Canalization of Phenotypes-When the Transcriptome is Constantly but Weakly Perturbed.

Recent studies have increasingly pointed to microRNAs (miRNAs) as the agent of gene regulatory network (GRN) stabilization as well as developmental canalization against constant but small environmental perturbations. To analyze mild perturbations, we construct a Dicer-1 knockdown line (dcr-1 KD) in Drosophila that modestly reduces all miRNAs by, on average, ∼20%. The defining characteristic of stabilizers is that, when their capacity is compromised, GRNs do not change their short-term behaviors. Indeed, even with such broad reductions across all miRNAs, the changes in the transcriptome are very modest during development in stable environment. By comparison, broad knockdowns of other regulatory genes (esp. transcription factors) by the same method should lead to drastic changes in the GRNs. The consequence of destabilization may thus be in long-term development as postulated by the theory of canalization. Flies with modest miRNA reductions may gradually deviate from the developmental norm, resulting in late-stage failures such as shortened longevity. In the optimal culture condition, the survival to adulthood is indeed normal in the dcr-1 KD line but, importantly, adult longevity is reduced by ∼90%. When flies are stressed by high temperature, dcr-1 KD induces lethality earlier in late pupation and, as the perturbations are shifted earlier, the affected stages are shifted correspondingly. Hence, in late stages of development with deviations piling up, GRN would be increasingly in need of stabilization. In conclusion, miRNAs appear to be a solution to weak but constant environmental perturbations.

Intra- vs. Interhost Evolution of SARS-CoV-2 Driven by Uncorrelated Selection-The Evolution Thwarted.

In viral evolution, a new mutation has to proliferate within the host (Stage I) in order to be transmitted and then compete in the host population (Stage II). We now analyze the intrahost single nucleotide variants (iSNVs) in a set of 79 SARS-CoV-2 infected patients with most transmissions tracked. Here, every mutation has two measures: 1) iSNV frequency within each individual host in Stage I; 2) occurrence among individuals ranging from 1 (private), 2-78 (public), to 79 (global) occurrences in Stage II. In Stage I, a small fraction of nonsynonymous iSNVs are sufficiently advantageous to rise to a high frequency, often 100%. However, such iSNVs usually fail to become public mutations. Thus, the selective forces in the two stages of evolution are uncorrelated and, possibly, antagonistic. For that reason, successful mutants, including many variants of concern, have to avoid being eliminated in Stage I when they first emerge. As a result, they may not have the transmission advantage to outcompete the dominant strains and, hence, are rare in the host population. Few of them could manage to slowly accumulate advantageous mutations to compete in Stage II. When they do, they would appear suddenly as in each of the six successive waves of SARS-CoV-2 strains. In conclusion, Stage I evolution, the gate-keeper, may contravene the long-term viral evolution and should be heeded in viral studies.

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.

Mutations Beget More Mutations-Rapid Evolution of Mutation Rate in Response to the Risk of Runaway Accumulation.

The rapidity with which the mutation rate evolves could greatly impact evolutionary patterns. Nevertheless, most studies simply assume a constant rate in the time scale of interest (Kimura 1983; Drake 1991; Kumar 2005; Li 2007; Lynch 2010). In contrast, recent studies of somatic mutations suggest that the mutation rate may vary by several orders of magnitude within a lifetime (Kandoth et al. 2013; Lawrence et al. 2013). To resolve the discrepancy, we now propose a runaway model, applicable to both the germline and soma, whereby mutator mutations form a positive-feedback loop. In this loop, any mutator mutation would increase the rate of acquiring the next mutator, thus triggering a runaway escalation in mutation rate. The process can be initiated more readily if there are many weak mutators than a few strong ones. Interestingly, even a small increase in the mutation rate at birth could trigger the runaway process, resulting in unfit progeny. In slowly reproducing species, the need to minimize the risk of this uncontrolled accumulation would thus favor setting the mutation rate low. In comparison, species that starts and ends reproduction sooner do not face the risk and may set the baseline mutation rate higher. The mutation rate would evolve in response to the risk of runaway mutation, in particular, when the generation time changes. A rapidly evolving mutation rate may shed new lights on many evolutionary phenomena (Elango et al. 2006; Thomas et al. 2010, 2018; Langergraber et al. 2012; Besenbacher et al. 2019).

Tumorigenesis as the Paradigm of Quasi-neutral Molecular Evolution.

In the absence of both positive and negative selections, coding sequences evolve at a neutral rate (R = 1). Such a high genomic rate is generally not achievable due to the prevalence of negative selection against codon substitutions. Remarkably, somatic evolution exhibits the seemingly neutral rate R ∼ 1 across normal and cancerous tissues. Nevertheless, R ∼ 1 may also mean that positive and negative selections are both strong, but equal in intensity. We refer to this regime as quasi-neutral. Indeed, individual genes in cancer cells often evolve at a much higher, or lower, rate than R ∼ 1. Here, we show that 1) quasi-neutrality is much more likely when populations are small (N < 50); 2) stem-cell populations in single normal tissue niches, from which tumors likely emerge, have a small N (usually <50) but selection at this stage is measurable and strong; 3) when N dips below 50, selection efficacy decreases precipitously; and 4) notably, N is smaller in the stem-cell niche of the small intestine than in the colon. Hence, the ∼70-fold higher rate of phenotypic evolution (observed as cancer risk) in the latter can be explained by the greater efficacy of selection, which then leads to the fixation of more advantageous and fewer deleterious mutations in colon cancers. In conclusion, quasi-neutral evolution sheds a new light on a general evolutionary principle that helps to explain aspects of cancer evolution.

Molecular Evolution in Large Steps-Codon Substitutions under Positive Selection.

Molecular evolution is believed to proceed in small steps. The step size can be defined by a distance reflecting physico-chemical disparities between amino acid (AA) pairs that can be exchanged by single 1-bp mutations. We show that AA substitution rates are strongly and negatively correlated with this distance but only when positive selection is relatively weak. We use the McDonald and Kreitman test to separate the influences of positive and negative selection. While negative selection is indeed stronger on AA substitutions generating larger changes in chemical properties of AAs, positive selection operates by different rules. For 65 of the 75 possible pairs, positive selection is comparable in strength regardless of AA distance. However, the ten pairs under the strongest positive selection all exhibit large leaps in chemical properties. Five of the ten pairs are shared between Drosophila and Hominoids, thus hinting at a common but modest biochemical basis of adaptation across taxa. The hypothesis that adaptive changes often take large functional steps will need to be extensively tested. If validated, molecular models will need to better integrate positive and negative selection in the search for adaptive signal.

Two evolutionary histories in the genome of rice: the roles of domestication genes.

Genealogical patterns in different genomic regions may be different due to the joint influence of gene flow and selection. The existence of two subspecies of cultivated rice provides a unique opportunity for analyzing these effects during domestication. We chose 66 accessions from the three rice taxa (about 22 each from Oryza sativa indica, O. sativa japonica, and O. rufipogon) for whole-genome sequencing. In the search for the signature of selection, we focus on low diversity regions (LDRs) shared by both cultivars. We found that the genealogical histories of these overlapping LDRs are distinct from the genomic background. While indica and japonica genomes generally appear to be of independent origin, many overlapping LDRs may have originated only once, as a result of selection and subsequent introgression. Interestingly, many such LDRs contain only one candidate gene of rice domestication, and several known domestication genes have indeed been "rediscovered" by this approach. In summary, we identified 13 additional candidate genes of domestication.

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.

Very large hidden genetic diversity in one single tumor: evidence for tumors-in-tumor.

Despite the concern of within-tumor genetic diversity, this diversity is in fact limited by the kinship among cells in the tumor. Indeed, genomic studies have amply supported the 'Nowell dogma' whereby cells of the same tumor descend from a single progenitor cell. In parallel, genomic data also suggest that the diversity could be >10-fold larger if tumor cells are of multiple origins. We develop an evolutionary hypothesis that a single tumor may often harbor multiple cell clones of independent origins, but only one would be large enough to be detected. To test the hypothesis, we search for independent tumors within a larger one (or tumors-in-tumor). Very high density sampling was done on two cases of colon tumors. Case 1 indeed has 13 independent clones of disparate sizes, many having heavy mutation burdens and potentially highly tumorigenic. In Case 2, despite a very intensive search, only two small independent clones could be found. The two cases show very similar movements and metastasis of the dominant clone. Cells initially move actively in the expanding tumor but become nearly immobile in late stages. In conclusion, tumors-in-tumor are plausible but could be very demanding to find. Despite their small sizes, they can enhance the within-tumor diversity by orders of magnitude. Such increases may contribute to the missing genetic diversity associated with the resistance to cancer therapy.

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.

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).

Application of Layered Coding Genetic Algorithm in Optimization of Unequal Area Production Facilities Layout.

Unequal area facilities layout problem (UA-FLP) is an inevitable problem in the process of new construction, reconstruction, and expansion of enterprises. The rationality of the facilities layout has a great influence on the operation performance of the production system. Finding the optimal solution of UA-FLP according to the requirement of production process is the main content of the plant design. The facilities were constrained by given areas and aspect ratio, respectively. By adopting the method of slicing tree, the layout space was divided into multiple regions for each facility. The genetic algorithm was developed by using layered coding to show the slicing process. Considering the production logistics cost as well as the adjacency relations between the facilities, the goal function was established and the optimal solution was obtained by running the proposed algorithm. Finally, the feasibility of the proposed approach was validated by a set of known problems. The comparison results show that it can provide decision support for rapid optimal layout of multifacilities.

Design and Analysis of a Turning Dynamometer Embedded in Thin-Film Sensor.

This paper proposes a high-strain sensitivity turning dynamometer that combines several thin-film resistor grids into three Wheatstone full-bridge circuits that can measure triaxial cutting forces. This dynamometer can replace different cutter heads using flange connections. In order to improve the strain effect of the dynamometer, the strain film sensor is fixed on the regular octagonal connection plates on both ends of the elastomer by vacuum brazing, and the stepped groove structure is also designed inside the elastomer. The dynamometer model is simplified as a four-segment cantilever beam which has different sections. The measurement mechanism model of the dynamometer system is established by the transformation relationship between deflection and strain, under external force. The standard turning tool of 20 mm square is used as a reference. The influence of the structural dimensions of the dynamometer on its strain sensitivity coefficient K is studied. The applicability of the theoretical model of dynamometer strain is verified by finite element analysis. Finally, the dynamometer with the largest K value is subjected to the bending test and compared with a standard turning tool. The experimental results show that the measurement sensitivity of the dynamometer is 2.32 times greater than that of the standard turning tool. The results also show that this dynamometer can effectively avoid the influence of the pasting process on strain transmission, thus indicating its great potential for measuring cutting force in the future.

Recurrent ECSIT mutation encoding V140A triggers hyperinflammation and promotes hemophagocytic syndrome in extranodal NK/T cell lymphoma.

Hemophagocytic syndrome (HPS) is a fatal hyperinflammatory disease with a poorly understood mechanism that occurs most frequently in extranodal natural killer/T cell lymphoma (ENKTL). Through exome sequencing of ENKTL tumor-normal samples, we have identified a hotspot mutation (c.419T>C) in the evolutionarily conserved signaling intermediate in Toll pathway (ECSIT) gene, encoding a V140A variant of ECSIT. ECSIT-V140A activated NF-κB more potently than the wild-type protein owing to its increased affinity for the S100A8 and S100A9 heterodimer, which promotes NADPH oxidase activity. ECSIT-T419C knock-in mice showed higher peritoneal NADPH oxidase activity than mice with wild-type ECSIT in response to LPS. ECSIT-T419C-transfected ENKTL cell lines produced tumor necrosis factor (TNF)-α and interferon (IFN)-γ, which induced macrophage activation and massive cytokine secretion in cell culture and mouse xenografts. In individuals with ENKTL, ECSIT-V140A was associated with activation of NF-κB, higher HPS incidence, and poor prognosis. The immunosuppressive drug thalidomide prevented NF-κB from binding to the promoters of its target genes (including TNF and IFNG), and combination treatment with thalidomide and dexamethasone extended survival of mice engrafted with ECSIT-T419C-transfected ENKTL cells. We added thalidomide to the conventional dexamethasone-containing therapy regimen for two patients with HPS who expressed ECSIT-V140A, and we observed reversal of their HPS and disease-free survival for longer than 3 years. These findings provide mechanistic insights and a potential therapeutic strategy for ENKTL-associated HPS.

A mathematical theory of the transcription repression (TR) therapy of cancer - whether and how it may work.

Transcription repression (TR) therapy of cancer has been widely discussed. Here, TR refers to global repression of transcription rather than specific targeting of cancer-causing genes such as MYC. TR drugs inhibit transcription by binding to the transcribed DNA or to RNA polymerase; for example, actinomycin D has been extensively used in research and therapy to shut down transcription globally [1-7]. As proliferating cells demand a high rate of transcription, restricting transcript production could be effective in slowing down cell proliferation. However, TR also deprives other less proliferative cells of new transcripts, thus leading to substantial toxicity [1, 8, 9]. We now develop a mathematical theory to exploit the greater demand for transcription in highly proliferating cells. A new strategy, referred to as the TRR (transcript repression-recovery) model, would insert a recovery phase to allow the more slowly proliferating cells to recover. It is most effective to have strong blocking for a short period (a few hours) followed by a longer recovery phase in each cell cycle. Hence, TRR can potentially achieve selective killing of cells based on their global transcription needs but precise fine-tuning is necessary.