Statistical properties of QTL linkage mapping in biparental genetic populations

A Compendium for Novel Marker-Based Breeding Strategies in Eggplant

The worldwide production of eggplant is estimated at about 58 Mt, with China, India and Egypt being the major producing countries. Breeding efforts in the species have mainly focused on increasing productivity, abiotic and biotic tolerance/resistance, shelf-life, the content of health-promoting metabolites in the fruit rather than decreasing the content of anti-nutritional compounds in the fruit. From the literature, we collected information on mapping quantitative trait loci (QTLs) affecting eggplant's traits following a biparental or multi-parent approach as well as genome-wide association (GWA) studies. The positions of QTLs were lifted according to the eggplant reference line (v4.1) and more than 700 QTLs were identified, here organized into 180 quantitative genomic regions (QGRs). Our findings thus provide a tool to: (i) determine the best donor genotypes for specific traits; (ii) narrow down QTL regions affecting a trait by combining information from different populations; (iii) pinpoint potential candidate genes.

Construction of a high density genetic linkage map to define the locus conferring seedlessness from Mukaku Kishu mandarin

Mukaku Kishu ('MK'), a small sized mandarin, is an important source of seedlessness in citrus breeding. Identification and mapping the gene(s) governing 'MK' seedlessness will expedite seedless cultivar development. In this study, two 'MK'-derived mapping populations- LB8-9 Sugar Belle^® ('SB') × 'MK' (N=97) and Daisy ('D') × 'MK' (N=68) were genotyped using an Axiom_Citrus56 Array encompassing 58,433 SNP probe sets, and population specific male and female parent linkage maps were constructed. The parental maps of each population were integrated to produce sub-composite maps, which were further merged to develop a consensus linkage map. All the parental maps (except 'MK_D') had nine major linkage groups, and contained 930 ('SB'), 810 ('MK_SB'), 776 ('D') and 707 ('MK_D') SNPs. The linkage maps displayed 96.9 ('MK_D') to 98.5% ('SB') chromosomal synteny with the reference Clementine genome. The consensus map was comprised of 2588 markers including a phenotypic seedless (Fs)-locus and spanned a genetic distance of 1406.84 cM, with an average marker distance of 0.54 cM, which is substantially lower than the reference Clementine map. For the phenotypic Fs-locus, the distribution of seedy and seedless progenies in both 'SB' × 'MK' (55:42, χ² = 1.74) and 'D' × 'MK' populations (33:35, χ² = 0.06) followed a test cross pattern. The Fs-locus mapped on chromosome 5 with SNP marker 'AX-160417325' at 7.4 cM in 'MK_SB' map and between two SNP markers 'AX-160536283' and 'AX-160906995' at a distance of 2.4 and 4.9 cM, respectively in 'MK_D' map. The SNPs 'AX-160417325' and 'AX-160536283' correctly predicted seedlessness of 25-91.9% progenies in this study. Based on the alignment of flanking SNP markers to the Clementine reference genome, the candidate gene for seedlessness hovered in a ~ 6.0 Mb region between 3.97 Mb (AX-160906995) to 10.00 Mb (AX-160536283). This region has 131 genes of which 13 genes (belonging to seven gene families) reportedly express in seed coat or developing embryo. The findings of the study will prove helpful in directing future research for fine mapping this region and eventually underpinning the exact causative gene governing seedlessness in 'MK'.

Combined QTL mapping on bi-parental immortalized heterozygous populations to detect the genetic architecture on heterosis

From bi-parental pure-inbred lines (PIL), immortalized backcross (i.e., IB₁ and IB₂, representing the two directions of backcrossing) and F₂ (i.e., IF₂) populations can be developed. These populations are suitable for genetic studies on heterosis, due to the present of both homozygous and heterozygous genotypes, and in the meantime allow repeated phenotyping trials across multiple locations and years. In this study, we developed a combined approach of quantitative trait locus (QTL) mapping, when some or all of the four immortalized populations (i.e., PIL, IB₁, IB₂, and IF₂) are available. To estimate the additive and dominant effects simultaneously and accurately, suitable transformations are made on phenotypic values from different populations. When IB₁ and IB₂ are present, summation and subtraction are used. When IF₂ and PIL are available, mid-parental values and mid-parental heterosis are used. One-dimensional genomic scanning is performed to detect the additive and dominant QTLs, based on the algorithm of inclusive composite interval mapping (ICIM). The proposed approach was applied to one IF₂ population together with PIL in maize, and identified ten QTLs on ear length, showing varied degrees of dominance. Simulation studies indicated the proposed approach is similar to or better than individual population mapping by QTL detection power, false discovery rate (FDR), and estimated QTL position and effects.

Molecular mapping of drought-responsive QTLs during the reproductive stage of rice using a GBS (genotyping-by-sequencing) based SNP linkage map

BACKGROUND

In rice, drought stress at reproductive stage drastically reduces yield, which in turn hampers farmer's efforts towards crop production. The majority of the rice varieties have resistance genes against several abiotic and biotic stresses. Therefore, the traditional landraces were studied to identify QTLs/candidate genes associated with drought tolerance.

METHODS AND RESULTS

A high-density SNP-based genetic map was constructed using a Genotyping-by-sequencing (GBS) approach. The recombinant inbred lines (RILs) derived from crossing 'Banglami × Ranjit' were used for QTL analysis. A total map length of 1306.424 cM was constructed, which had an average inter-marker distance of 0.281 cM. The phenotypic evaluation of F₆ and F₇ RILs were performed under drought stress and control conditions. A total of 42 QTLs were identified under drought stress and control conditions for yield component traits explaining 1.95-13.36% of the total phenotypic variance (PVE). Among these, 19 QTLs were identified under drought stress conditions, whereas 23 QTLs were located under control conditions. A total of 4 QTLs explained a PVE ≥ 10% which are considered as the major QTLs. Moreover, bioinformatics analysis revealed the presence of 6 candidate genes, which showed differential expression under drought and control conditions.

CONCLUSION

These QTLs/genes may be deployed for marker-assisted pyramiding to improve drought tolerance in the existing rice varieties.

Blib is a multi-module simulation platform for genetics studies and intelligent breeding

Simulation is an efficient approach for the investigation of theoretical and applied issues in population and quantitative genetics, and animal and plant breeding. In this study, we report a multi-module simulation platform called Blib, that is able to handle more complicated genetic effects and models than existing tools. Two derived data types are first defined in Blib, one to hold the required information on genetic models, and the other one to represent the genetics and breeding populations. A number of subroutines are then developed to perform specific tasks. Four case studies are present as examples to show the applications of Blib, i.e., genetic drift of multiple alleles in randomly mating populations, joint effects of neutral mutation and genetic drift, comparison of mass versus family selection, and choice of testers in hybrid breeding. Blib together with its application modules, has great potential to benefit theoretical genetic studies and intelligent breeding by simulating and predicting outcomes in a large number of scenarios, and identifying the best optimum selection and crossing schemes.

GAHP: An integrated software package on genetic analysis with bi-parental immortalized heterozygous populations

GAHP is a freely available software package for genetic analysis with bi-parental immortalized heterozygous and pure-line populations. The package is project-based and integrated with multiple functions. All operations and running results are properly saved in a project, which can be recovered when the project is re-open by the package. Four functionalities have been implemented in the current version of GAHP, i.e., 1) MHP: visualization of genetic linkage maps; 2) VHP: analysis of variance (ANOVA) and estimation of heritability on phenotypic data; 3) QHP: quantitative trait locus (QTL) mapping on both genotypic and phenotypic data; 4) SHP: simulation of bi-parental immortalized heterozygous and pure-line populations, and power analysis of QTL mapping. VHP and QHP can be conducted in individual populations, as well as in multiple populations by the combined analysis. Input files are arranged either in the plain text format with an extension name same as the functionality or in the MS Excel formats. Output files have the same prefix name as the input file, but with different extensions to indicate their contents. Three characters before the extension names stand for the types of populations used in analysis. In the interface of the software package, input files are grouped by functionality, and output files are grouped by individual or combined mapping populations. In addition to the text-format outputs, the constructed linkage map can be visualized per chromosome or for a number of selected chromosomes; line plots and bi-plots can be drawn from QTL mapping results and phenotypic data. Functionalities and analysis methods available in GAHP help the investigation of genetic architectures of complex traits and the mechanism of heterosis in plants.

Quantitative trait loci mapping reveals an oligogenic architecture of a rapidly adapting trait during the European invasion of common ragweed

Biological invasions offer a unique opportunity to investigate evolution over contemporary timescales. Rapid adaptation to local climates during range expansion can be a major determinant of invasion success, yet fundamental questions remain about its genetic basis. This study sought to investigate the genetic basis of climate adaptation in invasive common ragweed (Ambrosia artemisiifolia). Flowering time adaptation is key to this annual species' invasion success, so much so that it has evolved repeated latitudinal clines in size and phenology across its native and introduced ranges despite high gene flow among populations. Here, we produced a high-density linkage map (4493 SNPs) and paired this with phenotypic data from an F2 mapping population (n = 336) to identify one major and two minor quantitative trait loci (QTL) underlying flowering time and height differentiation in this species. Within each QTL interval, several candidate flowering time genes were also identified. Notably, the major flowering time QTL detected in this study was found to overlap with a previously identified haploblock (putative inversion). Multiple genetic maps of this region identified evidence of suppressed recombination in specific genotypes, consistent with inversions. These discoveries support the expectation that a concentrated genetic architecture with fewer, larger, and more tightly linked alleles should underlie rapid local adaptation during invasion, particularly when divergently adapting populations experience high levels of gene flow.

Evaluation of nine statistics to identify QTLs in bulk segregant analysis using next generation sequencing approaches

Background

Bulk segregant analysis (BSA) combined with next generation sequencing is a powerful tool to identify quantitative trait loci (QTL). The impact of the size of the study population and the percentage of extreme genotypes analysed have already been assessed. But a good comparison of statistical approaches designed to identify QTL regions using next generation sequencing (NGS) technologies for BSA is still lacking.

Results

We developed an R code to simulate QTLs in bulks of F2 contrasted lines. We simulated a range of recombination rates based on estimations using different crop species. The simulations were used to benchmark the ability of statistical methods identify the exact location of true QTLs. A single QTL led to a shift in allele frequency across a large fraction of the chromosome for plant species with low recombination rate. The smoothed version of all statistics performed best notably the smoothed Euclidean distance-based statistics was always found to be more accurate in identifying the location of QTLs. We propose a simulation approach to build confidence interval statistics for the detection of QTLs.

Conclusion

We highlight the statistical methods best suited for BSA studies using NGS technologies in crops even when recombination rate is low. We also provide simulation codes to build confidence intervals and to assess the impact of recombination for application to other studies. This computational study will help select NGS-based BSA statistics that are useful to the broad scientific community.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08718-y.

Validating a Major Quantitative Trait Locus and Predicting Candidate Genes Associated With Kernel Width Through QTL Mapping and RNA-Sequencing Technology Using Near-Isogenic Lines in Maize

Kernel size is an important agronomic trait for grain yield in maize. The purpose of this study was to validate a major quantitative trait locus (QTL), qKW-1, which was identified in the F₂ and F_2:3 populations from a cross between the maize inbred lines SG5/SG7 and to predict candidate genes for kernel width (KW) in maize. A major QTL, qKW-1, was mapped in multiple environments in our previous study. To validate and fine map qKW-1, near-isogenic lines (NILs) with 469 individuals were developed by continuous backcrossing between SG5 as the donor parent and SG7 as the recurrent parent. Marker-assisted selection was conducted from the BC₂F₁ generation with simple sequence repeat (SSR) markers near qKW-1. A secondary linkage map with four markers, PLK12, PLK13, PLK15, and PLK17, was developed and used for mapping the qKW-1 locus. Finally, qKW-1 was mapped between the PLK12 and PLK13 intervals, with a distance of 2.23 cM to PLK12 and 0.04 cM to PLK13, a confidence interval of 5.3 cM and a phenotypic contribution rate of 23.8%. The QTL mapping result obtained was further validated by using selected overlapping recombinant chromosomes on the target segment of maize chromosome 3. Transcriptome analysis showed that a total of 12 out of 45 protein-coding genes differentially expressed between the two parents were detected in the identified qKW-1 physical interval by blasting with the Zea_Mays_B73 v4 genome. GRMZM2G083176 encodes the Niemann-Pick disease type C, and GRMZM2G081719 encodes the nitrate transporter 1 (NRT1) protein. The two genes GRMZM2G083176 and GRMZM2G081719 were predicted to be candidate genes of qKW-1. Reverse transcription-polymerase chain reaction (RT-qPCR) validation was conducted, and the results provide further proof of the two candidate genes most likely responsible for qKW-1. The work will not only help to understand the genetic mechanisms of KW in maize but also lay a foundation for further cloning of promising loci.

QTL identification, fine mapping, and marker development for breeding peanut (Arachis hypogaea L.) resistant to bacterial wilt

A major QTL, qBWA12, was fine mapped to a 216.68 kb physical region, and A12.4097252 was identified as a useful KASP marker for breeding peanut varieties resistant to bacterial wilt. Bacterial wilt, caused by Ralstonia solanacearum, is a major disease detrimental to peanut production in China. Breeding disease-resistant peanut varieties is the most economical and effective way to prevent the disease and yield loss. Fine mapping the QTLs for bacterial wilt resistance is critical for the marker-assisted breeding of disease-resistant varieties. A recombinant inbred population comprising 521 lines was used to construct a high-density genetic linkage map and to identify QTLs for bacterial wilt resistance following restriction-site-associated DNA sequencing. The genetic map, which included 5120 SNP markers, covered a length of 3179 cM with an average marker distance of 0.6 cM. Four QTLs for bacterial wilt resistance were mapped on four chromosomes. One major QTL, qBWA12, with LOD score of 32.8-66.0 and PVE of 31.2-44.8%, was stably detected in all four development stages investigated over the 3 trial years. Additionally, qBWA12 spanned a 2.7 cM region, corresponding to approximately 0.4 Mb and was fine mapped to a 216.7 kb region by applying KASP markers that were polymorphic between the two parents based on whole-genome resequencing data. In a large collection of breeding and germplasm lines, it was proved that KASP marker A12.4097252 can be applied for the marker-assisted breeding to develop peanut varieties resistant to bacterial wilt. Of the 19 candidate genes in the region covered by qBWA12, nine NBS-LRR genes should be further investigated regarding their potential contribution to the resistance of peanut against bacterial wilt.

Identification and Validation of Quantitative Trait Loci Mapping for Spike-Layer Uniformity in Wheat

Spike-layer uniformity (SLU), the consistency of the spike distribution in the vertical space, is an important trait. It directly affects the yield potential and appearance. Revealing the genetic basis of SLU will provide new insights into wheat improvement. To map the SLU-related quantitative trait loci (QTL), 300 recombinant inbred lines (RILs) that were derived from a cross between H461 and Chinese Spring were used in this study. The RILs and parents were tested in fields from two continuous years from two different pilots. Phenotypic analysis showed that H461 was more consistent in the vertical spatial distribution of the spike layer than in Chinese Spring. Based on inclusive composite interval mapping, four QTL were identified for SLU. There were two major QTL on chromosomes 2BL and 2DL and two minor QTL on chromosomes 1BS and 2BL that were identified. The additive effects of QSlu.sicau-1B, Qslu.sicau-2B-2, and QSlu.sicau-2D were all from the parent, H461. The major QTL, QSlu.sicau-2B-2 and QSlu.sicau-2D, were detected in each of the conducted trials. Based on the best linear unbiased prediction values, the two loci explained 23.97% and 15.98% of the phenotypic variation, respectively. Compared with previous studies, the two major loci were potentially novel and the two minor loci were overlapped. Based on the kompetitive allele-specific PCR (KASP) marker, the genetic effects for QSlu.sicau-2B-2 were validated in an additional RIL population. The genetic effects ranged from 26.65% to 32.56%, with an average value of 30.40%. In addition, QSlu.sicau-2B-2 showed a significant (p < 0.01) and positive influence on the spike length, spikelet number, and thousand kernel weight. The identified QTL and the developed KASP marker will be helpful for fine-mapping these loci, finally contributing to wheat breeding programs in a marker-assisted selection way.

Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis

Grain weight is a key determinant for grain yield potential in wheat, which is highly governed by a type of quantitative genetic basis. The identification of major quantitative trait locus (QTL) and functional genes are urgently required for molecular improvements in wheat grain yield. In this study, major genomic regions and putative candidate genes for thousand grain weight (TGW) were revealed by integrative approaches with QTL linkage mapping, meta-analysis and transcriptome evaluation. Forty-five TGW QTLs were detected using a set of recombinant inbred lines, explaining 1.76-12.87% of the phenotypic variation. Of these, ten stable QTLs were identified across more than four environments. Meta-QTL (MQTL) analysis were performed on 394 initial TGW QTLs available from previous studies and the present study, where 274 loci were finally refined into 67 MQTLs. The average confidence interval of these MQTLs was 3.73-fold less than that of initial QTLs. A total of 134 putative candidate genes were mined within MQTL regions by combined analysis of transcriptomic and omics data. Some key putative candidate genes similar to those reported early for grain development and grain weight formation were further discussed. This finding will provide a better understanding of the genetic determinants of TGW and will be useful for marker-assisted selection of high yield in wheat breeding.

Angular Leaf Spot Resistance Loci Associated With Different Plant Growth Stages in Common Bean

Angular leaf spot (ALS) is a disease that causes major yield losses in the common bean crop. Studies based on different isolates and populations have already been carried out to elucidate the genetic mechanisms of resistance to ALS. However, understanding of the interaction of this resistance with the reproductive stages of common bean is lacking. The aim of the present study was to identify ALS resistance loci at different plant growth stages (PGS) by association and linkage mapping approaches. An BC₂F₃ inter-gene pool cross population (AND 277 × IAC-Milênio - AM population) profiled with 1,091 SNPs from genotyping by sequencing (GBS) was used for linkage mapping, and a carioca diversity panel (CDP) genotyped by 5,398 SNPs from BeadChip assay technology was used for association mapping. Both populations were evaluated for ALS resistance at the V2 and V3 PGSs (controlled conditions) and R8 PGS (field conditions). Different QTL (quantitative trait loci) were detected for the three PGSs and both populations, showing a different quantitative profile of the disease at different plant growth stages. For the three PGS, multiple interval mapping (MIM) identified seven significant QTL, and the Genome-wide association study (GWAS) identified fourteen associate SNPs. Several loci validated regions of previous studies, and Phg-1, Phg-2, Phg-4, and Phg-5, among the 5 loci of greatest effects reported in the literature, were detected in the CDP. The AND 277 cultivar contained both the Phg-1 and the Phg-5 QTL, which is reported for the first time in the descendant cultivar CAL143 as ALS10.1^UC. The novel QTL named ALS11.1^AM was located at the beginning of chromosome Pv11. Gene annotation revealed several putative resistance genes involved in the ALS response at the three PGSs, and with the markers and loci identified, new specific molecular markers can be developed, representing a powerful tool for common bean crop improvement and for gain in ALS resistance.

Genetic mapping of male sterility and pollen fertility QTLs in triticale with sterilizing Triticum timopheevii cytoplasm

Cytoplasmic male sterility (CMS) phenomenon is widely exploited in commercial hybrid seed production in economically important crop species, including rye, wheat, maize, rice, sorghum, cotton, sugar beets, and many vegetables. Although some commercial successes, little is known about QTLs responsible for the trait in case of triticale with sterilizing Triticum timopheevii (Tt) cytoplasm. Recombinant inbred line (RIL) F6 mapping population encompassing 182 individuals derived from the cross of individual plants representing the HT352 line and cv Borwo was employed for genetic map construction using SNP markers and identification of QTLs conferring pollen sterility in triticale with CMS Tt. The phenotypes of the F1 lines resulting from crossing of the HT352 (Tt) with HT352 (maintainer) × Borwo were determined by assessing the number of the F2 seeds per spike. A genetic map with 21 linkage groups encompasses 29,737 markers and spanned over the distance of 2549 cM. Composite (CIM) and multiple (MIM) interval mappings delivered comparable results. Single QTLs mapped to the 1A, 1B, 2A, 2R, 3B, 3R, 4B, and 5B chromosomes, whereas the 5R and 6B chromosomes shared 3 and 2 QTLs, respectively. The QTLs with the highest LOD score mapped to the 5R, 3R, 1B, and 4B chromosomes; however, the QRft-5R.3 has the highest explained variance of the trait.

Genetic Mapping with Background Control for Quantitative Trait Locus (QTL) in 8-Parental Pure-Line Populations

Multiparental advanced generation intercross (MAGIC) populations provide abundant genetic variation for use in plant genetics and breeding. In this study, we developed a method for quantitative trait locus (QTL) detection in pure-line populations derived from 8-way crosses, based on the principles of inclusive composite interval mapping (ICIM). We considered 8 parents carrying different alleles with different effects. To estimate the 8 genotypic effects, 1-locus genetic model was first built. Then, an orthogonal linear model of phenotypes against marker variables was established to explain genetic effects of the locus. The linear model was estimated by stepwise regression and finally used for phenotype adjustment and background genetic variation control in QTL mapping. Simulation studies using 3 genetic models demonstrated that the proposed method had higher detection power, lower false discovery rate (FDR), and unbiased estimation of QTL locations compared with other methods. Marginal bias was observed in the estimation of QTL effects. An 8-parental recombinant inbred line (RIL) population previously reported in cowpea and analyzed by interval mapping (IM) was reanalyzed by ICIM and genome-wide association mapping implemented in software FarmCPU. The results indicated that ICIM identified more QTLs explaining more phenotypic variation than did IM; ICIM provided more information on the detected QTL than did FarmCPU; and most QTLs identified by IM and FarmCPU were also detected by ICIM.

Detecting CSSLs and yield QTLs with additive, epistatic and QTL×environment interaction effects from Oryza sativa × O. nivara IRGC81832 cross

Chromosome segment substitution lines (CSSLs) are useful tools for precise mapping of quantitative trait loci (QTLs) and the evaluation of gene action and interaction in inter-specific crosses. In this study, a set of 90 back cross lines at BC2F8 generation derived from Swarna x Oryza nivara IRGC81832 was evaluated for yield traits under irrigated conditions in wet seasons of 3 consecutive years. We identified a set of 70 chromosome segment substitution lines, using genotyping data from 140 SSR markers covering 94.4% of O. nivara genome. Among these, 23 CSSLs were significantly different for 7 traits. 22 QTLs were detected for 11 traits with 6.51 to 46.77% phenotypic variation in 90 BILs. Three pleiotropic genomic regions associated with yield traits were mapped on chromosomes 1, 8 and 11. The marker interval RM206-RM144 at chromosome 11 was recurrently detected for various yield traits. Ten QTLs were identified consistently in the three consecutive years of testing. Seventeen pairs of significant epistatic QTLs (E-QTLs) were detected for days to flowering, days to maturity and plant height. Chromosome segments from O. nivara contributed trait enhancing alleles. The significantly improved lines and the stable QTLs identified in this study are valuable resource for gene discovery and yield improvement.

Identification of additional /novel QTL associated with resistance to cassava green mite in a biparental mapping population

Cassava green mite [CGM, Mononychellus tanajoa (Bondar)] is the most destructive dry-season pest in most cassava production areas. The pest is responsible for cassava fresh root yield losses of over 80%. Deployment of CGM resistant cultivars is the most cost-effective and sustainable approach of alleviating such production losses. The purposes of this study were to validate the stability of CGM resistance genes found in previously published results, to identify new genes for CGM resistance in bi-parental mapping population and estimate the heritability of the trait. A total of 109 F1 progeny derived from a cross between CGM resistant parent, TMEB778 and a very susceptible parent, TMEB419 were evaluated under CGM hotspot areas in Nigeria for two cropping seasons. A total of 42,204 SNP markers with MAF ≥ 0.05 were used for single-marker analysis. The most significant QTL (S12_7962234) was identified on the left arm on chromosome 12 which explained high phenotypic variance and harboured significant single nucleotide polymorphism (SNP) markers conferring resistance to CGM and leaf pubescence (LP). Colocalization of the most significant SNP associated with resistance to CGM and LP on chromosome 12 is possibly an indication of a beneficial pleiotropic effect or are physically linked. These significant SNPs markers were intersected with the gene annotations and 33 unique genes were identified within SNPs at 4 - 8MB on chromosome 12. Among these genes, nine novel candidate genes namely; Manes.12077600, Manes.12G086200, Manes.12G061200, Manes.12G083100, Manes.12G082000, Manes.12G094100, Manes.12G075600, Manes.12G091400 and Manes.12G069300 highly expressed direct link to cassava green mite resistance. Pyramiding the new QTL/genes identified on chromosome 12 in this study with previously discovered loci, such on chromosome 8, will facilitate breeding varieties that are highly resistant CGM.

Exploring genetic architecture of grain yield and quality traits in a 16-way indica by japonica rice MAGIC global population

Identification of Quantitative Trait Loci (QTL) has been a challenge for complex traits due to the use of populations with narrow genetic base. Most of QTL mapping studies were carried out from crosses made within the subspecies, either indica × indica or japonica × japonica. In this study we report advantages of using Multi-parent Advanced Generation Inter-Crosses global population, derived from a combination of eight indica and eight japonica elite parents, in QTL discovery for yield and grain quality traits. Genome-wide association study and interval mapping identified 38 and 34 QTLs whereas Bayesian networking detected 60 QTLs with 22 marker-marker associations, 32 trait-trait associations and 65 marker-trait associations. Notably, nine known QTLs/genes qPH₁/OsGA20ox2, qDF₃/OsMADS50, PL, QDg1, qGW-5b, grb7-2, qGL₃/GS3, Amy6/Wx gene and OsNAS3 were consistently identified by all approaches for nine traits whereas qDF₃/OsMADS50 was co-located for both yield and days-to-flowering traits on chromosome 3. Moreover, we identified a number of candidate QTLs in either one or two analyses but further validations will be needed. The results indicate that this new population has enabled identifications of significant QTLs and interactions for 16 traits through multiple approaches. Pyramided recombinant inbred lines provide a valuable source for integration into future breeding programs.

RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures

BACKGROUND

In recent years quantitative analysis of root growth has become increasingly important as a way to explore the influence of abiotic stress such as high temperature and drought on a plant's ability to take up water and nutrients. Segmentation and feature extraction of plant roots from images presents a significant computer vision challenge. Root images contain complicated structures, variations in size, background, occlusion, clutter and variation in lighting conditions. We present a new image analysis approach that provides fully automatic extraction of complex root system architectures from a range of plant species in varied imaging set-ups. Driven by modern deep-learning approaches, RootNav 2.0 replaces previously manual and semi-automatic feature extraction with an extremely deep multi-task convolutional neural network architecture. The network also locates seeds, first order and second order root tips to drive a search algorithm seeking optimal paths throughout the image, extracting accurate architectures without user interaction.

RESULTS

We develop and train a novel deep network architecture to explicitly combine local pixel information with global scene information in order to accurately segment small root features across high-resolution images. The proposed method was evaluated on images of wheat (Triticum aestivum L.) from a seedling assay. Compared with semi-automatic analysis via the original RootNav tool, the proposed method demonstrated comparable accuracy, with a 10-fold increase in speed. The network was able to adapt to different plant species via transfer learning, offering similar accuracy when transferred to an Arabidopsis thaliana plate assay. A final instance of transfer learning, to images of Brassica napus from a hydroponic assay, still demonstrated good accuracy despite many fewer training images.

CONCLUSIONS

We present RootNav 2.0, a new approach to root image analysis driven by a deep neural network. The tool can be adapted to new image domains with a reduced number of images, and offers substantial speed improvements over semi-automatic and manual approaches. The tool outputs root architectures in the widely accepted RSML standard, for which numerous analysis packages exist (http://rootsystemml.github.io/), as well as segmentation masks compatible with other automated measurement tools. The tool will provide researchers with the ability to analyse root systems at larget scales than ever before, at a time when large scale genomic studies have made this more important than ever.

Genetic architecture of maize chlorotic mottle virus and maize lethal necrosis through GWAS, linkage analysis and genomic prediction in tropical maize germplasm

KEY MESSAGE

Analysis of the genetic architecture of MCMV and MLN resistance in maize doubled-haploid populations revealed QTLs with major effects on chromosomes 3 and 6 that were consistent across genetic backgrounds and environments. Two major-effect QTLs, qMCMV3-108/qMLN3-108 and qMCMV6-17/qMLN6-17, were identified as conferring resistance to both MCMV and MLN. Maize lethal necrosis (MLN) is a serious threat to the food security of maize-growing smallholders in sub-Saharan Africa. The ability of the maize chlorotic mottle virus (MCMV) to interact with other members of the Potyviridae causes severe yield losses in the form of MLN. The objective of the present study was to gain insights and validate the genetic architecture of resistance to MCMV and MLN in maize. We applied linkage mapping to three doubled-haploid populations and a genome-wide association study (GWAS) on 380 diverse maize lines. For all the populations, phenotypic variation for MCMV and MLN was significant, and heritability was moderate to high. Linkage mapping revealed 13 quantitative trait loci (QTLs) for MCMV resistance and 12 QTLs conferring MLN resistance. One major-effect QTL, qMCMV3-108/qMLN3-108, was consistent across populations for both MCMV and MLN resistance. Joint linkage association mapping (JLAM) revealed 18 and 21 main-effect QTLs for MCMV and MLN resistance, respectively. Another major-effect QTL, qMCMV6-17/qMLN6-17, was detected for both MCMV and MLN resistance. The GWAS revealed a total of 54 SNPs (MCMV-13 and MLN-41) significantly associated (P ≤ 5.60 × 10-05) with MCMV and MLN resistance. Most of the GWAS-identified SNPs were within or adjacent to the QTLs detected through linkage mapping. The prediction accuracy for within populations as well as the combined populations is promising; however, the accuracy was low across populations. Overall, MCMV resistance is controlled by a few major and many minor-effect loci and seems more complex than the genetic architecture for MLN resistance.

A high-density genetic map and QTL mapping of leaf traits and glucosinolates in Barbarea vulgaris

Background

Barbarea vulgaris is a wild cruciferous plant and include two distinct types: the G- and P-types named after their glabrous and pubescent leaves, respectively. The types differ significantly in resistance to a range of insects and diseases as well as glucosinolates and other chemical defenses. A high-density linkage map was needed for further progress to be made in the molecular research of this plant.

Results

We performed restriction site-associated DNA sequencing (RAD-Seq) on an F₂ population generated from G- and P-type B. vulgaris. A total of 1545 SNP markers were mapped and ordered in eight linkage groups, which represents the highest density linkage map to date for the crucifer tribe Cardamineae. A total of 722 previously published genome contigs (50.2 Mb, 30% of the total length) can be anchored to this high density genetic map, an improvement compared to a previously published map (431 anchored contigs, 38.7 Mb, 23% of the assembly genome). Most of these (572 contigs, 31.2 Mb) were newly anchored to the map, representing a significant improvement. On the basis of the present high-density genetic map, 37 QTL were detected for eleven traits, each QTL explaining 2.9–71.3% of the phenotype variation. QTL of glucosinolates, leaf size and color traits were in most cases overlapping, possibly implying a functional connection.

Conclusions

This high-density linkage map and the QTL obtained in this study will be useful for further understanding of the genetic of the B. vulgaris and molecular basis of these traits, many of which are shared in the related crop watercress.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5769-z) contains supplementary material, which is available to authorized users.

Effect of drought stress on the genetic architecture of photosynthate allocation and remobilization in pods of common bean (Phaseolus vulgaris L.), a key species for food security

BACKGROUND

Common bean is the most important staple grain legume for direct human consumption and nutrition. It complements major sources of carbohydrates, including cereals, root crop, or plantain, as a source of dietary proteins. It is also a significant source of vitamins and minerals like iron and zinc. To fully play its nutritional role, however, its robustness against stresses needs to be strengthened. Foremost among these is drought, which commonly affects its productivity and seed quality. Previous studies have shown that photosynthate remobilization and partitioning is one of the main mechanisms of drought tolerance and overall productivity in common bean.

RESULTS

In this study, we sought to determine the inheritance of pod harvest index (PHI), a measure of the partitioning of pod biomass to seed biomass, relative to that of grain yield. We evaluated a recombinant inbred population of the cross of ICA Bunsi and SXB405, both from the Mesoamerican gene pool, to determine the effects of intermittent and terminal drought stresses on the genetic architecture of photosynthate allocation and remobilization in pods of common bean. The population was grown for two seasons, under well-watered conditions and terminal and intermittent drought stress in one year, and well-watered conditions and terminal drought stress in the second year. There was a significant effect of the water regime and year on all the traits, at both the phenotypic and QTL levels. We found nine QTLs for pod harvest index, including a major (17% of variation explained), stable QTL on linkage group Pv07. We also found eight QTLs for yield, three of which clustered with PHI QTLs, underscoring the importance of photosynthate remobilization in productivity. We also found evidence for substantial epistasis, explaining a considerable part of the variation for yield and PHI.

CONCLUSION

Our results highlight the genetic relationship between PHI and yield and confirm the role of PHI in selection of both additive and epistatic effects controlling drought tolerance. These results are a key component to strengthen the robustness of common bean against drought stresses.

Unravelling the genetic basis of Fusarium seedling rot resistance in the MAGIC maize population: novel targets for breeding

Fungal infection by Fusarium verticillioides is cause of prevalent maize disease leading to substantial reductions in yield and grain quality worldwide. Maize resistance to the fungus may occur at different developmental stages, from seedling to maturity. The breeding of resistant maize genotypes may take advantage of the identification of quantitative trait loci (QTL) responsible for disease resistance already commenced at seedling level. The Multi-parent Advance Generation Intercross (MAGIC) population was used to conduct high-definition QTL mapping for Fusarium seedling rot (FSR) resistance using rolled towel assay. Infection severity level, seedling weight and length were measured on 401 MAGIC maize recombinant inbred lines (RILs). QTL mapping was performed on reconstructed RIL haplotypes. One-fifth of the MAGIC RILs were resistant to FSR and 10 QTL were identified. For FSR, two QTL were detected at 2.8 Mb and 241.8 Mb on chromosome 4, and one QTL at 169.6 Mb on chromosome 5. Transcriptomic and sequencing information generated on the MAGIC founder lines was used to guide the identification of eight candidate genes within the identified FSR QTL. We conclude that the rolled towel assay applied to the MAGIC maize population provides a fast and cost-effective method to identify QTL and candidate genes for early resistance to F. verticillioides in maize.

Construction of a genetic linkage map in Pyropia yezoensis (Bangiales, Rhodophyta) and QTL analysis of several economic traits of blades

Pyropia yezoensis is an economically important seaweed but its molecular genetics is poorly understood. In the present study, we used a doubled haploid (DH) population that was established in our previous work to construct a genetic linkage map of P. yezoensis and analyze the quantitative trait loci (QTLs) of blades. The DH population was genotyped with fluorescent sequence-related amplified polymorphism (SRAP) markers. A chi-square test identified 301 loci with normal segregation (P ≥ 0.01) and 96 loci (24.18%) with low-level skewed segregation (0.001 ≤ P < 0.01). The genetic map was constructed after a total of 92 loci were assembled into three linkage groups (LGs). The map spanned 557.36 cM covering 93.71% of the estimated genome, with a mean interlocus space of 6.23 cM. Kolmogorov-Smirnov test (α = 5%) showed a uniform distribution of the markers along each LG. On the genetic map, 10 QTLs associated with five economic traits of blades were detected. One QTL was for length, one for width, two for fresh weight, two for specific growth rate of length and four for specific growth rate of fresh weight. These QTLs could explain 2.29–7.87% of the trait variations, indicating that their effects were all minor. The results may serve as a framework for future marker-assisted breeding in P. yezoensis.

High-density SNP linkage map construction and QTL mapping for flavonoid-related traits in a tea plant (Camellia sinensis) using 2b-RAD sequencing

BACKGROUND

Flavonoids are important components that confer upon tea plants a unique flavour and health functions. However, the traditional breeding method for selecting a cultivar with a high or unique flavonoid content is time consuming and labour intensive. High-density genetic map construction associated with quantitative trait locus (QTL) mapping provides an effective way to facilitate trait improvement in plant breeding. In this study, an F1 population (LJ43×BHZ) was genotyped using 2b-restriction site-associated DNA (2b-RAD) sequencing to obtain massive single nucleotide polymorphism (SNP) markers to construct a high-density genetic map for a tea plant. Furthermore, QTLs related to flavonoids were identified using our new genetic map.

RESULTS

A total of 13,446 polymorphic SNP markers were developed using 2b-RAD sequencing, and 4,463 of these markers were available for constructing the genetic linkage map. A 1,678.52-cM high-density map at an average interval of 0.40 cM with 4,217 markers, including 427 frameset simple sequence repeats (SSRs) and 3,800 novel SNPs, mapped into 15 linkage groups was successfully constructed. After QTL analysis, a total of 27 QTLs related to flavonoids or caffeine content (CAF) were mapped to 8 different linkage groups, LG01, LG03, LG06, LG08, LG10, LG11, LG12, and LG13, with an LOD from 3.14 to 39.54, constituting 7.5% to 42.8% of the phenotypic variation.

CONCLUSIONS

To our knowledge, the highest density genetic map ever reported was constructed since the largest mapping population of tea plants was adopted in present study. Moreover, novel QTLs related to flavonoids and CAF were identified based on the new high-density genetic map. In addition, two markers were located in candidate genes that may be involved in flavonoid metabolism. The present study provides valuable information for gene discovery, marker-assisted selection breeding and map-based cloning for functional genes that are related to flavonoid content in tea plants.

Efficient QTL detection of flowering date in a soybean RIL population using the novel restricted two-stage multi-locus GWAS procedure

KEY MESSAGE

Eighty-six R1 QTLs accounting for 89.92% phenotypic variance in a soybean RIL population were identified using RTM-GWAS with SNPLDB marker which performed superior over CIM and MLM-GWAS with BIN/SNPLDB marker. A population (NJRIKY) composed of 427 recombinant inbred lines (RILs) derived from Kefeng-1 × NN1138-2 (MGII × MGV, MG maturity group) was applied for detecting flowering date (R1) quantitative trait locus (QTL) system in soybean. From a low-depth re-sequencing (~ 0.75 ×), 576,874 SNPs were detected and organized into 4737 BINs (recombination breakpoint determinations) and 3683 SNP linkage disequilibrium blocks (SNPLDBs), respectively. Using the association mapping procedures "Restricted Two-stage Multi-locus Genome-wide Association Study" (RTM-GWAS), "Mixed Linear Model Genome-wide Association Study" (MLM-GWAS) and the linkage mapping procedure "Composite Interval Mapping" (CIM), 67, 36 and 10 BIN-QTLs and 86, 14 and 23 SNPLDB-QTLs were detected with their phenotypic variance explained (PVE) 88.70-89.92% (within heritability 98.2%), 146.41-353.62% (overflowing) and 88.29-172.34% (overflowing), respectively. The RTM-GWAS with SNPLDBs which showed to be more efficient and reasonable than the others was used to identify the R1 QTL system in NJRIKY. The detected 86 SNPLDB-QTLs with their PVE from 0.02 to 30.66% in a total of 89.92% covered 51 out of 104 R1 QTLs in 18 crosses in SoyBase and 26 out of 139 QTLs in a nested association mapping population, while the rest 29 QTLs were novel ones. From the QTL system, 52 candidate genes were annotated, including the verified gene E1, E2, E9 and J, and grouped into 3 categories of biological processes, among which 24 genes were enriched into three protein-protein interaction networks, suggesting gene networks working together. Since NJRIKY involves only MGII and MGV, the QTL/gene system among MG000-MGX should be explored further.

Triticale Improvement for Forage and Cover Crop Uses in the Southern Great Plains of the United States

Triticale (×Triticosecale Wittmack) is a man-made species developed by crossing wheat (Triticum spp.) and rye (Secale cereale L.). It incorporates favorable alleles from both progenitor species (wheat and rye), enabling adaptation to environments that are less favorable for wheat yet providing better biomass yield and forage quality. Triticale has huge potential for both grain and forage production, though research to improve the crop for better adaptation and grain quality is lagging behind that of other small grains. It is also gaining popularity as a cover crop to improve soil health and reduce nutrient leaching. Because of its genetic and flower structure, triticale is suitable for both line and hybrid breeding methods. Advances in the areas of molecular biology and the wealth of genomic resources from both wheat and rye can be exploited for triticale improvement. Gene mapping and genomic selection will facilitate triticale breeding by increasing selection precision and reducing time and cost. The objectives of this review are to summarize current triticale production status, breeding, and genetics research achievements and to highlight gaps for future research.

Detecting the QTL-allele system conferring flowering date in a nested association mapping population of soybean using a novel procedure

KEY MESSAGE

The RTM-GWAS was chosen among five procedures to identify DTF QTL-allele constitution in a soybean NAM population; 139 QTLs with 496 alleles accounting for 81.7% of phenotypic variance were detected. Flowering date (days to flowering, DTF) is an ecological trait in soybean, closely related to its ability to adapt to areas. A nested association mapping (NAM) population consisting of four RIL populations (LM, ZM, MT and MW with M8206 as their common parent) was established and tested for their DTF under five environments. Using restriction-site-associated DNA sequencing the population was genotyped with SNP markers. The restricted two-stage multi-locus (RTM) genome-wide association study (GWAS) (RTM-GWAS) with SNP linkage disequilibrium block (SNPLDB) as multi-allele genomic markers performed the best among the five mapping procedures with software publicly available. It identified the greatest number of quantitative trait loci (QTLs) (139) and alleles (496) on 20 chromosomes covering almost all of the QTLs detected by four other mapping procedures. The RTM-GWAS provided the detected QTLs with highest genetic contribution but without overflowing and missing heritability problems (81.7% genetic contribution vs. heritability of 97.6%), while SNPLDB markers matched the NAM population property of multiple alleles per locus. The 139 QTLs with 496 alleles were organized into a QTL-allele matrix, showing the corresponding DTF genetic architecture of the five parents and the NAM population. All lines and parents comprised both positive and negative alleles, implying a great potential of recombination for early and late DTF improvement. From the detected QTL-allele system, 126 candidate genes were annotated and χ 2 tested as a DTF candidate gene system involving nine biological processes, indicating the trait a complex, involving several biological processes rather than only a handful of major genes.

Background controlled QTL mapping in pure-line genetic populations derived from four-way crosses

Pure lines derived from multiple parents are becoming more important because of the increased genetic diversity, the possibility to conduct replicated phenotyping trials in multiple environments and potentially high mapping resolution of quantitative trait loci (QTL). In this study, we proposed a new mapping method for QTL detection in pure-line populations derived from four-way crosses, which is able to control the background genetic variation through a two-stage mapping strategy. First, orthogonal variables were created for each marker and used in an inclusive linear model, so as to completely absorb the genetic variation in the mapping population. Second, inclusive composite interval mapping approach was implemented for one-dimensional scanning, during which the inclusive linear model was employed to control the background variation. Simulation studies using different genetic models demonstrated that the new method is efficient when considering high detection power, low false discovery rate and high accuracy in estimating quantitative trait loci locations and effects. For illustration, the proposed method was applied in a reported wheat four-way recombinant inbred line population.

Genome-Wide Analysis of Tar Spot Complex Resistance in Maize Using Genotyping-by-Sequencing SNPs and Whole-Genome Prediction

Tar spot complex (TSC) is one of the most destructive foliar diseases of maize ( L.) in tropical and subtropical areas of Central and South America, causing significant grain yield losses when weather conditions are conducive. To dissect the genetic architecture of TSC resistance in maize, association mapping, in conjunction with linkage mapping, was conducted on an association-mapping panel and three biparental doubled-haploid (DH) populations using genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs). Association mapping revealed four quantitative trait loci (QTL) on chromosome 2, 3, 7, and 8. All the QTL, except for the one on chromosome 3, were further validated by linkage mapping in different genetic backgrounds. Additional QTL were identified by linkage mapping alone. A major QTL located on bin 8.03 was consistently detected with the largest phenotypic explained variation: 13% in association-mapping analysis and 13.18 to 43.31% in linkage-mapping analysis. These results indicated that TSC resistance in maize was controlled by a major QTL located on bin 8.03 and several minor QTL with smaller effects on other chromosomes. Genomic prediction results showed moderate-to-high prediction accuracies in different populations using various training population sizes and marker densities. Prediction accuracy of TSC resistance was >0.50 when half of the population was included into the training set and 500 to 1,000 SNPs were used for prediction. Information obtained from this study can be used for developing functional molecular markers for marker-assisted selection (MAS) and for implementing genomic selection (GS) to improve TSC resistance in tropical maize.

High-resolution mapping of QTL for fatty acid composition in soybean using specific-locus amplified fragment sequencing

KEY MESSAGE

We constructed a high-density linkage map comprising 3541 markers developed by specific-locus amplified fragment sequencing, and identified 26 stable QTL including nine novel loci, for fatty acid composition in soybean. Soybean oil quality and stability are mainly determined by the fatty acid composition of the seed. In the present study, we constructed a high-density genetic linkage map using 200 recombinant inbred lines derived from a cross between cultivated soybean varieties Luheidou2 and Nanhuizao, and SNP markers developed by specific-locus amplified fragment sequencing (SLAF-seq). This map comprises 3541 markers on 20 linkage groups and spans a genetic distance of 2534.42 cM, with an average distance of 0.72 cM between adjacent markers. Inclusive composite interval mapping revealed 26 stable QTL for five fatty acids, explaining 0.4-37.0% of the phenotypic variance for individual fatty acids across environments. Of these QTL, nine are novel loci (qLA1, qLNA2_1, qPA4_1, qLA4_1, qPA6_1, qSA12_1, qPA16_1, qOA18_1, and qFA19_1). These stable QTL harbor three fatty acid biosynthesis genes (GmFabG, GmACP, and GmFAD8), and 66 genes encoding lipid-related transcription factors. These stable QTL and tightly linked SNP markers can be used for marker-assisted selection in soybean breeding programs.

Genome-Wide Single Nucleotide Polymorphism Discovery and the Construction of a High-Density Genetic Map for Melon (Cucumis melo L.) Using Genotyping-by-Sequencing

Although genotyping-by-sequencing (GBS) enables the efficient and low-cost generation of large numbers of markers, the utility of resultant genotypes are limited, because they are enormously error-prone and contain high proportions of missing data. In this study, we generated single nucleotide polymorphism (SNP) markers for 109 recombinant inbred lines of melon (Cucumis melo L.) using the GBS approach and ordered them according to their physical position on the draft double haploid line DHL92 genome. Next, by investigating associations between these SNPs, we discovered that some segments on the physical map conflict with linkage relationships. Therefore, to filter out error-prone loci, 4,110 SNPs in which we have a high degree of confidence were selected as anchors to test independence with respect to unselected markers, and the resultant dataset was then analyzed using the Full-Sib Family Haplotype (FSFHap) algorithm in the software TASSEL 5.2. On the basis of this analysis, 22,933 loci that have an average rate of missing data of 0.281% were used to construct a genetic map, which spans 1,088.3 cM across 12 chromosomes and has a maximum spacing of 6.0 cM. Use of this high-quality linkage map enabled the identification of several quantitative trait loci (QTL) known to control traits in fruit and validated our approach. This study highlights the utility of GBS markers for the identification of trait-associated QTLs in melon and facilitates further investigation of genome structure.

QTLs for heading date and plant height under multiple environments in rice

Both heading date and plant height are important traits related to grain yield in rice. In this study, a recombinant inbred lines (RILs) population was used to map quantitative trait loci (QTLs) for both traits under 3 long-day (LD) environments and 1 short-day (SD) environment. A total of eight QTLs for heading date and three QTLs for plant height were detected by composite interval mapping under LD conditions. Additional one QTL for heading date and three QTLs for plant height were identified by Two-QTL model under LD conditions. Among them, major QTLs qHd7.1, qHd7.2 and qHd8 for heading date, and qPh1 and qPh7.1 for plant height were commonly detected. qHd7.1 and qHd7.2 were mapped to small regions of less than 1 cM. Genome position comparison of previously cloned genes with QTLs detected in this study revealed that qHd5 and qPh3.1 were two novel QTLs. The alleles of these QTLs increasing trait values were dispersed in both parents, which well explained the transgressive segregation observed in this population. In addition, the interaction between qHd7.1 and qHd8 was detected under all LD conditions. Multiple-QTL model analysis revealed that all QTLs and their interactions explained over 80% of heading date variation and 50% of plant height variation. Two heading date QTLs were detected under SD condition. Of them, qHd10 were commonly identified under LD condition. The difference in QTL detection between LD and SD conditions indicated most heading date QTLs are sensitive to photoperiod. These findings will benefit breeding design for heading date and plant height in rice.

QTL Mapping for Yield and Resistance against Mediterranean Corn Borer in Maize

Introduction: The Mediterranean corn borer (MCB), Sesamia nonagrioides, is a major pest of maize, Zea mays, in Mediterranean countries, inflicting significant kernel yield losses. For that reason, it necessary to know the genetic mechanisms that regulate the agronomic and resistance traits. A quantitative trait loci (QTL) mapping study for yield, resistance against MCB attack, and other relevant agronomic traits was performed using a recombinant inbred line (RIL) population derived from the cross A637 × A509 that is expected to segregate for yield, and ear, and stalk resistance to MCB. 171 RILs were evaluated in 2014 and 2015 at Pontevedra, Spain, along with the two parental inbreds A637 and A509 using a 13 × 14 single lattice design with two replications. A genetic map with 285 SNP markers was used for QTL analysis. Our objectives were to detect QTL for resistance to MCB and tolerance-related agronomic traits, to gain insights on the genetic relationship between resistance to MCB attack and yield, and to establish the best way for simultaneously improving yield and resistance to MCB. Results: Twelve significant QTL were detected for agronomic and resistance traits. QTL at bins 1.10 and 5.04 were especially interesting because the same allelic variant at these QTL simultaneously improved yield and insect resistance. In contrast, in the region 8.04-8.05, QTL showed opposite effects for yield and resistance. Several QTL for indexes which combine yield and resistance traits were found especially in the region 10.02-10.03. Conclusions: Selecting genotypes with the favorable allele of QTL on chromosome 5 (bin 5.01) will decrease tunnel length without affect yield, silking and plant height and QTL on the region 5.04 could be used to improve stalk resistance and yield simultaneously. An allele of QTL on bin 9.07 will increase ear resistance to MCB attack but it could produce later varieties while favorable allele in region 1.10 could improve ear and stalk resistance and yield without secondary negative effects. The region 8.03-8.05 mainly but also the region 10.02-10.03 and 5.04 may play an important role to elucidate the association between yield, other agronomic traits and MCB resistance.

Eggplant Resistance to the Ralstonia solanacearum Species Complex Involves Both Broad-Spectrum and Strain-Specific Quantitative Trait Loci

Bacterial wilt (BW) is a major disease of solanaceous crops caused by the Ralstonia solanacearum species complex (RSSC). Strains are grouped into five phylotypes (I, IIA, IIB, III, and IV). Varietal resistance is the most sustainable strategy for managing BW. Nevertheless, breeding to improve cultivar resistance has been limited by the pathogen's extensive genetic diversity. Identifying the genetic bases of specific and non-specific resistance is a prerequisite to breed improvement. A major gene (ERs1) was previously mapped in eggplant (Solanum melongena L.) using an intraspecific population of recombinant inbred lines derived from the cross of susceptible MM738 (S) × resistant AG91-25 (R). ERs1 was originally found to control three strains from phylotype I, while being totally ineffective against a virulent strain from the same phylotype. We tested this population against four additional RSSC strains, representing phylotypes I, IIA, IIB, and III in order to clarify the action spectrum of ERs1. We recorded wilting symptoms and bacterial stem colonization under controlled artificial inoculation. We constructed a high-density genetic map of the population using single nucleotide polymorphisms (SNPs) developed from genotyping-by-sequencing and added 168 molecular markers [amplified fragment length polymorphisms (AFLPs), simple sequence repeats (SSRs), and sequence-related amplified polymorphisms (SRAPs)] developed previously. The new linkage map based on a total of 1,035 markers was anchored on eggplant, tomato, and potato genomes. Quantitative trait locus (QTL) mapping for resistance against a total of eight RSSC strains resulted in the detection of one major phylotype-specific QTL and two broad-spectrum QTLs. The major QTL, which specifically controls three phylotype I strains, was located at the bottom of chromosome 9 and corresponded to the previously identified major gene ERs1. Five candidate R-genes were underlying this QTL, with different alleles between the parents. The two other QTLs detected on chromosomes 2 and 5 were found to be associated with partial resistance to strains of phylotypes I, IIA, III and strains of phylotypes IIA and III, respectively. Markers closely linked to these three QTLs will be crucial for breeding eggplant with broad-spectrum resistance to BW. Furthermore, our study provides an important contribution to the molecular characterization of ERs1, which was initially considered to be a major resistance gene.

Identification of a stable major-effect QTL (Parth 2.1) controlling parthenocarpy in cucumber and associated candidate gene analysis via whole genome re-sequencing

BACKGROUND

Parthenocarpy is an important trait for yield and quality in many plants. But due to its complex interactions with genetic and physiological factors, it has not been adequately understood and applied to breeding and production. Finding novel and effective quantitative trait loci (QTLs) is a critical step towards understanding its genetic mechanism. Cucumber (Cucumis sativus L.) is a typical parthenocarpic plant but the QTLs controlling parthenocarpy in cucumber were not mapped on chromosomes, and the linked markers were neither user-friendly nor confirmed by previous studies. Hence, we conducted a two-season QTL study of parthenocarpy based on the cucumber genome with 145 F2:3 families derived from a cross between EC1 (a parthenocarpic inbred line) and 8419 s-1 (a non-parthenocarpic inbred line) in order to map novel QTLs. Whole genome re-sequencing was also performed both to develop effective linked markers and to predict candidate genes.

RESULTS

A genetic linkage map, employing 133 Simple Sequence Repeats (SSR) markers and nine Insertion/Deletion (InDel) markers spanning 808.1 cM on seven chromosomes, was constructed from an F2 population. Seven novel QTLs were identified on chromosomes 1, 2, 3, 5 and 7. Parthenocarpy 2.1 (Parth2.1), a QTL on chromosome 2, was a major-effect QTL with a logarithm of odds (LOD) score of 9.0 and phenotypic variance explained (PVE) of 17.0 % in the spring season and with a LOD score of 6.2 and PVE of 10.2 % in the fall season. We confirmed this QTL using a residual heterozygous line97-5 (RHL97-5). Effectiveness of linked markers of the Parth2.1 was validated in F3:4 population and in 21 inbred lines. Within this region, there were 57 genes with nonsynonymous SNPs/InDels in the coding sequence. Based on further combined analysis with transcriptome data between two parents, CsARF19, CsWD40, CsEIN1, CsPPR, CsHEXO3, CsMDL, CsDJC77 and CsSMAX1 were predicted as potential candidate genes controlling parthenocarpy.

CONCLUSIONS

A major-effect QTL Parth2.1 and six minor-effect QTLs mainly contribute to the genetic architecture of parthenocarpy in cucumber. SSR16226 and Indel-T-39 can be used in marker-assisted selection (MAS) of cucumber breeding. Whole genome re-sequencing enhances the efficiency of polymorphic marker development and prediction of candidate genes.

Genetic dissection of maize plant architecture with an ultra-high density bin map based on recombinant inbred lines

Background

Plant architecture attributes, such as plant height, ear height, and internode number, have played an important role in the historical increases in grain yield, lodging resistance, and biomass in maize (Zea mays L.). Analyzing the genetic basis of variation in plant architecture using high density QTL mapping will be of benefit for the breeding of maize for many traits. However, the low density of molecular markers in existing genetic maps has limited the efficiency and accuracy of QTL mapping. Genotyping by sequencing (GBS) is an improved strategy for addressing a complex genome via next-generation sequencing technology. GBS has been a powerful tool for SNP discovery and high-density genetic map construction. The creation of ultra-high density genetic maps using large populations of advanced recombinant inbred lines (RILs) is an efficient way to identify QTL for complex agronomic traits.

Results

A set of 314 RILs derived from inbreds Ye478 and Qi319 were generated and subjected to GBS. A total of 137,699,000 reads with an average of 357,376 reads per individual RIL were generated, which is equivalent to approximately 0.07-fold coverage of the maize B73 RefGen_V3 genome for each individual RIL. A high-density genetic map was constructed using 4183 bin markers (100-Kb intervals with no recombination events). The total genetic distance covered by the linkage map was 1545.65 cM and the average distance between adjacent markers was 0.37 cM with a physical distance of about 0.51 Mb. Our results demonstrated a relatively high degree of collinearity between the genetic map and the B73 reference genome. The quality and accuracy of the bin map for QTL detection was verified by the mapping of a known gene, pericarp color 1 (P1), which controls the color of the cob, with a high LOD value of 80.78 on chromosome 1. Using this high-density bin map, 35 QTL affecting plant architecture, including 14 for plant height, 14 for ear height, and seven for internode number were detected across three environments. Interestingly, pQTL10, which influences all three of these traits, was stably detected in three environments on chromosome 10 within an interval of 14.6 Mb. Two MYB transcription factor genes, GRMZM2G325907 and GRMZM2G108892, which might regulate plant cell wall metabolism are the candidate genes for qPH10.

Conclusions

Here, an ultra-high density accurate linkage map for a set of maize RILs was constructed using a GBS strategy. This map will facilitate identification of genes and exploration of QTL for plant architecture in maize. It will also be helpful for further research into the mechanisms that control plant architecture while also providing a basis for marker-assisted selection.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2555-z) contains supplementary material, which is available to authorized users.

Quantitative trait locus mapping and functional genomics of an organophosphate resistance trait in the western corn rootworm, Diabrotica virgifera virgifera

The western corn rootworm, Diabrotica virgifera virgifera, is an insect pest of corn and population suppression with chemical insecticides is an important management tool. Traits conferring organophosphate insecticide resistance have increased in frequency amongst D. v. virgifera populations, resulting in the reduced efficacy in many corn-growing regions of the USA. We used comparative functional genomic and quantitative trait locus (QTL) mapping approaches to investigate the genetic basis of D. v. virgifera resistance to the organophosphate methyl-parathion. RNA from adult methyl-parathion resistant and susceptible adults was hybridized to 8331 microarray probes. The results predicted that 11 transcripts were significantly up-regulated in resistant phenotypes, with the most significant (fold increases ≥ 2.43) being an α-esterase-like transcript. Differential expression was validated only for the α-esterase (ST020027A20C03), with 11- to 13-fold greater expression in methyl-parathion resistant adults (P < 0.05). Progeny with a segregating methyl-parathion resistance trait were obtained from a reciprocal backcross design. QTL analyses of high-throughput single nucleotide polymorphism genotype data predicted involvement of a single genome interval. These data suggest that a specific carboyxesterase may function in field-evolved corn rootworm resistance to organophosphates, even though direct linkage between the QTL and this locus could not be established.

Quantitative trait loci mapping for Gibberella ear rot resistance and associated agronomic traits using genotyping-by-sequencing in maize

Unique and co-localized chromosomal regions affecting Gibberella ear rot disease resistance and correlated agronomic traits were identified in maize. Dissecting the mechanisms underlying resistance to Gibberella ear rot (GER) disease in maize provides insight towards more informed breeding. To this goal, we evaluated 410 recombinant inbred lines (RIL) for GER resistance over three testing years using silk channel and kernel inoculation techniques. RILs were also evaluated for agronomic traits like days to silking, husk cover, and kernel drydown rate. The RILs showed significant genotypic differences for all traits with above average to high heritability estimates. Significant (P < 0.01) but weak genotypic correlations were observed between disease severity and agronomic traits, indicating the involvement of agronomic traits in disease resistance. Common QTLs were detected for GER resistance and kernel drydown rate, suggesting the existence of pleiotropic genes that could be exploited to improve both traits at the same time. The QTLs identified for silk and kernel resistance shared some common regions on chromosomes 1, 2, and 8 and also had some regions specific to each tissue on chromosomes 9 and 10. Thus, effective GER resistance breeding could be achieved by considering screening methods that allow exploitation of tissue-specific disease resistance mechanisms and include kernel drydown rate either in an index or as indirect selection criterion.

Whole-Genome Mapping Reveals Novel QTL Clusters Associated with Main Agronomic Traits of Cabbage (Brassica oleracea var. capitata L.)

We describe a comprehensive quantitative trait locus (QTL) analysis for 24 main agronomic traits of cabbage. Field experiments were performed using a 196-line double haploid population in three seasons in 2011 and 2012 to evaluate important agronomic traits related to plant type, leaf, and head traits. In total, 144 QTLs with LOD threshold >3.0 were detected for the 24 agronomic traits: 25 for four plant-type-related traits, 64 for 10 leaf-related traits, and 55 for 10 head-related traits; each QTL explained 6.0-55.7% of phenotype variation. Of the QTLs, 95 had contribution rates higher than 10%, and 51 could be detected in more than one season. Major QTLs included Ph 3.1 (max R (2) = 55.7, max LOD = 28.2) for plant height, Ll 3.2 (max R (2) = 31.7, max LOD = 13.95) for leaf length, and Htd 3.2 (max R (2) = 28.5, max LOD = 9.49) for head transverse diameter; these could all be detected in more than one season. Twelve QTL clusters were detected on eight chromosomes, and the most significant four included Indel481-scaffold18376 (3.20 Mb), with five QTLs for five traits; Indel64-scaffold35418 (2.22 Mb), six QTLs for six traits; scaffold39782-Indel84 (1.78 Mb), 11 QTLs for 11 traits; and Indel353-Indel245 (9.89 Mb), seven QTLs for six traits. Besides, most traits clustered within the same region were significantly correlated with each other. The candidate genes at these regions were also discussed. Robust QTLs and their clusters obtained in this study should prove useful for marker-assisted selection (MAS) in cabbage breeding and in furthering our understanding of the genetic control of these traits.

Quantitative trait locus mapping with background control in genetic populations of clonal F1 and double cross

In this study, we considered five categories of molecular markers in clonal F1 and double cross populations, based on the number of distinguishable alleles and the number of distinguishable genotypes at the marker locus. Using the completed linkage maps, incomplete and missing markers were imputed as fully informative markers in order to simplify the linkage mapping approaches of quantitative trait genes. Under the condition of fully informative markers, we demonstrated that dominance effect between the female and male parents in clonal F1 and double cross populations can cause the interactions between markers. We then developed an inclusive linear model that includes marker variables and marker interactions so as to completely control additive effects of the female and male parents, as well as the dominance effect between the female and male parents. The linear model was finally used for background control in inclusive composite interval mapping (ICIM) of quantitative trait locus (QTL). The efficiency of ICIM was demonstrated by extensive simulations and by comparisons with simple interval mapping, multiple-QTL models and composite interval mapping. Finally, ICIM was applied in one actual double cross population to identify QTL on days to silking in maize.

Identification of QTL for resistance to Mediterranean corn borer in a maize tropical line to improve temperate germplasm

BACKGROUND

A QTL mapping study for maize resistance to the Mediterranean corn borer (MCB) was performed with a RIL population derived from the cross B73 × CML103. To develop commercial inbreds of maize resistant to the MCB for use in Europe, it would be useful to transfer resistance from tropical germplasm like the subtropical inbred CML103 to temperate lines. The inbred B73 was chosen as representative of the Stiff Stock heterotic group, a major heterotic group used in hybrid grown in both North American and Europe. The objectives were to study the architecture of genetic factors for resistance to MCB and to check the feasibility of using marker-assisted selection (MAS) for transferring those genetic factors.

RESULTS

Eight quantitative trait loci (QTL) were declared significant for resistance traits and eight QTL were located for agronomic traits. Alleles from CML103 at QTL significant for tunnel length could reduce tunnel length made for MCB in inbred B73 in more than 8 cm; favorable alleles for yield were also found in CML103 and no genetic correlation coefficient between tunnel length and yield was detected.

CONCLUSIONS

MAS for transferring resistance genes to corn borer attack from CML103 to B73 could be successful based on cross validation results and a negative effect on yield would not be expected.

Genetic dissection on rice grain shape by the two-dimensional image analysis in one japonica × indica population consisting of recombinant inbred lines

KEY MESSAGE

This article used seven characters from the 2D image analysis to dissect the genetic architecture underlying rice grain shape in one japonica × indica population consisting of 215 recombinant inbred lines. Two-dimensional (2D) digital image analysis is efficient for investigating the rice grain shape characters in large genetic and breeding populations. In this study, we used 2D image analysis to investigate seven characters, i.e., grain length (GL), grain width (GW), length-to-width ratio (LW), grain area (GA), grain circumference (GC), grain diameter (GD), and grain roundness (GR), in one japonica × indica genetic population consisting of 215 recombinant inbred lines. GL and GW can be recorded manually as well, and have been extensively used together with LW (i.e., GL/GW) in genetic studies on grain shape. GC and GA can be hardly measured manually, and have not been used together with GD and GR. Results indicated that the seven characters could be precisely measured by 2D image analysis, genotype by environment interaction was low, and heritability was high. Each character was controlled by a few major stable genes and multiple minor additive genes. A total of 51 QTL were detected for the seven characters across four diverse environments, 22 from GL, GW, and LW, the three traditional characters, and 29 from the other four characters. The 51 QTL were clustered in eighteen marker intervals. Comparing with previous studies and analyzing the stability of identified QTL, we found six non-reported marker intervals, one each on chromosomes 2 and 3, and two each on chromosomes 6 and 8. The newly identified loci and the large-scale phenotyping system would greatly improve our knowledge about the genetic architecture and the future rice breeding on grain shape.

Construction of a high-density genetic map using specific length amplified fragment markers and identification of a quantitative trait locus for anthracnose resistance in walnut (Juglans regia L.)

BACKGROUND

Walnut (Juglans regia, 2n = 32, approximately 606 Mb per 1C genome) is an economically important tree crop. Resistance to anthracnose, caused by Colletotrichum gloeosporioides, is a major objective of walnut genetic improvement in China. The recently developed specific length amplified fragment sequencing (SLAF-seq) is an efficient strategy that can obtain large numbers of markers with sufficient sequence information to construct high-density genetic maps and permits detection of quantitative trait loci (QTLs) for molecular breeding.

RESULTS

SLAF-seq generated 161.64 M paired-end reads. 153,820 SLAF markers were obtained, of which 49,174 were polymorphic. 13,635 polymorphic markers were sorted into five segregation types and 2,577 markers of them were used to construct genetic linkage maps: 2,395 of these fell into 16 linkage groups (LGs) for the female map, 448 markers for the male map, and 2,577 markers for the integrated map. Taking into account the size of all LGs, the marker coverage was 2,664.36 cM for the female map, 1,305.58 cM for the male map, and 2,457.82 cM for the integrated map. The average intervals between two adjacent mapped markers were 1.11 cM, 2.91 cM and 0.95 cM for three maps, respectively. 'SNP_only' markers accounted for 89.25% of the markers on the integrated map. Mapping markers contained 5,043 single nucleotide polymorphisms (SNPs) loci, which corresponded to two SNP loci per SLAF marker. According to the integrated map, we used interval mapping (Logarithm of odds, LOD > 3.0) to detect our quantitative trait. One QTL was detected for anthracnose resistance. The interval of this QTL ranged from 165.51 cM to 176.33 cM on LG14, and ten markers in this interval that were above the threshold value were considered to be linked markers to the anthracnose resistance trait. The phenotypic variance explained by each marker ranged from 16.2 to 19.9%, and their LOD scores varied from 3.22 to 4.04.

CONCLUSIONS

High-density genetic maps for walnut containing 16 LGs were constructed using the SLAF-seq method with an F1 population. One QTL for walnut anthracnose resistance was identified based on the map. The results will aid molecular marker-assisted breeding and walnut resistance genes identification.

A new allele of acid soil tolerance gene from a malting barley variety

Background

Acid soil is a serious limitation to crop production all over the world. Toxic aluminium (Al) cations in acid soil inhibit root growth and reduce yield. Although a gene tolerant to acid soil has been identified, it has not been used in malting barley breeding, which is partly due to the acid soil tolerance gene being linked to unfavorable malting quality traits.

Results

A Brazilian malting barley variety Br2 was identified as tolerant to acid soil. A doubled haploid (DH) population was developed from a cross between Br2 and the Australian acid-sensitive cultivar Hamelin. The DH population was tested for acid soil tolerance in native acid soil and a hydroponic system with pH 4.2, pH 4.2 + Al or pH 6.5, and genotyped using SSR, DArT and gene-specific markers. A single QTL was detected for all parameters related to acid soil tolerance. The QTL was mapped to the known HvMATE location on chromosome 4H. Sequence alignment of the HvMATE gene identified 13 INDELs and 87 SNPs, where one SNP coded for a single amino acid difference between the two varieties. A gene-specific marker was developed to detect the single nucleotide polymorphism between Hamelin and Br2. This marker co-segregated with aluminium tolerance and accounted for 79 % of phenotypic variation for acid soil tolerance.

Conclusion

The present study identified a novel source of acid soil/Al tolerance from a Brazilian malting barley cultivar Br2. This variety tolerated Al toxicity but was sensitive to low pH which is similar to most other Al-tolerant varieties. A gene-specific marker Cit7 was developed based on the HvMATE gene sequence. Cit7 will improve the efficiency of molecular-assisted selection of new barley varieties with tolerance to acid soil. Multiple alleles exist for the acid soil tolerance gene on chromosome 4H, so a malting barley variety that tolerates acid soil could be developed by selecting suitable tolerant alleles. Tolerance to low pH may play an important role for barley to adapt to acid soils.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0254-4) contains supplementary material, which is available to authorized users.

Inclusive Composite Interval Mapping of QTL by Environment Interactions in Biparental Populations

Identification of environment-specific QTL and stable QTL having consistent genetic effects across a wide range of environments is of great importance in plant breeding. Inclusive Composite Interval Mapping (ICIM) has been proposed for additive, dominant and epistatic QTL mapping in biparental populations for single environment. In this study, ICIM was extended to QTL by environment interaction (QEI) mapping for multi-environmental trials, where the QTL average effect and QEI effects could be properly estimated. Stepwise regression was firstly applied in each environment to identify the most significant marker variables which were then used to adjust the phenotypic values. One-dimensional scanning was then conducted on the adjusted phenotypic values across the environments in order to detect QTL with either average effect or QEI effects, or both average effect and QEI effects. In this way, the genetic background could be well controlled while the conventional interval mapping was applied. An empirical method to determine the threshold of logarithm of odds was developed, and the efficiency of the ICIM QEI mapping was demonstrated in simulated populations under different genetic models. One actual recombinant inbred line population was used to compare mapping results between QEI mapping and single-environment analysis.

Large-Scale SNP Discovery and Genotyping for Constructing a High-Density Genetic Map of Tea Plant Using Specific-Locus Amplified Fragment Sequencing (SLAF-seq)

Genetic maps are important tools in plant genomics and breeding. The present study reports the large-scale discovery of single nucleotide polymorphisms (SNPs) for genetic map construction in tea plant. We developed a total of 6,042 valid SNP markers using specific-locus amplified fragment sequencing (SLAF-seq), and subsequently mapped them into the previous framework map. The final map contained 6,448 molecular markers, distributing on fifteen linkage groups corresponding to the number of tea plant chromosomes. The total map length was 3,965 cM, with an average inter-locus distance of 1.0 cM. This map is the first SNP-based reference map of tea plant, as well as the most saturated one developed to date. The SNP markers and map resources generated in this study provide a wealth of genetic information that can serve as a foundation for downstream genetic analyses, such as the fine mapping of quantitative trait loci (QTL), map-based cloning, marker-assisted selection, and anchoring of scaffolds to facilitate the process of whole genome sequencing projects for tea plant.