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The genetic and functional analysis of flavor in commercial tomato : the FLORAL4 gene underlies a QTL for floral aroma volatiles in tomato fruit
Tikunov, Yury M. ; Roohanitaziani, Raana ; Meijer-Dekens, Fien ; Molthoff, Jos ; Paulo, Joao ; Finkers, Richard ; Capel, Iris ; Carvajal Moreno, Fatima ; Maliepaard, Chris ; Nijenhuis-de Vries, Mariska ; Labrie, Caroline W. ; Verkerke, Wouter ; Heusden, Adriaan W. van; Eeuwijk, Fred van; Visser, Richard G.F. ; Bovy, Arnaud G. - \ 2020
The Plant Journal (2020). - ISSN 0960-7412
2-phenylethanol - aroma - flavor - quantitative trait loci - Solanum lycopersicum - tomato - volatiles
Tomato (Solanum lycopersicum L.) has become a popular model for genetic studies of fruit flavor in the last two decades. In this article we present a study of tomato fruit flavor, including an analysis of the genetic, metabolic and sensorial variation of a collection of contemporary commercial glasshouse tomato cultivars, followed by a validation of the associations found by quantitative trait locus (QTL) analysis of representative biparental segregating populations. This led to the identification of the major sensorial and chemical components determining fruit flavor variation and detection of the underlying QTLs. The high representation of QTL haplotypes in the breeders’ germplasm suggests that there is great potential for applying these QTLs in current breeding programs aimed at improving tomato flavor. A QTL on chromosome 4 was found to affect the levels of the phenylalanine-derived volatiles (PHEVs) 2-phenylethanol, phenylacetaldehyde and 1-nitro-2-phenylethane. Fruits of near-isogenic lines contrasting for this locus and in the composition of PHEVs significantly differed in the perception of fruity and rose-hip-like aroma. The PHEV locus was fine mapped, which allowed for the identification of FLORAL4 as a candidate gene for PHEV regulation. Using a gene-editing-based (CRISPR-CAS9) reverse-genetics approach, FLORAL4 was demonstrated to be the key factor in this QTL affecting PHEV accumulation in tomato fruit.
Alleles to Enhance Antioxidant Content in Maize-A Genome-Wide Association Approach
Alves, Mara Lisa ; Bento-Silva, Andreia ; Carbas, Bruna ; Gaspar, Daniel ; Paulo, Manuel ; Brites, Claúdia ; Mendes-Moreira, Pedro ; Brites, Carla Moita ; Bronze, Maria Do Rosário ; Malosetti, Marcos ; Eeuwijk, Fred Van; Vaz Patto, Maria Carlota - \ 2020
Journal of Agricultural and Food Chemistry 68 (2020)13. - ISSN 0021-8561 - p. 4051 - 4061.
carotenoids - color - phenolic compounds - quantitative trait loci - tocopherols
The interest in antioxidant compound breeding in maize (Zea mays L.), a major food crop, has increased in recent years. However, breeding of antioxidant compounds in maize can be hampered, given the complex genetic nature of these compounds. In this work, we followed a genome-wide association approach, using a unique germplasm collection (containing Portuguese germplasm), to study the genetic basis of several antioxidants in maize. Sixty-seven genomic regions associated with seven antioxidant compounds and two color-related traits were identified. Several significant associations were located within or near genes involved in the carotenoid (Zm00001d036345) and tocopherol biosynthetic pathways (Zm00001d017746). Some indications of a negative selection against α-tocopherol levels were detected in the Portuguese maize germplasm. The strongest single nucleotide polymorphism (SNP)-trait associations and the SNP alleles with larger effect sizes were pinpointed and set as priority for future validation studies; these associations detected now constitute a benchmark for developing molecular selection tools for antioxidant compound selection in maize.
Genome-wide association study for αS1- and αS2-casein phosphorylation in Dutch Holstein Friesian
Fang, Z.H. ; Bovenhuis, H. ; Valenberg, H.J.F. van; Martin, P. ; Duchemin, S.I. ; Huppertz, T. ; Visker, M.H.P.W. - \ 2019
Journal of Dairy Science 102 (2019)2. - ISSN 0022-0302 - p. 1374 - 1385.
milk protein composition - post-translational modification - quantitative trait loci
Phosphorylation of caseins (CN) is a crucial post-translational modification that allows caseins to form colloid particles known as casein micelles. Both αS1- and αS2-CN show varying degrees of phosphorylation (isoforms) in cow milk and were suggested to be more relevant for stabilizing internal micellar structure than β- and κ-CN. However, little is known about the genetic background of individual αS2-CN phosphorylation isoforms and the phosphorylation degrees of αS1- and αS2-CN (αS1-CN PD and αS2-CN PD), defined as the proportion of isoforms with higher degrees of phosphorylation in total αS1- and αS2-CN, respectively. We aimed to identify genomic regions associated with these traits using 50K single nucleotide polymorphisms for 1,857 Dutch Holstein Friesian cows. A total of 10 quantitative trait loci (QTL) regions were identified for all studied traits on 10 Bos taurus autosomes (BTA1, 2, 6, 9, 11, 14, 15, 18, 24, and 28). Regions associated with multiple traits were found on BTA1, 6, 11, and 14. We showed 2 QTL regions on BTA1, one affecting αS2-CN production and the other harboring the SLC37A1 gene, which encodes a phosphorus antiporter and affects αS1- and αS2-CN PD. The QTL on BTA6 harbors the casein gene cluster and affects individual αS2-CN phosphorylation isoforms. The QTL on BTA11 harbors the PAEP gene that encodes for β-lactoglobulin and affects relative concentrations of αS2-CN-10P and αS2-CN-11P as well as αS1-CN PD and αS2-CN PD. The QTL on BTA14 harbors the DGAT1 gene and affects relative concentrations of αS2-CN-10P and αS2-CN-11P as well as αS1-CN PD and αS2-CN PD. Our results suggest that effects of identified genomic regions on phosphorylation of αS1- and αS2-CN are related to changes in milk synthesis and phosphorus secretion in milk. The actual roles of SLC37A1, PAEP, and DGAT1 in αS1- and αS2-CN phosphorylation in Dutch Holstein Friesian require further investigation.
Disentangling hexaploid genetics : towards DNA-informed breeding for postharvest performance in chrysanthemum
Geest, Geert van - \ 2017
Wageningen University. Promotor(en): R.G.F. Visser, co-promotor(en): U. van Meeteren; P.F.P. Arens. - Wageningen : Wageningen University - ISBN 9789463436427 - 142
chrysanthemum - plant breeding - postharvest quality - hexaploidy - polyploidy - quantitative trait loci - phenotypes - linkage mapping - metabolomics - polymorphism - dna - chrysanthemum - plantenveredeling - kwaliteit na de oogst - hexaploïdie - polyploïdie - loci voor kwantitatief kenmerk - fenotypen - koppelingskartering - metabolomica - polymorfisme - dna
DNA-informed selection can strongly improve the process of plant breeding. It requires the detection of DNA polymorphisms, calculation of genetic linkage, access to reliable phenotypes and methods to detect genetic loci associated with phenotypic traits of interest. Cultivated chrysanthemum is an outcrossing hexaploid with an unknown mode of inheritance. This complicates the development of resources and methods that enable the detection of trait loci. Postharvest performance is an essential trait in chrysanthemum, but is difficult to measure. This makes it an interesting but challenging trait to phenotype and detect associated genetic loci. In this thesis I describe the development of resources and methods to enable phenotyping for postharvest performance, genetic linkage map construction and detection of quantitative trait loci in hexaploid chrysanthemum.
Postharvest performance is a complicated trait because it is related to many different disorders that reduce quality. One of these disorders in chrysanthemum is disk floret degreening, which occurs after long storage. In chapter 2, we show that degreening can be prevented by feeding the flower heads with sucrose, suggesting carbohydrate starvation plays a role in the degreening process. To investigate the response to carbohydrate starvation of genotypes with different sensitivity to disk floret degreening, we investigated the metabolome of sugar-fed and carbohydrate-starved disk florets by 1H-NMR and HPAEC. We show that the metabolome is severely altered at carbohydrate starvation. In general, starvation results in an upregulation of amino acid and secondary metabolism. Underlying causes of genotypic differences explaining variation in disk floret degreening in the three investigated genotypes remained to be elucidated, but roles of regulation of respiration rate and camphor metabolism were posed as possible candidates.
In chapter 3, disk floret degreening was found to be the most important postharvest disorder after 3 weeks of storage among 44 white chrysanthemum cultivars. To investigate the inheritance of disk floret degreening, we crossed two genotypes with opposite phenotypic values of both disk floret degreening and carbohydrate content to obtain a population segregating for disk floret degreening. To phenotype the cultivar panel and the bi-parental population precisely and in a high throughput manner, we developed a method that quantified colour of detached capitula over time. This method was validated with visual observations of disk floret degreening during vase life tests. In a subset of the bi-parental population we measured carbohydrate content of the disk florets at harvest. The amount of total carbohydrates co-segregated with sensitivity to degreening, which shows that the difference in disk floret degreening sensitivity between the parents could be explained by their difference in carbohydrate content. However, the correlation was rather weak, indicating carbohydrate content is not the only factor playing a role.
In order to develop resources for DNA-informed breeding, one needs to be able to characterize DNA polymorphisms. In chapter 4, we describe the development of a genotyping array containing 183,000 single nucleotide polymorphisms (SNPs). These SNPs were acquired by sequencing the transcriptome of 13 chrysanthemum cultivars. By comparing the genomic dosage based on the SNP assay and the dosage as estimated by the read depth from the transcriptome sequencing data, we show that alleles are expressed conform the genomic dosage, which contradicts to what is often found in disomic polyploids. In line with this finding, we conclusively show that cultivated chrysanthemum exhibits genome-wide hexasomic inheritance, based on the segregation ratios of large numbers of different types of markers in two different populations.
Tools for genetic analysis in diploids are widely available, but these have limited use for polyploids. In chapter 5, we present a modular software package that enables genetic linkage map construction in tetraploids and hexaploids. Because of the modularity, functionality for other ploidy levels can be easily added. The software is written in the programming language R and we named it polymapR. It can generate genetic linkage maps from marker dosage scores in an F1 population, while taking the following steps: data inspection and filtering, linkage analysis, linkage group assignment and marker ordering. It is the first software package that can handle polysomic hexaploid and partial polysomic tetraploid data, and has advantages over other polyploid mapping software because of its scalability and cross-platform applicability.
With the marker dosage scores of the bi-parental F1 population from the genotyping array and the developed methods to perform linkage analysis we constructed an integrated genetic linkage map for the hexaploid bi-parental population described in chapter 3 and 4. We describe this process in chapter 6. With this integrated linkage map, we reconstructed the inheritance of parental haplotypes for each individual, and expressed this as identity-by-descent (IBD) probabilities. The phenotypic data on disk floret degreening sensitivity that was acquired as described in chapter 3, was used in addition to three other traits to detect quantitative trait loci (QTL). These QTL were detected based on the IBD probabilities of 1 centiMorgan intervals of each parental homologue. This enabled us to study genetic architecture by estimating the effects of each separate allele within a QTL on the trait. We showed that for many QTL the trait was affected by more than two alleles.
In chapter 7, the findings in this thesis are discussed in the context of breeding for heterogeneous traits, the implications of the mode of inheritance for breeding and the advantages and disadvantages of polyploidy in crop breeding. In conclusion, this thesis provides in general a significant step for DNA-informed breeding in polysomic hexaploids, and for postharvest performance in chrysanthemum in particular.
Prospects of whole-genome sequence data in animal and plant breeding
Binsbergen, Rianne van - \ 2017
Wageningen University. Promotor(en): R.F. Veerkamp; F.A. Eeuwijk, co-promotor(en): M.P.L. Calus. - Wageningen : Wageningen University - ISBN 9789463431903 - 220
next generation sequencing - dna sequencing - quantitative trait loci - cattle - genomics - solanum lycopersicum - animal breeding - plant breeding - next generation sequencing - dna-sequencing - loci voor kwantitatief kenmerk - rundvee - genomica - solanum lycopersicum - dierveredeling - plantenveredeling
The rapid decrease in costs of DNA sequencing implies that whole-genome sequence data will be widely available in the coming few years. Whole-genome sequence data includes all base-pairs on the genome that show variation in the sequenced population. Consequently, it is assumed that the causal mutations (e.g. quantitative trait loci; QTL) are included, which allows testing a given trait directly for association with a QTL, and might lead to discovery of new QTL or higher accuracies in genomic predictions compared to currently available marker panels. The main aim of this thesis was to investigate the benefits of using whole-genome sequence data in breeding of animals and plants compared to currently available marker panels. First the potential and benefits of using whole-genome sequence data were studied in (dairy) cattle. Accuracy of genotype imputation to whole-genome sequence data was generally high, depending on the used marker panel. In contrast to the expectations, genomic prediction showed no advantage of using whole-genome sequence data compared to a high density marker panel. Thereafter, the use of whole-genome sequence data for QTL detection in tomato (S. Lycopersicum) was studied. In a recombinant inbred line (RIL) population, more QTL were found when using sequence data compared to a marker panel, while increasing marker density was not expected to provide additional power to detect QTL. Next to the RIL population, also in an association panel it was shown that, even with limited imputation accuracy, the power of a genome-wide association study can be improved by using whole-genome sequence data. For successful application of whole-genome sequence data in animals or plants, genotype imputation will remain important to obtain accurate sequence data for all individuals in a cost effective way. Sequence data will increase the power of QTL detection in RIL populations, association panels or outbred populations. Added value of whole-genome sequence data in genomic prediction will be limited, unless more information is known about the biological background of traits and functional annotations of DNA. Also statistical models that incorporate this information and that can efficiently handle large datasets have to be developed.
Unraveling the genetics of Botrytis cinerea resistance in Gerbera hybrida
Fu, Yiqian - \ 2017
Wageningen University. Promotor(en): R.G.F. Visser, co-promotor(en): P.F.P. Arens; J.M. van Tuyl. - Wageningen : Wageningen University - ISBN 9789463431811 - 159
gerbera - plant pathogenic fungi - botrytis cinerea - disease resistance - genetic mapping - transcriptomics - quantitative trait loci - plant breeding - gerbera - plantenziekteverwekkende schimmels - botrytis cinerea - ziekteresistentie - genetische kartering - transcriptomica - loci voor kwantitatief kenmerk - plantenveredeling
Gerbera hybrida is one of the top five cut flowers. It is well-known to people for its variation in flower color and patterning. Gerbera breeding at the moment is done using conventional methods which are based on a phenotypic selection. This has drawbacks in breeding speed and efficiency, especially for complex traits like disease resistance. Gerbera gray mold, promoted by high humidity during the production in greenhouses or by an accumulation of condensate during transportation, is a considerable threat to the gerbera production. Gerbera gray mold is caused by Botrytis cinerea and plant resistance to B. cinerea is considered to be a polygenic trait that needs the contribution of multiple loci, and on top of that is highly affected by the environment. Conventional breeding might be inefficient for improving Botrytis resistance in gerbera.
In this study, the transcriptomes of four parents of two gerbera populations were sequenced using Illumina paired-end sequencing. Transcriptome data provides a resource for genetic dissection and an insight to explore gene functions for this ornamental crop. To identify the QTL regions leading to the phenotypic variation in Botrytis resistance, and establishing a relationship between marker genotype and phenotypic variation for marker assisted selection (MAS), genetic linkage maps were constructed with SNP markers in the two F1 segregating populations. A total of 20 QTLs were identified in the parental maps of the two populations. The number of QTLs found and the explained variance of most QTLs detected reflects the complex mechanism of Botrytis disease response. Narrowing down the QTL region and identifying the causal gene(s) underlying a QTL could maximize the effective use of MAS in breeding. Homologs of known functional genes involved in Botrytis resistance from other species were obtained in gerbera and SNP markers identified and mapped. Twenty-nine candidate genes were mapped and seven candidate genes could be mapped on both populations. Seven candidate genes were located in the vicinity of the QTLs detected. The co-localization of QTLs with CGs gives an indication that these candidate genes could probably be involved in resistance to Botrytis and provide a more precise possibility to use MAS in gerbera breeding in the future. A tobacco rattle virus (TRV) based gene silencing system which was used to inspect the function of two candidate genes. The two CGs are the homologs of the genes responsible for Botrytis resistance in tomato and both mapped in QTL regions related to Botrytis resistance in gerbera ray floret test. Silencing the two genes by VIGS, showed smaller lesion sizes upon Botrytis infection on gerbera ray florets compared with the controls.
The entire research went from the generation of four parental transcriptome data sets to development of SNP markers (Chapter 2), construction of genetic maps and to mapping QTLs for Botrytis resistance (Chapter 3). This was further on combined with candidate gene searching in other crops, querying and mapping homologous genes (Chapter 4) and characterizing the candidate genes which co-localized with QTLs (Chapter 5). The whole process not only helped us to unravel the genetics of Botrytis resistance in gerbera and develop genetic tools for gerbera improvement, but also could serve as guidance for developing marker-assisted selection for other ornamental plants from the beginning.
Genetic studies towards elucidation of drought tolerance of potato
Tessema, Biructa Bekele - \ 2017
Wageningen University. Promotor(en): R.G.F. Visser, co-promotor(en): C.G. van der Linden. - Wageningen : Wageningen University - ISBN 9789463431958 - 195
solanum tuberosum - potatoes - drought resistance - plant breeding - genetic analysis - quantitative trait loci - solanum tuberosum - aardappelen - droogteresistentie - plantenveredeling - genetische analyse - loci voor kwantitatief kenmerk
Drought is a major threat to agricultural production, which makes drought tolerance a prime target for breeding approaches towards crop improvement. Drought is a complex polygenic trait and poses a challenge for drought tolerance breeding. Improving crops for drought tolerance at least requires the knowledge of the physiological mechanisms of the contributing traits and their genetic control. Thus, identification of genetic variation for drought tolerance is the first step towards drought tolerance breeding. The effect of drought stress on potato tuber yield and quality is very significant as potato is considered sensitive to water shortage. To understand the genetic factors underlying drought tolerance in potato, we performed drought stress experiments under green house and field conditions with moderate drought and severe drought stress conditions, respectively. In the field, potato genotypes were exposed to severe drought stress for two consecutive years starting from tuber initiation, which progressed to severe drought stress. In addition, we examined potato cultivars for moderate drought tolerance under greenhouse conditions where water application was reduced 50-60% from optimum amount starting from stolon formation. Morphological and physiological trait data were collected that allowed precise monitoring of the drought response of potato. Phenotypic data collected under severe drought stress conditions which includes traits like shoot and root biomass (fresh and dry), yield and chlorophyll content were used for QTL mapping while data collected under moderate drought stress conditions was used for genome wide association mapping. With QTL mapping, 60 QTLs were identified controlling those traits both under well-watered and drought stress conditions. In the drought tolerance evaluation of the potato cultivars under greenhouse conditions we identified significant marker trait associations for both above- and belowground traits. Many of the QTLs detected for drought tolerance traits were specific to either moderate or severe drought tolerance conditions. However, a few QTLs showed an overlap between these drought stress environments. This demonstrates the presence of common genomic regions controlling drought tolerance traits under moderate and severe drought stress conditions. In addition, from the two years of field drought stress experiments we selected a subset of genotypes that showed contrasting responses to drought stress. We used these genotypes to further examine the relationship between canopy development and tuber yield under severe drought stress conditions. Canopy development was measured for several time points and the data were used for curve fitting. From the curve-fit, parameters related to the different developmental phase of canopy were extracted. We observed that there is positive correlation between canopy parameters and tuber yield under drought stress conditions. The evaluation of potato for drought tolerance under field and greenhouse conditions has resulted in the identification of several QTLs that can be interesting to be used for enhancing drought tolerance in potato. Furthermore, the use of model derived parameters gave a better insight into the relationship between canopy development and tuber yield under water stress conditions.
Using probabilistic graphical models to reconstruct biological networks and linkage maps
Wang, Huange - \ 2017
Wageningen University. Promotor(en): F.A. Eeuwijk, co-promotor(en): J. Jansen. - Wageningen : Wageningen University - ISBN 9789463431538 - 150
probabilistic models - models - networks - linkage - mathematics - statistics - quantitative trait loci - phenotypes - simulation - waarschijnlijkheidsmodellen - modellen - netwerken - koppeling - wiskunde - statistiek - loci voor kwantitatief kenmerk - fenotypen - simulatie
Probabilistic graphical models (PGMs) offer a conceptual architecture where biological and mathematical objects can be expressed with a common, intuitive formalism. This facilitates the joint development of statistical and computational tools for quantitative analysis of biological data. Over the last few decades, procedures based on well-understood principles for constructing PGMs from observational and experimental data have been studied extensively, and they thus form a model-based methodology for analysis and discovery. In this thesis, we further explore the potential of this methodology in systems biology and quantitative genetics, and illustrate the capabilities of our proposed approaches by several applications to both real and simulated omics data.
In quantitative genetics, we partition phenotypic variation into heritable, genetic, and non-heritable, environmental, parts. In molecular genetics, we identify chromosomal regions that drive genetic variation: quantitative trait loci (QTLs). In systems genetics, we would like to answer the question of whether relations between multiple phenotypic traits can be organized within wholly or partially directed network structures. Directed edges in those networks can be interpreted as causal relationships, causality meaning that the consequences of interventions are predictable: phenotypic interventions in upstream traits, i.e. traits occurring early in causal chains, will produce changes in downstream traits. The effect of a QTL allele can be considered to represent a genetic intervention on the phenotypic network. Various methods have been proposed for statistical reconstruction of causal phenotypic networks exploiting previously identified QTLs. In chapter 2, we present a novel heuristic search algorithm, namely the QTL+phenotype supervised orientation (QPSO) algorithm, to infer causal relationships between phenotypic traits. Our algorithm shows good performance in the common, but so far uncovered case, where some traits come without QTLs. Therefore, our algorithm is especially attractive for applications involving expensive phenotypes, like metabolites, where relatively few genotypes can be measured and population size is limited.
Standard QTL mapping typically models phenotypic variations observable in nature in relation to genetic variation in gene expression, regardless of multiple intermediate-level biological variations. In chapter 3, we present an approach integrating Gaussian graphical modeling (GGM) and causal inference for simultaneous modeling of multilevel biological responses to DNA variations. More specifically, for ripe tomato fruits, the dependencies of 24 sensory traits on 29 metabolites and the dependencies of all the sensory and metabolic traits further on 21 QTLs were investigated by three GGM approaches including: (i) lasso-based neighborhood selection in combination with a stability approach to regularization selection, (ii) the PC-skeleton algorithm and (iii) the Lasso in combination with stability selection, and then followed by the QPSO algorithm. The inferred dependency network which, though not essentially representing biological pathways, suggests how the effects of allele substitutions propagate through multilevel phenotypes. Such simultaneous study of the underlying genetic architecture and multifactorial interactions is expected to enhance the prediction and manipulation of complex traits. And it is applicable to a range of population structures, including offspring populations from crosses between inbred parents and outbred parents, association panels and natural populations.
In chapter 4, we report a novel method for linkage map construction using probabilistic graphical models. It has been shown that linkage map construction can be hampered by the presence of genotyping errors and chromosomal rearrangements such as inversions and translocations. Our proposed method is proven, both theoretically and practically, to be effective in filtering out markers that contain genotyping errors. In particular, it carries out marker filtering and ordering simultaneously, and is therefore superior to the standard post-hoc filtering using nearest-neighbour stress. Furthermore, we demonstrate empirically that the proposed method offers a promising solution to genetic map construction in the case of a reciprocal translocation.
In the domain of PGMs, Bayesian networks (BNs) have proven, both theoretically and practically, to be a promising tool for the reconstruction of causal networks. In particular, the PC algorithm and the Metropolis-Hastings algorithm, which are representatives of mainstream methods to BN structure learning, are reported to have been successfully applied to the field of biology. In view of the fact that most biological systems exist in the form of random network or scale-free network, in chapter 5 we compare the performance of the two algorithms in constructing both random and scale-free BNs. Our simulation study shows that for either type of BN, the PC algorithm is superior to the M-H algorithm in terms of timeliness; the M-H algorithm is preferable to the PC algorithm when the completeness of reconstruction is emphasized; but when the fidelity of reconstruction is taken into account, the better one of the two algorithms varies from case to case. Moreover, whichever algorithm is adopted, larger sample sizes generally permit more accurate reconstructions, especially in regard to the completeness of the resulting networks.
Finally, chapter 6 presents a further elaboration and discussion of the key concepts and results involved in this thesis.
From species to trait evolution in Aethionema (Brassicaceae)
Mohammadin, Setareh - \ 2017
Wageningen University. Promotor(en): M.E. Schranz. - Wageningen : Wageningen University - ISBN 9789463431385 - 125
brassicaceae - evolution - rna - genomes - genetic diversity - phytogeography - glucosinolates - quantitative trait loci - next generation sequencing - brassicaceae - evolutie - rna - genomen - genetische diversiteit - plantengeografie - glucosinolaten - loci voor kwantitatief kenmerk - next generation sequencing
The plant family Brassicaceae (or crucifers) is an economically important group that includes many food crops (e.g. cabbages and radishes), horticultural species (e.g. Draba, Iberis, Lunaria), and model plant species (particularly Arabidopsis thaliana). Because of the fundamental importance of A. thaliana to plant biology, it makes the Brassicaceae an ideal system for comparative genomics and to test wider evolutionary, ecological and speciation hypotheses. One such hypothesis is the ‘Whole Genome Duplication Radiation Lag Time’ (WGD-RLT) model for the role of polyploidy on the evolution of important plant families such as the Brassicaceae. The WGD-RLT model indicates a higher rate of diversification of a core-group compared to its sister group, due to a lag time after a whole genome duplication event that made it possible for novel traits or geo- or ecological events to increase the core groups diversification rate.
Aethionema is the species-poor sister genus of the core Brassicaceae and hence is at an important comparative position to analyse trait and genomic evolution of the species-rich core group. Aethionema species occur mainly in the western Irano-Turanian region, which is concordantly the biodiversity hotspot of the Brassicaceae family. Moreover comparing Aethionema to the Brassicaceae core group can help us to understand and test the ‘WGD-RLT’ model. However to be able to do so we first need to know more about Aethionema. In this thesis, I investigated various levels of evolutionary change (from macro, to micro to trait evolution) within the genus Aethionema, with a major focus the emerging model species Aethionema arabicum.
Next generation sequencing has made it possible to use the genomes of many species in a comparative framework. However, the formation of proteins and enzymes, and in the end the phenotype of the whole plant, relies on transcription from particular regions of the genome including genes. Hence, the transcriptome makes it possible to assess the functional parts of the genome. However, the functional part of the genome not only relies on the protein coding genes. Gene regulatory elements like promoters and long non-coding RNAs function as regulators of gene expression and hence are involved in increasing or decreasing transcription. In Chapter 2 I used the transcriptome of four different Aethionema species to understand the lineage specificity of these long non-coding RNAs. Moreover in a comparison with the Brassicaceae core group and Brassicaceae’s sister family the Cleomaceae I show that although the position of long non-coding RNAs can be conserved, their sequences do not have to be.
Most of the Aethionema species occur in the Irano-Turanian region, a politically instable region, making it hard for scientist to collect from. However the natural history collections made throughout the last centuries are a great resource. Combing these collections with the newest sequencing techniques, e.g. next generation sequencing, have allowed me to infer the phylogeny of ~75% of the known Aethionema species in a time calibrated and historical biogeographical framework. Hence, I was able to establish that Aethionema species likely originated from the Anatolian Diagonal and that major geological events like the uplift of the Turkish and Iranian plateau have had a hand in their speciation (Chapter 3).
To examine species-level processes I sequenced and analysed transcriptomes of eight Ae. arabicum accessions coming from Cyprus, Iran and Turkey to investigate population structure, genetic diversity and local adaptation (Chapter 4). The most prominent finding was a ploidy difference between the Iranian and Turkish/Cypriotic lines, whereby the former were (allo)tetraploid and the latter diploid. The tetraploid Iranian lines seem to have one set of alleles from the Turkish/Cypriotic gene-pool. However we do not know where the other alleles come from. In addition to the differences in ploidy level there are also differences in glucosinolate defence compounds between these two populations (Iranian vs Turkish/Cypriotic), with the Iranian lines lacking the diversity and concentration of indolic glucosinolates that the Turkish/Cypriotic lines have. This chapter serves as a good resource and starting point for future research in the region, maybe by using the natural history collections that are at hand.
Glucosinolates (i.e. mustard oils) are mainly made by Brassicales species, with their highest structural diversity in the Brassicaceae. In Chapter 5, I examined two Ae. arabicum lines (CYP and TUR) and their recombinant inbred lines to assess glucosinolate composition in different tissues and throughout the plants development. The levels of glucosinolates in the leaves changed when Ae. arabicum went from vegetative to a reproductive state. Moreover, a major difference in glucosinolate content (up to 10-fold) between CYP and TUR indicates a likely regulatory pathway outside of the main glucosinolate biosynthesis pathway. Multi-trait and multi-environment QTL analyses based on leaves, reproductive tissues and seeds identified a single major QTL. Fine mapping this region reduced the interval to only fifteen protein coding genes, including the two most intriguing candidates: FLOWERING LOCUS C (FLC) and the sulphate transporter SULTR2;1. These findings show an interesting correlation between development and defence.
Finally, Chapter 6 gives a final discussion of this thesis and its results. It brings the different topics together, put them in a bigger picture and look forward to new research possibilities.
The allo-octoploid strawberry: simply complex
Dijk, Thijs van - \ 2016
Wageningen University. Promotor(en): Richard Visser, co-promotor(en): Eric van de Weg. - Wageningen : Wageningen University - ISBN 9789462579637 - 185
fragaria ananassa - strawberries - polyploidy - microsatellites - linkage mapping - genome analysis - quantitative trait loci - genetic mapping - flowering - plant breeding - fragaria ananassa - aardbeien - polyploïdie - microsatellieten - koppelingskartering - genoomanalyse - loci voor kwantitatief kenmerk - genetische kartering - bloei - plantenveredeling
The garden strawberry (Fragaria x ananassa) is a fruit species that was developed through human intervention less than 300 years ago. Currently, it is the most important soft fruit in both production as well as value and renowned for its deliciousness. There are many challenges in growing such a delicate fruit, many of which have been overcome through improved cultivation techniques and breeding. The perishability of the product is, however, not the only challenge faced by strawberry breeders. In terms of genome composition, strawberry appears to have accumulated a wonderful array of obstacles to genetic studies. It is a vegetatively propagated allo-octoploid outbreeder, and only few crop species are worse of in this respect. Many of the molecular genetic ground work is therefore performed in its diploid ancestor, the woodland strawberry Fragaria vesca, which was sequenced in 2011. However, since nearly all strawberries that are eaten are octoploid, genetic research can’t linger at the wild diploids forever. In this thesis we developed new tools and analysis methods for genetic studies in the allo-octoploid strawberry and subsequently applied these methods in the detection of marker-trait associations.
The purpose of Chapter 2 was to develop a method to interpret the complex peak patterns generated by microsatellites in octoploid strawberry in such a way that we ended up with as much information as one would expect to retrieve from a microsatellite in a diploid system. This information could then be used to generate high quality linkage maps for the different sub-genomes and allow for easy alignment and comparison. We named the method MADCE, which stands for Microsatellite Allele Dose & Configuration Establishment. In the MADCE methodology, we first need to determine the dose of each allele present in an individual. For this we used the signal of fluorescent microsatellite peaks in relation to the total fluorescent signal generated by all peaks for that microsatellite. We then used the disomic inheritance of strawberry to establish the allelic configuration of each different homoeologue (subgenome). The repulsion of alleles from the same subgenome in offspring allowed us to form subgenomic pairs of alleles. We found that in single cross mapping populations, the deployment of our method was fairly easy due to the high number of offspring that can be used to establish repulsion between alleles. However, for pedigreed breeding germplasm this was another matter, as generally only few offspring were available. For this we added some additional tricks to the MADCE method, although some uncertainty about the configuration would remain for problematic lines and alleles.
In Chapter 3 we used the MADCE method from Chapter 2 to generate a genome wide linkage map for the Holiday x Korona (HxK) mapping population. This linkage map was to be used in subsequent experiments for QTL discovery as well as provide the strawberry community with a highly detailed map consisting not only of marker distances, but allele and haplotype configuration of the parents Holiday and Korona as well. The haplotype information revealed that inbreeding (homozygosity) levels in Holiday were similar to the levels expected from its pedigree, but that inbreeding levels of Korona were more than three times higher than expected, which could be resultant from selection pressure enacted by breeders. Selection pressure could also be causal to our discovery that the kinship between the two cultivars was twice as high as expected from their shared ancestry. Another discovery was a large inversion on one of the subgenomes of linkage group 2 (D). Up until the publication of our linkage map this inversion had not been reported in other linkage maps. Another innovation was our attempt at giving a biological or evolutionary meaning to the denomination of the linkage groups by arranging them according to similarity to the diploid ancestor F. vesca, based on F. vesca derived primer amplification efficiencies. The HxK map has been used in several (ongoing) research projects outside of our research group and has contributed to the development of the 90k Axiom SNP array for cultivated strawberry.
In Chapter 4 we performed a QTL mapping study for disease resistance against the problematic pathogen Phytophthora cactorum, which causes crown rot in strawberry plants. In this study we used two different mapping populations: the Holiday x Korona (HxK) population from the previous chapter as well as E1998-142 x Elsanta (ExEls), developed more specifically for the purpose of finding resistance against P. cactorum. The HxK and ExEls populations were phenotyped over three years (2008, 2010 and 2011) under different seasons and conditions. The correlation between years for was quite low for both populations (ranging from 0.18 to 0.47), indicating a large environmental effect on disease pressure. Results from the QTL analysis showed that most QTLs were small in effect and only just above the statistical significance threshold. Only for ExEls we uncovered two QTLs with relatively high significance levels, but none were significant in all three years. Because of the high environmental influence, and the desire to have QTLs that are robust over environments, we used the average of all three years (AOTY) as an additional phenotype. When we used the AOTY trait, the QTL on LG7D became stronger than for any of the individual years. Whereas for the LG7C QTL the significance dropped to just below threshold levels. These results indicated that removing environmental noise through averaging over experiments is a good way to uncover the most reliable and therefore more valuable to a breeding program.
In Chapter 5 we investigated the genetics behind two different flowering habits that are grown commercially worldwide: seasonal flowering habit (SF) and perpetual flowering (PF) These varieties initiate flowering under long days, and can therefore produce fruit for a much longer period: throughout the summer and early fall. Evidence from literature and practical breeding suggested that PF is under dominant control. We decided to treat PF as a qualitative trait and divided two small mapping populations into PF and SF individuals. After screening several microsatellites, we found one locus that completely cosegregated with the PF trait at the bottom of LG4D. At the moment of mapping, a paper was published which mapped the same trait to the same location. We found that there were two very clear candidate genes within our QTL interval, FaCDF2 and FaFT2, which were homologous to genes that are major factors in the flowering pathway of Arabidopsis and many other plant species. We then sequenced the FaCDF2 gene from a number of distinct PF and SF cultivars. This resulted in the discovery of two quite distinct allelic variants, one of which was present in all PF cultivars. However this variant was also present in some of the SF cultivars, indicating that either FaCDF2 is not the causal gene, or that other loci can have a qualitative effect on the switch from SF to PF. We then performed microsatellite haplotyping on hundreds of cultivars and this revealed that all PF varieties of all origins carry the same haplotype in the PF QTL region, and that there weren’t any recombinations between the candidate genes FaCDF2 and FaFT2, which are 250kb apart on the physical genome. This makes it still undecided which of these two candidate genes are causal to the PF trait. Another interesting result from the haplotyping was that the complete PF haplotype was present with moderate frequency in SF varieties as well. Not only does this suggest a common origin, it also complicates the establishment of a theory for the mechanisms behind perpetual flowering in cultivated strawberry. So far we have not been able to establish whether the PF haplotype that is present in SF cultivars is functionally distinct from the PF haplotype in PF cultivars. All we know is that it does not confer perpetual flowering in these SF cultivars, and further experiments would be needed to find out the exact mechanism behind perpetual flowering.
In the general discussion (Chapter 6), the results of this thesis were placed in the broader context of science in general and plant breeding in particular.
Statistical methods for QTL mapping and genomic prediction of multiple traits and environments: case studies in pepper
Alimi, Nurudeen Adeniyi - \ 2016
Wageningen University. Promotor(en): Fred van Eeuwijk, co-promotor(en): Marco Bink. - Wageningen : Wageningen University - ISBN 9789462579361 - 153
capsicum - statistical analysis - statistics - genomics - quantitative trait loci - quantitative traits - quantitative methods - genetics - crop yield - capsicum - statistische analyse - statistiek - genomica - loci voor kwantitatief kenmerk - kwantitatieve kenmerken - kwantitatieve methoden - genetica - gewasopbrengst
In this thesis we describe the results of a number of quantitative techniques that were used to understand the genetics of yield in pepper as an example of complex trait measured in a number of environments. Main objectives were; i) to propose a number of mixed models to detect QTLs for multiple traits and multiple environments, ii) to extend the multi-trait QTL models to a multi-trait genomic prediction model, iii) to study how well the complex trait yield can be indirectly predicted from its component traits, and iv) to understand the ‘causal’ relationships between the target trait yield and its component traits.
The thesis is part of an EU-FP7 project “Smart tools for Prediction and Improvements of Crop Yield” (SPICY- http://www.spicyweb.eu/). This project generated phenotypic data from four environments using 149 individuals from the sixth generation of recombinant inbred lines obtained from intraspecific cross between large – fruited inbred pepper cultivar ‘Yolo Wonder’ (YW) and the hot pepper cultivar ‘Criollo de Morelos 334’ (CM 334). A total of 16 physiological traits were evaluated across the four trials and various types of genetic parameters were estimated. In a first analysis, the traits were univariately analyzed using linear mixed model. Trait heritabilities were generally large (ranging between 0.43 – 0.96 with an average of 0.86) and mostly comparable across trials while many of the traits displayed heterosis and transgression. The same QTLs were detected across the four trials, though QTL magnitude differed for many of the traits. We also found that some QTLs affected more than one trait, suggesting QTL pleiotropy (a QTL region affecting more than one trait). We discussed our results in the light of previously reported QTLs for these and similar traits in pepper.
We addressed the presence of genotype-by-environment interaction (GEI) in yield and the other traits through a multi-environment (ME) mixed model methodology with terms for QTL-by-environment interaction (QEI). We opined that yield would benefit from joint analysis with other traits and so deployed two other mixed model based multi-response QTL approaches: a multi-trait approach (MT) and a multi-trait multi-environment approach (MTME). For yield as well as the other traits, MTME was superior to ME and MT in the number of QTLs, the explained variance and accuracy of predictions. Many of the detected QTLs were pleiotropic and showed quantitative QEI. The results confirmed the feasibility and strengths of novel mixed model QTL methodology to study the architecture of complex traits.
The QTL methods considered thus far are not well suited for prediction purposes as only a limited set of QTL-related markers are used. Since the main interest of this research includes improvement of yield prediction, we explored both single-trait and multi-trait versions of genomic prediction (GP) models as alternatives to the QTL-based prediction (QP) models. This was termed direct prediction. The methods differed in their predictive accuracies with GP methods outperforming QP methods in both single and multi-traits situations. We borrowed ideas from crop growth model (CGM) to dissect complex trait yield into a number of its component traits. Here, we integrated QTL/genomic prediction and CGM approaches and showed that the target trait yield can be predicted via its component traits together with environmental covariables. This was termed indirect prediction. The CGM approach seemed to work well at first sight, but this is especially due to the fact that yield appeared to be strongly driven by just one of its components, the partitioning to fruit.
An alternative representation of the biological knowledge of a complex target trait such as yield is provided by network type models. We constructed both conditional and unconditional networks across the four environments to understand the ‘causal’ relationships between target trait yield and its component traits. The final networks for each environment from both conditional and unconditional methods were used in a structural equation model to assess the causal relationships. Conditioning QTL mapping on network structure improved detection of refined genetic architecture by distinguishing between QTL with direct and indirect effects, thereby removing non-significant effects found in the unconditional network and resolving QTL pleiotropy. Similar to the CGM topology, yield was established to be downstream to its component traits, indicating that yield can be studied and predicted from its component traits. Thus, the genetic improvements of yield would benefit from improvements on the component traits.
Finally, complex trait prediction can be enhanced by a full integration of the methods described in the different chapters. Recent research efforts have been channelled to incorporating both multivariate whole genome prediction models and crop growth models. Further research is required, but we hope that the present thesis presents useful steps towards better prediction models for complex traits exhibiting genotype by environment interaction.
Building towards a multi-dimensional genetic architecture in Caenorhabditis elegans
Sterken, Mark G. - \ 2016
Wageningen University. Promotor(en): Jan Kammenga, co-promotor(en): Jaap Bakker; Gorben Pijlman. - Wageningen : Wageningen University - ISBN 9789462578692 - 167
caenorhabditis elegans - genetic models - introgression - genetic variation - quantitative trait loci - animal viruses - inheritance - rna interference - viral replication - gene expression - caenorhabditis elegans - genetische modellen - introgressie - genetische variatie - loci voor kwantitatief kenmerk - dierenvirussen - overerving - rna-interferentie - virusreplicatie - genexpressie
Trait variation within species is shaped by the genotype and the environment an individual is exposed to. Genomic information is inherited from the parents and forms the basis of the phenotype of an organism. The genetic variation between parents becomes differently distributed between their offspring, leading to trait variation in the offspring. Each trait can be affected by many genes, therefore the genetic architecture can be complex. In complex traits, multiple loci contribute to the ultimate trait value. However, complex traits are shaped not only by genetic variation but also by the environment and the interaction between genotype and environment. The interplay between genetic and environmental variation can affect the fitness of an organism.
Chapter 2 discusses how genotype and environment have shaped the phenotype of the nematode Caenorhabditis elegans, the model species used in this thesis, resulting in a laboratory adapted domesticized strain known as Bristol N2. Bristol N2 has been cultivated in the laboratory for over a decade, leading to the fixation of novel mutations in several genes that strongly affect its phenotype. Genotypic variation arisen by novel mutations in the genes npr-1, glb-5, and nath-10 was fixed in N2 due to the laboratory environment. The allelic variation in npr-1 affects the behaviour of this animal in an environment dependent manner, showcasing the interplay between genotype and environment. However, the altered behaviour warrants caution for interpretation of results obtained in the N2 strain.
The genotypic effects on trait variation can be large, and one of the more powerful population designs to study these effects are introgression lines. In chapter 3 the construction of a genome-wide introgression line (IL) panel between the N2 and the CB4856 strain is described. This panel contains loci of N2 introgressed in a homogeneous CB4856 background. It is demonstrated that together with CB4856-in-N2 ILs this new genome-wide introgression line library strongly facilitates the dissection of genetic interactions.
Chapter 4 and 5 investigate natural variation in infection with Orsay virus, a natural pathogen of the nematode C. elegans. In chapter 4 an assay is developed and tested on two wild-type strains (N2 and JU1580) and two mutant strains with mutations in the RNAi pathway. The development of the virus infection in the separate strains can be traced and the influence of genotype and age on the progression of the infection can be quantified. Furthermore, it is demonstrated that heritable RNAi plays a role in the viral load upon Orsay virus infection, an example of an epigenetically inherited environmental influence. In chapter 5 the assay is applied on an N2xCB4856 recombinant inbred line (RIL) population, after observing a lower viral load in CB4856 compared to N2. The RIL analysis resulted in the identification of two QTL on chromosome IV. These quantitative trait loci (QTL) were verified by CB4856-in-N2 ILs, but the IL analysis also indicated that there could be genetic interactions affecting the QTL. By a transcriptome analysis and a candidate gene search, the gene cul-6 was identified as a candidate underlying the allelic variation between the N2 and CB4856 strain.
Chapters 6 and 7 investigate the influence of genetic interactions and the environment on the genetic architecture of gene expression. In chapter 6 a N2xCB4856 RIL population was exposed to heat stress, leading to the identification of a trans-band on the top of chromosome IV. By analysis of candidate genes, cmk-1, egl-4, and eor-1 were implicated as contributing to the heat-stress induced transcriptional response affected by natural variation between N2 and CB4856. Furthermore, the genes with an expression-QTL on the trans-band were indicative of a stress response phenotype. By analysis of CB4856-in-N2 ILs, it was found that this locus leads to increased recovery from stress. In chapter 7 two-loci genetic interactions were mapped for gene expression in a N2xCB4856 RIL panel. These epistatic interactions were confirmed by measuring gene expression in a novel population of inbred line containing the full set of loci combinations. It was found that genetic interactions in gene expression can be identified by clustering and are pervasive. These genetically interacting loci affect evolutionary conserved genes.
In conclusion, this thesis unveils the mechanisms underlying the genetic architecture of complex traits in C. elegans resulting from genotype and interactions between genotype and environment. It provides tools to unravel these interactions in C. elegans, by providing the community with new resources such as the N2-in-CB4856 introgression lines. Although C. elegans has been a very powerful platform for quantitative trait dissection, we need to expand our mechanistic understanding of polygenic traits.
Mapping and fine-mapping of genetic factors affecting bovine milk composition
Duchemin, S.I. - \ 2016
Wageningen University. Promotor(en): Johan van Arendonk, co-promotor(en): Henk Bovenhuis; Marleen Visker; Willem F. Fikse. - Wageningen : Wageningen University - ISBN 9789462577305 - 190
dairy cows - dairy cattle - milk composition - milk fat - genetic factors - quantitative trait loci - genomics - genetic mapping - animal genetics - melkkoeien - melkvee - melksamenstelling - melkvet - genetische factoren - loci voor kwantitatief kenmerk - genomica - genetische kartering - diergenetica
Duchemin, S.I. (2016). Mapping and fine-mapping of genetic factors affecting bovine milk composition. Joint PhD thesis, between Swedish University of Agricultural Sciences, Sweden and Wageningen University, the Netherlands
Bovine milk is an important source of nutrients in Western diets. Unraveling the genetic background of bovine milk composition by finding genes associated with milk-fat composition and non-coagulation of milk were the main goals of this thesis. In Chapter 1, a brief description of phenotypes and genotypes used throughout the thesis is given. In Chapter 2, I calculated the genetic parameters for winter and summer milk-fat composition from ~2,000 Holstein-Friesian cows, and concluded that most of the fatty acids (FA) can be treated as genetically the same trait. The main differences between milk-fat composition between winter and summer milk samples are most likely due to differences in diets. In Chapter 3, I performed genome-wide association studies (GWAS) with imputed 777,000 single nucleotide polymorphism (SNP) genotypes. I targeted a quantitative trait locus (QTL) region on Bos taurus autosome (BTA) 17 previously identified with 50,000 SNP genotypes, and identified a region covering 5 mega-base pairs on BTA17 that explained a large proportion of the genetic variation in de novo synthesized milk FA. In Chapter 4, the availability of whole-genome sequences of keys ancestors of our population of cows allowed to fine-mapped BTA17 with imputed sequences. The resolution of the 5 mega base-pairs region substantially improved, which allowed the identification of the LA ribonucleoprotein domain family, member 1B (LARP1B) gene as the most likely candidate gene associated with de novo synthesized milk FA on BTA17. The LARP1B gene has not been associated with milk-fat composition before. In Chapter 5, I explored the genetic background of non-coagulation of bovine milk. I performed a GWAS with 777,000 SNP genotypes in 382 Swedish Red cows, and identified a region covering 7 mega base-pairs on BTA18 strongly associated with non-coagulation of milk. This region was further characterized by means of fine-mapping with imputed sequences. In addition, haplotypes were built, genetically differentiated by means of a phylogenetic tree, and tested in phenotype-genotype association studies. As a result, I identified the vacuolar protein sorting 35 homolog, mRNA (VPS35) gene, as candidate. The VPS35 gene has not been associated to milk composition before. In Chapter 6, the general discussion is presented. I start discussing the challenges with respect to high-density genotypes for gene discovery, and I continue discussing future possibilities to expand gene discovery studies, with which I propose some alternatives to identify causal variants underlying complex traits in cattle.
Genome-wide association study reveals regions associated with gestation length in two pig populations
Hidalgo, A.M. ; Lopes, M.S. ; Harlizius, B. ; Bastiaansen, J.W.M. - \ 2016
Animal Genetics 47 (2016)2. - ISSN 0268-9146 - p. 223 - 226.
HBEGF gene - length of pregnancy - quantitative trait loci - reproduction trait
Reproduction traits, such as gestation length (GLE), play an important role in dam line breeding in pigs. The objective of our study was to identify single nucleotide polymorphisms (SNPs) that are associated with GLE in two pig populations. Genotypes and deregressed breeding values were available for 2081 Dutch Landrace-based (DL) and 2301 Large White-based (LW) pigs. We identified two QTL regions for GLE, one in each population. For DL, three associated SNPs were detected in one QTL region spanning 0.52 Mbp on Sus scrofa chromosome (SSC) 2. For LW, four associated SNPs were detected in one region of 0.14 Mbp on SSC5. The region on SSC2 contains the heparin-binding EGF-like growth factor (HBEGF) gene, which promotes embryo implantation and has been described to be involved in embryo survival throughout gestation. The associated SNP can be used for marker-assisted selection in the studied populations, and further studies of the HBEGF gene are warranted to investigate its role in GLE.
Nitrogen use efficiency in potato : an integrated agronomic, physiological and genetic approach
Ospina Nieto, C.A. - \ 2016
Wageningen University. Promotor(en): P.C. Struik; E. Lammerts Van Bueren, co-promotor(en): C.G. van der Linden. - Wageningen : Wageningen University - ISBN 9789462576469 - 177
solanum tuberosum - potatoes - nitrogen - nutrient use efficiency - plant breeding - crop physiology - plant physiology - quantitative trait loci - cultivars - solanum tuberosum - aardappelen - stikstof - nutriëntengebruiksefficiëntie - plantenveredeling - gewasfysiologie - plantenfysiologie - loci voor kwantitatief kenmerk - cultivars
Nitrogen (N) fertilizers increased food production over the last 60 years, but also contributed significantly to the use of fossil energy and the total amount of reactive N in the environment. Agriculture needs to reduce N input and increase nitrogen use efficiency (NUE). Legislation like the Nitrate Directive (91/767/EEC) and the Water Framework Directive (2000/60/EC) forces a reduction in N supply in crop production. The effects of this constraint on yield and quality of potato are expected to be significant since N plays an important role in the vegetative development and production of potato. Considerable amounts of N are needed as N recovery is notoriously low due to the small and shallow roots. The overall aim of this thesis is to improve the nitrogen use efficiency of potato under low nitrogen supply. Specific aims are i) to understand the N effects on potato performance, especially under low N input, ii) to quantify the genotypic variation under contrasting N inputs, iii) to identify quantitative trait loci associated with the crop’s response to nitrogen. We used ecophysiological models to dissect the canopy development into biological meaningful parameters as phenotyping tools. Two potato populations (a set of tetraploid cultivars and a biparental diploid population) were phenotyped in the field under two contrasting N levels. Additionally, a set of 6 cultivars from three maturity groups (early, middle and late) were phenotyped in more detail under 5 nitrogen conditions combining two input levels and two fertilizers types plus a control without nitrogen fertilisation. The curve-fit parameters were, together with other agronomical traits, used in the agronomic and genetic analysis. Our approach using the ecophysiological models captured the phenotypic response to N, enhancing the interpretation of the nitrogen effects and of the differences among maturity types. The nitrogen effects on canopy development resulted in large differences in light interception, tuber yield, tuber size distribution and nitrogen uptake. There were differences in the response to nitrogen between the diploid biparental population and the set of tetraploid cultivars. In general, in the diploid population, having less vigour and therefore less potential to respond to the extra nitrogen, the time required to complete each phase of the canopy development was longer than in the set of tetraploids. In the set of cultivars the rate of early vegetative growth was higher, the onset of the phase with maximum canopy cover was earlier, and the duration of maximum canopy was longer than for the diploid population. However, in both the diploid and the tetraploid population maturity was the major factor accounting for genetic variation in canopy development and tuber development traits. The genotypic differences were reflected in quantitative trait loci that were either N dependent or N independent, with pleiotropic regions affecting most of the maturity-related traits. Few traits showed quantitative trait loci on common regions that were not maturity related like those on chromosomes 2 and 6 (association mapping) or linkage groups ma_VI, pa_VIII pa_XI. Maturity obscures other genotype-dependent physiological traits; therefore it is imperative to find traits that are responsible for genotypic variation, but not related to maturity type. Moreover the results showed that nitrogen use efficiency under low nitrogen input is higher than under high nitrogen input, and higher for late cultivars than for early cultivars. Therefore, breeding for nitrogen use efficiency under low input requires direct selection combined with good response to extra nitrogen and should be done within each maturity group. Finally in a broader context we discussed the need of high-throughput phenotyping in breeding for complex traits, like those involving efficiency, to make the most of the large amount of genetic data, all possible based on advances in technology in remote sensing and images analysis.
Keywords: Association mapping, Breeding for low input, Canopy development, Maturity type, Nitrogen use efficiency, Potato, Solanum tuberosum, Quantitative trait loci.
Multi-population genomic prediction
Wientjes, Y.C.J. - \ 2016
Wageningen University. Promotor(en): Roel Veerkamp; Mario Calus. - Wageningen : Wageningen University - ISBN 9789462576193 - 267
cum laude - dairy cattle - genomics - prediction - quantitative trait loci - genetic improvement - breeding value - selective breeding - animal breeding - animal genetics - melkvee - genomica - voorspelling - loci voor kwantitatief kenmerk - genetische verbetering - fokwaarde - selectief fokken - dierveredeling - diergenetica
Cum laude graduation
Genetic diversity and evolution in Lactuca L. (Asteraceae) : from phylogeny to molecular breeding
Wei, Z. - \ 2016
Wageningen University. Promotor(en): Eric Schranz. - Wageningen : Wageningen University - ISBN 9789462576148 - 210
lactuca sativa - leafy vegetables - phylogeny - genetic diversity - domestication - molecular breeding - genomes - dna - quantitative trait loci - evolution - lactuca sativa - bladgroenten - fylogenie - genetische diversiteit - domesticatie - moleculaire veredeling - genomen - dna - loci voor kwantitatief kenmerk - evolutie
Cultivated lettuce (Lactuca sativa L.) is an important leafy vegetable worldwide. However, the phylogenetic relationships between domesticated lettuce and its wild relatives are still not clear. In this thesis, I focus on the phylogenetic relationships within Lactuca L., including an analysis of the wild Lactuca species that are endemic to Africa for the first time. The genetic variation of responses to salinity in a recombinant inbred line population, derived from a cross between the lettuce crop (L. sativa ‘Salinas’) and wild species (L. serriola), was investigated and the candidate gene in the identified QTL regions was further studied.
In Chapter 1, I introduce and discuss topics related to genetic diversity and evolution in Lactuca, including an overview of lettuce cultivars and uses, its hypothesized domestication history, the taxonomic position of Lactuca, current status of molecular breeding in lettuce and mechanisms of salinity tolerance in plants, especially the High-affinity K+ Transporter (HKT) gene family.
In Chapter 2, the most extensive molecular phylogenetic analysis of Lactuca was constructed based on two chloroplast genes (ndhF and trnL-F), including endemic African species for the first time. This taxon sampling covers nearly 40% of the total Lactuca species endemic to Africa and 34% of all Lactuca species. DNA sequences from all the subfamilies of Asteraceae in Genbank and those generated from Lactuca herbarium samples were used to elucidate the monophyly of Lactuca and the affiliation of Lactuca within Asteracaeae. Based on the subfamily tree, 33 ndhF sequences from 30 species and 79 trnL-F sequences from 48 species were selected to infer phylogenetic relationships within Lactuca using Randomized Axelerated Maximum Likelihood (RAxML) and Bayesian Inference (BI) analyses. In addition, biogeographical, chromosomal and morphological character states were analysed based on the Bayesian tree topology. The results showed that Lactuca contains two distinct phylogenetic clades - the crop clade and the Pterocypsela clade. Other North American, Asian and widespread species either form smaller clades or mix with the Melanoseris species in an unresolved polytomy. The newly sampled African endemic species probably should be excluded from Lactuca and treated as a new genus.
In Chapter 3, twenty-seven wild Lactuca species and four outgroup species were sequenced using next generation sequencing (NGS) technology. The sampling covers 36% of total Lactuca species and all the important geographical groups in the genus. Thirty chloroplast genomes, including one complete (partial) large single copy region (LSC), one small single copy region (SSC), one inverted repeat (IR) region, and twenty-nine nuclear ribosomal DNA sequences (containing the internal transcribed spacer region ) were successfully assembled and analysed. A methodology paper for which I am co-author, but is not included in this thesis, of the sequencing pipeline was published: ‘Herbarium genomics: plastome sequence assembly from a range of herbarium specimens using an Iterative Organelle Genome Assembly (IOGA) pipeline’. These NGS data helped resolve deeper nodes in the phylogeny within Lactuca and resolved the polytomy from Chapter 2. The results showed that there are at least four main groups within Lactuca: the crop group, the Pterocypsela group, the North American group and the group containing widely-distributed species. I also confirmed that the endemic African species should be removed and treated as a new genus.
In Chapter 4, quantitative trait loci (QTLs) related to salt-induced changes in Root System Architecture (RSA) and ion accumulation were determined using a recombinant inbred line population derived from a cross between cultivated lettuce and wild lettuce. I measured the components of RSA by replicated lettuce seedlings grown on vertical agar plates with different NaCl concentrations in a controlled growth chamber environment. I also quantified the concentration of sodium and potassium in replicates of greenhouse-grown plants watered with 100 mM NaCl. The results identified a total of fourteen QTLs using multi-trait linkage analysis, including three major QTLs associated with general root development (qRC9.1), root growth in salt stress condition (qRS2.1), and ion accumulation (qLS7.2).
In Chapter 5, one of the identified QTL regions (qLS7.2) reported in Chapter 4 was found to contain a homolog of the HKT1 from Arabidopsis thaliana. I did a phylogenetic analysis of Lactuca HKT1-like protein sequences with other published HKT protein sequences and determined transmembrane and pore segments of lettuce HKT1;1 alleles, according to the model proposed for AtHKT1;1. Gene expression pattern and level of LsaHKT1;1 (L. sativa ‘Salinas’) and LseHKT1;1 (L. serriola) in root and shoot were investigated in plants growing hydroponically over a time-course. The measurements of Na+ and K+ contents were sampled at the same time as the samples used for gene expression test. In addition, I examined the 5’ promoter regions of the two genotypes. The results showed low expression levels of both HKT1;1 alleles in Lactuca root and relatively higher expression in shoot, probably due to the negative cis-regulatory elements of HKT1 alleles found in Lactuca promoter regions. Significant allelic differences were found in HKT1;1 expression in early stage (0-24 hours) shoots in and in late stage (2-6 days) roots. shoot HKT1;1 expression/root HKT1;1 expression was generally consistent with the ratios of Na+/K+ balance in the relevant tissues (shoot Na+/K+ divided by root Na+/K+).
In Chapter 6, I summarize and discuss the results from previous chapters briefly. The implications of Chapter 2 and 3 for Lactuca phylogenetics are discussed, including some key characters for the diagnosis of species within Lactuca, the use of herbarium DNA for NGS technology, and perspectives into Lactuca phylogeny. Future perspectives of genome-wide association mapping for lettuce breeding were also discussed. Lastly, I propose to integrate phylogenetic approaches into investigations of allelic differences in lettuce, not just associated with salinity stress but also with other stressed and beneficial characters, both within and between species.
Using selection index theory to estimate consistency of multi-locus linkage disequilibrium across populations
Wientjes, Y.C.J. ; Veerkamp, R.F. ; Calus, M.P.L. - \ 2015
BMC Genetics 16 (2015). - ISSN 1471-2156
genomic breeding values - genetic-relationship information - quantitative trait loci - dairy-cattle breeds - prediction - accuracy - haplotype - markers - impact - lines
The potential of combining multiple populations in genomic prediction is depending on the consistency of linkage disequilibrium (LD) between SNPs and QTL across populations. We investigated consistency of multi-locus LD across populations using selection index theory and investigated the relationship between consistency of multi-locus LD and accuracy of genomic prediction across different simulated scenarios. In the selection index, QTL genotypes were considered as breeding goal traits and SNP genotypes as index traits, based on LD among SNPs and between SNPs and QTL. The consistency of multi-locus LD across populations was computed as the accuracy of predicting QTL genotypes in selection candidates using a selection index derived in the reference population. Different scenarios of within and across population genomic prediction were evaluated, using all SNPs or only the four neighboring SNPs of a simulated QTL. Phenotypes were simulated using different numbers of QTL underlying the trait. The relationship between the calculated consistency of multi-locus LD and accuracy of genomic prediction using a GBLUP type of model was investigated.
The accuracy of predicting QTL genotypes, i.e. the measure describing consistency of multi-locus LD, was much lower for across population scenarios compared to within population scenarios, and was lower when QTL had a low MAF compared to QTL randomly selected from the SNPs. Consistency of multi-locus LD was highly correlated with the realized accuracy of genomic prediction across different scenarios and the correlation was higher when QTL were weighted according to their effects in the selection index instead of weighting QTL equally. By only considering neighboring SNPs of QTL, accuracy of predicting QTL genotypes within population decreased, but it substantially increased the accuracy across populations.
Consistency of multi-locus LD across populations is a characteristic of the properties of the QTL in the investigated populations and can provide more insight in underlying reasons for a low empirical accuracy of across population genomic prediction. By focusing in genomic prediction models only on neighboring SNPs of QTL, multi-locus LD is more consistent across populations since only short-range LD is considered, and accuracy of predicting QTL genotypes of individuals from another population is increased.
Linkage disequilibrium and genomic selection in pigs
Veroneze, R. - \ 2015
Wageningen University. Promotor(en): Johan van Arendonk; S.E.F. Guimarães, co-promotor(en): John Bastiaansen. - Wageningen : Wageningen University - ISBN 9789462574151 - 142
varkens - verstoord koppelingsevenwicht - loci voor kwantitatief kenmerk - genomica - populaties - kruising - inteeltlijnen - fokwaarde - selectief fokken - genetica - pigs - linkage disequilibrium - quantitative trait loci - genomics - populations - crossbreds - inbred lines - breeding value - selective breeding - genetics
Securing a sufficiently large set of genotypes and phenotypes can be a limiting factor when implementing genomic selection. This limitation may be overcome by combining data from multiple populations or by using information of crossbred animals. The research described in this thesis characterized linkage disequilibrium (LD) patterns in different pig populations and evaluated whether the consistency of LD between populations allows us to make predictions about the performance of genomic selection when multiple populations are included in the prediction and/or validation datasets.
In chapter 2 I evaluated the persistence of LD and patterns of LD decay of pure and crossbred pig populations using real data that was representative of the crossbreeding structure of pig production. The persistence of phase between the crosses and their parental populations was high, indicating that similar marker effects might be expected across these populations. Across the purebred populations the persistence of phase was low therefore higher density panels should be used to have the same marker-QTL associations across these populations.
In chapter 3, the well-known nonlinear model developed by Sved (1971) was compared against a an alternative, loess regression, to describe LD decay. The loess regression model was found to be less influenced by the lack of residual normality, independence and homogeneity of variance than the nonlinear regression model. The loess regression model resulted in more reliable LD predictions and can be used to formally compare the LD decay curves between populations.
Chapter 4 showed the utility of different reference sets (across- and multi-population) for the prediction of genomic breeding values, as well as the potential of using crossbred performance in genomic prediction. None of the accuracies obtained using across-population, or multi-population genomic prediction, nor the accuracies obtained using crossbred data, followed the expectations based on LD that was described in chapter 2. I showed that across-population prediction accuracy was negligible even when the populations had common breeds in their genetic background. The variable accuracies of multi-population prediction and moderate accuracy of prediction of crossbred performance appeared to be a result of the differences in genetic architecture between pure populations and between purebred and crossbred animals.
In chapter 5, a methodology that uses information from genome wide association analyses in the genomic predictions was developed and evaluated. The aim in chapter 5 was to let the genomic prediction model use information from the genetic architecture in single- and multi-population genomic prediction. I showed that using weights based on GWAS results from a combined population did result in higher accuracies of GBLUP in single- as well as in multi-population predictions.
In chapter 6 I placed my results in a broader context. I discussed about the theoretical and practical aspects of linkage disequilibrium in breeding and in the estimation of effective population size. I also discussed the application of genomic selection in a small population and in practical pig breeding, including the prospects of using whole genome sequence for genomic prediction.
Using natural variation to unravel the dynamic regulation of plant performance in diverse environments
Molenaar, J.A. - \ 2015
Wageningen University. Promotor(en): Harro Bouwmeester; Joost Keurentjes, co-promotor(en): Dick Vreugdenhil. - Wageningen : Wageningen University - ISBN 9789462573444 - 186
planten - genomen - loci voor kwantitatief kenmerk - warmtestress - genetische kartering - groei - droogte - plantengenetica - plantenfysiologie - plants - genomes - quantitative trait loci - heat stress - genetic mapping - growth - drought - plant genetics - plant physiology
All plants are able to respond to changes in their environment by adjusting their morphology and metabolism, but large differences are observed in the effectiveness of these responses in the light of plant fitness. Between and within species large differences are observed in plant responses to drought, heat and other abiotic stresses. This natural variation is partly due to variation in the genetic composition of individuals. Within-species variation can be used to identify and study genes involved in the genetic regulation of plant performance.
Growth of the world population will, in the coming years, lead to an increased demand for food, feed and other natural products. In addition, extreme weather conditions with, amongst others, more and prolonged periods of drought and heat are expected to occur due to climate change. Therefore breeders are challenged to produce stress tolerant cultivars with improved yield under sub-optimal conditions. Knowledge about the mechanisms and genes that underlie tolerance to drought, heat and other abiotic stresses will ease this challenge.
The aim of this thesis was to identify and study the role of genes that are underlying natural variation in plant performance under drought, salt and heat stress. To reach this goal a genome wide association (GWA) mapping approach was taken in the model species Arabidopsis thaliana. A population of 350 natural accessions of Arabidopsis, genotyped with 215k SNPs, was grown under control and several stress conditions and plant performance was evaluated by phenotyping one or several plant traits per environment. Genes located in the genomic regions that were significantly associated with plant performance, were studied in more detail.
Plant performance was first evaluated upon osmotic stress (Chapter 2). This treatment resulted not only in a reduced plant size, but also caused the colour of the rosette leaves to change from green to purple-red due to anthocyanin accumulation. The latter was visually quantified and subsequent GWA mapping revealed that a large part of the variation in anthocyanin accumulation could be explained by a small genomic region on chromosome 1. The analysis of re-sequence data allowed us to associate the second most frequent allele of MYB90 with higher anthocyanin accumulation and to identify the causal SNP. Interestingly MYB75, a close relative of MYB90, was not identified by GWA mapping, although causal sequence variation of this gene for anthocyanin accumulation was identified in the Cvi x Ler and Ler x Eri-1 RIL populations. Re-sequence data revealed that one allele of MYB75 was dominating the population and that the MYB75 alleles of Cvi and Ler were both rare, explaining the lack of association at this locus in GWA mapping. For MYB90, two alleles were present in a substantial part of the population, suggesting balancing selection between them.
Next, the natural population was exposed to short-term heat stress during flowering (Chapter 3). This short-term stress has a large impact on seed set, while it hardly affects the vegetative tissues. Natural variation for tolerance against the effect of heat on seed set was evaluated by measuring the length of all siliques along the inflorescence in both heat-treated and control plants. Because the flower that opened during the treatment was tagged, we could analyse the heat response for several developmental stages separately. GWA mapping revealed that the heat response before and after anthesis involved different genes. For the heat response before anthesis strong evidence was gained that FLC, a flowering time regulator and QUL2, a gene suggested to play a role in vascular tissue development, were causal for two strong associations.
Furthermore, the impact of moderate drought on plant performance was evaluated in the plant phenotyping platform PHENOPSIS. Homogeneous drought was assured by tight regulation of climate cell conditions and the robotic weighing and watering of the pots twice a day. Because plant growth is a dynamic trait it was monitored over time by top-view imaging under both moderate drought and control conditions (Chapter 4 and 5). To characterise growth it was modelled with an exponential function. GWA mapping of temporal growth data resulted in the detection of time-dependent QTLs whereas mapping of model parameters resulted in another set of QTLs related to the entire growth period. Most of these QTLs would not have been identified if plant size had only been determined on a single day. For the QTLs detected under control conditions eight candidate genes with a growth-related mutant or overexpression phenotype were identified (Chapter 4). Genes in the support window of the drought-QTLs were prioritized based on previously reported gene expression data (Chapter 5). Additional validation experiments are needed to confirm causality of the candidate genes.
Next, to search for genes that determine plant size across many environments, biomass accumulation in the natural population was determined in 25 different environments (Chapter 6). Joint analysis of these data by multi-environment GWA mapping resulted in the detection of 106 strongly associated SNPs with significant effects in 7 to 16 environments. Several genes involved in starch metabolism, leaf size control and flowering time determination were located in close proximity of the associated SNPs. Two genes, RPM1 and ACD6, were located in close proximity of SNPs with significant GxE effects. For both genes, alleles have been identified that increase resistance to bacterial infection, but that reduce biomass accumulation. The sign of the allelic effect is therefore dependent on the environmental conditions. Whole genome predictions revealed that most of the GxE interactions observed at the phenotypic level were not the consequence of strong associations with strong QxE effects, but of moderate and weak associations with weak QxE effects.
Finally, in Chapter 7 I discuss the usefulness of GWA mapping in the identification of genes underlying natural variation in plant performance under drought, heat stress and a number of other environments. Strong associations were observed for both environment-specific as well as common plant performance regulators. Some choices in phenotyping and experimental design were crucial for our success, like evaluation of plant performance over time and simplification of the quantification of the phenotype. It is suggested that follow-up work should focus on the functional characterization of the causal genes, because such analyses would be helpful to identify pathways in which the causal genes are involved and to understand why sequence variation results in changes at the phenotype level. Although translation of the findings to applications in crops is challenging, this thesis contributes to the understanding of the genetic regulation of stress response and therefore will likely contribute to the development of stress tolerant and stable yielding crops.