16 research outputs found
The Resilient Dairy Genome Project - a general overview of methods and objectives related to feed efficiency and methane emissions.
The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries, i.e., Australia [AUS], Canada [CAN], Denmark [DNK], Germany [DEU], Spain [ESP], Switzerland [CHE], and United States of America [USA] contribute with genotypes and phenotypes including DMI and CH4. However, combining data is challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis
Universal truths: Learning from the experience of cancer patients in Australia and England.
Ketone Body Signaling Mediates Intestinal Stem Cell Homeostasis and Adaptation to Diet
Little is known about how metabolites couple tissuespecific stem cell function with physiology. Here we show that, in the mammalian small intestine, the expression of Hmgcs2 (3-hydroxy-3-methylglutarylCoA synthetase 2), the gene encoding the ratelimiting enzyme in the production of ketone bodies, including beta-hydroxybutyrate (beta OHB), distinguishes self-renewing Lgr5(+) stem cells (ISCs) from differentiated cell types. Hmgcs2 loss depletes beta OHB levels in Lgr5(+) ISCs and skews their differentiation toward secretory cell fates, which can be rescued by exogenous beta OHB and class I histone deacetylase (HDAC) inhibitor treatment. Mechanistically, beta OHB acts by inhibiting HDACs to reinforce Notch signaling, instructing ISC self-renewal and lineage decisions. Notably, although a high-fat ketogenic diet elevates ISC function and postinjury regeneration through beta OHB-mediated Notch signaling, a glucose-supplemented diet has the opposite effects. These findings reveal how control of beta OHB-activated signaling in ISCs by diet helps to fine-tune stem cell adaptation in homeostasis and injury
Pitfalls of Autonomy: the Overlooked Challenges of Teaching Locally Developed Mathematics in Ontario High Schools
Strategies for Enrollment of African Americans into Cancer Genetic Studies
The enrollment of ethnically diverse populations in genetic and genomic research is vital to the parity of benefits resulting from research with biological specimens. Herein, we discuss strategies that may effectively improve the recruitment of African Americans into genetics studies. Specifically, we show that engaging physicians, genetic counselors, and community members is essential to enrolling participants into genetic studies. We demonstrate the impact of utilizing African American genetic counselors on study enrollment rates and implementing a two-page consent form that improved on a lengthy and inefficient consenting process. Lastly, we provided participants with the option of donating saliva instead of blood for study purposes. Descriptive statistics were used. Using the aforementioned strategies, recruitment goals for the Genetic Basis of Breast Cancer Subtype Study at Howard University (HU) were met. Our overall results yielded 182 participants in 18 months. Recruitment strategies that involve the engagement of physicians, genetic counselors, and community members may help researchers increase the enrollment of ethnically diverse and hard-to-reach participants into genetic studies
The Resilient Dairy Genome Project - a general overview of methods and objectives related to feed efficiency and methane emissions
The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries, i.e., Australia [AUS], Canada [CAN], Denmark [DNK], Germany [DEU], Spain [ESP], Switzerland [CHE], and United States of America [USA] contribute with genotypes and phenotypes including DMI and CH4. However, combining data is challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis