App-based intervention for parents of children with crying, sleeping, and feeding problems: Usability, usefulness and implications for improvement.

Background: There is a lack of evidence-based app guidance for parents of children with crying, sleeping, and feeding problems who are often highly burdened and not likely to seek professional help. A new psychoeducational app for parents providing scientifically sound information via text and videos, a diary function, selfcare strategies, a chat forum and a regional directory of specialized counseling centers may serve as a low-threshold intervention for this target group. Objective: We investigated how parents perceived the app in terms of the following: (1) overall impression and usability, (2) feedback on specific app functions regarding usefulness and (3) possible future improvements. Methods: Our clinical sample of N = 137 parents of children aged from 0 to 24 months was recruited from a cry baby outpatient clinic in Southern Germany between 2019 and 2022. A convergent parallel mixed methods design was used to collect and analyse cross-sectional data on app evaluation. After app use within the framework of a clinical trial, parents filled in an app evaluation questionnaire. Results: Most participants used the app at least once a week (86, 62.8 %) over an average period of 19.06 days (SD = 15.00). Participants rated overall impression and usability as good, and the informational texts, expert videos and regional register of counseling centers as appealing and useful. The diary function and chat forum were found to be helpful in theory, but improvements in implementation were requested, such as a timer function for the diary entry. Regarding future functionality, parents posed several suggestions such as the option to contact counseling centers directly via app, and the inclusion of the profile of their partners. Conclusions: Positive ratings of overall impression, usability, and specific app functions are important prerequisites for the app to be effective. App-based guidance for this target group should include easy-to-use information. The app is intended to serve as a secondary preventive low-threshold offer and to complement professional counseling.

TET2 lesions enhance the aggressiveness of CEBPA-mutant acute myeloid leukemia by rebalancing GATA2 expression.

The myeloid transcription factor CEBPA is recurrently biallelically mutated (i.e., double mutated; CEBPADM) in acute myeloid leukemia (AML) with a combination of hypermorphic N-terminal mutations (CEBPANT), promoting expression of the leukemia-associated p30 isoform, and amorphic C-terminal mutations. The most frequently co-mutated genes in CEBPADM AML are GATA2 and TET2, however the molecular mechanisms underlying this co-mutational spectrum are incomplete. By combining transcriptomic and epigenomic analyses of CEBPA-TET2 co-mutated patients with models thereof, we identify GATA2 as a conserved target of the CEBPA-TET2 mutational axis, providing a rationale for the mutational spectra in CEBPADM AML. Elevated CEBPA levels, driven by CEBPANT, mediate recruitment of TET2 to the Gata2 distal hematopoietic enhancer thereby increasing Gata2 expression. Concurrent loss of TET2 in CEBPADM AML induces a competitive advantage by increasing Gata2 promoter methylation, thereby rebalancing GATA2 levels. Of clinical relevance, demethylating treatment of Cebpa-Tet2 co-mutated AML restores Gata2 levels and prolongs disease latency.

PTBP1 promotes hematopoietic stem cell maintenance and red blood cell development by ensuring sufficient availability of ribosomal constituents.

Ribosomopathies constitute a range of disorders associated with defective protein synthesis mainly affecting hematopoietic stem cells (HSCs) and erythroid development. Here, we demonstrate that deletion of poly-pyrimidine-tract-binding protein 1 (PTBP1) in the hematopoietic compartment leads to the development of a ribosomopathy-like condition. Specifically, loss of PTBP1 is associated with decreases in HSC self-renewal, erythroid differentiation, and protein synthesis. Consistent with its function as a splicing regulator, PTBP1 deficiency results in splicing defects in hundreds of genes, and we demonstrate that the up-regulation of a specific isoform of CDC42 partly mimics the protein-synthesis defect associated with loss of PTBP1. Furthermore, PTBP1 deficiency is associated with a marked defect in ribosome biogenesis and a selective reduction in the translation of mRNAs encoding ribosomal proteins. Collectively, this work identifies PTBP1 as a key integrator of ribosomal functions and highlights the broad functional repertoire of RNA-binding proteins.

The ASXL1-G643W variant accelerates the development of CEBPA mutant acute myeloid leukemia.

ASXL1 is one of the most commonly mutated genes in myeloid malignancies, including Myelodysplastic Syndrome (MDS) and Acute Myeloid Leukemia (AML). In order to further our understanding of the role of ASXL1 lesions in malignant hematopoiesis, we generated a novel knock-in mouse model carrying the most frequent ASXL1 mutation identified in MDS patients, p.G643WfsX12. Mutant mice did not display any major hematopoietic defects nor developed any apparent hematological disease. In AML patients, ASXL1 mutations co-occur with mutations in CEBPA and we therefore generated compound Cebpa and Asxl1 mutated mice. Using a transplantation model, we found that the mutated Asxl1 allele significantly accelerated disease development in a CEBPA mutant context. Importantly, we demonstrated that, similar to the human setting, Asxl1 mutated mice responded poorly to chemotherapy. This model therefore constitutes an excellent experimental system for further studies into the clinically important question of chemotherapy resistance mediated by mutant ASXL1.

Heterozygous loss of Srp72 in mice is not associated with major hematological phenotypes.

OBJECTIVES: Familial cases of hematological malignancies are associated with germline mutations. In particular, heterozygous mutations of SRP72 correlate with the development of myelodysplasia and bone marrow aplasia in two families. The signal recognition particle 72 kDa protein (SRP72) is part of the SRP complex, responsible for targeting of proteins to the endoplasmic reticulum. The main objective of this study is to investigate the role of SRP72 in the hematopoietic system, thus explaining why a reduced dose could increase susceptibility to hematological malignancies. METHODS: We developed an Srp72 null mouse model and characterized its hematopoietic system using flow cytometry, bone marrow transplantations, and gene expression analysis. RESULTS: Heterozygous loss of Srp72 in mice is not associated with major changes in hematopoiesis, although causes mild reductions in blood and BM cellularity and minor changes within the stem/progenitor compartment. We did not observe any hematological disorder. Interestingly, gene expression analysis demonstrated that genes encoding secreted factors, including cytokines and receptors, were transcriptionally down-regulated in Srp72+/- animals. CONCLUSIONS: The Srp72+/- mouse model only partially recapitulates the phenotype observed in families with inherited SRP72 lesions. Nonetheless, these results can provide mechanistic insights into why SRP72 mutations are associated with aplasia and myelodysplasia in humans.

A splice-site variant in the lncRNA gene RP1-140A9.1 cosegregates in the large Volkmann cataract family.

Purpose: To identify the mutation for Volkmann cataract (CTRCT8) at 1p36.33. Methods: The genes in the candidate region 1p36.33 were Sanger and parallel deep sequenced, and informative single nucleotide polymorphisms (SNPs) were identified for linkage analysis. Expression analysis with reverse transcription polymerase chain reaction (RT-PCR) of the candidate gene was performed using RNA from different human tissues. Quantitative transcription polymerase chain reaction (qRT-PCR) analysis of the GNB1 gene was performed in affected and healthy individuals. Bioinformatic analysis of the linkage regions including the candidate gene was performed. Results: Linkage analysis of the 1p36.33 CCV locus applying new marker systems obtained with Sanger and deep sequencing reduced the candidate locus from 2.1 Mb to 0.389 Mb flanked by the markers STS-22AC and rs549772338 and resulted in an logarithm of the odds (LOD) score of Z = 21.67. The identified mutation, rs763295804, affects the donor splice site in the long non-coding RNA gene RP1-140A9.1 (ENSG00000231050). The gene including splice-site junctions is conserved in primates but not in other mammalian genomes, and two alternative transcripts were shown with RT-PCR. One of these transcripts represented a lens cell-specific transcript. Meta-analysis of the Cross-Linking-Immuno-Precipitation sequencing (CLIP-Seq) data suggested the RNA binding protein (RBP) eIF4AIII is an active counterpart for RP1-140A9.1, and several miRNA and transcription factors binding sites were predicted in the proximity of the mutation. ENCODE DNase I hypersensitivity and histone methylation and acetylation data suggest the genomic region may have regulatory functions. Conclusions: The mutation in RP1-140A9.1 suggests the long non-coding RNA as the candidate cataract gene associated with the autosomal dominant inherited congenital cataract from CCV. The mutation has the potential to destroy exon/intron splicing of both transcripts of RP1-140A9.1. Sanger and massive deep resequencing of the linkage region failed to identify alternative candidates suggesting the mutation in RP1-140A9.1 is causative for the CCV phenotype.

CRISPR-Cas9 off-targeting assessment with nucleic acid duplex energy parameters.

BACKGROUND: Recent experimental efforts of CRISPR-Cas9 systems have shown that off-target binding and cleavage are a concern for the system and that this is highly dependent on the selected guide RNA (gRNA) design. Computational predictions of off-targets have been proposed as an attractive and more feasible alternative to tedious experimental efforts. However, accurate scoring of the high number of putative off-targets plays a key role for the success of computational off-targeting assessment. RESULTS: We present an approximate binding energy model for the Cas9-gRNA-DNA complex, which systematically combines the energy parameters obtained for RNA-RNA, DNA-DNA, and RNA-DNA duplexes. Based on this model, two novel off-target assessment methods for gRNA selection in CRISPR-Cas9 applications are introduced: CRISPRoff to assign confidence scores to predicted off-targets and CRISPRspec to measure the specificity of the gRNA. We benchmark the methods against current state-of-the-art methods and show that both are in better agreement with experimental results. Furthermore, we show significant evidence supporting the inverse relationship between the on-target cleavage efficiency and specificity of the system, in which introduced binding energies are key components. CONCLUSIONS: The impact of the binding energies provides a direction for further studies of off-targeting mechanisms. The performance of CRISPRoff and CRISPRspec enables more accurate off-target evaluation for gRNA selections, prior to any CRISPR-Cas9 genome-editing application. For given gRNA sequences or all potential gRNAs in a given target region, CRISPRoff-based off-target predictions and CRISPRspec-based specificity evaluations can be carried out through our webserver at https://rth.dk/resources/crispr/ .

Genome-wide identification of clusters of predicted microRNA binding sites as microRNA sponge candidates.

The number of discovered natural miRNA sponges in plants, viruses, and mammals is increasing steadily. Some sponges like ciRS-7 for miR-7 contain multiple nearby miRNA binding sites. We hypothesize that such clusters of miRNA binding sites on the genome can function together as a sponge. No systematic effort has been made in search for clusters of miRNA targets. Here, we, to our knowledge, make the first genome-wide target site predictions for clusters of mature human miRNAs. For each miRNA, we predict the target sites on a genome-wide scale, build a graph with edge weights based on the pairwise distances between sites, and apply Markov clustering to identify genomic regions with high binding site density. Significant clusters are then extracted based on cluster size difference between real and shuffled genomes preserving local properties such as the GC content. We then use conservation and binding energy to filter a final set of miRNA target site clusters or sponge candidates. Our pipeline predicts 3673 sponge candidates for 1250 miRNAs, including the experimentally verified miR-7 sponge ciRS-7. In addition, we point explicitly to 19 high-confidence candidates overlapping annotated genomic sequence. The full list of candidates is freely available at http://rth.dk/resources/mirnasponge, where detailed properties for individual candidates can be explored, such as alignment details, conservation, accessibility and target profiles, which facilitates selection of sponge candidates for further context specific analysis.

RIsearch2: suffix array-based large-scale prediction of RNA-RNA interactions and siRNA off-targets.

Intermolecular interactions of ncRNAs are at the core of gene regulation events, and identifying the full map of these interactions bears crucial importance for ncRNA functional studies. It is known that RNA-RNA interactions are built up by complementary base pairings between interacting RNAs and high level of complementarity between two RNA sequences is a powerful predictor of such interactions. Here, we present RIsearch2, a large-scale RNA-RNA interaction prediction tool that enables quick localization of potential near-complementary RNA-RNA interactions between given query and target sequences. In contrast to previous heuristics which either search for exact matches while including G-U wobble pairs or employ simplified energy models, we present a novel approach using a single integrated seed-and-extend framework based on suffix arrays. RIsearch2 enables fast discovery of candidate RNA-RNA interactions on genome/transcriptome-wide scale. We furthermore present an siRNA off-target discovery pipeline that not only predicts the off-target transcripts but also computes the off-targeting potential of a given siRNA. This is achieved by combining genome-wide RIsearch2 predictions with target site accessibilities and transcript abundance estimates. We show that this pipeline accurately predicts siRNA off-target interactions and enables off-targeting potential comparisons between different siRNA designs. RIsearch2 and the siRNA off-target discovery pipeline are available as stand-alone software packages from http://rth.dk/resources/risearch.

Transcriptome-wide analysis of UTRs in non-small cell lung cancer reveals cancer-related genes with SNV-induced changes on RNA secondary structure and miRNA target sites.

Traditional mutation assessment methods generally focus on predicting disruptive changes in protein-coding regions rather than non-coding regulatory regions like untranslated regions (UTRs) of mRNAs. The UTRs, however, are known to have many sequence and structural motifs that can regulate translational and transcriptional efficiency and stability of mRNAs through interaction with RNA-binding proteins and other non-coding RNAs like microRNAs (miRNAs). In a recent study, transcriptomes of tumor cells harboring mutant and wild-type KRAS (V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog) genes in patients with non-small cell lung cancer (NSCLC) have been sequenced to identify single nucleotide variations (SNVs). About 40% of the total SNVs (73,717) identified were mapped to UTRs, but omitted in the previous analysis. To meet this obvious demand for analysis of the UTRs, we designed a comprehensive pipeline to predict the effect of SNVs on two major regulatory elements, secondary structure and miRNA target sites. Out of 29,290 SNVs in 6462 genes, we predict 472 SNVs (in 408 genes) affecting local RNA secondary structure, 490 SNVs (in 447 genes) affecting miRNA target sites and 48 that do both. Together these disruptive SNVs were present in 803 different genes, out of which 188 (23.4%) were previously known to be cancer-associated. Notably, this ratio is significantly higher (one-sided Fisher's exact test p-value = 0.032) than the ratio (20.8%) of known cancer-associated genes (n = 1347) in our initial data set (n = 6462). Network analysis shows that the genes harboring disruptive SNVs were involved in molecular mechanisms of cancer, and the signaling pathways of LPS-stimulated MAPK, IL-6, iNOS, EIF2 and mTOR. In conclusion, we have found hundreds of SNVs which are highly disruptive with respect to changes in the secondary structure and miRNA target sites within UTRs. These changes hold the potential to alter the expression of known cancer genes or genes linked to cancer-associated pathways.

RIsearch: fast RNA-RNA interaction search using a simplified nearest-neighbor energy model.

MOTIVATION: Regulatory, non-coding RNAs often function by forming a duplex with other RNAs. It is therefore of interest to predict putative RNA-RNA duplexes in silico on a genome-wide scale. Current computational methods for predicting these interactions range from fast complementary-based searches to those that take intramolecular binding into account. Together these methods constitute a trade-off between speed and accuracy, while leaving room for improvement within the context of genome-wide screens. A fast pre-filtering of putative duplexes would therefore be desirable. RESULTS: We present RIsearch, an implementation of a simplified Turner energy model for fast computation of hybridization, which significantly reduces runtime while maintaining accuracy. Its time complexity for sequences of lengths m and n is with a much smaller pre-factor than other tools. We show that this energy model is an accurate approximation of the full energy model for near-complementary RNA-RNA duplexes. RIsearch uses a Smith-Waterman-like algorithm using a dinucleotide scoring matrix which approximates the Turner nearest-neighbor energies. We show in benchmarks that we achieve a speed improvement of at least 2.4× compared with RNAplex, the currently fastest method for searching near-complementary regions. RIsearch shows a prediction accuracy similar to RNAplex on two datasets of known bacterial short RNA (sRNA)-messenger RNA (mRNA) and eukaryotic microRNA (miRNA)-mRNA interactions. Using RIsearch as a pre-filter in genome-wide screens reduces the number of binding site candidates reported by miRNA target prediction programs, such as TargetScanS and miRanda, by up to 70%. Likewise, substantial filtering was performed on bacterial RNA-RNA interaction data. AVAILABILITY: The source code for RIsearch is available at: http://rth.dk/resources/risearch.

webPIPSA: a web server for the comparison of protein interaction properties.

Protein molecular interaction fields are key determinants of protein functionality. PIPSA (Protein Interaction Property Similarity Analysis) is a procedure to compare and analyze protein molecular interaction fields, such as the electrostatic potential. PIPSA may assist in protein functional assignment, classification of proteins, the comparison of binding properties and the estimation of enzyme kinetic parameters. webPIPSA is a web server that enables the use of PIPSA to compare and analyze protein electrostatic potentials. While PIPSA can be run with downloadable software (see http://projects.eml.org/mcm/software/pipsa), webPIPSA extends and simplifies a PIPSA run. This allows non-expert users to perform PIPSA for their protein datasets. With input protein coordinates, the superposition of protein structures, as well as the computation and analysis of electrostatic potentials, is automated. The results are provided as electrostatic similarity matrices from an all-pairwise comparison of the proteins which can be subjected to clustering and visualized as epograms (tree-like diagrams showing electrostatic potential differences) or heat maps. webPIPSA is freely available at: http://pipsa.eml.org.