Human induced pluripotent stem cells (hiPSC) provide an attractive tool to study disease mechanisms of neurodevelopmental disorders such as schizophrenia. A pertinent problem is the development of hiPSC-based assays to discriminate schizophrenia (SZ) from autism spectrum disorder (ASD) models. Healthy control individuals as well as patients with SZ and ASD were examined by a panel of diagnostic tests. Subsequently, skin biopsies were taken for the generation, differentiation, and testing of hiPSC-derived neurons from all individuals. SZ and ASD neurons share a reduced capacity for cortical differentiation as shown by quantitative analysis of the synaptic marker PSD95 and neurite outgrowth. By contrast, pattern analysis of calcium signals turned out to discriminate among healthy control, schizophrenia, and autism samples. Schizophrenia neurons displayed decreased peak frequency accompanied by increased peak areas, while autism neurons showed a slight decrease in peak amplitudes. For further analysis of the schizophrenia phenotype, transcriptome analyses revealed a clear discrimination among schizophrenia, autism, and healthy controls based on differentially expressed genes. However, considerable differences were still evident among schizophrenia patients under inspection. For one individual with schizophrenia, expression analysis revealed deregulation of genes associated with the major histocompatibility complex class II (MHC class II) presentation pathway. Interestingly, antipsychotic treatment of healthy control neurons also increased MHC class II expression. In conclusion, transcriptome analysis combined with pattern analysis of calcium signals appeared as a tool to discriminate between SZ and ASD phenotypes in vitro.
The ability to infer the parameters of positive selection from genomic data has many important implications, from identifying drug-resistance mutations in viruses to increasing crop yield by genetically integrating favorable alleles. Although it has been well-described that selection and demography may result in similar patterns of diversity, the ability to jointly estimate these two processes has remained elusive. Here, we use simulation to explore the utility of the joint site frequency spectrum to estimate selection and demography simultaneously, including developing an extension of the previously proposed Jaatha program (Mathew et al., 2013). We evaluate both complete and incomplete selective sweeps under an isolation-with-migration model with and without population size change (both population growth and bottlenecks). Results suggest that while it may not be possible to precisely estimate the strength of selection, it is possible to infer the presence of selection while estimating accurate demographic parameters. We further demonstrate that the common assumption of selective neutrality when estimating demographic models may lead to severe biases. Finally, we apply the approach we have developed to better characterize the within-host demographic and selective history of human cytomegalovirus (HCMV) infection using published next generation sequencing data.
With the advent of next-generation sequencing technologies, large data sets of several thousand loci from multiple conspecific individuals are available. Such data sets should make it possible to obtain accurate estimates of population genetic parameters, even for complex models of population history. In the analyses of large data sets, it is difficult to consider finite-sites mutation models (FSMs). Here, we use extensive simulations to demonstrate that the inclusion of FSMs is necessary to avoid severe biases in the estimation of the population mutation rate θ, population divergence times, and migration rates. We present a new version of Jaatha, an efficient composite-likelihood method for estimating demographic parameters from population genetic data and evaluate the usefulness of Jaatha in two biological examples. For the first application, we infer the speciation process of two wild tomato species, Solanum chilense and Solanum peruvianum. In our second application example, we demonstrate that Jaatha is readily applicable to NGS data by analyzing genome-wide data from two southern European populations of Arabidopsis thaliana. Jaatha is now freely available as an R package from the Comprehensive R Archive Network (CRAN).
The KRAB-containing zinc finger (KRAB-ZF) proteins represent the largest family of transcription factors (TFs) in humans, yet for the great majority, their function and specific genomic target remain unknown. However, it has been shown that a large fraction of these genes arose from segmental duplications, and that they have expanded in gene and zinc finger number throughout vertebrate evolution. To determine whether this expansion is linked to selective pressures acting on different domains, we have manually curated all KRAB-ZF genes present in the human genome together with their orthologous genes in three closely related species and assessed the evolutionary forces acting at the sequence level as well as on their expression profiles. We provide evidence that KRAB-ZFs can be separated into two categories according to the polymorphism present in their DNA-contacting residues. Those carrying a nonsynonymous single nucleotide polymorphism (SNP) in their DNA-contacting amino acids exhibit significantly reduced expression in all tissues, have emerged in a recent lineage, and seem to be less strongly constrained evolutionarily than those without such a polymorphism. This work provides evidence for a link between age of the TF, as well as polymorphism in their DNA-contacting residues and expression levels-both of which may be jointly affected by selection. KeywordsDNA-contacting residues; endogenous retroelements; KRAB-containing zinc finger genes; population genetics; regulatory evolution; transcription factors Gene duplication can play a major role in species evolution: redundancy provides a medium for novelty while maintaining initial function. In the particular case of transcription factor (TF) genes, alterations in their expression profiles or binding properties can affect the expression of many target genes, often with a major functional impact. The KRAB-zinc finger (ZF) family of TFs, the largest family of TFs in the human genome, arose through tandem segmental duplications and contains arrays of C2H2 (also called Krüppel-type) ZFs combined with a KRAB (Krüppel-associated box) domain. Despite being so numerous, the 4 jeffrey.jensen@epfl.ch. Europe PMC Funders Group Europe PMC Funders Author ManuscriptsEurope PMC Funders Author Manuscripts function and specific genomic targets of the great majority of KRAB-containing ZF (KRAB-ZF) proteins remain unknown (Constantinou-Deltas et al. 1992;Huntley et al. 2006;Thomas and Emerson 2009).KRAB-ZF regulatory specificity is determined by a ZF-DNA recognition code, implicating interaction between specific amino acids within the ZF motifs and nucleotides at the binding sites (Choo and Klug 1994;Kim and Berg 1996). The amino acids playing the most critical role in this DNA recognition are those at the -1, 2, 3, and 6 positions relative to the alphahelical regions in each ZF domain (Pavletich and Pabo 1991;Elrod-Erickson et al. 1998).The strong conservation of some DNA-binding domains suggests that some genes have been stably integrated into essential regulatory rela...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.