Portability of genomic predictions trained on sparse factorial designs across two maize silage breeding cycles.

KEY MESSAGE: We validated the efficiency of genomic predictions calibrated on sparse factorial training sets to predict the next generation of hybrids and tested different strategies for updating predictions along generations. Genomic selection offers new prospects for revisiting hybrid breeding schemes by replacing extensive phenotyping of individuals with genomic predictions. Finding the ideal design for training genomic prediction models is still an open question. Previous studies have shown promising predictive abilities using sparse factorial instead of tester-based training sets to predict single-cross hybrids from the same generation. This study aims to further investigate the use of factorials and their optimization to predict line general combining abilities (GCAs) and hybrid values across breeding cycles. It relies on two breeding cycles of a maize reciprocal genomic selection scheme involving multiparental connected reciprocal populations from flint and dent complementary heterotic groups selected for silage performances. Selection based on genomic predictions trained on a factorial design resulted in a significant genetic gain for dry matter yield in the new generation. Results confirmed the efficiency of sparse factorial training sets to predict candidate line GCAs and hybrid values across breeding cycles. Compared to a previous study based on the first generation, the advantage of factorial over tester training sets appeared lower across generations. Updating factorial training sets by adding single-cross hybrids between selected lines from the previous generation or a random subset of hybrids from the new generation both improved predictive abilities. The CDmean criterion helped determine the set of single-crosses to phenotype to update the training set efficiently. Our results validated the efficiency of sparse factorial designs for calibrating hybrid genomic prediction experimentally and showed the benefit of updating it along generations.

Assessing the potential of genetic resource introduction into elite germplasm: a collaborative multiparental population for flint maize.

KEY MESSAGE: Implementing a collaborative pre-breeding multi-parental population efficiently identifies promising donor x elite pairs to enrich the flint maize elite germplasm. Genetic diversity is crucial for maintaining genetic gains and ensuring breeding programs' long-term success. In a closed breeding program, selection inevitably leads to a loss of genetic diversity. While managing diversity can delay this loss, introducing external sources of diversity is necessary to bring back favorable genetic variation. Genetic resources exhibit greater diversity than elite materials, but their lower performance levels hinder their use. This is the case for European flint maize, for which elite germplasm has incorporated only a limited portion of the diversity available in landraces. To enrich the diversity of this elite genetic pool, we established an original cooperative maize bridging population that involves crosses between private elite materials and diversity donors to create improved genotypes that will facilitate the incorporation of original favorable variations. Twenty donor × elite BC1S2 families were created and phenotyped for hybrid value for yield related traits. Crosses showed contrasted means and variances and therefore contrasted potential in terms of selection as measured by their usefulness criterion (UC). Average expected mean performance gain over the initial elite material was 5%. The most promising donor for each elite line was identified. Results also suggest that one more generation, i.e., 3 in total, of crossing to the elite is required to fully exploit the potential of a donor. Altogether, our results support the usefulness of incorporating genetic resources into elite flint maize. They call for further effort to create fixed diversity donors and identify those most suitable for each elite program.

Genotyping of DNA pools identifies untapped landraces and genomic regions to develop next-generation varieties.

Landraces, that is, traditional varieties, have a large diversity that is underexploited in modern breeding. A novel DNA pooling strategy was implemented to identify promising landraces and genomic regions to enlarge the genetic diversity of modern varieties. As proof of concept, DNA pools from 156 American and European maize landraces representing 2340 individuals were genotyped with an SNP array to assess their genome-wide diversity. They were compared to elite cultivars produced across the 20th century, represented by 327 inbred lines. Detection of selective footprints between landraces of different geographic origin identified genes involved in environmental adaptation (flowering times, growth) and tolerance to abiotic and biotic stress (drought, cold, salinity). Promising landraces were identified by developing two novel indicators that estimate their contribution to the genome of inbred lines: (i) a modified Roger's distance standardized by gene diversity and (ii) the assignation of lines to landraces using supervised analysis. It showed that most landraces do not have closely related lines and that only 10 landraces, including famous landraces as Reid's Yellow Dent, Lancaster Surecrop and Lacaune, cumulated half of the total contribution to inbred lines. Comparison of ancestral lines directly derived from landraces with lines from more advanced breeding cycles showed a decrease in the number of landraces with a large contribution. New inbred lines derived from landraces with limited contributions enriched more the haplotype diversity of reference inbred lines than those with a high contribution. Our approach opens an avenue for the identification of promising landraces for pre-breeding.

Identifying QTLs involved in hybrid performance and heterotic group complementarity: new GWAS models applied to factorial and admixed diallel maize hybrid panels.

KEY MESSAGE: An original GWAS model integrating the ancestry of alleles was proposed and allowed the detection of background specific additive and dominance QTLs involved in heterotic group complementarity and hybrid performance. Maize genetic diversity is structured into genetic groups selected and improved relative to each other. This process increases group complementarity and differentiation over time and ensures that the hybrids produced from inter-group crosses exhibit high performances and heterosis. To identify loci involved in hybrid performance and heterotic group complementarity, we introduced an original association study model that disentangles allelic effects from the heterotic group origin of the alleles and compared it with a conventional additive/dominance model. This new model was applied on a factorial between Dent and Flint lines and a diallel between Dent-Flint admixed lines with two different layers of analysis: within each environment and in a multiple-environment context. We identified several strong additive QTLs for all traits, including some well-known additive QTLs for flowering time (in the region of Vgt1/2 on chromosome 8). Yield trait displayed significant non-additive effects in the diallel panel. Most of the detected Yield QTLs exhibited overdominance or, more likely, pseudo-overdominance effects. Apparent overdominance at these QTLs contributed to a part of the genetic group complementarity. The comparison between environments revealed a higher stability of additive QTL effects than non-additive ones. Several QTLs showed variations of effects according to the local heterotic group origin. We also revealed large chromosomic regions that display genetic group origin effects. Altogether, our results illustrate how admixed panels combined with dedicated GWAS modeling allow the identification of new QTLs that could not be revealed by a classical hybrid panel analyzed with traditional modeling.

Disentangling group specific QTL allele effects from genetic background epistasis using admixed individuals in GWAS: An application to maize flowering.

When handling a structured population in association mapping, group-specific allele effects may be observed at quantitative trait loci (QTLs) for several reasons: (i) a different linkage disequilibrium (LD) between SNPs and QTLs across groups, (ii) group-specific genetic mutations in QTL regions, and/or (iii) epistatic interactions between QTLs and other loci that have differentiated allele frequencies between groups. We present here a new genome-wide association (GWAS) approach to identify QTLs exhibiting such group-specific allele effects. We developed genetic materials including admixed progeny from different genetic groups with known genome-wide ancestries (local admixture). A dedicated statistical methodology was developed to analyze pure and admixed individuals jointly, allowing one to disentangle the factors causing the heterogeneity of allele effects across groups. This approach was applied to maize by developing an inbred "Flint-Dent" panel including admixed individuals that was evaluated for flowering time. Several associations were detected revealing a wide range of configurations of allele effects, both at known flowering QTLs (Vgt1, Vgt2 and Vgt3) and new loci. We found several QTLs whose effect depended on the group ancestry of alleles while others interacted with the genetic background. Our GWAS approach provides useful information on the stability of QTL effects across genetic groups and can be applied to a wide range of species.

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.

Genotyping-by-sequencing and SNP-arrays are complementary for detecting quantitative trait loci by tagging different haplotypes in association studies.

BACKGROUND: Single Nucleotide Polymorphism (SNP) array and re-sequencing technologies have different properties (e.g. calling rate, minor allele frequency profile) and drawbacks (e.g. ascertainment bias). This lead us to study their complementarity and the consequences of using them separately or combined in diversity analyses and Genome-Wide Association Studies (GWAS). We performed GWAS on three traits (grain yield, plant height and male flowering time) measured in 22 environments on a panel of 247 F1 hybrids obtained by crossing 247 diverse dent maize inbred lines with a same flint line. The 247 lines were genotyped using three genotyping technologies (Genotyping-By-Sequencing, Illumina Infinium 50 K and Affymetrix Axiom 600 K arrays). RESULTS: The effects of ascertainment bias of the 50 K and 600 K arrays were negligible for deciphering global genetic trends of diversity and for estimating relatedness in this panel. We developed an original approach based on linkage disequilibrium (LD) extent in order to determine whether SNPs significantly associated with a trait and that are physically linked should be considered as a single Quantitative Trait Locus (QTL) or several independent QTLs. Using this approach, we showed that the combination of the three technologies, which have different SNP distributions and densities, allowed us to detect more QTLs (gain in power) and potentially refine the localization of the causal polymorphisms (gain in resolution). CONCLUSIONS: Conceptually different technologies are complementary for detecting QTLs by tagging different haplotypes in association studies. Considering LD, marker density and the combination of different technologies (SNP-arrays and re-sequencing), the genotypic data available were most likely enough to well represent polymorphisms in the centromeric regions, whereas using more markers would be beneficial for telomeric regions.

Genotyping-by-sequencing highlights original diversity patterns within a European collection of 1191 maize flint lines, as compared to the maize USDA genebank.

KEY MESSAGE: Genotyping by sequencing is suitable for analysis of global diversity in maize. We showed the distinctiveness of flint maize inbred lines of interest to enrich the diversity of breeding programs. Genotyping-by-sequencing (GBS) is a highly cost-effective procedure that permits the analysis of large collections of inbred lines. We used it to characterize diversity in 1191 maize flint inbred lines from the INRA collection, the European Cornfed association panel, and lines recently derived from landraces. We analyzed the properties of GBS data obtained with different imputation methods, through comparison with a 50 K SNP array. We identified seven ancestral groups within the Flint collection (dent, Northern flint, Italy, Pyrenees-Galicia, Argentina, Lacaune, Popcorn) in agreement with breeding knowledge. Analysis highlighted many crosses between different origins and the improvement of flint germplasm with dent germplasm. We performed association studies on different agronomic traits, revealing SNPs associated with cob color, kernel color, and male flowering time variation. We compared the diversity of both our collection and the USDA collection which has been previously analyzed by GBS. The population structure of the 4001 inbred lines confirmed the influence of the historical inbred lines (B73, A632, Oh43, Mo17, W182E, PH207, and Wf9) within the dent group. It showed distinctly different tropical and popcorn groups, a sweet-Northern flint group and a flint group sub-structured in Italian and European flint (Pyrenees-Galicia and Lacaune) groups. Interestingly, we identified several selective sweeps between dent, flint, and tropical inbred lines that co-localized with SNPs associated with flowering time variation. The joint analysis of collections by GBS offers opportunities for a global diversity analysis of maize inbred lines.

Genetic and Phenotypic Evaluation of European Maize Landraces as a Tool for Conservation and Valorization of Agrobiodiversity.

The ECPGR European Evaluation Network (EVA) for Maize involves genebanks, research institutions, and private breeding companies from nine countries focusing on the valorization of maize genetic resources across Europe. This study describes a diverse collection of 626 local landraces and traditional varieties of maize (Zea mays L.) from nine European genebanks, including criteria for selection of the collection and its genetic and phenotypic diversity. High-throughput pool genotyping grouped the landraces into nine genetic groups with a threshold of 0.6 admixture, while 277 accessions were designated admixed and likely to have resulted from previous breeding activities. The grouping correlated well with the geographic origins of the collection, also reflecting the various pathways of introduction of maize to Europe. Phenotypic evaluations of 588 accessions for flowering time and plant architecture in multilocation trials over three years confirmed the great diversity within the collection, although phenotypic clusters only partially correlated with the genetic grouping. The EVA approach promotes conservation of genetic resources and opens an opportunity to increase genetic variability for developing improved varieties and populations for farmers, with better adaptation to specific environments and greater tolerance to various stresses. As such, the EVA maize collection provides valuable sources of diversity for facing climate change due to the varieties' local adaptation.

Maize genetic diversity and association mapping using transposable element insertion polymorphisms.

Transposable elements are the major component of the maize genome and presumably highly polymorphic yet they have not been used in population genetics and association analyses. Using the Transposon Display method, we isolated and converted into PCR-based markers 33 Miniature Inverted Repeat Transposable Elements (MITE) polymorphic insertions. These polymorphisms were genotyped on a population-based sample of 26 American landraces for a total of 322 plants. Genetic diversity was high and partitioned within and among landraces. The genetic groups identified using Bayesian clustering were in agreement with published data based on SNPs and SSRs, indicating that MITE polymorphisms reflect maize genetic history. To explore the contribution of MITEs to phenotypic variation, we undertook an association mapping approach in a panel of 367 maize lines phenotyped for 26 traits. We found a highly significant association between the marker ZmV1-9, on chromosome 1, and male flowering time. The variance explained by this association is consistent with a flowering delay of +123 degree-days. This MITE insertion is located at only 289 nucleotides from the 3' end of a Cytochrome P450-like gene, a region that was never identified in previous association mapping or QTL surveys. Interestingly, we found (i) a non-synonymous mutation located in the exon 2 of the gene in strong linkage disequilibrium with the MITE polymorphism, and (ii) a perfect sequence homology between the MITE sequence and a maize siRNA that could therefore potentially interfere with the expression of the Cytochrome P450-like gene. Those two observations among others offer exciting perspectives to validate functionally the role of this region on phenotypic variation.

Physiological adaptive traits are a potential allele reservoir for maize genetic progress under challenging conditions.

Combined phenomic and genomic approaches are required to evaluate the margin of progress of breeding strategies. Here, we analyze 65 years of genetic progress in maize yield, which was similar (101 kg ha-1 year-1) across most frequent environmental scenarios in the European growing area. Yield gains were linked to physiologically simple traits (plant phenology and architecture) which indirectly affected reproductive development and light interception in all studied environments, marked by significant genomic signatures of selection. Conversely, studied physiological processes involved in stress adaptation remained phenotypically unchanged (e.g. stomatal conductance and growth sensitivity to drought) and showed no signatures of selection. By selecting for yield, breeders indirectly selected traits with stable effects on yield, but not physiological traits whose effects on yield can be positive or negative depending on environmental conditions. Because yield stability under climate change is desirable, novel breeding strategies may be needed for exploiting alleles governing physiological adaptive traits.

Deciphering the genetics of flowering time by an association study on candidate genes in bread wheat (Triticum aestivum L.).

Earliness is very important for the adaptation of wheat to environmental conditions and the achievement of high grain yield. A detailed knowledge of key genetic components of the life cycle would enable an easier control by the breeders. The objective of the study was to investigate the effect of candidate genes on flowering time. Using a collection of hexaploid wheat composed of 235 lines from diverse geographical origins, we conducted an association study for six candidate genes for flowering time and its components (vernalization sensitivity and earliness per se). The effect on the variation of earliness components of polymorphisms within the copies of each gene was tested in ANOVA models accounting for the underlying genetic structure. The collection was structured in five groups that minimized the residual covariance. Vernalization requirement and lateness tend to increase according to the mean latitude of each group. Heading date for an autumnal sowing was mainly determined by the earliness per se. Except for the Constans (CO) gene orthologous of the barley HvCO3, all gene polymorphisms had a significant impact on earliness components. The three traits used to quantify vernalization requirement were primarily associated with polymorphisms at Vrn-1 and then at Vrn-3 and Luminidependens (LD) genes. We found a good correspondence between spring/winter types and genotypes at the three homeologous copies of Vrn-1. Earliness per se was mainly explained by polymorphisms at Vrn-3 and to a lesser extent at Vrn-1, Hd-1 and Gigantea (GI) genes. Vernalization requirement and earliness as a function of geographical origin, as well as the possible role of the breeding practices in the geographical distribution of the alleles and the hypothetical adaptive value of the candidate genes, are discussed.

Genetic diversity of maize landraces from the South-West of France.

From the 17th century until the arrival of hybrids in 1960s, maize landraces were cultivated in the South-West of France (SWF), a traditional region for maize cultivation. A set of landraces were collected in this area between the 1950s and 1980s and were then conserved ex situ in a germplam collection. Previous studies using molecular markers on approx. twenty landraces from this region suggested that they belonged to a Pyrenees-Galicia Flint genetic group and originated from hybridizations between Caribbean and Northern Flint germplasms introduced to Europe. In this study, we assessed the structure and genetic diversity of 194 SWF maize landraces to better elucidate their origin, using a 50K SNP array and a bulk DNA approach. We identified two weakly differentiated genetic groups, one in the Western part and the other in the Eastern part of the studied region. We highlighted the existence of a longitudinal gradient along the SWF area that was probably maintained through the interplay between genetic drifts and restricted gene flows. The contact zone between the two groups observed near the Garonne valley may be the result of these evolutionnary forces. We found in landraces from the East part of the region significant cases of admixture between landraces from the Northern Flint group and landraces from either the Caribbean, Andean or Italian groups. We then assumed that SWF landraces had a multiple origin with a predonderance of Northern Flint germplasm for the two SWF groups, notably for the East part.

Deciphering the Genetic Diversity of Landraces With High-Throughput SNP Genotyping of DNA Bulks: Methodology and Application to the Maize 50k Array.

Genebanks harbor original landraces carrying many original favorable alleles for mitigating biotic and abiotic stresses. Their genetic diversity remains, however, poorly characterized due to their large within genetic diversity. We developed a high-throughput, cheap and labor saving DNA bulk approach based on single-nucleotide polymorphism (SNP) Illumina Infinium HD array to genotype landraces. Samples were gathered for each landrace by mixing equal weights from young leaves, from which DNA was extracted. We then estimated allelic frequencies in each DNA bulk based on fluorescent intensity ratio (FIR) between two alleles at each SNP using a two step-approach. We first tested either whether the DNA bulk was monomorphic or polymorphic according to the two FIR distributions of individuals homozygous for allele A or B, respectively. If the DNA bulk was polymorphic, we estimated its allelic frequency by using a predictive equation calibrated on FIR from DNA bulks with known allelic frequencies. Our approach: (i) gives accurate allelic frequency estimations that are highly reproducible across laboratories, (ii) protects against false detection of allele fixation within landraces. We estimated allelic frequencies of 23,412 SNPs in 156 landraces representing American and European maize diversity. Modified Roger's genetic Distance between 156 landraces estimated from 23,412 SNPs and 17 simple sequence repeats using the same DNA bulks were highly correlated, suggesting that the ascertainment bias is low. Our approach is affordable, easy to implement and does not require specific bioinformatics support and laboratory equipment, and therefore should be highly relevant for large-scale characterization of genebanks for a wide range of species.

Key impact of Vgt1 on flowering time adaptation in maize: evidence from association mapping and ecogeographical information.

An association study conducted on 375 maize inbred lines indicates a strong relationship between Vgt1 polymorphisms and flowering time, extending former quantitative trait loci (QTL) mapping results. Analysis of allele frequencies in a landrace collection supports a key role of Vgt1 in maize altilatitudinal adaptation.

Maize adaptation to temperate climate: relationship between population structure and polymorphism in the Dwarf8 gene.

To investigate the genetic basis of maize adaptation to temperate climate, collections of 375 inbred lines and 275 landraces, representative of American and European diversity, were evaluated for flowering time under short- and long-day conditions. The inbred line collection was genotyped for 55 genomewide simple sequence repeat (SSR) markers. Comparison of inbred line population structure with that of landraces, as determined with 24 SSR loci, underlined strong effects of both historical and modern selection on population structure and a clear relationship with geographical origins. The late tropical groups and the early "Northern Flint" group from the northern United States and northern Europe exhibited different flowering times. Both collections were genotyped for a 6-bp insertion/deletion in the Dwarf8 (D8idp) gene, previously reported to be potentially involved in flowering time variation in a 102 American inbred panel. Among-group D8idp differentiation was much higher than that for any SSR marker, suggesting diversifying selection. Correcting for population structure, D8idp was associated with flowering time under long-day conditions, the deletion allele showing an average earlier flowering of 29 degree days for inbreds and 145 degree days for landraces. Additionally, the deletion allele occurred at a high frequency (>80%) in Northern Flint while being almost absent (<5%) in tropical materials. Altogether, these results indicate that Dwarf8 could be involved in maize climatic adaptation through diversifying selection for flowering time.

Reciprocal Genetics: Identifying QTL for General and Specific Combining Abilities in Hybrids Between Multiparental Populations from Two Maize (Zea mays L.) Heterotic Groups.

Several plant and animal species of agricultural importance are commercialized as hybrids to take advantage of the heterosis phenomenon. Understanding the genetic architecture of hybrid performances is therefore of key importance. We developed two multiparental maize (Zea mays L.) populations, each corresponding to an important heterotic group (dent or flint) and comprised of six connected biparental segregating populations of inbred lines (802 and 822 lines for each group, respectively) issued from four founder lines. Instead of using "testers" to evaluate their hybrid values, segregating lines were crossed according to an incomplete factorial design to produce 951 dent-flint hybrids, evaluated for four biomass production traits in eight environments. QTL detection was carried out for the general-combining-ability (GCA) and specific-combining-ability (SCA) components of hybrid value, considering allelic effects transmitted from each founder line. In total, 42 QTL were detected across traits. We detected mostly QTL affecting GCA, 31% (41% for dry matter yield) of which also had mild effects on SCA. The small impact of dominant effects is consistent with the known differentiation between the dent and flint heterotic groups and the small percentage of hybrid variance due to SCA observed in our design (∼20% for the different traits). Furthermore, most (80%) of GCA QTL were segregating in only one of the two heterotic groups. Relative to tester-based designs, use of hybrids between two multiparental populations appears highly cost efficient to detect QTL in two heterotic groups simultaneously. This presents new prospects for selecting superior hybrid combinations with markers.

Linkage Analysis and Association Mapping QTL Detection Models for Hybrids Between Multiparental Populations from Two Heterotic Groups: Application to Biomass Production in Maize (Zea mays L.).

Identification of quantitative trait loci (QTL) involved in the variation of hybrid value is of key importance for cross-pollinated species such as maize (Zea mays L.). In a companion paper, we illustrated a new QTL mapping population design involving a factorial mating between two multiparental segregating populations. Six biparental line populations were developed from four founder lines in the Dent and Flint heterotic groups. They were crossed to produce 951 hybrids and evaluated for silage performances. Previously, a linkage analysis (LA) model that assumes each founder line carries a different allele was used to detect QTL involved in General and Specific Combining Abilities (GCA and SCA, respectively) of hybrid value. This previously introduced model requires the estimation of numerous effects per locus, potentially affecting QTL detection power. Using the same design, we compared this "Founder alleles" model to two more parsimonious models, which assume that (i) identity in state at SNP alleles from the same heterotic group implies identity by descent (IBD) at linked QTL ("SNP within-group" model) or (ii) identity in state implies IBD, regardless of population origin of the alleles ("Hybrid genotype" model). This last model assumes biallelic QTL with equal effects in each group. It detected more QTL on average than the two other models but explained lower percentages of variance. The "SNP within-group" model appeared to be a good compromise between the two other models. These results confirm the divergence between the Dent and Flint groups. They also illustrate the need to adapt the QTL detection model to the complexity of the allelic variation, which depends on the trait, the QTL, and the divergence between the heterotic groups.

Identification and characterization of water-stress-responsive genes in hydroponically grown maritime pine (Pinus pinaster) seedlings.

Growth, development and productivity of long-lived organisms such as forest trees are continuously challenged by abiotic stresses, and may also be greatly affected by predicted climatic change. As a first step toward creating stress-resistant maritime pine (Pinus pinaster Ait.) varieties by marker-assisted breeding, we describe the identification and characterization of water-stress-responsive genes in hydroponically grown seedlings that were well watered (-0.08 MPa) or subjected to water deprivation (-0.45 MPa) by the addition of polyethylene glycol. The cDNA amplified fragment-length polymorphism (cDNA-AFLP) technique was used to identify genes regulated by water deprivation. Approximately 4000 transcript-derived fragments (TDFs) were screened, of which 28 increased and 20 decreased in seedlings subjected to water deprivation. Of these 48 TDFs, 62.6% corresponded to proteins of known function, which indicate the main mechanisms involved in the osmotic stress response (photosynthesis, carbohydrate metabolism, cell wall synthesis and plant defense). We found that 16.6% of the 48 TDFs were similar to Arabidopsis thaliana (L.) Heynh gene products, 10.4% were similar to Pinus taeda L. expressed sequence tags (ESTs) and 10.4% did not match any sequences in the public databases. The relative abundance of these transcripts was quantitatively analyzed by reverse northern of both needle and root tissues, confirming the effectiveness of the cDNA-AFLP technique in detecting differentially expressed genes. The identification and characterization of water-stress-responsive genes provide new insights into the nature of the machinery involved in the response to water deprivation in a forest tree.

Recovering power in association mapping panels with variable levels of linkage disequilibrium.

Association mapping has permitted the discovery of major QTL in many species. It can be applied to existing populations and, as a consequence, it is generally necessary to take into account structure and relatedness among individuals in the statistical model to control false positives. We analytically studied power in association studies by computing noncentrality parameter of the tests and its relationship with parameters characterizing diversity (genetic differentiation between groups and allele frequencies) and kinship between individuals. Investigation of three different maize diversity panels genotyped with the 50k SNPs array highlighted contrasted average power among panels and revealed gaps of power of classical mixed models in regions with high linkage disequilibrium (LD). These gaps could be related to the fact that markers are used for both testing association and estimating relatedness. We thus considered two alternative approaches to estimating the kinship matrix to recover power in regions of high LD. In the first one, we estimated the kinship with all the markers that are not located on the same chromosome than the tested SNP. In the second one, correlation between markers was taken into account to weight the contribution of each marker to the kinship. Simulations revealed that these two approaches were efficient to control false positives and were more powerful than classical models.