Genome-wide analysis of G-type lectin genes in Fragaria vesca and functional characterization of FaMBL1 gene in defense response of F. × ananassa to fungal pathogens

Strawberry (Fragaria × ananassa) is an important soft fruit but easily to be infected by pathogens. Anthracnose and gray mold are two of the most destructive diseases of strawberry which lead to serious fruit rot. The first chapter introduced strawberry anthracnose caused by Colletotrichum acutatum. The infection strategy, disease cycle and management of C. acutatum on strawberry were reported. Likewise, the second chapter summarized the infection strategy of Botrytis cinerea and the defense responses of strawberry. As we already know white unripe strawberry fruits are more resistant to C. acutatum than red ripe fruits. During the interaction between strawberry white/red fruit and C. acutaum, a mannose binding lectin gene, FaMBL1, was found to be the most up-regulated gene and induced exclusively in white fruit. FaMBL1 belongs to the G-type lectin family which has important roles in plant development and defense process. To get insight into the role of FaMBL1, genome-wide identification was carried out on G-type lectin gene family in Fragaria vesca and the results were showed in chapter 3. G-type lectin genes make up a large family in F. vesca. Active expression upon biotic/abiotic stresses suggested a potential role of G-lectin genes in strawberry defenses. Hence, stable transgenic strawberry plants with FaMBL1 gene overexpressed were generated. Transformed strawberry plants were screened and identified. The results were showed in chapter 4, content of disease-related phytohormone, jasmonic acid, was found decreased in overexpressing lines compared with wild type (WT). Petioles inoculated by C. fioriniae of overexpressing lines had lower disease incidence than WT. Leaves of overexpressing lines challenged by B. cinerea showed remarkably smaller lesion diameters compared with WT. The chitinase 2-1 (FaChi2-1) showed higher expression in overexpressing lines than in WT during the interaction with B. cinerea, which could be related with the lower susceptibility of overexpressing lines.

Design and implementation of bioinformatics tools for large scale genome annotation

The continuous increase of genome sequencing projects produced a huge amount of data in the last 10 years: currently more than 600 prokaryotic and 80 eukaryotic genomes are fully sequenced and publically available. However the sole sequencing process of a genome is able to determine just raw nucleotide sequences. This is only the first step of the genome annotation process that will deal with the issue of assigning biological information to each sequence. The annotation process is done at each different level of the biological information processing mechanism, from DNA to protein, and cannot be accomplished only by in vitro analysis procedures resulting extremely expensive and time consuming when applied at a this large scale level. Thus, in silico methods need to be used to accomplish the task. The aim of this work was the implementation of predictive computational methods to allow a fast, reliable, and automated annotation of genomes and proteins starting from aminoacidic sequences. The first part of the work was focused on the implementation of a new machine learning based method for the prediction of the subcellular localization of soluble eukaryotic proteins. The method is called BaCelLo, and was developed in 2006. The main peculiarity of the method is to be independent from biases present in the training dataset, which causes the over‐prediction of the most represented examples in all the other available predictors developed so far. This important result was achieved by a modification, made by myself, to the standard Support Vector Machine (SVM) algorithm with the creation of the so called Balanced SVM. BaCelLo is able to predict the most important subcellular localizations in eukaryotic cells and three, kingdom‐specific, predictors were implemented. In two extensive comparisons, carried out in 2006 and 2008, BaCelLo reported to outperform all the currently available state‐of‐the‐art methods for this prediction task. BaCelLo was subsequently used to completely annotate 5 eukaryotic genomes, by integrating it in a pipeline of predictors developed at the Bologna Biocomputing group by Dr. Pier Luigi Martelli and Dr. Piero Fariselli. An online database, called eSLDB, was developed by integrating, for each aminoacidic sequence extracted from the genome, the predicted subcellular localization merged with experimental and similarity‐based annotations. In the second part of the work a new, machine learning based, method was implemented for the prediction of GPI‐anchored proteins. Basically the method is able to efficiently predict from the raw aminoacidic sequence both the presence of the GPI‐anchor (by means of an SVM), and the position in the sequence of the post‐translational modification event, the so called ω‐site (by means of an Hidden Markov Model (HMM)). The method is called GPIPE and reported to greatly enhance the prediction performances of GPI‐anchored proteins over all the previously developed methods. GPIPE was able to predict up to 88% of the experimentally annotated GPI‐anchored proteins by maintaining a rate of false positive prediction as low as 0.1%. GPIPE was used to completely annotate 81 eukaryotic genomes, and more than 15000 putative GPI‐anchored proteins were predicted, 561 of which are found in H. sapiens. In average 1% of a proteome is predicted as GPI‐anchored. A statistical analysis was performed onto the composition of the regions surrounding the ω‐site that allowed the definition of specific aminoacidic abundances in the different considered regions. Furthermore the hypothesis that compositional biases are present among the four major eukaryotic kingdoms, proposed in literature, was tested and rejected. All the developed predictors and databases are freely available at: BaCelLo http://gpcr.biocomp.unibo.it/bacello eSLDB http://gpcr.biocomp.unibo.it/esldb GPIPE http://gpcr.biocomp.unibo.it/gpipe

Computational methods for genome screening

Motivation An actual issue of great interest, both under a theoretical and an applicative perspective, is the analysis of biological sequences for disclosing the information that they encode. The development of new technologies for genome sequencing in the last years, opened new fundamental problems since huge amounts of biological data still deserve an interpretation. Indeed, the sequencing is only the first step of the genome annotation process that consists in the assignment of biological information to each sequence. Hence given the large amount of available data, in silico methods became useful and necessary in order to extract relevant information from sequences. The availability of data from Genome Projects gave rise to new strategies for tackling the basic problems of computational biology such as the determination of the tridimensional structures of proteins, their biological function and their reciprocal interactions. Results The aim of this work has been the implementation of predictive methods that allow the extraction of information on the properties of genomes and proteins starting from the nucleotide and aminoacidic sequences, by taking advantage of the information provided by the comparison of the genome sequences from different species. In the first part of the work a comprehensive large scale genome comparison of 599 organisms is described. 2,6 million of sequences coming from 551 prokaryotic and 48 eukaryotic genomes were aligned and clustered on the basis of their sequence identity. This procedure led to the identification of classes of proteins that are peculiar to the different groups of organisms. Moreover the adopted similarity threshold produced clusters that are homogeneous on the structural point of view and that can be used for structural annotation of uncharacterized sequences. The second part of the work focuses on the characterization of thermostable proteins and on the development of tools able to predict the thermostability of a protein starting from its sequence. By means of Principal Component Analysis the codon composition of a non redundant database comprising 116 prokaryotic genomes has been analyzed and it has been showed that a cross genomic approach can allow the extraction of common determinants of thermostability at the genome level, leading to an overall accuracy in discriminating thermophilic coding sequences equal to 95%. This result outperform those obtained in previous studies. Moreover, we investigated the effect of multiple mutations on protein thermostability. This issue is of great importance in the field of protein engineering, since thermostable proteins are generally more suitable than their mesostable counterparts in technological applications. A Support Vector Machine based method has been trained to predict if a set of mutations can enhance the thermostability of a given protein sequence. The developed predictor achieves 88% accuracy.

Identificazione di un QTL principale per resistenza a ruggine bruna sul cromosoma 7B di frumento duro

Leaf rust caused by Puccinia triticina is a serious disease of durum wheat (Triticum durum) worldwide. However, genetic and molecular mapping studies aimed at characterizing leaf rust resistance genes in durum wheat have been only recently undertaken. The Italian durum wheat cv. Creso shows a high level of resistance to P. triticina that has been considered durable and that appears to be due to a combination of a single dominant gene and one or more additional factors conferring partial resistance. In this study, the genetic basis of leaf rust resistance carried by Creso was investigated using 176 recombinant inbred lines (RILs) from the cross between the cv. Colosseo (C, leaf rust resistance donor) and Lloyd (L, susceptible parent). Colosseo is a cv. directly related to Creso with the leaf rust resistance phenotype inherited from Creso, and was considered as resistance donor because of its better adaptation to local (Emilia Romagna, Italy) cultivation environment. RILs have been artificially inoculated with a mixture of 16 Italian P. triticina isolates that were characterized for virulence to seedlings of 22 common wheat cv. Thatcher isolines each carrying a different leaf rust resistance gene, and for molecular genotypes at 15 simple sequence repeat (SSR) loci, in order to determine their specialization with regard to the host species. The characterization of the leaf rust isolates was conducted at the Cereal Disease Laboratory of the University of Minnesota (St. Paul, USA) (Chapter 2). A genetic linkage map was constructed using segregation data from the population of 176 RILs from the cross CL. A total of 662 loci, including 162 simple sequence repeats (SSRs) and 500 Diversity Arrays Technology markers (DArTs), were analyzed by means of the package EasyMap 0.1. The integrated SSR-DArT linkage map consisted of 554 loci (162 SSR and 392 DArT markers) grouped into 19 linkage blocks with an average marker density of 5.7 cM/marker. The final map spanned a total of 2022 cM, which correspond to a tetraploid genome (AABB) coverage of ca. 77% (Chapter 3). The RIL population was phenotyped for their resistance to leaf rust under artificial inoculation in 2006; the percentage of infected leaf area (LRS, leaf rust susceptibility) was evaluated at three stages through the disease developmental cycle and the area under disease progress curve (AUDPC) was then calculated. The response at the seedling stage (infection type, IT) was also investigated. QTL analysis was carried out by means of the Composite Interval Mapping method based on a selection of markers from the CL map. A major QTL (QLr.ubo-7B.2) for leaf rust resistance controlling both the seedling and the adult plant response, was mapped on the distal region of chromosome arm 7BL (deletion bin 7BL10-0.78-1.00), in a gene-dense region known to carry several genes/QTLs for resistance to rusts and other major cereal fungal diseases in wheat and barley. QLr.ubo-7B.2 was identified within a supporting interval of ca. 5 cM tightly associated with three SSR markers (Xbarc340.2, Xgwm146 e Xgwm344.2), and showed an R2 and an LOD peak value for the AUDPC equal to 72.9% an 44.5, respectively. Three additional minor QTLs were also detected (QLr.ubo-7B.1 on chr. 7BS; QLr.ubo-2A on chr. 2AL and QLr.ubo-3A on chr. 3AS) (Chapter 4). The presence of the major QTL (QLr.ubo-7B.2) was validated by a linkage disequilibrium (LD)-based test using field data from two different plant materials: i) a set of 62 advanced lines from multiple crosses involving Creso and his directly related resistance derivates Colosseo and Plinio, and ii) a panel of 164 elite durum wheat accessions representative of the major durum breeding program of the Mediterranean basin. Lines and accessions were phenotyped for leaf rust resistance under artificial inoculation in two different field trials carried out at Argelato (BO, Italy) in 2006 and 2007; the durum elite accessions were also evaluated in two additional field experiments in Obregon (Messico; 2007 and 2008) and in a green-house experiment (seedling resistance) at the Cereal Disease Laboratory (St. Paul, USA, 2008). The molecular characterization involved 14 SSR markers mapping on the 7BL chromosome region found to harbour the major QTL. Association analysis was then performed with a mixed-linear-model approach. Results confirmed the presence of a major QTL for leaf rust resistance, both at adult plant and at seedling stage, located between markers Xbarc340.2, Xgwm146 and Xgwm344.2, in an interval that coincides with the supporting interval (LOD-2) of QLr.ubo-7B.2 as resulted from the RIL QTL analysis. (Chapter 5). The identification and mapping of the major QTL associated to the durable leaf rust resistance carried by Creso, together with the identification of the associated SSR markers, will enhance the selection efficiency in durum wheat breeding programs (MAS, Marker Assisted Selection) and will accelerate the release of cvs. with durable resistance through marker-assisted pyramiding of the tagged resistance genes/QTLs most effective against wheat fungal pathogens.

Mitochondrial Genomics: structure, inheritance and phylogenetic utility of the Mitochondrial genome in Bivalvia and Insecta

This PhD Thesis is the result of my research activity in the last three years. My main research interest was centered on the evolution of mitochondrial genome (mtDNA), and on its usefulness as a phylogeographic and phylogenetic marker at different taxonomic levels in different taxa of Metazoa. From a methodological standpoint, my main effort was dedicated to the sequencing of complete mitochondrial genomes, and the approach to whole-genome sequencing was based on the application of Long-PCR and shotgun sequences. Moreover, this research project is a part of a bigger sequencing project of mtDNAs in many different Metazoans’ taxa, and I mostly dedicated myself to sequence and analyze mtDNAs in selected taxa of bivalves and hexapods (Insecta). Sequences of bivalve mtDNAs are particularly limited, and my study contributed to extend the sampling. Moreover, I used the bivalve Musculista senhousia as model taxon to investigate the molecular mechanisms and the evolutionary significance of their aberrant mode of mitochondrial inheritance (Doubly Uniparental Inheritance, see below). In Insects, I focused my attention on the Genus Bacillus (Insecta Phasmida). A detailed phylogenetic analysis was performed in order to assess phylogenetic relationships within the genus, and to investigate the placement of Phasmida in the phylogenetic tree of Insecta. The main goal of this part of my study was to add to the taxonomic coverage of sequenced mtDNAs in basal insects, which were only partially analyzed.

Transcriptional functions of DNA Topoisomerases at a genome-wide scale and a single gene levels

The DNA topology is an important modifier of DNA functions. Torsional stress is generated when right handed DNA is either over- or underwound, producing structural deformations which drive or are driven by processes such as replication, transcription, recombination and repair. DNA topoisomerases are molecular machines that regulate the topological state of the DNA in the cell. These enzymes accomplish this task by either passing one strand of the DNA through a break in the opposing strand or by passing a region of the duplex from the same or a different molecule through a double-stranded cut generated in the DNA. Because of their ability to cut one or two strands of DNA they are also target for some of the most successful anticancer drugs used in standard combination therapies of human cancers. An effective anticancer drug is Camptothecin (CPT) that specifically targets DNA topoisomerase 1 (TOP 1). The research project of the present thesis has been focused on the role of human TOP 1 during transcription and on the transcriptional consequences associated with TOP 1 inhibition by CPT in human cell lines. Previous findings demonstrate that TOP 1 inhibition by CPT perturbs RNA polymerase (RNAP II) density at promoters and along transcribed genes suggesting an involvement of TOP 1 in RNAP II promoter proximal pausing site. Within the transcription cycle, promoter pausing is a fundamental step the importance of which has been well established as a means of coupling elongation to RNA maturation. By measuring nascent RNA transcripts bound to chromatin, we demonstrated that TOP 1 inhibition by CPT can enhance RNAP II escape from promoter proximal pausing site of the human Hypoxia Inducible Factor 1 (HIF-1) and c-MYC genes in a dose dependent manner. This effect is dependent from Cdk7/Cdk9 activities since it can be reversed by the kinases inhibitor DRB. Since CPT affects RNAP II by promoting the hyperphosphorylation of its Rpb1 subunit the findings suggest that TOP 1inhibition by CPT may increase the activity of Cdks which in turn phosphorylate the Rpb1 subunit of RNAP II enhancing its escape from pausing. Interestingly, the transcriptional consequences of CPT induced topological stress are wider than expected. CPT increased co-transcriptional splicing of exon1 and 2 and markedly affected alternative splicing at exon 11. Surprisingly despite its well-established transcription inhibitory activity, CPT can trigger the production of a novel long RNA (5’aHIF-1) antisense to the human HIF-1 mRNA and a known antisense RNA at the 3’ end of the gene, while decreasing mRNA levels. The effects require TOP 1 and are independent from CPT induced DNA damage. Thus, when the supercoiling imbalance promoted by CPT occurs at promoter, it may trigger deregulation of the RNAP II pausing, increased chromatin accessibility and activation/derepression of antisense transcripts in a Cdks dependent manner. A changed balance of antisense transcripts and mRNAs may regulate the activity of HIF-1 and contribute to the control of tumor progression After focusing our TOP 1 investigations at a single gene level, we have extended the study to the whole genome by developing the “Topo-Seq” approach which generates a map of genome-wide distribution of sites of TOP 1 activity sites in human cells. The preliminary data revealed that TOP 1 preferentially localizes at intragenic regions and in particular at 5’ and 3’ ends of genes. Surprisingly upon TOP 1 downregulation, which impairs protein expression by 80%, TOP 1 molecules are mostly localized around 3’ ends of genes, thus suggesting that its activity is essential at these regions and can be compensate at 5’ ends. The developed procedure is a pioneer tool for the detection of TOP 1 cleavage sites across the genome and can open the way to further investigations of the enzyme roles in different nuclear processes.

Study of Italian isolates of Alternaria spp.: molecular and morphological characterization and pathogenesis on apple tree

It was decided to carry out a morphological and molecular characterization of the Italian Alternaria isolatescollected from apple , and evaluate their pathogenicity and subsequently combining the data collected. The strain collection (174 isolates) was constructed by collecting material (received from extension service personnel) between June and August of 2007, 2008, and 2009. A Preliminary bioassays were performed on detached plant materials (fruit and leaf wounded and unwounded), belonging to the Golden cultivar, with two different kind of inoculation (conidial suspension and conidial filtrate). Symptoms were monitored daily and a value of pathogenicity score (P.S.) was assigned on the basis of the diameter of the necrotic area that developed. On the basis of the bioassays, the number of isolates to undergo further molecular analysis was restricted to a representative set of single spore strains (44 strains). Morphological characteristics of the colony and sporulation pattern were determined according to previous systematic work on small-spored Alternaria spp. (Pryor and Michaelides, 2002 and Hong et al., 2006). Reference strains (Alternaria alternata, Alternaria tenuissima, Alternaria arborescens and four Japanese strains of Alternaria alternata mali pathotype), used in the study were kindly provided by Prof. Barry Pryor, who allows a open access to his own fungal collection. Molecular characterization was performed combining and comparing different data sets obtained from distinct molecular approach: 1) investigation of specific loci and 2) fingerprinting based on diverse randomly selected polymorphic sites of the genome. As concern the single locus analysis, it was chosen to sequence the EndoPG partial gene and three anonymous region (OPA1-3, OPA2- and OPa10-2). These markers has revealed a powerful tool in the latter systematic works on small-spored Alternaria spp. In fact, as reported in literature small-spored Alternaria taxonomy is complicated due to the inability to resolve evolutionary relationships among the taxa because of the lack of variability in the markers commonly used in fungi systematic. The three data set together provided the necessary variation to establish the phylogenetic relationships among the Italian isolates of Alternaria spp. On Italian strains these markers showed a variable number of informative sites (ranging from 7 for EndoPg to 85 for OPA1-3) and the parsimony analysis produced different tree topologies all concordant to define A. arborescens as a mophyletic clade. Fingerprinting analysis (nine ISSR primers and eight AFLP primers combination) led to the same result: a monophyleic A. arborescens clade and one clade containing both A. tenuissima and the A. alternata strains. This first attempt to characterize Italian Alternaria species recovered from apple produced concordant results with what was already described in a similar phylogenetic study on pistachio (Pryor and Michaelides, 2002), on walnut and hazelnut (Hong et al., 2006), apple (Kang et al., 2002) and citurus (Peever et al., 2004). Together with these studies, this research demonstrates that the three morphological groups are widely distributed and occupy similar ecological niches. Furthermore, this research suggest that these Alternaria species exhibit a similar infection pattern despite the taxonomic and pathogenic differences. The molecular characterization of the pathogens is a fundamental step to understanding the disease that is spreading in the apple orchards of the north Italy. At the beginning the causal agent was considered as Alteraria alternata (Marshall and Bertagnoll, 2006). Their preliminary studies purposed a pathogenic system related to the synthesis of toxins. Experimental data of our bioassays suggest an analogous hypothesis, considering that symptoms could be induced after inoculating plant material with solely the filtrate from pathogenic strains. Moreover, positive PCR reactions using AM-toxin gene specific primers, designed for identification of apple infecting Alternaria pathovar, led to a hypothesis that a host specific toxin (toxins) were involved. It remains an intriguing challenge to discover or not if the agent of the “Italian disease” is the same of the one previously typified as Alternaria mali, casual agent of the apple blotch disease.

Genome characterization through a mathematical model of the genetic code: an analysis of the whole chromosome 1 of A. thaliana

The objective of this work is to characterize the genome of the chromosome 1 of A.thaliana, a small flowering plants used as a model organism in studies of biology and genetics, on the basis of a recent mathematical model of the genetic code. I analyze and compare different portions of the genome: genes, exons, coding sequences (CDS), introns, long introns, intergenes, untranslated regions (UTR) and regulatory sequences. In order to accomplish the task, I transformed nucleotide sequences into binary sequences based on the definition of the three different dichotomic classes. The descriptive analysis of binary strings indicate the presence of regularities in each portion of the genome considered. In particular, there are remarkable differences between coding sequences (CDS and exons) and non-coding sequences, suggesting that the frame is important only for coding sequences and that dichotomic classes can be useful to recognize them. Then, I assessed the existence of short-range dependence between binary sequences computed on the basis of the different dichotomic classes. I used three different measures of dependence: the well-known chi-squared test and two indices derived from the concept of entropy i.e. Mutual Information (MI) and Sρ, a normalized version of the “Bhattacharya Hellinger Matusita distance”. The results show that there is a significant short-range dependence structure only for the coding sequences whose existence is a clue of an underlying error detection and correction mechanism. No doubt, further studies are needed in order to assess how the information carried by dichotomic classes could discriminate between coding and noncoding sequence and, therefore, contribute to unveil the role of the mathematical structure in error detection and correction mechanisms. Still, I have shown the potential of the approach presented for understanding the management of genetic information.

Analysis of the pig genome for the identification of genomic regions affecting production traits

The aim of this work was to identify markers associated with production traits in the pig genome using different approaches. We focused the attention on Italian Large White pig breed using Genome Wide Association Studies (GWAS) and applying a selective genotyping approach to increase the power of the analyses. Furthermore, we searched the pig genome using Next Generation Sequencing (NSG) Ion Torrent Technology to combine selective genotyping approach and deep sequencing for SNP discovery. Other two studies were carried on with a different approach. Allele frequency changes for SNPs affecting candidate genes and at Genome Wide level were analysed to identify selection signatures driven by selection program during the last 20 years. This approach confirmed that a great number of markers may affect production traits and that they are captured by the classical selection programs. GWAS revealed 123 significant or suggestively significant SNP associated with Back Fat Thickenss and 229 associated with Average Daily Gain. 16 Copy Number Variant Regions resulted more frequent in lean or fat pigs and showed that different copies of those region could have a limited impact on fat. These often appear to be involved in food intake and behavior, beside affecting genes involved in metabolic pathways and their expression. By combining NGS sequencing with selective genotyping approach, new variants where discovered and at least 54 are worth to be analysed in association studies. The study of groups of pigs undergone to stringent selection showed that allele frequency of some loci can drastically change if they are close to traits that are interesting for selection schemes. These approaches could be, in future, integrated in genomic selection plans.