Within the last years, more and more noncoding RNAs (ncRNAs) became the focal point to understand cell regulatory mechanisms because one class of ncRNAs, microRNAs (miRNAs), plays an essential role in translation repression or degradation of specific mRNAs and is implicated in disease etiology. miRNAs can serve as oncomiRs (oncogenic miRNAs) and tumor suppressor miRNAs, thus, miRNA therapeutics in clinical trials have become a vital component with respect to cancer treatment. To circumvent side-effects and allow an accurate effect it is crucial to accurately predict miRNAs and their mRNA targets. Over the last two decades, different approaches for miRNA prediction as well as miRNA target prediction have been developed and improved based on sequence and structure features. Nowadays, the abundance of high-throughput sequencing data and databases of miRNAs and miRNA targets from different species allow the training, testing, and validation of predicted miRNAs and miRNA targets with machine learning methods. This book chapter focuses on the important requirements for miRNA target prediction tools using ML like common features used for miRNA-binding site prediction. Furthermore, best practices for the prediction and validation of miRNA-mRNA targets are presented and set in the context of possible applications for cancer diagnosis and therapeutics.

[This corrects the article DOI: 10.3389/fgene.2022.931017.].

Tafazzin-an acyltransferase-is involved in cardiolipin (CL) remodeling. CL is associated with mitochondrial function, structure and more recently with cell proliferation. Various tafazzin isoforms exist in humans. The role of these isoforms in cardiolipin remodeling is unknown. Aim of this study was to investigate if specific isoforms like Δ5 can restore the wild type phenotype with respect to CL composition, cellular proliferation and gene expression profile. In addition, we aimed to determine the molecular mechanism by which tafazzin can modulate gene expression by applying promoter analysis and (Ingenuity Pathway Analyis) IPA to genes regulated by TAZ-deficiency. Expression of Δ5 and rat full length TAZ in C6-TAZ- cells could fully restore CL composition and-as proven for Δ5-this is naturally associated with restoration of mitochondrial respiration. A similar restoration of CL-composition could not be observed after re-expression of an enzymatically dead full-length rat TAZ (H69L; TAZMut). Re-expression of only rat full length TAZ could restore proliferation rate. Surprisingly, the Δ5 variant failed to restore wild-type proliferation. Further, as expected, re-expression of the TAZMut variant completely failed to reverse the gene expression changes, whereas re-expression of the TAZ-FL variant largely did so and the Δ5 variant to somewhat less extent. Very likely TAZ-deficiency provokes substantial long-lasting changes in cellular lipid metabolism which contribute to changes in proliferation and gene expression, and are not or only very slowly reversible.

Alternative splicing (AS) is a major mechanism for gene expression in eukaryotes, increasing proteome diversity but also regulating transcriptome abundance. High temperatures have a strong impact on the splicing profile of many genes and therefore AS is considered as an integral part of heat stress response. While many studies have established a detailed description of the diversity of the RNAome under heat stress in different plant species and stress regimes, little is known on the underlying mechanisms that control this temperature-sensitive process. AS is mainly regulated by the activity of splicing regulators. Changes in the abundance of these proteins through transcription and AS, post-translational modifications and interactions with exonic and intronic cis-elements and core elements of the spliceosomes modulate the outcome of pre-mRNA splicing. As a major part of pre-mRNAs are spliced co-transcriptionally, the chromatin environment along with the RNA polymerase II elongation play a major role in the regulation of pre-mRNA splicing under heat stress conditions. Despite its importance, our understanding on the regulation of heat stress sensitive AS in plants is scarce. In this review, we summarize the current status of knowledge on the regulation of AS in plants under heat stress conditions. We discuss possible implications of different pathways based on results from non-plant systems to provide a perspective for researchers who aim to elucidate the molecular basis of AS under high temperatures.

Probability distribution modeling is the basis for most competitive methods for lossless coding of screen content. One such state-of-the-art method is known as soft context formation (SCF). For each pixel to be encoded, a probability distribution is estimated based on the neighboring pattern and the occurrence of that pattern in the already encoded image. Using an arithmetic coder, the pixel color can thus be encoded very efficiently, provided that the current color has been observed before in association with a similar pattern. If this is not the case, the color is instead encoded using a color palette or, if it is still unknown, via residual coding. Both palette-based coding and residual coding have significantly worse compression efficiency than coding based on soft context formation. In this paper, the residual coding stage is improved by adaptively trimming the probability distributions for the residual error. Furthermore, an enhanced probability modeling for indicating a new color depending on the occurrence of new colors in the neighborhood is proposed. These modifications result in a bitrate reduction of up to 2.9% on average. Compared to HEVC (HM-16.21 + SCM-8.8) and FLIF, the improved SCF method saves on average about 11% and 18% rate, respectively.