Heifer conception rate to the first service (HCR1) is defined as the number of heifers that become pregnant to the first breeding service compared to the heifers bred. This study aimed to identify loci associated and gene sets enriched for HCR1 for heifers that were bred by artificial insemination (AI, n = 2829) or were embryo transfer (ET, n = 2086) recipients, by completing a genome-wide association analysis and gene set enrichment analysis using SNP data (GSEA-SNP). Three unique loci, containing four positional candidate genes, were associated (p < 1 × 10-5) with HCR1 for ET recipients, while the GSEA-SNP identified four gene sets (NES ≥ 3) and sixty-two leading edge genes (LEGs) enriched for HCR1. While no loci were associated with HCR1 bred by AI, one gene set and twelve LEGs were enriched (NES ≥ 3) for HCR1 with the GSEA-SNP. This included one gene (PKD2) shared between HCR1 AI and ET services. Identifying loci associated or enriched for HCR1 provides an opportunity to use them as genomic selection tools to facilitate the selection of cattle with higher reproductive efficiency, and to better understand embryonic loss.

Phylogenetic analysis has entered the genomics (multilocus) era. For less experienced researchers, conquering the large number of software programs required for a multilocus-based phylogenetic reconstruction can be somewhat daunting and time-consuming. PhyloSuite, a software with a user-friendly GUI, was designed to make this process more accessible by integrating multiple software programs needed for multilocus and single-gene phylogenies and further streamlining the whole process. In this protocol, we aim to explain how to conduct each step of the phylogenetic pipeline and tree-based analyses in PhyloSuite. We also present a new version of PhyloSuite (v1.2.3), wherein we fixed some bugs, made some optimizations, and introduced some new functions, including a number of tree-based analyses, such as signal-to-noise calculation, saturation analysis, spurious species identification, and etc. The step-by-step protocol includes background information (i.e., what the step does), reasons (i.e., why do the step), and operations (i.e., how to do it). This protocol will help researchers quick-start their way through the multilocus phylogenetic analysis, especially those interested in conducting organelle-based analyses.

BACKGROUND: Theory and correlational research indicate organizational leadership and climate are important for successful implementation of evidence-based practices (EBPs) in healthcare settings; however, experimental evidence is lacking. We addressed this gap using data from the WISDOM (Working to Implement and Sustain Digital Outcome Measures) hybrid type III effectiveness-implementation trial. Primary outcomes from WISDOM indicated the Leadership and Organizational Change for Implementation (LOCI) strategy improved fidelity to measurement-based care (MBC) in youth mental health services. In this study, we tested LOCI\'s hypothesized mechanisms of change, namely: (1) LOCI will improve implementation and transformational leadership, which in turn will (2) mediate LOCI\'s effect on implementation climate, which in turn will (3) mediate LOCI\'s effect on MBC fidelity.
METHODS: Twenty-one outpatient mental health clinics serving youth were randomly assigned to LOCI plus MBC training and technical assistance or MBC training and technical assistance only. Clinicians rated their leaders\' implementation leadership, transformational leadership, and clinic implementation climate for MBC at five time points (baseline, 4-, 8-, 12-, and 18-months post-baseline). MBC fidelity was assessed using electronic metadata for youth outpatients who initiated treatment in the 12 months following MBC training. Hypotheses were tested using longitudinal mixed-effects models and multilevel mediation analyses.
RESULTS: LOCI significantly improved implementation leadership and implementation climate from baseline to follow-up at 4-, 8-, 12-, and 18-month post-baseline (all ps < .01), producing large effects (range of ds = 0.76 to 1.34). LOCI\'s effects on transformational leadership were small at 4 months (d = 0.31, p = .019) and nonsignificant thereafter (ps > .05). LOCI\'s improvement of clinic implementation climate from baseline to 12 months was mediated by improvement in implementation leadership from baseline to 4 months (proportion mediated [pm] = 0.82, p = .004). Transformational leadership did not mediate LOCI\'s effect on implementation climate (p = 0.136). Improvement in clinic implementation climate from baseline to 12 months mediated LOCI\'s effect on MBC fidelity during the same period (pm = 0.71, p = .045).
CONCLUSIONS: LOCI improved MBC fidelity in youth mental health services by improving clinic implementation climate, which was itself improved by increased implementation leadership. Fidelity to EBPs in healthcare settings can be improved by developing organizational leaders and strong implementation climates.
BACKGROUND: ClinicalTrials.gov identifier: NCT04096274. Registered September 18, 2019.

BACKGROUND: Genome-wide association studies (GWAS) are important for the acceleration of crop improvement through knowledge of marker-trait association (MTA). This report used DArT SNP markers to successfully perform GWAS on agro-morphological traits using 270 bambara groundnut [Vigna subterranea (L.) Verdc.] landraces sourced from diverse origins. The study aimed to identify marker traits association for nine agronomic traits using GWAS and their candidate genes. The experiment was conducted at two different locations laid out in alpha lattice design. The cowpea [Vigna unguiculata (L.) Walp.] reference genome (i.e. legume genome most closely related to bambara groundnut) assisted in the identification of candidate genes.
RESULTS: The analyses showed that linkage disequilibrium was found to decay rapidly with an average genetic distance of 148 kb. The broadsense heritability was relatively high and ranged from 48.39% (terminal leaf length) to 79.39% (number of pods per plant). The GWAS identified a total of 27 significant marker-trait associations (MTAs) for the nine studied traits explaining 5.27% to 24.86% of phenotypic variations. Among studied traits, the highest number of MTAs was obtained from seed coat colour (6) followed by days to flowering (5), while the least is days to maturity (1), explaining 5.76% to 11.03%, 14.5% to 19.49%, and 11.66% phenotypic variations, respectively. Also, a total of 17 candidate genes were identified, varying in number for different traits; seed coat colour (6), days to flowering (3), terminal leaf length (2), terminal leaf width (2), number of seed per pod (2), pod width (1) and days to maturity (1).
CONCLUSIONS: These results revealed the prospect of GWAS in identification of SNP variations associated with agronomic traits in bambara groundnut. Also, its present new opportunity to explore GWAS and marker assisted strategies in breeding of bambara groundnut for acceleration of the crop improvement.

Autosomal dominant non-syndromic hearing loss (HL) typically occurs when only one dominant allele within the disease gene is sufficient to express the phenotype. Therefore, most patients diagnosed with autosomal dominant non-syndromic HL have a hearing-impaired parent, although de novo mutations should be considered in all cases of negative family history. To date, more than 50 genes and 80 loci have been identified for autosomal dominant non-syndromic HL. DFNA22 (MYO6 gene), DFNA8/12 (TECTA gene), DFNA20/26 (ACTG1 gene), DFNA6/14/38 (WFS1 gene), DFNA15 (POU4F3 gene), DFNA2A (KCNQ4 gene), and DFNA10 (EYA4 gene) are some of the most common forms of autosomal dominant non-syndromic HL. The characteristics of autosomal dominant non-syndromic HL are heterogenous. However, in most cases, HL tends to be bilateral, post-lingual in onset (childhood to early adulthood), high-frequency (sloping audiometric configuration), progressive, and variable in severity (mild to profound degree). DFNA1 (DIAPH1 gene) and DFNA6/14/38 (WFS1 gene) are the most common forms of autosomal dominant non-syndromic HL affecting low frequencies, while DFNA16 (unknown gene) is characterized by fluctuating HL. A long audiological follow-up is of paramount importance to identify hearing threshold deteriorations early and ensure prompt treatment with hearing aids or cochlear implants.

Numerous fungicide applications are required to control Erysiphe necator, the causative agent of powdery mildew. This increased demand for cultivars with strong and long-lasting field resistance to diseases and pests. In comparison to the susceptible cultivar \'Teroldego\', the current study provides information on some promising disease-resistant varieties (mono-locus) carrying one E. necator-resistant locus: BC4 and \'Kishmish vatkana\', as well as resistant genotypes carrying several E. necator resistant loci (pyramided): \'Bianca\', F26P92, F13P71, and NY42. A clear picture of the metabolites\' alterations in response to the pathogen is shown by profiling the main and secondary metabolism: primary compounds and lipids; volatile organic compounds and phenolic compounds at 0, 12, and 48 hours after pathogen inoculation. We identified several compounds whose metabolic modulation indicated that resistant plants initiate defense upon pathogen inoculation, which, while similar to the susceptible genotype in some cases, did not imply that the plants were not resistant, but rather that their resistance was modulated at different percentages of metabolite accumulation and with different effect sizes. As a result, we discovered ten up-accumulated metabolites that distinguished resistant from susceptible varieties in response to powdery mildew inoculation, three of which have already been proposed as resistance biomarkers due to their role in activating the plant defense response.

Left ventricular maximum wall thickness (LVMWT) is an important biomarker of left ventricular hypertrophy and provides diagnostic and prognostic information in hypertrophic cardiomyopathy (HCM). Limited information is available on the genetic determinants of LVMWT.
We performed a genome-wide association study of LVMWT measured from the cardiovascular magnetic resonance examinations of 42 176 European individuals. We evaluated the genetic relationship between LVMWT and HCM by performing pairwise analysis using the data from the Hypertrophic Cardiomyopathy Registry in which the controls were randomly selected from UK Biobank individuals not included in the cardiovascular magnetic resonance sub-study.
Twenty-one genetic loci were discovered at P<5×10-8. Several novel candidate genes were identified including PROX1, PXN, and PTK2, with known functional roles in myocardial growth and sarcomere organization. The LVMWT genetic risk score is predictive of HCM in the Hypertrophic Cardiomyopathy Registry (odds ratio per SD: 1.18 [95% CI, 1.13-1.23]) with pairwise analyses demonstrating a moderate genetic correlation (rg=0.53) and substantial loci overlap (19/21).
Our findings provide novel insights into the genetic underpinning of LVMWT and highlight its shared genetic background with HCM, supporting future endeavours to elucidate the genetic etiology of HCM.

Bovine coronavirus (BCoV) is associated with respiratory and enteric infections in both dairy and beef cattle worldwide. It is also one of a complex of pathogens associated with bovine respiratory disease (BRD), which affects millions of cattle annually. The objectives of this study were to identify loci and heritability estimates associated with BCoV infection and BRD in dairy calves and feedlot cattle. Dairy calves from California (n = 1,938) and New Mexico (n = 647) and feedlot cattle from Colorado (n = 915) and Washington (n = 934) were tested for the presence of BCoV when classified as BRD cases or controls following the McGuirk scoring system. Two comparisons associated with BCoV were investigated: (1) cattle positive for BCoV (BCoV+) were compared to cattle negative for BCoV (BCoV-) and (2) cattle positive for BCoV and affected with BRD (BCoV+BRD+) were compared to cattle negative for BCoV and BRD (BCoV-BRD-). The Illumina BovineHD BeadChip was used for genotyping, and genome-wide association analyses (GWAA) were performed using EMMAX (efficient mixed-model association eXpedited). The GWAA for BCoV+ identified 51 loci (p < 1 × 10-5; 24 feedlot, 16 dairy, 11 combined) associated with infection with BCoV. Three loci were associated with BCoV+ across populations. Heritability estimates for BCoV+ were 0.01 for dairy, 0.11 for feedlot cattle, and 0.03 for the combined population. For BCoV+BRD+, 80 loci (p < 1 × 10-5; 26 feedlot, 25 dairy, 29 combined) were associated including 14 loci across populations. Heritability estimates for BCoV+BRD+ were 0.003 for dairy, 0.44 for feedlot cattle, and 0.07 for the combined population. Several positional candidate genes associated with BCoV and BRD in this study have been associated with other coronaviruses and respiratory infections in humans and mice. These results suggest that selection may reduce susceptibility to BCoV infection and BRD in cattle.

Genome-wide association studies (GWAS) have been utilized to detect genetic variations related to several agronomic traits and disease resistance in common bean. However, its application in the powdery mildew (PM) disease to identify candidate genes and their location in the common bean genome has not been fully addressed. Single-nucleotide polymorphism (SNP) genotyping with a BeadChip containing 5398 SNPs was used to detect genetic variations related to PM disease resistance in a panel of 211 genotypes grown under two field conditions for two consecutive years. Significant SNPs identified on chromosomes Pv04 and Pv10 were repeatable, ensuring the phenotypic data\'s reliability and the causal relationship. A cluster of resistance genes was revealed on the Pv04 of the common bean genome, coiled-coil-nucleotide-binding site-leucine-rich repeat (CC-NBS-LRR, CNL), and Toll/interleukin-1 receptor-nucleotide-binding site-leucine-rich repeat type (TIR-NBS-LRR, TNL)-like resistance genes were identified. Furthermore, two resistance genes, Phavu_010G1320001g and Phavu_010G136800g, were also identified on Pv10. Further sequence analysis showed that these genes were homologs to the disease-resistance protein (RLM1A-like) and the putative disease-resistance protein (At4g11170.1) in Arabidopsis. Significant SNPs related to two LRR receptor-like kinases (RLK) were only identified on Pv11 in 2018. Many genes encoding the auxin-responsive protein, TIFY10A protein, growth-regulating factor five-like, ubiquitin-like protein, and cell wall RBR3-like protein related to PM disease resistance were identified nearby significant SNPs. These results suggested that the resistance to PM pathogen involves a network of many genes constitutively co-expressed.

Body composition (fat, skeletal muscle and bone mass) is an important determinant of overall health and risk of endocrine disorders such as type 2 diabetes and osteoporosis. Although diet and physical activity are strongly implicated, body composition is also heritable. We conducted a discovery genome-wide association study on 31 phenotypes from the three-compartment body composition model (fat, lean and bone mass) in a set of 4 386 individuals (n = 2 109 males, n = 2 294 females) from the UK Biobank pilot imaging enhancement program that underwent a dual energy X-ray absorptiometry (DXA) scan for assessment of body composition and genetic screening. From 6 137 607 imputed single nucleotide polymorphisms (SNPs) we identified 17 body composition loci (P<5.0 x 10-8). GWAS from the combined dataset identified four statistically significant SNPs (rs7592270, rs145972737, rs13212044, rs77772562). In sex-stratified GWAS, 10 male specific SNPs across all traits were identified and five female specific SNPs. Of the 17 SNPs, six were in or close to a gene where there was a plausible functional connection. Three SNPs (rs7592270, rs77772562 and rs7552312) were correlated with obesity phenotypes, one SNP (rs2236705) with lean phenotypes and two with bone mass phenotypes (rs112098641 and rs113380185). These results highlight candidate genes and biological pathways related to body composition, including glucose metabolism and estrogen regulation, that are of interest to replicate in future studies.