M-CSF and GM-CSF Regulation of STAT5 Activation and DNA Binding in Myeloid Cell Differentiation is Disrupted in Nonobese Diabetic Mice

Defects in macrophage colony-stimulating factor (M-CSF) signaling disrupt myeloid cell differentiation in nonobese diabetic (NOD) mice, blocking myeloid maturation into tolerogenic antigen-presenting cells (APCs). In the absence of M-CSF signaling, NOD myeloid cells have abnormally high granulocyte macrophage colony-stimulating factor (GM-CSF) expression, and as a result, persistent activation of signal transducer/activator of transcription 5 (STAT5). Persistent STAT5 phosphorylation found in NOD macrophages is not affected by inhibiting GM-CSF. However, STAT5 phosphorylation in NOD bone marrow cells is diminished if GM-CSF signaling is blocked. Moreover, if M-CSF signaling is inhibited, GM-CSF stimulation in vitro can promote STAT5 phosphorylation in nonautoimmune C57BL/6 mouse bone marrow cultures to levels seen in the NOD. These findings suggest that excessive GM-CSF production in the NOD bone marrow may interfere with the temporal sequence of GM-CSF and M-CSF signaling needed to mediate normal STAT5 function in myeloid cell differentiation gene regulation

Inferring human population sizes, divergence times and rates of gene flow from mitochondrial, X and Y chromosome resequencing data

We estimate parameters of a general isolation-with-migration model using resequence data from mitochondrial DNA (mtDNA), the Y chromosome, and two loci on the X chromosome in samples of 25-50 individuals from each of 10 human populations. Application of a coalescent-based Markov chain Monte Carlo technique allows simultaneous inference of divergence times, rates of gene flow, as well as changes in effective population size. Results from comparisons between sub-Saharan African and Eurasian populations estimate that 1500 individuals founded the ancestral Eurasian population similar to 40 thousand years ago (KYA). Furthermore, these small Eurasian founding populations appear to have grown much more dramatically than either African or Oceanian populations. Analyses of sub-Saharan African populations provide little evidence for a history, of population bottlenecks and suggest that die), began diverging from one another upward of 50 KYA. We surmise that ancestral African populations had already been geographically structured prior to the founding of ancestral Eurasian populations. African populations are shown to experience low levels of mitochondrial DNA gene flow, but high levels of Y chromosome gene flow. In particular, Y chromosome gene flow appears to be asymmetric, i.e., from the Bantu-speaking population into other African populations. Conversely, mitochondrial gene flow is more extensive between non-African populations, but appears to be absent between European and Asian Populations

Development of a T cell-based immunodiagnostic system to effectively distinguish SARS-CoV-2 infection and COVID-19 vaccination status

Both SARS-CoV-2 infections and COVID-19 vaccines elicit memory T cell responses. Here, we report the development of 2 pools of experimentally defined SARS-CoV-2 T cell epitopes that, in combination with spike, were used to discriminate 4 groups of subjects with different SARS-CoV-2 infection and COVID-19 vaccine status. The overall T cell-based classification accuracy was 89.2% and 88.5% in the experimental and validation cohorts. This scheme was applicable to different mRNA vaccines and different lengths of time post infection/post vaccination and yielded increased accuracy when compared to serological readouts. T cell responses from breakthrough infections were also studied and effectively segregated from vaccine responses, with a combined performance of 86.6% across all 239 subjects from the 5 groups. We anticipate that a T cell-based immunodiagnostic scheme to classify subjects based on their vaccination and natural infection history will be an important tool for longitudinal monitoring of vaccinations and for establishing SARS-CoV-2 correlates of protection

Composite likelihood estimation of demographic parameters

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background: Most existing likelihood-based methods for fitting historical demographic models to DNA sequence polymorphism data to do not scale feasibly up to the level of whole-genome data sets. Computational economies can be achieved by incorporating two forms of pseudo-likelihood: composite and approximate likelihood methods. Composite likelihood enables scaling up to large data sets because it takes the product of marginal likelihoods as an estimator of the likelihood of the complete data set. This approach is especially useful when a large number of genomic regions constitutes the data set. Additionally, approximate likelihood methods can reduce the dimensionality of the data by summarizing the information in the original data by either a sufficient statistic, or a set of statistics. Both composite and approximate likelihood methods hold promise for analyzing large data sets or for use in situations where the underlying demographic model is complex and has many parameters. This paper considers a simple demographic model of allopatric divergence between two populations, in which one of the population is hypothesized to have experienced a founder event, or population bottleneck. A large resequencing data set from human populations is summarized by the joint frequency spectrum, which is a matrix of the genomic frequency spectrum of derived base frequencies in two populations. A Bayesia

Polymorphisms of cytochrome P450 1A1, glutathione s-transferases M1 and T1 genes in Ouangolodougou (Northern Ivory Coast)

In this study, the frequencies of CYP1A1, GSTM1, and GSTT1 gene polymorphisms were determined in 133 healthy individuals from Ouangolodougou, a small rural town situated in the north of the Ivory Coast. As appeared in several published studies, ethnic differences in these frequencies have been found to play an important role in the metabolism of a relevant number of human carcinogens. In the studied sample, the frequencies of Ile/Ile (wild type), Ile/Val (heterozygous variant), and Val/Val (homozygous variant) CYP1A1 genotypes were 0.271, 0.692, and 0.037, respectively. Frequencies of GSTM1 and GSTT1 null genotypes were 0.361 and 0.331, respectively. No significant differences were noted between men and women. In contrast to published data for Africans, CYP1A1 *Val Allele frequency (0.383) was significantly high (p < 0.001) in this specific population. For the GSTT1 null genotype, no differences were found between the studied and other African populations, the contrary to what occurred for the GSTM1 null genotype in relation to Gambia and Egypt

The Microcephalin Ancestral Allele in a Neanderthal Individual

Background: The high frequency (around 0.70 worlwide) and the relatively young age (between 14,000 and 62,000 years) of a derived group of haplotypes, haplogroup D, at the microcephalin (MCPH1) locus led to the proposal that haplogroup D originated in a human lineage that separated from modern humans.1 million years ago, evolved under strong positive selection, and passed into the human gene pool by an episode of admixture circa 37,000 years ago. The geographic distribution of haplogroup D, with marked differences between Africa and Eurasia, suggested that the archaic human form admixing with anatomically modern humans might have been Neanderthal. Methodology/Principal Findings: Here we report the first PCR amplification and high- throughput sequencing of nuclear DNA at the microcephalin (MCPH1) locus from Neanderthal individual from Mezzena Rockshelter (Monti Lessini, Italy). We show that a well-preserved Neanderthal fossil dated at approximately 50,000 years B.P., was homozygous for the ancestral, non-D, allele. The high yield of Neanderthal mtDNA sequences of the studied specimen, the pattern of nucleotide misincorporation among sequences consistent with post-mortem DNA damage and an accurate control of the MCPH

R-gene variation across Arabidopsis lyrata subspecies: effects of population structure, selection and mating system.

BACKGROUND: Examining allelic variation of R-genes in closely related perennial species of Arabidopsis thaliana is critical to understanding how population structure and ecology interact with selection to shape the evolution of innate immunity in plants. We finely sampled natural populations of Arabidopsis lyrata from the Great Lakes region of North America (A. l. lyrata) and broadly sampled six European countries (A. l. petraea) to investigate allelic variation of two R-genes (RPM1 and WRR4) and neutral genetic markers (Restriction Associated DNA sequences and microsatellites) in relation to mating system, phylogeographic structure and subspecies divergence. RESULTS: Fine-scale sampling of populations revealed strong effects of mating system and population structure on patterns of polymorphism for both neutral loci and R-genes, with no strong evidence for selection. Broad geographic sampling revealed evidence of balancing selection maintaining polymorphism in R-genes, with elevated heterozygosity and diversity compared to neutral expectations and sharing of alleles among diverged subspecies. Codon-based tests detected both positive and purifying selection for both R-genes, as commonly found for animal immune genes. CONCLUSIONS: Our results highlight that combining fine and broad-scale sampling strategies can reveal the multiple factors influencing polymorphism and divergence at potentially adaptive genes such as R-genes

Estimating Parameters of Speciation Models Based on Refined Summaries of the Joint Site-Frequency Spectrum

Understanding the processes and conditions under which populations diverge to give rise to distinct species is a central question in evolutionary biology. Since recently diverged populations have high levels of shared polymorphisms, it is challenging to distinguish between recent divergence with no (or very low) inter-population gene flow and older splitting events with subsequent gene flow. Recently published methods to infer speciation parameters under the isolation-migration framework are based on summarizing polymorphism data at multiple loci in two species using the joint site-frequency spectrum (JSFS). We have developed two improvements of these methods based on a more extensive use of the JSFS classes of polymorphisms for species with high intra-locus recombination rates. First, using a likelihood based method, we demonstrate that taking into account low-frequency polymorphisms shared between species significantly improves the joint estimation of the divergence time and gene flow between species. Second, we introduce a local linear regression algorithm that considerably reduces the computational time and allows for the estimation of unequal rates of gene flow between species. We also investigate which summary statistics from the JSFS allow the greatest estimation accuracy for divergence time and migration rates for low (around 10) and high (around 100) numbers of loci. Focusing on cases with low numbers of loci and high intra-locus recombination rates we show that our methods for the estimation of divergence time and migration rates are more precise than existing approaches