Genetic Variation Among Certain Fish Species in Terms of Evolution and Lineages

Three tests of phylogenetic including likelihood-joining tree, neighbour-joining tree, and minimum evolution tree have been used based on sox3 gene. Phylogenetic analysis was used to detect the genetic affinity and common ancestors for selected species that belong to the same or different families. This study showed the most appropriate methods for testing the genetic affinity among species and the methodology of each test according to the requirement of molecular applications. Secondary RNA predicted structure and minimum free energy were also included in this study because of their contribution to the detection of the orthologous gene and variance in RNA folding among species related to the different families. The genetic distance in the studied populations was calculated to know the most appropriate way to find out the genetic similarity among the studied species. The low distance-variance value of each group indicated significant genetic affinity among the species of the same family, this result is more consistent with the test of maximum-likelihood tree indicating the validity of this test to measure the genetic affinity among species that have common ancestors.

Characterization of 67 Confirmed Clustered Regularly Interspaced Short Palindromic Repeats Loci in 52 Strains of Staphylococci

Staphylococcus aureus (S. aureus), which is one of the most important species of Staphylococci, poses a great threat to public health. Clustered regularly interspaced short palindromic repeats (CRISPR) and their CRISPR-associated proteins (Cas) are an adaptive immune platform to combat foreign mobile genetic elements (MGEs) such as plasmids and phages. The aim of this study is to describe the distribution and structure of CRISPR-Cas system in S. aureus, and to explore the relationship between CRISPR and horizontal gene transfer (HGT). Here, we analyzed 67 confirmed CRISPR loci and 15 companion Cas proteins in 52 strains of Staphylococci with bioinformatics methods. Comparing with the orphan CRISPR loci in Staphylococci, the strains harboring complete CRISPR-Cas systems contained multiple CRISPR loci, direct repeat sequences (DR) forming stable RNA secondary structures with lower minimum free energy (MFE), and variable spacers with detectable protospacers. In S. aureus, unlike the orphan CRISPRs away from Staphylococcal cassette chromosome mec (SCCmec), the complete CRISPR-Cas systems were in J1 region of SCCmec. In addition, we found a conserved motif 5′-TTCTCGT-3′ that may protect their downstream sequences from DNA interference. In general, orphan CRISPR locus in S. aureus differed greatly from the structural characteristics of the CRISPR-Cas system. Collectively, our results provided new insight into the diversity and characterization of the CRISPR-Cas system in S. aureus.

Evolution and structural variations in chloroplast tRNAs in gymnosperms

Background Chloroplast transfer RNAs (tRNAs) can participate in various vital processes. Gymnosperms have important ecological and economic value, and they are the dominant species in forest ecosystems in the Northern Hemisphere. However, the evolution and structural changes in chloroplast tRNAs in gymnosperms remain largely unclear. Results In this study, we determined the nucleotide evolution, phylogenetic relationships, and structural variations in 1779 chloroplast tRNAs in gymnosperms. The numbers and types of tRNA genes present in the chloroplast genomes of different gymnosperms did not differ greatly, where the average number of tRNAs was 33 and the frequencies of occurrence for various types of tRNAs were generally consistent. Nearly half of the anticodons were absent. Molecular sequence variation analysis identified the conserved secondary structures of tRNAs. About a quarter of the tRNA genes were found to contain precoded 3′ CCA tails. A few tRNAs have undergone novel structural changes that are closely related to their minimum free energy, and these structural changes affect the stability of the tRNAs. Phylogenetic analysis showed that tRNAs have evolved from multiple common ancestors. The transition rate was higher than the transversion rate in gymnosperm chloroplast tRNAs. More loss events than duplication events have occurred in gymnosperm chloroplast tRNAs during their evolutionary process. Conclusions These findings provide novel insights into the molecular evolution and biological characteristics of chloroplast tRNAs in gymnosperms.

The First Report of Genetic Polymorphisms of the Equine SPRN Gene in Outbred Horses, Jeju and Halla Horses

Prion disease is a fatal infectious disease caused by the accumulation of pathogenic prion protein (PrPSc) in several mammals. However, to date, prion disease has not been reported in horses. The Sho protein encoded by the shadow of the prion protein gene (SPRN) plays an essential role in the pathomechanism of prion diseases. To date, the only genetic study of the equine SPRN gene has been reported in the inbred horse, Thoroughbred horse. We first discovered four SPRN single nucleotide polymorphisms (SNPs) in 141 Jeju and 88 Halla horses by direct DNA sequencing. In addition, we found that the genotype, allele and haplotype frequencies of these SNPs of Jeju horses were significantly different from those of Halla and Thoroughbred horses, this latter breed is also included in this study. Furthermore, we observed that the minimum free energy and mRNA secondary structure were significantly different according to haplotypes of equine SPRN polymorphisms by the RNAsnp program. Finally, we compared the SNPs in the coding sequence (CDS) of the SPRN gene between horses and prion disease-susceptible species. Notably, prion disease-susceptible animals had polymorphisms that cause amino acid changes in the open reading frame (ORF) of the SPRN gene, while these polymorphisms were not found in horses.

KnotAli: Informed Energy Minimization Through the Use of Evolutionary Information

BackgroundImproving the prediction of structures, especially those containing pseudoknots (structures with crossing base pairs) is an ongoing challenge. Homology-based methods utilize structural similarities within a family to predict the structure. However, their prediction is limited to the consensus structure, and the quality of the alignment. Minimum free energy (MFE) based methods, on the other hand, do not rely on familial information and can predict structures of novel RNA molecules. Their prediction normally suffers from inaccuracies due to their underlying energy parameters. ResultsWe present a new method for prediction of RNA pseudoknotted secondary structures that combines the strengths of MFE prediction and alignment-based methods. KnotAli takes a multiple RNA sequence alignment and uses covariation and thermodynamic energy minimization to predict secondary structures for each individual sequence in the alignment. We compared KnotAli’s performance to that of three other alignment-based programs, on a large data set of 10 families with pseudoknotted and pseudoknot-free reference structures. We produced sequence alignments for each family using two well-known sequence aligners (MUSCLE and MAFFT). We found KnotAli to be superior in 6 of the 10 families for MUSCLE and 7 of the 10 for MAFFT. ConclusionsWe find KnotAli’s predictions to be less dependent on alignment quality. In particular, KnotAli is shown to have more accurate predictions compared to other leading methods as alignment quality deteriorates. KnotAli can be found online on github at https://github.com/mateog4712/KnotAli

MiREDiBase, a manually curated database of validated and putative editing events in microRNAs

MicroRNAs (miRNAs) are regulatory small non-coding RNAs that function as translational repressors. MiRNAs are involved in most cellular processes, and their expression and function are presided by several factors. Amongst, miRNA editing is an epitranscriptional modification that alters the original nucleotide sequence of selected miRNAs, possibly influencing their biogenesis and target-binding ability. A-to-I and C-to-U RNA editing are recognized as the canonical types, with the A-to-I type being the predominant one. Albeit some bioinformatics resources have been implemented to collect RNA editing data, it still lacks a comprehensive resource explicitly dedicated to miRNA editing. Here, we present MiREDiBase, a manually curated catalog of editing events in miRNAs. The current version includes 3,059 unique validated and putative editing sites from 626 pre-miRNAs in humans and three primates. Editing events in mature human miRNAs are supplied with miRNA-target predictions and enrichment analysis, while minimum free energy structures are inferred for edited pre-miRNAs. MiREDiBase represents a valuable tool for cell biology and biomedical research and will be continuously updated and expanded at https://ncrnaome.osumc.edu/miredibase.

Annealing synchronizes the 70S ribosome into a minimum-energy conformation

Researchers commonly anneal metals, alloys, and semiconductors to repair defects and improve microstructures via recrystallization. Theoretical studies indicate simulated annealing on biological macromolecules helps predict the final structures with minimum free energy. Experimental validation of this homogenizing effect and further exploration of its applications are fascinating scientific questions that remain elusive. Here, we chose the apo-state 70S ribosome from Escherichia coli as a model, wherein the 30S subunit undergoes a thermally driven inter-subunit rotation and exhibits substantial structural flexibility as well as distinct free energy. We experimentally demonstrate that annealing at a fast cooling rate enhances the 70S ribosome homogeneity and improves local resolution on the 30S subunit. After annealing, the 70S ribosome is in a nonrotated state with respect to corresponding intermediate structures in unannealed or heated ribosomes, and exhibits a minimum energy in the free energy landscape. One can readily crystallize these minimum-energy ribosomes, which have great potential for synchronizing proteins on a single-molecule level. Our experimental results are consistent with theoretical analysis on the temperature-dependent Boltzmann distribution, and offer a facile yet robust approach to enhance protein stability, which is ideal for high-resolution cryogenic electron microscopy. Beyond structure determination, annealing can be extended to study protein folding and explore conformational and energy landscape.

Predicting Selective RNA Processing and Stabilization Operons in Clostridium spp.

In selective RNA processing and stabilization (SRPS) operons, stem–loops (SLs) located at the 3′-UTR region of selected genes can control the stability of the corresponding transcripts and determine the stoichiometry of the operon. Here, for such operons, we developed a computational approach named SLOFE (stem–loop free energy) that identifies the SRPS operons and predicts their transcript- and protein-level stoichiometry at the whole-genome scale using only the genome sequence via the minimum free energy (ΔG) of specific SLs in the intergenic regions within operons. As validated by the experimental approach of differential RNA-Seq, SLOFE identifies genome-wide SRPS operons in Clostridium cellulolyticum with 80% accuracy and reveals that the SRPS mechanism contributes to diverse cellular activities. Moreover, in the identified SRPS operons, SLOFE predicts the transcript- and protein-level stoichiometry, including those encoding cellulosome complexes, ATP synthases, ABC transporter family proteins, and ribosomal proteins. Its accuracy exceeds those of existing in silico approaches in C. cellulolyticum, Clostridium acetobutylicum, Clostridium thermocellum, and Bacillus subtilis. The ability to identify genome-wide SRPS operons and predict their stoichiometry via DNA sequence in silico should facilitate studying the function and evolution of SRPS operons in bacteria.

Investigating the concept of accessibility for predicting novel RNA-RNA interactions

State-of-the-art methods for predicting novel trans RNA-RNA interactions use the so-called accessibility as key concept. It estimates whether a region in a given RNA sequence is accessible for forming trans interactions, using a thermodynamic model which quantifies its secondary structure features. RNA-RNA interactions are then predicted by finding the minimum free energy base pairing between the two transcripts, taking into account the accessibility as energy penalty. We investigated the underlying assumptions of this approach using the two methods RNAPLEX and INTARNA on two datasets, containing sRNA-mRNA and snoRNA-rRNA interactions, respectively. We find that (1) known trans RNA-RNA interactions frequently overlap regions containing RNA structure features, (2) the estimated accessibility reflects sRNA structures fairly well, but often disagrees with structures of longer transcripts, (3) the prediction performance of RNA-RNA interaction prediction methods is independent of the quality of the estimated accessibility profiles, and (4) one important overall effect of accessibility profiles is to prevent the thermodynamic model from predicting too long interactions. Based on our findings, we conclude that the accessibility concept to the minimum free energy approach to predicting novel RNA-RNA interactions has conceptual limitations and discuss potential ways of improving the field in the future.

A meta-analysis of gRNA library screens enables an improved understanding of the impact of gRNA folding and structural stability on CRISPR-Cas9 activity.

CRISPR systems are known to be inhibited by unwanted secondary structures that form within the guide RNA (gRNA). The minimum free energy of predicted secondary structures has been used in prediction algorithms. However, the types of structures as well as the degree to which a predicted structure can inhibit Cas9/gRNA activity is not well characterized. Here we perform a meta-analysis of published CRISPR-Cas9 datasets to better understand the role of secondary structures in inhibiting gRNA activity. We identify two inhibitory structures and provide estimated free energy cutoffs at which they become impactful. Further, we identify the prevalence of these structures in existing datasets. The cutoffs provided help to explain conflicting impacts of free energy values in different datasets as well as providing a guideline for future gRNA designs.