Achieving single-cell-resolution lineage tracing in zebrafish by continuous barcoding mutations during embryogenesis.

Unraveling the lineage relationships of all descendants from a zygote is fundamental to advancing our understanding of developmental and stem cell biology. However, existing cell barcoding technologies in zebrafish lack the resolution to capture the majority of cell divisions during embryogenesis. A recently developed method, SMALT, successfully reconstructed high-resolution cell phylogenetic trees for Drosophila melanogaster. Here, we implement the SMALT system in zebrafish, recording a median of 14 substitution mutations on a one-kilobase-pair barcoding sequence for one-day post-fertilization embryos. Leveraging this system, we reconstruct four cell lineage trees for zebrafish fin cells, encompassing both original and regenerated fin. Each tree consists of hundreds of internal nodes with a median bootstrap support of 99%. Analysis of the obtained cell lineage trees reveals that regenerated fin cells mainly originate from cells in the same part of the fins. Through multiple times sampling germ cells from the same individual, we confirm the stability of the germ cell pool and the early separation of germ cell and somatic cell progenitors. Our system offers the potential for reconstructing high-quality cell phylogenies across diverse tissues, providing valuable insights into development and disease in zebrafish.

A statistical method for quantifying progenitor cells reveals incipient cell fate commitments.

Quantifying the number of progenitor cells that found an organ, tissue or cell population is of fundamental importance for understanding the development and homeostasis of a multicellular organism. Previous efforts rely on marker genes that are specifically expressed in progenitors. This strategy is, however, often hindered by the lack of ideal markers. Here we propose a general statistical method to quantify the progenitors of any tissues or cell populations in an organism, even in the absence of progenitor-specific markers, by exploring the cell phylogenetic tree that records the cell division history during development. The method, termed targeting coalescent analysis (TarCA), computes the probability that two randomly sampled cells of a tissue coalesce within the tissue-specific monophyletic clades. The inverse of this probability then serves as a measure of the progenitor number of the tissue. Both mathematic modeling and computer simulations demonstrated the high accuracy of TarCA, which was then validated using real data from nematode, fruit fly and mouse, all with related cell phylogenetic trees. We further showed that TarCA can be used to identify lineage-specific upregulated genes during embryogenesis, revealing incipient cell fate commitments in mouse embryos.

Split complementation of base editors to minimize off-target edits.

Base editors (BEs) empower the efficient installation of beneficial or corrective point mutations in crop and human genomes. However, conventional BEs can induce unpredictable guide RNA (gRNA)-independent off-target edits in the genome and transcriptome due to spurious activities of BE-enclosing deaminases, and current improvements mostly rely on deaminase-specific mutagenesis or exogenous regulators. Here we developed a split deaminase for safe editing (SAFE) system applicable to BEs containing distinct cytidine or adenosine deaminases, with no need of external regulators. In SAFE, a BE was properly split at a deaminase domain embedded inside a Cas9 nickase, simultaneously fragmenting and deactivating both the deaminase and the Cas9 nickase. The gRNA-conditioned BE reassembly conferred robust on-target editing in plant, human and yeast cells, while minimizing both gRNA-independent and gRNA-dependent off-target DNA/RNA edits. SAFE also substantially increased product purity by eliminating indels. Altogether, SAFE provides a generalizable solution for BEs to suppress off-target editing and improve on-target performance.

Evolution of Human Brain Left-Right Asymmetry: Old Genes with New Functions.

The human brain is generally anatomically symmetrical, boasting mirror-like brain regions in the left and right hemispheres. Despite this symmetry, fine-scale structural asymmetries are prevalent and are believed to be responsible for distinct functional divisions within the brain. Prior studies propose that these asymmetric structures are predominantly primate specific or even unique to humans, suggesting that the genes contributing to the structural asymmetry of the human brain might have evolved recently. In our study, we identified approximately 1,500 traits associated with human brain asymmetry by collecting paired brain magnetic resonance imaging features from the UK Biobank. Each trait is measured in a specific region of one hemisphere and mirrored in the corresponding region of the other hemisphere. Conducting genome-wide association studies on these traits, we identified over 1,000 quantitative trait loci. Around these index single nucleotide polymorphisms, we found approximately 200 genes that are enriched in brain-related Gene Ontology terms and are predominantly upregulated in brain tissues. Interestingly, most of these genes are evolutionarily old, originating just prior to the emergence of Bilateria (bilaterally symmetrical animals) and Euteleostomi (bony vertebrates with a brain), at a significantly higher ratio than expected. Further analyses of these genes reveal a brain-specific upregulation in humans relative to other mammalian species. This suggests that the structural asymmetry of the human brain has been shaped by evolutionarily ancient genes that have assumed new functions over time.

PhyloVelo enhances transcriptomic velocity field mapping using monotonically expressed genes.

Single-cell RNA sequencing (scRNA-seq) is a powerful approach for studying cellular differentiation, but accurately tracking cell fate transitions can be challenging, especially in disease conditions. Here we introduce PhyloVelo, a computational framework that estimates the velocity of transcriptomic dynamics by using monotonically expressed genes (MEGs) or genes with expression patterns that either increase or decrease, but do not cycle, through phylogenetic time. Through integration of scRNA-seq data with lineage information, PhyloVelo identifies MEGs and reconstructs a transcriptomic velocity field. We validate PhyloVelo using simulated data and Caenorhabditis elegans ground truth data, successfully recovering linear, bifurcated and convergent differentiations. Applying PhyloVelo to seven lineage-traced scRNA-seq datasets, generated using CRISPR-Cas9 editing, lentiviral barcoding or immune repertoire profiling, demonstrates its high accuracy and robustness in inferring complex lineage trajectories while outperforming RNA velocity. Additionally, we discovered that MEGs across tissues and organisms share similar functions in translation and ribosome biogenesis.

Insecticide resistance reduces the profitability of insect-resistant rice cultivars.

INTRODUCTION: Preventing crop yield loss caused by pests is critical for global agricultural production. Agricultural pest control has largely relied on chemical pesticides. The interaction between insecticide resistance and the adaptation of herbivorous pests to host plants may represent an emerging threat to future food security. OBJECTIVES: This study aims to unveil genetic evidence for the reduction in the profitability of resistant cultivars derived from insecticide resistance in target pest insects. METHODS: An experimental evolution system encompassing resistant rice and its major monophagous pest, the brown planthopper Nilaparvata lugens, was constructed. Whole genome resequencing and selective sweep analysis were utilized to identify the candidate gene loci related to the adaptation. RNA interference and induced expression assay were conducted to validate the function of the candidate loci. RESULTS: We found that the imidacloprid-resistant population of N. lugens rapidly adapted to resistant rice IR36. Gene loci related to imidacloprid resistance may contribute to this phenomenon. Multiple alleles in the nicotinic acetylcholine receptor (nAChR)-7-like and P450 CYP4C61 were significantly correlated with changes in virulence to IR36 rice and insecticide resistance of N. lugens. One avirulent/susceptible genotype and two virulent/resistant genotypes could be inferred from the corresponding alleles. Importantly, we found that the virulent/resistant genotypes already exist in the wild in China, exhibiting increasing frequencies along with insecticide usage. We validated the relevance of these genotypes and the virulence to three more resistant rice cultivars. Knockdown of the above two genes in N. lugens significantly decreased both the resistance to imidacloprid and the virulence towards resistant rice. CONCLUSION: Our findings provide direct genetic evidence to the eco-evolutionary consequence of insecticide resistance, and suggest an urgent need for the implementation of predictably sustainable pest management.

Exploiting spatial dimensions to enable parallelized continuous directed evolution.

Current strategies to improve the throughput of continuous directed evolution technologies often involve complex mechanical fluid-controlling system or robotic platforms, which limits their popularization and application in general laboratories. Inspired by our previous study on bacterial range expansion, in this study, we report a system termed SPACE for rapid and extensively parallelizable evolution of biomolecules by introducing spatial dimensions into the landmark phage-assisted continuous evolution system. Specifically, M13 phages and chemotactic Escherichia coli cells were closely inoculated onto a semisolid agar. The phages came into contact with the expanding front of the bacterial range, and then comigrated with the bacteria. This system leverages competition over space, wherein evolutionary progress is closely associated with the production of spatial patterns, allowing the emergence of improved or new protein functions. In a prototypical problem, SPACE remarkably simplified the process and evolved the promoter recognition of T7 RNA polymerase (RNAP) to a library of 96 random sequences in parallel. These results establish SPACE as a simple, easy to implement, and massively parallelizable platform for continuous directed evolution in general laboratories.

Predicting Egg Passage Adaptations to Design Better Vaccines for the H3N2 Influenza Virus.

Seasonal H3N2 influenza evolves rapidly, leading to an extremely poor vaccine efficacy. Substitutions employed during vaccine production using embryonated eggs (i.e., egg passage adaptation) contribute to the poor vaccine efficacy (VE), but the evolutionary mechanism remains elusive. Using an unprecedented number of hemagglutinin sequences (n = 89,853), we found that the fitness landscape of passage adaptation is dominated by pervasive epistasis between two leading residues (186 and 194) and multiple other positions. Convergent evolutionary paths driven by strong epistasis explain most of the variation in VE, which has resulted in extremely poor vaccines for the past decade. Leveraging the unique fitness landscape, we developed a novel machine learning model that can predict egg passage substitutions for any candidate vaccine strain before the passage experiment, providing a unique opportunity for the selection of optimal vaccine viruses. Our study presents one of the most comprehensive characterizations of the fitness landscape of a virus and demonstrates that evolutionary trajectories can be harnessed for improved influenza vaccines.

The twin-beginnings of COVID-19 in Asia and Europe-one prevails quickly.

In the spread of SARS-CoV-2, there have been multiple waves of replacement between strains, each of which having a distinct set of mutations. The first wave is a group of four mutations (C241T, C3037T, C14408T and A23403G [this being the amino acid change D614G]; all designated 0 to 1 below). This DG (D614G) group, fixed at the start of the pandemic, is the foundation of all subsequent waves of strains. Curiously, the DG group is absent in early Asian samples but present (and likely common) in Europe from the beginning. European data show that the high fitness of DG1111 requires the synergistic effect of all four mutations. However, the European strains would have had no time to evolve the four DG mutations (0 to 1), had they come directly from the early Asian DG0000 strain. Very likely, the European DG1111 strain had acquired the highly adaptive DG mutations in pre-pandemic Europe and had been spreading in parallel with the Asian strains. Two recent reports further support this twin-beginning interpretation. There was a period of two-way spread between Asia and Europe but, by May 2020, the European strains had supplanted the Asian strains globally. This large-scale replacement of one set of mutations for another has since been replayed many times as COVID-19 progresses.

Rapid Intraspecies Evolution of Fitness Effects of Yeast Genes.

Organisms within species have numerous genetic and phenotypic variations. Growing evidences show intraspecies variation of mutant phenotypes may be more complicated than expected. Current studies on intraspecies variations of mutant phenotypes are limited to just a few strains. This study investigated the intraspecies variation of fitness effects of 5,630 gene mutants in ten Saccharomyces cerevisiae strains using CRISPR-Cas9 screening. We found that the variability of fitness effects induced by gene disruptions is very large across different strains. Over 75% of genes affected cell fitness in a strain-specific manner to varying degrees. The strain specificity of the fitness effect of a gene is related to its evolutionary and functional properties. Subsequent analysis revealed that younger genes, especially those newly acquired in S. cerevisiae species, are more likely to be strongly strain-specific. Intriguingly, there seems to exist a ceiling of fitness effect size for strong strain-specific genes, and among them, the newly acquired genes are still evolving and have yet to reach this ceiling. Additionally, for a large proportion of protein complexes, the strain specificity profile is inconsistent among genes encoding the same complex. Taken together, these results offer a genome-wide map of intraspecies variation for fitness effect as a mutant phenotype and provide an updated insight on intraspecies phenotypic evolution.

The Runaway Evolution of SARS-CoV-2 Leading to the Highly Evolved Delta Strain.

In new epidemics after the host shift, the pathogens may experience accelerated evolution driven by novel selective pressures. When the accelerated evolution enters a positive feedback loop with the expanding epidemics, the pathogen's runaway evolution may be triggered. To test this possibility in coronavirus disease 2019 (COVID-19), we analyze the extensive databases and identify five major waves of strains, one replacing the previous one in 2020-2021. The mutations differ entirely between waves and the number of mutations continues to increase, from 3-4 to 21-31. The latest wave in the fall of 2021 is the Delta strain which accrues 31 new mutations to become highly prevalent. Interestingly, these new mutations in Delta strain emerge in multiple stages with each stage driven by 6-12 coding mutations that form a fitness group. In short, the evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from the oldest to the youngest wave, and from the earlier to the later stages of the Delta wave, is a process of acceleration with more and more mutations. The global increase in the viral population size (M(t), at time t) and the mutation accumulation (R(t)) may have indeed triggered the runaway evolution in late 2020, leading to the highly evolved Alpha and then Delta strain. To suppress the pandemic, it is crucial to break the positive feedback loop between M(t) and R(t), neither of which has yet to be effectively dampened by late 2021. New waves after Delta, hence, should not be surprising.

Mapping single-cell-resolution cell phylogeny reveals cell population dynamics during organ development.

Mapping the cell phylogeny of a complex multicellular organism relies on somatic mutations accumulated from zygote to adult. Available cell barcoding methods can record about three mutations per barcode, enabling only low-resolution mapping of the cell phylogeny of complex organisms. Here we developed SMALT, a substitution mutation-aided lineage-tracing system that outperforms the available cell barcoding methods in mapping cell phylogeny. We applied SMALT to Drosophila melanogaster and obtained on average more than 20 mutations on a three-kilobase-pair barcoding sequence in early-adult cells. Using the barcoding mutations, we obtained high-quality cell phylogenetic trees, each comprising several thousand internal nodes with 84-93% median bootstrap support. The obtained cell phylogenies enabled a population genetic analysis that estimates the longitudinal dynamics of the number of actively dividing parental cells (Np) in each organ through development. The Np dynamics revealed the trajectory of cell births and provided insight into the balance of symmetric and asymmetric cell division.

On the founder effect in COVID-19 outbreaks: how many infected travelers may have started them all?

How many incoming travelers (I0 at time 0, equivalent to the 'founders' in evolutionary genetics) infected with SARS-CoV-2 who visit or return to a region could have started the epidemic of that region? I0 would be informative about the initiation and progression of epidemics. To obtain I0 , we analyze the genetic divergence among viral populations of different regions. By applying the 'individual-output' model of genetic drift to the SARS-CoV-2 diversities, we obtain I0 < 10, which could have been achieved by one infected traveler in a long-distance flight. The conclusion is robust regardless of the source population, the continuation of inputs (It for t > 0) or the fitness of the variants. With such a tiny trickle of human movement igniting many outbreaks, the crucial stage of repressing an epidemic in any region should, therefore, be the very first sign of local contagion when positive cases first become identifiable. The implications of the highly 'portable' epidemics, including their early evolution prior to any outbreak, are explored in the companion study (Ruan et al., personal communication).

An instantaneous coalescent method insensitive to population structure.

Conventional coalescent inferences of population history make the critical assumption that the population under examination is panmictic. However, most populations are structured. This complicates the prevailing coalescent analyses and sometimes leads to inaccurate estimates. To develop a coalescent method unhampered by population structure, we perform two analyses. First, we demonstrate that the coalescent probability of two randomly sampled alleles from the immediate preceding generation (one generation back) is independent of population structure. Second, motivated by this finding, we propose a new coalescent method: i-coalescent analysis. The i-coalescent analysis computes the instantaneous coalescent rate by using a phylogenetic tree of sampled alleles. Using simulated data, we broadly demonstrate the capability of i-coalescent analysis to accurately reconstruct population size dynamics of highly structured populations, although we find this method often requires larger sample sizes for structured populations than for panmictic populations. Overall, our results indicate i-coalescent analysis to be a useful tool, especially for the inference of population histories with intractable structure such as the developmental history of cell populations in the organs of complex organisms.

Peroxiredoxin alleviates the fitness costs of imidacloprid resistance in an insect pest of rice.

Chemical insecticides have been heavily employed as the most effective measure for control of agricultural and medical pests, but evolution of resistance by pests threatens the sustainability of this approach. Resistance-conferring mutations sometimes impose fitness costs, which may drive subsequent evolution of compensatory modifier mutations alleviating the costs of resistance. However, how modifier mutations evolve and function to overcome the fitness cost of resistance still remains unknown. Here we show that overexpression of P450s not only confers imidacloprid resistance in the brown planthopper, Nilaparvata lugens, the most voracious pest of rice, but also leads to elevated production of reactive oxygen species (ROS) through metabolism of imidacloprid and host plant compounds. The inevitable production of ROS incurs a fitness cost to the pest, which drives the increase or fixation of the compensatory modifier allele T65549 within the promoter region of N. lugens peroxiredoxin (NlPrx) in the pest populations. T65549 allele in turn upregulates the expression of NlPrx and thus increases resistant individuals' ability to clear the cost-incurring ROS of any source. The frequent involvement of P450s in insecticide resistance and their capacity to produce ROS while metabolizing their substrates suggest that peroxiredoxin or other ROS-scavenging genes may be among the common modifier genes for alleviating the fitness cost of insecticide resistance.

A theoretical exploration of the origin and early evolution of a pandemic.

A virus that can cause a global pandemic must be highly adaptive to human conditions. Such adaptation is not likely to have emerged suddenly but, instead, may have evolved step by step with each step favored by natural selection. It is thus necessary to develop a theory about the origin in order to guide the search. Here, we propose such a model whereby evolution occurs in both the virus and the hosts (where the evolution is somatic; i.e., in the immune system). The hosts comprise three groups - the wild animal hosts, the nearby human population, and farther-away human populations. The theory suggests that the conditions under which the pandemic has initially evolved are: (i) an abundance of wild animals in the place of origin (PL0); (ii) a nearby human population of low density; (iii) frequent and long-term animal-human contacts to permit step-by-step evolution; and (iv) a level of herd immunity in the animal and human hosts. In this model, the evolving virus may have regularly spread out of PL0 although such invasions often fail, leaving sporadic cases of early infections. The place of the first epidemic (PL1), where humans are immunologically naïve to the virus, is likely a distance away from PL0. Finally, this current model is only a first attempt and more theoretical models can be expected to guide the search for the origin of SARS-CoV-2.