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Abstract To understand the relative importance of cis and trans effects on regulation, we crossed multi-parent recombinant-inbred-lines (RILs) to a common tester and measured allele specific gene expression in the offspring. Testing difference of allelic imbalance between two RIL x Tester crosses is a test of cis or trans depending on the RIL alleles compared. The study design also enables to separate two sources of trans variation, genetic and environmental, detected via interactions with cis effects. We demonstrate the effectiveness of this approach in a long-read RNA-seq experiment in female abdominal tissue at two time points in Drosophila melanogaster. Among the 40% of all loci that show evidence of genetic variation in cis, trans effects due to environment are detectable in 31% of loci and trans effects due to genetic background in 19%, with little overlap in sources of trans variation. The genes identified in this study are associated with genes previously reported to exhibit genetic variation in gene expression. Eleven genes in a QTL for thermotolerance, previously shown to differ in expression based on temperature, have evidence for regulation of gene expression regardless of the environment, including the cuticular protein Cpr67B, suggesting a functional role for standing variation in gene expression. This study provides a blueprint for identifying regulatory variation in gene expression, as the tester design maximizes cis variation and enables the efficient assessment of all pairs of RIL alleles relative to the tester, a much smaller study compared to the pairwise direct assessment. 

Objectives: An effective vaccine to SARS-CoV-2 cannot be successfully deployed if a significant number of people worldwide are unwilling to accept it. We investigated the relationship between trust in scientists and medical professionals and perceptions of vaccine safety and effectiveness. We also build on past studies by exploring the relationship between confidence in global health organizations and vaccine hesitancy. Methods: We conducted an online survey in seventeen countries/territories across five world regions between May -June 2020. We assessed the relationship between COVID19 vaccine hesitancy, confidence in public health organizations, and trust in key experts and leaders. Results: Our findings strongly suggest that confidence in the World Health Organization combined with trust in domestic scientists and healthcare professionals is a strong driver of vaccine acceptance across multiple countries/territories. Conclusion: We find that hesitancy is widespread, and uptake would be insufficient to achieve herd immunity. There is widespread confidence in how public health organizations have responded to the current pandemic and this is related to vaccine acceptance. Our results also highlight the important role of trust in health care providers and scientists in reducing COVID19 vaccine hesitancy. 

Plant growth, development, and nutritional quality depends upon amino acid homeostasis, especially in seeds. However, our understanding of the underlying genetics influencing amino acid content and composition remains limited, with only a few candidate genes and quantitative trait loci identified to date. Improved knowledge of the genetics and biological processes that determine amino acid levels will enable researchers to use this information for plant breeding and biological discovery. Toward this goal, we used genomic prediction to identify biological processes that are associated with, and therefore potentially influence, free amino acid (FAA) composition in seeds of the model plant Arabidopsis thaliana . Markers were split into categories based on metabolic pathway annotations and fit using a genomic partitioning model to evaluate the influence of each pathway on heritability explained, model fit, and predictive ability. Selected pathways included processes known to influence FAA composition, albeit to an unknown degree, and spanned four categories: amino acid, core, specialized, and protein metabolism. Using this approach, we identified associations for pathways containing known variants for FAA traits, in addition to finding new trait-pathway associations. Markers related to amino acid metabolism, which are directly involved in FAA regulation, improved predictive ability for branched chain amino acids and histidine. The use of genomic partitioning also revealed patterns across biochemical families, in which serine-derived FAAs were associated with protein related annotations and aromatic FAAs were associated with specialized metabolic pathways. Taken together, these findings provide evidence that genomic partitioning is a viable strategy to uncover the relative contributions of biological processes to FAA traits in seeds, offering a promising framework to guide hypothesis testing and narrow the search space for candidate genes. 

Abstract Learning and memory are critical functions for all animals, giving individuals the ability to respond to changes in their environment. Within populations, individuals vary, however the mechanisms underlying this variation in performance are largely unknown. Thus, it remains to be determined what genetic factors cause an individual to have high learning ability and what factors determine how well an individual will remember what they have learned. To genetically dissect learning and memory performance, we used theDrosophilasynthetic population resource (DSPR), a multiparent mapping resource in the model systemDrosophila melanogaster, consisting of a large set of recombinant inbred lines (RILs) that naturally vary in these and other traits. Fruit flies can be trained in a “heat box” to learn to remain on one side of a chamber (place learning) and can remember this (place memory) over short timescales. Using this paradigm, we measured place learning and memory for ~49 000 individual flies from over 700 DSPR RILs. We identified 16 different loci across the genome that significantly affect place learning and/or memory performance, with 5 of these loci affecting both traits. To identify transcriptomic differences associated with performance, we performed RNA‐Seq on pooled samples of seven high performing and seven low performing RILs for both learning and memory and identified hundreds of genes with differences in expression in the two sets. Integrating our transcriptomic results with the mapping results allowed us to identify nine promising candidate genes, advancing our understanding of the genetic basis underlying natural variation in learning and memory performance.