The probable ancestral haplotype for human apolipoprotein B (apoB) has been identified through immunological analysis of chimpanzee and gorilla serum and sequence analysis of their DNA. Moreover, the frequency of this ancestral apoB haplotype among different human populations provides strong support for the African origin of Homo sapiens sapiens and their subsequent migration from Africa to Europe and to the Pacific. The approach used here for the identification of the ancestral human apoB haplotype is likely to be applicable to many other genes.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC51026 | PMC |
http://dx.doi.org/10.1073/pnas.88.4.1403 | DOI Listing |
Ann Hum Genet
January 2025
Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria.
Introduction: Southern Africa has been inhabited by hunter-gatherers for at least 20,000 years and has received diverse immigration flows in the last 2000 years. The original inhabitants have interacted with the pastoralist migrants from Eastern Africa (∼2000 ybp), followed by the southern Bantu migration arriving some 1000 ybp, and more recently with the European and Asian settlers after the 17th century. Many of the original Khoekhoe and San inhabitants have either become extinct or have disappeared through admixture in South Africa (SA), in a sex-biased manner involving KhoeSan women.
View Article and Find Full Text PDFNucleotide sequence can be translated in three reading frames from 5' to 3' producing distinct protein products. Many examples of RNA translation in two reading frames (dual coding) have been identified so far. We report simultaneous translation of mRNA transcripts derived from locus in all three reading frames that result in the synthesis of long proteins.
View Article and Find Full Text PDFJ Mach Learn Res
January 2024
Division of Biostatistics, University of Minnesota, Minneapolis, MN 55455, USA.
This article presents a novel method for causal discovery with generalized structural equation models suited for analyzing diverse types of outcomes, including discrete, continuous, and mixed data. Causal discovery often faces challenges due to unmeasured confounders that hinder the identification of causal relationships. The proposed approach addresses this issue by developing two peeling algorithms (bottom-up and top-down) to ascertain causal relationships and valid instruments.
View Article and Find Full Text PDFSchizophrenia (Heidelb)
January 2025
Department of Psychiatry, University of Campania "Luigi Vanvitelli", 80138, Naples, Italy.
The present study aimed to investigate the causal relationships among cognitive impairment, psychopathology, and real-life functioning in a large sample of people with schizophrenia, using a data-driven causal discovery procedure based on partial ancestral graphs (PAGs). This method may provide additional insights for the identification of potential therapeutic targets to promote recovery in people with chronic schizophrenia. State-of-the-art instruments were used to assess the study variables.
View Article and Find Full Text PDFFront Genet
December 2024
Department of Statistics, Federal University of São Carlos (UFSCar), São Carlos, Brazil.
Introduction: Cardiometabolic diseases, a major global health concern, stem from complex interactions of lifestyle, genetics, and biochemical markers. While extensive research has revealed strong associations between various risk factors and these diseases, latent confounding and limited causal discovery methods hinder understanding of their causal relationships, essential for mechanistic insights and developing effective prevention and intervention strategies.
Methods: We introduce anchorFCI, a novel adaptation of the conservative Really Fast Causal Inference (RFCI) algorithm, designed to enhance robustness and discovery power in causal learning by strategically selecting and integrating reliable anchor variables from a set of variables known not to be caused by the variables of interest.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!