ABSTRACT
Admixture, the exchange of genetic information between distinct source populations, is thought to be a major source of adaptive genetic variation. Unlike mutation events, which periodically generate single alleles, admixture can introduce many selected alleles simultaneously. As such, the effects of linkage between selected alleles may be especially pronounced in admixed populations. However, existing tools for identifying selected mutations within admixed populations only account for selection at a single site, overlooking phenomena such as linkage among proximal selected alleles. Here, we develop and extensively validate a method for identifying and quantifying the individual effects of multiple linked selected sites on a chromosome in admixed populations. Our approach numerically calculates the expected local ancestry landscape in an admixed population for a given multi-locus selection model, and then maximizes the likelihood of the model. After applying this method to admixed populations of Drosophila melanogaster and Passer italiae, we found that the impacts between linked sites may be an important contributor to natural selection in admixed populations. Furthermore, for the situations we considered, the selection coefficients and number of selected sites are overestimated in analyses that do not consider the effects of linkage among selected sites. Our results imply that linkage among selected sites may be an important evolutionary force in admixed populations. This tool provides a powerful generalized method to investigate these crucial phenomena in diverse populations.
Subject(s)
Drosophila melanogaster , Genetics, Population , Animals , Drosophila melanogaster/genetics , Selection, GeneticABSTRACT
Objective: To compare the agreement between patient and clinician perceptions of care-related financial issues. Patients and Methods: We surveyed patient-clinician dyads immediately after an outpatient medical encounter between September 2019 and May 2021. They were asked to separately rate (1-10) patient's level of difficulty in paying medical bills and the importance of discussing cost issues with that patient during clinical encounters. We calculated agreement between patient-clinician ratings using the intraclass correlation coefficient and used random effects regression models to identify patient predictors of paired score differences in difficulty and importance of ratings. Results: 58 pairs of patients (n=58) and clinicians (n=40) completed the survey. Patient-clinician agreement was poor for both measures, but higher for difficulty in paying medical bills (intraclass correlation coefficient=0.375; 95% CI, 0.13-0.57) than for the importance of discussing cost (-0.051; 95% CI, -0.31 to 0.21). Agreement on difficulty in paying medical bills was not lower in encounters with conversations about the cost of care. In adjusted models, poor patient-clinician agreement on difficulty in paying medical bills was associated with lower patient socioeconomic status and education level, whereas poor agreement on patient-perceived importance of discussing cost was significant for patients who were White, married, reported 1 or more long-term conditions, and had higher education and income levels. Conclusion: Even in encounters where cost conversations occurred, there was poor patient-clinician agreement on ratings of the patient's difficulty in paying medical bills and perceived importance of discussing cost issues. Clinicians need more training and support in detecting the level of financial burden and tailoring cost conversations to the needs of individual patients.
ABSTRACT
Histone methyltransferases (HMTs) comprise a subclass of epigenetic regulators. Dysregulation of these enzymes results in aberrant epigenetic regulation, commonly observed in various tumor types, including hepatocellular adenocarcinoma (HCC). Probably, these epigenetic changes could lead to tumorigenesis processes. To predict how histone methyltransferase genes and their genetic alterations (somatic mutations, somatic copy number alterations, and gene expression changes) are involved in hepatocellular adenocarcinoma processes, we performed an integrated computational analysis of genetic alterations in 50 HMT genes present in hepatocellular adenocarcinoma. Biological data were obtained through the public repository with 360 samples from patients with hepatocellular carcinoma. Through these biological data, we identified 10 HMT genes (SETDB1, ASH1L, SMYD2, SMYD3, EHMT2, SETD3, PRDM14, PRDM16, KMT2C, and NSD3) with a significant genetic alteration rate (14%) within 360 samples. Of these 10 HMT genes, KMT2C and ASH1L have the highest mutation rate in HCC samples, 5.6% and 2.8%, respectively. Regarding somatic copy number alteration, ASH1L and SETDB1 are amplified in several samples, while SETD3, PRDM14, and NSD3 showed a high rate of large deletion. Finally, SETDB1, SETD3, PRDM14, and NSD3 could play an important role in the progression of hepatocellular adenocarcinoma since alterations in these genes lead to a decrease in patient survival, unlike patients who present these genes without genetic alterations. Our computational analysis provides new insights that help to understand how HMTs are associated with hepatocellular carcinoma, as well as provide a basis for future experimental investigations using HMTs as genetic targets against hepatocellular carcinoma.
ABSTRACT
Accurate and timely detection of recombinant lineages is crucial for interpreting genetic variation, reconstructing epidemic spread, identifying selection and variants of interest, and accurately performing phylogenetic analyses1-4. During the SARS-CoV-2 pandemic, genomic data generation has exceeded the capacities of existing analysis platforms, thereby crippling real-time analysis of viral evolution5. Here, we use a new phylogenomic method to search a nearly comprehensive SARS-CoV-2 phylogeny for recombinant lineages. In a 1.6 million sample tree from May 2021, we identify 589 recombination events, which indicate that around 2.7% of sequenced SARS-CoV-2 genomes have detectable recombinant ancestry. Recombination breakpoints are inferred to occur disproportionately in the 3' portion of the genome that contains the spike protein. Our results highlight the need for timely analyses of recombination for pinpointing the emergence of recombinant lineages with the potential to increase transmissibility or virulence of the virus. We anticipate that this approach will empower comprehensive real-time tracking of viral recombination during the SARS-CoV-2 pandemic and beyond.
