrate the efficacy of association mapping for dissecting natural variation in primary metabolic pathways. The considerable genetic diversity observed in maize CCM genes underlies heritable phenotypic variation in enzyme activities and can be useful to identify putative functional sites.     

Mapping in the era of sequencing: high density genotyping and its application for mapping TYLCV resistance in Solanum pimpinellifolium

Background

A RIL population between Solanum lycopersicum cv. Moneymaker and S. pimpinellifolium G1.1554 was genotyped with a custom made SNP array. Additionally, a subset of the lines was genotyped by sequencing (GBS).

Results

A total of 1974 polymorphic SNPs were selected to develop a linkage map of 715 unique genetic loci. We generated plots for visualizing the recombination patterns of the population relating physical and genetic positions along the genome.This linkage map was used to identify two QTLs for TYLCV resistance which contained favourable alleles derived from S. pimpinellifolium. Further GBS was used to saturate regions of interest, and the mapping resolution of the two QTLs was improved. The analysis showed highest significance on Chromosome 11 close to the region of 51.3 Mb (qTy-p11) and another on Chromosome 3 near 46.5 Mb (qTy-p3). Furthermore, we explored the population using untargeted metabolic profiling, and the most significant differences between susceptible and resistant plants were mainly associated with sucrose and flavonoid glycosides.

Conclusions

The SNP information obtained from an array allowed a first QTL screening of our RIL population. With additional SNP data of a RILs subset, obtained through GBS, we were able to perform an in silico mapping improvement to further confirm regions associated with our trait of interest. With the combination of different ~ omics platforms we provide valuable insight into the genetics of S. pimpinellifolium-derived TYLCV resistance.

Electronic supplementary material

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Genetic analysis of Verticillium wilt resistance in a backcross inbred line population and a meta-analysis of quantitative trait loci for disease resistance in cotton

Background

Verticillium wilt (VW) and Fusarium wilt (FW), caused by the soil-borne fungi Verticillium dahliae and Fusarium oxysporum f. sp. vasinfectum, respectively, are two most destructive diseases in cotton production worldwide. Root-knot nematodes (Meloidogyne incognita, RKN) and reniform nematodes (Rotylenchulus reniformis, RN) cause the highest yield loss in the U.S. Planting disease resistant cultivars is the most cost effective control method. Numerous studies have reported mapping of quantitative trait loci (QTLs) for disease resistance in cotton; however, very few reliable QTLs were identified for use in genomic research and breeding.

Results

This study first performed a 4-year replicated test of a backcross inbred line (BIL) population for VW resistance, and 10 resistance QTLs were mapped based on a 2895 cM linkage map with 392 SSR markers. The 10 VW QTLs were then placed to a consensus linkage map with other 182 VW QTLs, 75 RKN QTLs, 27 FW QTLs, and 7 RN QTLs reported from 32 publications. A meta-analysis of QTLs identified 28 QTL clusters including 13, 8 and 3 QTL hotspots for resistance to VW, RKN and FW, respectively. The number of QTLs and QTL clusters on chromosomes especially in the A-subgenome was significantly correlated with the number of nucleotide-binding site (NBS) genes, and the distribution of QTLs between homeologous A- and D- subgenome chromosomes was also significantly correlated.

Conclusions

Ten VW resistance QTL identified in a 4-year replicated study have added useful information to the understanding of the genetic basis of VW resistance in cotton. Twenty-eight disease resistance QTL clusters and 24 hotspots identified from a total of 306 QTLs and linked SSR markers provide important information for marker-assisted selection and high resolution mapping of resistance QTLs and genes. The non-overlapping of most resistance QTL hotspots for different diseases indicates that their resistances are controlled by different genes.

Electronic supplementary material

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Susceptibility to klebsiella pneumonaie infection in collaborative cross mice is a complex trait controlled by at least three loci acting at different time points

Background

Klebsiella pneumoniae (Kp) is a bacterium causing severe pneumonia in immunocompromised hosts and is often associated with sepsis. With the rise of antibiotic resistant bacteria, there is a need for new effective and affordable control methods; understanding the genetic architecture of susceptibility to Kp will help in their development. We performed the first quantitative trait locus (QTL) mapping study of host susceptibility to Kp infection in immunocompetent Collaborative Cross mice (CC). We challenged 328 mice from 73 CC lines intraperitoneally with 10⁴ colony forming units of Kp strain K2. Survival and body weight were monitored for 15 days post challenge. 48 of the CC lines were genotyped with 170,000 SNPs, with which we mapped QTLs.

Results

CC lines differed significantly (P < 0.05) in mean survival time, between 1 to 15 days post infection, and broad sense heritability was 0.45. Distinct QTL were mapped at specific time points during the challenge. A QTL on chromosome 4 was found only on day 2 post infection, and QTL on chromosomes 8 and 18, only on day 8. By using the sequence variations of the eight inbred strain founders of the CC to refine QTL localization we identify several candidate genes.

Conclusion

Host susceptibility to Kp is a complex trait, controlled by multiple genetic factors that act sequentially during the course of infection.

Electronic supplementary material

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A Single Locus Is Responsible for Salinity Tolerance in a Chinese Landrace Barley (Hordeum vulgare L.)

Introduction

Salinity and waterlogging are two major abiotic stresses severely limiting barley production. The lack of a reliable screening method makes it very hard to improve the tolerance through breeding programs.

Methods

This work used 188 DH lines from a cross between a Chinese landrace variety, TX9425 (waterlogging and salinity tolerant), and a Japanese malting barley, Naso Nijo (waterlogging and salinity sensitive), to identify QTLs associated with the tolerance.

Results

Four QTLs were found for waterlogging tolerance. The salinity tolerance was evaluated with both a hydroponic system and in potting mixture. In the trial with potting mixture, only one major QTL was identified to associate with salinity tolerance. This QTL explained nearly 50% of the phenotypic variation, which makes it possible for further fine mapping and cloning of the gene. This QTL was also identified in the hydroponic experiment for different salt-related traits. The position of this QTL was located at a similar position to one of the major QTLs for waterlogging tolerance, indicating the possibility of similar mechanisms controlling both waterlogging and salinity tolerance.

Conclusion

The markers associated with the QTL provided a unique opportunity in breeding programs for selection of salinity and waterlogging tolerance.