Mapping QTL for grain yield and other agronomic traits in post-rainy sorghum [Sorghum bicolor (L.) Moench]

Sorghum, a cereal of economic importance ensures food and fodder security for millions of rural families in the semi-arid tropics. The objective of the present study was to identify and validate quantitative trait loci (QTL) for grain yield and other agronomic traits using replicated phenotypic data sets from three post-rainy dry sorghum crop seasons involving a mapping population with 245 F₉ recombinant inbred lines derived from a cross of M35-1 × B35. A genetic linkage map was constructed with 237 markers consisting of 174 genomic, 60 genic and 3 morphological markers. The QTL analysis for 11 traits following composite interval mapping identified 91 QTL with 5–12 QTL for each trait. QTL detected in the population individually explained phenotypic variation between 2.5 and 30.3 % for a given trait and six major genomic regions with QTL effect on multiple traits were identified. Stable QTL across seasons were identified. Of the 60 genic markers mapped, 21 were found at QTL peak or tightly linked with QTL. A gene-based marker XnhsbSFCILP67 (Sb03g028240) on SBI-03, encoding indole-3-acetic acid-amido synthetase GH3.5, was found to be involved in QTL for seven traits. The QTL-linked markers identified for 11 agronomic traits may assist in fine mapping, map-based gene isolation and also for improving post-rainy sorghum through marker-assisted breeding.     

Sorghum stay-green QTL individually reduce post-flowering drought-induced leaf senescence

Sorghum is an important source of food, feed, and biofuel, especially in the semi-arid tropics because this cereal is well adapted to harsh, drought-prone environments. Post-flowering drought adaptation in sorghum is associated with the stay-green phenotype. Alleles that contribute to this complex trait have been mapped to four major QTL, Stg1-Stg4, using a population derived from BTx642 and RTx7000. Near-isogenic RTx7000 lines containing BTx642 DNA spanning one or more of the four stay-green QTL were constructed. The size and location of BTx642 DNA regions in each RTx7000 NIL were analysed using 62 DNA markers spanning the four stay-green QTL. RTx7000 NILs were identified that contained BTx642 DNA completely or partially spanning Stg1, Stg2, Stg3, or Stg4. NILs were also identified that contained sub-portions of each QTL and various combinations of the four major stay-green QTL. Physiological analysis of four RTx7000 NILs containing only Stg1, Stg2, Stg3, or Stg4 showed that BTx642 alleles in each of these loci could contribute to the stay-green phenotype. RTx7000 NILs containing BTx642 DNA corresponding to Stg2 retained more green leaf area at maturity under terminal drought conditions than RTx7000 or the other RTx7000 NILs. Under post-anthesis water deficit, a trend for delayed onset of leaf senescence compared with RTx7000 was also exhibited by the Stg2, Stg3, and Stg4 NILs, while significantly lower rates of leaf senescence in relation to RTx7000 were displayed by all of the Stg NILs to varying degrees, but particularly by the Stg2 NIL. Greener leaves at anthesis relative to RTx7000, indicated by higher SPAD values, were exhibited by the Stg1 and Stg4 NILs. The RTx7000 NILs created in this study provide the starting point for in-depth analysis of stay-green physiology, interaction among stay-green QTL and map-based cloning of the genes that underlie this trait.     

Molecular mapping of QTLs conferring stay-green in grain sorghum (Sorghum bicolor L. Moench).

Drought resistance is of enormous importance in crop production. The identification of genetic factors involved in plant response to drought stress provides a strong foundation for improving drought tolerance. Stay-green is a drought resistance trait in sorghum (Sorghum bicolor L. Moench) that gives plants resistance to premature senescence under severe soil moisture stress during the post-flowering stage. The objective of this study was to map quantitative trait loci (QTLs) that control the stay-green and chlorophyll content in sorghum. By using a restriction fragment length polymorphism (RFLP) map, developed from a recombinant inbred line (RIL) population, we identified four stay-green QTLs, located on three linkage groups. The QTLs (Stg1 and Stg2) are on linkage group A, with the other two, Stg3 and Stg4, on linkage groups D and J, respectively. Two stay-green QTLs, Stg1 and Stg2, explaining 13-20% and 20-30% of the phenotypic variability, respectively, were consistently identified in all trials at different locations in two years. Three QTLs for chlorophyll content (Chl1, Chl2, and Chl3), explaining 25-30% of the phenotypic variability were also identified under post-flowering drought stress. All coincided with the three stay-green QTL regions (Stg1, Stg2, and Stg3) accounting for 46% of the phenotypic variation. The Stg1 and Stg2 regions also contain the genes for key photosynthetic enzymes, heat shock proteins, and an abscisic acid (ABA) responsive gene. Such spatial arrangement shows that linkage group A is important for drought- and heat-stress tolerance and yield production in sorghum. High-resolution mapping and cloning of the consistent stay-green QTLs may help to develop drought-resistant hybrids and to understand the mechanism of drought-induced senescence in plants.     

Quantitative trait loci for the stay green trait in sorghum (Sorghum bicolor L. Moench): consistency across genetic backgrounds and environments

 Stay green in sorghum (Sorghum bicolor L. Moench) is characterized by the plant’s ability to tolerate post-flowering drought stress, thereby delaying the premature leaf and plant death. It contributes to normal grain filling and reduces the incidence of stalk lodging and charcoal rot disease during the late stages of grain development. Breeding for improving post-flowering drought tolerance in sorghum hybrids remains an important objective of sorghum breeders. Since evaluation of the stay green response is difficult and unreliable under field conditions, due to the timing and intensity of moisture stress and large environmental interaction, progress in improving drought tolerance by conventional breeding methods has been slow. The objective of the present study was to determine the consistency of quantitative trait loci (QTLs) controlling stay green in sorghum. We re-evaluated the Recombinant Inbred Line (RIL)-mapping population from the cross B35 x Tx7000 in two locations over 2 years and compared it with earlier reports. Analysis using the combined stay green-rating means of seven environments and the expanded molecular map reconfirmed all four stay green QTLs (Stg1, Stg2, Stg3 and Stg4) that were identified earlier by Xu et al. (2000). Similarly, comparison of the stay green QTL locations with earlier reported results indicated that all four stay green QTLs showed consistency across different genetic backgrounds. Examination of the stay green QTL profiles of the best and poorest stay-green lines indicated that three stay green QTLs, Stg1, Stg2 and Stg3, appear to be important for the expression of this trait when the percent phenotypic variation, and the consistency in different backgrounds and different environments, are considered. A significant epistatic interaction involving Stg2 and a region on linkage group C was also identified for the stay green and chlorophyll content. We concluded that Stg2 is the most important QTL controlling stay green, explaining the maximum amount of phenotypic variation. This report further strengthens our view to target the Stg2 QTL region for gene discovery in order to improve the basic understanding of the stay green phenomenon, which might be helpful in manipulating this trait not only in sorghum but also in other cereal crop species. Received: 12 January 2000 / Accepted: 12 February 2000     

QTL mapping of stay-green in two sorghum recombinant inbred populations

The stay-green trait is a reported component of tolerance to terminal drought stress in sorghum. To map quantitative trait loci (QTLs) for stay-green, two sorghum recombinant inbred populations (RIPs) of 226 F(3:5) lines each were developed from crosses (1) IS9830 x E36-1 and (2) N13 x E36-1. The common parental line, E36-1 of Ethiopian origin, was the stay-green trait source. The genetic map of RIP 1 had a total length of 1,291 cM, with 128 markers (AFLPs, RFLPs, SSRs and RAPDs) distributed over ten linkage groups. The map of RIP 2 spanned 1,438 cM and contained 146 markers in 12 linkage groups. The two RIPs were evaluated during post-rainy seasons at Patancheru, India, in 1999/2000 (RIP 2) and 2000/2001 (RIP 1). The measures of stay-green mapped were the green leaf area percentages at 15, 30 and 45 days after flowering (% GL15, % GL30 and % GL45, respectively). Estimated repeatabilities for % GL15, % GL30 and % GL45 amounted to 0.89, 0.81 and 0.78 in RIP 1, and 0.91, 0.88 and 0.85 in RIP 2, respectively. The number of QTLs for the three traits detected by composite interval mapping ranged from 5 to 8, explaining 31% to 42% of the genetic variance. In both RIPs, both parent lines contributed stay-green alleles. Across the three measures of the stay-green trait, three QTLs on linkage groups A, E and G were common to both RIPs, with the stay-green alleles originating from E36-1. These QTLs were therefore consistent across the tested genetic backgrounds and years. After QTL validation across sites and verification of the general benefit of the stay-green trait for grain yield performance and stability in the target areas, the corresponding chromosomal regions could be candidates for marker-assisted transfer of stay-green into elite materials.     

Identification of QTL for sugar-related traits in a sweet × grain sorghum (<Emphasis Type="Italic">Sorghum bicolor</Emphasis> L. Moench) recombinant inbred population

QTL for stem sugar-related and other agronomic traits were identified in a converted sweet (R9188) × grain (R9403463-2-1) sorghum population. QTL analyses were conducted using phenotypic data for 11 traits measured in two field experiments and a genetic map comprising 228 SSR and AFLP markers grouped into 16 linkage groups, of which 11 could be assigned to the 10 sorghum chromosomes (SBI-01 to SBI-10). QTL were identified for all traits and were generally co-located to five locations (SBI-01, SBI-03, SBI-05, SBI-06 and SBI-10). QTL alleles from R9188 were detected for increased sucrose content and sugar content on SBI-01, SBI-05 and SBI-06. R9188 also contributed QTL alleles for increased Brix on SBI-05 and SBI-06, and increased sugar content on SBI-03. QTL alleles from R9403463-2-1 were found for increased sucrose content and sucrose yield on SBI-10, and increased glucose content on SBI-07. QTL alleles for increased height, later flowering and greater total dry matter yield were located on SBI-01 of R9403463-2-1, and SBI-06 of R9188. QTL alleles for increased grain yield from both R9403463-2-1 and R9188 were found on SBI-03. As an increase in stem sugars is an important objective in sweet sorghum breeding, the QTL identified in this study could be further investigated for use in marker-assisted selection of sweet sorghum.     

Genetic dissection of early-season cold tolerance in sorghum: genome-wide association studies for seedling emergence and survival under field and controlled environment conditions

Key message

A QTL on sorghum chromosome SBI-06 putatively improves field emergence under low-temperature conditions.

Abstract

Low temperatures decisively limit seedling emergence and vigor during early growth of sorghum and, thus, strongly impair geographical expansion. To broaden sorghum cultivation to temperate regions, the establishment of cold-tolerant genotypes is a prioritized breeding goal. The present study aims at the quantification of seedling emergence and survival under chilling temperatures and the detection of marker–trait associations controlling temperature-related seedling establishment. A diversity set consisting of 194 biomass sorghum lines was subjected to extensive phenotyping comprising field trials and controlled environment experiments. The final emergence percentage (FEP) under field conditions was significantly reduced under cold stress. Broad-sense heritability was h ² = 0.87 for FEP in the field and h ² = 0.93 for seedling survival rate (SR) under controlled conditions. Correlations between FEP in the field and under controlled conditions were low; higher correlations were observed between field FEP and SR in controlled environments. Genome-wide association studies (GWAS) were conducted using 44,515 single nucleotide polymorphisms (SNPs) and revealed eight regions with suggestive marker–trait associations for FEP and SR on chromosomes SBI-01, -02, -03, -06, -09, and -10 (p < 5.7 × 10^?5) and a significant association on SBI-06 for field FEP (p < 2.9 × 10^?6). Although not significant under controlled conditions, SR of genotypes carrying the minor allele on the field FEP quantitative trait loci (QTL) on SBI-06 was on average 13.1% higher, while FEP under controlled conditions was on average 9.7% higher with a linearly decreasing effect with increasing temperatures (R ² = 0.82). Promising candidate genes putatively conferring seedling cold tolerance were identified.

     

Genetic dissection of temperature-dependent sorghum growth during juvenile development

Key message

Promising genome regions for improving cold tolerance of sorghum were identified on chromosomes SBI-01, SBI-03, SBI-07, and SBI-10. Chlorophyll fluorescence had no major effect on growth rates at low temperatures.

Abstract

Developing fast growing sorghum seedlings is an important breeding goal for temperate climates since low springtime temperatures are resulting in a prolonged juvenile development. The adaptation of sorghum to tropical and subtropical highlands gives hint for certain genetic variation. The goals of the present study were to detect marker-trait associations for leaf and dry matter growth rate and for chlorophyll fluorescence and content (SPAD) in relation to temperature. A diversity set comprising 194 genotypes was tested in eight controlled environments with temperatures ranging from 9.4 to 20.8 °C. Significant marker-trait associations (p < 0.05) were identified for each individual temperature regime and on the parameters of regression analyses describing the responses of growth or chlorophyll related traits to temperatures. The diversity set was fingerprinted with 171 diversity array technology (DArT) and 31 simple-sequence repeat (SSR) markers. SSRs were used to analyze the population structure while association studies were performed on DArT markers. Promising marker-trait associations for growth rates in relation to temperature were detected on chromosomes SBI-01, SBI-03, SBI-07, and SBI-10. Many promising loci were also significantly associated to the results obtained in individual low-temperature environments. Marker-trait associations for chlorophyll content and fluorescence did occasionally co-locate to those for growth during juvenile development but there was no evidence supporting our hypothesis that seedling growth at low temperatures is largely influenced by SPAD or fluorescence.     

Association analysis for udder health based on SNP-panel and sequence data in Danish Holsteins

Background

The sensitivity of genome-wide association studies for the detection of quantitative trait loci (QTL) depends on the density of markers examined and the statistical models used. This study compares the performance of three marker densities to refine six previously detected QTL regions for mastitis traits: 54 k markers of a medium-density SNP (single nucleotide polymorphism) chip (MD), imputed 777 k markers of a high-density SNP chip (HD), and imputed whole-genome sequencing data (SEQ). Each dataset contained data for 4496 Danish Holstein cattle. Comparisons were performed using a linear mixed model (LM) and a Bayesian variable selection model (BVS).

Results

After quality control, 587, 7825, and 78 856 SNPs in the six targeted regions remained for MD, HD, and SEQ data, respectively. In general, the association patterns between SNPs and traits were similar for the three marker densities when tested using the same statistical model. With the LM model, 120 (MD), 967 (HD), and 7209 (SEQ) SNPs were significantly associated with mastitis, whereas with the BVS model, 43 (MD), 131 (HD), and 1052 (SEQ) significant SNPs (Bayes factor > 3.2) were observed. A total of 26 (MD), 75 (HD), and 465 (SEQ) significant SNPs were identified by both models. In addition, one, 16, and 33 QTL peaks for MD, HD, and SEQ data were detected according to the QTL intensity profile of SNP bins by post-analysis of the BVS model.

Conclusions

The power to detect significant associations increased with increasing marker density. The BVS model resulted in clearer boundaries between linked QTL than the LM model. Using SEQ data, the six targeted regions were refined to 33 candidate QTL regions for udder health. The comparison between these candidate QTL regions and known genes suggested that NPFFR2, SLC4A4, DCK, LIFR, and EDN3 may be considered as candidate genes for mastitis susceptibility.

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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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.

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Mapping of post-flowering drought resistance traits in grain sorghum: association between QTLs influencing premature senescence and maturity

The identification of genetic factors underlying the complex responses of plants to drought stress provides a solid basis for improving drought resistance. The stay-green character in sorghum (Sorghum bicolor L. Moench) is a post-flowering drought resistance trait, which makes plants resistant to premature senescence under drought stress during the grainfilling stage. The objective of this study was to identify quantitative trait loci (QTLs) that control premature senescence and maturity traits, and to investigate their association under post-flowering drought stress in grain sorghum. A genetic linkage map was developed using a set of recombinant inbred lines (RILs) obtained from the cross B35 × Tx430, which were scored for 142 restriction fragment length polymorphism (RFLP) markers. The RILs and their parental lines were evaluated for post-flowering drought resistance and maturity in four environments. Simple interval mapping identified seven stay-green QTLs and two maturity QTLs. Three major stay-green QTLs (SGA, SGD and SGG) contributed to 42% of the phenotypic variability (LOD 9.0) and four minor QTLs (SGB, SGI.1, SGI.2, and SGJ) significantly contributed to an additional 25% of the phenotypic variability in stay-green ratings. One maturity QTL (DFB) alone contributed to 40% of the phenotypic variability (LOD 10.0), while the second QTL (DFG) significantly contributed to an additional 17% of the phenotypic variability (LOD 4.9). Composite interval mapping confirmed the above results with an additional analysis of the QTL × Environment interaction. With heritability estimates of 0.72 for stay-green and 0.90 for maturity, the identified QTLs explained about 90% and 63% of genetic variability for stay-green and maturity traits, respectively. Although stay-green ratings were significantly correlated (r=0.22, P ≤ 0.05) with maturity, six of the seven stay-green QTLs were independent of the QTLs influencing maturity. Similarly, one maturity QTL (DFB) was independent of the stay-green QTLs. One stay-green QTL (SGG), however, mapped in the vicinity of a maturity QTL (DFG), and all markers in the vicinity of the independent maturity QTL (DFB) were significantly (P ≤ 0.1) correlated with stay-green ratings, confounding the phenotyping of stay-green. The molecular genetic analysis of the QTLs influencing stay-green and maturity, together with the association between these two inversely related traits, provides a basis for further study of the underlying physiological mechanisms and demonstrates the possibility of improving drought resistance in plants by pyramiding the favorable QTLs. Received: 10 October 1998 / Accepted: 12 July 1999     

Evidence for selection on a CONSTANS-like gene between two red oak species

Background and Aims

Hybridizing species such as oaks may provide a model to study the role of selection in speciation with gene flow. Discrete species'' identities and different adaptations are maintained among closely related oak species despite recurrent gene flow. This is probably due to ecologically mediated selection at a few key genes or genomic regions. Neutrality tests can be applied to identify so-called outlier loci, which demonstrate locus-specific signatures of divergent selection and are candidate genes for further study.

Methods

Thirty-six genic microsatellite markers, some with putative functions in flowering time and drought tolerance, and eight non-genic microsatellite markers were screened in two population pairs (n = 160) of the interfertile species Quercus rubra and Q. ellipsoidalis, which are characterized by contrasting adaptations to drought. Putative outliers were then tested in additional population pairs from two different geographic regions (n = 159) to support further their potential role in adaptive divergence.

Key Results

A marker located in the coding sequence of a putative CONSTANS-like (COL) gene was repeatedly identified as under strong divergent selection across all three geographically disjunct population pairs. COL genes are involved in the photoperiodic control of growth and development and are implicated in the regulation of flowering time.

Conclusions

The location of the polymorphism in the Quercus COL gene and given the potential role of COL genes in adaptive divergence and reproductive isolation makes this a promising candidate speciation gene. Further investigation of the phenological characteristics of both species and flowering time pathway genes is suggested in order to elucidate the importance of phenology genes for the maintenance of species integrity. Next-generation sequencing in multiple population pairs in combination with high-density genetic linkage maps could reveal the genome-wide distribution of outlier genes and their potential role in reproductive isolation between these species.     

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

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Homoeologous duplicated regions are involved in quantitative resistance of Brassica napus to stem canker

Background

Several major crop species are current or ancient polyploids. To better describe the genetic factors controlling traits of agronomic interest (QTL), it is necessary to understand the structural and functional organisation of these QTL regions in relation to genome duplication. We investigated quantitative resistance to the fungal disease stem canker in Brassica napus, a highly duplicated amphidiploid species, to assess the proportion of resistance QTL located at duplicated positions.

Results

Genome-wide association analysis on a panel of 116 oilseed rape varieties genotyped with 3228 SNP indicated that 321 markers, corresponding to 64 genomic regions, are associated with resistance to stem canker. These genomic regions are relatively equally distributed on the A (53%) and C (47%) genomes of B. napus. Overall, 44% of these regions (28/64) are duplicated homoeologous regions. They are located in duplications of six (E, J, R, T, U and W) of the 24 ancestral blocks that constitute the B. napus genome. Overall, these six ancestral blocks have 34 duplicated copies in the B.napus genome. Almost all of the duplicated copies (82% of the 34 regions) harboured resistance associated markers for stem canker resistance, which suggests structural and functional conservation of genetic factors involved in this trait in B. napus.

Conclusions

Our study provides information on the involvement of duplicated loci in the control of stem canker resistance in B. napus. Further investigation of the similarity/divergence in sequence and gene content of these duplicated regions will provide insight into the conservation and allelic diversity of the underlying genes.

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.