Plant pathogens are one of the biggest threats to plant health and food security worldwide. To effectively contain plant disease outbreaks, classification and precise identification of pathogens is crucial to determine treatment and preventive measurements. Conventional methods of detection such as PCR may not be sufficient when the pathogen in question is unknown. Advances in sequencing technology have made it possible to sequence entire genomes and metagenomes in real-time and at a relatively low cost, opening an opportunity for the development of alternative methods for detection of novel and unknown plant pathogens. Within this dissertation, an integrated approach is used to reclassify a high-impact group of plant pathogens. Additionally, the application of metagenomics and nanopore sequencing using the Oxford Nanopore Technologies (ONT) MinION for fungal and bacterial plant pathogen detection and precise identification are demonstrated. To improve the classification of the strains belonging to the Ralstonia solanacearum species complex (RSSC), we performed a meta-analysis using a comparative genomics and a reverse ecology approach to accurately portray and refine the understanding of the diversity and evolution of the RSSC. The groups identified by these approaches were circumscribed and made publicly available through the LINbase web server so future isolates can be properly classified. To develop a culture-free detection method of plant pathogens, we used metagenomes of various plants and long-read nanopore sequencing to precisely identify plant pathogens to the strain-level and performed phylogenetic analysis with SNP resolution. In the first paper, we used tomato plants to demonstrate the detection power of bacterial plant pathogens. We compared bioinformatics tools for detection at the strain-level using reads and assemblies. In the second paper, we used a read-based approach to test the feasibility of the methodology to precisely detect the fungal pathogen causing boxwood blight. Lastly, with the improvement in nanopore sequencing, we used grapevine petioles to investigate whether we can go beyond detection and identification and do a phylogenetic analysis. We assembled a metagenome-assembled genome (MAG) of almost the same quality as the genomes obtained from cultured isolates and did a phylogenetic analysis with SNP resolution. Finally, for the cases where there may be no related genome in the database like the pathogen in question, we used machine learning and metagenomics to develop a reference-free approach to detection of plant diseases. We trained eight different machine learning models with reads from healthy and infected plant metagenomes and compared the classification accuracy of reads as belonging to a healthy or infected plant. From the comparison, random forest was the best model in terms of computational resources needed while maintaining a high accuracy (> 0.90). / Doctor of Philosophy / Microbes are present in every environment on the planet and have been on Earth for billions of years. While some microbes are beneficial, others can cause diseases. To differentiate the ones causing diseases from those who do not, looking into the evolutionary forces making them different is crucial to classify and identify them correctly. Although microorganisms cause diseases in humans and animals, the ones causing diseases in plants are one of the biggest threats to plant health and food security worldwide. In a perfect world, plant diseases would be diagnosed by eye or simple procedures. However, when a plant disease is present, it is not always obvious which organism, if any, is causing the disease making it hard for outbreaks to be detected and contained promptly. With technological advances, it is now possible to obtain all the genetic information of not only one organism but all the organisms living in an environment at a time. This genetic information can then be used to precisely identify what organism is causing a disease in a plant for faster disease diagnosis and, consequently, more efficient disease prevention and control. In this dissertation, we used the bacterial group, called Ralstonia solanacearum species complex, which can cause different diseases in more than 200 crops, to investigate and understand the evolution and diversity of the members of this group. We also used newly developed technologies to obtain the genetic material of all the organisms living in multiple important plants including tomato, grapevine, and the ornamental bush, boxwood. Using this genetic material, we developed a methodology for the detection of bacteria and a fungus causing plant diseases. While this works well when the suspected organism or a similar one is available for comparison, the detection of plant diseases in cases where this information is not available is challenging. Machine learning models, where computers can learn complex patterns from data, have the potential to detect pathogens without the need to compare the sequences to sequences of other pathogens. Here we also used the genetic material to train and compare different machine learning models to classify plants as either being infected or healthy.

Epigenetics are stable heritable traits that are not a result of the DNA sequence. Epigenetic modification of DNA cytosine plays a role in development and disease. The covalent bonding of a methyl group or a hydroxymethyl group to the 5-carbon of cytosine epigenetically modifies cytosine to 5-methylcytosine or 5-hydroxymethylcytosine. Upon PCR amplification, the bisulfite treatment of DNA converts unmethylated cytosine to thymine, while 5-methylcytosine, 5-hydroxymethylcytosine, and other bases remain unchanged. The resulting sequences can be mapped to a reference genome; however, this can be challenging due to sequencing technology complexity, low sequence complexity, and biases and errors introduced with bisulfite treatment. Once the short read is mapped, the identity of 5-methylcytosine or 5-hydroxymethylcytosine can be determined by comparing the mapped read to the aligned reference genome. Bisulfite DNA read mapping is characterized by mapping performance as low as 40%. This research improves bisulfite short read mapping quality. First, reads generated from the bisulfite hairpin PCR protocol are used to study mapping failure and solutions. A read may not map to the genome; it may map uniquely, or it may map to multiple locations. Sequence complexity correlates with these mapping categories. The hairpin protocol allows for a recovery, in some cases, of the original untreated read, and mapping this read with the regular read mapper Bowtie2 improved mapper performance by 10%. New bisulfite read mapping software called BisPin was created that calls BFAST (BLAT-like Fast Accurate Search Tool) for mapping. BisPin resolves ambiguously mapped reads with a rescoring strategy, which yields a statistically significant improvement. BFAST-Gap for Ion Torrent reads was developed, since Ion Torrent machines are less expensive than Illumina machines and since Ion Torrent reads are longer. There are few mappers for Ion Torrent data. BFAST-Gap uses homopolymer run length for contextual gap penalty functions, since homopolymer runs cause errors in Ion Torrent reads. In conjunction with BisPin, this software performed well on real and simulated bisulfite Ion Torrent data and Illumina data. InfoTrim, a read trimmer with an entropy term, was developed with competitive results. / Ph. D.

Viruses have huge impact on controlling diseases and regulating many key ecosystem processes. As metagenomic data can contain many microbiomes including many viruses, by analyzing metagenomic data we can analyze many viruses at the same time. The first step towards analyzing metagenomic data is to identify and quantify viruses present in the data. In order to answer this question, we developed a computational pipeline, FastViromeExplorer. FastViromeExplorer leverages a pseudoalignment based approach, which is faster than the traditional alignment based approach to quickly align millions/billions of reads. Application of FastViromeExplorer on both human gut samples and environmental samples shows that our tool can successfully identify viruses and quantify the abundances of viruses quickly and accurately even for a large data set. As viruses are getting increased attention in recent times, most of the viruses are still unknown or uncategorized. To discover novel viruses from metagenomic data, we developed a computational pipeline named FVE-novel. FVE-novel leverages a hybrid of both reference based and de novo assembly approach to recover novel viruses from metagenomic data. By applying FVE-novel to an ocean metagenome sample, we successfully recovered two novel viruses and two different strains of known phages. Analysis of viral assemblies from metagenomic data reveals that viral assemblies often contain assembly errors like chimeric sequences which means more than one viral genomes are incorrectly assembled together. In order to identify and fix these types of assembly errors, we developed a computational tool called VirChecker. Our tool can identify and fix assembly errors due to chimeric assembly. VirChecker also extends the assembly as much as possible to complete it and then annotates the extended and improved assembly. Application of VirChecker to viral scaffolds collected from an ocean meatgenome sample shows that our tool successfully fixes the assembly errors and extends two novel virus genomes and two strains of known phage genomes. / Doctor of Philosophy / Virus, the most abundant micro-organism on earth has a profound impact on human health and environment. Analyzing metagenomic data for viruses has the beneFIt of analyzing many viruses at a time without the need of cultivating them in the lab environment. Here, in this dissertation, we addressed three research problems of analyzing viruses from metagenomic data. To analyze viruses in metagenomic data, the first question needs to answer is what viruses are there and at what quantity. To answer this question, we developed a computational pipeline, FastViromeExplorer. Our tool can identify viruses from metagenomic data and quantify the abundances of viruses present in the data quickly and accurately even for a large data set. To recover novel virus genomes from metagenomic data, we developed a computational pipeline named FVE-novel. By applying FVE-novel to an ocean metagenome sample, we successfully recovered two novel viruses and two strains of known phages. Examination of viral assemblies from metagenomic data reveals that due to the complex nature of metagenome data, viral assemblies often contain assembly errors and are incomplete. To solve this problem, we developed a computational pipeline, named VirChecker, to polish, extend and annotate viral assemblies. Application of VirChecker to virus genomes recovered from an ocean metagenome sample shows that our tool successfully extended and completed those virus genomes.

Many children in the United States struggle with mental health issues. The increase in mental health difficulties for children and adolescents has increased so greatly after the COVID19 pandemic that it has been declared a national mental health emergency by the American Academy of Pediatrics, the American Academy of Child and Adolescent Psychiatry and the Children’s Hospital Association (AAP et al., 2021). The burden to provide children with socialemotional learning, opportunities, access, and support often falls on teachers, and this burden can be particularly acute in rural communities, stemming from the limited availability of resources. Using picturebooks through means such as developmental bibliotherapy is one way for educators to address the increasing need to care for children’s social and emotional wellness in schools. This self-study explored my lived experience reading and connecting with award-winning Mo Willems picturebooks for emotional literacy content and considering the possibility of using them in interactive read-aloud sessions. Analyses revealed four overarching themes: (a) my personal journey, (b) discovering emotions in characters, (c) the importance of relationships, and (d) nurturing and recognizing positivity. These findings highlight important implications for supporting young children’s emotional literacy through interactive read-alouds, emphasizing the idea that teaching is a personal act, the potential for interactive read-alouds to provide hope or positivity, and the opportunities afforded to foster meaningful interactions with text through developmental bibliotherapy. This study may inform future work regarding teaching and supporting social-emotional learning concepts for young children, specifically applying insights related to pedagogy, teacher perspective, and student learning.

The purpose of this study is to develop a readiness program which will be an aid in eliminating many failures in reading and to help the children be happy while learning to read.

This is a study of how four teachers work with pupils’ early literacy learning. Interviews were conducted with two teachers who chose to use a specific method, Writing to Read (WTR), for teaching pupils to read, and with two teachers who had not chosen a specific method. The aim of the study was to compare how the teachers worked, their motives for their choice of method, and the ideas the teachers have about early literacy learning. To see whether the teachers’ choice of method was related to the individualization of the teaching and their views of pupils’ learning in interaction, Vygotsky’s theories about children’s learning have been used. The result shows that there are both similarities and differences in the teachers’ reasons for their choice of method. Those who use WTR say that they do so to be able to individualize the teaching, while the teachers who do not use a specific method use the same arguments. There is a difference in whether the teachers aim for structured or unstructured teaching, regardless of the choice of method. Several parallels to Vygotsky’s theories were found, in that all four teachers, irrespective of method, think that their teaching should be characterized by interaction and individualization.

Made available in DSpace on 2016-08-03T16:16:11Z (GMT). No. of bitstreams: 1 Maria Matilde Antonelli.pdf: 3019163 bytes, checksum: b1fa56e5a12288562365f215644e6ba2 (MD5) Previous issue date: 2009-03-19 / This work aims to investigate the knowledge present in the pedagogical practice of six teachers who during their professional career presented a successful practice in teaching how to read and write, always acting in the peripheral region of one city of Big São Paulo. In this study I used semi-structured interviews, participant observation and report of their life history with the intention to answer the following questions: What is there of significance in the well succeeded practice of these teachers? Which knowledge is mobilized with students in the process of reading and writing? How do the teachers deal with different knowledge of the students and with the situations that they face with a possible absence of knowledge? Initially I describe the historical context of the read and write process in 1983 with the implantation of the Basic Cycle (DURAN, 1995), period in which the target teachers of this research began their teaching career in the state web of schools and were challenged to face a new forms of thinking the read and write process within the psychogenesis of the written language (FERREIRO AND TEBEROSKY, 1979), which takes as basis the Piaget constructivism in a dialogic action with authors who prioritize the reflection on knowledge and pedagogical practice. (FREIRE, 1996, OLIVEIRA, 1997, ALARCÃO 2005 AND TARDIF, 2007). The results show that the construction of knowledge of the teachers in the conduct of the work in classrooms occur along with the trajectory of formation and pedagogical acting in different moments. In the dialogue with live experience with produced pedagogical material in the relation with the children they work with in the course of formation in which they take part in the partnership and exchanges with teachers. The creativity facing the challenges of read/write process make they reorganize the knowledge and look for knowledge in which the quality of their intervention and pedagogical actions attend the diversity which constitutes the classroom space. Because they believe in the capacity of children they present challenging activities which can make possible the reflection on the reading and writing processes. Always respecting the previous knowledge of the students who interact with them and constructing knowledge.(AU) / Objetivando investigar os saberes presentes na prática pedagógica de seis professoras que, ao longo de sua trajetória profissional, apresentaram uma prática bem-sucedida na alfabetização, sempre atuando em região periférica de uma cidade da Grande São Paulo, utilizei, neste estudo, entrevista semiestruturada, observação participante e relato de história de vida, no intuito de responder às questões: O que há de significativo nas práticas bem-sucedidas das professoras alfabetizadoras? Quais saberes são mobilizados com os educandos no processo de alfabetização? Como as professoras lidam com diferentes saberes dos alunos e com as situações em que se defrontam com um possível não saber? Inicialmente, descrevo o contexto histórico da alfabetização em 1983, com a implantação do Ciclo Básico de Alfabetização (DURAN, 1995), período em que as professoras-alvo da pesquisa iniciaram carreira no magistério na rede pública estadual e foram desafiadas a uma nova forma de pensar a alfabetização no âmbito da Psicogênese da Língua Escrita (FERREIRO e TEBEROSKY, 1979), embasadas no construtivismo piagetiano, numa ação dialógica com autores que priorizam a reflexão sobre saberes e prática pedagógica (FREIRE, 1996; OLIVEIRA, 1997; ALARCÃO, 2005 e TARDIF, 2007). Os resultados mostram que a constituição dos saberes das professoras na condução do trabalho em sala de aula ocorre ao longo da trajetória de formação e atuação pedagógica, em diferentes momentos: no diálogo com experiências vividas, com materiais pedagógicos produzidos; na relação com as crianças com quem convivem; nos cursos de formação de que participam; nas parcerias e trocas com professores. A criatividade diante dos desafios de alfabetizar faz com que reorganizem o saber e busquem conhecimentos para que a qualidade das intervenções e ações pedagógicas atenda a diversidade que compõe o espaço da sala de aula. Por acreditarem na capacidade das crianças, propiciam atividades desafiadoras que oportunizam a reflexão sobre a leitura e a escrita (FERREIRO, 1989, LERNER, 2002 & WEISZ, 2002), sempre respeitando os conhecimentos prévios do aprendiz que interage com elas e constrói conhecimentos.(AU)

I skolans tidigare åldrar fokuseras till stor del på läs- och skrivutveckling och vilka metoder som lämpar sig bäst för elevers lärande. Den här systematiska litteraturstudien handlar om elevers tidiga skrivutveckling med hjälp av digitala verktyg och att skriva sig till läsning (ASL-metoden). Syftet är att studera om digitala verktyg och ASL-metoden kan gynna elevers tidiga skrivande. Studiens syfte och frågeställning besvaras med en analys av flertalet vetenskapliga artiklar. Resultatet visar att digitala verktyg och ASL-metoden kan vara ett bra komplement till den mer traditionella skrivundervisningen med penna och papper. Dock visar ett resultat att bland det viktigaste, oavsett modell, är att skrivundervisningen behöver vara systematisk och tydligt strukturerad.

The aim of this thesis is the development and benchmarking of computational methods for the analysis of high-throughput data from tiling arrays and next-generation sequencing. Tiling arrays have been a mainstay of genome-wide transcriptomics, e.g., in the identification of functional elements in the human genome. Due to limitations of existing methods for the data analysis of this data, a novel statistical approach is presented that identifies expressed segments as significant differences from the background distribution and thus avoids dataset-specific parameters. This method detects differentially expressed segments in biological data with significantly lower false discovery rates and equivalent sensitivities compared to commonly used methods. In addition, it is also clearly superior in the recovery of exon-intron structures. Moreover, the search for local accumulations of expressed segments in tiling array data has led to the identification of very large expressed regions that may constitute a new class of macroRNAs. This thesis proceeds with next-generation sequencing for which various protocols have been devised to study genomic, transcriptomic, and epigenomic features. One of the first crucial steps in most NGS data analyses is the mapping of sequencing reads to a reference genome. This work introduces algorithmic methods to solve the mapping tasks for three major NGS protocols: DNA-seq, RNA-seq, and MethylC-seq. All methods have been thoroughly benchmarked and integrated into the segemehl mapping suite. First, mapping of DNA-seq data is facilitated by the core mapping algorithm of segemehl. Since the initial publication, it has been continuously updated and expanded. Here, extensive and reproducible benchmarks are presented that compare segemehl to state-of-the-art read aligners on various data sets. The results indicate that it is not only more sensitive in finding the optimal alignment with respect to the unit edit distance but also very specific compared to most commonly used alternative read mappers. These advantages are observable for both real and simulated reads, are largely independent of the read length and sequencing technology, but come at the cost of higher running time and memory consumption. Second, the split-read extension of segemehl, presented by Hoffmann, enables the mapping of RNA-seq data, a computationally more difficult form of the mapping task due to the occurrence of splicing. Here, the novel tool lack is presented, which aims to recover missed RNA-seq read alignments using de novo splice junction information. It performs very well in benchmarks and may thus be a beneficial extension to RNA-seq analysis pipelines. Third, a novel method is introduced that facilitates the mapping of bisulfite-treated sequencing data. This protocol is considered the gold standard in genome-wide studies of DNA methylation, one of the major epigenetic modifications in animals and plants. The treatment of DNA with sodium bisulfite selectively converts unmethylated cytosines to uracils, while methylated ones remain unchanged. The bisulfite extension developed here performs seed searches on a collapsed alphabet followed by bisulfite-sensitive dynamic programming alignments. Thus, it is insensitive to bisulfite-related mismatches and does not rely on post-processing, in contrast to other methods. In comparison to state-of-the-art tools, this method achieves significantly higher sensitivities and performs time-competitive in mapping millions of sequencing reads to vertebrate genomes. Remarkably, the increase in sensitivity does not come at the cost of decreased specificity and thus may finally result in a better performance in calling the methylation rate. Lastly, the potential of mapping strategies for de novo genome assemblies is demonstrated with the introduction of a new guided assembly procedure. It incorporates mapping as major component and uses the additional information (e.g., annotation) as guide. With this method, the complete mitochondrial genome of Eulimnogammarus verrucosus has been successfully assembled even though the sequencing library has been heavily dominated by nuclear DNA. In summary, this thesis introduces algorithmic methods that significantly improve the analysis of tiling array, DNA-seq, RNA-seq, and MethylC-seq data, and proposes standards for benchmarking NGS read aligners. Moreover, it presents a new guided assembly procedure that has been successfully applied in the de novo assembly of a crustacean mitogenome. / Diese Arbeit befasst sich mit der Entwicklung und dem Benchmarken von Verfahren zur Analyse von Daten aus Hochdurchsatz-Technologien, wie Tiling Arrays oder Hochdurchsatz-Sequenzierung. Tiling Arrays bildeten lange Zeit die Grundlage für die genomweite Untersuchung des Transkriptoms und kamen beispielsweise bei der Identifizierung funktioneller Elemente im menschlichen Genom zum Einsatz. In dieser Arbeit wird ein neues statistisches Verfahren zur Auswertung von Tiling Array-Daten vorgestellt. Darin werden Segmente als exprimiert klassifiziert, wenn sich deren Signale signifikant von der Hintergrundverteilung unterscheiden. Dadurch werden keine auf den Datensatz abgestimmten Parameterwerte benötigt. Die hier vorgestellte Methode erkennt differentiell exprimierte Segmente in biologischen Daten bei gleicher Sensitivität mit geringerer Falsch-Positiv-Rate im Vergleich zu den derzeit hauptsächlich eingesetzten Verfahren. Zudem ist die Methode bei der Erkennung von Exon-Intron Grenzen präziser. Die Suche nach Anhäufungen exprimierter Segmente hat darüber hinaus zur Entdeckung von sehr langen Regionen geführt, welche möglicherweise eine neue Klasse von macroRNAs darstellen. Nach dem Exkurs zu Tiling Arrays konzentriert sich diese Arbeit nun auf die Hochdurchsatz-Sequenzierung, für die bereits verschiedene Sequenzierungsprotokolle zur Untersuchungen des Genoms, Transkriptoms und Epigenoms etabliert sind. Einer der ersten und entscheidenden Schritte in der Analyse von Sequenzierungsdaten stellt in den meisten Fällen das Mappen dar, bei dem kurze Sequenzen (Reads) auf ein großes Referenzgenom aligniert werden. Die vorliegende Arbeit stellt algorithmische Methoden vor, welche das Mapping-Problem für drei wichtige Sequenzierungsprotokolle (DNA-Seq, RNA-Seq und MethylC-Seq) lösen. Alle Methoden wurden ausführlichen Benchmarks unterzogen und sind in der segemehl-Suite integriert. Als Erstes wird hier der Kern-Algorithmus von segemehl vorgestellt, welcher das Mappen von DNA-Sequenzierungsdaten ermöglicht. Seit der ersten Veröffentlichung wurde dieser kontinuierlich optimiert und erweitert. In dieser Arbeit werden umfangreiche und auf Reproduzierbarkeit bedachte Benchmarks präsentiert, in denen segemehl auf zahlreichen Datensätzen mit bekannten Mapping-Programmen verglichen wird. Die Ergebnisse zeigen, dass segemehl nicht nur sensitiver im Auffinden von optimalen Alignments bezüglich der Editierdistanz sondern auch sehr spezifisch im Vergleich zu anderen Methoden ist. Diese Vorteile sind in realen und simulierten Daten unabhängig von der Sequenzierungstechnologie oder der Länge der Reads erkennbar, gehen aber zu Lasten einer längeren Laufzeit und eines höheren Speicherverbrauchs. Als Zweites wird das Mappen von RNA-Sequenzierungsdaten untersucht, welches bereits von der Split-Read-Erweiterung von segemehl unterstützt wird. Aufgrund von Spleißen ist diese Form des Mapping-Problems rechnerisch aufwendiger. In dieser Arbeit wird das neue Programm lack vorgestellt, welches darauf abzielt, fehlende Read-Alignments mit Hilfe von de novo Spleiß-Information zu finden. Es erzielt hervorragende Ergebnisse und stellt somit eine sinnvolle Ergänzung zu Analyse-Pipelines für RNA-Sequenzierungsdaten dar. Als Drittes wird eine neue Methode zum Mappen von Bisulfit-behandelte Sequenzierungsdaten vorgestellt. Dieses Protokoll gilt als Goldstandard in der genomweiten Untersuchung der DNA-Methylierung, einer der wichtigsten epigenetischen Modifikationen in Tieren und Pflanzen. Dabei wird die DNA vor der Sequenzierung mit Natriumbisulfit behandelt, welches selektiv nicht methylierte Cytosine zu Uracilen konvertiert, während Methylcytosine davon unberührt bleiben. Die hier vorgestellte Bisulfit-Erweiterung führt die Seed-Suche auf einem reduziertem Alphabet durch und verifiziert die erhaltenen Treffer mit einem auf dynamischer Programmierung basierenden Bisulfit-sensitiven Alignment-Algorithmus. Das verwendete Verfahren ist somit unempfindlich gegenüber Bisulfit-Konvertierungen und erfordert im Gegensatz zu anderen Verfahren keine weitere Nachverarbeitung. Im Vergleich zu aktuell eingesetzten Programmen ist die Methode sensitiver und benötigt eine vergleichbare Laufzeit beim Mappen von Millionen von Reads auf große Genome. Bemerkenswerterweise wird die erhöhte Sensitivität bei gleichbleibend guter Spezifizität erreicht. Dadurch könnte diese Methode somit auch bessere Ergebnisse bei der präzisen Bestimmung der Methylierungsraten erreichen. Schließlich wird noch das Potential von Mapping-Strategien für Assemblierungen mit der Einführung eines neuen, Kristallisation-genanntes Verfahren zur unterstützten Assemblierung aufgezeigt. Es enthält Mapping als Hauptbestandteil und nutzt Zusatzinformation (z.B. Annotationen) als Unterstützung. Dieses Verfahren ermöglichte die erfolgreiche Assemblierung des kompletten mitochondrialen Genoms von Eulimnogammarus verrucosus trotz einer vorwiegend aus nukleärer DNA bestehenden genomischen Bibliothek. Zusammenfassend stellt diese Arbeit algorithmische Methoden vor, welche die Analysen von Tiling Array, DNA-Seq, RNA-Seq und MethylC-Seq Daten signifikant verbessern. Es werden zudem Standards für den Vergleich von Programmen zum Mappen von Daten der Hochdurchsatz-Sequenzierung vorgeschlagen. Darüber hinaus wird ein neues Verfahren zur unterstützten Genom-Assemblierung vorgestellt, welches erfolgreich bei der de novo-Assemblierung eines mitochondrialen Krustentier-Genoms eingesetzt wurde.

This study examines a reader used in grade 1, Den magiska kulan, which is a part of the ABC-klubben series of teaching material. It is level-based, available in three different levels of difficulty, and one and the same class is supposed to share the same reading experience but be able to read the story at the level that each individual pupil has reached. The study analyses linguistic adaptation and elements intended to give motivation in the different books. The study shows that the simplest of the books may not help to increase the pupils’ motivation for reading but can only be regarded as training in decoding. The two more advanced books can give pupils more pleasurable reading because the language is more nuanced and expressive. The pupils thus have the chance to become absorbed in the books, with an understanding for the characters and events.