Convergent evolution of desiccation tolerance in grasses.

Desiccation tolerance has evolved repeatedly in plants as an adaptation to survive extreme environments. Plants use similar biophysical and cellular mechanisms to survive life without water, but convergence at the molecular, gene and regulatory levels remains to be tested. Here we explore the evolutionary mechanisms underlying the recurrent evolution of desiccation tolerance across grasses. We observed substantial convergence in gene duplication and expression patterns associated with desiccation. Syntenic genes of shared origin are activated across species, indicative of parallel evolution. In other cases, similar metabolic pathways are induced but using different gene sets, pointing towards phenotypic convergence. Species-specific mechanisms supplement these shared core mechanisms, underlining the complexity and diversity of evolutionary adaptations to drought. Our findings provide insight into the evolutionary processes driving desiccation tolerance and highlight the roles of parallel and convergent evolution in response to environmental challenges.

Variability in drought gene expression datasets highlight the need for community standardization.

Physiologically relevant drought stress is difficult to apply consistently, and the heterogeneity in experimental design, growth conditions, and sampling schemes make it challenging to compare water deficit studies in plants. Here, we re-analyzed hundreds of drought gene expression experiments across diverse model and crop species and quantified the variability across studies. We found that drought studies are surprisingly uncomparable, even when accounting for differences in genotype, environment, drought severity, and method of drying. Many studies, including most Arabidopsis work, lack high-quality phenotypic and physiological datasets to accompany gene expression, making it impossible to assess the severity or in some cases the occurrence of water deficit stress events. From these datasets, we developed supervised learning classifiers that can accurately predict if RNA-seq samples have experienced a physiologically relevant drought stress, and suggest this can be used as a quality control for future studies. Together, our analyses highlight the need for more community standardization, and the importance of paired physiology data to quantify stress severity for reproducibility and future data analyses.

Single-cell profiling of vascular endothelial cells reveals progressive organ-specific vulnerabilities during obesity.

Obesity promotes diverse pathologies, including atherosclerosis and dementia, which frequently involve vascular defects and endothelial cell (EC) dysfunction. Each organ has distinct EC subtypes, but whether ECs are differentially affected by obesity is unknown. Here we use single-cell RNA sequencing to analyze transcriptomes of ~375,000 ECs from seven organs in male mice at progressive stages of obesity to identify organ-specific vulnerabilities. We find that obesity deregulates gene expression networks, including lipid handling, metabolic pathways and AP1 transcription factor and inflammatory signaling, in an organ- and EC-subtype-specific manner. The transcriptomic aberrations worsen with sustained obesity and are only partially mitigated by dietary intervention and weight loss. For example, dietary intervention substantially attenuates dysregulation of liver, but not kidney, EC transcriptomes. Through integration with human genome-wide association study data, we further identify a subset of vascular disease risk genes that are induced by obesity. Our work catalogs the impact of obesity on the endothelium, constitutes a useful resource and reveals leads for investigation as potential therapeutic targets.

Association Between Abnormal Fetal Head Growth and Autism Spectrum Disorder.

OBJECTIVE: Despite evidence for the prenatal onset of abnormal head growth in children with autism spectrum disorder (ASD), studies on fetal ultrasound data in ASD are limited and controversial. METHOD: We conducted a longitudinal matched case-sibling-control study on prenatal ultrasound biometric measures of children with ASD, and 2 control groups: (1) their own typically developed sibling (TDS) and (2) typically developed population (TDP). The cohort comprised 528 children (72.7% male), 174 with ASD, 178 TDS, and 176 TDP. RESULTS: During the second trimester, ASD and TDS fetuses had significantly smaller biparietal diameter (BPD) than TDP fetuses (adjusted odds ratio for the z score of BPD [aORzBPD] = 0.685, 95% CI = 0.527-0.890, and aORzBPD = 0.587, 95% CI = 0.459-0.751, respectively). However, these differences became statistically indistinguishable in the third trimester. Interestingly, head biometric measures varied by sex, with male fetuses having larger heads than female fetuses within and across groups. A linear mixed-effect model assessing the effects of sex and group assignment on fetal longitudinal head growth indicated faster BPD growth in TDS versus both ASD and TDP in male fetuses (ß = 0.084 and ß = 0.100 respectively; p < .001) but not in female fetuses, suggesting an ASD-sex interaction in head growth during gestation. Finally, fetal head growth showed conflicting correlations with ASD severity in male and female children across different gestation periods, thus further supporting the sex effect on the association between fetal head growth and ASD. CONCLUSION: Our findings suggest that abnormal fetal head growth is a familial trait of ASD, which is modulated by sex and is associated with the severity of the disorder. Thus, it could serve as an early biomarker for ASD.