A Case Study of Fall versus Spring Calving for the Rocky Mountain West

Feeder cattle prices are generally lower in the fall, when the volume of calves for sale is highest. Most ranches in the Rocky Mountains calve in March or April, which results in the sale of weaned calves in October, when feeder cattle prices tend to be lowest. This study was initiated with the idea that a rancher might improve profitability by switching to fall calving, which would enable them to sell calves in April at a higher price. In this study, fall calving generated both higher and less variable profit, but mainly because of cost savings.Livestock Production/Industries,

IL-10 from CD4+CD25−Foxp3−CD127− Adaptive Regulatory T Cells Modulates Parasite Clearance and Pathology during Malaria Infection

The outcome of malaria infection is determined, in part, by the balance of pro-inflammatory and regulatory immune responses. Failure to develop an effective pro-inflammatory response can lead to unrestricted parasite replication, whilst failure to regulate this response leads to the development of severe immunopathology. IL-10 and TGF-β are known to be important components of the regulatory response, but the cellular source of these cytokines is still unknown. Here we have examined the role of natural and adaptive regulatory T cells in the control of malaria infection and find that classical CD4+CD25hi (and Foxp3+) regulatory T cells do not significantly influence the outcome of infections with the lethal (17XL) strain of Plasmodium yoelii (PyL). In contrast, we find that adaptive IL-10-producing, CD4+ T cells (which are CD25−, Foxp3−, and CD127− and do not produce Th1, Th2, or Th17 associated cytokines) that are generated during both PyL and non-lethal P. yoelii 17X (PyNL) infections are able to down-regulate pro-inflammatory responses and impede parasite clearance. In summary, we have identified a population of induced Foxp3− regulatory (Tr1) T cells, characterised by production of IL-10 and down regulation of IL-7Rα, that modulates the inflammatory response to malaria

Low-frequency variation near common germline susceptibility loci are associated with risk of Ewing sarcoma

Background: Ewing sarcoma (EwS) is a rare, aggressive solid tumor of childhood, adolescence and young adulthood associated with pathognomonic EWSR1-ETS fusion oncoproteins altering transcriptional regulation. Genome-wide association studies (GWAS) have identified 6 common germline susceptibility loci but have not investigated low-frequency inherited variants with minor allele frequencies below 5% due to limited genotyped cases of this rare tumor. Methods We investigated the contribution of rare and low-frequency variation to EwS susceptibility in the largest EwS genome-wide association study to date (733 EwS cases and 1,346 unaffected controls of European ancestry). Results We identified two low-frequency variants, rs112837127 and rs2296730, on chromosome 20 that were associated with EwS risk (OR = 0.186 and 2.038, respectively;P-value < 5x10(-8)) and located near previously reported common susceptibility loci. After adjusting for the most associated common variant at the locus, only rs112837127 remained a statistically significant independent signal (OR = 0.200, P-value = 5.84x10(-8)). Conclusions: These findings suggest rare variation residing on common haplotypes are important contributors to EwS risk. Impact Motivate future targeted sequencing studies for a comprehensive evaluation of low-frequency and rare variation around common EwS susceptibility loci

Natural Regulatory T Cells in Malaria: Host or Parasite Allies?

Plasmodium falciparum malaria causes 500 million clinical cases with approximately one million deaths each year. After many years of exposure, individuals living in endemic areas develop a form of clinical immunity to disease known as premunition, which is characterised by low parasite burdens rather than sterilising immunity. The reason why malaria parasites persist under a state of premunition is unknown but it has been suggested that suppression of protective immunity might be a mechanism leading to parasite persistence. Although acquired immunity limits the clinical impact of infection and provides protection against parasite replication, experimental evidence indicates that cell-mediated immune responses also result in detrimental inflammation and contribute to the aetiology of severe disease. Thus, an appropriate regulatory balance between protective immune responses and immune-mediated pathology is required for a favourable outcome of infection. As natural regulatory T (Treg) cells are identified as an immunosuppressive lineage able to modulate the magnitude of effector responses, several studies have investigated whether this cell population plays a role in balancing protective immunity and pathogenesis during malaria. The main findings to date are summarised in this review and the implication for the induction of pathogenesis and immunity to malaria is discussed

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes

Penetrance of variants in monogenic disease and clinical utility of common polygenic variation has not been well explored on a large-scale. Here, the authors use exome sequencing data from 77,184 individuals to generate penetrance estimates and assess the utility of polygenic variation in risk prediction of monogenic variants

Community-Wide Assessment of Protein-Interface Modeling Suggests Improvements to Design Methodology

The CAPRI and CASP prediction experiments have demonstrated the power of community wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting there may be important physical chemistry missing in the energy calculations. 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the non-polar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were on average structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a non-binder

Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels