N-methyladenosine (mA) is the most common internal modification in eukaryotic mRNA. It is dynamically installed and removed, and acts as a new layer of mRNA metabolism, regulating biological processes including stem cell pluripotency, cell differentiation, and energy homeostasis. mA is recognized by selective binding proteins; YTHDF1 and YTHDF3 work in concert to affect the translation of mA-containing mRNAs, YTHDF2 expedites mRNA decay, and YTHDC1 affects the nuclear processing of its targets. The biological function of YTHDC2, the final member of the YTH protein family, remains unknown. We report that YTHDC2 selectively binds mA at its consensus motif. YTHDC2 enhances the translation efficiency of its targets and also decreases their mRNA abundance. Ythdc2 knockout mice are infertile; males have significantly smaller testes and females have significantly smaller ovaries compared to those of littermates. The germ cells of Ythdc2 knockout mice do not develop past the zygotene stage and accordingly, Ythdc2 is upregulated in the testes as meiosis begins. Thus, YTHDC2 is an mA-binding protein that plays critical roles during spermatogenesis.

Emerging evidence revealed important roles of tumor neoantigens in generating spontaneous antitumor immune responses and predicting clinical responses to immunotherapies 1 , 2 . Despite the presence of numerous neoantigens, complete tumor elimination rarely occurs in many patients, due to failures in mounting a sufficient and lasting antitumor immune response 3 , 4 . Here, we show that durable neoantigen-specific immunity is regulated by messenger RNA (mRNA) N 6 -methyadenosine (m 6 A) methylation through the m 6 A-binding protein YTHDF1 5 . In contrast to wild-type mice, Ythdf1 -deficient ( Ythdf1 −/− ) mice exhibit an elevated antigen-specific CD8 + T cell antitumor response. Loss of YTHDF1 in classical dendritic cells (cDCs) enhanced the cross-presentation of tumor antigen and the cross-priming of CD8 + T cells in vivo . Mechanistically, transcripts encoding lysosomal proteases are marked by m 6 A and recognized by YTHDF1. Binding of YTHDF1 to these transcripts elevates translation of lysosomal cathepsins in DCs, with the inhibition of cathepsins markedly enhancing cross-presentation of the wild-type DCs. Furthermore, the therapeutic efficacy of PD-L1 checkpoint blockade is enhanced in Ythdf1 −/− mice, implicating YTHDF1 as a new potential therapeutic target in anticancer immunotherapy.

l e t t e r sHow an insect evolves to become a successful herbivore is of profound biological and practical importance. Herbivores are often adapted to feed on a specific group of evolutionarily and biochemically related host plants 1 , but the genetic and molecular bases for adaptation to plant defense compounds remain poorly understood 2 . We report the first whole-genome sequence of a basal lepidopteran species, Plutella xylostella, which contains 18,071 protein-coding and 1,412 unique genes with an expansion of gene families associated with perception and the detoxification of plant defense compounds. A recent expansion of retrotransposons near detoxification-related genes and a wider system used in the metabolism of plant defense compounds are shown to also be involved in the development of insecticide resistance. This work shows the genetic and molecular bases for the evolutionary success of this worldwide herbivore and offers wider insights into insect adaptation to plant feeding, as well as opening avenues for more sustainable pest management.The global pest P. xylostella (Lepidoptera: Yponomeutidae) is thought to have coevolved with the crucifer plant family 3 ( Supplementary Fig. 1) and has become the most destructive pest of economically important food crops, including rapeseed, cauliflower and cabbage 4 . Recently, the total cost of damage and management worldwide was estimated at $4-5 billion per annum 5,6 . This insect is the first species to have evolved resistance to dichlorodiphenyltrichloroethane (DDT) in the 1950s 7 and to Bacillus thuringiensis (Bt) toxins in the 1990s 8 and has developed resistance to all classes of insecticide, making it increasingly difficult to control 9,10 . P. xylostella provides an exceptional system for understanding the genetic and molecular bases of how insect herbivores cope with the broad range of plant defenses and chemicals encountered in the environment (Supplementary Fig. 2).We used a P. xylostella strain (Fuzhou-S) collected from a field in Fuzhou in southeastern China (26.08 °N, 119.28 °E) for sequencing ( Supplementary Fig. 1). Whole-genome shotgun-based Illumina sequencing of single individuals (Supplementary Table 1), even after ten generations of laboratory inbreeding, resulted in a poor initial assembly (N50 = 2.4 kb, representing the size above which 50% of the total length of the sequences is included), owing to high levels of heterozygosity ( Supplementary Figs. 3 and 4 and Supplementary Table 2). Subsequently, we sequenced 100,800 fosmid clones (comprising ~10× the genome length) to a depth of 200× ( Supplementary Fig. 5 and Supplementary Tables 3-5), assembling the resulting sequence data into 1,819 scaffolds, with an N50 of 737 kb, spanning ~394 Mb of the genome sequence (version 1; Supplementary Fig. 6 and Supplementary Table 6). The assembly covered 85.5% of a set of protein-coding ESTs (Supplementary Tables 7 and 8) generated by transcriptome sequencing 11 . Alignment of a subject scaffold against a 126-kb BAC (GenBank GU058050) from an altern...

In pharmaceutical sciences, a crucial step of the drug discovery process is the identification of drug-target interactions. However, only a small portion of the drug-target interactions have been experimentally validated, as the experimental validation is laborious and costly. To improve the drug discovery efficiency, there is a great need for the development of accurate computational approaches that can predict potential drug-target interactions to direct the experimental verification. In this paper, we propose a novel drug-target interaction prediction algorithm, namely neighborhood regularized logistic matrix factorization (NRLMF). Specifically, the proposed NRLMF method focuses on modeling the probability that a drug would interact with a target by logistic matrix factorization, where the properties of drugs and targets are represented by drug-specific and target-specific latent vectors, respectively. Moreover, NRLMF assigns higher importance levels to positive observations (i.e., the observed interacting drug-target pairs) than negative observations (i.e., the unknown pairs). Because the positive observations are already experimentally verified, they are usually more trustworthy. Furthermore, the local structure of the drug-target interaction data has also been exploited via neighborhood regularization to achieve better prediction accuracy. We conducted extensive experiments over four benchmark datasets, and NRLMF demonstrated its effectiveness compared with five state-of-the-art approaches.

BackgroundYAP activation is crucial for cancer development including colorectal cancer (CRC). Nevertheless, it remains unclear whether N6-Methyladenosine (m6A) modified transcripts of long noncoding RNAs (lncRNAs) can regulate YAP activation in cancer progression. We investigated the functional link between lncRNAs and the m6A modification in YAP signaling and CRC progression.MethodsYAP interacting lncRNAs were screened by RIP-sequencing, RNA FISH and immunofluorescence co-staining assays. Interaction between YAP and lncRNA GAS5 was studied by biochemical methods. MeRIP-sequencing combined with lncRNA-sequencing were used to identify the m6A modified targets of YTHDF3 in CRC. Gain-of-function and Loss-of-function analysis were performed to measure the function of GAS5-YAP-YTHDF3 axis in CRC progression in vitro and in vivo.ResultsGAS5 directly interacts with WW domain of YAP to facilitate translocation of endogenous YAP from the nucleus to the cytoplasm and promotes phosphorylation and subsequently ubiquitin-mediated degradation of YAP to inhibit CRC progression in vitro and in vivo. Notably, we demonstrate the m6A reader YTHDF3 not only a novel target of YAP but also a key player in YAP signaling by facilitating m6A-modified lncRNA GAS5 degradation, which profile a new insight into CRC progression. Clinically, lncRNA GAS5 expressions is negatively correlated with YAP and YTHDF3 protein levels in tumors from CRC patients.ConclusionsOur study uncovers a negative functional loop of lncRNA GAS5-YAP-YTHDF3 axis, and identifies a new mechanism for m6A-induced decay of GAS5 on YAP signaling in progression of CRC which may offer a promising approach for CRC treatment.

A facile and efficient photoreduction method is employed to synthesize the composite of methylammonium lead iodide perovskite (MAPbI ) with reduced graphene oxide (rGO). This MAPbI /rGO composite is shown to be an outstanding visible-light photocatalyst for H evolution in aqueous HI solution saturated with MAPbI . Powder samples of MAPbI /rGO (100 mg) show a H evolution rate of 93.9 µmol h , which is 67 times faster than that of pristine MAPbI , under 120 mW cm visible-light (λ ≥ 420 nm) illumination, and the composite is highly stable showing no significant decrease in the catalytic activity after 200 h (i.e., 20 cycles) of repeated H evolution experiments. The electrochemiluminescence performance of MAPbI is investigated to explore the charge transfer process, to find that the photogenerated electrons in MAPbI are transferred to the rGO sites, where protons are reduced to H .

N-methyladenosine (mA) affects multiple aspects of mRNA metabolism and regulates developmental transitions by promoting mRNA decay. Little is known about the role of mA in the adult mammalian nervous system. Here we report that sciatic nerve lesion elevates levels of mA-tagged transcripts encoding many regeneration-associated genes and protein translation machinery components in the adult mouse dorsal root ganglion (DRG). Single-base resolution mA-CLIP mapping further reveals a dynamic mA landscape in the adult DRG upon injury. Loss of either mA methyltransferase complex component Mettl14 or mA-binding protein Ythdf1 globally attenuates injury-induced protein translation in adult DRGs and reduces functional axon regeneration in the peripheral nervous system in vivo. Furthermore, Pten deletion-induced axon regeneration of retinal ganglion neurons in the adult central nervous system is attenuated upon Mettl14 knockdown. Our study reveals a critical epitranscriptomic mechanism in promoting injury-induced protein synthesis and axon regeneration in the adult mammalian nervous system.

Experimental determination of drug-target interactions is expensive and time-consuming. Therefore, there is a continuous demand for more accurate predictions of interactions using computational techniques. Algorithms have been devised to infer novel interactions on a global scale where the input to these algorithms is a drug-target network (i.e., a bipartite graph where edges connect pairs of drugs and targets that are known to interact). However, these algorithms had difficulty predicting interactions involving new drugs or targets for which there are no known interactions (i.e., "orphan" nodes in the network). Since data usually lie on or near to low-dimensional non-linear manifolds, we propose two matrix factorization methods that use graph regularization in order to learn such manifolds. In addition, considering that many of the non-occurring edges in the network are actually unknown or missing cases, we developed a preprocessing step to enhance predictions in the "new drug" and "new target" cases by adding edges with intermediate interaction likelihood scores. In our cross validation experiments, our methods achieved better results than three other state-of-the-art methods in most cases. Finally, we simulated some "new drug" and "new target" cases and found that GRMF predicted the left-out interactions reasonably well.