Large-scale mutant libraries have been indispensable for genetic studies, and the development of next-generation genome sequencing technologies has greatly advanced efforts to analyze mutants. In this work, we sequenced the genomes of 660 Chlamydomonas reinhardtii acetate-requiring mutants, part of a larger photosynthesis mutant collection previously generated by insertional mutagenesis with a linearized plasmid. We identified 554 insertion events from 509 mutants by mapping the plasmid insertion sites through paired-end sequences, in which one end aligned to the plasmid and the other to a chromosomal location. Nearly all (96%) of the events were associated with deletions, duplications, or more complex rearrangements of genomic DNA at the sites of plasmid insertion, and together with deletions that were unassociated with a plasmid insertion, 1470 genes were identified to be affected. Functional annotations of these genes were enriched in those related to photosynthesis, signaling, and tetrapyrrole synthesis as would be expected from a library enriched for photosynthesis mutants. Systematic manual analysis of the disrupted genes for each mutant generated a list of 253 higher-confidence candidate photosynthesis genes, and we experimentally validated two genes that are essential for photoautotrophic growth, CrLPA3 and CrPSBP4. The inventory of candidate genes includes 53 genes from a phylogenomically defined set of conserved genes in green algae and plants. Altogether, 70 candidate genes encode proteins with previously characterized functions in photosynthesis in Chlamydomonas, land plants, and/or cyanobacteria, 14 genes encode proteins previously shown to have functions unrelated to photosynthesis. Among the remaining 169 uncharacterized genes, 38 genes encode proteins without any functional annotation, signifying that our results connect a function related to photosynthesis to these previously unknown proteins. This mutant library, with genome sequences that reveal the molecular extent of the chromosomal lesions and resulting higher-confidence candidate genes, will aid in advancing gene discovery and protein functional analysis in photosynthesis.

The COVID-19 pandemic has had a significant impact on mental health. Identifying risk factors and susceptible subgroups will guide efforts to address mental health concerns during the pandemic and long-term management and monitoring after the pandemic. We aimed to examine associations of insecurity (concerns about food, health insurance, and/or money), social support, and change in family relationships with poor mental health and to explore disparities in these associations. An online survey was collected from 3952 US adults between May and August 2020. Symptoms of anxiety, depression, stress, and trauma-related disorders were assessed by the Generalized Anxiety Disorder 7-item scale, the Patient Health Questionnaire-9, the Perceived Stress Scale-4, and the Primary Care Post-Traumatic Stress Disorder Screen, respectively. Social support was measured by the Oslo Social Support Scale. Logistic regression was used and stratified analyses by age, race/ethnicity, and sex were performed. We found a higher prevalence of poor mental health among those who were younger, female, with lower socioeconomic status, and racial/ethnic minorities. Participants who were worried about money, health insurance, or food had higher odds of symptoms of anxiety (OR = 3.74, 95% CI: 3.06–4.56), depression (OR = 3.20, 95% CI: 2.67–3.84), stress (OR = 3.08, 95% CI: 2.67–3.57), and trauma-related disorders (OR = 2.93, 95% CI: 2.42–3.55) compared to those who were not. Compared to poor social support, moderate and strong social support was associated with lower odds of all four symptoms. Participants who had changes in relationships with parents, children, or significant others had worse mental health. Our findings identified groups at higher risk for poor mental health, which offers insights for implementing targeted interventions.

We conducted a case-control study (532 cases and 532 control) in Chinese adults to investigate the independent and interactive effects of dietary nutrients (pro- or anti-inflammation) on Esophageal Squamous Cell Carcinoma (ESCC) risk. Dietary data were collected using a food questionnaire survey that included 171 items. Two algorithms, the Least Absolute Shrinkage and Selector Operation (LASSO) and Bayesian Kernel Machine Regression (BKMR) were employed to select indicators and evaluate the interactive effect of nutrients’ mixture on ESCC risk. Thirteen nutrients were selected, including three pro-inflammatory nutrients (protein, fat and carbohydrate) and ten anti-inflammatory nutrients (fiber, Vitamin A, riboflavin, niacin, Vitamin C, Fe, Se, MUFA, n-3 PUFA and n-6 PUFA). Single-exposure effects of fat, carbohydrate and fiber significantly contributed to ESCC risk. The pro-inflammatory nutrients’ submodel discovered that the combined effect was statistically associated with increased ESCC risk. In addition, a higher fat level was significantly associated with ESCC risk. On the contrary, for fiber and riboflavin, the anti-inflammatory nutrients’ submodel delineated a significant negative effect on the risk of ESCC. Our result implies that dietary nutrients and their inflammatory traits significantly impacted ESCC occurrence. Additional studies are warranted to verify our findings.

Large-scale mutant libraries have been indispensable for genetic studies, and the development of next-generation genome sequencing technologies has greatly advanced efforts to analyze mutants. In this work, we sequenced the genomes of 660 Chlamydomonas reinhardtii acetate-requiring mutants, part of a larger photosynthesis mutant collection previously generated by insertional mutagenesis with a linearized plasmid. We identified 554 insertion events from 509 mutants by mapping the plasmid insertion sites through paired-end sequences, in which one end aligned to the plasmid and the other to a chromosomal location. Nearly all (96%) of the events were associated with deletions, duplications, or more complex rearrangements of genomic DNA at the sites of plasmid insertion, and 1405 genes in total were affected. Functional annotations of these genes were enriched in those related to photosynthesis, signaling, and tetrapyrrole synthesis as would be expected from a library enriched for photosynthesis mutants. Systematic manual analysis of the disrupted genes for each mutant generated a list of 273 higher-confidence candidate photosynthesis genes, and we experimentally validated two genes that are essential for photoautotrophic growth, CrLPA3 and CrPSBP4. The inventory of candidate genes includes 55 genes from a phylogenomically defined set of conserved genes in green algae and plants. Altogether, 68 candidate genes encode proteins with previously characterized functions in photosynthesis in Chlamydomonas, land plants, and/or cyanobacteria, 15 genes encode proteins previously shown to have functions unrelated to photosynthesis, and 190 genes encode proteins without any functional annotation, signifying that our results connect a function related to photosynthesis to these previously unknown proteins. This mutant library, with genome sequences that reveal the molecular extent of the chromosomal lesions and resulting higher-confidence candidate genes, represents a rich resource for gene discovery and protein functional analysis in photosynthesis.