The BRaliBase Dent – a Tale of Benchmark Design and Interpretation

Löwes B, Chauve C, Ponty Y, Giegerich R. The BRaliBase Dent – a Tale of Benchmark Design and Interpretation. Briefings in Bioinformatics. 2017;18(2):306-311.BRaliBase is a widely used benchmark for assessing the accuracy of RNA secondary structure alignment methods. In most case studies based on the BRaliBase benchmark, one can observe a puzzling drop in accuracy in the 40%-60% sequence identity range, the so-called “BRaliBase Dent”. In the present note, we show this dent is due to a bias in the composition of the BRaliBase benchmark, namely the inclusion of a disproportionate number of tRNAs, which exhibit a very conserved secondary structure. Our analysis, aside of its interest regarding the specific case of the BRaliBase benchmark, also raises important questions regarding the design and use of benchmarks in computational biology

Detecting and comparing non-coding RNAs in the high-throughput era.

In recent years there has been a growing interest in the field of non-coding RNA. This surge is a direct consequence of the discovery of a huge number of new non-coding genes and of the finding that many of these transcripts are involved in key cellular functions. In this context, accurately detecting and comparing RNA sequences has become important. Aligning nucleotide sequences is a key requisite when searching for homologous genes. Accurate alignments reveal evolutionary relationships, conserved regions and more generally any biologically relevant pattern. Comparing RNA molecules is, however, a challenging task. The nucleotide alphabet is simpler and therefore less informative than that of amino-acids. Moreover for many non-coding RNAs, evolution is likely to be mostly constrained at the structural level and not at the sequence level. This results in very poor sequence conservation impeding comparison of these molecules. These difficulties define a context where new methods are urgently needed in order to exploit experimental results to their full potential. This review focuses on the comparative genomics of non-coding RNAs in the context of new sequencing technologies and especially dealing with two extremely important and timely research aspects: the development of new methods to align RNAs and the analysis of high-throughput data

New Methods to Improve Protein Structure Modeling

Proteins are considered the central compound necessary for life, as they play a crucial role in governing several life processes by performing the most essential biological and chemical functions in every living cell. Understanding protein structures and functions will lead to a significant advance in life science and biology. Such knowledge is vital for various fields such as drug development and synthetic biofuels production. Most proteins have definite shapes that they fold into, which are the most stable state they can adopt. Due to the fact that the protein structure information provides important insight into its functions, many research efforts have been conducted to determine the protein 3-dimensional structure from its sequence. The experimental methods for protein 3-dimensional structure determination are often time-consuming, costly, and even not feasible for some proteins. Accordingly, recent research efforts focus more and more on computational approaches to predict protein 3-dimensional structures. Template-based modeling is considered one of the most accurate protein structure prediction methods. The success of template-based modeling relies on correctly identifying one or a few experimentally determined protein structures as structural templates that are likely to resemble the structure of the target sequence as well as accurately producing a sequence alignment that maps the residues in the target sequence to those in the template. In this work, we aim at improving the template-based protein structure modeling by enhancing the correctness of identifying the most appropriate templates and precisely aligning the target and template sequences. Firstly, we investigate employing inter-residue contact score to measure the favorability of a target sequence fitting in the folding topology of a certain template. Secondly, we design a multi-objective alignment algorithm extending the famous Needleman-Wunsch algorithm to obtain a complete set of alignments yielding Pareto optimality. Then, we use protein sequence and structural information as objectives and generate the complete Pareto optimal front of alignments between target sequence and template. The alignments obtained enable one to analyze the trade-offs between the potentially conflicting objectives. These approaches lead to accuracy enhancement in template-based protein structure modeling

The role of histone acetyltransferases in plant immunity

Activation of plant defence responses requires significant transcriptional reprogramming to mount an effective response to pathogens. This response must be finely balanced with growth and development processes to ensure optimal allocation of cellular resources. A fundamental mechanism of gene expression regulation is covalent modification of histones. Histone acetyltransferases (HATs) and histone deacetylases (HDACs) antagonistically control the acetylation levels of histones at specific genomic loci to ultimately affect gene expression. This thesis focuses on histone acetylation as a mechanism by which plants mount an effective immune response. In Chapter 3, a reverse genetic screen of Arabidopsis HAT mutants is presented where a negative regulator (HAM2) of defence against the plant pathogen Pto DC3000 was identified. Whilst mutants of the negative regulator (ham2 ) demonstrate enhanced resistance to P. syringae, their susceptibility to the necrotrophic pathogen B. cinerea is unchanged. Alongside the immunity phenotype, ham2 plants exhibit increased adult leaf surface area, fresh weight and root length. Since ham2 is the only known Arabidopsis mutant with increased immunity and growth, it represents a promising target in an agricultural context. In Chapter 4, homology models of A. thaliana, B. napus and S. lycopersicum HAM2 proteins were created, supported by a series of cheminformatics and in silico docking methods, to identify chemical inhibitors for future agricultural applications. Finally, the role of Arabidopsis HATs in effector-triggered immunity was investigated in Chapter 5. Here, HAG1 was identified as a key positive regulator of effector-triggered responses. Overall, this thesis contributes to our understanding of the role of HAM2 and HAG1 histone acetyltransferases in plant immunity, and presents HAM2 as a novel target in an agricultural context

Detection of secondary structure motifs in long non-coding RNAs

nicht vorhandenThe almost complete transcription of the human genome yield in a high number of transcripts, that do not encode proteins. However, the functional elucidation of especially long non cod-ing RNAs is still difficult. Secondary structure analysis is assumed to be a possible method to detect functional relationships of lncRNAs on a large scale, but it is still time consuming and error-prone. GRAPHCLUST, the currently most suitable clustering tool based on RNA secondary structure analysis, lacks mainly in an efficient method for the interpretation of its results. Hence, an independent and interactive RNA clustering interpretation tool was developed to allow visu-alisation and an efficient analysis of RNA clustering results