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.

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.

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.

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.

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.

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.

The Origin of Additive Genetic Variance Driven by Positive Selection.

Fisher's fundamental theorem of natural selection predicts no additive variance of fitness in a natural population. Consistently, studies in a variety of wild populations show virtually no narrow-sense heritability (h2) for traits important to fitness. However, counterexamples are occasionally reported, calling for a deeper understanding on the evolution of additive variance. In this study, we propose adaptive divergence followed by population admixture as a source of the additive genetic variance of evolutionarily important traits. We experimentally tested the hypothesis by examining a panel of ∼1,000 yeast segregants produced by a hybrid of two yeast strains that experienced adaptive divergence. We measured >400 yeast cell morphological traits and found a strong positive correlation between h2 and evolutionary importance. Because adaptive divergence followed by population admixture could happen constantly, particularly in species with wide geographic distribution and strong migratory capacity (e.g., humans), the finding reconciles the observation of abundant additive variances in evolutionarily important traits with Fisher's fundamental theorem of natural selection. Importantly, the revealed role of positive selection in promoting rather than depleting additive variance suggests a simple explanation for why additive genetic variance can be dominant in a population despite the ubiquitous between-gene epistasis observed in functional assays.

A hMTR4-PDIA3P1-miR-125/124-TRAF6 Regulatory Axis and Its Function in NF kappa B Signaling and Chemoresistance.

BACKGROUND AND AIMS: DNA damage-induced NF-κB activation is a major obstacle to effective antitumour chemotherapy. Long noncoding RNAs (lncRNAs) that regulate chemoresistance of cancer cells remain largely unknown. This study aimed to characterize the lncRNAs that may affect chemotherapy sensitivity. APPROACH AND RESULTS: We found that lncRNA PDIA3P1 (protein disulfide isomerase family A member 3 pseudogene 1) was up-regulated in multiple cancer types and following treatment with DNA-damaging chemotherapeutic agents, like doxorubicin (Dox). Higher PDIA3P1 level was associated with poorer recurrence-free survival of human hepatocellular carcinoma (HCC). Both gain-of-function and loss-of-function studies revealed that PDIA3P1 protected cancer cells from Dox-induced apoptosis and allowed tumor xenografts to grow faster and to be more resistant to Dox treatment. Mechanistically, miR-125a/b and miR-124 suppressed the expression of tumor necrosis factor receptor-associated factor 6 (TRAF6), but PDIA3P1 bound to miR-125a/b/miR-124 and relieved their repression on TRAF6, leading to activation of the nuclear factor kappa B (NF-κB) pathway. Consistently, the effect of PDIA3P1 inhibition in promoting Dox-triggered apoptosis was antagonized by silencing the inhibitor of κBα (IκBα) or overexpressing TRAF6. Administration of BAY 11-7085, an NF-κB inhibitor attenuated PDIA3P1-induced resistance to Dox treatment in mouse xenografts. Moreover, up-regulation of PDIA3P1 was significantly correlated with elevation of TRAF6, phosphorylated p65, or NF-κB downstream anti-apoptosis genes in human HCC tissues. These data indicate that enhanced PDIA3P1 expression may confer chemoresistance by acting as a microRNA sponge to increase TRAF6 expression and augment NF-κB signaling. Subsequent investigations into the mechanisms of PDIA3P1 up-regulation revealed that human homologue of mRNA transport mutant 4 (hMTR4), which promotes RNA degradation, could bind to PDIA3P1, and this interaction was disrupted by Dox treatment. Overexpression of hMTR4 attenuated Dox-induced elevation of PDIA3P1, whereas silencing hMTR4 increased PDIA3P1 level, suggesting that Dox may up-regulate PDIA3P1 by abrogating the hMTR4-mediated PDIA3P1 degradation. CONCLUSION: There exists a hMTR4-PDIA3P1-miR-125/124-TRAF6 regulatory axis that regulates NF-κB signaling and chemoresistance, which may be exploited for anticancer therapy.

The Genotype-Phenotype Relationships in the Light of Natural Selection.

Although any genotype-phenotype relationships are a result of evolution, little is known about how natural selection and neutral drift, two distinct driving forces of evolution, operate to shape the relationships. By analyzing ∼500 yeast quantitative traits, we reveal a basic "supervisor-worker" gene architecture underlying a trait. Supervisors are often identified by "perturbational" approaches (such as gene deletion), whereas workers, which usually show small and statistically insignificant deletion effects, are tracked primarily by "observational" approaches that examine the correlation between gene activity and trait value across a number of conditions. Accordingly, supervisors provide most of the genetic understandings of the trait whereas workers provide rich mechanistic understandings. Further analyses suggest that most observed supervisor-worker interactions may evolve largely neutrally, resulting in pervasive between-worker epistasis that suppresses the tractability of workers. In contrast, a fraction of supervisors are recruited/maintained by natural selection to build worker co-expression, boosting the tractability of workers. Thus, by revealing a supervisor-worker gene architecture underlying complex traits, the opposite roles of natural selection versus neutral drift in shaping the gene architecture, and the complementary strengths of the perturbational and observational research strategies in characterizing the gene architecture, this study may lay a new conceptual foundation for understanding the molecular basis of complex traits.

The nonessentiality of essential genes in yeast provides therapeutic insights into a human disease.

Essential genes refer to those whose null mutation leads to lethality or sterility. Theoretical reasoning and empirical data both suggest that the fatal effect of inactivating an essential gene can be attributed to either the loss of indispensable core cellular function (Type I), or the gain of fatal side effects after losing dispensable periphery function (Type II). In principle, inactivation of Type I essential genes can be rescued only by re-gain of the core functions, whereas inactivation of Type II essential genes could be rescued by a further loss of function of another gene to eliminate the otherwise fatal side effects. Because such loss-of-function rescuing mutations may occur spontaneously, Type II essential genes may become nonessential in a few individuals of a large population. Motivated by this reasoning, we here carried out a systematic screening for Type II essentiality in the yeast Saccharomyces cerevisiae Large-scale whole-genome sequencing of essentiality-reversing mutants reveals 14 cases whereby the inactivation of an essential gene is rescued by loss-of-function mutations on another gene. In particular, the essential gene encoding the enzyme adenylosuccinate lyase (ADSL) is shown to be Type II, suggesting a loss-of-function therapeutic strategy for the human disorder ADSL deficiency. A proof-of-principle test of this strategy in the nematode Caenorhabditis elegans shows promising results.

Assessing the Influence of Dietary History on Gut Microbiota.

Diet is known to play a major role in determining the composition and function of the gut microbiota. Previous studies have often focused on the immediate effects of dietary intervention. How dietary history prior to a given dietary intervention influences the gut microbiota is, however, not well understood. To assess the influence of dietary history, in this study, mice with different dietary histories were subjected to the same dietary interventions, and the gut microbial communities of these mice were characterized by 16S rDNA sequencing. We found that dietary history played a long-lasting role in the composition of the gut microbiota when the dietary switch was moderate. In sharp contrast, such effects nearly vanished when the diet was switched to certain extreme dietary conditions. Interestingly, the abundance of Akkermansia, a bacterial genus associated with loss of body weight, was elevated dramatically in mice subjected to a diet composed exclusively of meat. Our results revealed a more complex picture of the influence of dietary history on gut microbiota than anticipated.

The Biology Complicated by Genetic Analysis.

Genetics is used as a tool to study living systems because of a key assumption that the phenotypes of loss-of-function mutations on a gene indicate the gene's normal/native functions. I propose that inactivation of a gene not only suppresses the gene's native functions but may also create spurious functions that cause phenotypes irrelevant to the gene's native functions. Such spurious functions represent the otherwise dormant physical/chemical potentials of a living system, do not follow the existing rules built by natural selection, and can hardly be integrated with other functions using empirical data. Thus, the rationale of using loss-of-function phenotypic data to understand a living system is challenged. Fortunately, spurious functions are expected to be evolutionarily unstable while native functions should be conserved, suggesting a means of separating them. I argue that current biology is confused by the undiscerned use of genetic data and suggest a solution.

The Convergent Cancer Evolution toward a Single Cellular Destination.

The essence of Darwin's theory is that evolution is driven by purposeless mutations that are subsequently selected by natural environments, so there is often no predefined destination in organismal evolution. Using gene expressions of 107 cell types, we built a functional space of human cells to trace the evolutionary trajectory of 18 types of solid tumor cancers. We detected a dominant evolving trend toward the functional status of embryonic stem cells (ESC) for approximately 3,000 tumors growing in distinct tissue environments. This pattern remained the same after excluding known cancer/ESC signature genes (∼ 3,000 genes) or excluding all oncogenic gene sets (∼ 12,000 genes) annotated in MSigDB, suggesting a convergent evolution of the overall functional status in cancers. In support of this, the functional distance to ESC served as a common prognostic indicator for cancers of various types, with shorter distance corresponding to poor prognosis, which was true even when randomly selected gene sets were considered. Thus, regardless of the external environments, cancer evolution is a directional process toward a defined cellular destination, a finding reconciling development and evolution, the two seemingly incompatible philosophies both adopted by the cancer research community, and also raising new questions to evolutionary biology.

Reassessing the "duon" hypothesis of protein evolution.

There are two distinct types of DNA sequences, namely coding sequences and regulatory sequences, in a genome. A recent study of the occupancy of transcription factors (TFs) in human cells suggested that protein-coding sequences also serve as the codes of TF occupancy, and proposed a "duon" hypothesis in which up to 15% of codons of human protein genes are constrained by the additional coding requirements that regulate gene expression. This hypothesis challenges our basic understanding on the human genome. We reanalyzed the data and found that the previous study was confounded by ascertainment bias related to base composition. Using an unbiased comparison in which G/C and A/T sites are considered separately, we reveal a similar level of conservation between TF-bound codons and TF-depleted codons, suggesting largely no extra purifying selection provided by the TF occupancy on the codons of human genes. Given the generally short binding motifs of TFs and the open chromatin structure during transcription, we argue that the occupancy of TFs on protein-coding sequences is mostly passive and evolutionarily neutral, with to-be-determined functions in the regulation of gene expression.

The dJ/dS Ratio Test Reveals Hundreds of Novel Putative Cancer Drivers.

Computational tools with a balanced sensitivity and specificity in identification of candidate cancer drivers are highly desired. In this study, we propose a new statistical test, namely the dJ/dS ratio test, to compute the relative mutation rate of exon/intron junction sites (dJ) to synonymous sites (dS); observation of dJ/dS ratio larger than 1 in cancer indicates positive selection for splicing deregulation, a signature of cancer driver genes. Using this method, we analyzed the data from The Cancer Genome Atlas and identified hundreds of novel putative cancer drivers. Interestingly, these genes are highly enriched in biological processes related to the development and maintenance of multicellularity, paralleling a previous finding that cancer evolves back to be unicellular by knocking down the multicellularity-associated genetic network.

Lineage analysis by microsatellite loci deep sequencing in mice.

Lineage analysis is the identification of all the progeny of a single progenitor cell, and has become particularly useful for studying developmental processes and cancer biology. Here, we propose a novel and effective method for lineage analysis that combines sequence capture and next-generation sequencing technology. Genome-wide mononucleotide and dinucleotide microsatellite loci in eight samples from two mice were identified and used to construct phylogenetic trees based on somatic indel mutations at these loci, which were unique enough to distinguish and parse samples from different mice into different groups along the lineage tree. For example, biopsies from the liver and stomach, which originate from the endoderm, were located in the same clade, while samples in kidney, which originate from the mesoderm, were located in another clade. Yet, tissue with a common developmental origin may still contain cells of a mixed ancestry. This genome-wide approach thus provides a non-invasive lineage analysis method based on mutations that accumulate in the genomes of opaque multicellular organism somatic cells. Mol. Reprod. Dev. 83: 387-391, 2016. © 2016 Wiley Periodicals, Inc.

Expression reduction in mammalian X chromosome evolution refutes Ohno's hypothesis of dosage compensation.

Susumu Ohno proposed in 1967 that, during the origin of mammalian sex chromosomes from a pair of autosomes, per-allele expression levels of X-linked genes were doubled to compensate for the degeneration of their Y homologs. This conjecture forms the foundation of the current evolutionary model of sex chromosome dosage compensation, but has been tested in mammals only indirectly via a comparison of expression levels between X-linked and autosomal genes in the same genome. The test results have been controversial, because examinations of different gene sets led to different conclusions that either support or refute Ohno's hypothesis. Here we resolve this uncertainty by directly comparing mammalian X-linked genes with their one-to-one orthologs in species that diverged before the origin of the mammalian sex chromosomes. Analyses of RNA sequencing data and proteomic data provide unambiguous evidence for expression halving (i.e., no change in per-allele expression level) of X-linked genes during evolution, with the exception of only ∼5% of genes that encode members of large protein complexes. We conclude that Ohno's hypothesis is rejected for the vast majority of genes, reopening the search for the evolutionary force driving the origin of chromosome-wide X inactivation in female mammals.

Measuring the evolutionary rate of protein-protein interaction.

Despite our extensive knowledge about the rate of protein sequence evolution for thousands of genes in hundreds of species, the corresponding rate of protein function evolution is virtually unknown, especially at the genomic scale. This lack of knowledge is primarily because of the huge diversity in protein function and the consequent difficulty in gauging and comparing rates of protein function evolution. Nevertheless, most proteins function through interacting with other proteins, and protein-protein interaction (PPI) can be tested by standard assays. Thus, the rate of protein function evolution may be measured by the rate of PPI evolution. Here, we experimentally examine 87 potential interactions between Kluyveromyces waltii proteins, whose one to one orthologs in the related budding yeast Saccharomyces cerevisiae have been reported to interact. Combining our results with available data from other eukaryotes, we estimate that the evolutionary rate of protein interaction is (2.6 ± 1.6) × 10(-10) per PPI per year, which is three orders of magnitude lower than the rate of protein sequence evolution measured by the number of amino acid substitutions per protein per year. The extremely slow evolution of protein molecular function may account for the remarkable conservation of life at molecular and cellular levels and allow for studying the mechanistic basis of human disease in much simpler organisms.

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, a substitution mutation-aided lineage-tracing system (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.

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.