Detection of favorable alleles for plant height and crown rust tolerance in three connected populations of perennial ryegrass (Lolium perenne L.)

Epichloë seed transmission efficiency is influenced by plant defense response mechanisms

Asexual Epichloë are endophytic fungi that form mutualistic symbioses with cool-season grasses, conferring to their hosts protection against biotic and abiotic stresses. Symbioses are maintained between grass generations as hyphae are vertically transmitted from parent to progeny plants through seed. However, endophyte transmission to the seed is an imperfect process where not all seeds become infected. The mechanisms underpinning the varying efficiencies of seed transmission are poorly understood. Host gene expression in response to Epichloë sp. LpTG-3 strain AR37 was examined within inflorescence primordia and ovaries of high and low endophyte transmission genotypes within a single population of perennial ryegrass. A genome-wide association study was conducted to identify population-level single nucleotide polymorphisms (SNPs) and associated genes correlated with vertical transmission efficiency. For low transmitters of AR37, upregulation of perennial ryegrass receptor-like kinases and resistance genes, typically associated with phytopathogen detection, comprised the largest group of differentially expressed genes (DEGs) in both inflorescence primordia and ovaries. DEGs involved in signaling and plant defense responses, such as cell wall modification, secondary metabolism, and reactive oxygen activities were also abundant. Transmission-associated SNPs were associated with genes for which gene ontology analysis identified "response to fungus" as the most significantly enriched term. Moreover, endophyte biomass as measured by quantitative PCR of Epichloë non-ribosomal peptide synthetase genes, was significantly lower in reproductive tissues of low-transmission hosts compared to high-transmission hosts. Endophyte seed-transmission efficiency appears to be influenced primarily by plant defense responses which reduce endophyte colonization of host reproductive tissues.

Molecular Dissection of Quantitative Variation in Bermudagrass Hybrids (Cynodon dactylon x transvaalensis): Morphological Traits

Bermudagrass (Cynodon (L.)) is the most important warm-season grass grown for forage or turf. It shows extensive variation in morphological characteristics and growth attributes, but the genetic basis of this variation is little understood. Detection and tagging of quantitative trait loci (QTL) affecting above-ground morphology with diagnostic DNA markers would provide a foundation for genetic and molecular breeding applications in bermudagrass. Here, we report early findings regarding genetic architecture of foliage (canopy height, HT), stolon (stolon internode length, ILEN and length of the longest stolon LLS), and leaf traits (leaf blade length, LLEN and leaf blade width, LW) in 110 F1 individuals derived from a cross between Cynodon dactylon (T89) and C. transvaalensis (T574). Separate and joint environment analyses were performed on trait data collected across two to five environments (locations, and/or years, or time), finding significant differences (P < 0.001) among the hybrid progeny for all traits. Analysis of marker-trait associations detected 74 QTL and 135 epistatic interactions. Composite interval mapping (CIM) and mixed-model CIM (MCIM) identified 32 main effect QTL (M-QTL) and 13 interacting QTL (int-QTL). Colocalization of QTL for plant morphology partially explained significant correlations among traits. M-QTL qILEN-3-2 (for ILEN; R2 = 11-19%), qLLS-7-1 (for LLS; R2 = 13-27%), qLEN-1-1 (for LLEN; R2 = 10-11%), and qLW-3-2 (for LW; R2 = 10-12%) were 'stable' across multiple environments, representing candidates for fine mapping and applied breeding applications. QTL correspondence between bermudagrass and divergent grass lineages suggests opportunities to accelerate progress by predictive breeding of bermudagrass.

A novel high-density grapevine (Vitis vinifera L.) integrated linkage map using GBS in a half-diallel population

A half-diallel population involving five elite grapevine cultivars was generated and genotyped by GBS, and highly-informative segregation data was used to construct a high-density genetic map for Vitis vinifera L. Grapevine is one of the most relevant fruit crops in the world. Deeper genetic knowledge could assist modern grapevine breeding programs to develop new wine grape varieties able to face climate change effects. To assist in the rapid identification of markers for crop yield components, grape quality traits and adaptation potential, we generated a large Vitis vinifera L. population (N = 624) by crossing five red wine cultivars in a half-diallel scheme, which was subsequently sequenced by an efficient GBS procedure. A high number of fully informative genetic variants was detected using a novel mapping approach capable of reconstructing local haplotypes from adjacent biallelic SNPs, which were subsequently used to construct the densest consensus genetic map available for the cultivated grapevine to date. This 1378.3-cM map integrates 10 bi-parental consensus maps and orders 4437 markers in 3353 unique positions on 19 chromosomes. Markers are well distributed all along the grapevine reference genome, covering up to 98.8% of its genomic sequence. Additionally, a good agreement was observed between genetic and physical orders, adding confidence in the quality of this map. Collectively, our results pave the way for future genetic studies (such as fine QTL mapping) aimed to understand the complex relationship between genotypic and phenotypic variation in the cultivated grapevine. In addition, the method used (which efficiently delivers a high number of fully informative markers) could be of interest to other outbred organisms, notably perennial fruit crops.

Genetic Dissection of Bloom Time in Low Chilling Sweet Cherry (Prunus avium L.) Using a Multi-Family QTL Approach

Bloom time in sweet cherry (Prunus avium L.) is a highly heritable trait that varies between genotypes and depends on the environmental conditions. Bud-break occurs after chill and heat requirements of each genotype are fulfilled, and dormancy is released. Bloom time is a critical trait for fruit production as matching cultivar adaptation to the growing area is essential for adequate fruit set. Additionally, low chilling cultivars are of interest to extend sweet cherry production to warmer regions, and for the crop adaptation to increasing winter and spring temperatures. The aim of this work is to investigate the genetic control of this trait by analyzing multiple families derived from the low chilling and extra-early flowering local Spanish cultivar 'Cristobalina' and other cultivars with higher chilling requirements and medium to late bloom times. Bloom time evaluation in six related sweet cherry populations confirmed a high heritability of this trait, and skewed distribution toward late flowering, revealing possible dominance of the late bloom alleles. SNP genotyping of the six populations (n = 406) resulted in a consensus map of 1269 SNPs. Quantitative trait loci (QTL) analysis using the Bayesian approach implemented by FlexQTL™ software revealed two major QTLs on linkage groups 1 and 2 (qP-BT1.1m and qP-BT2.1m) that explained 47.6% of the phenotypic variation. The QTL on linkage group 1 was mapped to a 0.26 Mbp region that overlaps with the DORMANCY ASSOCIATED MADS-BOX (DAM) genes. This finding is consistent with peach results that indicate that these genes are major determinants of chilling requirement in Prunus. Haplotype analysis of the linkage group 1 and 2 QTL regions showed that 'Cristobalina' was the only cultivar tested that contributed early bloom time alleles for these two QTLs. This work contributes to knowledge of the genetic control of chilling requirement and bloom date and will enable marker-assisted selection for low chilling in sweet cherry breeding programs.

Toward Genomics-Based Breeding in C3 Cool-Season Perennial Grasses

Most important food and feed crops in the world belong to the C3 grass family. The future of food security is highly reliant on achieving genetic gains of those grasses. Conventional breeding methods have already reached a plateau for improving major crops. Genomics tools and resources have opened an avenue to explore genome-wide variability and make use of the variation for enhancing genetic gains in breeding programs. Major C3 annual cereal breeding programs are well equipped with genomic tools; however, genomic research of C3 cool-season perennial grasses is lagging behind. In this review, we discuss the currently available genomics tools and approaches useful for C3 cool-season perennial grass breeding. Along with a general review, we emphasize the discussion focusing on forage grasses that were considered orphan and have little or no genetic information available. Transcriptome sequencing and genotype-by-sequencing technology for genome-wide marker detection using next-generation sequencing (NGS) are very promising as genomics tools. Most C3 cool-season perennial grass members have no prior genetic information; thus NGS technology will enhance collinear study with other C3 model grasses like Brachypodium and rice. Transcriptomics data can be used for identification of functional genes and molecular markers, i.e., polymorphism markers and simple sequence repeats (SSRs). Genome-wide association study with NGS-based markers will facilitate marker identification for marker-assisted selection. With limited genetic information, genomic selection holds great promise to breeders for attaining maximum genetic gain of the cool-season C3 perennial grasses. Application of all these tools can ensure better genetic gains, reduce length of selection cycles, and facilitate cultivar development to meet the future demand for food and fodder.

Genetic dissection of powdery mildew resistance in interspecific half-sib grapevine families using SNP-based maps

Quantitative trait locus (QTL) identification in perennial fruit crops is impeded largely by their lengthy generation time, resulting in costly and labor-intensive maintenance of breeding programs. In a grapevine (genus Vitis) breeding program, although experimental families are typically unreplicated, the genetic backgrounds may contain similar progenitors previously selected due to their contribution of favorable alleles. In this study, we investigated the utility of joint QTL identification provided by analyzing half-sib families. The genetic control of powdery mildew was studied using two half-sib F₁ families, namely GE0711/1009 (MN1264 × MN1214; N = 147) and GE1025 (MN1264 × MN1246; N = 125) with multiple species in their ancestry. Maternal genetic maps consisting of 1077 and 1641 single nucleotide polymorphism (SNP) markers, respectively, were constructed using a pseudo-testcross strategy. Ratings of field resistance to powdery mildew were obtained based on whole-plant evaluation of disease severity. This 2-year analysis uncovered two QTLs that were validated on a consensus map in these half-sib families with improved precision relative to the parental maps. Examination of haplotype combinations based on the two QTL regions identified strong association of haplotypes inherited from 'Seyval blanc', through MN1264, with powdery mildew resistance. This investigation also encompassed the use of microsatellite markers to establish a correlation between 206-bp (UDV-015b) and 357-bp (VViv67) fragment sizes with resistance-carrying haplotypes. Our work is one of the first reports in grapevine demonstrating the use of SNP-based maps and haplotypes for QTL identification and tagging of powdery mildew resistance in half-sib families.

Predicting Flowering Behavior and Exploring Its Genetic Determinism in an Apple Multi-family Population Based on Statistical Indices and Simplified Phenotyping

Irregular flowering over years is commonly observed in fruit trees. The early prediction of tree behavior is highly desirable in breeding programmes. This study aims at performing such predictions, combining simplified phenotyping and statistics methods. Sequences of vegetative vs. floral annual shoots (AS) were observed along axes in trees belonging to five apple related full-sib families. Sequences were analyzed using Markovian and linear mixed models including year and site effects. Indices of flowering irregularity, periodicity and synchronicity were estimated, at tree and axis scales. They were used to predict tree behavior and detect QTL with a Bayesian pedigree-based analysis, using an integrated genetic map containing 6,849 SNPs. The combination of a Biennial Bearing Index (BBI) with an autoregressive coefficient (γ _g ) efficiently predicted and classified the genotype behaviors, despite few misclassifications. Four QTLs common to BBIs and γ _g and one for synchronicity were highlighted and revealed the complex genetic architecture of the traits. Irregularity resulted from high AS synchronism, whereas regularity resulted from either asynchronous locally alternating or continual regular AS flowering. A relevant and time-saving method, based on a posteriori sampling of axes and statistical indices is proposed, which is efficient to evaluate the tree breeding values for flowering regularity and could be transferred to other species.

On the Accuracy of Genomic Selection

Genomic selection is focused on prediction of breeding values of selection candidates by means of high density of markers. It relies on the assumption that all quantitative trait loci (QTLs) tend to be in strong linkage disequilibrium (LD) with at least one marker. In this context, we present theoretical results regarding the accuracy of genomic selection, i.e., the correlation between predicted and true breeding values. Typically, for individuals (so-called test individuals), breeding values are predicted by means of markers, using marker effects estimated by fitting a ridge regression model to a set of training individuals. We present a theoretical expression for the accuracy; this expression is suitable for any configurations of LD between QTLs and markers. We also introduce a new accuracy proxy that is free of the QTL parameters and easily computable; it outperforms the proxies suggested in the literature, in particular, those based on an estimated effective number of independent loci (M_e). The theoretical formula, the new proxy, and existing proxies were compared for simulated data, and the results point to the validity of our approach. The calculations were also illustrated on a new perennial ryegrass set (367 individuals) genotyped for 24,957 single nucleotide polymorphisms (SNPs). In this case, most of the proxies studied yielded similar results because of the lack of markers for coverage of the entire genome (2.7 Gb).

Detecting QTLs and putative candidate genes involved in budbreak and flowering time in an apple multiparental population

In temperate trees, growth resumption in spring time results from chilling and heat requirements, and is an adaptive trait under global warming. Here, the genetic determinism of budbreak and flowering time was deciphered using five related full-sib apple families. Both traits were observed over 3 years and two sites and expressed in calendar and degree-days. Best linear unbiased predictors of genotypic effect or interaction with climatic year were extracted from mixed linear models and used for quantitative trait locus (QTL) mapping, performed with an integrated genetic map containing 6849 single nucleotide polymorphisms (SNPs), grouped into haplotypes, and with a Bayesian pedigree-based analysis. Four major regions, on linkage group (LG) 7, LG10, LG12, and LG9, the latter being the most stable across families, sites, and years, explained 5.6-21.3% of trait variance. Co-localizations for traits in calendar days or growing degree hours (GDH) suggested common genetic determinism for chilling and heating requirements. Homologs of two major flowering genes, AGL24 and FT, were predicted close to LG9 and LG12 QTLs, respectively, whereas Dormancy Associated MADs-box (DAM) genes were near additional QTLs on LG8 and LG15. This suggests that chilling perception mechanisms could be common among perennial and annual plants. Progenitors with favorable alleles depending on trait and LG were identified and could benefit new breeding strategies for apple adaptation to temperature increase.

Combining Drought Survival via Summer Dormancy and Annual Biomass Productivity in Dactylis glomerata L

Under Mediterranean climates, the best strategy to produce rain-fed fodder crops is to develop perennial drought resistant varieties. Summer dormancy present in native germplasm has been shown to confer a high level of survival under severe drought. Nevertheless it has also been shown to be negatively correlated with annual biomass productivity. The aim of this study was to analyze the correlations between summer dormancy and annual biomass productivity related traits and to identify quantitative trait loci (QTL) for these traits in a progeny of a summer dormant cocksfoot parent (Kasbah) and a summer active parent (Medly). A total of 283 offspring and the parents were phenotyped for summer dormancy, plant growth rate (PGR) and heading date in Morocco and for maximum leaf elongation rate (LERm) in France. The individuals were genotyped with a total of 325 markers including 59 AFLP, 64 SSR, and 202 DArT markers. The offspring exhibited a large quantitative variation for all measured traits. Summer dormancy showed a negative correlation with both PGR (-0.34 p < 0.005) and LERm (-0.27 p < 0.005). However, genotypes with both a high level of summer dormancy and a high level of PGR were detected in the progeny. One genetic map per parent was built with a total length of 377 and 423 cM for Kasbah and Medly, respectively. Both different and co-localized QTL for summer dormancy and PGR were identified. These results demonstrate that it should be possible to create summer dormant cocksfoot varieties with a high annual biomass productivity.

QTL mapping of carrot resistance to leaf blight with connected populations: stability across years and consequences for breeding

Combining biparental and multiparental connected population analyses was useful for the identification of 11 QTLs in two new genetic backgrounds of carrot resistance to Alternaria dauci and for breeding recommendations. Leaf blight due to the fungus Alternaria dauci is the major carrot foliar disease worldwide. Some resistance QTLs have been previously identified in one population, but the evaluation of additional genetic backgrounds with higher level of resistance would give opportunities for breeders to combine them by pyramiding. For this purpose, two segregating populations were evaluated twice across 4 years in the same environment (1) to compare the efficiency of the single vs. the connected populations approach for characterizing the new sources of carrot resistance to Alternaria dauci; (2) to evaluate the stability of QTLs over the years; and (3) to give recommendations to breeders for marker-assisted selection. Single and connected analyses were complementary; their combination allowed the detection of 11 QTLs. Connected analyses allowed the identification of common and specific QTLs among the two populations and the most favorable allele at each QTL. Important contrasts between allelic effects were observed with four and five most favorable alleles coming from the two resistant parental lines, whereas two other favorable alleles came from the susceptible parental line. While four QTLs were consistent across years, seven were detected within a single year. The heritabilities for both populations PC2 and PC3 were high (75 and 78%, respectively), suggesting that the resistance of carrot to A. dauci was little affected by these environmental conditions, but the instability of QTL over years may be due to changing environmental conditions. The complementarity between these parental lines in terms of interesting allelic combinations is also discussed.

Evidence and consequences of self-fertilisation in the predominantly outbreeding forage legume Onobrychis viciifolia

Background

Sainfoin (Onobrychis viciifolia) is a promising alternative forage plant of good quality, moderate nutrient demand and a high content of polyphenolic compounds. Its poor adoption is caused by the limited availability of well performing varieties. Sainfoin is characterised as tetraploid and mainly outcrossing, but the extent of self-fertilisation and its consequences was not investigated so far. This study aimed at assessing the rate of self-fertilisation in sainfoin under different pollination regimes and at analysing the consequences on plant performance in order to assist future breeding efforts.

Methods

The self-fertilisation rate was assessed in three sainfoin populations with artificially directed pollination (ADP) and in three populations with non-directed pollination (NDP). Dominant SRAP (sequence-related amplified polymorphism) and codominant SSR (simple sequence repeats) markers were used to detect self-fertilisation in sainfoin for the first time based on molecular marker data.

Results

High rates of self-fertilisation of up to 64.8 % were observed for ADP populations in contrast to only up to 3.9 % for NDP populations. Self-fertilisation in ADP populations led to a reduction in plant height, plant vigour and, most severely, for seed yield.

Conclusions

Although sainfoin is predominantly outcrossing, self-fertilisation can occur to a high degree under conditions of limited pollen availability. These results will influence future breeding efforts because precautions have to be taken when crossing breeding material. The resulting inbreeding depression can lead to reduced performance in self-fertilised offspring. Nevertheless the possibility of self-fertilisation also offers new ways for hybrid breeding based on the development of homogenous inbred lines.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0275-z) contains supplementary material, which is available to authorized users.

Clusthaplo: a plug-in for MCQTL to enhance QTL detection using ancestral alleles in multi-cross design

We enhance power and accuracy of QTL mapping in multiple related families, by clustering the founders of the families on their local genomic similarity. MCQTL is a linkage mapping software application that allows the joint QTL mapping of multiple related families. In its current implementation, QTLs are modeled with one or two parameters for each parent that is a founder of the multi-cross design. The higher the number of parents, the higher the number of model parameters which can impact the power and the accuracy of the mapping. We propose to make use of the availability of denser and denser genotyping information on the founders to lessen the number of MCQTL parameters and thus boost the QTL discovery. We developed clusthaplo, an R package ( http://cran.r-project.org/web/packages/clusthaplo/index.html ), which aims to cluster haplotypes using a genomic similarity that reflects the probability of sharing the same ancestral allele. Computed in a sliding window along the genome and followed by a clustering method, the genomic similarity allows the local clustering of the parent haplotypes. Our assumption is that the haplotypes belonging to the same class transmit the same ancestral allele. So their putative QTL allelic effects can be modeled with the same parameter, leading to a parsimonious model, that is plugged in MCQTL. Intensive simulations using three maize data sets showed the significant gain in power and in accuracy of the QTL mapping with the ancestral allele model compared to the classical MCQTL model. MCQTL_LD (clusthaplo outputs plug in MCQTL) is a versatile and powerful tool for QTL mapping in multiple related families that makes use of linkage and linkage disequilibrium (web site http://carlit.toulouse.inra.fr/MCQTL/ ).

Pathotype-specific QTL for stem rust resistance in Lolium perenne

A genetic map populated with RAD and SSR markers was created from F1 progeny of a stem rust-susceptible and stem rust-resistant parent of perennial ryegrass (Lolium perenne). The map supplements a previous map of this population by having markers in common with several other Lolium spp. maps including EST-SSR anchor markers from a consensus map published by other researchers. A QTL analysis was conducted with disease severity and infection type data obtained by controlled inoculation of the population with each of two previously characterized pathotypes of Puccinia graminis subsp. graminicola that differ in virulence to different host plant genotypes in the F1 population. Each pathotype activated a specific QTL on one linkage group (LG): qLpPg1 on LG7 for pathotype 101, or qLpPg2 on LG1 for pathotype 106. Both pathotypes also activated a third QTL in common, qLpPg3 on LG6. Anchor markers, present on a consensus map, were located in proximity to each of the three QTL. These QTL had been detected also in previous experiments in which a genetically heterogeneous inoculum of the stem rust pathogen activated all three QTL together. The results of this and a previous study are consistent with the involvement of the pathotype-specific QTL in pathogen recognition and the pathotype-nonspecific QTL in a generalized resistance response. By aligning the markers common to other published reports, it appears that two and possibly all three of the stem rust QTL reported here are in the same general genomic regions containing some of the L. perenne QTL reported to be activated in response to the crown rust pathogen (P. coronata).