Cognitive abilities, such as memory, learning, language, problem solving, and planning, involve the frontal lobe and other brain areas. Not much is known yet about the molecular basis of cognitive abilities, but it seems clear that cognitive abilities are determined by the interplay of many genes. One approach for analyzing the genetic networks involved in cognitive functions is to study the coexpression networks of genes with known importance for proper cognitive functions, such as genes that have been associated with cognitive disorders like intellectual disability (ID) or autism spectrum disorders (ASD). Because many of these genes are gene regulatory factors (GRFs) we aimed to provide insights into the gene regulatory networks active in the human frontal lobe. Using genome wide human frontal lobe expression data from 10 independent data sets, we first derived 10 individual coexpression networks for all GRFs including their potential target genes. We observed a high level of variability among these 10 independently derived networks, pointing out that relying on results from a single study can only provide limited biological insights. To instead focus on the most confident information from these 10 networks we developed a method for integrating such independently derived networks into a consensus network. This consensus network revealed robust GRF interactions that are conserved across the frontal lobes of different healthy human individuals. Within this network, we detected a strong central module that is enriched for 166 GRFs known to be involved in brain development and/or cognitive disorders. Interestingly, several hubs of the consensus network encode for GRFs that have not yet been associated with brain functions. Their central role in the network suggests them as excellent new candidates for playing an essential role in the regulatory network of the human frontal lobe, which should be investigated in future studies.

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Differences in gene regulation have been suggested to play essential roles in the evolution of phenotypic changes. Although DNA changes in cis-regulatory elements affect only the regulation of its corresponding gene, variations in gene regulatory factors (trans) can have a broader effect, because the expression of many target genes might be affected. Aiming to better understand how natural selection may have shaped the diversity of gene regulatory factors in human, we assembled a catalog of all proteins involved in controlling gene expression. We found that at least five DNA-binding transcription factor classes are enriched among genes located in candidate regions for selection, suggesting that they might be relevant for understanding regulatory mechanisms involved in human local adaptation. The class of KRAB-ZNFs, zinc-finger (ZNF) genes with a Krüppel-associated box, stands out by first, having the most genes located on candidate regions for positive selection. Second, displaying most nonsynonymous single nucleotide polymorphisms (SNPs) with high genetic differentiation between populations within these regions. Third, having 27 KRAB-ZNF gene clusters with high extended haplotype homozygosity. Our further characterization of nonsynonymous SNPs in ZNF genes located within candidate regions for selection, suggests regulatory modifications that might influence the expression of target genes at population level. Our detailed investigation of three candidate regions revealed possible explanations for how SNPs may influence the prevalence of schizophrenia, eye development, and fertility in humans, among other phenotypes. The genetic variation we characterized here may be responsible for subtle to rough regulatory changes that could be important for understanding human adaptation.

A substantial fraction of phenotypic differences between closely related species are likely caused by differences in gene regulation. While this has already been postulated over 30 years ago, only few examples of evolutionary changes in gene regulation have been verified. Here, we identified and investigated binding sites of the transcription factor GA-binding protein alpha (GABPa) aiming to discover cis-regulatory adaptations on the human lineage. By performing chromatin immunoprecipitation-sequencing experiments in a human cell line, we found 11,619 putative GABPa binding sites. Through sequence comparisons of the human GABPa binding regions with orthologous sequences from 34 mammals, we identified substitutions that have resulted in 224 putative human-specific GABPa binding sites. To experimentally assess the transcriptional impact of those substitutions, we selected four promoters for promoter-reporter gene assays using human and African green monkey cells. We compared the activities of wild-type promoters to mutated forms, where we have introduced one or more substitutions to mimic the ancestral state devoid of the GABPa consensus binding sequence. Similarly, we introduced the human-specific substitutions into chimpanzee and macaque promoter backgrounds. Our results demonstrate that the identified substitutions are functional, both in human and nonhuman promoters. In addition, we performed GABPa knock-down experiments and found 1,215 genes as strong candidates for primary targets. Further analyses of our data sets link GABPa to cognitive disorders, diabetes, KRAB zinc finger (KRAB-ZNF), and human-specific genes. Thus, we propose that differences in GABPa binding sites played important roles in the evolution of human-specific phenotypes.

The major histocompatibility complex (MHC) is a key genomic model region for understanding the evolution of gene families and the co-evolution between host and pathogen. To date, MHC studies have mostly focused on species from major vertebrate lineages. The evolution of MHC classical (Ia) and non-classical (Ib) genes in pigs has attracted interest because of their antigen presentation roles as part of the adaptive immune system. The pig family Suidae comprises over 18 extant species (mostly wild), but only the domestic pig has been extensively sequenced and annotated. To address this, we used a DNA-capture approach, with probes designed from the domestic pig genome, to generate MHC data for 11 wild species of pigs and their closest living family, Tayassuidae. The approach showed good efficiency for wild pigs (~80% reads mapped, ~87× coverage), compared to tayassuids (~12% reads mapped, ~4× coverage). We retrieved 145 MHC loci across both families. Phylogenetic analyses show that the class Ia and Ib genes underwent multiple duplications and diversifications before suids and tayassuids diverged from their common ancestor. The histocompatibility genes mostly form orthologous groups and there is genetic differentiation for most of these genes between Eurasian and sub-Saharan African wild pigs. Tests of selection showed that the peptide-binding region of class Ib genes was under positive selection. These findings contribute to better understanding of the evolutionary history of the MHC, specifically, the class I genes, and provide useful data for investigating the immune response of wild populations against pathogens.

Lohmann Brown (LB) and Lohmann Selected Leghorn (LSL) are two commercially important laying hen strains due to their high egg production and excellent commercial suitability. The present study integrated multiple data sets along the genotype-phenotype map to better understand how the genetic background of the two strains influences their molecular pathways. In total, 71 individuals were analyzed (LB, n = 36; LSL, n = 35). Data sets include gut miRNA and mRNA transcriptome data, microbiota composition, immune cells, inositol phosphate metabolites, minerals, and hormones from different organs of the two hen strains. All complex data sets were pre-processed, normalized, and compatible with the mixOmics platform. The most discriminant features between two laying strains included 20 miRNAs, 20 mRNAs, 16 immune cells, 10 microbes, 11 phenotypic traits, and 16 metabolites. The expression of specific miRNAs and the abundance of immune cell types were related to the enrichment of immune pathways in the LSL strain. In contrast, more microbial taxa specific to the LB strain were identified, and the abundance of certain microbes strongly correlated with host gut transcripts enriched in immunological and metabolic pathways. Our findings indicate that both strains employ distinct inherent strategies to acquire and maintain their immune and metabolic systems under high-performance conditions. In addition, the study provides a new perspective on a view of the functional biodiversity that emerges during strain selection and contributes to the understanding of the role of host–gut interaction, including immune phenotype, microbiota, gut transcriptome, and metabolome.

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Background Impaired skeletal muscle growth in utero can result in reduced birth weight and pathogenesis of intrauterine growth restriction. Fetal and placental growth is influenced by many factors including genetic, epigenetic and environmental factors. In fact, the sex and genotype of the fetus itself, as well as the mother providing it with a suitable environment, influence the growth of the fetus. Hence, our goal was to decipher and elucidate the molecular pathways of developmental processes mediated by miRNAs and mRNAs in fetal muscle tissue in the context of sex, dam, and fetal weight. Therefore, we analyse the variation of miRNA and mRNA expression in relation to these factors. In addition, the coincidence of genetic regulation of these mRNAs and miRNAs, as revealed by expression quantitative trait loci (eQTL) analyses, with sex-, mother- and weight-associated expression was investigated. Methods A three-generation pig F2 population (n = 118) based on reciprocal crossing of German Landrace (DL) and Pietrain (Pi) was used. Genotype information and transcriptomic data (mRNA and miRNA) from longissimus dorsi muscle (LDM) of pig fetuses sampled at 63 days post-conception (dpc) were used for eQTL analyses. Results The transcript abundances of 13, 853, and 275 probe-sets were influenced by sex, dam and fetal weight at 63 dpc, respectively (FDR < 5%). Most of significant transcripts affected by sex were located on the sex chromosomes including KDM6A and ANOS1 or autosomes including ANKS1B, LOC100155138 and miR-153. The fetal muscle transcripts associated with fetal weight indicated clearer metabolic directions than maternally influenced fetal muscle transcripts. Moreover, coincidence of genetic regulation (eQTL) and variation in transcript abundance due to sex, dam and fetal weight were identified. Conclusions Integrating information on eQTL, sex-, dam- and weight-associated differential expression and QTL for fetal weight allowed us to identify molecular pathways and shed light on the basic biological processes associated with differential muscle development in males and females, with implications for adaptive fetal programming.