Maintaining a high level of beef consumption requires paying attention not only to quantitative traits but also to the quality and dietary properties of meat. Growing consumer demands do not leave producers many options for how animals are selected for breeding and animal keeping. Meat and carcass fatness quality traits, which are influenced by multiple genes, are economically important in beef cattle breeding programs. The recent availability of genome sequencing methods and many previously identified molecular markers offer new opportunities for animal breeding, including the use of molecular information in selection programs. Many gene polymorphisms have thus far been analyzed and evaluated as potential candidates for molecular markers of meat quality traits. Knowledge of these markers can be further applied to breeding programs through marker-assisted selection. In this literature review, we discuss the most promising and well-described candidates and their associations with selected beef production traits.
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http://dx.doi.org/10.5713/ab.20.0672 | DOI Listing |
Malariaworld J
January 2025
Biosciences Training and Research Unit (UFR), Felix Houphouët-Boigny University, Abidjan, Côte d'Ivoire.
Background: has developed resistance to almost all the antimalarial drugs currently in use. This resistance has been and remains one of the greatest threats to the control and elimination of malaria. The use of molecular markers of resistance to monitor the emergence and spread of antimalarial drug-resistant parasite strains has proved highly effective.
View Article and Find Full Text PDFInt J Chron Obstruct Pulmon Dis
January 2025
Department of Rehabilitation Medicine, General Hospital of Central Theater Command, Wuhan, 430065, People's Republic of China.
Background: In preliminary research and literature review, we identified a potential link between chronic obstructive pulmonary disease (COPD) and lipid metabolism. Therefore, this study employed Mendelian randomization (MR) analysis to investigate the potential causal connection between blood lipids and COPD.
Materials And Methods: A genome-wide association study (GWAS) on COPD was conducted, encompassing a total of 112,583 European participants from the MRC-IEU.
J Diabetes Metab Disord
June 2025
Department of Biology, Islamshahr Branch, Islamic Azad University, Islamshahr, Tehran, Iran.
Objectives: The study investigates the association of single nucleotide polymorphisms (SNP) in resistin gene (RETN) with resistin level, insulin resistance, and the risk of type 2 diabetes in an early diagnosed type 2 diabetic population of Iran.
Methods: The total of 80 healthy subjects and 80 individuals diagnosed with type 2 diabetes. To ascertain the genotypes of rs1862513 and rs3745367, we performed the polymerase chain reaction with restriction fragment length polymorphism (PCR-RFLP) technique.
Expert Rev Mol Diagn
January 2025
Department of Pathology, Yale University School of Medicine, New Haven.
Introduction: Gestational trophoblastic disease (GTD) encompasses a constellation of rare to common gynecologic conditions stemming from aberrant gestations with distinct genetic backgrounds and variable degrees of trophoblast proliferation of either neoplastic or non-neoplastic nature. GTD is categorized into hydatidiform moles and gestational trophoblastic neoplasms, and their clinical outcomes vary widely across different subtypes. Prompt and accurate diagnosis plays a pivotal role in the effective management and prognostication of patients.
View Article and Find Full Text PDFJ Oral Facial Pain Headache
June 2024
Department of Stomatology, Suzhou Wujiang District Hospital of Traditional Chinese Medicine, 215221 Suzhou, Jiangsu, China.
The coronavirus disease 2019 (COVID-19) and temporomandibular joint disorders (TMD) as the two major diseases are being focused by the public in modern societies. Previous epidemiological studies have shown increase in TMD prevalence during COVID-19 pandemic era. This study was aimed to verify the causal association between two sides using bidirectional mendelian randomization (MR) analysis.
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