High throughput genotyping of structural variations in a complex plant genome using an original Affymetrix® axiom® array

Background

Insertions/deletions (InDels) and more specifically presence/absence variations (PAVs) are pervasive in several species and have strong functional and phenotypic effect by removing or drastically modifying genes. Genotyping of such variants on large panels remains poorly addressed, while necessary for approaches such as association mapping or genomic selection.

Results

We have developed, as a proof of concept, a new high-throughput and affordable approach to genotype InDels. We first identified 141,000 InDels by aligning reads from the B73 line against the genome of three temperate maize inbred lines (F2, PH207, and C103) and reciprocally. Next, we designed an Affymetrix® Axiom® array to target these InDels, with a combination of probes selected at breakpoint sites (13%) or within the InDel sequence, either at polymorphic (25%) or non-polymorphic sites (63%) sites. The final array design is composed of 662,772 probes and targets 105,927 InDels, including PAVs ranging from 35 bp to 129kbp. After Affymetrix® quality control, we successfully genotyped 86,648 polymorphic InDels (82% of all InDels interrogated by the array) on 445 maize DNA samples with 422,369 probes. Genotyping InDels using this approach produced a highly reliable dataset, with low genotyping error (~ 3%), high call rate (~ 98%), and high reproducibility (> 95%). This reliability can be further increased by combining genotyping of several probes calling the same InDels (< 0.1% error rate and > 99.9% of call rate for 5 probes). This “proof of concept” tool was used to estimate the kinship matrix between 362 maize lines with 57,824 polymorphic InDels. This InDels kinship matrix was highly correlated with kinship estimated using SNPs from Illumina 50 K SNP arrays.

Conclusions

We efficiently genotyped thousands of small to large InDels on a sizeable number of individuals using a new Affymetrix® Axiom® array. This powerful approach opens the way to studying the contribution of InDels to trait variation and heterosis in maize. The approach is easily extendable to other species and should contribute to decipher the biological impact of InDels at a larger scale.

SNP discovery and genetic mapping using genotyping by sequencing of whole genome genomic DNA from a pea RIL population

BACKGROUND

Progress in genetics and breeding in pea still suffers from the limited availability of molecular resources. SNP markers that can be identified through affordable sequencing processes, without the need for prior genome reduction or a reference genome to assemble sequencing data would allow the discovery and genetic mapping of thousands of molecular markers. Such an approach could significantly speed up genetic studies and marker assisted breeding for non-model species.

RESULTS

A total of 419,024 SNPs were discovered using HiSeq whole genome sequencing of four pea lines, followed by direct identification of SNP markers without assembly using the discoSnp tool. Subsequent filtering led to the identification of 131,850 highly designable SNPs, polymorphic between at least two of the four pea lines. A subset of 64,754 SNPs was called and genotyped by short read sequencing on a subpopulation of 48 RILs from the cross 'Baccara' x 'PI180693'. This data was used to construct a WGGBS-derived pea genetic map comprising 64,263 markers. This map is collinear with previous pea consensus maps and therefore with the Medicago truncatula genome. Sequencing of four additional pea lines showed that 33 % to 64 % of the mapped SNPs, depending on the pairs of lines considered, are polymorphic and can therefore be useful in other crosses. The subsequent genotyping of a subset of 1000 SNPs, chosen for their mapping positions using a KASP™ assay, showed that almost all generated SNPs are highly designable and that most (95 %) deliver highly qualitative genotyping results. Using rather low sequencing coverages in SNP discovery and in SNP inferring did not hinder the identification of hundreds of thousands of high quality SNPs.

CONCLUSIONS

The development and optimization of appropriate tools in SNP discovery and genetic mapping have allowed us to make available a massive new genomic resource in pea. It will be useful for both fine mapping within chosen QTL confidence intervals and marker assisted breeding for important traits in pea improvement.

QTL analysis of frost damage in pea suggests different mechanisms involved in frost tolerance

KEY MESSAGE

Avoidance mechanisms and intrinsic resistance are complementary strategies to improve winter frost tolerance and yield potential in field pea. The development of the winter pea crop represents a major challenge to expand plant protein production in temperate areas. Breeding winter cultivars requires the combination of freezing tolerance as well as high seed productivity and quality. In this context, we investigated the genetic determinism of winter frost tolerance and assessed its genetic relationship with yield and developmental traits. Using a newly identified source of frost resistance, we developed a population of recombinant inbred lines and evaluated it in six environments in Dijon and Clermont-Ferrand between 2005 and 2010. We developed a genetic map comprising 679 markers distributed over seven linkage groups and covering 947.1 cM. One hundred sixty-one quantitative trait loci (QTL) explaining 9-71 % of the phenotypic variation were detected across the six environments for all traits measured. Two clusters of QTL mapped on the linkage groups III and one cluster on LGVI reveal the genetic links between phenology, morphology, yield-related traits and frost tolerance in winter pea. QTL clusters on LGIII highlighted major developmental gene loci (Hr and Le) and the QTL cluster on LGVI explained up to 71 % of the winter frost damage variation. This suggests that a specific architecture and flowering ideotype defines frost tolerance in winter pea. However, two consistent frost tolerance QTL on LGV were independent of phenology and morphology traits, showing that different protective mechanisms are involved in frost tolerance. Finally, these results suggest that frost tolerance can be bred independently to seed productivity and quality.

Transcriptome sequencing for high throughput SNP development and genetic mapping in Pea

BACKGROUND

Pea has a complex genome of 4.3 Gb for which only limited genomic resources are available to date. Although SNP markers are now highly valuable for research and modern breeding, only a few are described and used in pea for genetic diversity and linkage analysis.

RESULTS

We developed a large resource by cDNA sequencing of 8 genotypes representative of modern breeding material using the Roche 454 technology, combining both long reads (400 bp) and high coverage (3.8 million reads, reaching a total of 1,369 megabases). Sequencing data were assembled and generated a 68 K unigene set, from which 41 K were annotated from their best blast hit against the model species Medicago truncatula. Annotated contigs showed an even distribution along M. truncatula pseudochromosomes, suggesting a good representation of the pea genome. 10 K pea contigs were found to be polymorphic among the genetic material surveyed, corresponding to 35 K SNPs.We validated a subset of 1538 SNPs through the GoldenGate assay, proving their ability to structure a diversity panel of breeding germplasm. Among them, 1340 were genetically mapped and used to build a new consensus map comprising a total of 2070 markers. Based on blast analysis, we could establish 1252 bridges between our pea consensus map and the pseudochromosomes of M. truncatula, which provides new insight on synteny between the two species.

CONCLUSIONS

Our approach created significant new resources in pea, i.e. the most comprehensive genetic map to date tightly linked to the model species M. truncatula and a large SNP resource for both academic research and breeding.

Combining gene expression and genetic analyses to identify candidate genes involved in cold responses in pea

Cold stress affects plant growth and development. In order to better understand the responses to cold (chilling or freezing tolerance), we used two contrasted pea lines. Following a chilling period, the Champagne line becomes tolerant to frost whereas the Terese line remains sensitive. Four suppression subtractive hybridisation libraries were obtained using mRNAs isolated from pea genotypes Champagne and Terese. Using quantitative polymerase chain reaction (qPCR) performed on 159 genes, 43 and 54 genes were identified as differentially expressed at the initial time point and during the time course study, respectively. Molecular markers were developed from the differentially expressed genes and were genotyped on a population of 164 RILs derived from a cross between Champagne and Terese. We identified 5 candidate genes colocalizing with 3 different frost damage quantitative trait loci (QTL) intervals and a protein quantity locus (PQL) rich region previously reported. This investigation revealed the role of constitutive differences between both genotypes in the cold responses, in particular with genes related to glycine degradation pathway that could confer to Champagne a better frost tolerance. We showed that freezing tolerance involves a decrease of expression of genes related to photosynthesis and the expression of a gene involved in the production of cysteine and methionine that could act as cryoprotectant molecules. Although it remains to be confirmed, this study could also reveal the involvement of the jasmonate pathway in the cold responses, since we observed that two genes related to this pathway were mapped in a frost damage QTL interval and in a PQL rich region interval, respectively.

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.

Experiments and 3D simulations of flow structures in junctions and their influence on location of flowmeters

Open-channel junctions are common occurrences in sewer networks and flow rate measurement often occurs near these singularities. Local flow structures are 3D, impact on the representativeness of the local flow measurements and thus lead to deviations in the flow rate estimation. The present study aims (i) to measure and simulate the flow pattern in a junction flow, (ii) to analyse the impact of the junction on the velocity distribution according to the distance from the junction and thus (iii) to evaluate the typical error derived from the computation of the flow rate close to the junction.

Cross-genome map based dissection of a nitrogen use efficiency ortho-metaQTL in bread wheat unravels concerted cereal genome evolution

Monitoring nitrogen use efficiency (NUE) in plants is becoming essential to maintain yield while reducing fertilizer usage. Optimized NUE application in major crops is essential for long-term sustainability of agriculture production. Here, we report the precise identification of 11 major chromosomal regions controlling NUE in wheat that co-localise with key developmental genes such as Ppd (photoperiod sensitivity), Vrn (vernalization requirement), Rht (reduced height) and can be considered as robust markers from a molecular breeding perspective. Physical mapping, sequencing, annotation and candidate gene validation of an NUE metaQTL on wheat chromosome 3B allowed us to propose that a glutamate synthase (GoGAT) gene that is conserved structurally and functionally at orthologous positions in rice, sorghum and maize genomes may contribute to NUE in wheat and other cereals. We propose an evolutionary model for the NUE locus in cereals from a common ancestral region, involving species specific shuffling events such as gene deletion, inversion, transposition and the invasion of repetitive elements.

Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray

BACKGROUND

Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax.

RESULTS

Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties.

CONCLUSION

All results suggest that our high-density flax oligo-microarray platform can be used as a very sensitive tool for analyzing gene expression in a large variety of tissues as well as in different cultivars. Moreover, this highly reliable platform can also be used for the quantification of mRNA transcriptional profiling in different flax tissues.

Nitric oxide participates in the complex interplay of defense-related signaling pathways controlling disease resistance to Sclerotinia sclerotiorum in Arabidopsis thaliana

Studies of the interaction between Arabidopsis thaliana and the necrotrophic fungal pathogen Sclerotinia sclerotiorum have been hampered by the extreme susceptibility of this model plant to the fungus. In addition, analyses of the plant defense response suggested the implication of a complex interplay of hormonal and signaling pathways. To get a deeper insight into this host-pathogen interaction, we first analyzed the natural variation in Arabidopsis for resistance to S. sclerotiorum. The results revealed a large variation of resistance and susceptibility in Arabidopsis, with some ecotypes, such as Ws-4, Col-0, and Rbz-1, being strongly resistant, and others, such as Shahdara, Ita-0, and Cvi-0, exhibiting an extreme susceptibility. The role of different signaling pathways in resistance was then determined by assessing the symptoms of mutants affected in the perception, production, or transduction of hormonal signals after inoculation with S. sclerotiorum. This analysis led to the conclusions that i) signaling of inducible defenses is predominantly mediated by jasmonic acid and abscisic acid, influenced by ethylene, and independent of salicylic acid; and ii) nitric oxide (NO) and reactive oxygen species are important signals required for plant resistance to S. sclerotiorum. Defense gene expression analysis supported the specific role of NO in defense activation.

Urban flooding: one-dimensional modelling of the distribution of the discharges through cross-road intersections accounting for energy losses

Many investigations have been carried out in order to develop models which allow the understanding of complex physical processes involved in urban flooding. The modelling of the interactions between overland flows on streets and flooding flows from rivers and sewer networks is one of the main objectives of recent and current research programs in hydraulics and urban hydrology. However, the modelling of the discharge distribution in the street network with crossroad needs further research due to the complexity of the flow through junctions. This paper outlines the ability of the improved one-dimensional CANOE software to simulate the street flows through the virtual network (developed under the Hy(2)Ville French National project framework) with several cross-roads. The improvements are done by adding in CANOE the energy losses coefficients deriving from the calibration phase based on the experimental study of the flow through small scale physical model of cross-road channels. Comparisons between 1D and 2D simulated distribution of discharges through the virtual network show a good agreement for the global distribution. However, large differences are observed focusing on the individual cross-road intersections in the virtual network.

One-dimensional modelling of the interactions between heavy rainfall-runoff in an urban area and flooding flows from sewer networks and rivers

Many investigations have been carried out in order to develop models which allow the linking of complex physical processes involved in urban flooding. The modelling of the interactions between overland flows on streets and flooding flows from rivers and sewer networks is one of the main objectives of recent and current research programs in hydraulics and urban hydrology. This paper outlines the original one-dimensional linking of heavy rainfall-runoff in urban areas and flooding flows from rivers and sewer networks under the RIVES project framework (Estimation of Scenario and Risks of Urban Floods). The first part of the paper highlights the capacity of Canoe software to simulate the street flows. In the second part, we show the original method of connection which enables the modelling of interactions between processes in urban flooding. Comparisons between simulated results and the results of Despotovic et al. or Gomez & Mur show a good agreement for the calibrated one-dimensional connection model. The connection operates likes a manhole with the orifice/weir coefficients used as calibration parameters. The influence of flooding flows from river was taken into account as a variable water depth boundary condition.

Flooding flows in city crossroads: experiments and 1-D modelling

This study focuses on the discharge distribution in an intersection of four channels, similar to a city crossroad. The channels and the intersection are all horizontal. Flow enters through two of the channels, and leaves through the other two. The flow is subcritical everywhere, and flow depths are controlled by vertical weirs at the exits of the outlet channels. The main variables that are measured are the flow rates in the four channels. When the weir heights in the outlet channels are the same, the ratio of flow rates in the outlet channels depends only on the ratio of flow rates in the inlet channels; if the outlet conditions are different, other parameters, such as the total flow rate also become important. The flow has also been simulated numerically using a solution of the 1-D Saint Venant equations, with a simple model to predict flow distribution in the intersection. A comparison with the experimental data shows that this model works well for the limited range of experimental conditions studied here. However, further work is needed on a wider range of conditions, closer to real conditions, before the model can be considered valid for practical applications.