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PubMed1993

Sequence evolution of mitochondrial tRNA genes and deep-branch animal phylogenetics.

Mitochondrial DNA sequences are often used to construct molecular phylogenetic trees among closely related animals. In order to examine the usefulness of mtDNA sequences for deep-branch phylogenetics, genes in previously reported mtDNA sequences were analyzed among several animals that diverged 20-600 million years ago. Unambiguous alignment was achieved for stem-forming regions of mitochondrial tRNA genes by virtue of their conservative secondary structures. Sequences derived from stem parts of the mitochondrial tRNA genes appeared to accumulate much variation linearly for a long period of time: nearly 100 Myr for transition differences and more than 350 Myr for transversion differences. This characteristic could be attributed, in part, to the structural variability of mitochondrial tRNAs, which have fewer restrictions on their tertiary structure than do nonmitochondrial tRNAs. The tRNA sequence data served to reconstruct a well-established phylogeny of the animals with 100% bootstrap probabilities by both maximum parsimony and neighbor-joining methods. By contrast, mitochondrial protein genes coding for cytochrome b and cytochrome oxidase subunit I did not reconstruct the established phylogeny or did so only weakly, although a variety of fractions of the protein gene sequences were subjected to tree-building. This discouraging phylogenetic performance of mitochondrial protein genes, especially with respect to branches originating over 300 Myr ago, was not simply due to high randomness in the data. It may have been due to the relative susceptibility of the protein genes to natural selection as compared with the stem parts of mitochondrial tRNA genes. On the basis of these results, it is proposed that mitochondrial tRNA genes may be useful in resolving deep branches in animal phylogenies with divergences that occurred some hundreds of Myr ago. For this purpose, we designed a set of primers with which mtDNA fragments encompassing clustered tRNA genes were successfully amplified from various vertebrates by the polymerase chain reaction.

Animals↗

PubMed2026

Translating functional molecular knowledge into crop-breeding success.

Historical plant breeding, which optimizes phenotypes through selective crossing guided by phenotypic evaluation and molecular markers, is limited by evolutionary constraints that hinder rapid crop improvement. A new paradigm, precision breeding, circumvents these limitations by targeting genetic variants through functional molecular knowledge. To generate this knowledge at scale, sequence-based deep learning leverages high-quality genome sequence data to predict variant effects at base-pair resolution. When linked to agronomically important traits, these predictions enable breeders to prioritize variants for precision selection or editing. Although it is still in the early stages of development, we foresee three key applications for this approach: introgressing genes from distant breeding pools, purging deleterious mutations and designing new plant ideotypes. Looking ahead, refined computational models will facilitate targeted editing and the systematic redesign of complex physiological processes to address emerging breeding goals under shifting environmental conditions.

Crops, Agricultural↗

PubMed1988

N-terminal amino acid sequence of the deep-sea tube worm haemoglobin remarkably resembles that of annelid haemoglobin.

The deep-sea giant tube worm Lamellibrachia, belonging to the phylum Vestimentifera, contains two extracellular haemoglobins, an Mr 3,000,000 haemoglobin and an Mr 440,000 haemoglobin. The former has a hexagonal bilayer structure and consists of six polypeptide chains (AI-VI); a study of its haem content shows that not all of the chains contain haem. The Mr 440,000 haemoglobin consists of four haem-containing chains (BI-IV). We isolated most of the chains by reverse-phase chromatography and determined the amino acid sequences of the 21-45 N-terminal residues. Eight chains (AI-IV and BI-IV) showed significant homology with haem-containing chains of annelid giant haemoglobin. The highest homology was found between Lamellibrachia chain AI and Tylorrhynchus chain I; surprisingly, 18 out of the 20 N-terminal residues are identical. On the other hand, chain AV, with an unusual Mr of 32,000, showed a rather different sequence and is likely to be a non-haem chain which might act as a linker protein in the assembly of the haem-containing chains. From these results, we conclude that the tube worm Mr 3,000,000 haemoglobin is highly homologous with annelid haemoglobin.

Amino Acid Sequence↗

PubMed1990

Nucleotide sequence and expression of a deep-sea ribulose-1,5-bisphosphate carboxylase gene cloned from a chemoautotrophic bacterial endosymbiont.

The gene coding for ribulose-1,5-bisphosphate carboxylase [RuBisCO; 3-phospho-D-glycerate carboxy-lyase (dimerizing), EC 4.1.1.39] was cloned from a sulfur-oxidizing chemoautotrophic bacterium that resides as an endosymbiont within the gill tissues of Alvinoconcha hessleri, a gastropod inhabiting deep-sea hydrothermal vents. Nucleotide sequence analysis of the cloned fragment demonstrated that the genes encoding the large (RbcL) and small (RbcS) subunits of the symbiont RuBisCO were organized similarly to the RuBisCO operons of free-living photo- and chemoautotrophic prokaryotes. The symbiont rbcL gene shared the highest degree of nucleotide sequence identity with the cyanobacterium Anabaena (69%) while the rbcS nucleotide sequence shared 61% identity with that of the green alga Chlamydomonas reinhardtii. Comparison with a 153-nucleotide partial rbcL sequence from a symbiont of the bivalve Solemya reidi indicated that the two symbiont sequences shared 85% sequence identity at the nucleotide level and 93% at the amino acid level, suggesting a relatively recent common origin. Escherichia coli transformed with a plasmid carrying the RuBisCO operon of the gastropod symbiont in the proper orientation for transcription from the plasmid lac promoter expressed catalytically active RuBisCO. The presence of enzyme activity suggests the proper assembly of the subunits of this deep-sea RuBisCO into the holoenzyme.

Amino Acid Sequence↗

PubMed2026

Flexible use of conserved motifs constrains genome access in cell type evolution.

Cell types can be organized into related families, but the regulatory mechanisms that define and maintain these families across deep evolutionary time remain unknown. Here, combining single-nucleus multi-omic sequencing with deep learning to analyse the accessible genomes of two groups of vastly divergent animals including flatworms and vertebrates, we find that hundreds of accessibility-dictating sequence motifs partition into distinct yet conserved sets, or 'vocabularies', each associated with a specific cell type family. However, combinatorial relationships among these motifs preferred by individual cell types are largely species specific. Deep-learning models trained on one species accurately predict family-level chromatin accessibility in distantly related species, albeit frequently rely on different motifs from shared vocabularies to reach convergent predictions. By contrast, models trained on individual cell types within a family lose cross-species predictive power, indicating that the regulatory syntax governing cell type-level identity evolves rapidly. We propose a 'collective maintenance' model in which motif vocabularies defining cell type families are evolutionarily stable, while recombination of these motifs generates cell type-specific regulatory programmes. This suggests that family identity is maintained collectively by large, conserved pools of regulatory factors, analogous to the logic of developmental homology, where character identity persists through network-level conservation despite extensive rewiring.

Journal Article↗

PubMedDate not supplied

Impact of externally attached loggers on the diving behaviour of the king penguin.

The impact of relatively small externally attached time series recorders on some foraging parameters of seabirds was investigated during the austral summer of 1995 by monitoring the diving behaviour of 10 free-ranging king penguins (Aptenodytes patagonicus) over one foraging trip. Time-depth recorders were implanted in the abdominal cavities of the birds, and half of the animals also had dummy loggers attached on their backs. Although most of the diving behaviour was not significantly affected by the external loggers (P>0.05), the birds with externally attached loggers performed almost twice as many shallow dives, between 0 and 10 m depth, as the birds without external loggers. These shallow dives interrupted more frequently the deep-diving sequences in the case of birds with external loggers (percentage of deep dives followed by deep dives: 46% for birds with implants only vs. 26% for birds with an external attachment). Finally, the distribution pattern of the postdive durations plotted against the hour of the day was more heterogeneous for the birds with an external package. In addition, these penguins had extended surfacing times between two deep dives compared to birds without external attachments (P<0.0001). These results suggest the existence of an extra energy cost induced by externally attached loggers.

Animals↗

PubMed2025

The Use of Next-Generation Sequencing in Personalized Medicine.

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.

Humans↗

PubMed2026

Identification of Freezing-Responsive microRNAs and Their Targets in Chinese Jujube by Small RNA and Degradome Sequencing.

The jujube tree fruit remains a primary fruit in northern China, yet its geographical distribution and yield are significantly constrained by freezing stress during winter. Numerous studies have highlighted the pivotal regulatory function of microRNAs (miRNAs) in plant responses to low-temperature stress. Nevertheless, the specific miRNAs involved in the response to low temperatures and their associated gene networks in Ziziphus jujuba Mill are not well understood. In this investigation, we utilized high-throughput sequencing to analyze small RNA libraries from branches subjected to temperatures of 4 °C and -30 °C. Our analysis identified a total of 342 miRNAs, comprising 123 known miRNAs and 219 novel miRNAs. The differential expression analysis revealed that under low-temperature conditions, 177 miRNAs underwent significant changes. Among them, specific upregulation of miR319 in the less cold-resistant variety and miR6483 in sensitive variety was observed. By employing degradome sequencing, we identified a total of 1551 target genes corresponding to 3059 unique miRNA target interaction pairs involving 299 miRNAs. Functional analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways indicated that these target genes are primarily associated with transcriptional regulation, metabolic pathways, and genetic information processing. Through a comprehensive analysis, we pinpointed 11 genes corresponding to 9 miRNAs that are implicated in jujube tree cold stress, and 7 target genes of 7 miRNAs were confirmed by 5'-RACE analysis. These miRNAs are likely to exert crucial regulatory functions in the context of jujube tree cold stress. This study is the first to systematically identify miRNAs and their target genes in the response of Ziziphus jujuba Mill to low-temperature stress, which provides important resources for in-depth analysis of the molecular mechanism of jujube tree cold resistance and for cold-resistant breeding.

Ziziphus↗

PubMed2024

Microbial diversity and metabolic pathways linked to benzene degradation in petrochemical-polluted groundwater.

The rapid advance in shotgun metagenome sequencing has enabled us to identify uncultivated functional microorganisms in polluted environments. While aerobic petrochemical-degrading pathways have been extensively studied, the anaerobic mechanisms remain less explored. Here, we conducted a study at a petrochemical-polluted groundwater site in Henan Province, Central China. A total of twelve groundwater monitoring wells were installed to collect groundwater samples. Benzene appeared to be the predominant pollutant, detected in 10 out of 12 samples, with concentrations ranging from 1.4 μg/L to 5,280 μg/L. Due to the low aquifer permeability, pollutant migration occurred slowly, resulting in relatively low benzene concentrations downstream within the heavily polluted area. Deep metagenome sequencing revealed Proteobacteria as the dominant phylum, accounting for over 63 % of total abundances. Microbial α-diversity was low in heavily polluted samples, with community compositions substantially differing from those in lightly polluted samples. dmpK encoding the phenol/toluene 2-monooxygenase was detected across all samples, while the dioxygenase bedC1 was not detected, suggesting that aerobic benzene degradation might occur through monooxygenation. Sequence assembly and binning yielded 350 high-quality metagenome-assembled genomes (MAGs), with 30 MAGs harboring functional genes associated with aerobic or anaerobic benzene degradation. About 80 % of MAGs harboring functional genes associated with anaerobic benzene degradation remained taxonomically unclassified at the genus level, suggesting that our current database coverage of anaerobic benzene-degrading microorganisms is very limited. Furthermore, two genes integral to anaerobic benzene metabolism, i.e, benzoyl-CoA reductase (bamB) and glutaryl-CoA dehydrogenase (acd), were not annotated by metagenome functional analyses but were identified within the MAGs, signifying the importance of integrating both contig-based and MAG-based approaches. Together, our efforts of functional annotation and metagenome binning generate a robust blueprint of microbial functional potentials in petrochemical-polluted groundwater, which is crucial for designing proficient bioremediation strategies.

Groundwater↗

PubMed2026

HyLnc: a hybrid deep learning and feature-based approach for long non-coding RNA prediction.

Long non-coding RNAs (lncRNAs) play important roles in gene regulation, development and disease, yet accurate identification of lncRNAs from transcriptomic data remains a major computational challenge. Existing methods often rely either on handcrafted sequence features or deep learning approaches, each with their inherent limitations in capturing the full complexity of RNA sequences. In this study, we proposed HyLnc, a computational framework that integrates transformer-based contextual embeddings with biologically meaningful sequence features for improved lncRNA prediction. A custom BERT-based model was first pre-trained on a large corpus of metazoan RNA sequences using a masked language modelling strategy to learn contextual nucleotide dependencies. The model was subsequently fine-tuned on curated datasets of lncRNAs and protein-coding transcripts and 256-dimensional deep sequence embeddings were extracted. Parallelly, 348 handcrafted features, including ORF characteristics, untranslated region (UTR) properties, nucleotide composition and Fickett scores, were computed. A multi-stage feature selection strategy was applied to identify the most informative features, resulting in optimized hybrid feature sets. Multiple machine learning classifiers were evaluated, with the RF model achieving the best performance. The proposed framework attained an accuracy of 91.30%, F1-score of 91.23% and MCC of 82.60 on an independent validation dataset, outperforming several existing lncRNA prediction tools. Thus, HyLnc demonstrates that integrating deep contextual representations with biologically interpretable features enhances lncRNA prediction. This approach provides a robust and scalable solution for large-scale transcriptome annotation and can be extended to other sequence-based prediction.

RNA, Long Noncoding↗

PubMed2001

Molecular phylogenetics of Australo-Papuan possums and gliders (family Petauridae).

Phylogenetic relationships within the possums of the family Petauridae, including their affinities with the family Pseudocheiridae, were inferred from DNA sequences obtained for the mitochondrial ND2 gene (1040 bp) combined with previously published partial 12S rDNA sequences. Short, deep internodes characterize some of the divergences obtained. The robustness of these nodes was assessed by several methods such as exclusion of taxa and partitioning of characters. In all analyses a monophyletic Pseudocheiridae was evident, whereas a monophyletic Petauridae was not as well supported. Within the Petauridae, Gymnobelideus was more closely related to Dactylopsila-Dactylonax than to Petaurus. This supports the results obtained from microcomplement fixation of albumin and DNA-DNA hybridization studies but conflicts with morphological data.

Animals↗

PubMed2001

DNA footprints of European hedgehogs, Erinaceus europaeus and E. concolor: Pleistocene refugia, postglacial expansion and colonization routes.

European hedgehogs, Erinaceus europaeus and E. concolor, are among the many European plant and animal taxa that have been subjected to cyclical restriction to glacial refugia and interglacial expansion. An analysis of 95 mitotypes, comprising partial cytochrome b and control region sequences, shows deep divergence between the two hedgehog species. Three europaeus and two concolor clades are clearly identified and are consistent with previously identified refugia for Europe: the Iberian peninsula, Italy, and the Balkans. The degree of mitochondrial divergence among these clades suggests pre-Pleistocene separation of the refugial populations. In contrast, analysis of two nuclear introns clearly separates the two concolor clades, as in the mitochondrial data, but cannot discriminate the three europaeus clades. This discrepancy between nuclear and mitochondrial data is attributed to historical differences in the refugial population size of europaeus and concolor. The geographical distribution of mitotypes is analysed using nested clade analysis. This method, by including unobserved ('missing') mitotypes, can identify mitotype groupings that remain undetected in conventional analyses. However, the application of nested clade analysis to the study of refugial populations may be hampered by such factors as the loss of haplotypes from the refugial areas by repeated contractions of the population and the recent time scale of colonization relative to mutation rate.

Animals↗

PubMed1992

Transfer RNA genes from the hyperthermophilic Archaeon, Methanopyrus kandleri.

Genes encoding the Leu (GAG), Ser (UGA), Gln (UUG) and Lys (UUU) tRNAs have been cloned and sequenced from the deep sea hyperthermophilic Archaeon, Methanopyrus kandleri. Sequences conforming to the TATA box element established for methanogen promoters are located upstream of the tRNA(Gln) and tRNA(Lys) genes. All four of the tRNA genes appear to encode the 3' terminal CCA residues of the mature tRNA. These methanogen tRNAs are predicted to contain most, but not all, invariant residues and are characterized by a high level of G + C base pairing, consistent with the 98 degrees C optimum growth temperature of M. kandleri.

Base Sequence↗

PubMed1988

Molecular evolution of the 5'-terminal domain of large-subunit rRNA from lower eukaryotes. A broad phylogeny covering photosynthetic and non-photosynthetic protists.

This paper summarizes the present status of an analysis of protist phylogeny using rapid partial sequencing of 28S rRNA. Data from 12 protistan phyla are now available and have been used to construct a tentative dendrogram based on a distance matrix method. The tree is robust and has considerable internal consistency. The following salient points are observed: a number of flagellate groups (particularly Euglenozoa) emerge very early among eukaryotes, whereas ciliates and dinoflagellates emerge late, suggesting that some characteristics that had been considered as primitive may in fact be derived. Both chlorophytic and chromophytic photosynthetic protists emerge very late in the tree, close to the Metazoa-Metaphyta-Fungi radiation, suggesting relatively late occurrence of the photosynthetic symbiosis. Taxonomic and phylogenetic information is also obtained within a phylum where rRNA of enough species are sequenced. A deep trichotomy is thus observed within the ciliates. The data are discussed with respect to classical protist phylogenies.

Animals↗

PubMed2025

A deep metagenomic atlas of Qinghai-Xizang Plateau lakes reveals their microbial diversity and salinity adaptation mechanisms.

The Qinghai-Xizang Plateau (QXP), harboring the planet's highest density of plateau lakes, offers an exceptional biogeographic environment for studying extremophilic microbial communities and their adaptation to salinity. Through deep metagenomic sequencing, we construct the Qinghai-Xizang Lake Sediment Genome (QXLSG) catalog, a high-resolution genomic catalog comprising 5,866 metagenome-assembled genomes (MAGs), 58.16 million non-redundant protein encoding genes, and 19,008 biosynthetic gene clusters. Notably, 80.78% of the 2,742 species-level MAGs represent undescribed taxa, significantly expanding the known microbial diversity. Salinity emerges as the primary environmental factor influencing microbial community. Functional annotation highlights that the "salt-out" strategy, particularly the uptake of glycine betaine, is the main mechanism for salinity tolerance. This strategy is prevalent in both hypersaline lake communities and the dominant microbial phyla. Overall, this study provides a crucial genetic resource for future bioprospecting and deepens our understanding of the fundamental mechanisms of microbial adaptation to extreme saline environments.

Lakes↗

PubMed2025

Phyllosphere microbiomes in grassland plants harbor a vast reservoir of novel antimicrobial peptides and biosynthetic diversity.

INTRODUCTION: The phyllosphere microorganisms colonizing plant surface harbor capacities to synthesize diverse specialized metabolites that mediate communication and interactions with environment and host. However, most known metabolites are derived from a few culturable microorganisms, and the genomic diversity and biosynthetic potential of the vast majority of bacteria associated with plants remain largely unexplored. OBJECTIVES: Here, we aim to explore the genome architecture, biosynthetic ability, and host specific adaptability of grassland ecosystems, uncovering new perspectives on grassland phyllosphere microbial resources. METHODS: We employed ultra-deep metagenomic sequencing, functional analysis, host-associated characterization, and bioactivity assays to explore the phyllosphere microbiome across 221 grassland plant samples representing 45 families. This approach revealed host preference in biosynthetic gene clusters (BGCs) and validated the antimicrobial efficacy of phyllosphere-derived antimicrobial peptides (AMPs). RESULTS: Grassland plant phyllosphere microbiomes encode diverse BGCs. We identified 885,396 potential AMPs from over 68 million non-redundant gene sequences. Then, we reconstructed hundreds of near-complete genomes from phyllosphere metagenomes, and 32.61 % of reconstructed genomes were identified as unclassified genomes, primarily within Pseudomonadota, Actinomycetota, Bacillota and Bacteroidota phyla. Of the near-complete genomes, 91.97 % of the BGCs and 99.76 % of the identified AMPs were previously uncharacterized. Host phylogenetic analysis revealed functional divergence. Poaceae-associated Pseudomonas genomes contain an average of 28 BGCs, significantly higher than those in Asteraceae-associated genomes (mean = 14.76, P = 0.033). Similarly, Poaceae-associated Pantoea genomes carried an average of 9 BGCs, exhibiting significant enrichment compared to genomes from Asteraceae (mean = 7.13, P = 6.1e-05), Lamiaceae (mean = 7, P = 0.015), Ranunculaceae (mean = 8.22, P = 0.0053), and Rosaceae (mean = 7.75, P = 0.00069). ParaFit analyses further confirmed that host phylogeny significantly structures microbial functional repertoires, with intra-family hosts sharing more KEGG pathways than inter-family hosts. These results suggest that host evolutionary relationships are associated with metabolic specialization in phyllosphere microbiomes. All 13 AMPs synthesized via solid-phase peptide synthesis demonstrated antimicrobial activity, inhibiting the growth of at least one tested bacterial strain. CONCLUSION: This study demonstrates the promise of grassland plant phyllosphere microbiome as a rich source for novel antimicrobial agents.

Antimicrobial Peptides↗

PubMed2024

NovoBoard: A Comprehensive Framework for Evaluating the False Discovery Rate and Accuracy of De Novo Peptide Sequencing.

De novo peptide sequencing is one of the most fundamental research areas in mass spectrometry-based proteomics. Many methods have often been evaluated using a couple of simple metrics that do not fully reflect their overall performance. Moreover, there has not been an established method to estimate the false discovery rate (FDR) of de novo peptide-spectrum matches. Here we propose NovoBoard, a comprehensive framework to evaluate the performance of de novo peptide-sequencing methods. The framework consists of diverse benchmark datasets (including tryptic, nontryptic, immunopeptidomics, and different species) and a standard set of accuracy metrics to evaluate the fragment ions, amino acids, and peptides of the de novo results. More importantly, a new approach is designed to evaluate de novo peptide-sequencing methods on target-decoy spectra and to estimate and validate their FDRs. Our FDR estimation provides valuable information to assess the reliability of new peptides identified by de novo sequencing tools, especially when no ground-truth information is available to evaluate their accuracy. The FDR estimation can also be used to evaluate the capability of de novo peptide sequencing tools to distinguish between de novo peptide-spectrum matches and random matches. Our results thoroughly reveal the strengths and weaknesses of different de novo peptide-sequencing methods and how their performances depend on specific applications and the types of data.

Peptides↗

PubMed2026

A Robust, Self-Digestion-Resistant LysN with Superior Activity and Cleavage Fidelity for Advanced Proteomic Workflows.

LysN is a valuable protease in proteomics because it cleaves peptide bonds N-terminal to lysine, generating peptides with physicochemical properties complementary to those produced by LysC and trypsin. However, the broader adoption of LysN in proteomic workflows has been limited by the lack of commercially available enzymes that combine high activity, low missed-cleavage rates, and sufficient stability under practical sample-processing conditions. Here, we report the recombinant production and proteomic characterization of a self-digestion-resistant and highly active LysN from Shewanella loihica (SL-LysN). Using terminomics, we mapped the mature N- and C-termini of the enzyme and established the primary structure of the active protease. We further developed a high-density fermentation, refolding, and purification workflow to obtain highly purified recombinant SL-LysN. Biochemical and proteomic benchmarking showed that SL-LysN displayed 3.3-fold higher specific activity than commercial LysN and reduced missed cleavages by approximately 80%. Notably, SL-LysN retained high activity in the presence of 8 M urea or 1% SDS and showed strong resistance to autolysis, indicating exceptional robustness for proteomic sample preparation. In complex mammalian proteome digests, SL-LysN achieved >95% cleavage specificity and a missed-cleavage rate of only 5.9%. These features address a long-standing bottleneck in N-terminal proteolysis and establish SL-LysN as a high-performance enzymatic tool for advanced proteomic workflows, including deep protein sequencing, quantitative proteomics, terminomics, de novo sequencing and analyses requiring efficient digestion under denaturing conditions.

Shewanella↗