Group II intron-like reverse transcriptases function in double-strand break repair.

Bacteria encode reverse transcriptases (RTs) of unknown function that are closely related to group II intron-encoded RTs. We found that a Pseudomonas aeruginosa group II intron-like RT (G2L4 RT) with YIDD instead of YADD at its active site functions in DNA repair in its native host and when expressed in Escherichia coli. G2L4 RT has biochemical activities strikingly similar to those of human DNA repair polymerase Î¸ and uses them for translesion DNA synthesis and double-strand break repair (DSBR) via microhomology-mediated end-joining (MMEJ). We also found that a group II intron RT can function similarly in DNA repair, with reciprocal active-site substitutions showing isoleucine favors MMEJ and alanine favors primer extension in both enzymes. These DNA repair functions utilize conserved structural features of non-LTR-retroelement RTs, including human LINE-1 and other eukaryotic non-LTR-retrotransposon RTs, suggesting such enzymes may have inherent ability to function in DSBR in a wide range of organisms.

BRICseq Bridges Brain-wide Interregional Connectivity to Neural Activity and Gene Expression in Single Animals.

Comprehensive analysis of neuronal networks requires brain-wide measurement of connectivity, activity, and gene expression. Although high-throughput methods are available for mapping brain-wide activity and transcriptomes, comparable methods for mapping region-to-region connectivity remain slow and expensive because they require averaging across hundreds of brains. Here we describe BRICseq (brain-wide individual animal connectome sequencing), which leverages DNA barcoding and sequencing to map connectivity from single individuals in a few weeks and at low cost. Applying BRICseq to the mouse neocortex, we find that region-to-region connectivity provides a simple bridge relating transcriptome to activity: the spatial expression patterns of a few genes predict region-to-region connectivity, and connectivity predicts activity correlations. We also exploited BRICseq to map the mutant BTBR mouse brain, which lacks a corpus callosum, and recapitulated its known connectopathies. BRICseq allows individual laboratories to compare how age, sex, environment, genetics, and species affect neuronal wiring and to integrate these with functional activity and gene expression.

Global Trends in Marine Plankton Diversity across Kingdoms of Life.

The ocean is home to myriad small planktonic organisms that underpin the functioning of marine ecosystems. However, their spatial patterns of diversity and the underlying drivers remain poorly known, precluding projections of their responses to global changes. Here we investigate the latitudinal gradients and global predictors of plankton diversity across archaea, bacteria, eukaryotes, and major virus clades using both molecular and imaging data from Tara Oceans. We show a decline of diversity for most planktonic groups toward the poles, mainly driven by decreasing ocean temperatures. Projections into the future suggest that severe warming of the surface ocean by the end of the 21st century could lead to tropicalization of the diversity of most planktonic groups in temperate and polar regions. These changes may have multiple consequences for marine ecosystem functioning and services and are expected to be particularly significant in key areas for carbon sequestration, fisheries, and marine conservation. VIDEO ABSTRACT.

Tempo and Mode of Genome Evolution in the Budding Yeast Subphylum.

Budding yeasts (subphylum Saccharomycotina) are found in every biome and are as genetically diverse as plants or animals. To understand budding yeast evolution, we analyzed the genomes of 332 yeast species, including 220 newly sequenced ones, which represent nearly one-third of all known budding yeast diversity. Here, we establish a robust genus-level phylogeny comprising 12 major clades, infer the timescale of diversification from the Devonian period to the present, quantify horizontal gene transfer (HGT), and reconstruct the evolution of 45 metabolic traits and the metabolic toolkit of the budding yeast common ancestor (BYCA). We infer that BYCA was metabolically complex and chronicle the tempo and mode of genomic and phenotypic evolution across the subphylum, which is characterized by very low HGT levels and widespread losses of traits and the genes that control them. More generally, our results argue that reductive evolution is a major mode of evolutionary diversification.

ALL-tRNAseq enables robust tRNA profiling in tissue samples.

Transfer RNAs (tRNAs) are small adaptor RNAs essential for mRNA translation. Alterations in the cellular tRNA population can directly affect mRNA decoding rates and translational efficiency during cancer development and progression. To evaluate changes in the composition of the tRNA pool, multiple sequencing approaches have been developed to overcome reverse transcription blocks caused by the stable structures of these molecules and their numerous base modifications. However, it remains unclear whether current sequencing protocols faithfully capture tRNAs existing in cells or tissues. This is specifically challenging for clinical tissue samples that often present variable RNA qualities. For this reason, we developed ALL-tRNAseq, which combines the highly processive MarathonRT and RNA demethylation for the robust assessment of tRNA expression, together with a randomized adapter ligation strategy prior to reverse transcription to assess tRNA fragmentation levels in both cell lines and tissues. Incorporation of tRNA fragments not only informed on sample integrity but also significantly improved tRNA profiling of tissue samples. Our data showed that our profiling strategy effectively improves classification of oncogenic signatures in glioblastoma and diffuse large B-cell lymphoma tissues, particularly for samples presenting higher levels of RNA fragmentation, further highlighting the utility of ALL-tRNAseq for translational research.

Genome-wide RNA structure changes during human neurogenesis modulate gene regulatory networks.

The distribution, dynamics, and function of RNA structures in human development are under-explored. Here, we systematically assayed RNA structural dynamics and their relationship with gene expression, translation, and decay during human neurogenesis. We observed that the human ESC transcriptome is globally more structurally accessible than differentiated cells and undergoes extensive RNA structure changes, particularly in the 3' UTR. Additionally, RNA structure changes during differentiation are associated with translation and decay. We observed that RBP and miRNA binding is associated with RNA structural changes during early neuronal differentiation, and splicing is associated during later neuronal differentiation. Furthermore, our analysis suggests that RBPs are major factors in structure remodeling and co-regulate additional RBPs and miRNAs through structure. We demonstrated an example of this by showing that PUM2-induced structure changes on LIN28A enable miR-30 binding. This study deepens our understanding of the widespread and complex role of RNA-based gene regulation during human development.

METTL1 Promotes let-7 MicroRNA Processing via m7G Methylation.

7-methylguanosine (m7G) is present at mRNA caps and at defined internal positions within tRNAs and rRNAs. However, its detection within low-abundance mRNAs and microRNAs (miRNAs) has been hampered by a lack of sensitive detection strategies. Here, we adapt a chemical reactivity assay to detect internal m7G in miRNAs. Using this technique (Borohydride Reduction sequencing [BoRed-seq]) alongside RNA immunoprecipitation, we identify m7G within a subset of miRNAs that inhibit cell migration. We show that the METTL1 methyltransferase mediates m7G methylation within miRNAs and that this enzyme regulates cell migration via its catalytic activity. Using refined mass spectrometry methods, we map m7G to a single guanosine within the let-7e-5p miRNA. We show that METTL1-mediated methylation augments let-7 miRNA processing by disrupting an inhibitory secondary structure within the primary miRNA transcript (pri-miRNA). These results identify METTL1-dependent N7-methylation of guanosine as a new RNA modification pathway that regulates miRNA structure, biogenesis, and cell migration.

Future of DNA-based insect monitoring.

Insects are crucial for ecosystem health but climate change and pesticide use are driving massive insect decline. To mitigate this loss, we need new and effective monitoring techniques. Over the past decade there has been a shift to DNA-based techniques. We describe key emerging techniques for sample collection. We suggest that the selection of tools should be broadened, and that DNA-based insect monitoring data need to be integrated more rapidly into policymaking. We argue that there are four key areas for advancement, including the generation of more complete DNA barcode databases to interpret molecular data, standardisation of molecular methods, scaling up of monitoring efforts, and integrating molecular tools with other technologies that allow continuous, passive monitoring based on images and/or laser imaging, detection, and ranging (LIDAR).

Chemical manipulation of m1A mediates its detection in human tRNA.

N 1-methyl adenosine (m1A) is a widespread RNA modification present in tRNA, rRNA, and mRNA. m1A modification sites in tRNAs are evolutionarily conserved and its formation on tRNA is catalyzed by methyltransferase TRMT61A and TRMT6 complex. m1A promotes translation initiation and elongation. Due to its positive charge under physiological conditions, m1A can notably modulate RNA structure. It also blocks Watson-Crick-Franklin base-pairing and causes mutation and truncation during reverse transcription. Several misincorporation-based high-throughput sequencing methods have been developed to sequence m1A. In this study, we introduce a reduction-based m1A sequencing (red-m1A-seq). We report that NaBH4 reduction of m1A can improve the mutation and readthrough rates using commercially available RT enzymes to give a better positive signature, while alkaline-catalyzed Dimroth rearrangement can efficiently convert m1A to m6A to provide good controls, allowing the detection of m1A with higher sensitivity and accuracy. We applied red-m1A-seq to sequence human small RNA, and we not only detected all the previously reported tRNA m1A sites, but also new m1A sites in mt-tRNAAsn-GTT and 5.8S rRNA.

PKR Senses Nuclear and Mitochondrial Signals by Interacting with Endogenous Double-Stranded RNAs.

Protein kinase RNA-activated (PKR) induces immune response by sensing viral double-stranded RNAs (dsRNAs). However, growing evidence suggests that PKR can also be activated by endogenously expressed dsRNAs. Here, we capture these dsRNAs by formaldehyde-mediated crosslinking and immunoprecipitation sequencing and find that various noncoding RNAs interact with PKR. Surprisingly, the majority of the PKR-interacting RNA repertoire is occupied by mitochondrial RNAs (mtRNAs). MtRNAs can form intermolecular dsRNAs owing to bidirectional transcription of the mitochondrial genome and regulate PKR and eIF2α phosphorylation to control cell signaling and translation. Moreover, PKR activation by mtRNAs is counteracted by PKR phosphatases, disruption of which causes apoptosis from PKR overactivation even in uninfected cells. Our work unveils dynamic regulation of PKR even without infection and establishes PKR as a sensor for nuclear and mitochondrial signaling cues in regulating cellular metabolism.

Diversity of plant DNA in stool is linked to dietary quality, age, and household income.

Eating a varied diet is a central tenet of good nutrition. Here, we develop a molecular tool to quantify human dietary plant diversity by applying DNA metabarcoding with the chloroplast trnL-P6 marker to 1,029 fecal samples from 324 participants across two interventional feeding studies and three observational cohorts. The number of plant taxa per sample (plant metabarcoding richness or pMR) correlated with recorded intakes in interventional diets and with indices calculated from a food frequency questionnaire in typical diets (ρ = 0.40 to 0.63). In adolescents unable to collect validated dietary survey data, trnL metabarcoding detected 111 plant taxa, with 86 consumed by more than one individual and four (wheat, chocolate, corn, and potato family) consumed by >70% of individuals. Adolescent pMR was associated with age and household income, replicating prior epidemiologic findings. Overall, trnL metabarcoding promises an objective and accurate measure of the number and types of plants consumed that is applicable to diverse human populations.

IMperm: a fast and comprehensive IMmune Paired-End Reads Merger for sequencing data.

The adaptive immune receptor repertoire (AIRR), consisting of T- and B-cell receptors, is the core component of the immune system. The AIRR sequencing is commonly used in cancer immunotherapy and minimal residual disease (MRD) detection of leukemia and lymphoma. The AIRR is captured by primers and sequenced to yield paired-end (PE) reads. The PE reads could be merged into one sequence by the overlapped region between them. However, the wide range of AIRR data raises the difficulty, so a special tool is required. We developed a software package for IMmune PE reads merger of sequencing data, named IMperm. We used the k-mer-and-vote strategy to pin down the overlapped region rapidly. IMperm could handle all types of PE reads, eliminate adapter contamination and successfully merge low-quality and minor/non-overlapping reads. Compared with existing tools, IMperm performed better in both simulated and sequencing data. Notably, IMperm was well suited to processing the data of MRD detection in leukemia and lymphoma and detected 19 novel MRD clones in 14 patients with leukemia from previously published data. Additionally, IMperm can handle PE reads from other sources, and we demonstrated its effectiveness on two genomic and one cell-free deoxyribonucleic acid datasets. IMperm is implemented in the C programming language and consumes little runtime and memory. It is freely available at https://github.com/zhangwei2015/IMperm.

Analyzing RNA posttranscriptional modifications to decipher the epitranscriptomic code.

The discovery of RNA silencing has revealed that non-protein-coding sequences (ncRNAs) can cover essential roles in regulatory networks and their malfunction may result in severe consequences on human health. These findings have prompted a general reassessment of the significance of RNA as a key player in cellular processes. This reassessment, however, will not be complete without a greater understanding of the distribution and function of the over 170 variants of the canonical ribonucleotides, which contribute to the breathtaking structural diversity of natural RNA. This review surveys the analytical approaches employed for the identification, characterization, and detection of RNA posttranscriptional modifications (rPTMs). The merits of analyzing individual units after exhaustive hydrolysis of the initial biopolymer are outlined together with those of identifying their position in the sequence of parent strands. Approaches based on next generation sequencing and mass spectrometry technologies are covered in depth to provide a comprehensive view of their respective merits. Deciphering the epitranscriptomic code will require not only mapping the location of rPTMs in the various classes of RNAs, but also assessing the variations of expression levels under different experimental conditions. The fact that no individual platform is currently capable of meeting all such demands implies that it will be essential to capitalize on complementary approaches to obtain the desired information. For this reason, the review strived to cover the broadest possible range of techniques to provide readers with the fundamental elements necessary to make informed choices and design the most effective possible strategy to accomplish the task at hand.

Systematic Investigation of Transcription Factor Activity in the Context of Chromatin Using Massively Parallel Binding and Expression Assays.

Precise gene expression patterns are established by transcription factor (TFs) binding to regulatory sequences. While these events occur in the context of chromatin, our understanding of how TF-nucleosome interplay affects gene expression is highly limited. Here, we present an assay for high-resolution measurements of both DNA occupancy and gene expression on large-scale libraries of systematically designed regulatory sequences. Our assay reveals occupancy patterns at the single-cell level. It provides an accurate quantification of the fraction of the population bound by a nucleosome and captures distinct, even adjacent, TF binding events. By applying this assay to over 1,500 promoter variants in yeast, we reveal pronounced differences in the dependency of TF activity on chromatin and classify TFs by their differential capacity to alter chromatin and promote expression. We further demonstrate how different regulatory sequences give rise to nucleosome-mediated TF collaborations that quantitatively account for the resulting expression.

Single-base resolution quantitative genome methylation analysis in the model bacterium Helicobacter pylori by enzymatic methyl sequencing (EM-Seq) reveals influence of strain, growth phase, and methyl homeostasis.

BACKGROUND: Bacterial epigenetics is a rapidly expanding research field. DNA methylation by diverse bacterial methyltransferases (MTases) contributes to genomic integrity and replication, and many recent studies extended MTase function also to global transcript regulation and phenotypic variation. Helicobacter pylori is currently one of those bacterial species which possess the highest number and the most variably expressed set of DNA MTases. Next-generation sequencing technologies can directly detect DNA base methylation. However, they still have limitations in their quantitative and qualitative performance, in particular for cytosine methylation. RESULTS: As a complementing approach, we used enzymatic methyl sequencing (EM-Seq), a technology recently established that has not yet been fully evaluated for bacteria. Thereby, we assessed quantitatively, at single-base resolution, whole genome cytosine methylation for all methylated cytosine motifs in two different H. pylori strains and isogenic MTase mutants. EM-Seq reliably detected both m5C and m4C methylation. We demonstrated that three different active cytosine MTases in H. pylori provide considerably different levels of average genome-wide single-base methylation, in contrast to isogenic mutants which completely lost specific motif methylation. We found that strain identity and changed environmental conditions, such as growth phase and interference with methyl donor homeostasis, significantly influenced quantitative global and local genome-wide methylation in H. pylori at specific motifs. We also identified significantly hyper- or hypo-methylated cytosines, partially linked to overlapping MTase target motifs. Notably, we revealed differentially methylated cytosines in genome-wide coding regions under conditions of methionine depletion, which can be linked to transcript regulation. CONCLUSIONS: This study offers new knowledge on H. pylori global and local genome-wide methylation and establishes EM-Seq for quantitative single-site resolution analyses of bacterial cytosine methylation.

Taxanorm: a novel taxa-specific normalization approach for microbiome data.

BACKGROUND: In high-throughput sequencing studies, sequencing depth, which quantifies the total number of reads, varies across samples. Unequal sequencing depth can obscure true biological signals of interest and prevent direct comparisons between samples. To remove variability due to differential sequencing depth, taxa counts are usually normalized before downstream analysis. However, most existing normalization methods scale counts using size factors that are sample specific but not taxa specific, which can result in over- or under-correction for some taxa. RESULTS: We developed TaxaNorm, a novel normalization method based on a zero-inflated negative binomial model. This method assumes the effects of sequencing depth on mean and dispersion vary across taxa. Incorporating the zero-inflation part can better capture the nature of microbiome data. We also propose two corresponding diagnosis tests on the varying sequencing depth effect for validation. We find that TaxaNorm achieves comparable performance to existing methods in most simulation scenarios in downstream analysis and reaches a higher power for some cases. Specifically, it balances power and false discovery control well. When applying the method in a real dataset, TaxaNorm has improved performance when correcting technical bias. CONCLUSION: TaxaNorm both sample- and taxon- specific bias by introducing an appropriate regression framework in the microbiome data, which aids in data interpretation and visualization. The 'TaxaNorm' R package is freely available through the CRAN repository https://CRAN.R-project.org/package=TaxaNorm and the source code can be downloaded at https://github.com/wangziyue57/TaxaNorm .

Still water run deep: Therapeutic TP effect of ucMSC-Ex via regulating mTOR to enhance autophagy.

Our previous study confirmed that umbilical cord mesenchymal stem cells-exosomes (ucMSC-Ex) inhibit apoptosis of pancreatic acinar cells to exert protective effects. However, the relationship between apoptosis and autophagy in traumatic pancreatitis (TP) has rarely been reported. We dissected the transcriptomics after pancreatic trauma and ucMSC-Ex therapy by high-throughput sequencing. Additionally, we used rapamycin and MHY1485 to regulate mTOR. HE, inflammatory factors and pancreatic enzymatic assays were used to comprehensively determine the local versus systemic injury level, fluorescence staining and electron microscopy were used to detect the effect of autophagy, and observe the expression levels of autophagy-related markers at the gene and protein levels. High-throughput sequencing identified that autophagy played a crucial role in the pathophysiological process of TP and ucMSC-Ex therapy. The results of electron microscopy, immunofluorescence staining, polymerase chain reaction and western blot suggested that therapeutic effect of ucMSC-Ex was mediated by activation of autophagy in pancreatic acinar cells through inhibition of mTOR. ucMSC-Ex can attenuate pancreas injury by inhibiting mTOR to regulate acinar cell autophagy after TP. Future studies will build on the comprehensive sequencing of RNA carried by ucMSC-Ex to predict and verify specific non-coding RNA.

Luteolin exerts anti-tumour immunity in hepatocellular carcinoma by accelerating CD8+ T lymphocyte infiltration.

Luteolin, a commonly used traditional Chinese medicine, has been utilized for several decades in the treatment of hepatocellular carcinoma (HCC). Previous research has demonstrated its anti-tumour efficacy, but its underlying mechanism remains unclear. This study aimed to assess the therapeutic effects of luteolin in H22 tumour-bearing mice. luteolin effectively inhibited the growth of solid tumours in a well-established mouse model of HCC. High-throughput sequencing revealed that luteolin treatment could enhance T-cell activation, cell chemotaxis and cytokine production. In addition, luteolin helped sustain a high ratio of CD8+ T lymphocytes in the spleen, peripheral blood and tumour tissues. The effects of luteolin on the phenotypic and functional changes in tumour-infiltrating CD8+ T lymphocytes were also investigated. Luteolin restored the cytotoxicity of tumour-infiltrating CD8+ T lymphocytes in H22 tumour-bearing mice. The CD8+ T lymphocytes exhibited intensified phenotype activation and increased production of granzyme B, IFN-γ and TNF-α in serum. The combined administration of luteolin and the PD-1 inhibitor enhanced the anti-tumour effects in H22 tumour-bearing mice. Luteolin could exert an anti-tumour immune response by inducing CD8+ T lymphocyte infiltration and enhance the anti-tumour effects of the PD-1 inhibitor on H22 tumour-bearing mice.

Comparative and phylogenetic analysis of the complete chloroplast genomes of 10 Artemisia selengensis resources based on high-throughput sequencing.

BACKGROUND: Artemisia selengensis, classified within the genus Artemisia of the Asteraceae family, is a perennial herb recognized for its dual utility in culinary and medicinal domains. There are few studies on the chloroplast genome of A. selengensis, and the phylogeographic classification is vague, which makes phylogenetic analysis and evolutionary studies very difficult. RESULTS: The chloroplast genomes of 10 A. selengensis in this study were highly conserved in terms of gene content, gene order, and gene intron number. The genome lengths ranged from 151,148 to 151,257 bp and were typical of a quadripartite structure with a total GC content of approximately 37.5%. The chloroplast genomes of all species encode 133 genes, including 88 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Due to the contraction and expansion of the inverted repeats (IR), the overlap of ycf1 and ndhF genes occurred at the inverted repeats B (IRB) and short single copy sequence (SSC) boundaries. According to a codon use study, the frequent base in the chloroplast genome of A. selengensis' third codon position was A/T. The number of SSR repeats was 42-44, most of which were single nucleotide A/T repeats. Sequence alignment analysis of the chloroplast genome showed that variable regions were mainly distributed in single copy regions, nucleotide diversity values of 0 to 0.009 were calculated by sliding window analysis, 8 mutation hotspot regions were detected, and coding regions were more conserved than non-coding regions. Analysis of non-synonymous substitution (Ka) and synonymous substitution (Ks) revealed that accD, rps12, petB, and atpF genes were affected by positive selection and no genes were affected by neutral selection. Based on the findings of the phylogenetic analysis, Artemisia selengensis was sister to the genus Artemisia Chrysanthemum and formed a monophyletic group with other Artemisia genera. CONCLUSIONS: In this research, the present study systematically compared the chloroplast genomic features of A. selengensis and provided important information for the study of the chloroplast genome of A. selengensis and the evolutionary relationships among Asteraceae species.

Unveiling putative modulators of mutable collagenous tissue in the brittle star Ophiomastix wendtii: an RNA-Seq analysis.

Collagenous connective tissue, found throughout the bodies of metazoans, plays a crucial role in maintaining structural integrity. This versatile tissue has the potential for numerous biomedical applications, including the development of innovative collagen-based biomaterials. Inspiration for such advancements can be drawn from echinoderms, a group of marine invertebrates that includes sea stars, sea cucumbers, brittle stars, sea urchins, and sea lilies. Through their nervous system, these organisms can reversibly control the pliability of their connective tissue components (i.e., tendons and ligaments) that are composed of mutable collagenous tissue (MCT). The variable tensile properties of the MCT allow echinoderms to perform unique functions, including postural maintenance, reduction of muscular energy use, autotomy to avoid predators, and asexual reproduction through fission. The changes in the tensile strength of MCT structures are specifically controlled by specialized neurosecretory cells called juxtaligamental cells. These cells release substances that either soften or stiffen the MCT. So far, only a few of these substances have been purified and characterized, and the genetic underpinning of MCT biology remains unknown. Therefore, we have conducted this research to identify MCT-related genes in echinoderms as a first step towards a better understanding of the MCT molecular control mechanisms. Our ultimate goal is to unlock new biomaterial applications based on this knowledge. In this project, we used RNA-Seq to identify and annotate differentially expressed genes in the MCT structures of the brittle star Ophiomastix wendtii. As a result, we present a list of 16 putative MCT modulator genes, which will be validated and characterized in forthcoming functional analyses.