Institute of Genetics and Developmental Biology

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is thatthere is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the completeprocess including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increasedautophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in manycases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as forreviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multipleassays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagyrelated protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

The genome of the japonica subspecies of rice, an important cereal and model monocot, was sequenced and assembled by whole-genome shotgun sequencing. The assembled sequence covers 93% of the 420-megabase genome. Gene predictions on the assembled sequence suggest that the genome contains 32,000 to 50,000 genes. Homologs of 98% of the known maize, wheat, and barley proteins are found in rice. Synteny and gene homology between rice and the other cereal genomes are extensive, whereas synteny with Arabidopsis is limited. Assignment of candidate rice orthologs to Arabidopsis genes is possible in many cases. The rice genome sequence provides a foundation for the improvement of cereals, our most important crops.

Here we analyse genetic variation, population structure and diversity among 3,010 diverse Asian cultivated rice (Oryza sativa L.) genomes from the 3,000 Rice Genomes Project. Our results are consistent with the five major groups previously recognized, but also suggest several unreported subpopulations that correlate with geographic location. We identified 29 million single nucleotide polymorphisms, 2.4 million small indels and over 90,000 structural variations that contribute to within- and between-population variation. Using pan-genome analyses, we identified more than 10,000 novel full-length protein-coding genes and a high number of presence-absence variations. The complex patterns of introgression observed in domestication genes are consistent with multiple independent rice domestication events. The public availability of data from the 3,000 Rice Genomes Project provides a resource for rice genomics research and breeding.

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development.

Crop domestications are long-term selection experiments that have greatly advanced human civilization. The domestication of cultivated rice (Oryza sativa L.) ranks as one of the most important developments in history. However, its origins and domestication processes are controversial and have long been debated. Here we generate genome sequences from 446 geographically diverse accessions of the wild rice species Oryza rufipogon, the immediate ancestral progenitor of cultivated rice, and from 1,083 cultivated indica and japonica varieties to construct a comprehensive map of rice genome variation. In the search for signatures of selection, we identify 55 selective sweeps that have occurred during domestication. In-depth analyses of the domestication sweeps and genome-wide patterns reveal that Oryza sativa japonica rice was first domesticated from a specific population of O. rufipogon around the middle area of the Pearl River in southern China, and that Oryza sativa indica rice was subsequently developed from crosses between japonica rice and local wild rice as the initial cultivars spread into South East and South Asia. The domestication-associated traits are analysed through high-resolution genetic mapping. This study provides an important resource for rice breeding and an effective genomics approach for crop domestication research. Whole-genome sequences of wild rice and cultivated rice varieties are used to produce a map of rice genome variation, and show that rice was probably first domesticated in southern China. Cultivated rice (Oryza sativa) is thought to have been domesticated from wild rice (Oryza rufipogon) thousands of years ago. This Chinese/Japanese collaboration reports whole-genome sequences from 446 wild rice isolates from across Asia and Oceana, and from more than 1,000 indica and japonica subspecies of cultivated rice. The resulting map of genome variation will be an important resource for rice breeding and for crop-domestication research.

Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.

Enhanced agricultural production through innovative breeding technology is urgently needed to increase access to nutritious foods worldwide. Recent advances in CRISPR/Cas genome editing enable efficient targeted modification in most crops, thus promising to accelerate crop improvement. Here, we review advances in CRISPR/Cas9 and its variants and examine their applications in plant genome editing and related manipulations. We highlight base-editing tools that enable targeted nucleotide substitutions and describe the various delivery systems, particularly DNA-free methods, that have linked genome editing with crop breeding. We summarize the applications of genome editing for trait improvement, development of techniques for fine-tuning gene regulation, strategies for breeding virus resistance, and the use of high-throughput mutant libraries. We outline future perspectives for genome editing in plant synthetic biology and domestication, advances in delivery systems, editing specificity, homology-directed repair, and gene drives. Finally, we discuss the challenges and opportunities for precision plant breeding and its bright future in agriculture.

from the atmosphere. Herein, we review innovative technologies that offer solutions achieving carbon (C) neutrality and sustainable development, including those for renewable energy production, food system transformation, waste valorization, C sink conservation, and C-negative manufacturing. The wealth of knowledge disseminated in this review could inspire the global community and drive the further development of innovative technologies to mitigate climate change and sustainably support human activities.

The role of Fat Mass and Obesity-associated protein (FTO) and its substrate N6-methyladenosine (m6A) in mRNA processing and adipogenesis remains largely unknown. We show that FTO expression and m6A levels are inversely correlated during adipogenesis. FTO depletion blocks differentiation and only catalytically active FTO restores adipogenesis. Transcriptome analyses in combination with m6A-seq revealed that gene expression and mRNA splicing of grouped genes are regulated by FTO. M6A is enriched in exonic regions flanking 5'- and 3'-splice sites, spatially overlapping with mRNA splicing regulatory serine/arginine-rich (SR) protein exonic splicing enhancer binding regions. Enhanced levels of m6A in response to FTO depletion promotes the RNA binding ability of SRSF2 protein, leading to increased inclusion of target exons. FTO controls exonic splicing of adipogenic regulatory factor RUNX1T1 by regulating m6A levels around splice sites and thereby modulates differentiation. These findings provide compelling evidence that FTO-dependent m6A demethylation functions as a novel regulatory mechanism of RNA processing and plays a critical role in the regulation of adipogenesis.

MicroRNAs (miRNAs) are approximately 21 nucleotide noncoding RNAs produced by Dicer-catalyzed excision from stem-loop precursors. Many plant miRNAs play critical roles in development, nutrient homeostasis, abiotic stress responses, and pathogen responses via interactions with specific target mRNAs. miRNAs are not the only Dicer-derived small RNAs produced by plants: A substantial amount of the total small RNA abundance and an overwhelming amount of small RNA sequence diversity is contributed by distinct classes of 21- to 24-nucleotide short interfering RNAs. This fact, coupled with the rapidly increasing rate of plant small RNA discovery, demands an increased rigor in miRNA annotations. Herein, we update the specific criteria required for the annotation of plant miRNAs, including experimental and computational data, as well as refinements to standard nomenclature.

Understanding soybean (Glycine max) domestication and improvement at a genetic level is important to inform future efforts to further improve a crop that provides the world's main source of oilseed. We detect 230 selective sweeps and 162 selected copy number variants by analysis of 302 resequenced wild, landrace and improved soybean accessions at >11× depth. A genome-wide association study using these new sequences reveals associations between 10 selected regions and 9 domestication or improvement traits, and identifies 13 previously uncharacterized loci for agronomic traits including oil content, plant height and pubescence form. Combined with previous quantitative trait loci (QTL) information, we find that, of the 230 selected regions, 96 correlate with reported oil QTLs and 21 contain fatty acid biosynthesis genes. Moreover, we observe that some traits and loci are associated with geographical regions, which shows that soybean populations are structured geographically. This study provides resources for genomics-enabled improvements in soybean breeding.

Changes in redox status have been observed during immune responses in different organisms, but the associated signaling mechanisms are poorly understood. In plants, these redox changes regulate the conformation of NPR1, a master regulator of salicylic acid (SA)-mediated defense genes. NPR1 is sequestered in the cytoplasm as an oligomer through intermolecular disulfide bonds. We report that S-nitrosylation of NPR1 by S-nitrosoglutathione (GSNO) at cysteine-156 facilitates its oligomerization, which maintains protein homeostasis upon SA induction. Conversely, the SA-induced NPR1 oligomer-to-monomer reaction is catalyzed by thioredoxins (TRXs). Mutations in both NPR1 cysteine-156 and TRX compromised NPR1-mediated disease resistance. Thus, the regulation of NPR1 is through the opposing action of GSNO and TRX. These findings suggest a link between pathogen-triggered redox changes and gene regulation in plant immunity.

Although several plant microRNAs (miRNAs) have been shown to play a role in plant development, no phenotype has yet been associated with a reduction or loss of expression of any plant miRNA. Arabidopsis thaliana miR164 was predicted to target five NAM/ATAF/CUC (NAC) domain-encoding mRNAs, including NAC1, which transduces auxin signals for lateral root emergence. Here, we show that miR164 guides the cleavage of endogenous and transgenic NAC1 mRNA, producing 3'-specific fragments. Cleavage was blocked by NAC1 mutations that disrupt base pairing with miR164. Compared with wild-type plants, Arabidopsis mir164a and mir164b mutant plants expressed less miR164 and more NAC1 mRNA and produced more lateral roots. These mutant phenotypes can be complemented by expression of the appropriate MIR164a and MIR164b genomic sequences. By contrast, inducible expression of miR164 in wild-type plants led to decreased NAC1 mRNA levels and reduced lateral root emergence. Auxin induction of miR164 was mirrored by an increase in the NAC1 mRNA 3' fragment, which was not observed in the auxin-insensitive mutants auxin resistant1 (axr1-12), axr2-1, and transport inhibitor response1. Moreover, the cleavage-resistant form of NAC1 mRNA was unaffected by auxin treatment. Our results indicate that auxin induction of miR164 provides a homeostatic mechanism to clear NAC1 mRNA to downregulate auxin signals.

Substantial efforts are being made to optimize the CRISPR/Cas9 system for precision crop breeding. The avoidance of transgene integration and reduction of off-target mutations are the most important targets for optimization. Here, we describe an efficient genome editing method for bread wheat using CRISPR/Cas9 ribonucleoproteins (RNPs). Starting from RNP preparation, the whole protocol takes only seven to nine weeks, with four to five independent mutants produced from 100 immature wheat embryos. Deep sequencing reveals that the chance of off-target mutations in wheat cells is much lower in RNP mediated genome editing than in editing with CRISPR/Cas9 DNA. Consistent with this finding, no off-target mutations are detected in the mutant plants. Because no foreign DNA is used in CRISPR/Cas9 RNP mediated genome editing, the mutants obtained are completely transgene free. This method may be widely applicable for producing genome edited crop plants and has a good prospect of being commercialized.

Receptor-like kinases (RLKs) and Receptor-like proteins (RLPs) play crucial roles in plant immunity, growth, and development. Plants deploy a large number of RLKs and RLPs as pattern recognition receptors (PRRs) that detect microbe- and host-derived molecular patterns as the first layer of inducible defense. Recent advances have uncovered novel PRRs, their corresponding ligands, and mechanisms underlying PRR activation and signaling. In general, PRRs associate with other RLKs and function as part of multiprotein immune complexes at the cell surface. Innovative strategies have emerged for the rapid identification of microbial patterns and their cognate PRRs. Successful pathogens can evade or block host recognition by secreting effector proteins to "hide" microbial patterns or inhibit PRR-mediated signaling. Furthermore, newly identified pathogen effectors have been shown to manipulate RLKs controlling growth and development by mimicking peptide hormones of host plants. The ongoing studies illustrate the importance of diverse plant RLKs in plant disease resistance and microbial pathogenesis.

Editing plant genomes is technically challenging in hard-to-transform plants and usually involves transgenic intermediates, which causes regulatory concerns. Here we report two simple and efficient genome-editing methods in which plants are regenerated from callus cells transiently expressing CRISPR/Cas9 introduced as DNA or RNA. This transient expression-based genome-editing system is highly efficient and specific for producing transgene-free and homozygous wheat mutants in the T0 generation. We demonstrate our protocol to edit genes in hexaploid bread wheat and tetraploid durum wheat, and show that we are able to generate mutants with no detectable transgenes. Our methods may be applicable to other plant species, thus offering the potential to accelerate basic and applied plant genome-engineering research.

Significance China has launched six key ecological restoration projects since the late 1970s, but the contribution of these projects to terrestrial C sequestration remains unknown. In this study we examined the ecosystem C sink in the project area (∼16% of the country’s land area) and evaluated the project-induced C sequestration. The total annual C sink in the project area between 2001 and 2010 was estimated to be 132 Tg C per y, over half of which (74 Tg C per y, 56%) was caused by the implementation of the six projects. This finding indicates that the implementation of the ecological restoration projects in China has significantly increased ecosystem C sequestration across the country.

and are required for colonization by pathogens. We suggest that the mutualistic mycorrhizal and pathogenic fungi similarly recruit the fatty acid biosynthesis program to facilitate host invasion.

We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.

Advances in high-throughput sequencing (HTS) have fostered rapid developments in the field of microbiome research, and massive microbiome datasets are now being generated. However, the diversity of software tools and the complexity of analysis pipelines make it difficult to access this field. Here, we systematically summarize the advantages and limitations of microbiome methods. Then, we recommend specific pipelines for amplicon and metagenomic analyses, and describe commonly-used software and databases, to help researchers select the appropriate tools. Furthermore, we introduce statistical and visualization methods suitable for microbiome analysis, including alpha- and beta-diversity, taxonomic composition, difference comparisons, correlation, networks, machine learning, evolution, source tracing, and common visualization styles to help researchers make informed choices. Finally, a step-by-step reproducible analysis guide is introduced. We hope this review will allow researchers to carry out data analysis more effectively and to quickly select the appropriate tools in order to efficiently mine the biological significance behind the data.