The availability of molecular markers covering the entire genome, such as single nucleotide polymorphism (SNP) markers, allied to the computational resources for processing large amounts of data, enabled the development of an approach for marker assisted selection for quantitative traits, known as genomic selection. In the last decade, genomic selection has been successfully implemented in a wide variety of animal and plant species, showing its benefits over traditional marker assisted selection and selection based only on pedigree information. However, some practical challenges may still limit the wide implementation of this method in a plant breeding program. For example, we cite the cost of high-density genotyping of a large number of individuals and the application of more complex models that take into account multiple traits and environments. Thus, this study aimed to i) investigate SNP calling and imputation strategies that allow cost-effective high-density genotyping, as well as ii) evaluating the application of multivariate genomic selection models to data from multiple traits and environments. This work was divided into two chapters. In the first chapter, we compared the accuracy of four imputation methods: NPUTE, Beagle, KNNI and FILLIN, using genotyping-by-sequencing (GBS) data from 1060 maize inbred lines, which were genotyped using different depths of coverage. In addition, two SNP calling and imputation strategies were evaluated. Our results indicated that combining SNP-calling and imputation strategies can enhance cost-effective genotyping, resulting in higher imputation accuracies. In the second chapter, multivariate genomic selection models, for multiple traits and environments, were compared with their univariate versions. We used data from 415 hybrids evaluated in the second season in four years (2006-2009) for grain yield, number of ears and grain moisture. Hybrid genotypes were inferred in silico based on their parental inbred lines using SNP markers obtained via GBS. However, genotypic information was available only for 257 hybrids, motivating the use of the H matrix, which combines genetic information based on pedigree and molecular markers. Our results demonstrated that the use of multi-trait multi-environment models can improve predictive abilities, especially to predict the performance of hybrids that have not yet been evaluated in any environment. / A disponibilidade de marcadores moleculares cobrindo todo o genoma, como os polimorfismos de nucleotídeos individuais (single nucleotide polymorphism - SNP), aliada aos recursos computacionais para o processamento de grande volume de dados, tornou possível o desenvolvimento de uma abordagem de melhoramento assistido para caracteres de herança quantitativa, conhecida como seleção genômica. Na última década a seleção genômica tem sido implementada com sucesso em uma enorme variedade de espécies animais e vegetais, comprovando suas vantagens sobre a seleção assistida por marcadores tradicional e a seleção baseada apenas em informações de parentesco. No entanto, alguns desafios práticos ainda podem limitar a implementação deste método em um programa de melhoramento de plantas. Como exemplos, citam-se o custo da genotipagem de alta densidade de um grande número de indivíduos e a aplicação de modelos mais complexos, que consideram múltiplos caracteres e ambientes. Dessa forma, este estudo teve como objetivos: i) investigar estratégias de identificação de SNPs e imputação que possibilitem uma genotipagem de alta densidade economicamente viável; e ii) avaliar a aplicação de modelos multivariados de seleção genômica para múltiplos caracteres e ambientes. Este trabalho foi divido em dois capítulos. No primeiro capítulo, comparou-se a acurácia de quatro métodos de imputação: NPUTE, Beagle, KNNI e FILLIN, usando dados de genotipagem por sequenciamento (genotyping-by-sequencing - GBS) de 1.060 linhagens de milho, que foram genotipadas usando diferentes profundidades de cobertura. Além disso, duas estratégias de identificação de SNPs e imputação foram avaliadas. Os resultados indicaram que a combinação de estratégias de detecção de polimorfismos e imputação pode possibilitar uma genotipagem economicamente viável, resultando em maiores acurácias de imputação. No segundo capítulo, modelos multivariados de seleção genômica, para múltiplos caracteres e ambientes, foram comparados com suas versões univariadas. Dados de 415 híbridos avaliados na segunda safra em quatro anos (2006-2009) para os caracteres produtividade de grãos, número de espigas e umidade foram utilizados. Os genótipos dos híbridos foram inferidos in silico com base nos genótipos das linhagens parentais usando marcadores SNPs obtidos via GBS. No entanto, informações genotípicas estavam disponíveis para apenas 257 híbridos, de modo que foi necessário fazer uso da matriz H, a qual combina informações de parentesco genético baseadas em pedigree e marcadores. Os resultados obtidos demonstraram que o uso de modelos de seleção genômica para múltiplos caracteres e ambientes pode aumentar a capacidade preditiva, especialmente para predizer a performance de híbridos nunca avaliados em qualquer ambiente.

As crescentes preocupações com questões ambientais têm despertado interesse global pelo uso de combustíveis alternativos, e o uso da biomassa vegetal surge como uma alternativa viável para a geração de biocombustíveis. Diferentes materiais orgânicos têm sido utilizados, e dentre eles destaca-se o sorgo biomassa (Sorghum bicolor L. Moench). A seleção genômica apresenta grande potencial e pode, em médio prazo, reestruturar os programas de melhoramento de plantas, promovendo maiores ganhos genéticos quando comparada a outros métodos, além de reduzir significativamente o tempo necessário para o desenvolvimento de novas cultivares, através da seleção precoce. Este trabalho teve como objetivo avaliar modelos de seleção genômica e aplicá-los para a predição dos valores genéticos de indivíduos do painel de sorgo biomassa da Embrapa/Milho e Sorgo. Tal painel inclui materiais do banco de germoplasma e materiais utilizados em programas de melhoramento de sorgo dessa instituição, bem como coleções núcleo do CIRAD e ICRISAT, sendo, portanto, subdividido em dois sub-painéis. As 100 linhagens do sub-painel 1 foram avaliadas fenotipicamente por dois anos (2011 e 2012) e as 100 linhagens do sub-painel 2 por um ano (2011), ambas no município de Sete Lagoas-MG, para as seguintes características fenotípicas: tempo até o florescimento, altura de plantas, produção de massa verde e massa seca, proporções de fibra ácida e neutra, celulose, hemicelulose e lignina. Posteriormente, as 200 linhagens integrantes do painel foram genotipadas através da técnica de genotipagem por sequenciamento. A partir desses dados genotípicos e fenotípicos, os modelos de seleção genômica Bayes A, Bayes B, Bayes Cπ, Bayes Lasso, Bayes Ridge Regression e Random Regression BLUP (RRBLUP) foram ajustados e comparados. As capacidades preditivas obtidas foram elevadas e pouco variaram entre os diversos modelos, variando de 0,61 para o caráter florescimento a 0,85 para a proporção de fibra ácida, quando o modelo RRBLUP foi empregado na análise conjunta dos dois sub-painéis. Por outro lado, a predição cruzada entre sub-painéis resultou em capacidades preditivas substancialmente menores, nunca superiores a 0,66 e em alguns cenários virtualmente iguais a zero, além de apresentar maiores variações entre os modelos ajustados. Simulações do uso de subconjuntos dos marcadores moleculares são apresentadas e indicam possibilidades de obtenção de capacidades preditivas mais elevadas. Análises de enriquecimento funcional realizadas a partir dos efeitos preditos dos marcadores sugeriram associações interessantes, as quais devem ser investigadas com maiores detalhes em estudos futuros, com potencial de elucidação da arquitetura genética dos caracteres quantitativos. / Increased concerns about environmental issues have aroused global interest in the use of alternative fuels, and the use of plant biomass emerges as a viable alternative for the generation of biofuels. Different organic materials have been used, including high biomass sorghum (Sorghum bicolor L. Moench). Genomic selection has great potential and could, in the medium term, restructure plant breeding programs, promoting greater genetic gains when compared to other methods and significantly reducing the time required for the development of new cultivars through early selection. This work aimed at evaluating models of genomic selection and applying them to the prediction of breeding values for a panel of high biomass sorghum genotypes of Embrapa / Milho e Sorgo. This panel includes materials from the gene bank and materials used in sorghum breeding programs of this institution, as well as core collections from CIRAD and ICRISAT, and is therefore divided into two sub-panels. The 100 lines of sub-panel 1 were evaluated phenotypically for two years (2011 and 2012) and the 100 lines of sub-panel 2 for one year (2011), both in the city of Sete Lagoas, Minas Gerais, for the following phenotypic traits: days to flowering, plant height, fresh and dry matter yield and fiber, cellulose, hemicellulose and lignin proportions. Subsequently, the 200 lines were genotyped by via the genotyping by sequencing technique. From these genotypic and phenotypic data, genomic selection models Bayes A, Bayes B, Bayes Cπ, Bayes Lasso, Bayes Ridge Regression and Random Regression BLUP (RRBLUP) were fitted and compared. The predictive capabilities obtained were high and varied little between the different models, ranging from 0.61 for days to flowering to 0.85 for acid fiber, when the RRBLUP model was used on the combined analysis of the two sub-panels. On the other hand, cross prediction between sub-panels resulted in substantially lower predictive capability, never above 0.66 and in some scenarios virtually equal to zero, with greater variations between the fitted models. Simulations of using subsets of molecular markers are presented and indicate possibilities of achieving higher predictive capabilities. Functional enrichment analyses performed with the marker predicted effects suggested interesting associations, which should be investigated in more detail in future studies, with potential for elucidating the genetic architecture of quantitative traits.

<p>The studies in this thesis describe the development of a microarray based minisequencing system and its application to highly parallel genotyping of single nucleotide polymorphisms. The technical developments included identification of a three-dimensional microarray surface coating with high binding capacity for oligonucleotides modified with amino groups as the most optimal one for the system. The system was also established for multiplexed, reproducible quantitative analysis of SNP alleles both on the level of DNA and RNA. The sensitivity of the system to distinguish SNP alleles present as a minority in a mixed sample was found to be 1-6%. </p><p>The microarray based minisequencing system was applied in a pharmacogenetic study on antihypertensive drug response. A panel of 74 SNPs located in candidate genes related to blood pressure regulation were genotyped in DNA samples from hypertensive patients that had been treated with the antihypertensive drugs irbesartan or atenolol. Multiple regression analysis of the genotype data against the reduction in blood pressure identified genotype combinations of four to five SNPs that explain 44-56% of the reduction in blood pressure in the two treatment groups. The genotypes of two individual SNPs in the angiotensinogen (AGT) gene and a SNP in the low density lipoprotein receptor (LDLR) gene appeared to be associated to reduced blood pressure after treatment with atenolol, while a SNP in the apolipoprotein B (APOB) gene was associated to blood pressure reduction after irbesartan treatment. The genotype of one SNP in the adrenergic alpha-2A-receptor gene (ADRA2A) was related to the reduction in left ventricular mass following atenolol treatment while the genotypes of two SNPs, one in the APOB gene and one in the AGT gene were related to the reduction in left ventricular mass in the patients treated with irbesartan.</p>

<p>Single nucleotide polymorphisms (SNPs) are the most common form of genetic variation. We developed a novel multiplexed method for SNP genotyping based on four-color fluorophore tag-microarray minisequencing. This method allows simultaneous genotyping of 80 samples and up to 200 SNPs in any allele combination. In study I we set up the method for a panel of SNPs from genes in the type I interferon system, and applied it in study III. In study II we used the technique to genotype SNPs from the coding region of the mitochondrial genome. A panel of 150 SNPs was genotyped in 265 individuals representing nine different populations. We demonstrated that the multiplexed SNP genotyping method for mitochondrial DNA increases the power of forensic identification in combination with sequencing of the hypervariable region of mitochondrial DNA. </p><p>In study III we performed a genetic association study of SNPs in genes related to the type I Interferon system in Systemic Lupus Erythematosus (SLE). SLE is a chronic autoimmune inflammatory disease with a complex etiology. The SNPs were genotyped in DNA samples from Swedish, Finnish, and Icelandic patients with SLE, unaffected family members, and unrelated controls. The analysis identified SNPs in two genes, the tyrosine kinase 2 (TYK2) and interferon regulatory factor 5 (IRF5) genes that are highly associated with SLE with p-values <10^-7 for joint linkage and association. </p><p>Study IV describes the analysis of the TYK2 and IRF5 SNPs in a large Rheumatoid Arthritis (RA) sample cohort. We found that SNPs in the IRF5 gene were significantly associated with RA with a p-value = 0.00008. In contrast, we did not detect an association with SNPs in the TYK2 gene. These findings demonstrate that SLE and RA may have a common genetic background in the case of IRF5, while the TYK2 variants appear to be unique for SLE. </p>

<p>Many of our closest relatives, the primates, are endangered and could be extinct in a near future. To increase the knowledge of non-human primate genomes, and at the same time acquire information on our own genomic evolution, studies using high-throughput technologies are applied, which raises the demand for large amounts of high quality DNA.</p><p>In study I and II, we evaluated the multiple displacement amplification (MDA) technique, a whole genome amplification method, on a wide range of DNA sources, such as blood, hair and semen, by comparing MDA products to genomic DNA as templates for several commonly used genotyping methods. In general, the genotyping success rate from the MDA products was in concordance with the genomic DNA. The quality of sequences of the mitochondrial control region obtained from MDA products from blood and non-invasively collected semen samples was maintained. However, the readable sequence length was shorter for MDA products.</p><p>Few studies have focused on the genetic variation in the nuclear genes of non-human primates. In study III, we discovered 23 new single nucleotide polymorphisms (SNPs) in the Y-chromosome of the chimpanzee. We designed a tag-microarray minisequencing assay for genotyping the SNPs together with 19 SNPs from the literature and 45 SNPs in the mitochondrial DNA. Using the microarray, we were able to analyze the population structure of wild-living chimpanzees.</p><p>In study IV, we established 111 diagnostic nucleotide positions for primate genera determination. We used sequence alignments of the nuclear epsilon globin gene and apolipoprotein B gene to identify positions for determination on the infraorder and Catarrhini subfamily level, respectively, and sequence alignments of the mitochondrial 12S rRNA (MT-RNR1) to identify positions to distinguish between genera. We designed a microarray assay for immobilized minisequencing primers for genotyping these positions to aid in the forensic determination of an unknown sample.</p>

Single nucleotide polymorphisms (SNPs) are the most common form of genetic variation. We developed a novel multiplexed method for SNP genotyping based on four-color fluorophore tag-microarray minisequencing. This method allows simultaneous genotyping of 80 samples and up to 200 SNPs in any allele combination. In study I we set up the method for a panel of SNPs from genes in the type I interferon system, and applied it in study III. In study II we used the technique to genotype SNPs from the coding region of the mitochondrial genome. A panel of 150 SNPs was genotyped in 265 individuals representing nine different populations. We demonstrated that the multiplexed SNP genotyping method for mitochondrial DNA increases the power of forensic identification in combination with sequencing of the hypervariable region of mitochondrial DNA. In study III we performed a genetic association study of SNPs in genes related to the type I Interferon system in Systemic Lupus Erythematosus (SLE). SLE is a chronic autoimmune inflammatory disease with a complex etiology. The SNPs were genotyped in DNA samples from Swedish, Finnish, and Icelandic patients with SLE, unaffected family members, and unrelated controls. The analysis identified SNPs in two genes, the tyrosine kinase 2 (TYK2) and interferon regulatory factor 5 (IRF5) genes that are highly associated with SLE with p-values &lt;10-7 for joint linkage and association. Study IV describes the analysis of the TYK2 and IRF5 SNPs in a large Rheumatoid Arthritis (RA) sample cohort. We found that SNPs in the IRF5 gene were significantly associated with RA with a p-value = 0.00008. In contrast, we did not detect an association with SNPs in the TYK2 gene. These findings demonstrate that SLE and RA may have a common genetic background in the case of IRF5, while the TYK2 variants appear to be unique for SLE.

Studies on genetic variation can reveal effects on traits and disease, both in humans and in model organisms. Good technology for the analysis of DNA sequence variations is critical. Currently the development towards assays for large-scale and parallel DNA sequencing and genotyping is progressing rapidly. Single base primer extension (SBE) is a robust reaction principle based on four-colour fluorescent terminating nucleotides to interrogate all four DNA nucleotides in a single reaction. In this thesis, SBE methods were applied to the analysis and discovery of single nucleotide polymorphism (SNP) in the model organism Drosophila melanogaster and in humans. The tag-array minisequencing system in a microarray format is convenient for intermediate sized genotyping projects. The system is scalable and flexible to adapt to specialized and novel applications. In Study I of the thesis a tool was established to automate quality control of clustered genotype data. By calculating “Silhouette scores”, the SNP genotype assignment can be evaluated by a single numeric measure. Silhouette scores were then applied in Study I to compare the performance of four DNA polymerases and in Study III to evaluate freeze-dried reagents in the tag-array minisequencing system. The characteristics of the tag-array minisequencing system makes it suitable for inexpensive genome-wide gene mapping in the fruit fly. In Study II a high-resolution SNP map, and 293 genotyping assays, were established across the X, 2nd and 3rd chromosomes to distinguish commonly used Drosophila strains. A database of the SNP markers and a program for automatic allele calling and identification of map positions of mutants was also developed. The utility of the system was demonstrated by rapid mapping of 14 genes that disrupt embryonic muscle patterning. In Study III the tag-array minisequencing system was adapted to a lab-on-a-chip format for diagnostic testing for mutations in the TP53 gene. Freeze-drying was evaluated for storing reagents, including thermo-sensitive enzymes, on the microchip to reduce the complexity of the integrated test. Correct genotyping results were obtained using freeze-dried reagents in each reaction step of the genotyping protocol, both in test tubes and in single polymer test chambers. The results showed the potential of the approach to be implemented in fully integrated systems. The four-colour chemistry of SBE has been developed further to allow massively parallel sequencing (MPS) of short DNA fragments as in the Genome Analyzer system (Solexa/Illumina). In Study IV MPS was used to compare Nimblegen arrays and the SureSelect solution-based system for targeted enrichment of 56 continuous human candidate-gene regions totalling 3.1 Mb in size. Both methods detected known SNPs and discovered novel SNPs in the target regions, demonstrating the feasibility for complexity reduction of sequencing libraries by hybridization methods.

Many of our closest relatives, the primates, are endangered and could be extinct in a near future. To increase the knowledge of non-human primate genomes, and at the same time acquire information on our own genomic evolution, studies using high-throughput technologies are applied, which raises the demand for large amounts of high quality DNA. In study I and II, we evaluated the multiple displacement amplification (MDA) technique, a whole genome amplification method, on a wide range of DNA sources, such as blood, hair and semen, by comparing MDA products to genomic DNA as templates for several commonly used genotyping methods. In general, the genotyping success rate from the MDA products was in concordance with the genomic DNA. The quality of sequences of the mitochondrial control region obtained from MDA products from blood and non-invasively collected semen samples was maintained. However, the readable sequence length was shorter for MDA products. Few studies have focused on the genetic variation in the nuclear genes of non-human primates. In study III, we discovered 23 new single nucleotide polymorphisms (SNPs) in the Y-chromosome of the chimpanzee. We designed a tag-microarray minisequencing assay for genotyping the SNPs together with 19 SNPs from the literature and 45 SNPs in the mitochondrial DNA. Using the microarray, we were able to analyze the population structure of wild-living chimpanzees. In study IV, we established 111 diagnostic nucleotide positions for primate genera determination. We used sequence alignments of the nuclear epsilon globin gene and apolipoprotein B gene to identify positions for determination on the infraorder and Catarrhini subfamily level, respectively, and sequence alignments of the mitochondrial 12S rRNA (MT-RNR1) to identify positions to distinguish between genera. We designed a microarray assay for immobilized minisequencing primers for genotyping these positions to aid in the forensic determination of an unknown sample.

<p>In this thesis techniques are presented that aim to determine individual DNA signatures by controlled synthesis of nucleic acid multimers. Allele-specific extension reactions with an improved specificity were applied for several genomic purposes. Since DNA polymerases extend some mismatched 3’-end primers, an improved specificity is a concern. This has been possible by exploiting the faster extension of matched primers and applying the enzymes apyrase or Proteinase K. The findings were applied to methods for resequencing and viral and single nucleotide polymorphism (SNP) genotyping.</p><p>P53 mutation is the most frequent event in human cancers. Here, a model system for resequencing of 15 bps in p53 based on apyrase-mediated allele-specific extension (AMASE) is described, investigated and evaluated (Paper I). A microarray format with fluorescence detection was used. On each array, four oligonucleotides were printed for each base to resequence. Target PCR products were hybridized and an AMASE-reaction performed in situ to distinguish which of the printed oligonucleotides matched the target. The results showed that without the inclusion of apyrase, the resulting sequence was unreadable. The results open the possibilities for developing large-scale resequencing tools.</p><p>The presence of certain types of human papillomaviruses (HPV) transforms normal cells into cervical cancer cells. Thus, HPV type determination is clinically important. Also, multiple HPV infections are common but difficult to distinguish. Therefore, a genotyping platform based on competitive hybridization and AMASE is described, used on clinical sample material and evaluated by comparison to Sanger DNA sequencing (Papers II and III). A flexible tag-microarray was used for detection and the two levels of discrimination gave a high level of specificity. Easy identification of multiple infections was possible which provides new opportunities to investigate the importance of multiply infected samples.</p><p>To achieve highly multiplexed allele-specific extension reactions, large numbers of primers will be employed and lead to spurious hybridizations. Papers IV to VI focus on an alternative approach to control oligomerization by using protease mediated allele-specific extension (PrASE). In order to maintain stringency at higher temperatures, Proteinase K, was used instead of apyrase, leading to DNA polymerase degradation and preventing unspecific extensions. An automated assay with tag-array detection for SNP genotyping was established. First PrASE was introduced and characterized (Paper IV), then used for genotyping of 10 SNPs in 442 samples (Paper V). A 99.8 % concordance to pyrosequencing was found. PrASE is a flexible tool for association studies and the results indicate an improved assay conversion rate as compared to plain allele-specific extension.</p><p>The highly polymorphic melanocortin-1 receptor gene (MC1R) is involved in melanogenesis. Twenty-one MC1R variants were genotyped with PrASE since variants in the gene have been associated to an increased risk of developing melanoma. A pilot study was performed to establish the assay (Paper VI) and subsequently a larger study was executed to investigate allele frequencies in the Swedish population (Paper VII). The case and control groups consisted of 1001 and 721 samples respectively. A two to sevenfold increased risk of developing melanoma was observed for carriers of variants.</p>

Contexte. Les phénotypes ABO et Rh(D) des donneurs de sang ainsi que des patients transfusés sont analysés de façon routinière pour assurer une complète compatibilité. Ces analyses sont accomplies par agglutination suite à une réaction anticorps-antigènes. Cependant, pour des questions de coûts et de temps d’analyses faramineux, les dons de sang ne sont pas testés sur une base routinière pour les antigènes mineurs du sang. Cette lacune peut résulter à une allo-immunisation des patients receveurs contre un ou plusieurs antigènes mineurs et ainsi amener des sévères complications pour de futures transfusions. Plan d’étude et Méthodes. Pour ainsi aborder le problème, nous avons produit un panel génétique basé sur la technologie « GenomeLab _SNPstream» de Beckman Coulter, dans l’optique d’analyser simultanément 22 antigènes mineurs du sang. La source d’ADN provient des globules blancs des patients préalablement isolés sur papiers FTA. Résultats. Les résultats démontrent que le taux de discordance des génotypes, mesuré par la corrélation des résultats de génotypage venant des deux directions de l’ADN, ainsi que le taux d’échec de génotypage sont très bas (0,1%). Également, la corrélation entre les résultats de phénotypes prédit par génotypage et les phénotypes réels obtenus par sérologie des globules rouges et plaquettes sanguines, varient entre 97% et 100%. Les erreurs expérimentales ou encore de traitement des bases de données ainsi que de rares polymorphismes influençant la conformation des antigènes, pourraient expliquer les différences de résultats. Cependant, compte tenu du fait que les résultats de phénotypages obtenus par génotypes seront toujours co-vérifiés avant toute transfusion sanguine par les technologies standards approuvés par les instances gouvernementales, les taux de corrélation obtenus sont de loin supérieurs aux critères de succès attendus pour le projet. Conclusion. Le profilage génétique des antigènes mineurs du sang permettra de créer une banque informatique centralisée des phénotypes des donneurs, permettant ainsi aux banques de sang de rapidement retrouver les profiles compatibles entre les donneurs et les receveurs. / Background. ABO and Rh(D) phenotyping of both blood donors and transfused patients is routinely performed by blood banks to ensure compatibility. These analyses are done by antibody-based agglutination assays. However, blood is not routinely tested for minor blood group antigens on a regular basis because of cost and time constraints. This can result in alloimmunization of the patient against one or more minor antigens and may complicate future transfusions. Study design and Methods. To address this problem, we have generated an assay on the GenomeLab SNPstream genotyping system (Beckman Coulter, Fullerton, CA) to simultaneously test polymorphisms linked to 22 different blood antigens using donor’s DNA isolated from minute amounts of white blood cells. Results. The results showed that both the error rate of the assay, as measured by the strand concordance rate, and the no-call rate were very low (0.1%). The concordance rate with the actual red blood cell and platelet serology data varied from 97 to 100%. Experimental or database errors as well as rare polymorphisms contributing to antigen conformation could explain the observed differences. However, these rates are well above requirements since phenotyping and cross-matching will always be performed prior to transfusion. Conclusion. Molecular profiling of blood donors for minor red blood cell and platelet antigens will give blood banks instant access to many different compatible donors through the set-up of a centralized data storage system.