Comparative mitochondrial genomics in Nematoda reveal astonishing variation in compositional biases and substitution rates indicative of multi-level selection.

BACKGROUND: Nematodes are the most abundant and diverse metazoans on Earth, and are known to significantly affect ecosystem functioning. A better understanding of their biology and ecology, including potential adaptations to diverse habitats and lifestyles, is key to understanding their response to global change scenarios. Mitochondrial genomes offer high species level characterization, low cost of sequencing, and an ease of data handling that can provide insights into nematode evolutionary pressures. RESULTS: Generally, nematode mitochondrial genomes exhibited similar structural characteristics (e.g., gene size and GC content), but displayed remarkable variability around these general patterns. Compositional strand biases showed strong codon position specific G skews and relationships with nematode life traits (especially parasitic feeding habits) equal to or greater than with predicted phylogeny. On average, nematode mitochondrial genomes showed low non-synonymous substitution rates, but also high clade specific deviations from these means. Despite the presence of significant mutational saturation, non-synonymous (dN) and synonymous (dS) substitution rates could still be significantly explained by feeding habit and/or habitat. Low ratios of dN:dS rates, particularly associated with the parasitic lifestyles, suggested the presence of strong purifying selection. CONCLUSIONS: Nematode mitochondrial genomes demonstrated a capacity to accumulate diversity in composition, structure, and content while still maintaining functional genes. Moreover, they demonstrated a capacity for rapid evolutionary change pointing to a potential interaction between multi-level selection pressures and rapid evolution. In conclusion, this study helps establish a background for our understanding of the potential evolutionary pressures shaping nematode mitochondrial genomes, while outlining likely routes of future inquiry.

GAE-LGA: integration of multi-omics data with graph autoencoders to identify lncRNA-PCG associations.

Long non-coding RNAs (lncRNAs) can disrupt the biological functions of protein-coding genes (PCGs) to cause cancer. However, the relationship between lncRNAs and PCGs remains unclear and difficult to predict. Machine learning has achieved a satisfactory performance in association prediction, but to our knowledge, it is currently less used in lncRNA-PCG association prediction. Therefore, we introduce GAE-LGA, a powerful deep learning model with graph autoencoders as components, to recognize potential lncRNA-PCG associations. GAE-LGA jointly explored lncRNA-PCG learning and cross-omics correlation learning for effective lncRNA-PCG association identification. The functional similarity and multi-omics similarity of lncRNAs and PCGs were accumulated and encoded by graph autoencoders to extract feature representations of lncRNAs and PCGs, which were subsequently used for decoding to obtain candidate lncRNA-PCG pairs. Comprehensive evaluation demonstrated that GAE-LGA can successfully capture lncRNA-PCG associations with strong robustness and outperformed other machine learning-based identification methods. Furthermore, multi-omics features were shown to improve the performance of lncRNA-PCG association identification. In conclusion, GAE-LGA can act as an efficient application for lncRNA-PCG association prediction with the following advantages: It fuses multi-omics information into the similarity network, making the feature representation more accurate; it can predict lncRNA-PCG associations for new lncRNAs and identify potential lncRNA-PCG associations with high accuracy.

Characterization of the mitochondrial genomes of the Mexican endemic bats Corynorhinus mexicanus and Corynorhinus leonpaniaguae (Chiroptera: Vespertilionidae).

BACKGROUND: The genus Corynorhinus is composed of four recognized species: C. rafinesquii, C. townsendii, C. mexicanus, and C. leonpaniaguae, the latter two being endemic to Mexico. According to the IUCN, C. mexicanus is considered "Near Threatened", as its populations are dwindling and habitats are affected by anthropogenic disturbance. Corynorhinus leonpaniaguae has not been assigned to an IUCN Red List risk category due to its recent description. METHODS AND RESULTS: In this study, the mitochondrial genomes of C. mexicanus and C. leonpaniaguae were assembled and characterized in detail. The mitochondrial genomes (mtDNA) of C. mexicanus and C. leonpaniaguae have lengths of 16,470 and 16,581 bp respectively, with a predominant nucleotide usage of adenine (31.670% and 31.729%, respectively) and thymine (26.15% and 26.18%, respectively). The mtDNA of C. mexicanus and C. leonpaniaguae is composed of 37 coding and non-coding elements: 22 transfer RNAs (tRNA), 13 protein-coding genes (PCGs), two ribosomal RNAs and a non-coding region, the control region, which has a length of 933 bp and 1,149 bp, respectively. All tRNAs exhibited a cloverleaf secondary structure, with the exception of trn-Ser1 which showed a deletion of the dihydrouridine arm in the two species. All PCGs are subjected to purifying selection, with atp8 being the gene showing the highest Ka/Ks value. CONCLUSIONS: These are the first whole mitogenomic resources developed for C. mexicanus and C. leonpaniaguae and enhance our knowledge of the ecology of these species and aid in their conservation.

Genomic analysis and phylogenetic characterization of Himalayan snow trout, Schizothorax esocinus based on mitochondrial protein-coding genes.

BACKGROUND: Mitochondrial DNA (mtDNA) has become a significant tool for exploring genetic diversity and delineating evolutionary links across diverse taxa. Within the group of cold-water fish species that are native to the Indian Himalayan region, Schizothorax esocinus holds particular importance due to its ecological significance and is potentially vulnerable to environmental changes. This research aims to clarify the phylogenetic relationships within the Schizothorax genus by utilizing mitochondrial protein-coding genes. METHODS: Standard protocols were followed for the isolation of DNA from S. esocinus. For the amplification of mtDNA, overlapping primers were used, and then subsequent sequencing was performed. The genetic features were investigated by the application of bioinformatic approaches. These approaches covered the evaluation of nucleotide composition, codon usage, selective pressure using nonsynonymous substitution /synonymous substitution (Ka/Ks) ratios, and phylogenetic analysis. RESULTS: The study specifically examined the 13 protein-coding genes of Schizothorax species which belongs to the Schizothoracinae subfamily. Nucleotide composition analysis showed a bias towards A + T content, consistent with other cyprinid fish species, suggesting evolutionary conservation. Relative Synonymous Codon Usage highlighted leucine as the most frequent (5.18%) and cysteine as the least frequent (0.78%) codon. The positive AT-skew and the predominantly negative GC-skew indicated the abundance of A and C. Comparative analysis revealed significant conservation of amino acids in multiple genes. The majority of amino acids were hydrophobic rather than polar. The purifying selection was revealed by the genetic distance and Ka/Ks ratios. Phylogenetic study revealed a significant genetic divergence between S. esocinus and other Schizothorax species with interspecific K2P distances ranging from 0.00 to 8.87%, with an average of 5.76%. CONCLUSION: The present study provides significant contributions to the understanding of mitochondrial genome diversity and genetic evolution mechanisms in Schizothoracinae, hence offering vital insights for the development of conservation initiatives aimed at protecting freshwater fish species.

Streamlined Full-Length Total RNA Sequencing of Paraformaldehyde-Fixed Brain Tissues.

Paraformaldehyde (PFA) fixation is the preferred method for preserving tissue architecture for anatomical and pathological observations. Meanwhile, PFA reacts with the amine groups of biomolecules to form chemical cross-linking, which preserves RNA within the tissue. This has great prospects for RNA sequencing to characterize the molecular underpinnings after anatomical and pathological observations. However, RNA is inaccessible due to cross-linked adducts forming between RNA and other biomolecules in prolonged PFA-fixed tissue. It is also difficult to perform reverse transcription and PCR, resulting in low sequencing sensitivity and reduced reproducibility. Here, we developed a method to perform RNA sequencing in PFA-fixed tissue, which is easy to use, cost-effective, and allows efficient sample multiplexing. We employ cross-link reversal to recover RNA and library construction using random primers without artificial fragmentation. The yield and quality of recovered RNA significantly increased through our method, and sequencing quality metrics and detected genes did not show any major differences compared with matched fresh samples. Moreover, we applied our method for gene expression analysis in different regions of the mouse brain and identified unique gene expression profiles with varied functional implications. We also find significant dysregulation of genes involved in Alzheimer's disease (AD) pathogenesis within the medial septum (MS)/vertical diagonal band of Broca (VDB) of the 5×FAD mouse brain. Our method can thus increase the performance of high-throughput RNA sequencing with PFA-fixed samples and allows longitudinal studies of small tissue regions isolated by their in situ context.

Structure, Evolution, and Mitochondrial Genome Analysis of Mussel Species (Bivalvia, Mytilidae).

Based on the nucleotide sequences of the mitochondrial genome (mitogenome) of specimens taken from two mussel species (Arcuatula senhousia and Mytilus coruscus), an investigation was performed by means of the complex approaches of the genomics, molecular phylogenetics, and evolutionary genetics. The mitogenome structure of studied mussels, like in many other invertebrates, appears to be much more variable than in vertebrates and includes changing gene order, duplications, and deletions, which were most frequent for tRNA genes; the mussel species' mitogenomes also have variable sizes. The results demonstrate some of the very important properties of protein polypeptides, such as hydrophobicity and its determination by the purine and pyrimidine nucleotide ratio. This fact might indirectly indicate the necessity of purifying natural selection for the support of polypeptide functionality. However, in accordance with the widely accepted and logical concept of natural cutoff selection for organisms living in nature, which explains its action against deleterious nucleotide substitutions in the nonsynonymous codons (mutations) and its holding of the active (effective) macromolecules of the polypeptides in a population, we were unable to get unambiguous evidence in favor of this concept in the current paper. Here, the phylogeny and systematics of mussel species from one of the largest taxons of bivalve mollusks are studied, the family known as Mytilidae. The phylogeny for Mytilidae (order Mytilida), which currently has no consensus in terms of systematics, is reconstructed using a data matrix of 26-27 mitogenomes. Initially, a set of 100 sequences from GenBank were downloaded and checked for their gender: whether they were female (F) or male (M) in origin. Our analysis of the new data confirms the known drastic differences between the F/M mitogenome lines in mussels. Phylogenetic reconstructions of the F-lines were performed using the combined set of genetic markers, reconstructing only protein-coding genes (PCGs), only rRNA + tRNA genes, and all genes. Additionally, the analysis includes the usage of nucleotide sequences composed of other data matrices, such as 20-68 mitogenome sequences. The time of divergence from MRCA, estimated via BEAST2, for Mytilidae is close to 293 Mya, suggesting that they originate in the Silurian Period. From all these data, a consensus for the phylogeny of the subfamily of Mytilinae and its systematics is suggested. In particular, the long-debated argument on mussel systematics was resolved as to whether Mytilidae, and the subfamily of Mytilinae, are monophyletic. The topology signal, which was strongly resolved in this paper and in the literature, has refuted the theory regarding the monophyly of Mytilinae.

[Identification of Protein-Coding Gene Markers in Breast Invasive Carcinoma Based on Machine Learning].

Objective To screen out the biomarkers linked to prognosis of breast invasive carcinoma based on the analysis of transcriptome data by random forest (RF),extreme gradient boosting (XGBoost),light gradient boosting machine (LightGBM),and categorical boosting (CatBoost). Methods We obtained the expression data of breast invasive carcinoma from The Cancer Genome Atlas and employed DESeq2,t-test,and Cox univariate analysis to identify the differentially expressed protein-coding genes associated with survival prognosis in human breast invasive carcinoma samples.Furthermore,RF,XGBoost,LightGBM,and CatBoost models were established to mine the protein-coding gene markers related to the prognosis of breast invasive cancer and the model performance was compared.The expression data of breast cancer from the Gene Expression Omnibus was used for validation. Results A total of 151 differentially expressed protein-coding genes related to survival prognosis were screened out.The machine learning model established with C3orf80,UGP2,and SPC25 demonstrated the best performance. Conclusions Three protein-coding genes (UGP2,C3orf80,and SPC25) were screened out to identify breast invasive carcinoma.This study provides a new direction for the treatment and diagnosis of breast invasive carcinoma.

Characterization of the complete mitochondrial genome of the brazilian cownose ray Rhinoptera brasiliensis (Myliobatiformes, Rhinopteridae) in the western Atlantic and its phylogenetic implications.

BACKGROUND: The Brazilian cownose ray, Rhinoptera brasiliensis has undergone a global population reduction and is currently classified by IUCN as Vulnerable. This species is sometimes confused with Rhinoptera bonasus, the only external diagnostic characteristic to distinguish between both species is the number of rows of tooth plates. Both cownose rays overlap geographically from Rio de Janeiro to the western North Atlantic. This calls for a more comprehensive phylogenetic assessment using mitochondria DNA genomes to better understand the relationships and delimitation of these two species. METHODS AND RESULTS: The mitochondrial genome sequences of R. brasiliensis was obtained by next-generation sequencing. The length of the mitochondrial genome was 17,759 bp containing 13 protein-coding genes (PCGs), two ribosomal RNA (rRNA) genes, 22 transfer RNA (tRNA) genes, and a non-coding control region (D-loop). Each PCG was initiated by an authoritative ATG codon, except for COX1 initiated by a GTG codon. Most of the PCGs were terminated by a complete codon (TAA/TAG), while an incomplete termination codon (TA/T) was found in five out of the 13 PCGs. The phylogenetic analysis showed that R. brasiliensis was closely related to R. steindachneri whereas the reported mitogenome as R. steindachneri (GenBank accession number KM364982), differs from multiple mitocondrial DNA sequences of R. steindachneri and is nearly identical to that of R. javanica. CONCLUSION: The new mitogenome determined in this study provides new insight into the phylogenetic relationships in Rhinoptera, while providing new molecular data that can be applied to population genetic studies.

Genome-wide annotation of protein-coding genes in pig.

BACKGROUND: There is a need for functional genome-wide annotation of the protein-coding genes to get a deeper understanding of mammalian biology. Here, a new annotation strategy is introduced based on dimensionality reduction and density-based clustering of whole-body co-expression patterns. This strategy has been used to explore the gene expression landscape in pig, and we present a whole-body map of all protein-coding genes in all major pig tissues and organs. RESULTS: An open-access pig expression map ( www.rnaatlas.org ) is presented based on the expression of 350 samples across 98 well-defined pig tissues divided into 44 tissue groups. A new UMAP-based classification scheme is introduced, in which all protein-coding genes are stratified into tissue expression clusters based on body-wide expression profiles. The distribution and tissue specificity of all 22,342 protein-coding pig genes are presented. CONCLUSIONS: Here, we present a new genome-wide annotation strategy based on dimensionality reduction and density-based clustering. A genome-wide resource of the transcriptome map across all major tissues and organs in pig is presented, and the data is available as an open-access resource ( www.rnaatlas.org ), including a comparison to the expression of human orthologs.

The Functional Meaning of 5'UTR in Protein-Coding Genes.

As it is well known, messenger RNA has many regulatory regions along its sequence length. One of them is the 5' untranslated region (5'UTR), which itself contains many regulatory elements such as upstream ORFs (uORFs), internal ribosome entry sites (IRESs), microRNA binding sites, and structural components involved in the regulation of mRNA stability, pre-mRNA splicing, and translation initiation. Activation of the alternative, more upstream transcription start site leads to an extension of 5'UTR. One of the consequences of 5'UTRs extension may be head-to-head gene overlap. This review describes elements in 5'UTR of protein-coding transcripts and the functional significance of protein-coding genes 5' overlap with implications for transcription, translation, and disease.

The Beneficial Effects of Pine Nuts and Its Major Fatty Acid, Pinolenic Acid, on Inflammation and Metabolic Perturbations in Inflammatory Disorders.

Inflammatory disorders such as atherosclerosis, diabetes and rheumatoid arthritis are regulated by cytokines and other inflammatory mediators. Current treatments for these conditions are associated with significant side effects and do not completely suppress inflammation. The benefits of diet, especially the role of specific components, are poorly understood. Polyunsaturated fatty acids (PUFAs) have several beneficial health effects. The majority of studies on PUFAs have been on omega-3 fatty acids. This review will focus on a less studied fatty acid, pinolenic acid (PNLA) from pine nuts, which typically constitutes up to 20% of its total fatty acids. PNLA is emerging as a dietary PUFA and a promising supplement in the prevention of inflammatory disorders or as an alternative therapy. Some studies have shown the health implications of pine nuts oil (PNO) and PNLA in weight reduction, lipid-lowering and anti-diabetic actions as well as in suppression of cell invasiveness and motility in cancer. However, few reviews have specifically focused on the biological and anti-inflammatory effects of PNLA. Furthermore, in recent bioinformatic studies on human samples, the expression of many mRNAs and microRNAs was regulated by PNLA indicating potential transcriptional and post-transcriptional regulation of inflammatory and metabolic processes. The aim of this review is to summarize, highlight, and evaluate research findings on PNO and PNLA in relation to potential anti-inflammatory benefits and beneficial metabolic changes. In this context, the focus of the review is on the potential actions of PNLA on inflammation along with modulation of lipid metabolism and oxidative stress based on data from both in vitro and in vivo experiments, and human findings, including gene expression analysis.

The Genome of the Marine Alga Ulva compressa (Chlorophyta) Reveals Protein-Coding Genes with Similarity to Plants and Green Microalgae, but Also to Animal, Bacterial, and Fungal Genes.

The genome of the marine alga Ulva compressa was assembled using long and short reads. The genome assembly was 80.8 Mb in size and encoded 19,207 protein-coding genes. Several genes encoding antioxidant enzymes and a few genes encoding enzymes that synthesize ascorbate and glutathione were identified, showing similarity to plant and bacterial enzymes. Additionally, several genes encoding signal transduction protein kinases, such as MAPKs, CDPKS, CBLPKs, and CaMKs, were also detected, showing similarity to plants, green microalgae, and bacterial proteins. Regulatory transcription factors, such as ethylene- and ABA-responsive factors, MYB, WRKY, and HSTF, were also present and showed similarity to plant and green microalgae transcription factors. Genes encoding enzymes that synthesize ACC and ABA-aldehyde were also identified, but oxidases that synthesize ethylene and ABA, as well as enzymes that synthesize other plant hormones, were absent. Interestingly, genes involved in plant cell wall synthesis and proteins related to animal extracellular matrix were also detected. Genes encoding cyclins and CDKs were also found, and CDKs showed similarity to animal and fungal CDKs. Few genes encoding voltage-dependent calcium channels and ionotropic glutamate receptors were identified as showing similarity to animal channels. Genes encoding Transient Receptor Potential (TRP) channels were not identified, even though TRPs have been experimentally detected, indicating that the genome is not yet complete. Thus, protein-coding genes present in the genome of U. compressa showed similarity to plant and green microalgae, but also to animal, bacterial, and fungal genes.

Progress on molecular composition and genetic mechanism of plant B chromosomes.

In addition to the standard set of chromosomes (A chromosomes, As), so-called supernumerary B chromosomes (Bs) have been found causing a numerical chromosome variation. Bs have been considered to be genetically inert elements without any functional genes for a long period, because of the limited experimental methods and its dispensable property. More recently, sequencing of dissected Bs from several organisms has revealed the DNA composition, a vast number of protein-coding genes have been found with the effects on the transcripts and protein expression of the host. In this review, we summarize current understanding of B chromosomes carrying plants including rye (Secale cereale L.), maize (Zea mays L.) and Aegilops (Aegilops speltoides Tausch.), with the emphasis on Bs phenotypic effects, the inheritance mechanism of Bs, the molecular composition of Bs, the effects on host transcription regulation and protein expression upon the presence of Bs. Besides, we discuss the current study state and potential application of B chromosomes, aim to provide a new venue for chromosome engineering and breeding research.

TSEBRA: transcript selector for BRAKER.

BACKGROUND: BRAKER is a suite of automatic pipelines, BRAKER1 and BRAKER2, for the accurate annotation of protein-coding genes in eukaryotic genomes. Each pipeline trains statistical models of protein-coding genes based on provided evidence and, then predicts protein-coding genes in genomic sequences using both the extrinsic evidence and statistical models. For training and prediction, BRAKER1 and BRAKER2 incorporate complementary extrinsic evidence: BRAKER1 uses only RNA-seq data while BRAKER2 uses only a database of cross-species proteins. The BRAKER suite has so far not been able to reliably exceed the accuracy of BRAKER1 and BRAKER2 when incorporating both types of evidence simultaneously. Currently, for a novel genome project where both RNA-seq and protein data are available, the best option is to run both pipelines independently, and to pick one, likely better output. Therefore, one or another type of the extrinsic evidence would remain unexploited. RESULTS: We present TSEBRA, a software that selects gene predictions (transcripts) from the sets generated by BRAKER1 and BRAKER2. TSEBRA uses a set of rules to compare scores of overlapping transcripts based on their support by RNA-seq and homologous protein evidence. We show in computational experiments on genomes of 11 species that TSEBRA achieves higher accuracy than either BRAKER1 or BRAKER2 running alone and that TSEBRA compares favorably with the combiner tool EVidenceModeler. CONCLUSION: TSEBRA is an easy-to-use and fast software tool. It can be used in concert with the BRAKER pipeline to generate a gene prediction set supported by both RNA-seq and homologous protein evidence.

The Protein-Coding Human Genome: Annotating High-Hanging Fruits.

The major transcript variants of human protein-coding genes are annotated to a certain degree of accuracy combining manual curation, transcript data, and proteomics evidence. However, there is considerable disagreement on the annotation of about 2000 genes-they can be protein-coding, noncoding, or pseudogenes-and on the annotation of most of the predicted alternative transcripts. Pure transcriptome mapping approaches seem to be limited in discriminating functional expression from noise. These limitations have partially been overcome by dedicated algorithms to detect alternative spliced micro-exons and wobble splice variants. Recently, knowledge about splice mechanism and protein structure are incorporated into an algorithm to predict neighboring homologous exons, often spliced in a mutually exclusive manner. Predicted exons are evaluated by transcript data, structural compatibility, and evolutionary conservation, revealing hundreds of novel coding exons and splice mechanism re-assignments. The emerging human pan-genome is necessitating distinctive annotations incorporating differences between individuals and between populations.

Comparative Analysis of Mitochondrial Genome Features among Four Clonostachys Species and Insight into Their Systematic Positions in the Order Hypocreales.

The mycoparasite fungi of Clonostachys have contributed to the biological control of plant fungal disease and nematodes. The Clonostachys fungi strains were isolated from Ophiocordyceps highlandensis, Ophiocordycepsnigrolla and soil, which identified as Clonostachyscompactiuscula, Clonostachysrogersoniana, Clonostachyssolani and Clonostachys sp. To explore the evolutionary relationship between the mentioned species, the mitochondrial genomes of four Clonostachys species were sequenced and assembled. The four mitogenomes consisted of complete circular DNA molecules, with the total sizes ranging from 27,410 bp to 42,075 bp. The GC contents, GC skews and AT skews of the mitogenomes varied considerably. Mitogenomic synteny analysis indicated that these mitogenomes underwent gene rearrangements. Among the 15 protein-coding genes within the mitogenomes, the nad4L gene exhibited the least genetic distance, demonstrating a high degree of conservation. The selection pressure analysis of these 15 PCGs were all below 1, indicating that PCGs were subject to purifying selection. Based on protein-coding gene calculation of the significantly supported topologies, the four Clonostachys species were divided into a group in the phylogenetic tree. The results supplemented the database of mitogenomes in Hypocreales order, which might be a useful research tool to conduct a phylogenetic analysis of Clonostachys. Additionally, the suitable molecular marker was significant to study phylogenetic relationships in the Bionectriaceae family.

Ancient evolutionary signals of protein-coding sequences allow the discovery of new genes in the Drosophila melanogaster genome.

BACKGROUND: The current growth in DNA sequencing techniques makes of genome annotation a crucial task in the genomic era. Traditional gene finders focus on protein-coding sequences, but they are far from being exhaustive. The number of this kind of genes continuously increases due to new experimental data and development of improved bioinformatics algorithms. RESULTS: In this context, AnABlast represents a novel in silico strategy, based on the accumulation of short evolutionary signals identified by protein sequence alignments of low score. This strategy potentially highlights protein-coding regions in genomic sequences regardless of traditional homology or translation signatures. Here, we analyze the evolutionary information that the accumulation of these short signals encloses. Using the Drosophila melanogaster genome, we stablish optimal parameters for the accurate gene prediction with AnABlast and show that this new strategy significantly contributes to add genes, exons and pseudogenes regions, yet to be discovered in both already annotated and new genomes. CONCLUSIONS: AnABlast can be freely used to analyze genomic regions of whole genomes where it contributes to complete the previous annotation.

A robust two-gene signature for glioblastoma survival prediction.

Glioblastoma multiforme (GBM) is a highly malignant brain tumor. We explored the prognostic gene signature in 443 GBM samples by systematic bioinformatics analysis, using GSE16011 with microarray expression and corresponding clinical data from Gene Expression Omnibus as the training set. Meanwhile, patients from The Chinese Glioma Genome Atlas database (CGGA) were used as the test set and The Cancer Genome Atlas database (TCGA) as the validation set. Through Cox regression analysis, Kaplan-Meier analysis, t-distributed Stochastic Neighbor Embedding algorithm, clustering, and receiver operating characteristic analysis, a two-gene signature (GRIA2 and RYR3) associated with survival was selected in the GSE16011 dataset. The GRIA2-RYR3 signature divided patients into two risk groups with significantly different survival in the GSE16011 dataset (median: 0.72, 95% confidence interval [CI]: 0.64-0.98, vs median: 0.98, 95% CI: 0.65-1.61 years, logrank test P < .001), the CGGA dataset (median: 0.84, 95% CI: 0.70-1.18, vs median: 1.21, 95% CI: 0.95-2.94 years, logrank test P = .0017), and the TCGA dataset (median: 1.03, 95% CI: 0.86-1.24, vs median: 1.23, 95% CI: 1.04-1.85 years, logrank test P = .0064), validating the predictive value of the signature. And the survival predictive potency of the signature was independent from clinicopathological prognostic features in multivariable Cox analysis. We found that after transfection of U87 cells with small interfering RNA, GRIA2 and RYR3 influenced the biological behaviors of proliferation, migration, and invasion of glioblastoma cells. In conclusion, the two-gene signature was a robust prognostic model to predict GBM survival.

Characterization of the Whole Mitogenome of Largehead Hairtail Trichiurus lepturus (Trichiuridae): Insights into Special Characteristics.

Mitochondrial genomes are valuable for making inferences regarding population genetics, phylogenetics and recently in understanding adaptive variation in OXPHOS genes. Ribbon fish, Trichiurus lepturus is distributed in the Indian Ocean and contributes to a major share of pelagic fish landings. Considering the importance, we characterized the complete mitogenome of large head hairtail T. lepturus from Indian waters by PCR amplification and sequencing. The entire mitogenome is 16,840 bp in length, with 13 protein coding genes, 2 subunit ribosomal RNA genes, and 1 control region similar to other vertebrates. Genome contains only 21 tRNAs (tRNAPro is absent) as against 22 tRNAs reported in other vertebrates. The putative origin of L-strand replication (OL) was located in a cluster of five tRNA genes (WANCY region) and may not be functional due to the variation of conserved motif (5'-GCCGG-3') and loop. These two unusual features are common for Trichiurus mitogenomes. Phylogenetic analysis supported the monophyly of Trichiuridae. This study will provide information for further studies on taxonomy, phylogeny and patterns of adaptive evolution in the mitogenome of Trichiurus species.

A novel multidimensional signature predicts prognosis in hepatocellular carcinoma patients.

The abnormal expression of microRNAs (miRNAs) or protein-coding genes (PCGs) have been found to be associated with the prognosis of hepatocellular carcinoma (HCC) patients. Using bioinformatics analysis methods including Cox's proportional hazards regression analysis, the random survival forest algorithm, Kaplan-Meier, and receiver operating characteristic (ROC) curve analysis, we mined the gene expression profiles of 469 HCC patients from The Cancer Genome Atlas (n = 379) and Gene Expression Omnibus (GSE14520; n = 90) public database. We selected a signature comprising one protein-coding gene (PCG; DNA polymerase µ) and three miRNAs (hsa-miR-149-5p, hsa-miR-424-5p, hsa-miR-579-5p) with highest accurate prediction (area under the ROC curve [AUC] = 0.72; n = 189) from the training data set. The signature stratified patients into high- and low-risk groups with significantly different survival (median 27.9 vs. 55.2 months, log-rank test, p < 0.001) in the training data set, and its risk stratification ability were validated in the test data set (median 47.4 vs. 84.4 months, log-rank test, p = 0.03) and an independent data set (median 31.0 vs. 46.0 months, log-rank test, p = 0.01). Multivariable Cox regression analysis showed that the signature was an independent prognostic factor. And the signature was proved to have a better survival prediction power than tumor-node-metastasis (TNM) stage (AUC signature = 0.72/0.64/0.62 vs. AUC TNM = 0.65/0.61/0.61; p < 0.05). Moreover, we validated the expression of these prognostic genes from the PCG-miRNA signature in Huh-7 cell by real-time polymerase chain reaction. In conclusion, we found a signature that can predict survival of HCC patients and serve as a prognostic marker for HCC.