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Height is one of the most heritable and easily measured traits in maize (Zea mays L.). Given a pedigree or estimates of the genomic identity-by-state (IBS) among related plants, height is also accurately predictable. But, mapping alleles explaining natural variation in maize height remains a formidable challenge. To address this challenge, we measured the plant height, ear height, flowering time, and node counts of plants grown in >64,500 plots across 13 environments. These plots contained >7,300 inbreds representing most publically available maize inbreds in the U.S.A. as well as families of the maize Nested Association Mapping (NAM) panel. Joint-linkage mapping of quantitative trait loci (QTL), fine mapping in near isogenic lines (NILs), genome wide association studies (GWAS), and genomic best linear unbiased prediction (GBLUP) were performed. The heritability of plant height was estimated to be over 90%. Mapping of NAM family-nested QTL revealed the largest explained about 2.1 ± 0.9% of height variation. The effects of two tropical alleles at this QTL were independently validated by fine mapping. Several significant associations found by GWAS co-localized with established height loci including brassinosteroid-deficient dwarf1, dwarf plant1, and semi-dwarf2. GBLUP explained >80% of plant height variation in the observed panels and outperformed bootstrap aggregation of family-nested QTL models in evaluations of prediction accuracy. These results revealed maize height was under strong genetic control and had a highly polygenic genetic architecture. They also showed that multiple models of genetic architecture differing in polygenicity and effect sizes can plausibly explain a population’s variation in maize height, but they may vary in predictive efficacy.

Abstract Single-cross hybrids have been critical to the improvement of maize (Zea mays L.), but the characterization of their genetic architectures remains challenging. Previous studies of hybrid maize have shown the contribution of within-locus complementation effects (dominance) and their differential importance across functional classes of loci. However, they have generally considered panels of limited genetic diversity, and have shown little benefit from genomic prediction based on dominance or functional enrichments. This study investigates the relevance of dominance and functional classes of variants in genomic models for agronomic traits in diverse populations of hybrid maize. We based our analyses on a diverse panel of inbred lines crossed with two testers representative of the major heterotic groups in the U.S. (1106 hybrids), as well as a collection of 24 biparental populations crossed with a single tester (1640 hybrids). We investigated three agronomic traits: days to silking (DTS), plant height (PH), and grain yield (GY). Our results point to the presence of dominance for all traits, but also among-locus complementation (epistasis) for DTS and genotype-by-environment interactions for GY. Consistently, dominance improved genomic prediction for PH only. In addition, we assessed enrichment of genetic effects in classes defined by genic regions (gene annotation), structural features (recombination rate and chromatin openness), and evolutionary features (minor allele frequency and evolutionary constraint). We found support for enrichment in genic regions and subsequent improvement of genomic prediction for all traits. Our results suggest that dominance and gene annotations improve genomic prediction across diverse populations in hybrid maize.

Single-cross hybrids have been critical to the improvement of maize (Zea mays L.), but the characterization of their genetic architectures remains challenging. Previous studies of hybrid maize have shown the contribution of within-locus complementation effects (dominance) and their differential importance across functional classes of loci. However, they have generally considered panels of limited genetic diversity, and have shown little benefit from genomic prediction based on dominance or functional enrichments. This study investigates the relevance of dominance and functional classes of variants in genomic models for agronomic traits in diverse populations of hybrid maize. We based our analyses on a diverse panel of inbred lines crossed with two testers representative of the major heterotic groups in the U.S. (1106 hybrids), as well as a collection of 24 biparental populations crossed with a single tester (1640 hybrids). We investigated three agronomic traits: days to silking (DTS), plant height (PH), and grain yield (GY). Our results point to the presence of dominance for all traits, but also among-locus complementation (epistasis) for DTS and genotype-by-environment interactions for GY. Consistently, dominance improved genomic prediction for PH only. In addition, we assessed enrichment of genetic effects in classes defined by genic regions (gene annotation), structural features (recombination rate and chromatin openness), and evolutionary features (minor allele frequency and evolutionary constraint). We found support for enrichment in genic regions and subsequent improvement of genomic prediction for all traits. Our results suggest that dominance and gene annotations improve genomic prediction across diverse populations in hybrid maize.

Heterosis has been key to the development of maize breeding but describing its genetic basis has been challenging. Previous studies of heterosis have shown the contribution of within-locus complementation effects (dominance) and their differential importance across genomic regions. However, they have generally considered panels of limited genetic diversity and have shown little benefit to including dominance effects for predicting genotypic value in breeding populations. This study examined within-locus complementation and enrichment of genetic effects by functional classes in maize. We based our analyses on a diverse panel of inbred lines crossed with two testers representative of the major heterotic groups in the United States (1,106 hybrids), as well as a collection of 24 biparental populations crossed with a single tester (1,640 hybrids). We assayed three agronomic traits: days to silking (DTS), plant height (PH) and grain yield (GY). Our results point to the presence of dominance for all traits, but also among-locus complementation (epistasis) for DTS and genotype-by-environment interactions for GY. Consistently, dominance improved genomic prediction for PH only. In addition, we assessed enrichment of genetic effects in classes defined by genic regions (gene annotation), structural features (recombination rate and chromatin openness), and evolutionary features (minor allele frequency and evolutionary constraint). We found support for enrichment in genic regions and subsequent improvement of genomic prediction for all traits. Our results point to mechanisms by which heterosis arises through local complementation in proximal gene regions and suggest the relevance of dominance and gene annotations for genomic prediction in maize.

Background Insomnia symptoms are widespread in the population and might have effects on many chronic conditions and their risk factors but previous research has focused on select hypothesised associations/effects rather than taking a systematic hypothesis-free approach across many health outcomes. Methods We performed a Mendelian randomisation (MR) phenome-wide association study (PheWAS) in 336,975 unrelated white-British UK Biobank participants. Self-reported i nsomnia symptoms were instrumented by a genetic risk score (GRS) created from 129 single-nucleotide polymorphisms (SNPs). A total of 11,409 outcomes from UK Biobank were extracted and processed by an automated pipeline (PHESANT) for the MR-PheWAS. Potential causal effects (those passing a Bonferroni-corrected significance threshold) were followed up with two-sample MR in MR-Base, where possible. Results Four hundred thirty-seven potential causal effects of insomnia symptoms were observed for a diverse range of outcomes, including anxiety, depression, pain, body composition, respiratory, musculoskeletal and cardiovascular traits. We were able to undertake two-sample MR for 71 of these 437 and found evidence of causal effects (with directionally concordant effect estimates across main and sensitivity analyses) for 30 of these. These included novel findings (by which we mean not extensively explored in conventional observational studies and not previously explored using MR based on a systematic search) of an adverse effect on risk of spondylosis (OR [95%CI] = 1.55 [1.33, 1.81]) and bronchitis (OR [95%CI] = 1.12 [1.03, 1.22]), among others. Conclusions Insomnia symptoms potentially cause a wide range of adverse health-related outcomes and behaviours. This has implications for developing interventions to prevent and treat a number of diseases in order to reduce multimorbidity and associated polypharmacy.

Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction 1 . There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity 1 , 2 . Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments. Single-cell transcriptomic and proteomic data from synovial tissue from individuals with rheumatoid arthritis classify patients into groups based on abundance of cell states that can provide insights into pathology and predict individual treatment responses.

Horseshoe crabs have persisted for more than 200 million years, and fossil forms date to 450 million years ago. The American horseshoe crab ( Limulus polyphemus ), one of four extant horseshoe crab species, is found along the Atlantic coastline of North America ranging from Alabama to Maine, USA with another distinct population on the coasts of Campeche, Yucatán and Quintana Roo in the Yucatán Peninsula, México. Although the American horseshoe crab tolerates broad environmental conditions, exploitation and habitat loss threaten the species. We assessed the conservation status of the American horseshoe crab by comprehensively reviewing available scientific information on its range, life history, genetic structure, population trends and analyses, major threats, and conservation. We structured the status assessment by six genetically-informed regions and accounted for sub-regional differences in environmental conditions, threats, and management. The transnational regions are Gulf of Maine (USA), Mid-Atlantic (USA), Southeast (USA), Florida Atlantic (USA), Northeast Gulf of México (USA), and Yucatán Peninsula (México). Our conclusion is that the American horseshoe crab species is vulnerable to local extirpation and that the degree and extent of risk vary among and within the regions. The risk is elevated in the Gulf of Maine region due to limited and fragmented habitat. The populations of horseshoe crabs in the Mid-Atlantic region are stable in the Delaware Bay area, and regulatory controls are in place, but the risk is elevated in the New England area as evidenced by continuing declines understood to be caused by over-harvest. The populations of horseshoe crabs in the Southeast region are stable or increasing. The populations of horseshoe crabs in the Florida Atlantic region show mixed trends among areas, and continuing population reductions at the embayment level have poorly understood causes. Within the Northeast Gulf of Mexico, causes of population trends are poorly understood and currently there is no active management of horseshoe crabs. Horseshoe crabs within México have conservation protection based on limited and fragmented habitat and geographic isolation from other regions, but elevated risk applies to the horseshoe crabs in the Yucatán Peninsula region until sufficient data can confirm population stability. Future species status throughout its range will depend on the effectiveness of conservation to mitigate habitat loss and manage for sustainable harvest among and within regions.

We find that several key endogenous protein structures give rise to intense second-harmonic generation (SHG)—nonabsorptive frequency doubling of an excitation laser line. Second-harmonic imaging microscopy (SHIM) on a laser-scanning system proves, therefore, to be a powerful and unique tool for high-resolution, high-contrast, three-dimensional studies of live cell and tissue architecture. Unlike fluorescence, SHG suffers no inherent photobleaching or toxicity and does not require exogenous labels. Unlike polarization microscopy, SHIM provides intrinsic confocality and deep sectioning in complex tissues. In this study, we demonstrate the clarity of SHIM optical sectioning within unfixed, unstained thick specimens. SHIM and two-photon excited fluorescence (TPEF) were combined in a dual-mode nonlinear microscopy to elucidate the molecular sources of SHG in live cells and tissues. SHG arose not only from coiled-coil complexes within connective tissues and muscle thick filaments, but also from microtubule arrays within interphase and mitotic cells. Both polarization dependence and a local symmetry cancellation effect of SHG allowed the signal from species generating the second harmonic to be decoded, by ratiometric correlation with TPEF, to yield information on local structure below optical resolution. The physical origin of SHG within these tissues is addressed and is attributed to the laser interaction with dipolar protein structures that is enhanced by the intrinsic chirality of the protein helices.

Tuberculosis (TB) was once a major killer in Europe, but it is unclear how the strains and patterns of infection at ‘peak TB’ relate to what we see today. Here we describe 14 genome sequences of M. tuberculosis , representing 12 distinct genotypes, obtained from human remains from eighteenth-century Hungary using metagenomics. All our historic genotypes belong to M. tuberculosis Lineage 4. Bayesian phylogenetic dating, based on samples with well-documented dates, places the most recent common ancestor of this lineage in the late Roman period. We find that most bodies yielded more than one M. tuberculosis genotype and we document an intimate epidemiological link between infections in two long-dead individuals. Our results suggest that metagenomic approaches usefully inform detection and characterization of historical and contemporary infections. Tuberculosis was once a major killer in Europe. Here the authors use metagenomics to obtain genomic sequences of Mycobacterium tuberculosis from human remains from eighteenth-century Hungary, revealing mixed infections within individuals as well as presence of the same strain in two individuals.