A cell size threshold triggers commitment to stomatal fate in Arabidopsis.

How flexible developmental programs integrate information from internal and external factors to modulate stem cell behavior is a fundamental question in developmental biology. Cells of the Arabidopsis stomatal lineage modify the balance of stem cell proliferation and differentiation to adjust the size and cell type composition of mature leaves. Here, we report that meristemoids, one type of stomatal lineage stem cell, trigger the transition from asymmetric self-renewing divisions to commitment and terminal differentiation by crossing a critical cell size threshold. Through computational simulation, we demonstrate that this cell size-mediated transition allows robust, yet flexible termination of stem cell proliferation, and we observe adjustments in the number of divisions before the differentiation threshold under several genetic manipulations. We experimentally evaluate several mechanisms for cell size sensing, and our data suggest that this stomatal lineage transition is dependent on a nuclear factor that is sensitive to DNA content.

Function follows form: How cell size is harnessed for developmental decisions.

Cell size has profound effects on biological function, influencing a wide range of processes, including biosynthetic capacity, metabolism, and nutrient uptake. As a result, size is typically maintained within a narrow, population-specific range through size control mechanisms, which are an active area of study. While the physiological consequences of cell size are relatively well-characterized, less is known about its developmental consequences, and specifically its effects on developmental transitions. In this review, we compare systems where cell size is linked to developmental transitions, paying particular attention to examples from plants. We conclude by proposing that size can offer a simple readout of complex inputs, enabling flexible decisions during plant development.

The Household Secondary Attack Rate of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): A Rapid Review.

BACKGROUND: Although much of the public health effort to combat coronavirus disease 2019 (COVID-19) has focused on disease control strategies in public settings, transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within households remains an important problem. The nature and determinants of household transmission are poorly understood. METHODS: To address this gap, we gathered and analyzed data from 22 published and prepublished studies from 10 countries (20 291 household contacts) that were available through 2 September 2020. Our goal was to combine estimates of the SARS-CoV-2 household secondary attack rate (SAR) and to explore variation in estimates of the household SAR. RESULTS: The overall pooled random-effects estimate of the household SAR was 17.1% (95% confidence interval [CI], 13.7-21.2%). In study-level, random-effects meta-regressions stratified by testing frequency (1 test, 2 tests, >2 tests), SAR estimates were 9.2% (95% CI, 6.7-12.3%), 17.5% (95% CI, 13.9-21.8%), and 21.3% (95% CI, 13.8-31.3%), respectively. Household SARs tended to be higher among older adult contacts and among contacts of symptomatic cases. CONCLUSIONS: These findings suggest that SARs reported using a single follow-up test may be underestimated, and that testing household contacts of COVID-19 cases on multiple occasions may increase the yield for identifying secondary cases.

Effects of spatial patterning of co-flowering plant species on pollination quantity and purity.

Background and Aims: If two plant species share pollinators, it has been proposed that the interaction between them may range from competitive to facilitative, depending on the way in which they intermingle. In particular, the presence of a rewarding plant species may increase the rate of pollinator visitation to a less rewarding species in its vicinity, but the beneficial increase in visitation may be counteracted by a detrimental increase in heterospecific pollen transfer. We assessed this trade-off using bumble-bees foraging over a gradual spatial transition between two plant species in an indoor cage experiment. Methods: We used two 'species' of artificial flowers - one more rewarding than the other - in arrays that varied in the degree of species intermingling. The flowers dispensed and received powdered food dyes serving as pollen analogues. Captive bumble-bees visited to collect sucrose solution. We quantified dye delivery to the adhesive-tape 'stigmas' in flowers by spectrophotometry. Key Results: Across the spatial transition between species, the less attractive species received more dye (more bee visits) when in proximity to the more attractive species than it did when alone, but the larger dye loads were less pure (more heterospecific pollen transfer). The decline in purity cancelled out the gain in acquisition, so conspecific pollen receipt by the less attractive species was neutrally affected. The more attractive species received fewer visits when surrounded by the less attractive species, so the interaction between the two species was amensalism when considering conspecific pollen reception. Conclusions: Pollinator-mediated interactions between plant species depend on pollination quantity and purity, both of which can depend on spatial intermingling.

A note on measuring natural selection on principal component scores.

Measuring natural selection through the use of multiple regression has transformed our understanding of selection, although the methods used remain sensitive to the effects of multicollinearity due to highly correlated traits. While measuring selection on principal component (PC) scores is an apparent solution to this challenge, this approach has been heavily criticized due to difficulties in interpretation and relating PC axes back to the original traits. We describe and illustrate how to transform selection gradients for PC scores back into selection gradients for the original traits, addressing issues of multicollinearity and biological interpretation. In addition to reducing multicollinearity, we suggest that this method may have promise for measuring selection on high-dimensional data such as volatiles or gene expression traits. We demonstrate this approach with empirical data and examples from the literature, highlighting how selection estimates for PC scores can be interpreted while reducing the consequences of multicollinearity.