Kopsutransplantatsioon

Tänapäeval teostatakse maailmas üle 2000 kopsutransplantatsiooni aastas. Peamisteks näidustusteks on lõppstaadiumis krooniline obstruktiivne kopsuhaigus, α1-antitrüpsiini puudulikkus, idiopaatiline kopsufibroos ja tsüstiline fibroos. Esmaseks kopsutransplantatsiooni eesmärgiks on haigete eluea pikendamine, teisel olulisel kohal on elukvaliteedi parandamine. Tulenevalt haigusest, patsiendi vanusest jm teguritest kasutatakse nii ühe kui ka kahe kopsu transplantatsiooni. Doonorelundid kopsutransplantatsiooniks saadakse peamiselt ajusurmas doonoritelt. Tüsistusteta kulu korral on transplantatsioonijärgse haiglaravi kestuseks 3–4 nädalat. Järgneb elukestev ambulatoorne jälgimine eesmärgiga korraldada immunosupressiivset ravi ja diagnoosida ning ravida võimalikke tüsistusi. Keskmine 5 aasta elulemus pärast kopsutransplantatsiooni on tänapäeval üle 50%. Eesti Arst 2009; 88(11):730−74

A Major Locus Controls a Genital Shape Difference Involved in Reproductive Isolation Between Drosophila yakuba and Drosophila santomea

International audienceRapid evolution of genitalia shape, a widespread phenomenon in animals with internal fertilization, offers the opportunity to dissect the genetic architecture of morphological evolution linked to sexual selection and speciation. Most quantitative trait loci (QTL) mapping studies of genitalia divergence have focused on Drosophila melanogaster and its three most closely related species, D. simulans, D. mauritiana, and D. sechellia, and have suggested that the genetic basis of genitalia evolution involves many loci. We report the first genetic study of male genitalia evolution between D. yakuba and D. santomea, two species of the D. melanogaster species subgroup. We focus on male ventral branches, which harm females during interspecific copulation. Using landmark-based geometric morphometrics, we characterized shape variation in parental species, F1 hybrids, and backcross progeny and show that the main axis of shape variation within the backcross population matches the interspecific variation between parental species. For genotyping, we developed a new molecular method to perform multiplexed shotgun genotyping (MSG), which allowed us to prepare genomic DNA libraries from 365 backcross individuals in a few days using little DNA. We detected only three QTL, one of which spans 2.7 Mb and exhibits a highly significant effect on shape variation that can be linked to the harmfulness of the ventral branches. We conclude that the genetic architecture of genitalia morphology divergence may not always be as complex as suggested by previous studies

Nimmelülivaheketta väljasopistumisest põhjustatud cauda equina sündroom keskealisel mehel. Haigusjuhu kirjeldus

Keskealine mees haigestus äkitselt jalalabade süveneva nõrkuse, uriiniretentsiooni ning lahkliha ja perianaalpiirkonna tundlikkuse halvenemisega. Enne cauda equina kahjustumist tehtud kompuutertomograafilisel (KT) natiivuuringul ilmnes mahukas 4.–5. nimmelüli vahemiku diski sekvester keskjoonel, mis põhjustas seljaaju kõvakesta koti ventraalse osa deformatsiooni ning spinaalkanali ahenemise. Haige hospitaliseeriti mõne tunni möödudes pärast haigusilmingute kujunemist. Kliinilise ja radioloogilise leiu põhjal diagnoositi cauda equina sündroom (CES). Patsiendile tehti erakorraliselt 4.–5. nimmelüli vahemiku interlaminektoomia prolabeerunud diskisekvestri eemaldamiseks nimmekanalist. Järgnevatel päevadel põiehäired ning tundlikkus- ja motoorikahäired aegamööda taandusid

Transcription and splicing dynamics during early Drosophila development

© 2022 Prudêncio et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society. This article, published in RNA, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.Widespread cotranscriptional splicing has been demonstrated from yeast to human. However, most studies to date addressing the kinetics of splicing relative to transcription used either Saccharomyces cerevisiae or metazoan cultured cell lines. Here, we adapted native elongating transcript sequencing technology (NET-seq) to measure cotranscriptional splicing dynamics during the early developmental stages of Drosophila melanogaster embryos. Our results reveal the position of RNA polymerase II (Pol II) when both canonical and recursive splicing occur. We found heterogeneity in splicing dynamics, with some RNAs spliced immediately after intron transcription, whereas for other transcripts no splicing was observed over the first 100 nt of the downstream exon. Introns that show splicing completion before Pol II has reached the end of the downstream exon are necessarily intron-defined. We studied the splicing dynamics of both nascent pre-mRNAs transcribed in the early embryo, which have few and short introns, as well as pre-mRNAs transcribed later in embryonic development, which contain multiple long introns. As expected, we found a relationship between the proportion of spliced reads and intron size. However, intron definition was observed at all intron sizes. We further observed that genes transcribed in the early embryo tend to be isolated in the genome whereas genes transcribed later are often overlapped by a neighboring convergent gene. In isolated genes, transcription termination occurred soon after the polyadenylation site, while in overlapped genes, Pol II persisted associated with the DNA template after cleavage and polyadenylation of the nascent transcript. Taken together, our data unravel novel dynamic features of Pol II transcription and splicing in the developing Drosophila embryo.This work was supported by funding to M.C.-F. (Fundação para a Ciência e Tecnologia, FCT/Ministério da Ciência, Tecnologia e Ensino Superior - Fundos do Orçamento de Estado [UIDB/50005/2020], and FCT/ FEDER/POR Lisboa 2020, Programa Operacional Regional de Lisboa PORTUGAL 2020, grant LISBOA-01-0145-FEDER-016394) and to R.G.M (FCT grant PTDC/BIA-BID/28441/2017). P.P. was a recipient of an FCT fellowship (SFRH/BD/109689/2015). R.S. was a recipient of an EMBO Long-Term Fellowship (EMBO ALTF 101-2019). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements no. 842695 (Marie Skłodowska- Curie Actions) and no. 857119 (RiboMed)info:eu-repo/semantics/publishedVersio

Vena Galeni aneurüsm

Vastsündinueas poisil diagnoositi harva esinev aju venoosse süsteemi kaasasündinud anomaalia – vena Galeni aneurüsm, mille kliinilisteks nähtudeks oli meningeaalsündroom, koljusisese rõhu tõus ja hüdrotsefaalia. Aneurüsm tromboseerus spontaanselt, hüdrotsefaalia kompenseerus ja lapse areng on olnud eakohane. Artiklis on käsitletud ka v. Galeni aneurüsmi diagnoosimist ja ravi. Eesti Arst 2003; 82 (8): 571–57

Purifying selection on exonic splice enhancers in intronless genes

Exonic splice enhancers (ESEs) are short nucleotide motifs, enriched near exon ends, that enhance the recognition of the splice site and thus promote splicing. Are intronless genes under selection to avoid these motifs so as not to attract the splicing machinery to an mRNA that should not be spliced, thereby preventing the production of an aberrant transcript? Consistent with this possibility, we find that ESEs in putative recent retrocopies are at a higher density and evolving faster than those in other intronless genes, suggesting that they are being lost. Moreover, intronless genes are less dense in putative ESEs than intron-containing ones. However, this latter difference is likely due to the skewed base composition of intronless sequences, a skew that is in line with the general GC richness of few exon genes. Indeed, after controlling for such biases, we find that both intronless and intron-containing genes are denser in ESEs than expected by chance. Importantly, nucleotide-controlled analysis of evolutionary rates at synonymous sites in ESEs indicates that the ESEs in intronless genes are under purifying selection in both human and mouse. We conclude that on the loss of introns, some but not all, ESE motifs are lost, the remainder having functions beyond a role in splice promotion. These results have implications for the design of intronless transgenes and for understanding the causes of selection on synonymous sites

Both maintenance and avoidance of RNA-binding protein interactions constrain coding region evolution

While the principal force directing coding sequence (CDS) evolution is selection on protein function, to ensure correct gene expression CDSs must also maintain interactions with RNA-binding proteins (RBPs). Understanding how our genes are shaped by these RNA-level pressures is necessary for diagnostics and for improving transgenes. However, the evolutionary impact of the need to maintain RBP interactions remains unresolved. Are coding sequences constrained by the need to specify RBP binding motifs? If so, what proportion of mutations are affected? Might sequence evolution also be constrained by the need not to specify motifs that might attract unwanted binding, for instance because it would interfere with exon definition? Here, we have scanned human CDSs for motifs that have been experimentally determined to be recognized by RBPs. We observe two sets of motifs - those that are enriched over nucleotide-controlled null and those that are depleted. Importantly, the depleted set is enriched for motifs recognized by non-CDS binding RBPs. Supporting the functional relevance of our observations, we find that motifs that are more enriched are also slower-evolving. The net effect of this selection to preserve is a reduction in the over-all rate of synonymous evolution of 2-3% in both primates and rodents. Stronger motif depletion, on the other hand, is associated with stronger selection against motif gain in evolution. The challenge faced by our CDSs is therefore not only one of attracting the right RBPs but also of avoiding the wrong ones, all while also evolving under selection pressures related to protein structure

Investigating DNA-, RNA-, and protein-based features as a means to discriminate pathogenic synonymous variants

Synonymous single-nucleotide variants (SNVs), although they do not alter the encoded protein sequences, have been implicated in many genetic diseases. Experimental studies indicate that synonymous SNVs can lead to changes in the secondary and tertiary structures of DNA and RNA, thereby affecting translational efficiency, cotranslational protein folding as well as the binding of DNA-/RNA-binding proteins. However, the importance of these various features in disease phenotypes is not clearly understood. Here, we have built a support vector machine (SVM) model (termed DDIG-SN) as a means to discriminate disease-causing synonymous variants. The model was trained and evaluated on nearly 900 disease-causing variants. The method achieves robust performance with the area under the receiver operating characteristic curve of 0.84 and 0.85 for protein-stratified 10-fold cross-validation and independent testing, respectively. We were able to show that the disease-causing effects in the immediate proximity to exon–intron junctions (1–3 bp) are driven by the loss of splicing motif strength, whereas the gain of splicing motif strength is the primary cause in regions further away from the splice site (4–69 bp). The method is available as a part of the DDIG server at http://sparks-lab.org/ddig

Evidence in disease and non-disease contexts that nonsense mutations cause altered splicing via motif disruption

Transcripts containing premature termination codons (PTCs) can be subject to nonsense-associated alternative splicing (NAS). Two models have been evoked to explain this, scanning and splice motif disruption. The latter postulates that exonic cis motifs, such as exonic splice enhancers (ESEs), are disrupted by nonsense mutations. We employ genome-wide transcriptomic and k-mer enrichment methods to scrutinize this model. First, we show that ESEs are prone to disruptive nonsense mutations owing to their purine richness and paucity of TGA, TAA and TAG. The motif model correctly predicts that NAS rates should be low (we estimate 5–30%) and approximately in line with estimates for the rate at which random point mutations disrupt splicing (8–20%). Further, we find that, as expected, NAS-associated PTCs are predictable from nucleotide-based machine learning approaches to predict splice disruption and, at least for pathogenic variants, are enriched in ESEs. Finally, we find that both in and out of frame mutations to TAA, TGA or TAG are associated with exon skipping. While a higher relative frequency of such skip-inducing mutations in-frame than out of frame lends some credence to the scanning model, these results reinforce the importance of considering splice motif modulation to understand the etiology of PTC-associated disease

Semantically Rich Local Dataset Generation for Explainable AI in Genomics

Black box deep learning models trained on genomic sequences excel at predicting the outcomes of different gene regulatory mechanisms. Therefore, interpreting these models may provide novel insights into the underlying biology, supporting downstream biomedical applications. Due to their complexity, interpretable surrogate models can only be built for local explanations (e.g., a single instance). However, accomplishing this requires generating a dataset in the neighborhood of the input, which must maintain syntactic similarity to the original data while introducing semantic variability in the model\u27s predictions. This task is challenging due to the complex sequence-to-function relationship of DNA. We propose using Genetic Programming to generate datasets by evolving perturbations in sequences that contribute to their semantic diversity. Our custom, domain-guided individual representation effectively constrains syntactic similarity, and we provide two alternative fitness functions that promote diversity with no computational effort. Applied to the RNA splicing domain, our approach quickly achieves good diversity and significantly outperforms a random baseline in exploring the search space, as shown by our proof-of-concept, short RNA sequence. Furthermore, we assess its generalizability and demonstrate scalability to larger sequences, resulting in a ~30% improvement over the baseline