Genetic diversity, population structure, and linkage disequilibrium in the context of genome-wide association mapping of northern corn leaf blight resistance

Besides linkage mapping, association mapping (AM) has become a powerful complement for understanding the genetic basis of complex traits. AM utilizes the natural genetic diversity and the linkage disequilibrium (LD) present in a diverse germplasm set. Setosphaeria turcica is a fungal pathogen that causes northern corn leaf blight (NCLB) in maize. The objective of this thesis research was to set the stage for and perform AM in elite maize breeding populations for NCLB resistance. Information about the genetic diversity and population structure in elite breeding material is of fundamental importance for the improvement of crops. The objectives of my study were to (i) examine the population structure and the genetic diversity in elite maize germplasm based on simple sequence repeat (SSR) markers, (ii) compare these results with those obtained from single nucleotide polymorphism (SNP) markers, and (iii) compare the coancestry coefficient calculated from pedigree records with genetic distance estimates calculated from SSR and SNP markers. The study was based on 1 537 elite maize inbred lines genotyped with 359 SSR and 8 244 SNP markers. My results indicated that both SSR and SNP markers are suitable for uncovering population structure. The same conclusions regarding the structure and the diversity of heterotic pools can be drawn from both markers types. However, fewer SSRs as SNPs are required for this goal, which facilitates the computations, for instance by the STRUCTURE software. Finally, the findings indicated that under the assumption of a fixed budget, modified Roger?s distances and gene diversity could be more precisely estimated with SNPs than with SSRs, and we proposed that between 7 and 11 times more SNPs than SSRs should be used for analyzing population structure and genetic diversity. Association mapping is based on LD shaped by historical recombinations. Many factors affect LD and, therefore, it must be determined empirically in the germplasm under investigation to examine the prospects of genomewide association mapping studies. The objectives of my study were to (i) examine the extent of LD with SSR and SNP markers in 1 537 commercial maize inbred lines belonging to four heterotic pools, (ii) compare the LD patterns determined by these two marker types, (iii) evaluate the number of SNP markers needed to perform genome-wide association analyses, and (iv) investigate temporal trends of LD. The results suggested that SNP markers of the examined density, unlike SSR markers, can be used effectively for association studies in commercial maize germplasm. Based on the decay of LD in the various heterotic pools, between 4 000 and 65 000 SNP markers would be needed to detect with a reasonable power associations with rather large quantitative trait loci (QTL). The 60 K SNP chip currently available for maize seems appropriate to identify QTLs that explain at least 10% of the phenotypic variance. However, to identify QTLs with smaller effects, which is a realistic situation for most traits of interest to maize breeders, a much higher marker density is required. NCLB is a serious foliar disease in maize. In order to unravel the genetic architecture of the resistance against this disease, a vast association mapping panel comprising 1 487 European maize inbred lines was used to (i) identify chromosomal regions affecting flowering time (FT) and NCLB resistance, (ii) examine the epistatic interactions of the identified chromosomal regions with the genetic background on an individual molecular marker basis, and (iii) dissect the correlation between NCLB resistance and FT. We observed for FT, a trait for which already various genetic analyses have been performed in maize, a very well interpretable pattern of SNP associations, suggesting that data from practical plant breeding programs can be used to dissect polygenic traits. Furthermore, we described SNPs associated with NCLB and NCLB corrected for FT resistance that are located in genes for which a direct link to the trait is discernable or which are located in bins of the maize genome for which previously QTLs have been reported. Some of the SNPs showed significant epistatic interactions with markers from the genetic background. The observation that the listed SNPs and their epistatic interactions explained in the entire germplasm set about 10% and in some individual heterotic pools up to 30% of the genetic variance suggests that significant progress towards improving the resistance of maize against NCLB by marker-assisted selection is possible with these markers, without much compromising on late flowering time. Furthermore, these regions are interesting for further research to understand the mechanisms of resistance against NCLB and diseases in general, because some of the genes identified have not been annotated so far for these functions.Neben der Kopplungsanalyse hat sich die Assoziationskartierung (AM) als eine vielversprechende Methodenergänzung zur Untersuchung der genetischen Grundlage komplexer Merkmale erwiesen. Die AM nutzt die natürliche genetische Diversität und das Gametenphasenungleichgewicht (LD), die in einem vielfältigen Genpool bestehen. Setosphaeria turcica ist ein pilzlicher Erreger, der die Turcicum-Blattfleckenkrankheit (NCLB) an Mais verursacht. Ziel dieser Doktorarbeit war die Überprüfung der Voraussetzungen einer AM sowie deren Durchführung in Maiselitezüchtungspopulationen für NCLB Resistenz. Informationen über die genetische Diversität und Populationsstruktur in Elitezüchtungsmaterial sind von grundlegender Bedeutung für die Verbesserung von Kulturpflanzen. Die Ziele dieser Studie waren (i) die Erfassung von Populationsstruktur und genetischer Diversität in Maiselitezüchtungsmaterial anhand von Mikrosatelliten (SSR) Markern, (ii) der Vergleich dieser Ergebnisse mit denen von Einzelbasenpaaraustausch (SNP) Markern, und (iii) der Vergleich des Verwandschaftskoeffizienten berechnet anhand von Abstammungsinformationen mit der genetischen Distanz berechnet mit Hilfe von SSR und SNP Markern. Diese Studie basierte auf 1 537 Maiseliteinzuchtlinien, die mit 359 SSR und 8 244 SNP Markern genotypisiert waren. Die Ergebnisse dieser Studie zeigten, dass für die Zuordnung der Inzuchtlinien zu Subgruppen mittels SNP Daten und STRUCTURE das Kriterium der höchsten Zugehörigkeitswahrscheinlichkeit angewendet werden muss, um Subgruppen zu finden, die mit denjenigen, welche anhand von SSR Daten ermittelt wurden, identisch sind. Dennoch können für beide Markertypen die gleichen Schlussfolgerungen bezüglich Populationsstruktur und genetischer Diversität der heterotischen Gruppen gezogen werden. Darüber hinaus zeigten die Ergebnisse, dass unter der Annahme eines festen Budgets modifizierte Roger?s Distanzen und die genetische Diversität mit SNP Markern genauer geschätzt werden können als mit SSR Markern. Zusätzlich ergaben die Untersuchungen, dass um ähnlich genaue Schätzwerte der genetische Distanz und Diversität zu erzielen, zwischen 7 und 11 mal mehr SNP als SSR Markern eingesetzt werden müssen. Die AM nutzt LD, welches durch historische Rekombinationen geformt wurde. Darüber hinaus beeinflussen viele andere populationsgenetische Faktoren das LD. Es ist deshalb erforderlich, das LD in dem interessierenden genetischen Material empirisch zu erfassen, um die Aussichten einer genomweiten AM beurteilen zu können. Die Ziele dieser Studie waren (i) das Ausmaß des LD anhand von SSR und SNP Markern in 1 537 Maiseliteinzuchtlinien aus vier heterotischen Gruppen zu untersuchen und vergleichen, (ii) die Anzahl der SNP Marker, die benötigt werden, um genomweite Assoziationsstudien durchführen zu können, zu bestimmen, und (iii) das Ausmaß vom LD in Inzuchtlinien verschiedener Zulassungsdaten zu vergleichen. Die Ergebnisse legen nahe, dass die verwendete Zahl von SNP Markern, im Gegensatz zur Zahl der SSR Markern, ausreichend war, um AM in Maiselitezüchtungsmaterial durchführen zu können. Basierend auf der beobachtete Abnahme des LD mit der genetischen Kartendistanz in den verschiedenen heterotischen Gruppen, konnte gezeigt werden, dass zwischen 4 000 und 65 000 SNP Marker benötigt werden, um mit einer angemessenen statistischen Güte Assoziationen mit großen ?Quantitative Trait Loci? (QTL) zu erkennen. Der 60 K SNP Chip, der heutzutage für Mais verfügbar ist, scheint daher notwendig zu sein, um QTL zu erfassen, die mindestens 10% der phänotypischen Varianz erklären. Um jedoch QTL mit kleineren Effekten identifizieren zu können, ist eine wesentlich höhere Markerdichte erforderlich. NCLB ist ein bedeutende Blattkrankheit von Mais. Mit dem Ziel, die genetische Architektur der Resistenz gegen diese Krankheit zu entschlüsseln, wurden 1 487 europäischen Maiseliteinzuchtlinien zur AM verwendet, um (i) die Genomregionen, die zu Variation des Blühzeitpunktes (FT) und NCLB Resistenz beitragen aufzufinden, (ii) mögliche epistatische Interaktionen der identifizierten Genomregionen mit dem genetischen Hintergrund zu ermitteln, und (iii) die Korrelation zwischen NCLB Resistenz und FT zu untersuchen. Für FT, für das bereits verschiedene genetische Analysen in Mais durchgeführt wurden, wurde ein sehr gut interpretierbares Muster von SNP Assoziationen beobachtet. Dies belegt, dass Daten aus praktischen Pflanzenzüchtungsprogrammen verwendet werden können, um die polygenen Merkmalen zugrunde liegenden genetischen Faktoren zu detektieren. Darüber hinaus wurden SNP Marker, die assoziiert mit NCLB Resistenz sind, beschrieben, die sich in Genen befinden, für die eine direkte Verbindung zu dem Merkmal erkennbar ist oder sich in Chromosomenregionen des Maisgenoms befinden, in den bereits QTL für dieses Merkmal beschrieben worden sind. Einige der SNP Marker zeigten signifikante epistatische Interaktionen mit Markern ausdem genetischen Hintergrund. Die Beobachtung, dass die ermittelten SNP Marker und deren epistatische Interaktionen im gesamten untersuchten genetischen Material etwa 10% und in einzelnen heterotischen Gruppen bis zu 30% der genetischen Varianz erklärten, legt nahe, dass mit diesen Markern ein beträchtlicher Fortschritt bei der Verbesserung der Resistenz von Mais gegen NCLB durch markergestütze Selektion möglich ist. Darüber hinaus sind diese Regionen interessant für weitere Untersuchungen, um die Mechanismen der Resistenz gegen NCLB sowie andere Krankheiten bei Mais zu verstehen, da einige der identifizierten Gene hiermit bislang noch nicht in Verbindung gebracht worden sind

Population structure and genetic diversity in a commercial maize breeding program assessed with SSR and SNP markers

Information about the genetic diversity and population structure in elite breeding material is of fundamental importance for the improvement of crops. The objectives of our study were to (a) examine the population structure and the genetic diversity in elite maize germplasm based on simple sequence repeat (SSR) markers, (b) compare these results with those obtained from single nucleotide polymorphism (SNP) markers, and (c) compare the coancestry coefficient calculated from pedigree records with genetic distance estimates calculated from SSR and SNP markers. Our study was based on 1,537 elite maize inbred lines genotyped with 359 SSR and 8,244 SNP markers. The average number of alleles per locus, of group specific alleles, and the gene diversity (D) were higher for SSRs than for SNPs. Modified Roger’s distance (MRD) estimates and membership probabilities of the STRUCTURE matrices were higher for SSR than for SNP markers but the germplasm organization in four heterotic pools was consistent with STRUCTURE results based on SSRs and SNPs. MRD estimates calculated for the two marker systems were highly correlated (0.87). Our results suggested that the same conclusions regarding the structure and the diversity of heterotic pools could be drawn from both markers types. Furthermore, although our results suggested that the ratio of the number of SSRs and SNPs required to obtain MRD or D estimates with similar precision is not constant across the various precision levels, we propose that between 7 and 11 times more SNPs than SSRs should be used for analyzing population structure and genetic diversity

Prospects and Potential Uses of Genomic Prediction of Key Performance Traits in Tetraploid Potato

Genomic prediction is a routine tool in breeding programs of most major animal and plant species. However, its usefulness for potato breeding has not yet been evaluated in detail. The objectives of this study were to (i) examine the prospects of genomic prediction of key performance traits in a diversity panel of tetraploid potato modeling additive, dominance, and epistatic effects, (ii) investigate the effects of size and make up of training set, number of test environments and molecular markers on prediction accuracy, and (iii) assess the effect of including markers from candidate genes on the prediction accuracy. With genomic best linear unbiased prediction (GBLUP), BayesA, BayesCπ, and Bayesian LASSO, four different prediction methods were used for genomic prediction of relative area under disease progress curve after a Phytophthora infestans infection, plant maturity, maturity corrected resistance, tuber starch content, tuber starch yield (TSY), and tuber yield (TY) of 184 tetraploid potato clones or subsets thereof genotyped with the SolCAP 8.3k SNP array. The cross-validated prediction accuracies with GBLUP and the three Bayesian approaches for the six evaluated traits ranged from about 0.5 to about 0.8. For traits with a high expected genetic complexity, such as TSY and TY, we observed an 8% higher prediction accuracy using a model with additive and dominance effects compared with a model with additive effects only. Our results suggest that for oligogenic traits in general and when diagnostic markers are available in particular, the use of Bayesian methods for genomic prediction is highly recommended and that the diagnostic markers should be modeled as fixed effects. The evaluation of the relative performance of genomic prediction vs. phenotypic selection indicated that the former is superior, assuming cycle lengths and selection intensities that are possible to realize in commercial potato breeding programs

Table1.CSV

<p>Genomic prediction is a routine tool in breeding programs of most major animal and plant species. However, its usefulness for potato breeding has not yet been evaluated in detail. The objectives of this study were to (i) examine the prospects of genomic prediction of key performance traits in a diversity panel of tetraploid potato modeling additive, dominance, and epistatic effects, (ii) investigate the effects of size and make up of training set, number of test environments and molecular markers on prediction accuracy, and (iii) assess the effect of including markers from candidate genes on the prediction accuracy. With genomic best linear unbiased prediction (GBLUP), BayesA, BayesCπ, and Bayesian LASSO, four different prediction methods were used for genomic prediction of relative area under disease progress curve after a Phytophthora infestans infection, plant maturity, maturity corrected resistance, tuber starch content, tuber starch yield (TSY), and tuber yield (TY) of 184 tetraploid potato clones or subsets thereof genotyped with the SolCAP 8.3k SNP array. The cross-validated prediction accuracies with GBLUP and the three Bayesian approaches for the six evaluated traits ranged from about 0.5 to about 0.8. For traits with a high expected genetic complexity, such as TSY and TY, we observed an 8% higher prediction accuracy using a model with additive and dominance effects compared with a model with additive effects only. Our results suggest that for oligogenic traits in general and when diagnostic markers are available in particular, the use of Bayesian methods for genomic prediction is highly recommended and that the diagnostic markers should be modeled as fixed effects. The evaluation of the relative performance of genomic prediction vs. phenotypic selection indicated that the former is superior, assuming cycle lengths and selection intensities that are possible to realize in commercial potato breeding programs.</p

Optimal implementation of genomic selection in clone breeding programs—Exemplified in potato: I. Effect of selection strategy, implementation stage, and selection intensity on short‐term genetic gain

Abstract Genomic selection (GS) is used in many animal and plant breeding programs to enhance genetic gain for complex traits. However, its optimal integration in clone breeding programs, for example potato, that up to now relied on phenotypic selection (PS) requires further research. In this study, we performed computer simulations based on an empirical genomic dataset of tetraploid potato to (i) investigate under a fixed budget how the weight of GS relative to PS, the stage of implementing GS, the correlation between an auxiliary trait and the target trait, the variance components, and the prediction accuracy affect the genetic gain of the target trait, (ii) determine the optimal allocation of resources maximizing the genetic gain of the target trait, and (iii) make recommendations to breeders how to implement GS in clone and especially potato breeding programs. In our simulation results, any selection strategy involving GS had a higher short‐term genetic gain for the target trait than Standard‐PS. In addition, we showed that implementing GS in consecutive selection stages can largely enhance short‐term genetic gain and recommend the breeders to implement GS at single hills and A clone stages. Furthermore, we observed for selection strategies involving GS that the optimal allocation of resources maximizing the genetic gain of the target trait differed considerably from those typically used in potato breeding programs and, thus, require the adjustment of the selection and phenotyping intensities. The trends are described in our study. Therefore, our study provides new insight for breeders regarding how to optimally implement GS in a commercial potato breeding program to improve the short‐term genetic gain for their target trait