Ensemble Detection of DNA Engineering Signatures.

Synthetic biology is creating genetically engineered organisms at an increasing rate for many potentially valuable applications, but this potential comes with the risk of misuse or accidental release. To begin to address this issue, we have developed a system called GUARDIAN that can automatically detect signatures of engineering in DNA sequencing data, and we have conducted a blinded test of this system using a curated Test and Evaluation (T&E) data set. GUARDIAN uses an ensemble approach based on the guiding principle that no single approach is likely to be able to detect engineering with perfect accuracy. Critically, ensembling enables GUARDIAN to detect sequence inserts in 13 target organisms with a high degree of specificity that requires no subject matter expert (SME) review.

On the optimization of 3D inflow-based vascular-space-occupancy (iVASO) MRI for the quantification of arterial cerebral blood volume (CBVa).

PURPOSE: The inflow-based vascular-space-occupancy (iVASO) MRI was originally developed in a single-slice mode to measure arterial cerebral blood volume (CBVa). When vascular crushers are applied in iVASO, the signals can be sensitized predominantly to small pial arteries and arterioles. The purpose of this study is to perform a systematic optimization and evaluation of a 3D iVASO sequence on both 3 T and 7 T for the quantification of CBVa values in the human brain. METHODS: Three sets of experiments were performed in three separate cohorts. (1) 3D iVASO MRI protocols were compared to single-slice iVASO, and the reproducibility of whole-brain 3D iVASO MRI was evaluated. (2) The effects from different vascular crushers in iVASO were assessed. (3) 3D iVASO MRI results were evaluated in arterial and venous blood vessels identified using ultrasmall-superparamagnetic-iron-oxides-enhanced MRI to validate its arterial origin. RESULTS: 3D iVASO scans showed signal-to-noise ratio (SNR) and CBVa measures consistent with single-slice iVASO with reasonable intrasubject reproducibility. Among the iVASO scans performed with different vascular crushers, the whole-brain 3D iVASO scan with a motion-sensitized-driven-equilibrium preparation with two binomial refocusing pulses and an effective TE of 50 ms showed the best suppression of macrovascular signals, with a relatively low specific absorption rate. When no vascular crusher was applied, the CBVa maps from 3D iVASO scans showed large CBVa values in arterial vessels but well-suppressed signals in venous vessels. CONCLUSION: A whole-brain 3D iVASO MRI scan was optimized for CBVa measurement in the human brain. When only microvascular signals are desired, a motion-sensitized-driven-equilibrium-based vascular crusher with binomial refocusing pulses can be applied in 3D iVASO.

Debugging and consolidating multiple synthetic chromosomes reveals combinatorial genetic interactions.

The Sc2.0 project is building a eukaryotic synthetic genome from scratch. A major milestone has been achieved with all individual Sc2.0 chromosomes assembled. Here, we describe the consolidation of multiple synthetic chromosomes using advanced endoreduplication intercrossing with tRNA expression cassettes to generate a strain with 6.5 synthetic chromosomes. The 3D chromosome organization and transcript isoform profiles were evaluated using Hi-C and long-read direct RNA sequencing. We developed CRISPR Directed Biallelic URA3-assisted Genome Scan, or "CRISPR D-BUGS," to map phenotypic variants caused by specific designer modifications, known as "bugs." We first fine-mapped a bug in synthetic chromosome II (synII) and then discovered a combinatorial interaction associated with synIII and synX, revealing an unexpected genetic interaction that links transcriptional regulation, inositol metabolism, and tRNASerCGA abundance. Finally, to expedite consolidation, we employed chromosome substitution to incorporate the largest chromosome (synIV), thereby consolidating >50% of the Sc2.0 genome in one strain.

Design, construction, and functional characterization of a tRNA neochromosome in yeast.

Here, we report the design, construction, and characterization of a tRNA neochromosome, a designer chromosome that functions as an additional, de novo counterpart to the native complement of Saccharomyces cerevisiae. Intending to address one of the central design principles of the Sc2.0 project, the ∼190-kb tRNA neochromosome houses all 275 relocated nuclear tRNA genes. To maximize stability, the design incorporates orthogonal genetic elements from non-S. cerevisiae yeast species. Furthermore, the presence of 283 rox recombination sites enables an orthogonal tRNA SCRaMbLE system. Following construction in yeast, we obtained evidence of a potent selective force, manifesting as a spontaneous doubling in cell ploidy. Furthermore, tRNA sequencing, transcriptomics, proteomics, nucleosome mapping, replication profiling, FISH, and Hi-C were undertaken to investigate questions of tRNA neochromosome behavior and function. Its construction demonstrates the remarkable tractability of the yeast model and opens up opportunities to directly test hypotheses surrounding these essential non-coding RNAs.

Manipulating the 3D organization of the largest synthetic yeast chromosome.

Whether synthetic genomes can power life has attracted broad interest in the synthetic biology field. Here, we report de novo synthesis of the largest eukaryotic chromosome thus far, synIV, a 1,454,621-bp yeast chromosome resulting from extensive genome streamlining and modification. We developed megachunk assembly combined with a hierarchical integration strategy, which significantly increased the accuracy and flexibility of synthetic chromosome construction. Besides the drastic sequence changes, we further manipulated the 3D structure of synIV to explore spatial gene regulation. Surprisingly, we found few gene expression changes, suggesting that positioning inside the yeast nucleoplasm plays a minor role in gene regulation. Lastly, we tethered synIV to the inner nuclear membrane via its hundreds of loxPsym sites and observed transcriptional repression of the entire chromosome, demonstrating chromosome-wide transcription manipulation without changing the DNA sequences. Our manipulation of the spatial structure of synIV sheds light on higher-order architectural design of the synthetic genomes.

Synthetic chromosome fusion: Effects on mitotic and meiotic genome structure and function.

We designed and synthesized synI, which is ∼21.6% shorter than native chrI, the smallest chromosome in Saccharomyces cerevisiae. SynI was designed for attachment to another synthetic chromosome due to concerns surrounding potential instability and karyotype imbalance and is now attached to synIII, yielding the first synthetic yeast fusion chromosome. Additional fusion chromosomes were constructed to study nuclear function. ChrIII-I and chrIX-III-I fusion chromosomes have twisted structures, which depend on silencing protein Sir3. As a smaller chromosome, chrI also faces special challenges in assuring meiotic crossovers required for efficient homolog disjunction. Centromere deletions into fusion chromosomes revealed opposing effects of core centromeres and pericentromeres in modulating deposition of the crossover-promoting protein Red1. These effects extend over 100 kb and promote disproportionate Red1 enrichment, and thus crossover potential, on small chromosomes like chrI. These findings reveal the power of synthetic genomics to uncover new biology and deconvolute complex biological systems.

Context-dependent neocentromere activity in synthetic yeast chromosome VIII.

Pioneering advances in genome engineering, and specifically in genome writing, have revolutionized the field of synthetic biology, propelling us toward the creation of synthetic genomes. The Sc2.0 project aims to build the first fully synthetic eukaryotic organism by assembling the genome of Saccharomyces cerevisiae. With the completion of synthetic chromosome VIII (synVIII) described here, this goal is within reach. In addition to writing the yeast genome, we sought to manipulate an essential functional element: the point centromere. By relocating the native centromere sequence to various positions along chromosome VIII, we discovered that the minimal 118-bp CEN8 sequence is insufficient for conferring chromosomal stability at ectopic locations. Expanding the transplanted sequence to include a small segment (∼500 bp) of the CDEIII-proximal pericentromere improved chromosome stability, demonstrating that minimal centromeres display context-dependent functionality.

Establishing chromosomal design-build-test-learn through a synthetic chromosome and its combinatorial reconfiguration.

Chromosome-level design-build-test-learn cycles (chrDBTLs) allow systematic combinatorial reconfiguration of chromosomes with ease. Here, we established chrDBTL with a redesigned synthetic Saccharomyces cerevisiae chromosome XV, synXV. We designed and built synXV to harbor strategically inserted features, modified elements, and synonymously recoded genes throughout the chromosome. Based on the recoded chromosome, we developed a method to enable chrDBTL: CRISPR-Cas9-mediated mitotic recombination with endoreduplication (CRIMiRE). CRIMiRE allowed the creation of customized wild-type/synthetic combinations, accelerating genotype-phenotype mapping and synthetic chromosome redesign. We also leveraged synXV as a "build-to-learn" model organism for translation studies by ribosome profiling. We conducted a locus-to-locus comparison of ribosome occupancy between synXV and the wild-type chromosome, providing insight into the effects of codon changes and redesigned features on translation dynamics in vivo. Overall, we established synXV as a versatile reconfigurable system that advances chrDBTL for understanding biological mechanisms and engineering strains.

Synthetic yeast chromosome XI design provides a testbed for the study of extrachromosomal circular DNA dynamics.

We describe construction of the synthetic yeast chromosome XI (synXI) and reveal the effects of redesign at non-coding DNA elements. The 660-kb synthetic yeast genome project (Sc2.0) chromosome was assembled from synthesized DNA fragments before CRISPR-based methods were used in a process of bug discovery, redesign, and chromosome repair, including precise compaction of 200 kb of repeat sequence. Repaired defects were related to poor centromere function and mitochondrial health and were associated with modifications to non-coding regions. As part of the Sc2.0 design, loxPsym sequences for Cre-mediated recombination are inserted between most genes. Using the GAP1 locus from chromosome XI, we show that these sites can facilitate induced extrachromosomal circular DNA (eccDNA) formation, allowing direct study of the effects and propagation of these important molecules. Construction and characterization of synXI contributes to our understanding of non-coding DNA elements, provides a useful tool for eccDNA study, and will inform future synthetic genome design.

Consequences of a telomerase-related fitness defect and chromosome substitution technology in yeast synIX strains.

We describe the complete synthesis, assembly, debugging, and characterization of a synthetic 404,963 bp chromosome, synIX (synthetic chromosome IX). Combined chromosome construction methods were used to synthesize and integrate its left arm (synIXL) into a strain containing previously described synIXR. We identified and resolved a bug affecting expression of EST3, a crucial gene for telomerase function, producing a synIX strain with near wild-type fitness. To facilitate future synthetic chromosome consolidation and increase flexibility of chromosome transfer between distinct strains, we combined chromoduction, a method to transfer a whole chromosome between two strains, with conditional centromere destabilization to substitute a chromosome of interest for its native counterpart. Both steps of this chromosome substitution method were efficient. We observed that wild-type II tended to co-transfer with synIX and was co-destabilized with wild-type IX, suggesting a potential gene dosage compensation relationship between these chromosomes.

Improved EfficientNet for corn disease identification.

Introduction: Corn is one of the world's essential crops, and the presence of corn diseases significantly affects both the yield and quality of corn. Accurate identification of corn diseases in real time is crucial to increasing crop yield and improving farmers' income. However, in real-world environments, the complexity of the background, irregularity of the disease region, large intraclass variation, and small interclass variation make it difficult for most convolutional neural network models to achieve disease recognition under such conditions. Additionally, the low accuracy of existing lightweight models forces farmers to compromise between accuracy and real-time. Methods: To address these challenges, we propose FCA-EfficientNet. Building upon EfficientNet, the fully-convolution-based coordinate attention module allows the network to acquire spatial information through convolutional structures. This enhances the network's ability to focus on disease regions while mitigating interference from complex backgrounds. Furthermore, the adaptive fusion module is employed to fuse image information from different scales, reducing interference from the background in disease recognition. Finally, through multiple experiments, we have determined the network structure that achieves optimal performance. Results: Compared to other widely used deep learning models, this proposed model exhibits outstanding performance in terms of accuracy, precision, recall, and F1 score. Furthermore, the model has a parameter count of 3.44M and Flops of 339.74M, which is lower than most lightweight network models. We designed and implemented a corn disease recognition application and deployed the model on an Android device with an average recognition speed of 92.88ms, which meets the user's needs. Discussion: Overall, our model can accurately identify corn diseases in realistic environments, contributing to timely and effective disease prevention and control.

Pervasive RNA folding is crucial for narnavirus genome maintenance.

A synthetic biology approach toward constructing an RNA-based genome expands our understanding of living things and opens avenues for technological advancement. For the precise design of an artificial RNA replicon either from scratch or based on a natural RNA replicon, understanding structure-function relationships of RNA sequences is critical. However, our knowledge remains limited to a few particular structural elements intensively studied so far. Here, we conducted a series of site-directed mutagenesis studies of yeast narnaviruses ScNV20S and ScNV23S, perhaps the simplest natural autonomous RNA replicons, to identify RNA elements required for maintenance and replication. RNA structure disruption corresponding to various portions of the entire narnavirus genome suggests that pervasive RNA folding, in addition to the precise secondary structure of genome termini, is essential for maintenance of the RNA replicon in vivo. Computational RNA structure analyses suggest that this scenario likely applies to other "narna-like" viruses. This finding implies selective pressure on these simplest autonomous natural RNA replicons to fold into a unique structure that acquires both thermodynamic and biological stability. We propose the importance of pervasive RNA folding for the design of RNA replicons that could serve as a platform for in vivo continuous evolution as well as an interesting model to study the origin of life.

Priors, population sizes, and power in genome-wide hypothesis tests.

BACKGROUND: Genome-wide tests, including genome-wide association studies (GWAS) of germ-line genetic variants, driver tests of cancer somatic mutations, and transcriptome-wide association tests of RNAseq data, carry a high multiple testing burden. This burden can be overcome by enrolling larger cohorts or alleviated by using prior biological knowledge to favor some hypotheses over others. Here we compare these two methods in terms of their abilities to boost the power of hypothesis testing. RESULTS: We provide a quantitative estimate for progress in cohort sizes and present a theoretical analysis of the power of oracular hard priors: priors that select a subset of hypotheses for testing, with an oracular guarantee that all true positives are within the tested subset. This theory demonstrates that for GWAS, strong priors that limit testing to 100-1000 genes provide less power than typical annual 20-40% increases in cohort sizes. Furthermore, non-oracular priors that exclude even a small fraction of true positives from the tested set can perform worse than not using a prior at all. CONCLUSION: Our results provide a theoretical explanation for the continued dominance of simple, unbiased univariate hypothesis tests for GWAS: if a statistical question can be answered by larger cohort sizes, it should be answered by larger cohort sizes rather than by more complicated biased methods involving priors. We suggest that priors are better suited for non-statistical aspects of biology, such as pathway structure and causality, that are not yet easily captured by standard hypothesis tests.

Improved YOLOX-Tiny network for detection of tobacco brown spot disease.

Introduction: Tobacco brown spot disease caused by Alternaria fungal species is a major threat to tobacco growth and yield. Thus, accurate and rapid detection of tobacco brown spot disease is vital for disease prevention and chemical pesticide inputs. Methods: Here, we propose an improved YOLOX-Tiny network, named YOLO-Tobacco, for the detection of tobacco brown spot disease under open-field scenarios. Aiming to excavate valuable disease features and enhance the integration of different levels of features, thereby improving the ability to detect dense disease spots at different scales, we introduced hierarchical mixed-scale units (HMUs) in the neck network for information interaction and feature refinement between channels. Furthermore, in order to enhance the detection of small disease spots and the robustness of the network, we also introduced convolutional block attention modules (CBAMs) into the neck network. Results: As a result, the YOLO-Tobacco network achieved an average precision (AP) of 80.56% on the test set. The AP was 3.22%, 8.99%, and 12.03% higher than that obtained by the classic lightweight detection networks YOLOX-Tiny network, YOLOv5-S network, and YOLOv4-Tiny network, respectively. In addition, the YOLO-Tobacco network also had a fast detection speed of 69 frames per second (FPS). Discussion: Therefore, the YOLO-Tobacco network satisfies both the advantages of high detection accuracy and fast detection speed. It will likely have a positive impact on early monitoring, disease control, and quality assessment in diseased tobacco plants.