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Population-based studies of human mitochondrial genetic diversity often require the classification of mitochondrial DNA (mtDNA) haplotypes into more than 5400 described haplogroups, and further grouping those into hierarchically higher haplogroups. Such secondary haplogroup groupings (e.g., "macro-haplogroups") vary across studies, as they depend on the sample quality, technical factors of haplogroup calling, the aims of the study, and the researchers' understanding of the mtDNA haplogroup nomenclature. Retention of historical nomenclature coupled with a growing number of newly described mtDNA lineages results in increasingly complex and inconsistent nomenclature that does not reflect phylogeny well. This "clutter" leaves room for grouping errors and inconsistencies across scientific publications, especially when the haplogroup names are used as a proxy for secondary groupings, and represents a source for scientific misinterpretation. Here we explore the effects of phylogenetically insensitive secondary mtDNA haplogroup groupings, and the lack of standardized secondary haplogroup groupings on downstream analyses and interpretation of genetic data. We demonstrate that frequency-based analyses produce inconsistent results when different secondary mtDNA groupings are applied, and thus allow for vastly different interpretations of the same genetic data. The lack of guidelines and recommendations on how to choose appropriate secondary haplogroup groupings presents an issue for the interpretation of results, as well as their comparison and reproducibility across studies. To reduce biases originating from arbitrarily defined secondary nomenclature-based groupings, we suggest that future updates of mtDNA phylogenies aimed for the use in mtDNA haplogroup nomenclature should also provide well-defined and standardized sets of phylogenetically meaningful algorithm-based secondary haplogroup groupings such as "macro-haplogroups", "meso-haplogroups", and "micro-haplogroups". Ideally, each of the secondary haplogroup grouping levels should be informative about different human population history events. Those phylogenetically informative levels of haplogroup groupings can be easily defined using TreeCluster, and then implemented into haplogroup callers such as HaploGrep3. This would foster reproducibility across studies, provide a grouping standard for population-based studies, and reduce errors associated with haplogroup nomenclatures in future studies., (© 2024. The Author(s).)

The European green lizards of the Lacerta viridis complex consist of two closely related species, L. viridis and Lacerta bilineata that split less than 7 million years ago in the presence of gene flow. Recently, a third lineage, referred to as the "Adriatic" was described within the L. viridis complex distributed from Slovenia to Greece. However, whether gene flow between the Adriatic lineage and L. viridis or L. bilineata has occurred and the evolutionary processes involved in their diversification are currently unknown. We hypothesized that divergence occurred in the presence of gene flow between multiple lineages and involved tissue-specific gene evolution. In this study, we sequenced the whole genome of an individual of the Adriatic lineage and tested for the presence of gene flow amongst L. viridis, L. bilineata, and Adriatic. Additionally, we sequenced transcriptomes from multiple tissues to understand tissue-specific effects. The species tree supports that the Adriatic lineage is a sister taxon to L. bilineata. We detected gene flow between the Adriatic lineage and L. viridis suggesting that the evolutionary history of the L. viridis complex is likely shaped by gene flow. Interestingly, we observed topological differences between the autosomal and Z-chromosome phylogenies with a few fast evolving genes on the Z-chromosome. Genes highly expressed in the ovaries and strongly co-expressed in the brain experienced accelerated evolution presumably contributing to establishing reproductive isolation in the L. viridis complex., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Gene regulatory factors (GRFs), such as transcription factors, co-factors and histone-modifying enzymes, play many important roles in modifying gene expression in biological processes. They have also been proposed to underlie speciation and adaptation. To investigate potential contributions of GRFs to primate evolution, we analyzed GRF genes in 27 publicly available primate genomes. Genes coding for zinc finger (ZNF) proteins, especially ZNFs with a Krüppel-associated box (KRAB) domain were the most abundant TFs in all genomes. Gene numbers per TF family differed between all species. To detect signs of positive selection in GRF genes we investigated more than 3,000 human GRFs with their more than 70,000 orthologs in 26 non-human primates. We implemented two independent tests for positive selection, the branch-site-model of the PAML suite and aBSREL of the HyPhy suite, focusing on the human and great ape branch. Our workflow included rigorous procedures to reduce the number of false positives: excluding distantly similar orthologs, manual corrections of alignments, and considering only genes and sites detected by both tests for positive selection. Furthermore, we verified the candidate sites for selection by investigating their variation within human and non-human great ape population data. In order to approximately assign a date to positively selected sites in the human lineage, we analyzed archaic human genomes. Our work revealed with high confidence five GRFs that have been positively selected on the human lineage and one GRF that has been positively selected on the great ape lineage. These GRFs are scattered on different chromosomes and have been previously linked to diverse functions. For some of them a role in speciation and/or adaptation can be proposed based on the expression pattern or association with human diseases, but it seems that they all contributed independently to human evolution. Four of the positively selected GRFs are KRAB-ZNF proteins, that induce changes in target genes co-expression and/or through arms race with transposable elements. Since each positively selected GRF contains several sites with evidence for positive selection, we suggest that these GRFs participated pleiotropically to phenotypic adaptations in humans., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Jovanovic, Sarfert, Reyna-Blanco, Indrischek, Valdivia, Shelest and Nowick.)

Biological and medical sciences are increasingly acknowledging the significance of gene co-expression-networks for investigating complex-systems, phenotypes or diseases. Typically, complex phenotypes are investigated under varying conditions. While approaches for comparing nodes and links in two networks exist, almost no methods for the comparison of multiple networks are available and-to best of our knowledge-no comparative method allows for whole transcriptomic network analysis. However, it is the aim of many studies to compare networks of different conditions, for example, tissues, diseases, treatments, time points, or species. Here we present a method for the systematic comparison of an unlimited number of networks, with unlimited number of transcripts: Co-expression Differential Network Analysis (CoDiNA). In particular, CoDiNA detects links and nodes that are common, specific or different among the networks. We developed a statistical framework to normalize between these different categories of common or changed network links and nodes, resulting in a comprehensive network analysis method, more sophisticated than simply comparing the presence or absence of network nodes. Applying CoDiNA to a neurogenesis study we identified candidate genes involved in neuronal differentiation. We experimentally validated one candidate, demonstrating that its overexpression resulted in a significant disturbance in the underlying gene regulatory network of neurogenesis. Using clinical studies, we compared whole transcriptome co-expression networks from individuals with or without HIV and active tuberculosis (TB) and detected signature genes specific to HIV. Furthermore, analyzing multiple cancer transcription factor (TF) networks, we identified common and distinct features for particular cancer types. These CoDiNA applications demonstrate the successful detection of genes associated with specific phenotypes. Moreover, CoDiNA can also be used for comparing other types of undirected networks, for example, metabolic, protein-protein interaction, ecological and psychometric networks. CoDiNA is publicly available as an R package in CRAN (https://CRAN.R-project.org/package=CoDiNA)., Competing Interests: No competing interests.

Network approaches have become pervasive in many research fields. They allow for a more comprehensive understanding of complex relationships between entities as well as their group-level properties and dynamics. Many networks change over time, be it within seconds or millions of years, depending on the nature of the network. Our focus will be on comparative network analyses in life sciences, where deciphering temporal network changes is a core interest of molecular, ecological, neuropsychological and evolutionary biologists. Further, we will take a journey through different disciplines, such as social sciences, finance and computational gastronomy, to present commonalities and differences in how networks change and can be analysed. Finally, we envision how borrowing ideas from these disciplines could enrich the future of life science research.

The flat periwinkles, Littorina fabalis and L. obtusata, comprise two sister gastropod species that have an enormous potential to elucidate the mechanisms involved in ecological speciation in the marine realm. However, the molecular resources currently available for these species are still scarce. In order to circumvent this limitation, we used RNA-seq data to characterize the transcriptome of four individuals from each species sampled in different locations across the Iberian Peninsula. Four de novo transcriptome assemblies were generated, as well as a pseudo-reference using the L. saxatilis reference transcriptome as backbone. After transcripts' annotation, variant calling resulted in the identification of 19,072 to 45,340 putatively species-diagnostic SNPs. The discriminatory power of a subset of these SNPs was validated by implementing an independent genotyping assay to characterize reference populations, resulting in an accurate classification of individuals into each species and in the identification of hybrids between the two. These data comprise valuable genomic resources for a wide range of evolutionary and conservation studies in flat periwinkles and related taxa.

With the discovery of increasingly more functional noncoding RNAs (ncRNAs), it becomes eminent to more strongly consider them as important players during species evolution. Although tests for negative selection of ncRNAs already exist since the beginning of this century, the SSS-test is the first one for also investigating positive selection. When analyzing selection in ncRNAs, it should be taken into account that selection pressures can independently act on sequence and structure. We applied the SSS-test to explore the evolution of ncRNAs in primates and identified more than 100 long noncoding RNAs (lncRNAs) that might evolve under positive selection in humans. With this test, it is now possible to more thoroughly include ncRNAs into evolutionary studies., Competing Interests: Declaration of conflicting interests:The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Background: Long non-coding RNAs (lncRNAs) play an important role in regulating gene expression and are thus important for determining phenotypes. Most attempts to measure selection in lncRNAs have focused on the primary sequence. The majority of small RNAs and at least some parts of lncRNAs must fold into specific structures to perform their biological function. Comprehensive assessments of selection acting on RNAs therefore must also encompass structure. Selection pressures acting on the structure of non-coding genes can be detected within multiple sequence alignments. Approaches of this type, however, have so far focused on negative selection. Thus, a computational method for identifying ncRNAs under positive selection is needed., Results: We introduce the SSS-test (test for Selection on Secondary Structure) to identify positive selection and thus adaptive evolution. Benchmarks with biological as well as synthetic controls yield coherent signals for both negative and positive selection, demonstrating the functionality of the test. A survey of a lncRNA collection comprising 15,443 families resulted in 110 candidates that appear to be under positive selection in human. In 26 lncRNAs that have been associated with psychiatric disorders we identified local structures that have signs of positive selection in the human lineage., Conclusions: It is feasible to assay positive selection acting on RNA secondary structures on a genome-wide scale. The detection of human-specific positive selection in lncRNAs associated with cognitive disorder provides a set of candidate genes for further experimental testing and may provide insights into the evolution of cognitive abilities in humans., Availability: The SSS-test and related software is available at: https://github.com/waltercostamb/SSS-test . The databases used in this work are available at: http://www.bioinf.uni-leipzig.de/Software/SSS-test/ .

Background: Lacerta viridis and Lacerta bilineata are sister species of European green lizards (eastern and western clades, respectively) that, until recently, were grouped together as the L. viridis complex. Genetic incompatibilities were observed between lacertid populations through crossing experiments, which led to the delineation of two separate species within the L. viridis complex. The population history of these sister species and processes driving divergence are unknown. We constructed the first high-quality de novo genome assemblies for both L. viridis and L. bilineata through Illumina and PacBio sequencing, with annotation support provided from transcriptome sequencing of several tissues. To estimate gene flow between the two species and identify factors involved in reproductive isolation, we studied their evolutionary history, identified genomic rearrangements, detected signatures of selection on non-coding RNA, and on protein-coding genes., Findings: Here we show that gene flow was primarily unidirectional from L. bilineata to L. viridis after their split at least 1.15 million years ago. We detected positive selection of the non-coding repertoire; mutations in transcription factors; accumulation of divergence through inversions; selection on genes involved in neural development, reproduction, and behavior, as well as in ultraviolet-response, possibly driven by sexual selection, whose contribution to reproductive isolation between these lacertid species needs to be further evaluated., Conclusion: The combination of short and long sequence reads resulted in one of the most complete lizard genome assemblies. The characterization of a diverse array of genomic features provided valuable insights into the demographic history of divergence among European green lizards, as well as key species differences, some of which are candidates that could have played a role in speciation. In addition, our study generated valuable genomic resources that can be used to address conservation-related issues in lacertids., (© The Author(s) 2018. Published by Oxford University Press.)

Background: Network analyses, such as of gene co-expression networks, metabolic networks and ecological networks have become a central approach for the systems-level study of biological data. Several software packages exist for generating and analyzing such networks, either from correlation scores or the absolute value of a transformed score called weighted topological overlap (wTO). However, since gene regulatory processes can up- or down-regulate genes, it is of great interest to explicitly consider both positive and negative correlations when constructing a gene co-expression network., Results: Here, we present an R package for calculating the weighted topological overlap (wTO), that, in contrast to existing packages, explicitly addresses the sign of the wTO values, and is thus especially valuable for the analysis of gene regulatory networks. The package includes the calculation of p-values (raw and adjusted) for each pairwise gene score. Our package also allows the calculation of networks from time series (without replicates). Since networks from independent datasets (biological repeats or related studies) are not the same due to technical and biological noise in the data, we additionally, incorporated a novel method for calculating a consensus network (CN) from two or more networks into our R package. To graphically inspect the resulting networks, the R package contains a visualization tool, which allows for the direct network manipulation and access of node and link information. When testing the package on a standard laptop computer, we can conduct all calculations for systems of more than 20,000 genes in under two hours. We compare our new wTO package to state of art packages and demonstrate the application of the wTO and CN functions using 3 independently derived datasets from healthy human pre-frontal cortex samples. To showcase an example for the time series application we utilized a metagenomics data set., Conclusion: In this work, we developed a software package that allows the computation of wTO networks, CNs and a visualization tool in the R statistical environment. It is publicly available on CRAN repositories under the GPL -2 Open Source License ( https://cran.r-project.org/web/packages/wTO/ ).

Non-coding RNAs regulate many biological processes including neurogenesis. The brain-enriched miR-124 has been assigned as a key player of neuronal differentiation via its complex but little understood regulation of thousands of annotated targets. To systematically chart its regulatory functions, we used CRISPR/Cas9 gene editing to disrupt all six miR-124 alleles in human induced pluripotent stem cells. Upon neuronal induction, miR-124-deleted cells underwent neurogenesis and became functional neurons, albeit with altered morphology and neurotransmitter specification. Using RNA-induced-silencing-complex precipitation, we identified 98 high-confidence miR-124 targets, of which some directly led to decreased viability. By performing advanced transcription-factor-network analysis, we identified indirect miR-124 effects on apoptosis, neuronal subtype differentiation, and the regulation of previously uncharacterized zinc finger transcription factors. Our data emphasize the need for combined experimental- and system-level analyses to comprehensively disentangle and reveal miRNA functions, including their involvement in the neurogenesis of diverse neuronal cell types found in the human brain., (Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.)

The human prefrontal cortex (PFC) differs from that of other primates with respect to size, histology, and functional abilities. Here, we analyzed genome-wide expression data of humans, chimpanzees, and rhesus macaques to discover evolutionary changes in transcription factor (TF) networks that may underlie these phenotypic differences. We determined the co-expression networks of all TFs with species-specific expression including their potential target genes and interaction partners in the PFC of all three species. Integrating these networks allowed us inferring an ancestral network for all three species. This ancestral network as well as the networks for each species is enriched for genes involved in forebrain development, axonogenesis, and synaptic transmission. Our analysis allows us to directly compare the networks of each species to determine which links have been gained or lost during evolution. Interestingly, we detected that most links were gained on the human lineage, indicating increase TF cooperativity in humans. By comparing network changes between different tissues, we discovered that in brain tissues, but not in the other tissues, the human networks always had the highest connectivity. To pinpoint molecular changes underlying species-specific phenotypes, we analyzed the sub-networks of TFs derived only from genes with species-specific expression changes in the PFC. These sub-networks differed significantly in structure and function between the human and chimpanzee. For example, the human-specific sub-network is enriched for TFs implicated in cognitive disorders and for genes involved in synaptic plasticity and cognitive functions. Our results suggest evolutionary changes in TF networks that might have shaped morphological and functional differences between primate brains, in particular in the human PFC.

The Human Accelerated Region 1 (HAR1) is the most rapidly evolving region in the human genome. It is part of two overlapping long non-coding RNAs, has a length of only 118 nucleotides and features 18 human specific changes compared to an ancestral sequence that is extremely well conserved across non-human primates. The human HAR1 forms a stable secondary structure that is strikingly different from the one in chimpanzee as well as other closely related species, again emphasizing its human-specific evolutionary history. This suggests that positive selection has acted to stabilize human-specific features in the ensemble of HAR1 secondary structures. To investigate the evolutionary history of the human HAR1 structure, we developed a computational model that evaluates the relative likelihood of evolutionary trajectories as a probabilistic version of a Hamiltonian path problem. The model predicts that the most likely last step in turning the ancestral primate HAR1 into the human HAR1 was exactly the substitution that distinguishes the modern human HAR1 sequence from that of Denisovan, an archaic human, providing independent support for our model. The MutationOrder software is available for download and can be applied to other instances of RNA structure evolution., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Differential co-expression network analyses have recently become an important step in the investigation of cellular differentiation and dysfunctional gene-regulation in cell and tissue disease-states. The resulting networks have been analyzed to identify and understand pathways associated with disorders, or to infer molecular interactions. However, existing methods for differential co-expression network analysis are unable to distinguish between various forms of differential co-expression. To close this gap, here we define the three different kinds (conserved, specific, and differentiated) of differential co-expression and present a systematic framework, CSD, for differential co-expression network analysis that incorporates these interactions on an equal footing. In addition, our method includes a subsampling strategy to estimate the variance of co-expressions. Our framework is applicable to a wide variety of cases, such as the study of differential co-expression networks between healthy and disease states, before and after treatments, or between species. Applying the CSD approach to a published gene-expression data set of cerebral cortex and basal ganglia samples from healthy individuals, we find that the resulting CSD network is enriched in genes associated with cognitive function, signaling pathways involving compounds with well-known roles in the central nervous system, as well as certain neurological diseases. From the CSD analysis, we identify a set of prominent hubs of differential co-expression, whose neighborhood contains a substantial number of genes associated with glioblastoma. The resulting gene-sets identified by our CSD analysis also contain many genes that so far have not been recognized as having a role in glioblastoma, but are good candidates for further studies. CSD may thus aid in hypothesis-generation for functional disease-associations.

Background: Organisms typically face infection by diverse pathogens, and hosts are thought to have developed specific responses to each type of pathogen they encounter. The advent of transcriptomics now makes it possible to test this hypothesis and compare host gene expression responses to multiple pathogens at a genome-wide scale. Here, we performed a meta-analysis of multiple published and new transcriptomes using a newly developed bioinformatics approach that filters genes based on their expression profile across datasets. Thereby, we identified common and unique molecular responses of a model host species, the honey bee (Apis mellifera), to its major pathogens and parasites: the Microsporidia Nosema apis and Nosema ceranae, RNA viruses, and the ectoparasitic mite Varroa destructor, which transmits viruses., Results: We identified a common suite of genes and conserved molecular pathways that respond to all investigated pathogens, a result that suggests a commonality in response mechanisms to diverse pathogens. We found that genes differentially expressed after infection exhibit a higher evolutionary rate than non-differentially expressed genes. Using our new bioinformatics approach, we unveiled additional pathogen-specific responses of honey bees; we found that apoptosis appeared to be an important response following microsporidian infection, while genes from the immune signalling pathways, Toll and Imd, were differentially expressed after Varroa/virus infection. Finally, we applied our bioinformatics approach and generated a gene co-expression network to identify highly connected (hub) genes that may represent important mediators and regulators of anti-pathogen responses., Conclusions: Our meta-analysis generated a comprehensive overview of the host metabolic and other biological processes that mediate interactions between insects and their pathogens. We identified key host genes and pathways that respond to phylogenetically diverse pathogens, representing an important source for future functional studies as well as offering new routes to identify or generate pathogen resilient honey bee stocks. The statistical and bioinformatics approaches that were developed for this study are broadly applicable to synthesize information across transcriptomic datasets. These approaches will likely have utility in addressing a variety of biological questions.

We sequenced the mitochondrial genome of the Western green lizard (Lacerta bilineata) using Illumina technology and additional Sanger sequencing. The assembled 17 086 bp mitogenome had a GC content of 40.32% and consisted of 13 protein-coding genes, 22 tRNA genes, two rRNA genes, and one control region (CR), with a gene order identical to the chordate consensus. In addition, we re-sequenced the mitogenome of the closely related Eastern green lizard L. viridis using the same techniques as for L. bilineata. The mitogenomes of L. bilineata and L. viridis showed a sequence identity of 94.4% and 99.9%, respectively, relative to the previously published L. viridis mitogenome. The phylogenetic reconstruction based on 17 Lacertinae mitogenomes using Anolis carolinensis as the outgroup supported L. bilineata and its sister species L. viridis as distinct lineages.

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 Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

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.

Function is a central concept in biological theories and explanations. Yet discussions about function are often based on a narrow understanding of biological systems and processes, such as idealized molecular systems or simple evolutionary, i.e., selective, dynamics. Conflicting conceptions of function continue to be used in the scientific literature to support certain claims, for instance about the fraction of "functional DNA" in the human genome. Here we argue that all biologically meaningful interpretations of function are necessarily context dependent. This implies that they derive their meaning as well as their range of applicability only within a specific theoretical and measurement context. We use this framework to shed light on the current debate about functional DNA and argue that without considering explicitly the theoretical and measurement contexts all attempts to integrate biological theories are prone to fail.

Over the last decade, methods have been developed for the reconstruction of gene trees that take into account the species tree. Many of these methods have been based on the probabilistic duplication-loss model, which describes how a gene-tree evolves over a species-tree with respect to duplication and losses, as well as extension of this model, e.g., the DLRS (Duplication, Loss, Rate and Sequence evolution) model that also includes sequence evolution under relaxed molecular clock. A disjoint, almost as recent, and very important line of research has been focused on non protein-coding, but yet, functional DNA. For instance, DNA sequences being pseudogenes in the sense that they are not translated, may still be transcribed and the thereby produced RNA may be functional.

Deciphering the molecular basis of how modern human phenotypes have evolved is one of the most fascinating challenges in biology. Here, we will focus on the roles of gene regulatory factors (GRFs), in particular transcription factors (TFs) and long non-coding RNAs (lncRNAs) during human evolution. We will present examples of TFs and lncRNAs that have changed or show signs of positive selection in humans compared to chimpanzees, in modern humans compared to archaic humans, or within modern human populations. On the basis of current knowledge about the functions of these GRF genes, we speculate that they have been involved in speciation as well as in shaping phenotypes such as brain functions, skeletal morphology, and metabolic processes., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

To fully understand human biology and link genotype to phenotype, the phase of DNA variants must be known. Here we present a comprehensive analysis of haplotype-resolved genomes to assess the nature and variation of haplotypes and their pairs, diplotypes, in European population samples. We use a set of 14 haplotype-resolved genomes generated by fosmid clone-based sequencing, complemented and expanded by up to 372 statistically resolved genomes from the 1000 Genomes Project. We find immense diversity of both haploid and diploid gene forms, up to 4.1 and 3.9 million corresponding to 249 and 235 per gene on average. Less than 15% of autosomal genes have a predominant form. We describe a 'common diplotypic proteome', a set of 4,269 genes encoding two different proteins in over 30% of genomes. We show moreover an abundance of cis configurations of mutations in the 386 genomes with an average cis/trans ratio of 60:40, and distinguishable classes of cis- versus trans-abundant genes. This work identifies key features characterizing the diplotypic nature of human genomes and provides a conceptual and analytical framework, rich resources and novel hypotheses on the functional importance of diploidy.

The mechanisms of speciation have been one of the most debated topics in evolutionary biology. Among all reproductive barriers, postzygotic reproductive isolation is perhaps the one that has attracted the most attention from geneticists. Despite remarkable advances in the identification of loci involved in Drosophila speciation, little is known about the genes, functions, and biochemical interactions of the molecules underlying hybrid sterility and inviability in mammals. Here, we discuss the main evolutionary and molecular features that make transcription factors (TFs), especially the family of zinc finger proteins with a Krüppel-associated box domain (KRAB-ZNF), strong candidates to play an important role in postzygotic reproductive isolation. Motivated by the recent identification of the gene encoding PR domain zinc finger protein 9 (Prdm9; a KRAB-ZNF gene) as the first hybrid sterility gene identified in mammals, we further propose integrative approaches to study KRAB-ZNF genes with the main goal of characterizing the molecular pathways and interactions involved in hybrid incompatibilities., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Independent determination of both haplotype sequences of an individual genome is essential to relate genetic variation to genome function, phenotype, and disease. To address the importance of phase, we have generated the most complete haplotype-resolved genome to date, "Max Planck One" (MP1), by fosmid pool-based next generation sequencing. Virtually all SNPs (>99%) and 80,000 indels were phased into haploid sequences of up to 6.3 Mb (N50 ~1 Mb). The completeness of phasing allowed determination of the concrete molecular haplotype pairs for the vast majority of genes (81%) including potential regulatory sequences, of which >90% were found to be constituted by two different molecular forms. A subset of 159 genes with potentially severe mutations in either cis or trans configurations exemplified in particular the role of phase for gene function, disease, and clinical interpretation of personal genomes (e.g., BRCA1). Extended genomic regions harboring manifold combinations of physically and/or functionally related genes and regulatory elements were resolved into their underlying "haploid landscapes," which may define the functional genome. Moreover, the majority of genes and functional sequences were found to contain individual or rare SNPs, which cannot be phased from population data alone, emphasizing the importance of molecular phasing for characterizing a genome in its molecular individuality. Our work provides the foundation to understand that the distinction of molecular haplotypes is essential to resolve the (inherently individual) biology of genes, genomes, and disease, establishing a reference point for "phase-sensitive" personal genomics. MP1's annotated haploid genomes are available as a public resource.

The molecular changes underlying major phenotypic differences between humans and other primates are not well understood, but alterations in gene regulation are likely to play a major role. Here we performed a thorough evolutionary analysis of the largest family of primate transcription factors, the Krüppel-type zinc finger (KZNF) gene family. We identified and curated gene and pseudogene models for KZNFs in three primate species, chimpanzee, orangutan and rhesus macaque, to allow for a comparison with the curated set of human KZNFs. We show that the recent evolutionary history of primate KZNFs has been complex, including many lineage-specific duplications and deletions. We found 213 species-specific KZNFs, among them 7 human-specific and 23 chimpanzee-specific genes. Two human-specific genes were validated experimentally. Ten genes have been lost in humans and 13 in chimpanzees, either through deletion or pseudogenization. We also identified 30 KZNF orthologs with human-specific and 42 with chimpanzee-specific sequence changes that are predicted to affect DNA binding properties of the proteins. Eleven of these genes show signatures of accelerated evolution, suggesting positive selection between humans and chimpanzees. During primate evolution the most extensive re-shaping of the KZNF repertoire, including most gene additions, pseudogenizations, and structural changes occurred within the subfamily homininae. Using zinc finger (ZNF) binding predictions, we suggest potential impact these changes have had on human gene regulatory networks. The large species differences in this family of TFs stands in stark contrast to the overall high conservation of primate genomes and potentially represents a potent driver of primate evolution.

Humans differ from other primates by marked differences in cognitive abilities and a significantly larger brain. These differences correlate with metabolic changes, as evidenced by the relative up-regulation of energy-related genes and metabolites in human brain. While the mechanisms underlying these evolutionary changes have not been elucidated, altered activities of key transcription factors (TFs) could play a pivotal role. To assess this possibility, we analyzed microarray data from five tissues from humans and chimpanzees. We identified 90 TF genes with significantly different expression levels in human and chimpanzee brain among which the rapidly evolving KRAB-zinc finger genes are markedly over-represented. The differentially expressed TFs cluster within a robust regulatory network consisting of two distinct but interlinked modules, one strongly associated with energy metabolism functions, and the other with transcription, vesicular transport, and ubiquitination. Our results suggest that concerted changes in a relatively small number of interacting TFs may coordinate major gene expression differences in human and chimpanzee brain.

Basal (intermediate) progenitors are the major source of neurons in the mammalian neocortex. The molecular machinery governing basal progenitor biogenesis is unknown. Here, we show that the zinc-finger transcription factor Insm1 (insulinoma-associated 1) is expressed specifically in progenitors undergoing neurogenic divisions, has a panneurogenic role throughout the brain, and promotes basal progenitor formation in the neocortex. Mouse embryos lacking Insm1 contained half the number of basal progenitors and showed a marked reduction in cortical plate radial thickness. Forced premature expression of Insm1 in neuroepithelial cells resulted in their mitosis occurring at the basal (rather than apical) side of the ventricular zone and induced expression of the basal progenitor marker Tbr2. Remarkably, these cells remained negative for Tis21, a marker of neurogenic progenitors, and did not generate neurons but underwent self-amplification. Our data imply that Insm1 is involved in the generation and expansion of basal progenitors, a hallmark of neocortex evolution.

FOXP (FOXP1-4) is a newly defined subfamily of the forkhead box (FOX) transcription factors. A mutation in the FOXP2 forkhead domain cosegregates with a severe speech disorder, whereas several mutations in the FOXP3 forkhead domain are linked to the IPEX syndrome in human and a similar autoimmune phenotype in mice. Here we report a 1.9 A crystal structure of the forkhead domain of human FOXP2 bound to DNA. This structure allows us to revise the previously proposed DNA recognition mechanism and provide a unifying model of DNA binding for the FOX family of proteins. Our studies also reveal that the FOXP2 forkhead domain can form a domain-swapped dimer, made possible by a strategic substitution of a highly conserved proline in conventional FOX proteins with alanine in the P subfamily. Disease-causing mutations in FOXP2 and FOXP3 map either to the DNA binding surface or the domain-swapping dimer interface, functionally corroborating the crystal structure.

The determination of the chimpanzee genome sequence provides a means to study both structural and functional aspects of the evolution of the human genome. Here we compare humans and chimpanzees with respect to differences in expression levels and protein-coding sequences for genes active in brain, heart, liver, kidney, and testis. We find that the patterns of differences in gene expression and gene sequences are markedly similar. In particular, there is a gradation of selective constraints among the tissues so that the brain shows the least differences between the species whereas liver shows the most. Furthermore, expression levels as well as amino acid sequences of genes active in more tissues have diverged less between the species than have genes active in fewer tissues. In general, these patterns are consistent with a model of neutral evolution with negative selection. However, for X-chromosomal genes expressed in testis, patterns suggestive of positive selection on sequence changes as well as expression changes are seen. Furthermore, although genes expressed in the brain have changed less than have genes expressed in other tissues, in agreement with previous work we find that genes active in brain have accumulated more changes on the human than on the chimpanzee lineage.

A controlled prospective study was conducted to evaluate possible effects of the use of three intrapartum fetal monitoring techniques on the offspring of high-risk mothers in labor after at least 34 weeks' gestation. Six hundred and ninety women were randomly assigned to one of the three monitoring groups: auscultation alone, electronic monitoring alone, and electronic monitoring with option to obtain fetal scalp pH. There were no significant differences among the three groups of offspring with respect to neonatal mortality or morbidity, Apgar scores, cord blood gas values, or Brazelton examinations at ages 2 to 3 days. Assessment of the infants at 9 months revealed no significant differences in their growth and development as assessed by physical examination. Bayley Scales of Infant Development, and Milani-Comparetti tests. The frequency of delivery by cesarean section was significantly higher in the electronically monitored group than in the auscultated group. This study failed to show beneficial effects of electronic fetal monitoring over auscultated monitoring for high-risk but relatively mature fetuses.