Background: Spliceosomal introns are a common feature of eukaryotic genomes. To approach a comprehensive understanding of intron evolution on Earth, studies should look beyond repeatedly studied groups such as animals, plants, and fungi. The slime mold Dictyostelium belongs to a supergroup of eukaryotes not covered in previous studies. Results: We found 441 precise intron losses in Dictyostelium discoideum and 202 precise intron losses in Dictyostelium purpureum. Consistent with these observations, Dictyostelium discoideum was found to have significantly more copies of reverse transcriptase genes than Dictyostelium purpureum. We also found that the lost introns are significantly further from the 5′ end of genes than the conserved introns. Adjacent introns were prone to be lost simultaneously in Dictyostelium discoideum. In both Dictyostelium species, the exonic sequences flanking lost introns were found to have a significantly higher GC content than those flanking conserved introns. Together, these observations support a reverse-transcription model of intron loss in which intron losses were caused by gene conversion between genomic DNA and cDNA reverse transcribed from mature mRNA. We also identified two imprecise intron losses in Dictyostelium discoideum that may have resulted from genomic deletions. Ninety-eight putative intron gains were also observed. Consistent with previous studies of other lineages, the source sequences were found in only a small number of cases, with only two instances of intron gain identified in Dictyostelium discoideum. Conclusions: Although they diverged very early from animals and fungi, Dictyostelium species have similar mechanisms of intron loss.

In this study, we identified 19 intron losses, including 11 precise intron losses (PILs), six imprecise intron losses (IILs), one de-exonization, and one exon deletion in tomato and potato, and 17 IILs in Arabidopsis thaliana. Comparative analysis of related genomes confirmed that all of the IILs have been fixed during evolution. Consistent with previous studies, our results indicate that PILs are a major type of intron loss. However, at least in plants, IILs are unlikely to be as rare as previously reported. This article was reviewed by Jun Yu and Zhang Zhang. For complete reviews, see the Reviewers’ Reports section.

Bipolar disorder is a common and severe mental illness with unsolved pathophysiology. A genome-wide association study (GWAS) has been used to find a number of risk genes, but it is difficult for a GWAS to find genes indirectly associated with a disease. To find core hub genes, we introduce a network analysis after the GWAS was conducted. Six thousand four hundred fifty eight single nucleotide polymorphisms (SNPs) with p < 0.01 were sifted out from Wellcome Trust Case Control Consortium (WTCCC) dataset and mapped to 2045 genes, which are then compared with the protein–protein network. One hundred twelve genes with a degree >17 were chosen as hub genes from which five significant modules and four core hub genes (FBXL13, WDFY2, bFGF, and MTHFD1L) were found. These core hub genes have not been reported to be directly associated with BD but may function by interacting with genes directly related to BD. Our method engenders new thoughts on finding genes indirectly associated with, but important for, complex diseases.

The origin and subsequent accumulation of spliceosomal introns are prominent events in the evolution of eukaryotic gene structure. However, the mechanisms underlying intron gain remain unclear because there are few proven cases of recently gained introns. In anRNA-dependent RNA polymerase(RdRp) gene, we found that a tandem duplication occurred after the divergence of potato and its wild relatives among otherSolanumplants. The duplicated sequence crosses the intron-exon boundary of the first intron and the second exon. A new intron was detected at this duplicated region, and it includes a small previously exonic segment of the upstream copy of the duplicated sequence and the intronic segment of the downstream copy of the duplicated sequence. The donor site of this new intron was directly obtained from the small previously exonic segment. Most of the splicing signals were inherited directly from the parental intron/exon structure, including a putative branch site, the polypyrimidine tract, the 3′ splicing site, two putative exonic splicing enhancers, and the GC contents differed between the intron and exon. In the widely cited model of intron gain by tandem genomic duplication, the duplication of an AGGT-containing exonic segment provides the GT and AG splicing sites for the new intron. Our results illustrate that the tandem duplication model of intron gain should be diverse in terms of obtaining the proper splicing signals.

Misfolding and aggregation of transthyretin (TTR) is widely known to be responsible for a progressive systemic disorder called amyloid transthyretin (ATTR) amyloidosis. Studies suggest that TTR aggregation is initiated by a rate-limiting dissociation of the homo-tetramer into its monomers, which can rapidly misfold and self-assemble into amyloid fibril. Thus, exploring conformational change involved in TTR monomer misfolding is of vital importance for understanding the pathogenesis of ATTR amyloidosis. In this work, microsecond timescale hybrid-resolution molecular dynamics (MD) simulations combined with Markov state model (MSM) analysis were performed to investigate the misfolding mechanism of the TTR monomer. The results indicate that a macrostate with partially unfolded conformations may serve as the misfolded state of the TTR monomer. This misfolded state was extremely stable with a very large equilibrium probability of about 85.28%. With secondary structure analysis, we found the DAGH sheet in this state to be significantly destroyed. The CBEF sheet was relatively stable and sheet structure was maintained. However, the F-strand in this sheet was likely to move away from E-strand and reform a new β-sheet with the H-strand. This observation is consistent with experimental finding that F and H strands in the outer edge drive the misfolding of TTR. Finally, transition pathways from a near native state to this misfolded macrostate showed that the conformational transition can occur either through a native-like β-sheet intermediates or through partially unfolded intermediates, while the later appears to be the main pathway. As a whole, we identified a potential misfolded state of the TTR monomer and elucidated the misfolding pathway for its conformational transition. This work can provide a valuable theoretical basis for understanding of TTR aggregation and the pathogenesis of ATTR amyloidosis at the atomic level.

Hepatocellular carcinoma (HCC) is a highly heterogeneous cancer with a poor prognosis. During the development of cancer cells, mitochondria influence various cell death patterns by regulating metabolic pathways such as oxidative phosphorylation. However, the relationship between mitochondrial function and cell death patterns in HCC remains unclear. In this study, we used a comprehensive machine learning framework to construct a mitochondrial functional activity-associated programmed cell death index (MPCDI) based on scRNA-seq and RNA-seq data from TCGA, GEO, and ICGC datasets. The index signature was used to classify HCC patients, and studied the multi-omics features, immune microenvironment, and drug sensitivity of the subtypes. Finally, we constructed the MPCDI signature consisting of four genes (S100A9, FYN, LGALS3, and HMOX1), which was one of the independent risk factors for the prognosis of HCC patients. The HCC patients were divided into high- and low-MPCDI groups, and the immune status was different between the two groups. Patients with a high MPCDI had higher TIDE scores and poorer responses to immunotherapy, suggesting that high-MPCDI patients might not be suitable for immunotherapy. By analyzing the drug sensitivity data of CTRP, GDSC, and PRISM databases, it was found that staurosporine has potential therapeutic significance for patients with a high MPCDI. In summary, based on the characteristics of mitochondria function and PCD patterns, we used single-cell and transcriptome data to identify four genes and construct the MPCDI signature, which provided new perspectives and directions for the clinical diagnosis and personalized treatment of HCC patients.