BioMercator: integrating genetic maps and QTL towards discovery of candidate genes

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.

Yield QTLome distribution correlates with gene density in maize

The genetic control of yield and related traits in maize has been addressed by many quantitative trait locus (QTL) studies, which have produced a wealth of QTL information, also known as QTLome. In this study, we assembled a yield QTLome database and carried out QTL meta-analysis based on 44 published studies, representing 32 independent mapping populations and 49 parental lines. A total of 808 unique QTLs were condensed to 84 meta-QTLs and were projected on the 10 maize chromosomes. Seventy-four percent of QTLs showed a proportion of phenotypic variance explained (PVE) smaller than 10% confirming the high genetic complexity of grain yield. Yield QTLome projection on the genetic map suggested pericentromeric enrichment of QTLs. Conversely, pericentromeric depletion of QTLs was observed when the physical map was considered, suggesting gene density as the main driver of yield QTL distribution on chromosomes. Dominant and overdominant yield QTLs did not distribute differently from additive effect QTLs.

Genome-Wide Identification of QTL for Seed Yield and Yield-Related Traits and Construction of a High-Density Consensus Map for QTL Comparison in Brassica napus

Seed yield (SY) is the most important trait in rapeseed, is determined by multiple seed yield-related traits (SYRTs) and is also easily subject to environmental influence. Many quantitative trait loci (QTLs) for SY and SYRTs have been reported in Brassica napus; however, no studies have focused on seven agronomic traits simultaneously affecting SY. Genome-wide QTL analysis for SY and seven SYRTs in eight environments was conducted in a doubled haploid population containing 348 lines. Totally, 18 and 208 QTLs for SY and SYRTs were observed, respectively, and then these QTLs were integrated into 144 consensus QTLs using a meta-analysis. Three major QTLs for SY were observed, including cqSY-C6-2 and cqSY-C6-3 that were expressed stably in winter cultivation area for 3 years and cqSY-A2-2 only expressed in spring rapeseed area. Trait-by-trait meta-analysis revealed that the 144 consensus QTLs were integrated into 72 pleiotropic unique QTLs. Among them, all the unique QTLs affected SY, except for uq.A6-1, including uq.A2-3, uq.C1-2, uq.C1-3, uq.C6-1, uq.C6-5, and uq.C6-6 could also affect more than two SYRTs. According to the constructed high-density consensus map and QTL comparison from literatures, 36 QTLs from five populations were co-localized with QTLs identified in this study. In addition, 13 orthologous genes were observed, including five each gene for SY and thousand seed weight, and one gene each for biomass yield, branch height, and plant height. The genomic information of these QTLs will be valuable in hybrid cultivar breeding and in analyzing QTL expression in different environments.

Dissecting the Genetic Architecture of Leaf Rust Resistance in Wheat by QTL Meta-Analysis

Leaf rust is an important disease that causes significant yield losses in wheat. Many studies have reported the identification of quantitative trait loci (QTL) controlling leaf rust resistance; therefore, QTL meta-analysis has become a useful tool for identifying consensus QTL and refining QTL positions among them. In this study, QTL meta-analysis was conducted using reported results on the number, position, and effects of QTL for leaf rust resistance in bread and durum wheat. Investigation of 14 leaf rust resistance traits from 19 studies involving 20 mapping populations and 33 different parental lines provided information for 144 unique QTL that were projected onto the Wheat Composite 2004 reference map. In total, 35 meta-QTL for leaf rust resistance traits were identified in 17 wheat chromosomes and 13 QTL remained as unique QTL. The results will facilitate further work on the cloning of QTL for pyramiding minor- and partial-effect resistance genes to develop varieties with durable resistance to leaf rust.

Mapping and introgression of QTL for yield and related traits in two backcross populations derived from Oryza sativa cv. Swarna and two accessions of O. nivara

Advanced backcross QTL (AB-QTL) analysis was carried out in two Oryza nivara-derived BC2F2 populations. For nine traits, we identified 28 QTL in population 1 and 26 QTL in population 2. The two most significant yield-enhancing QTL, yldp9.1 and yldp2.1 showed an additive effect of 16 and 7 g per plant in population 1, while yld2.1 and yld11.1 showed an additive effect of 11 and 10 g per plant in population 2. At least one O. nivara-derived QTL with a phenotypic variance of >15% was detected for seven traits in population 1 and three traits in population 2. The O. nivara-derived QTL ph1.1, nt12.1, nsp1.1, nfg1.1, bm11.1, yld2.1 and yld11.1 were conserved at the same chromosomal locations in both populations. Two major QTL clusters were detected at the marker intervals RM488-RM431 and RM6-RM535 on chromosomes 1 and 2, respectively. The colocation of O. nivara-derived yield QTL with yield meta-QTL on chromosomes 1, 2 and 9 indicates their accuracy and consistency. The major-effect QTL reported in this study are useful for marker-assisted breeding and are also suitable for further fine mapping and candidate gene identification.

High Resolution Consensus Mapping of Quantitative Trait Loci for Fiber Strength, Length and Micronaire on Chromosome 25 of the Upland Cotton (Gossypium hirsutum L.)

Cotton (Gossypium hirsutum L.) is an important agricultural crop that provides renewable natural fiber resources for the global textile industry. Technological developments in the textile industry and improvements in human living standards have increased the requirement for supplies and better quality cotton. Upland cotton 0-153 is an elite cultivar harboring strong fiber strength genes. To conduct quantitative trait locus (QTL) mapping for fiber quality in 0-153, we developed a population of 196 recombinant inbred lines (RILs) from a cross between 0-153 and sGK9708. The fiber quality traits in 11 environments were measured and a genetic linkage map of chromosome 25 comprising 210 loci was constructed using this RIL population, mainly using simple sequence repeat markers and single nucleotide polymorphism markers. QTLs were identified across diverse environments using the composite interval mapping method. A total of 37 QTLs for fiber quality traits were identified on chromosome 25, of which 17 were stably expressed in at least in two environments. A stable fiber strength QTL, qFS-chr25-4, which was detected in seven environments and was located in the marker interval between CRI-SNP120491 and BNL2572, could explain 6.53%-11.83% of the observed phenotypic variations. Meta-analysis also confirmed the above QTLs with previous reports. Application of these QTLs could contribute to improving fiber quality and provide information for marker-assisted selection.

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

The online version of this article (doi:10.1186/s12864-015-1682-2) contains supplementary material, which is available to authorized users.

QTL Mapping for Fiber and Yield Traits in Upland Cotton under Multiple Environments

A population of 178 recombinant inbred lines (RILs) was developed using a single seed descendant from a cross between G. hirsutum. acc DH962 and G. hirsutum. cv Jimian5, was used to construct a genetic map and to map QTL for fiber and yield traits. A total of 644 polymorphic loci were used to construct a final genetic map, containing 616 loci and spanning 2016.44 cM, with an average of 3.27 cM between adjacent markers. Statistical analysis revealed that segregation distortion in the intraspecific population was more serious than that in the interspecific population. The RIL population and the two parents were phenotyped under 8 environments (two locations, six years), revealing a total of 134 QTL, including 64 for fiber qualities and 70 for yield components, independently detected in seven environments, explaining 4.40-15.28% of phenotypic variation (PV). Among the 134 QTL, 9 common QTL were detected in more than one environment, and 22 QTL and 19 new QTL were detected in combined analysis (E9). A total of 26 QTL hotspot regions were observed on 13 chromosomes and 2 larger linkage groups, and some QTL clusters related to fiber qualities or yield components were also observed. The results obtained in the present study suggested that to map accurate QTL in crops with larger plant types, such as cotton, phenotyping under multiple environments is necessary to effectively apply the obtained results in molecular marker-assisted selection breeding and QTL cloning.

Dynamic and comparative QTL analysis for plant height in different developmental stages of Brassica napus L

This report describes a dynamic QTL analysis for plant height at various stages using a large doubled haploid population and performs a QTL comparison between different populations in Brassica napus. Plant height (PH) not only plays an important role in determining plant architecture, but is also an important character related to yield. The process of determining PH occurs through a series of steps; however, no studies have focused on developmental behavior factors affecting PH in Brassica napus. In the present study, KN DH, a large doubled haploid population containing 348 lines was used for a dynamic quantitative trait locus (QTL) analysis for PH in six experiments. In all, 20 QTLs were identified at maturity, whereas 50 QTLs were detected by conditional m apping method and the same number was identified by unconditional mapping strategies. Interestingly, five unconditional QTLs ucPH.A2-2, ucPH.A3-2, ucPH.C5-1, ucPH.C6-2 and ucPH.C6-3 were identified that were consistent over the all growth stages of one or two particular experiments, and one conditional QTL cPH.A2-3 was expressed throughout the entire growth process in one experiment. A total of 70 QTLs were obtained after combining QTLs identified at maturity, by conditional and unconditional mapping strategies, in which 25 showed opposite genetic effects in different periods/stages and experiments. A consensus map containing 1357 markers was constructed to compare QTLs identified in the KN population with five previously mapped populations. Alignment of the QTLs detected in different populations onto the consensus map showed that 27 were repeatedly detected in different genetic backgrounds. These findings will enhance our understanding of the genetic control of PH regulation in B. napus, and will be useful for rapeseed genetic manipulation through molecular marker-assisted selection.

Deciphering allelic variations for seed glucosinolate traits in oilseed mustard (Brassica juncea) using two bi-parental mapping populations

QTL mapping by two DH mapping populations deciphered allelic variations for five different seed glucosinolate traits in B. juncea. Allelic variations for five different seed glucosinolate (GS) traits, namely % propyl, % butyl, % pentyl, aliphatics and total GS content were studied through QTL analysis using two doubled haploid (DH) mapping populations. While the high GS parents in two populations differed in their profiles of seed aliphatic GS, the low GS parents were similar. Phenotypic data of seed GS traits from three environments of the two populations were subjected to QTL analysis. The first population (referred to as DE population) detected a total of 60 QTL from three environments which upon intra-population meta-QTL analysis were merged to 17 S-QTL (Stable QTL) and 15 E-QTL (Environment QTL). The second population (referred to as VH population) detected 58 QTL from the three environments that were merged to 15S-QTL and 16E-QTL. In both the populations, majority of S-QTL were detected as major QTL. Inter-population meta-analysis identified three C-QTL (consensus QTL) formed by merging major QTL from the two populations. Candidate genes of GS pathway were co-localized to the QTL regions either through genetic mapping or through in silico comparative analysis. Parental allelic variants of QTL or of the co-mapped candidate gene(s) were determined on the basis of the significantly different R (2) values of the component QTL from the two populations which were merged to form C-QTL. The results of the study are significant for marker-assisted transfer of the low GS trait and also for developing lines with lower GS than are present in Brassica juncea.

New insights into the genetic networks affecting seed fatty acid concentrations in Brassica napus

BACKGROUND

Rapeseed (B. napus, AACC, 2n = 38) is one of the most important oil seed crops in the world, it is also one of the most common oil for production of biodiesel. Its oil is a mixture of various fatty acids and dissection of the genetic network for fatty acids biosynthesis is of great importance for improving seed quality.

RESULTS

The genetic basis of fatty acid biosynthesis in B. napus was investigated via quantitative trail locus (QTL) analysis using a doubled haploid (DH) population with 202 lines. A total of 72 individual QTLs and a large number pairs of epistatic interactions associated with the content of 10 different fatty acids were detected. A total of 234 homologous genes of Arabidopsis thaliana that are involved in fatty acid metabolism were found within the confidence intervals (CIs) of 47 QTLs. Among them, 47 and 15 genes homologous to those of B. rapa and B. oleracea were detected, respectively. After the QTL mapping, the epistatic and the candidate gene interaction analysis, a potential regulatory pathway controlling fatty acid biosynthesis in B. napus was constructed, including 50 enzymes encoded genes and five regulatory factors (LEC1, LEC2, FUS3, WRI1 and ABI3). Subsequently, the interaction between these five regulatory factors and the genes involved in fatty acid metabolism were analyzed.

CONCLUSIONS

In this study, a potential regulatory pathway controlling the fatty acid was constructed by QTL analysis and in silico mapping analysis. These results enriched our knowledge of QTLs for fatty acids metabolism and provided a new clue for genetic engineering fatty acids composition in B. napus.

Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum × G. barbadense populations

KEY MESSAGE

A specialized database currently containing more than 2200 QTL is established, which allows graphic presentation, visualization and submission of QTL. In cotton quantitative trait loci (QTL), studies are focused on intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations. These two populations are commercially important for the textile industry and are evaluated for fiber quality, yield, seed quality, resistance, physiological, and morphological trait QTL. With meta-analysis data based on the vast amount of QTL studies in cotton it will be beneficial to organize the data into a functional database for the cotton community. Here we provide a tool for cotton researchers to visualize previously identified QTL and submit their own QTL to the Cotton QTLdb database. The database provides the user with the option of selecting various QTL trait types from either the G. hirsutum or G. hirsutum × G. barbadense populations. Based on the user's QTL trait selection, graphical representations of chromosomes of the population selected are displayed in publication ready images. The database also provides users with trait information on QTL, LOD scores, and explained phenotypic variances for all QTL selected. The CottonQTLdb database provides cotton geneticist and breeders with statistical data on cotton QTL previously identified and provides a visualization tool to view QTL positions on chromosomes. Currently the database (Release 1) contains 2274 QTLs, and succeeding QTL studies will be updated regularly by the curators and members of the cotton community that contribute their data to keep the database current. The database is accessible from http://www.cottonqtldb.org.

Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum × G. barbadense populations

KEY MESSAGE

A specialized database currently containing more than 2200 QTL is established, which allows graphic presentation, visualization and submission of QTL. In cotton quantitative trait loci (QTL), studies are focused on intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations. These two populations are commercially important for the textile industry and are evaluated for fiber quality, yield, seed quality, resistance, physiological, and morphological trait QTL. With meta-analysis data based on the vast amount of QTL studies in cotton it will be beneficial to organize the data into a functional database for the cotton community. Here we provide a tool for cotton researchers to visualize previously identified QTL and submit their own QTL to the Cotton QTLdb database. The database provides the user with the option of selecting various QTL trait types from either the G. hirsutum or G. hirsutum × G. barbadense populations. Based on the user's QTL trait selection, graphical representations of chromosomes of the population selected are displayed in publication ready images. The database also provides users with trait information on QTL, LOD scores, and explained phenotypic variances for all QTL selected. The CottonQTLdb database provides cotton geneticist and breeders with statistical data on cotton QTL previously identified and provides a visualization tool to view QTL positions on chromosomes. Currently the database (Release 1) contains 2274 QTLs, and succeeding QTL studies will be updated regularly by the curators and members of the cotton community that contribute their data to keep the database current. The database is accessible from http://www.cottonqtldb.org.

Genetic analysis and major quantitative trait locus mapping of leaf widths at different positions in multiple populations

BACKGROUND

Leaf width is an important agricultural trait in maize. Leaf development is dependent on cell proliferation and expansion, and these processes exhibit polarity with respect to the longitudinal and transverse axes of the leaf. However, the molecular mechanism of the genetic control of seed vigor remains unknown in maize, and a better understanding of this mechanism is required.

METHODOLOGY/PRINCIPAL FINDINGS

To reveal the genetic architecture of leaf width, a comprehensive evaluation using four RIL populations was performed, followed by a meta-analysis. Forty-six QTLs associated with the widths of leaves at different positions above the uppermost ear were detected in the four RIL populations in three environments. The individual effects of the QTLs ranged from 4.33% to 18.01% of the observed phenotypic variation, with 14 QTLs showing effects of over 10%. We identified three common QTLs associated with leaf width at all of the examined positions, in addition to one common QTL associated with leaf width at three of the positions and six common QTLs associated with leaf width at two of the positions. The results indicate that leaf width at different leaf positions may be affected by one QTL or several of the same QTLs. Such traits may also be regulated by many different QTLs. Thirty-one of the forty-six initial QTLs were integrated into eight mQTLs through a meta-analysis, and 10 of the 14 initial QTLs presenting an R2>10% were integrated into six mQTLs.

CONCLUSIONS/SIGNIFICANCE

mQTL1-2, mQTL3-1, mQTL7, and mQTL8 were composed of the initial QTLs showing an R2>10% and included four to six of the initial QTLs that were associated with two to four positions in a single population. Therefore, these four chromosome regions may be hot spots for important QTLs for these traits. Thus, they warrant further studies and may be useful for marker-assisted breeding.

Comparative mapping combined with homology-based cloning of the rice genome reveals candidate genes for grain zinc and iron concentration in maize

BACKGROUND

Grain zinc and iron concentration is a complex trait that is controlled by quantitative trait loci (QTL) and is important for maintaining body health. Despite the substantial effort that has been put into identifying QTL for grain zinc and iron concentration, the integration of independent QTL is useful for understanding the genetic foundation of traits. The number of QTL for grain zinc and iron concentration is relatively low in a single species. Therefore, combined analysis of different genomes may help overcome this challenge.

RESULTS

As a continuation of our work on maize, meta-analysis of QTL for grain zinc and iron concentration in rice was performed to identify meta-QTL (MQTL). Based on MQTL in rice and maize, comparative mapping combined with homology-based cloning was performed to identify candidate genes for grain zinc and iron concentration in maize. In total, 22 MQTL in rice, 4 syntenic MQTL-related regions, and 3 MQTL-containing candidate genes in maize (ortho-mMQTL) were detected. Two maize orthologs of rice, GRMZM2G366919 and GRMZM2G178190, were characterized as natural resistance-associated macrophage protein (NRAMP) genes and considered to be candidate genes. Phylogenetic analysis of NRAMP genes among maize, rice, and Arabidopsis thaliana further demonstrated that they are likely responsible for the natural variation of maize grain zinc and iron concentration.

CONCLUSIONS

Syntenic MQTL-related regions and ortho-mMQTL are prime areas for future investigation as well as for marker-assisted selection breeding programs. Furthermore, the combined method using the rice genome that was used in this study can shed light on other species and help direct future quantitative trait research. In conclusion, these results help elucidate the molecular mechanism that underlies grain zinc and iron concentration in maize.

High-Density SNP Map Construction and QTL Identification for the Apetalous Character in Brassica napus L

The apetalous genotype is a morphological ideotype for increasing seed yield and should be of considerable agricultural use; however, only a few studies have focused on the genetic control of this trait in Brassica napus. In the present study, a recombinant inbred line, the AH population, containing 189 individuals was derived from a cross between an apetalous line 'APL01' and a normally petalled variety 'Holly'. The Brassica 60 K Infinium BeadChip Array harboring 52,157 single nucleotide polymorphism (SNP) markers was used to genotype the AH individuals. A high-density genetic linkage map was constructed based on 2,755 bins involving 11,458 SNPs and 57 simple sequence repeats, and was used to identify loci associated with petalous degree (PDgr). The linkage map covered 2,027.53 cM, with an average marker interval of 0.72 cM. The AH map had good collinearity with the B. napus reference genome, indicating its high quality and accuracy. After phenotypic analyses across five different experiments, a total of 19 identified quantitative trait loci (QTLs) distributed across chromosomes A3, A5, A6, A9 and C8 were obtained, and these QTLs were further integrated into nine consensus QTLs by a meta-analysis. Interestingly, the major QTL qPD.C8-2 was consistently detected in all five experiments, and qPD.A9-2 and qPD.C8-3 were stably expressed in four experiments. Comparative mapping between the AH map and the B. napus reference genome suggested that there were 328 genes underlying the confidence intervals of the three steady QTLs. Based on the Gene Ontology assignments of 52 genes to the regulation of floral development in published studies, 146 genes were considered as potential candidate genes for PDgr. The current study carried out a QTL analysis for PDgr using a high-density SNP map in B. napus, providing novel targets for improving seed yield. These results advanced our understanding of the genetic control of PDgr regulation in B. napus.

Genetic dissection of internode length above the uppermost ear in four RIL populations of maize (Zea mays L.)

The internode length above the uppermost ear (ILAU) is an important influencing factor for canopy architecture in maize. Analyzing the genetic characteristics of internode length is critical for improving plant population structure and increasing photosynthetic efficiency. However, the genetic control of ILAU has not been determined. In this study, quantitative trait loci (QTL) for internode length at five positions above the uppermost ear were identified using four sets of recombinant inbred line (RIL) populations in three environments. Genetic maps and initial QTL were integrated using meta-analyses across the four populations. Seventy QTL were identified: 16 in population 1; 14 in population 2; 25 in population 3; and 15 in population 4. Individual effects ranged from 5.36% to 26.85% of phenotypic variation, with 27 QTL >10%. In addition, the following common QTL were identified across two populations: one common QTL for the internode length of all five positions; one common QTL for the internode length of three positions; and one common QTL for the internode length of one position. In addition, four common QTL for the internode length of four positions were identified in one population. The results indicated that the ILAU at different positions above the uppermost ear could be affected by one or several of the same QTL. The traits may also be regulated by many different QTL. Of the 70 initial QTL, 46 were integrated in 14 meta-QTL (mQTLs) by meta-analysis, and 17 of the 27 initial QTL with R² >10% were integrated in 7 mQTLs. Four of the key mQTLs (mQTL2-2, mQTL3-2, mQTL5-1, mQTL5-2, and mQTL9) in which the initial QTL displayed R² >10% included four to 11 initial QTL for an internode length of four to five positions from one or two populations. These results may provide useful information for marker-assisted selection to improve canopy architecture.

A comparative meta-analysis of QTL between intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations

KEY MESSAGE

Based on 1075 and 1059 QTL from intraspecific Upland and interspecific Upland × Pima populations, respectively, the identification of QTL clusters and hotspots provides a useful resource for cotton breeding. Mapping of quantitative trait loci (QTL) is a pre-requisite of marker-assisted selection for crop yield and quality. Recent meta-analysis of QTL in tetraploid cotton (Gossypium spp.) has identified regions of the genome with high concentrations of QTL for various traits called clusters and specific trait QTL called hotspots or meta-QTL (mQTL). However, the meta-analysis included all population types of Gossypium mixing both intraspecific G. hirsutum and interspecific G. hirsutum × G. barbadense populations. This study used 1,075 QTL from 58 publications on intraspecific G. hirsutum and 1,059 QTL from 30 publications on G. hirsutum × G. barbadense populations to perform a comprehensive comparative analysis of QTL clusters and hotspots between the two populations for yield, fiber and seed quality, and biotic and abiotic stress tolerance. QTL hotspots were further analyzed for mQTL within the hotspots using Biomercator V3 software. The ratio of QTL between the two population types was proportional yet differences in hotspot type and placement were observed between the two population types. However, on some chromosomes QTL clusters and hotspots were similar between the two populations. This shows that there are some universal QTL regions in the cultivated tetraploid cotton which remain consistent and some regions which differ between population types. This study for the first time elucidates the similarities and differences in QTL clusters and hotspots between intraspecific and interspecific populations, providing an important resource to cotton breeding programs in marker-assisted selection .

A genome-wide identification of chromosomal regions determining nitrogen use efficiency components in wheat (Triticum aestivum L.)

This study identified 333 genomic regions associated to 28 traits related to nitrogen use efficiency in European winter wheat using genome-wide association in a 214-varieties panel experimented in eight environments. Improving nitrogen use efficiency is a key factor to sustainably ensure global production increase. However, while high-throughput screening methods remain at a developmental stage, genetic progress may be mainly driven by marker-assisted selection. The objective of this study was to identify chromosomal regions associated with nitrogen use efficiency-related traits in bread wheat (Triticum aestivum L.) using a genome-wide association approach. Two hundred and fourteen European elite varieties were characterised for 28 traits related to nitrogen use efficiency in eight environments in which two different nitrogen fertilisation levels were tested. The genome-wide association study was carried out using 23,603 SNP with a mixed model for taking into account parentage relationships among varieties. We identified 1,010 significantly associated SNP which defined 333 chromosomal regions associated with at least one trait and found colocalisations for 39 % of these chromosomal regions. A method based on linkage disequilibrium to define the associated region was suggested and discussed with reference to false positive rate. Through a network approach, colocalisations were analysed and highlighted the impact of genomic regions controlling nitrogen status at flowering, precocity, and nitrogen utilisation on global agronomic performance. We were able to explain 40 ± 10 % of the total genetic variation. Numerous colocalisations with previously published genomic regions were observed with such candidate genes as Ppd-D1, Rht-D1, NADH-Gogat, and GSe. We highlighted selection pressure on yield and nitrogen utilisation discussing allele frequencies in associated regions.

Plant genetics. Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome

Oilseed rape (Brassica napus L.) was formed ~7500 years ago by hybridization between B. rapa and B. oleracea, followed by chromosome doubling, a process known as allopolyploidy. Together with more ancient polyploidizations, this conferred an aggregate 72× genome multiplication since the origin of angiosperms and high gene content. We examined the B. napus genome and the consequences of its recent duplication. The constituent An and Cn subgenomes are engaged in subtle structural, functional, and epigenetic cross-talk, with abundant homeologous exchanges. Incipient gene loss and expression divergence have begun. Selection in B. napus oilseed types has accelerated the loss of glucosinolate genes, while preserving expansion of oil biosynthesis genes. These processes provide insights into allopolyploid evolution and its relationship with crop domestication and improvement.

Constructing a dense genetic linkage map and mapping QTL for the traits of flower development in Brassica carinata

An integrated dense genetic linkage map was constructed in a B. carinata population and used for comparative genome analysis and QTL identification for flowering time. An integrated dense linkage map of Brassica carinata (BBCC) was constructed in a doubled haploid population based on DArT-Seq(TM) markers. A total of 4,031 markers corresponding to 1,366 unique loci were mapped including 639 bins, covering a genetic distance of 2,048 cM. We identified 136 blocks and islands conserved in Brassicaceae, which showed a feature of hexaploidisation representing the suggested ancestral crucifer karyotype. The B and C genome of B. carinata shared 85 % of commonly conserved blocks with the B genome of B. nigra/B. juncea and 80 % of commonly conserved blocks with the C genome of B. napus, and shown frequent structural rearrangements such as insertions and inversions. Up to 24 quantitative trait loci (QTL) for flowering and budding time were identified in the DH population. Of these QTL, one consistent QTL (qFT.B4-2) for flowering time was identified in all of the environments in the J block of the B4 linkage group, where a group of genes for flowering time were aligned in A. thaliana. Another major QTL for flowering time under a winter-cropped environment was detected in the E block of C6, where the BnFT-C6 gene was previously localised in B. napus. This high-density map would be useful not only to reveal the genetic variation in the species with QTL analysis and genome sequencing, but also for other applications such as marker-assisted selection and genomic selection, for the African mustard improvement.

QTL meta-analysis in Arabidopsis reveals an interaction between leaf senescence and resource allocation to seeds

Sequential and monocarpic senescence are observed at vegetative and reproductive stages, respectively. Both facilitate nitrogen (N) remobilization and control the duration of carbon (C) fixation. Genetic and environmental factors control N and C resource allocation to seeds. Studies of natural variation in Arabidopsis thaliana revealed differences between accessions for leaf senescence phenotypes, seed N and C contents, and N remobilization efficiency-related traits. Here, a quantitative genetics approach was used to gain a better understanding of seed filling regulation in relation to leaf senescence and resource allocation. For that purpose, three Arabidopsis recombinant inbred line populations (Ct-1×Col-0, Cvi-0×Col-0, Bur-0×Col-0) were used to map QTL (quantitative trait loci) for ten traits related to senescence, resource allocation, and seed filling. The use of common markers across the three different maps allowed direct comparisons of the positions of the detected QTL in a single consensus map. QTL meta-analysis was then used to identify interesting regions (metaQTL) where QTL for several traits co-localized. MetaQTL were compared with positions of candidate genes known to be involved in senescence processes and flowering time. Finally, investigation of the correlation between yield and seed N concentration in the three populations suggests that leaf senescence disrupts the negative correlation generally observed between these two traits.

A combined linkage and regional association mapping validation and fine mapping of two major pleiotropic QTLs for seed weight and silique length in rapeseed (Brassica napus L.)

BACKGROUND

Seed weight (SW) and silique length (SL) are important determinants of the yield potential in rapeseed (Brassica napus L.). However, the genetic basis of both traits is poorly understood. The main objectives of this study were to dissect the genetic basis of SW and SL in rapeseed through the preliminary mapping of quantitative trait locus (QTL) by linkage analysis and fine mapping of the target major QTL by regional association analysis.

RESULTS

Preliminary linkage mapping identified thirteen and nine consensus QTLs for SW and SL, respectively. These QTLs explained 0.7-67.1% and 2.1-54.4% of the phenotypic variance for SW and SL, respectively. Of these QTLs, three pairs of SW and SL QTLs were co-localized and integrated into three unique QTLs. In addition, the significance level and genetic effect of the three co-localized QTLs for both SW and SL showed great variation before and after the conditional analysis. Moreover, the allelic effects of the three QTLs for SW were highly consistent with those for SL. Two of the three co-localized QTLs, uq.A09-1 (mean R(2) = 20.1% and 19.0% for SW and SL, respectively) and uq.A09-3 (mean R(2) = 13.5% and 13.2% for SW and SL, respectively), were detected in all four environments and showed the opposite additive-effect direction. These QTLs were validated and fine mapped (their confidence intervals were narrowed down from 5.3 cM to 1 cM for uq.A09-1 and 13.2 cM to 2.5 cM for uq.A09-3) by regional association analysis with a panel of 576 inbred lines, which has a relatively rapid linkage disequilibrium decay (0.3 Mb) in the target QTL region.

CONCLUSIONS

A few QTLs with major effects and several QTLs with moderate effects might contribute to the natural variation of SW and SL in rapeseed. The meta-, conditional and allelic effect analyses suggested that pleiotropy, rather than tight linkage, was the genetic basis of the three pairs of co-localized of SW and SL QTLs. Regional association analysis was an effective and highly efficient strategy for the direct fine mapping of target major QTL identified by preliminary linkage mapping.

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

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

QTLs for seed vigor-related traits identified in maize seeds germinated under artificial aging conditions

High seed vigor is important for agricultural production due to the associated potential for increased growth and productivity. However, a better understanding of the underlying molecular mechanisms is required because the genetic basis for seed vigor remains unknown. We used single-nucleotide polymorphism (SNP) markers to map quantitative trait loci (QTLs) for four seed vigor traits in two connected recombinant inbred line (RIL) maize populations under four treatment conditions during seed germination. Sixty-five QTLs distributed between the two populations were identified and a meta-analysis was used to integrate genetic maps. Sixty-one initially identified QTLs were integrated into 18 meta-QTLs (mQTLs). Initial QTLs with contribution to phenotypic variation values of R²>10% were integrated into mQTLs. Twenty-three candidate genes for association with seed vigor traits coincided with 13 mQTLs. The candidate genes had functions in the glycolytic pathway and in protein metabolism. QTLs with major effects (R²>10%) were identified under at least one treatment condition for mQTL2, mQTL3-2, and mQTL3-4. Candidate genes included a calcium-dependent protein kinase gene (302810918) involved in signal transduction that mapped in the mQTL3-2 interval associated with germination energy (GE) and germination percentage (GP), and an hsp20/alpha crystallin family protein gene (At5g51440) that mapped in the mQTL3-4 interval associated with GE and GP. Two initial QTLs with a major effect under at least two treatment conditions were identified for mQTL5-2. A cucumisin-like Ser protease gene (At5g67360) mapped in the mQTL5-2 interval associated with GP. The chromosome regions for mQTL2, mQTL3-2, mQTL3-4, and mQTL5-2 may be hot spots for QTLs related to seed vigor traits. The mQTLs and candidate genes identified in this study provide valuable information for the identification of additional quantitative trait genes.

Meta-analysis and candidate gene mining of low-phosphorus tolerance in maize

Plants with tolerance to low-phosphorus (P) can grow better under low-P conditions, and understanding of genetic mechanisms of low-P tolerance can not only facilitate identifying relevant genes but also help to develop low-P tolerant cultivars. QTL meta-analysis was conducted after a comprehensive review of the reports on QTL mapping for low-P tolerance-related traits in maize. Meta-analysis produced 23 consensus QTL (cQTL), 17 of which located in similar chromosome regions to those previously reported to influence root traits. Meanwhile, candidate gene mining yielded 215 genes, 22 of which located in the cQTL regions. These 22 genes are homologous to 14 functionally characterized genes that were found to participate in plant low-P tolerance, including genes encoding miR399s, Pi transporters and purple acid phosphatases. Four cQTL loci (cQTL2-1, cQTL5-3, cQTL6-2, and cQTL10-2) may play important roles for low-P tolerance because each contains more original QTL and has better consistency across previous reports.

A negative MYB regulator of proanthocyanidin accumulation, identified through expression quantitative locus mapping in the grape berry

Flavonoids are secondary metabolites with multiple functions. In grape (Vitis vinifera), the most abundant flavonoids are proanthocyanidins (PAs), major quality determinants for fruit and wine. However, knowledge about the regulation of PA composition is sparse. Thus, we aimed to identify novel genomic regions involved in this mechanism. Expression quantitative trait locus (eQTL) mapping was performed on the transcript abundance of five downstream PA synthesis genes (dihydroflavonol reductase (VvDFR), leucoanthocyanidin dioxygenase (VvLDOX), leucoanthocyanidin reductase (VvLAR1), VvLAR2 and anthocyanidin reductase (VvANR)) measured by real-time quantitative PCR on a pseudo F1 population in two growing seasons. Twenty-one eQTLs were identified; 17 of them did not overlap with known candidate transcription factors or cis-regulatory sequences. These novel loci and the presence of digenic epistasis support the previous hypothesis of a polygenic regulatory mechanism for PA biosynthesis. In a genomic region co-locating eQTLs for VvDFR, VvLDOX and VvLAR1, gene annotation and a transcriptomic survey suggested that VvMYBC2-L1, a gene coding for an R2R3-MYB protein, is involved in regulating PA synthesis. Phylogenetic analysis showed its high similarity to characterized negative MYB factors. Its spatiotemporal expression profile in grape coincided with PA synthesis. Its functional characterization via overexpression in grapevine hairy roots demonstrated its ability to reduce the amount of PA and to down-regulate expression of PA genes.

Identification of QTLs associated with oil content in a high-oil Brassica napus cultivar and construction of a high-density consensus map for QTLs comparison in B. napus

Increasing seed oil content is one of the most important goals in breeding of rapeseed (B. napus L.). To dissect the genetic basis of oil content in B. napus, a large and new double haploid (DH) population containing 348 lines was obtained from a cross between 'KenC-8' and 'N53-2', two varieties with >10% difference in seed oil content, and this population was named the KN DH population. A genetic linkage map consisting of 403 markers was constructed, which covered a total length of 1783.9 cM with an average marker interval of 4.4 cM. The KN DH population was phenotyped in eight natural environments and subjected to quantitative trait loci (QTL) analysis for oil content. A total of 63 identified QTLs explaining 2.64-17.88% of the phenotypic variation were identified, and these QTLs were further integrated into 24 consensus QTLs located on 11 chromosomes using meta-analysis. A high-density consensus map with 1335 marker loci was constructed by combining the KN DH map with seven other published maps based on the common markers. Of the 24 consensus QTLs in the KN DH population, 14 were new QTLs including five new QTLs in A genome and nine in C genome. The analysis revealed that a larger population with significant differences in oil content gave a higher power detecting new QTLs for oil content, and the construction of the consensus map provided a new clue for comparing the QTLs detected in different populations. These findings enriched our knowledge of QTLs for oil content and should be a potential in marker-assisted breeding of B. napus.

A comprehensive meta QTL analysis for fiber quality, yield, yield related and morphological traits, drought tolerance, and disease resistance in tetraploid cotton

BACKGROUND

The study of quantitative trait loci (QTL) in cotton (Gossypium spp.) is focused on traits of agricultural significance. Previous studies have identified a plethora of QTL attributed to fiber quality, disease and pest resistance, branch number, seed quality and yield and yield related traits, drought tolerance, and morphological traits. However, results among these studies differed due to the use of different genetic populations, markers and marker densities, and testing environments. Since two previous meta-QTL analyses were performed on fiber traits, a number of papers on QTL mapping of fiber quality, yield traits, morphological traits, and disease resistance have been published. To obtain a better insight into the genome-wide distribution of QTL and to identify consistent QTL for marker assisted breeding in cotton, an updated comparative QTL analysis is needed.

RESULTS

In this study, a total of 1,223 QTL from 42 different QTL studies in Gossypium were surveyed and mapped using Biomercator V3 based on the Gossypium consensus map from the Cotton Marker Database. A meta-analysis was first performed using manual inference and confirmed by Biomercator V3 to identify possible QTL clusters and hotspots. QTL clusters are composed of QTL of various traits which are concentrated in a specific region on a chromosome, whereas hotspots are composed of only one trait type. QTL were not evenly distributed along the cotton genome and were concentrated in specific regions on each chromosome. QTL hotspots for fiber quality traits were found in the same regions as the clusters, indicating that clusters may also form hotspots.

CONCLUSIONS

Putative QTL clusters were identified via meta-analysis and will be useful for breeding programs and future studies involving Gossypium QTL. The presence of QTL clusters and hotspots indicates consensus regions across cultivated tetraploid Gossypium species, environments, and populations which contain large numbers of QTL, and in some cases multiple QTL associated with the same trait termed a hotspot. This study combines two previous meta-analysis studies and adds all other currently available QTL studies, making it the most comprehensive meta-analysis study in cotton to date.

Genetic basis of qualitative and quantitative resistance to powdery mildew in wheat: from consensus regions to candidate genes

Background

Powdery mildew (Blumeria graminis f. sp. tritici) is one of the most damaging diseases of wheat. The objective of this study was to identify the wheat genomic regions that are involved in the control of powdery mildew resistance through a quantitative trait loci (QTL) meta-analysis approach. This meta-analysis allows the use of collected QTL data from different published studies to obtain consensus QTL across different genetic backgrounds, thus providing a better definition of the regions responsible for the trait, and the possibility to obtain molecular markers that will be suitable for marker-assisted selection.

Results

Five QTL for resistance to powdery mildew were identified under field conditions in the durum-wheat segregating population Creso × Pedroso. An integrated map was developed for the projection of resistance genes/ alleles and the QTL from the present study and the literature, and to investigate their distribution in the wheat genome. Molecular markers that correspond to candidate genes for plant responses to pathogens were also projected onto the map, particularly considering NBS-LRR and receptor-like protein kinases. More than 80 independent QTL and 51 resistance genes from 62 different mapping populations were projected onto the consensus map using the Biomercator statistical software. Twenty-four MQTL that comprised 2–6 initial QTL that had widely varying confidence intervals were found on 15 chromosomes. The co-location of the resistance QTL and genes was investigated. Moreover, from analysis of the sequences of DArT markers, 28 DArT clones mapped on wheat chromosomes have been shown to be associated with the NBS-LRR genes and positioned in the same regions as the MQTL for powdery mildew resistance.

Conclusions

The results from the present study provide a detailed analysis of the genetic basis of resistance to powdery mildew in wheat. The study of the Creso × Pedroso durum-wheat population has revealed some QTL that had not been previously identified. Furthermore, the analysis of the co-localization of resistance loci and functional markers provides a large list of candidate genes and opens up a new perspective for the fine mapping and isolation of resistance genes, and for the marker-assisted improvement of resistance in wheat.

Evidence of Multiple Disease Resistance (MDR) and implication of meta-analysis in marker assisted selection

Meta-analysis was performed for three major foliar diseases with the aim to find out the total number of QTL responsible for these diseases and depict some real QTL for molecular breeding and marker assisted selection (MAS) in maize. Furthermore, we confirmed our results with some major known disease resistance genes and most well-known gene family of nucleotide binding site (NBS) encoding genes. Our analysis revealed that disease resistance QTL were randomly distributed in maize genome, but were clustered at different regions of the chromosomes. Totally 389 QTL were observed for these three major diseases in diverse maize germplasm, out of which 63 QTL were controlling more than one disease revealing the presence of multiple disease resistance (MDR). 44 real-QTLs were observed based on 4 QTL as standard in a specific region of genome. We also confirmed the Ht1 and Ht2 genes within the region of real QTL and 14 NBS-encoding genes. On chromosome 8 two NBS genes in one QTL were observed and on chromosome 3, several cluster and maximum MDR QTL were observed indicating that the apparent clustering could be due to genes exhibiting pleiotropic effect. Significant relationship was observed between the number of disease QTL and total genes per chromosome based on the reference genome B73. Therefore, we concluded that disease resistance genes are abundant in maize genome and these results can unleash the phenomenon of MDR. Furthermore, these results could be very handy to focus on hot spot on different chromosome for fine mapping of disease resistance genes and MAS.

Meta-analyses of QTL for grain yield and anthesis silking interval in 18 maize populations evaluated under water-stressed and well-watered environments

BACKGROUND

Identification of QTL with large phenotypic effects conserved across genetic backgrounds and environments is one of the prerequisites for crop improvement using marker assisted selection (MAS). The objectives of this study were to identify meta-QTL (mQTL) for grain yield (GY) and anthesis silking interval (ASI) across 18 bi-parental maize populations evaluated in the same conditions across 2-4 managed water stressed and 3-4 well watered environments.

RESULTS

The meta-analyses identified 68 mQTL (9 QTL specific to ASI, 15 specific to GY, and 44 for both GY and ASI). Mean phenotypic variance explained by each mQTL varied from 1.2 to 13.1% and the overall average was 6.5%. Few QTL were detected under both environmental treatments and/or multiple (>4 populations) genetic backgrounds. The number and 95% genetic and physical confidence intervals of the mQTL were highly reduced compared to the QTL identified in the original studies. Each physical interval of the mQTL consisted of 5 to 926 candidate genes.

CONCLUSIONS

Meta-analyses reduced the number of QTL by 68% and narrowed the confidence intervals up to 12-fold. At least the 4 mQTL (mQTL2.2, mQTL6.1, mQTL7.5 and mQTL9.2) associated with GY under both water-stressed and well-watered environments and detected up to 6 populations may be considered for fine mapping and validation to confirm effects in different genetic backgrounds and pyramid them into new drought resistant breeding lines. This is the first extensive report on meta-analysis of data from over 3100 individuals genotyped using the same SNP platform and evaluated in the same conditions across a wide range of managed water-stressed and well-watered environments.

Combined linkage and association mapping of flowering time in Sunflower (Helianthus annuus L.)

Association mapping and linkage mapping were used to identify quantitative trait loci (QTL) and/or causative mutations involved in the control of flowering time in cultivated sunflower Helianthus annuus. A panel of 384 inbred lines was phenotyped through testcrosses with two tester inbred lines across 15 location × year combinations. A recombinant inbred line (RIL) population comprising 273 lines was phenotyped both per se and through testcrosses with one or two testers in 16 location × year combinations. In the association mapping approach, kinship estimation using 5,923 single nucleotide polymorphisms was found to be the best covariate to correct for effects of panel structure. Linkage disequilibrium decay ranged from 0.08 to 0.26 cM for a threshold of 0.20, after correcting for structure effects, depending on the linkage group (LG) and the ancestry of inbred lines. A possible hitchhiking effect is hypothesized for LG10 and LG08. A total of 11 regions across 10 LGs were found to be associated with flowering time, and QTLs were mapped on 11 LGs in the RIL population. Whereas eight regions were demonstrated to be common between the two approaches, the linkage disequilibrium approach did not detect a documented QTL that was confirmed using the linkage mapping approach.

QTL meta-analysis provides a comprehensive view of loci controlling partial resistance to Aphanomyces euteiches in four sources of resistance in pea

BACKGROUND

Development of durable plant genetic resistance to pathogens through strategies of QTL pyramiding and diversification requires in depth knowledge of polygenic resistance within the available germplasm. Polygenic partial resistance to Aphanomyces root rot, caused by Aphanomyces euteiches, one of the most damaging pathogens of pea worldwide, was previously dissected in individual mapping populations. However, there are no data available regarding the diversity of the resistance QTL across a broader collection of pea germplasm. In this study, we performed a meta-analysis of Aphanomyces root rot resistance QTL in the four main sources of resistance in pea and compared their genomic localization with genes/QTL controlling morphological or phenological traits and with putative candidate genes.

RESULTS

Meta-analysis, conducted using 244 individual QTL reported previously in three mapping populations (Puget x 90-2079, Baccara x PI180693 and Baccara x 552) and in a fourth mapping population in this study (DSP x 90-2131), resulted in the identification of 27 meta-QTL for resistance to A. euteiches. Confidence intervals of meta-QTL were, on average, reduced four-fold compared to mean confidence intervals of individual QTL. Eleven consistent meta-QTL, which highlight seven highly consistent genomic regions, were identified. Few meta-QTL specificities were observed among mapping populations, suggesting that sources of resistance are not independent. Seven resistance meta-QTL, including six of the highly consistent genomic regions, co-localized with six of the meta-QTL identified in this study for earliness and plant height and with three morphological genes (Af, A, R). Alleles contributing to the resistance were often associated with undesirable alleles for dry pea breeding. Candidate genes underlying six main meta-QTL regions were identified using colinearity between the pea and Medicago truncatula genomes.

CONCLUSIONS

QTL meta-analysis provided an overview of the moderately low diversity of loci controlling partial resistance to A. euteiches in four main sources of resistance in pea. Seven highly consistent genomic regions with potential use in marker-assisted-selection were identified. Confidence intervals at several main QTL regions were reduced and co-segregation among resistance and morphological/phenological alleles was identified. Further work will be required to identify the best combinations of QTL for durably increasing partial resistance to A. euteiches.

High-density SNP-based genetic map development and linkage disequilibrium assessment in Brassica napus L

Background

High density genetic maps built with SNP markers that are polymorphic in various genetic backgrounds are very useful for studying the genetics of agronomical traits as well as genome organization and evolution. Simultaneous dense SNP genotyping of segregating populations and variety collections was applied to oilseed rape (Brassica napus L.) to obtain a high density genetic map for this species and to study the linkage disequilibrium pattern.

Results

We developed an integrated genetic map for oilseed rape by high throughput SNP genotyping of four segregating doubled haploid populations. A very high level of collinearity was observed between the four individual maps and a large number of markers (>59%) was common to more than two maps. The precise integrated map comprises 5764 SNP and 1603 PCR markers. With a total genetic length of 2250 cM, the integrated map contains a density of 3.27 markers (2.56 SNP) per cM. Genotyping of these mapped SNP markers in oilseed rape collections allowed polymorphism level and linkage disequilibrium (LD) to be studied across the different collections (winter vs spring, different seed quality types) and along the linkage groups. Overall, polymorphism level was higher and LD decayed faster in spring than in “00” winter oilseed rape types but this was shown to vary greatly along the linkage groups.

Conclusions

Our study provides a valuable resource for further genetic studies using linkage or association mapping, for marker assisted breeding and for Brassica napus sequence assembly and genome organization analyses.

QTL detection for forage quality and stem histology in four connected mapping populations of the model legume Medicago truncatula

Forage quality combines traits related to protein content and energy value. High-quality forages contribute to increase farm autonomy by reducing the use of energy or protein-rich supplements. Genetic analyses in forage legume species are complex because of their tetraploidy and allogamy. Indeed, no genetic studies of quality have been published at the molecular level on these species. Nonetheless, mapping populations of the model species M. truncatula can be used to detect QTL for forage quality. Here, we studied a crossing design involving four connected populations of M. truncatula. Each population was composed of ca. 200 recombinant inbred lines (RIL). We sought population-specific QTL and QTL explaining the whole design variation. We grew parents and RIL in a greenhouse for 2 or 3 seasons and analysed plants for chemical composition of vegetative organs (protein content, digestibility, leaf-to-stem ratio) and stem histology (stem cross-section area, tissue proportions). Over the four populations and all the traits, QTL were found on all chromosomes. Among these QTL, only four genomic regions, on chromosomes 1, 3, 7 and 8, contributed to explaining the variations in the whole crossing design. Surprisingly, we found that quality QTL were located in the same genomic regions as morphological QTL. We thus confirmed the quantitative inheritance of quality traits and tight relationships between quality and morphology. Our findings could be explained by a co-location of genes involved in quality and morphology. This study will help to detect candidate genes involved in quantitative variation for quality in forage legume species.

Verification of QTL for grain starch content and its genetic correlation with oil content using two connected RIL populations in high-oil maize

Grain oil content is negatively correlated with starch content in maize in general. In this study, 282 and 263 recombinant inbred lines (RIL) developed from two crosses between one high-oil maize inbred and two normal dent maize inbreds were evaluated for grain starch content and its correlation with oil content under four environments. Single-trait QTL for starch content in single-population and joint-population analysis, and multiple-trait QTL for both starch and oil content were detected, and compared with the result obtained in the two related F(2∶3) populations. Totally, 20 single-population QTL for grain starch content were detected. No QTL was simultaneously detected across all ten cases. QTL at bins 5.03 and 9.03 were all detected in both populations and in 4 and 5 cases, respectively. Only 2 of the 16 joint-population QTL had significant effects in both populations. Three single-population QTL and 8 joint-population QTL at bins 1.03, 1.04-1.05, 3.05, 8.04-8.05, 9.03, and 9.05 could be considered as fine-mapped. Common QTL across F(2∶3) and RIL generations were observed at bins 5.04, 8.04 and 8.05 in population 1 (Pop.1), and at bin 5.03 in population 2 (Pop.2). QTL at bins 3.02-3.03, 3.05, 8.04-8.05 and 9.03 should be focused in high-starch maize breeding. In multiple-trait QTL analysis, 17 starch-oil QTL were detected, 10 in Pop.1 and 7 in Pop.2. And 22 single-trait QTL failed to show significance in multiple-trait analysis, 13 QTL for starch content and 9 QTL for oil content. However, QTL at bins 1.03, 6.03-6.04 and 8.03-8.04 might increase grain starch content and/or grain oil content without reduction in another trait. Further research should be conducted to validate the effect of these QTL in the simultaneous improvement of grain starch and oil content in maize.

Comparative mapping in watermelon [Citrullus lanatus (Thunb.) Matsum. et Nakai]

The first single-nucleotide polymorphism (SNP) maps for watermelon [Citrullus lanatus (Thunb.) Matsum. et Nakai] were constructed and compared. Three populations were developed from crosses between two elite cultivars, Klondike Black Seeded × New Hampshire Midget (KBS × NHM), an elite cultivar and wild egusi accession, Strain II × PI 560023 (SII × Egusi) and an elite cultivar and a wild citron accession, ZWRM50 × PI 244019 (ZWRM × Citroides). The SII × Egusi and ZWRM × Citroides F(2) populations consisted of 187 and 182 individuals respectively while the KBS × NHM recombinant inbred line (RIL) population consisted of 164 lines. The length of the genetic maps were 1,438, 1,514 and 1,144 cM with average marker distances of 3.8, 4.2, and 3.4 cM for the KBS × NHM, SII × Egusi and ZWRM × Citroides populations, respectively. Shared markers were used to align the three maps so that the linkage groups (LGs) represented the 11 chromosomes of the species. Marker segregation distortion were observed in all three populations, but was highest (12.7 %) in the ZWRM × Citroides population, where Citroides alleles were favored. The three maps were used to construct a consensus map containing 378 SNP markers with an average distance of 5.1 cM between markers. Phenotypic data was collected for fruit weight (FWT), fruit length (FL), fruit width (FWD), fruit shape index (FSI), rind thickness (RTH) and Brix (BRX) and analyzed for quantitative trait loci (QTL) associated with these traits. A total of 40 QTL were identified in the three populations, including major QTL for fruit size and shape that were stable across genetic backgrounds and environments. The present study reports the first SNP maps for Citrullus and the first map constructed using two elite parents. We also report the first stable QTL associated with fruit size and shape in Citrullus lanatus. These maps, QTL and SNPs should be useful for the watermelon community and represent a significant step towards the potential use of molecular tools in watermelon breeding.

Genetic analysis of phytosterol content in sunflower seeds

Interest in phytosterol contents due to their potential benefits for human health has been largely documented in several crop species. Studies were focused mainly on total sterol content and their concentration or distribution in seed. This study aimed at providing new insight into the genetic control of total and individual sterol contents in sunflower seed through QTL analyses in a RIL population characterized over 2 years showing contrasted rainfall during seed filling. Results indicated that 13 regions on 9 linkage groups were involved in different phytosterol traits. Most of the QTL mapped were stable across years in spite of contrasted growing conditions. Some of them explained up to 30 % of phenotypic variation. Two QTL, located on LG10, near b1, and on LG14, were found to co-localize with QTL for oil content, indicating that likely, a part of the genetic variation for sterol content is only the result of genetic variation for oil content. However, three other QTL, stable over the 2 years, were found on LG1, LG4 and LG7 each associated with a particular class of sterols, suggesting that some enzymes known to be involved in the sterol metabolic pathway may determine the specificity of sterol profiles in sunflower seeds. These results suggest that it may be possible to introduce these traits as criteria in breeding programmes for quality in sunflower. The molecular markers linked to genetic factors controlling phytosterol contents could help selection during breeding programs.

Unraveling the genetic basis of seed tocopherol content and composition in rapeseed (Brassica napus L.)

BACKGROUND

Tocopherols are important antioxidants in vegetable oils; when present as vitamin E, tocopherols are an essential nutrient for humans and livestock. Rapeseed (Brassica napus L, AACC, 2 n = 38) is one of the most important oil crops and a major source of tocopherols. Although the tocopherol biosynthetic pathway has been well elucidated in the model photosynthetic organisms Arabidopsis thaliana and Synechocystis sp. PCC6803, knowledge about the genetic basis of tocopherol biosynthesis in seeds of rapeseed is scant. This project was carried out to dissect the genetic basis of seed tocopherol content and composition in rapeseed through quantitative trait loci (QTL) detection, genome-wide association analysis, and homologous gene mapping.

METHODOLOGY/PRINCIPAL FINDINGS

We used a segregating Tapidor × Ningyou7 doubled haploid (TNDH) population, its reconstructed F(2) (RC-F(2)) population, and a panel of 142 rapeseed accessions (association panel). Genetic effects mainly contributed to phenotypic variations in tocopherol content and composition; environmental effects were also identified. Thirty-three unique QTL were detected for tocopherol content and composition in TNDH and RC-F(2) populations. Of these, seven QTL co-localized with candidate sequences associated with tocopherol biosynthesis through in silico and linkage mapping. Several near-isogenic lines carrying introgressions from the parent with higher tocopherol content showed highly increased tocopherol content compared with the recurrent parent. Genome-wide association analysis was performed with 142 B. napus accessions. Sixty-one loci were significantly associated with tocopherol content and composition, 11 of which were localized within the confidence intervals of tocopherol QTL.

CONCLUSIONS/SIGNIFICANCE

This joint QTL, candidate gene, and association mapping study sheds light on the genetic basis of seed tocopherol biosynthesis in rapeseed. The sequences presented here may be used for marker-assisted selection of oilseed rape lines with superior tocopherol content and composition.

Quantitative Trait Locus (QTL) meta-analysis and comparative genomics for candidate gene prediction in perennial ryegrass (Lolium perenne L.)

BACKGROUND

In crop species, QTL analysis is commonly used for identification of factors contributing to variation of agronomically important traits. As an important pasture species, a large number of QTLs have been reported for perennial ryegrass based on analysis of biparental mapping populations. Further characterisation of those QTLs is, however, essential for utilisation in varietal improvement programs.

RESULTS

A bibliographic survey of perennial ryegrass trait-dissection studies identified a total of 560 QTLs from previously published papers, of which 189, 270 and 101 were classified as morphology-, physiology- and resistance/tolerance-related loci, respectively. The collected dataset permitted a subsequent meta-QTL study and implementation of a cross-species candidate gene identification approach. A meta-QTL analysis based on use of the BioMercator software was performed to identify two consensus regions for pathogen resistance traits. Genes that are candidates for causal polymorphism underpinning perennial ryegrass QTLs were identified through in silico comparative mapping using rice databases, and 7 genes were assigned to the p150/112 reference map. Markers linked to the LpDGL1, LpPh1 and LpPIPK1 genes were located close to plant size, leaf extension time and heading date-related QTLs, respectively, suggesting that these genes may be functionally associated with important agronomic traits in perennial ryegrass.

CONCLUSIONS

Functional markers are valuable for QTL meta-analysis and comparative genomics. Enrichment of such genetic markers may permit further detailed characterisation of QTLs. The outcomes of QTL meta-analysis and comparative genomics studies may be useful for accelerated development of novel perennial ryegrass cultivars with desirable traits.

Family-based linkage and association mapping reveals novel genes affecting Plum pox virus infection in Arabidopsis thaliana

Sharka is a devastating viral disease caused by the Plum pox virus (PPV) in stone fruit trees and few sources of resistance are known in its natural hosts. Since any knowledge gained from Arabidopsis on plant virus susceptibility factors is likely to be transferable to crop species, Arabidopsis's natural variation was searched for host factors essential for PPV infection. To locate regions of the genome associated with susceptibility to PPV, linkage analysis was performed on six biparental populations as well as on multiparental lines. To refine quantitative trait locus (QTL) mapping, a genome-wide association analysis was carried out using 147 Arabidopsis accessions. Evidence was found for linkage on chromosomes 1, 3 and 5 with restriction of PPV long-distance movement. The most relevant signals occurred within a region at the bottom of chromosome 3, which comprises seven RTM3-like TRAF domain-containing genes. Since the resistance mechanism analyzed here is recessive and the rtm3 knockout mutant is susceptible to PPV infection, it suggests that other gene(s) present in the small identified region encompassing RTM3 are necessary for PPV long-distance movement. In consequence, we report here the occurrence of host factor(s) that are indispensable for virus long-distance movement.

QTL mapping of yield-associated traits in Brassica juncea: meta-analysis and epistatic interactions using two different crosses between east European and Indian gene pool lines

Genetic analysis of 12 yield-associated traits was undertaken by dissection of quantitative trait loci (QTL) through meta-analysis and epistatic interaction studies in Brassica juncea. A consensus (integrated) map in B. juncea was constructed using two maps. These were VH map, developed earlier in the laboratory by using a DH population from the cross between Varuna and Heera (Pradhan et al. in Theor Appl Genet 106:607-614, 2003; Ramchiary et al. in Theor Appl Genet. 115:807-817, 2007; Panjabi et al. in BMC Genomics 9:113, 2008), and the TD map, developed in the present study using a DH population of 100 lines from the cross between TM-4 and Donskaja-IV. The TD map was constructed with 911 markers consisting of 585 AFLP, 8 SSR and 318 IP markers covering a total genome length of 1,629.9 cM. The consensus map constructed by using the common markers between the two maps contained a total of 2,662 markers and covered a total genome length of 1,927.1 cM. Firstly, QTL analysis of 12 yield-associated traits was undertaken for the TD population based on three-environment phenotypic data. Secondly, the three-environment phenotypic data for the same 12 quantitative traits generated by Ramchiary et al. (2007) were re-analyzed for the QTL detection in the VH map. Comparative analysis identified both common and population-specific QTL. The study revealed the presence of QTL clusters on LG A7, A8 and A10 in both TD and VH maps. Meta-analyses resolved 187 QTL distributed over nine linkage groups of TD and VH maps into 20 meta-QTL. Maximum resolution was recorded for the LG A10 wherein all the 54 QTL were mapped to a single meta-QTL within a confidence interval of 3.0 cM. Digenic epistatic interactions of QTL in both TD and VH maps revealed substantial additive × additive interactions showing a higher frequency of Type 1 and Type 2 interactions than Type 3 interactions. Some of the loci interacted with more than one locus indicating the presence of higher order epistatic interactions. These findings provided some detailed insight into the genetic architecture of the yield-associated traits in B. juncea.

Toward allotetraploid cotton genome assembly: integration of a high-density molecular genetic linkage map with DNA sequence information

Background

Cotton is the world’s most important natural textile fiber and a significant oilseed crop. Decoding cotton genomes will provide the ultimate reference and resource for research and utilization of the species. Integration of high-density genetic maps with genomic sequence information will largely accelerate the process of whole-genome assembly in cotton.

Results

In this paper, we update a high-density interspecific genetic linkage map of allotetraploid cultivated cotton. An additional 1,167 marker loci have been added to our previously published map of 2,247 loci. Three new marker types, InDel (insertion-deletion) and SNP (single nucleotide polymorphism) developed from gene information, and REMAP (retrotransposon-microsatellite amplified polymorphism), were used to increase map density. The updated map consists of 3,414 loci in 26 linkage groups covering 3,667.62 cM with an average inter-locus distance of 1.08 cM. Furthermore, genome-wide sequence analysis was finished using 3,324 informative sequence-based markers and publicly-available Gossypium DNA sequence information. A total of 413,113 EST and 195 BAC sequences were physically anchored and clustered by 3,324 sequence-based markers. Of these, 14,243 ESTs and 188 BACs from different species of Gossypium were clustered and specifically anchored to the high-density genetic map. A total of 2,748 candidate unigenes from 2,111 ESTs clusters and 63 BACs were mined for functional annotation and classification. The 337 ESTs/genes related to fiber quality traits were integrated with 132 previously reported cotton fiber quality quantitative trait loci, which demonstrated the important roles in fiber quality of these genes. Higher-level sequence conservation between different cotton species and between the A- and D-subgenomes in tetraploid cotton was found, indicating a common evolutionary origin for orthologous and paralogous loci in Gossypium.

Conclusion

This study will serve as a valuable genomic resource for tetraploid cotton genome assembly, for cloning genes related to superior agronomic traits, and for further comparative genomic analyses in Gossypium.

A high density consensus genetic map of tetraploid cotton that integrates multiple component maps through molecular marker redundancy check

A consensus genetic map of tetraploid cotton was constructed using six high-density maps and after the integration of a sequence-based marker redundancy check. Public cotton SSR libraries (17,343 markers) were curated for sequence redundancy using 90% as a similarity cutoff. As a result, 20% of the markers (3,410) could be considered as redundant with some other markers. The marker redundancy information had been a crucial part of the map integration process, in which the six most informative interspecific Gossypium hirsutum×G. barbadense genetic maps were used for assembling a high density consensus (HDC) map for tetraploid cotton. With redundant markers being removed, the HDC map could be constructed thanks to the sufficient number of collinear non-redundant markers in common between the component maps. The HDC map consists of 8,254 loci, originating from 6,669 markers, and spans 4,070 cM, with an average of 2 loci per cM. The HDC map presents a high rate of locus duplications, as 1,292 markers among the 6,669 were mapped in more than one locus. Two thirds of the duplications are bridging homoeologous A(T) and D(T) chromosomes constitutive of allopolyploid cotton genome, with an average of 64 duplications per A(T)/D(T) chromosome pair. Sequences of 4,744 mapped markers were used for a mutual blast alignment (BBMH) with the 13 major scaffolds of the recently released Gossypium raimondii genome indicating high level of homology between the diploid D genome and the tetraploid cotton genetic map, with only a few minor possible structural rearrangements. Overall, the HDC map will serve as a valuable resource for trait QTL comparative mapping, map-based cloning of important genes, and better understanding of the genome structure and evolution of tetraploid cotton.

Dissecting quantitative trait loci for boron efficiency across multiple environments in Brassica napus

High yield is the most important goal in crop breeding, and boron (B) is an essential micronutrient for plants. However, B deficiency, leading to yield decreases, is an agricultural problem worldwide. Brassica napus is one of the most sensitive crops to B deficiency, and considerable genotypic variation exists among different cultivars in response to B deficiency. To dissect the genetic basis of tolerance to B deficiency in B. napus, we carried out QTL analysis for seed yield and yield-related traits under low and normal B conditions using the double haploid population (TNDH) by two-year and the BQDH population by three-year field trials. In total, 80 putative QTLs and 42 epistatic interactions for seed yield, plant height, branch number, pod number, seed number, seed weight and B efficiency coefficient (BEC) were identified under low and normal B conditions, singly explaining 4.15-23.16% and 0.53-14.38% of the phenotypic variation. An additive effect of putative QTLs was a more important controlling factor than the additive-additive effect of epistatic interactions. Four QTL-by-environment interactions and 7 interactions between epistatic interactions and the environment contributed to 1.27-4.95% and 1.17-3.68% of the phenotypic variation, respectively. The chromosome region on A2 of SYLB-A2 for seed yield under low B condition and BEC-A2 for BEC in the two populations was equivalent to the region of a reported major QTL, BE1. The B. napus homologous genes of Bra020592 and Bra020595 mapped to the A2 region and were speculated to be candidate genes for B efficiency. These findings reveal the complex genetic basis of B efficiency in B. napus. They provide a basis for the fine mapping and cloning of the B efficiency genes and for breeding B-efficient cultivars by marker-assisted selection (MAS).

Consensus mapping of major resistance genes and independent QTL for quantitative resistance to sunflower downy mildew

Major gene resistance to sunflower downy mildew (Plasmopara halstedii) races 304 and 314 was found to segregate independently from the resistance to races 334, 307 and 304 determined by the gene Pl2, already positioned on Linkage Group (LG) 8 of sunflower molecular maps. Using a consensus SSR-SNP map constructed from the INEDI RIL population and a new RIL population FU × PAZ2, the positions of Pl2 and Pl5 were confirmed and the new gene, denoted Pl21, was mapped on LG13, at 8 cM from Pl5. The two RIL populations were observed for their quantitative resistance to downy mildew in the field and both indicated the existence of a QTL on LG8 at 20-40 cM from the major resistance gene cluster. In addition, for the INEDI population, a strong QTL on LG10, reported previously, was confirmed and a third QTL was mapped on LG7. A growth chamber test methodology, significantly correlated with field results, also revealed the major QTL on LG10, explaining 65 % of variability. This QTL mapped in the same area as a gene involved in stomatal opening and root growth, which may be suggested as a possible candidate to explain the control of this character. These results indicate that it should be possible to combine major genes and other resistance mechanisms, a strategy that could help to improve durability of sunflower resistance to downy mildew.