Comparative genomics as a tool to understand evolution and disease

Evolutionary origin of germline pathogenic variants in human DNA mismatch repair genes

BACKGROUND

Mismatch repair (MMR) system is evolutionarily conserved for genome stability maintenance. Germline pathogenic variants (PVs) in MMR genes that lead to MMR functional deficiency are associated with high cancer risk. Knowing the evolutionary origin of germline PVs in human MMR genes will facilitate understanding the biological base of MMR deficiency in cancer. However, systematic knowledge is lacking to address the issue. In this study, we performed a comprehensive analysis to know the evolutionary origin of human MMR PVs.

METHODS

We retrieved MMR gene variants from the ClinVar database. The genomes of 100 vertebrates were collected from the UCSC genome browser and ancient human sequencing data were obtained through comprehensive data mining. Cross-species conservation analysis was performed based on the phylogenetic relationship among 100 vertebrates. Rescaled ancient sequencing data were used to perform variant calling for archeological analysis.

RESULTS

Using the phylogenetic approach, we traced the 3369 MMR PVs identified in modern humans in 99 non-human vertebrate genomes but found no evidence for cross-species conservation as the source for human MMR PVs. Using the archeological approach, we searched the human MMR PVs in over 5000 ancient human genomes dated from 45,045 to 100 years before present and identified a group of MMR PVs shared between modern and ancient humans mostly within 10,000 years with similar quantitative patterns.

CONCLUSION

Our study reveals that MMR PVs in modern humans were arisen within the recent human evolutionary history.

Revolutionizing Biological Science: The Synergy of Genomics in Health, Bioinformatics, Agriculture, and Artificial Intelligence

With climate emergency, COVID-19, and the rise of planetary health scholarship, the binary of human and ecosystem health has been deeply challenged. The interdependence of human and nonhuman animal health is increasingly acknowledged and paving the way for new frontiers in integrative biology. The convergence of genomics in health, bioinformatics, agriculture, and artificial intelligence (AI) has ushered in a new era of possibilities and applications. However, the sheer volume of genomic/multiomics big data generated also presents formidable sociotechnical challenges in extracting meaningful biological, planetary health and ecological insights. Over the past few years, AI-guided bioinformatics has emerged as a powerful tool for managing, analyzing, and interpreting complex biological datasets. The advances in AI, particularly in machine learning and deep learning, have been transforming the fields of genomics, planetary health, and agriculture. This article aims to unpack and explore the formidable range of possibilities and challenges that result from such transdisciplinary integration, and emphasizes its radically transformative potential for human and ecosystem health. The integration of these disciplines is also driving significant advancements in precision medicine and personalized health care. This presents an unprecedented opportunity to deepen our understanding of complex biological systems and advance the well-being of all life in planetary ecosystems. Notwithstanding in mind its sociotechnical, ethical, and critical policy challenges, the integration of genomics, multiomics, planetary health, and agriculture with AI-guided bioinformatics opens up vast opportunities for transnational collaborative efforts, data sharing, analysis, valorization, and interdisciplinary innovations in life sciences and integrative biology.

Evolution of neuronal cell classes and types in the vertebrate retina

The basic plan of the retina is conserved across vertebrates, yet species differ profoundly in their visual needs1. Retinal cell types may have evolved to accommodate these varied needs, but this has not been systematically studied. Here we generated and integrated single-cell transcriptomic atlases of the retina from 17 species: humans, two non-human primates, four rodents, three ungulates, opossum, ferret, tree shrew, a bird, a reptile, a teleost fish and a lamprey. We found high molecular conservation of the six retinal cell classes (photoreceptors, horizontal cells, bipolar cells, amacrine cells, retinal ganglion cells (RGCs) and Müller glia), with transcriptomic variation across species related to evolutionary distance. Major subclasses were also conserved, whereas variation among cell types within classes or subclasses was more pronounced. However, an integrative analysis revealed that numerous cell types are shared across species, based on conserved gene expression programmes that are likely to trace back to an early ancestral vertebrate. The degree of variation among cell types increased from the outer retina (photoreceptors) to the inner retina (RGCs), suggesting that evolution acts preferentially to shape the retinal output. Finally, we identified rodent orthologues of midget RGCs, which comprise more than 80% of RGCs in the human retina, subserve high-acuity vision, and were previously believed to be restricted to primates2. By contrast, the mouse orthologues have large receptive fields and comprise around 2% of mouse RGCs. Projections of both primate and mouse orthologous types are overrepresented in the thalamus, which supplies the primary visual cortex. We suggest that midget RGCs are not primate innovations, but are descendants of evolutionarily ancient types that decreased in size and increased in number as primates evolved, thereby facilitating high visual acuity and increased cortical processing of visual information.

Comparative Genomics Identifies the Evolutionarily Conserved Gene TPM3 as a Target of eca-miR-1 Involved in the Skeletal Muscle Development of Donkeys

Species within the genus Equus are valued for their draft ability. Skeletal muscle forms the foundation of the draft ability of Equus species; however, skeletal muscle development-related conserved genes and their target miRNAs are rarely reported for Equus. In this study, a comparative genomics analysis was performed among five species (horse, donkey, zebra, cattle, and goat), and the results showed that a total of 15,262 (47.43%) genes formed the core gene set of the five species. Only nine chromosomes (Chr01, Chr02, Chr03, Chr06, Chr10, Chr18, Chr22, Chr27, Chr29, and Chr30) exhibited a good collinearity relationship among Equus species. The micro-synteny analysis results showed that TPM3 was evolutionarily conserved in chromosome 1 in Equus. Furthermore, donkeys were used as the model species for Equus to investigate the genetic role of TPM3 in muscle development. Interestingly, the results of comparative transcriptomics showed that the TPM3 gene was differentially expressed in donkey skeletal muscle S1 (2 months old) and S2 (24 months old), as verified via RT-PCR. Dual-luciferase test analysis showed that the TPM3 gene was targeted by differentially expressed miRNA (eca-miR-1). Furthermore, a total of 17 TPM3 gene family members were identified in the whole genome of donkey, and a heatmap analysis showed that EaTPM3-5 was a key member of the TPM3 gene family, which is involved in skeletal muscle development. In conclusion, the TPM3 gene was conserved in Equus, and EaTPM3-5 was targeted by eca-miR-1, which is involved in skeletal muscle development in donkeys.

Learning functional conservation between human and pig to decipher evolutionary mechanisms underlying gene expression and complex traits

Assessment of genomic conservation between humans and pigs at the functional level can improve the potential of pigs as a human biomedical model. To address this, we developed a deep learning-based approach to learn the genomic conservation at the functional level (DeepGCF) between species by integrating 386 and 374 functional profiles from humans and pigs, respectively. DeepGCF demonstrated better prediction performance compared with the previous method. In addition, the resulting DeepGCF score captures the functional conservation between humans and pigs by examining chromatin states, sequence ontologies, and regulatory variants. We identified a core set of genomic regions as functionally conserved that plays key roles in gene regulation and is enriched for the heritability of complex traits and diseases in humans. Our results highlight the importance of cross-species functional comparison in illustrating the genetic and evolutionary basis of complex phenotypes.

Decoding DNA sequence-driven evolution of the human brain epigenome at cellular resolution

DNA-based evolutionary comparisons of regulatory genomic elements enable insight into functional changes, overcoming tissue inaccessibility. Here, we harnessed adult and fetal cortex single-cell ATAC-seq datasets to uncover DNA substitutions specific to the human and human-ancestral lineages within apes. We found that fetal microglia identity is evolutionarily divergent in all lineages, whereas other cell types are conserved. Using multiomic datasets, we further identified genes linked to multiple lineage-divergent gene regulatory elements and implicated biological pathways associated with these divergent features. We also uncovered patterns of transcription factor binding site evolution across lineages and identified expansion of bHLH-PAS factor targets in human-hominin lineages, and MEF2 factor targets in the ape lineage. Finally, conserved features were more enriched in brain disease variants, whereas there was no distinct enrichment on the human lineage compared to its ancestral lineages. Our study identifies major evolutionary patterns in the human brain epigenome at cellular resolution.

Comparative neurogenetics of dog behavior complements efforts towards human neuropsychiatric genetics

Domestic dogs display a wide array of heritable behaviors that have intermediate genetic complexity thanks to a long history of human-influenced selection. Comparative genetics in dogs could address the scarcity of non-human neurogenetic systems relevant to human neuropsychiatric disorders, which are characterized by mental, emotional, and behavioral symptoms and involve vastly complex genetic and non-genetic risk factors. Our review describes the diverse behavioral "phenome" of domestic dogs, past and ongoing sources of behavioral selection, and the state of canine behavioral genetics. We highlight two naturally disordered behavioral domains that illustrate how dogs may prove useful as a comparative, forward neurogenetic system: canine age-related cognitive dysfunction, which can be examined more rapidly given the attenuated lifespan of dogs, and compulsive disorders, which may have genetic roots in purpose-bred behaviors. Growing community science initiatives aimed at the companion dog population will be well suited to investigating such complex behavioral phenotypes and offer a comparative resource that parallels human genomic initiatives in scale and dimensionality.

The Relationship between Cognition and Brain Size or Neuron Number

The comparative approach is a powerful way to explore the relationship between brain structure and cognitive function. Thus far, the field has been dominated by the assumption that a bigger brain somehow means better cognition. Correlations between differences in brain size or neuron number between species and differences in specific cognitive abilities exist, but these correlations are very noisy. Extreme differences exist between clades in the relationship between either brain size or neuron number and specific cognitive abilities. This means that correlations become weaker, not stronger, as the taxonomic diversity of sampled groups increases. Cognition is the outcome of neural networks. Here we propose that considering plausible neural network models will advance our understanding of the complex relationships between neuron number and different aspects of cognition. Computational modelling of networks suggests that adding pathways, or layers, or changing patterns of connectivity in a network can all have different specific consequences for cognition. Consequently, models of computational architecture can help us hypothesise how and why differences in neuron number might be related to differences in cognition. As methods in connectomics continue to improve and more structural information on animal brains becomes available, we are learning more about natural network structures in brains, and we can develop more biologically plausible models of cognitive architecture. Natural animal diversity then becomes a powerful resource to both test the assumptions of these models and explore hypotheses for how neural network structure and network size might delimit cognitive function.

Comparing genomic and epigenomic features across species using the WashU Comparative Epigenome Browser

Genome browsers have become an intuitive and critical tool to visualize and analyze genomic features and data. Conventional genome browsers display data/annotations on a single reference genome/assembly; there are also genomic alignment viewer/browsers that help users visualize alignment, mismatch, and rearrangement between syntenic regions. However, there is a growing need for a comparative epigenome browser that can display genomic and epigenomic data sets across different species and enable users to compare them between syntenic regions. Here, we present the WashU Comparative Epigenome Browser. It allows users to load functional genomic data sets/annotations mapped to different genomes and display them over syntenic regions simultaneously. The browser also displays genetic differences between the genomes from single-nucleotide variants (SNVs) to structural variants (SVs) to visualize the association between epigenomic differences and genetic differences. Instead of anchoring all data sets to the reference genome coordinates, it creates independent coordinates of different genome assemblies to faithfully present features and data mapped to different genomes. It uses a simple, intuitive genome-align track to illustrate the syntenic relationship between different species. It extends the widely used WashU Epigenome Browser infrastructure and can be expanded to support multiple species. This new browser function will greatly facilitate comparative genomic/epigenomic research, as well as support the recent growing needs to directly compare and benchmark the T2T CHM13 assembly and other human genome assemblies.

Evolution of neuronal cell classes and types in the vertebrate retina

The basic plan of the retina is conserved across vertebrates, yet species differ profoundly in their visual needs (Baden et al., 2020). One might expect that retinal cell types evolved to accommodate these varied needs, but this has not been systematically studied. Here, we generated and integrated single-cell transcriptomic atlases of the retina from 17 species: humans, two non-human primates, four rodents, three ungulates, opossum, ferret, tree shrew, a teleost fish, a bird, a reptile and a lamprey. Molecular conservation of the six retinal cell classes (photoreceptors, horizontal cells, bipolar cells, amacrine cells, retinal ganglion cells [RGCs] and Muller glia) is striking, with transcriptomic differences across species correlated with evolutionary distance. Major subclasses are also conserved, whereas variation among types within classes or subclasses is more pronounced. However, an integrative analysis revealed that numerous types are shared across species based on conserved gene expression programs that likely trace back to the common ancestor of jawed vertebrates. The degree of variation among types increases from the outer retina (photoreceptors) to the inner retina (RGCs), suggesting that evolution acts preferentially to shape the retinal output. Finally, we identified mammalian orthologs of midget RGCs, which comprise >80% of RGCs in the human retina, subserve high-acuity vision, and were believed to be primate-specific (Berson, 2008); in contrast, the mouse orthologs comprise <2% of mouse RGCs. Projections both primate and mouse orthologous types are overrepresented in the thalamus, which supplies the primary visual cortex. We suggest that midget RGCs are not primate innovations, but descendants of evolutionarily ancient types that decreased in size and increased in number as primates evolved, thereby facilitating high visual acuity and increased cortical processing of visual information.

A Cross-Species Analysis Reveals Dysthyroidism of the Ovaries as a Common Trait of Premature Ovarian Aging

Although the imbalance of circulating levels of Thyroid Hormones (THs) affects female fertility in vertebrates, its involvement in the promotion of Premature Ovarian Aging (POA) is debated. Therefore, altered synthesis of THs in both thyroid and ovary can be a trait of POA. We investigated the relationship between abnormal TH signaling, dysthyroidism, and POA in evolutionary distant vertebrates: from zebrafish to humans. Ovarian T3 signaling/metabolism was evaluated by measuring T3 levels, T3 responsive transcript, and protein levels along with transcripts governing T3 availability (deiodinases) and signaling (TH receptors) in distinct models of POA depending on genetic background and environmental exposures (e.g., diets, pesticides). Expression levels of well-known (Amh, Gdf9, and Inhibins) and novel (miR143/145 and Gas5) biomarkers of POA were assessed. Ovarian dysthyroidism was slightly influenced by genetics since very few differences were found between C57BL/6J and FVB/NJ females. However, diets exacerbated it in a strain-dependent manner. Similar findings were observed in zebrafish and mouse models of POA induced by developmental and long-life exposure to low-dose chlorpyrifos (CPF). Lastly, the T3 decrease in follicular fluids from women affected by diminished ovarian reserve, as well as of the transcripts modulating T3 signaling/availability in the cumulus cells, confirmed ovarian dysthyroidism as a common and evolutionary conserved trait of POA.

Systematic annotation of conservation states provides insights into regulatory regions in rice

Plant genomes contain a large fraction of noncoding sequences. The discovery and annotation of conserved noncoding sequences (CNSs) in plants is an ongoing challenge. Here we report the application of comparative genomics to systematically identify CNSs in 50 well-annotated Gramineae genomes using rice (Oryza sativa) as the reference. We conduct multiple-way whole-genome alignments to the rice genome. The rice genome is annotated as 20 conservation states (CSs) at single-nucleotide resolution using a multivariate hidden Markov model (ConsHMM) based on the multiple-genome alignments. Different states show distinct enrichments for various genomic features, and the conservation scores of CSs are highly correlated with the level of associated chromatin accessibility. We find that at least 33.5% of the rice genome is highly under selection, with more than 70% of the sequence lying outside of coding regions. A catalog of 855,366 regulatory CNSs is generated, and they significantly overlapped with putative active regulatory elements such as promoters, enhancers, and transcription factor binding sites. Collectively, our study provides a resource for elucidating functional noncoding regions of the rice genome and an evolutionary aspect of regulatory sequences in higher plants.

Reproducible acquisition, management and meta-analysis of nucleotide sequence (meta)data using q2-fondue

MOTIVATION

The volume of public nucleotide sequence data has blossomed over the past two decades and is ripe for re- and meta-analyses to enable novel discoveries. However, reproducible re-use and management of sequence datasets and associated metadata remain critical challenges. We created the open source Python package q2-fondue to enable user-friendly acquisition, re-use and management of public sequence (meta)data while adhering to open data principles.

RESULTS

q2-fondue allows fully provenance-tracked programmatic access to and management of data from the NCBI Sequence Read Archive (SRA). Unlike other packages allowing download of sequence data from the SRA, q2-fondue enables full data provenance tracking from data download to final visualization, integrates with the QIIME 2 ecosystem, prevents data loss upon space exhaustion and allows download of (meta)data given a publication library. To highlight its manifold capabilities, we present executable demonstrations using publicly available amplicon, whole genome and metagenome datasets.

AVAILABILITY AND IMPLEMENTATION

q2-fondue is available as an open-source BSD-3-licensed Python package at https://github.com/bokulich-lab/q2-fondue. Usage tutorials are available in the same repository. All Jupyter notebooks used in this article are available under https://github.com/bokulich-lab/q2-fondue-examples.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Which field of research would Gregor Mendel choose in the 21st century?

Gregor Mendel's work on segregation of traits in plants established the basic methodology and rules of genetics. The interruption of Mendel's research activities in 1870 impeded the immediate recognition of the value of his work until the dawn of the 20th century. Only then were his founding laws of genetics validated, propelling the development of biological research toward the birth of molecular biology in the second half of the 20th century. While molecular plant genetics can be viewed as the spiritual heir of Mendel's research, one might wonder whether in the 21st century Gregor Mendel would prefer to practice scientific approaches other than molecular genetics such as population genetics, comparative genomics, or the emerging field of evo-chromo. In this perspective, I review aspects of these fields that might have attracted or perplexed a 21st century Mendel.

Inferring mammalian tissue-specific regulatory conservation by predicting tissue-specific differences in open chromatin

BACKGROUND

Evolutionary conservation is an invaluable tool for inferring functional significance in the genome, including regions that are crucial across many species and those that have undergone convergent evolution. Computational methods to test for sequence conservation are dominated by algorithms that examine the ability of one or more nucleotides to align across large evolutionary distances. While these nucleotide alignment-based approaches have proven powerful for protein-coding genes and some non-coding elements, they fail to capture conservation of many enhancers, distal regulatory elements that control spatial and temporal patterns of gene expression. The function of enhancers is governed by a complex, often tissue- and cell type-specific code that links combinations of transcription factor binding sites and other regulation-related sequence patterns to regulatory activity. Thus, function of orthologous enhancer regions can be conserved across large evolutionary distances, even when nucleotide turnover is high.

RESULTS

We present a new machine learning-based approach for evaluating enhancer conservation that leverages the combinatorial sequence code of enhancer activity rather than relying on the alignment of individual nucleotides. We first train a convolutional neural network model that can predict tissue-specific open chromatin, a proxy for enhancer activity, across mammals. Next, we apply that model to distinguish instances where the genome sequence would predict conserved function versus a loss of regulatory activity in that tissue. We present criteria for systematically evaluating model performance for this task and use them to demonstrate that our models accurately predict tissue-specific conservation and divergence in open chromatin between primate and rodent species, vastly out-performing leading nucleotide alignment-based approaches. We then apply our models to predict open chromatin at orthologs of brain and liver open chromatin regions across hundreds of mammals and find that brain enhancers associated with neuron activity have a stronger tendency than the general population to have predicted lineage-specific open chromatin.

CONCLUSION

The framework presented here provides a mechanism to annotate tissue-specific regulatory function across hundreds of genomes and to study enhancer evolution using predicted regulatory differences rather than nucleotide-level conservation measurements.

A high-quality assembly reveals genomic characteristics, phylogenetic status, and causal genes for leucism plumage of Indian peafowl

Background

The dazzling phenotypic characteristics of male Indian peafowl (Pavo cristatus) are attractive both to the female of the species and to humans. However, little is known about the evolution of the phenotype and phylogeny of these birds at the whole-genome level. So far, there are no reports regarding the genetic mechanism of the formation of leucism plumage in this variant of Indian peafowl.

Results

A draft genome of Indian peafowl was assembled, with a genome size of 1.05 Gb (the sequencing depth is 362×), and contig and scaffold N50 were up to 6.2 and 11.4 Mb, respectively. Compared with other birds, Indian peafowl showed changes in terms of metabolism, immunity, and skeletal and feather development, which provided a novel insight into the phenotypic evolution of peafowl, such as the large body size and feather morphologies. Moreover, we determined that the phylogeny of Indian peafowl was more closely linked to turkey than chicken. Specifically, we first identified that PMEL was a potential causal gene leading to the formation of the leucism plumage variant in Indian peafowl.

Conclusions

This study provides an Indian peafowl genome of high quality, as well as a novel understanding of phenotypic evolution and phylogeny of Indian peafowl. These results provide a valuable reference for the study of avian genome evolution. Furthermore, the discovery of the genetic mechanism for the development of leucism plumage is both a breakthrough in the exploration of peafowl plumage and also offers clues and directions for further investigations of the avian plumage coloration and artificial breeding in peafowl.

Comparative Transcriptome Analysis Provides Insight into Spatio-Temporal Expression Characteristics and Genetic Regulatory Network in Postnatal Developing Subcutaneous and Visceral Fat of Bama Pig

The depot differences between Subcutaneous Fat (SAF) and Visceral Fat (VAF) are critical for human well-being and disease processes in regard to energy metabolism and endocrine function. Miniature pigs (Sus scrofa) are ideal biomedical models for human energy metabolism and obesity due to the similarity of their lipid metabolism with that of humans. However, the regulation of differences in fat deposition and development remains unclear. In this study, the development of SAF and VAF was characterized and compared in Bama pig during postnatal development (infancy, puberty and adulthood), using RNA sequencing techniques (RNA-Seq). The transcriptome of SAF and VAF was profiled and isolated from 1-, 3- and 6 months-old pigs and identified 23,636 expressed genes, of which 1,165 genes were differentially expressed between the depots and/or developmental stages. Upregulated genes in SAF showed significant function and pathway enrichment in the central nervous system development, lipid metabolism, oxidation-reduction process and cell adhesion, whereas genes involved in the immune system, actin cytoskeleton organization, male gonad development and the hippo signaling pathway were preferentially expressed in VAF. Miner analysis of short time-series expression demonstrated that differentiation in gene expression patterns between the two depots corresponded to their distinct responses in sexual development, hormone signaling pathways, lipid metabolism and the hippo signaling pathway. Transcriptome analysis of SAF and VAF suggested that the depot differences in adipose tissue are not only related to lipid metabolism and endocrine function, but are closely associated with sexual development and organ size regulation.

COVID-19 challenges: From SARS-CoV-2 infection to effective point-of-care diagnosis by electrochemical biosensing platforms

In January 2020, the World Health Organization (WHO) identified a new zoonotic virus, SARS-CoV-2, responsible for causing the COVID-19 (coronavirus disease 2019). Since then, there has been a collaborative trend between the scientific community and industry. Multidisciplinary research networks try to understand the whole SARS-CoV-2 pathophysiology and its relationship with the different grades of severity presented by COVID-19. The scientific community has gathered all the data in the quickly developed vaccines that offer a protective effect for all variants of the virus and promote new diagnostic alternatives able to have a high standard of efficiency, added to shorter response analysis time and portability. The industry enters in the context of accelerating the path taken by science until obtaining the final product. In this review, we show the principal diagnostic methods developed during the COVID-19 pandemic. However, when we observe the diagnostic tools section of an efficient infection outbreak containment report and the features required for such tools, we could observe a highlight of electrochemical biosensing platforms. Such devices present a high standard of analytical performance, are low-cost tools, easy to handle and interpret, and can be used in the most remote and low-resource regions. Therefore, probably, they are the ideal point-of-care diagnostic tools for pandemic scenarios.

Flor Yeasts Rewire the Central Carbon Metabolism During Wine Alcoholic Fermentation

The identification of natural allelic variations controlling quantitative traits could contribute to decipher metabolic adaptation mechanisms within different populations of the same species. Such variations could result from human-mediated selection pressures and participate to the domestication. In this study, the genetic causes of the phenotypic variability of the central carbon metabolism of Saccharomyces cerevisiae were investigated in the context of the enological fermentation. The genetic determinism of this trait was found out by a quantitative trait loci (QTL) mapping approach using the offspring of two strains belonging to the wine genetic group of the species. A total of 14 QTL were identified from which 8 were validated down to the gene level by genetic engineering. The allelic frequencies of the validated genes within 403 enological strains showed that most of the validated QTL had allelic variations involving flor yeast specific alleles. Those alleles were brought in the offspring by one parental strain that contains introgressions from the flor yeast genetic group. The causative genes identified are functionally linked to quantitative proteomic variations that would explain divergent metabolic features of wine and flor yeasts involving the tricarboxylic acid cycle (TCA), the glyoxylate shunt and the homeostasis of proton and redox cofactors. Overall, this work led to the identification of genetic factors that are hallmarks of adaptive divergence between flor yeast and wine yeast in the wine biotope. These results also reveal that introgressions originated from intraspecific hybridization events promoted phenotypic variability of carbon metabolism observed in wine strains.

LipiDisease: associate lipids to diseases using literature mining

Summary

Lipids exhibit an essential role in cellular assembly and signaling. Dysregulation of these functions has been linked with many complications including obesity, diabetes, metabolic disorders, cancer and more. Investigating lipid profiles in such conditions can provide insights into cellular functions and possible interventions. Hence the field of lipidomics is expanding in recent years. Even though the role of individual lipids in diseases has been investigated, there is no resource to perform disease enrichment analysis considering the cumulative association of a lipid set. To address this, we have implemented the LipiDisease web server. The tool analyzes millions of records from the PubMed biomedical literature database discussing lipids and diseases, predicts their association and ranks them according to false discovery rates generated by random simulations. The tool takes into account 4270 diseases and 4798 lipids. Since the tool extracts the information from PubMed records, the number of diseases and lipids will be expanded over time as the biomedical literature grows.

Availability and implementation

The LipiDisease webserver can be freely accessed at http://cbdm-01.zdv.uni-mainz.de:3838/piyusmor/LipiDisease/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Unraveling Genome Evolution Throughout Visual Analysis: The XCout Portal

Due to major breakthroughs in sequencing technologies throughout the last decades, the time and cost per sequencing experiment have reduced drastically, overcoming the data generation barrier during the early genomic era. Such a shift has encouraged the scientific community to develop new computational methods that are able to compare large genomic sequences, thus enabling large-scale studies of genome evolution. The field of comparative genomics has proven itself invaluable for studying the evolutionary mechanisms and the forces driving genome evolution. In this line, a full genome comparison study between 2 species requires a quadratic number of comparisons in terms of the number of sequences (around 400 chromosome comparisons in the case of mammalian genomes); however, when studying conserved syntenies or evolutionary rearrangements, many sequence comparisons can be skipped for not all will contain significant signals. Subsequently, the scientific community has developed fast heuristics to perform multiple pairwise comparisons between large sequences to determine whether significant sets of conserved similarities exist. The data generation problem is no longer an issue, yet the limitations have shifted toward the analysis of such massive data. Therefore, we present XCout, a Web-based visual analytics application for multiple genome comparisons designed to improve the analysis of large-scale evolutionary studies using novel techniques in Web visualization. XCout enables to work on hundreds of comparisons at once, thus reducing the time of the analysis by identifying significant signals between chromosomes across multiple species. Among others, XCout introduces several techniques to aid in the analysis of large-scale genome rearrangements, particularly (1) an interactive heatmap interface to display comparisons using automatic color scales based on similarity thresholds to ease detection at first sight, (2) an overlay system to detect individual signal contributions between chromosomes, (3) a tracking tool to trace conserved blocks across different species to perform evolutionary studies, and (4) a search engine to search annotations throughout different species.

Comparative genomics of Chlamydomonas

Despite its role as a reference organism in the plant sciences, the green alga Chlamydomonas reinhardtii entirely lacks genomic resources from closely related species. We present highly contiguous and well-annotated genome assemblies for three unicellular C. reinhardtii relatives: Chlamydomonas incerta, Chlamydomonas schloesseri, and the more distantly related Edaphochlamys debaryana. The three Chlamydomonas genomes are highly syntenous with similar gene contents, although the 129.2 Mb C. incerta and 130.2 Mb C. schloesseri assemblies are more repeat-rich than the 111.1 Mb C. reinhardtii genome. We identify the major centromeric repeat in C. reinhardtii as a LINE transposable element homologous to Zepp (the centromeric repeat in Coccomyxa subellipsoidea) and infer that centromere locations and structure are likely conserved in C. incerta and C. schloesseri. We report extensive rearrangements, but limited gene turnover, between the minus mating type loci of these Chlamydomonas species. We produce an eight-species core-Reinhardtinia whole-genome alignment, which we use to identify several hundred false positive and missing genes in the C. reinhardtii annotation and >260,000 evolutionarily conserved elements in the C. reinhardtii genome. In summary, these resources will enable comparative genomics analyses for C. reinhardtii, significantly extending the analytical toolkit for this emerging model system.

Comparative genome analysis of Corynebacterium species: The underestimated pathogens with high virulence potential

Non-diphtherial Corynebacterium species or diphtheroids were previously considered as the mere contaminants of clinical samples. Of late, they have been reckoned as the formidable infection causing agents of various diseases. While the scientific database is filled with articles that document whole genome analysis of individual isolates, a comprehensive comparative genomic analysis of diphtheroids alongside Corynebacterium diphtheriae is expected to enable us in understanding their genomic as well as evolutionary divergence. Here, we have analysed the whole genome sequences of forty strains that were selected from a range of eleven Corynebacterium species (pathogenic and non-pathogenic). A statistical analysis of the pan and core genomes revealed that even though the core genome is saturated, the pan genome is yet open rendering scope for newer gene families to be accumulated in the course of evolution that might further change the pathogenic behavior of these species. Every strain had bacteriophage components integrated in its genome and some of them were intact and consisted of toxins. The presence of diversified genomic islands was observed across the dataset and most of them consisted of genes for virulence and multidrug resistance. Moreover, the phylogenetic analysis showed that a diphtheroid is the last common ancestor of all the Corynebacterium species. The current study is a compilation of genomic features of pathogenic as well as non-pathogenic Corynebacterium species which provides insights into their virulence potential in the times to come.

Accelerated Evolution of Tissue-Specific Genes Mediates Divergence Amidst Gene Flow in European Green Lizards

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 Pectobacterium pangenome, with a focus on Pectobacterium brasiliense, shows a robust core and extensive exchange of genes from a shared gene pool

BACKGROUND

Bacterial plant pathogens of the Pectobacterium genus are responsible for a wide spectrum of diseases in plants, including important crops such as potato, tomato, lettuce, and banana. Investigation of the genetic diversity underlying virulence and host specificity can be performed at genome level by using a comprehensive comparative approach called pangenomics. A pangenomic approach, using newly developed functionalities in PanTools, was applied to analyze the complex phylogeny of the Pectobacterium genus. We specifically used the pangenome to investigate genetic differences between virulent and avirulent strains of P. brasiliense, a potato blackleg causing species dominantly present in Western Europe.

RESULTS

Here we generated a multilevel pangenome for Pectobacterium, comprising 197 strains across 19 species, including type strains, with a focus on P. brasiliense. The extensive phylogenetic analysis of the Pectobacterium genus showed robust distinct clades, with most detail provided by 452,388 parsimony-informative single-nucleotide polymorphisms identified in single-copy orthologs. The average Pectobacterium genome consists of 47% core genes, 1% unique genes, and 52% accessory genes. Using the pangenome, we zoomed in on differences between virulent and avirulent P. brasiliense strains and identified 86 genes associated to virulent strains. We found that the organization of genes is highly structured and linked with gene conservation, function, and transcriptional orientation.

CONCLUSION

The pangenome analysis demonstrates that evolution in Pectobacteria is a highly dynamic process, including gene acquisitions partly in clusters, genome rearrangements, and loss of genes. Pectobacterium species are typically not characterized by a set of species-specific genes, but instead present themselves using new gene combinations from the shared gene pool. A multilevel pangenomic approach, fusing DNA, protein, biological function, taxonomic group, and phenotypes, facilitates studies in a flexible taxonomic context.

Novel metric for hyperbolic phylogenetic tree embeddings

Advances in experimental technologies, such as DNA sequencing, have opened up new avenues for the applications of phylogenetic methods to various fields beyond their traditional application in evolutionary investigations, extending to the fields of development, differentiation, cancer genomics, and immunogenomics. Thus, the importance of phylogenetic methods is increasingly being recognized, and the development of a novel phylogenetic approach can contribute to several areas of research. Recently, the use of hyperbolic geometry has attracted attention in artificial intelligence research. Hyperbolic space can better represent a hierarchical structure compared to Euclidean space, and can therefore be useful for describing and analyzing a phylogenetic tree. In this study, we developed a novel metric that considers the characteristics of a phylogenetic tree for representation in hyperbolic space. We compared the performance of the proposed hyperbolic embeddings, general hyperbolic embeddings, and Euclidean embeddings, and confirmed that our method could be used to more precisely reconstruct evolutionary distance. We also demonstrate that our approach is useful for predicting the nearest-neighbor node in a partial phylogenetic tree with missing nodes. Furthermore, we proposed a novel approach based on our metric to integrate multiple trees for analyzing tree nodes or imputing missing distances. This study highlights the utility of adopting a geometric approach for further advancing the applications of phylogenetic methods.

Transposable Elements and Stress in Vertebrates: An Overview

Since their identification as genomic regulatory elements, Transposable Elements (TEs) were considered, at first, molecular parasites and later as an important source of genetic diversity and regulatory innovations. In vertebrates in particular, TEs have been recognized as playing an important role in major evolutionary transitions and biodiversity. Moreover, in the last decade, a significant number of papers has been published highlighting a correlation between TE activity and exposition to environmental stresses and dietary factors. In this review we present an overview of the impact of TEs in vertebrate genomes, report the silencing mechanisms adopted by host genomes to regulate TE activity, and finally we explore the effects of environmental and dietary factor exposures on TE activity in mammals, which is the most studied group among vertebrates. The studies here reported evidence that several factors can induce changes in the epigenetic status of TEs and silencing mechanisms leading to their activation with consequent effects on the host genome. The study of TE can represent a future challenge for research for developing effective markers able to detect precocious epigenetic changes and prevent human diseases.

A non-invasive method to generate induced pluripotent stem cells from primate urine

Comparing the molecular and cellular properties among primates is crucial to better understand human evolution and biology. However, it is difficult or ethically impossible to collect matched tissues from many primates, especially during development. An alternative is to model different cell types and their development using induced pluripotent stem cells (iPSCs). These can be generated from many tissue sources, but non-invasive sampling would decisively broaden the spectrum of non-human primates that can be investigated. Here, we report the generation of primate iPSCs from urine samples. We first validate and optimize the procedure using human urine samples and show that suspension- Sendai Virus transduction of reprogramming factors into urinary cells efficiently generates integration-free iPSCs, which maintain their pluripotency under feeder-free culture conditions. We demonstrate that this method is also applicable to gorilla and orangutan urinary cells isolated from a non-sterile zoo floor. We characterize the urinary cells, iPSCs and derived neural progenitor cells using karyotyping, immunohistochemistry, differentiation assays and RNA-sequencing. We show that the urine-derived human iPSCs are indistinguishable from well characterized PBMC-derived human iPSCs and that the gorilla and orangutan iPSCs are well comparable to the human iPSCs. In summary, this study introduces a novel and efficient approach to non-invasively generate iPSCs from primate urine. This will extend the zoo of species available for a comparative approach to molecular and cellular phenotypes.

The influence of evolutionary history on human health and disease

Nearly all genetic variants that influence disease risk have human-specific origins; however, the systems they influence have ancient roots that often trace back to evolutionary events long before the origin of humans. Here, we review how advances in our understanding of the genetic architectures of diseases, recent human evolution and deep evolutionary history can help explain how and why humans in modern environments become ill. Human populations exhibit differences in the prevalence of many common and rare genetic diseases. These differences are largely the result of the diverse environmental, cultural, demographic and genetic histories of modern human populations. Synthesizing our growing knowledge of evolutionary history with genetic medicine, while accounting for environmental and social factors, will help to achieve the promise of personalized genomics and realize the potential hidden in an individual's DNA sequence to guide clinical decisions. In short, precision medicine is fundamentally evolutionary medicine, and integration of evolutionary perspectives into the clinic will support the realization of its full potential.

Dark Matter of Primate Genomes: Satellite DNA Repeats and Their Evolutionary Dynamics

A substantial portion of the primate genome is composed of non-coding regions, so-called "dark matter", which includes an abundance of tandemly repeated sequences called satellite DNA. Collectively known as the satellitome, this genomic component offers exciting evolutionary insights into aspects of primate genome biology that raise new questions and challenge existing paradigms. A complete human reference genome was recently reported with telomere-to-telomere human X chromosome assembly that resolved hundreds of dark regions, encompassing a 3.1 Mb centromeric satellite array that had not been identified previously. With the recent exponential increase in the availability of primate genomes, and the development of modern genomic and bioinformatics tools, extensive growth in our knowledge concerning the structure, function, and evolution of satellite elements is expected. The current state of knowledge on this topic is summarized, highlighting various types of primate-specific satellite repeats to compare their proportions across diverse lineages. Inter- and intraspecific variation of satellite repeats in the primate genome are reviewed. The functional significance of these sequences is discussed by describing how the transcriptional activity of satellite repeats can affect gene expression during different cellular processes. Sex-linked satellites are outlined, together with their respective genomic organization. Mechanisms are proposed whereby satellite repeats might have emerged as novel sequences during different evolutionary phases. Finally, the main challenges that hinder the detection of satellite DNA are outlined and an overview of the latest methodologies to address technological limitations is presented.

Prioritizing sequence variants in conserved non-coding elements in the chicken genome using chCADD

The availability of genomes for many species has advanced our understanding of the non-protein-coding fraction of the genome. Comparative genomics has proven itself to be an invaluable approach for the systematic, genome-wide identification of conserved non-protein-coding elements (CNEs). However, for many non-mammalian model species, including chicken, our capability to interpret the functional importance of variants overlapping CNEs has been limited by current genomic annotations, which rely on a single information type (e.g. conservation). We here studied CNEs in chicken using a combination of population genomics and comparative genomics. To investigate the functional importance of variants found in CNEs we develop a ch(icken) Combined Annotation-Dependent Depletion (chCADD) model, a variant effect prediction tool first introduced for humans and later on for mouse and pig. We show that 73 Mb of the chicken genome has been conserved across more than 280 million years of vertebrate evolution. The vast majority of the conserved elements are in non-protein-coding regions, which display SNP densities and allele frequency distributions characteristic of genomic regions constrained by purifying selection. By annotating SNPs with the chCADD score we are able to pinpoint specific subregions of the CNEs to be of higher functional importance, as supported by SNPs found in these subregions are associated with known disease genes in humans, mice, and rats. Taken together, our findings indicate that CNEs harbor variants of functional significance that should be object of further investigation along with protein-coding mutations. We therefore anticipate chCADD to be of great use to the scientific community and breeding companies in future functional studies in chicken.

Advances in optical mapping for genomic research

Recent advances in optical mapping have allowed the construction of improved genome assemblies with greater contiguity. Optical mapping also enables genome comparison and identification of large-scale structural variations. Association of these large-scale genomic features with biological functions is an important goal in plant and animal breeding and in medical research. Optical mapping has also been used in microbiology and still plays an important role in strain typing and epidemiological studies. Here, we review the development of optical mapping in recent decades to illustrate its importance in genomic research. We detail its applications and algorithms to show its specific advantages. Finally, we discuss the challenges required to facilitate the optimization of optical mapping and improve its future development and application.

Synteny-Guided Resolution of Gene Trees Clarifies the Functional Impact of Whole-Genome Duplications

Whole-genome duplications (WGDs) have major impacts on the evolution of species, as they produce new gene copies contributing substantially to adaptation, isolation, phenotypic robustness, and evolvability. They result in large, complex gene families with recurrent gene losses in descendant species that sequence-based phylogenetic methods fail to reconstruct accurately. As a result, orthologs and paralogs are difficult to identify reliably in WGD-descended species, which hinders the exploration of functional consequences of WGDs. Here, we present Synteny-guided CORrection of Paralogies and Orthologies (SCORPiOs), a novel method to reconstruct gene phylogenies in the context of a known WGD event. WGDs generate large duplicated syntenic regions, which SCORPiOs systematically leverages as a complement to sequence evolution to infer the evolutionary history of genes. We applied SCORPiOs to the 320-My-old WGD at the origin of teleost fish. We find that almost one in four teleost gene phylogenies in the Ensembl database (3,394) are inconsistent with their syntenic contexts. For 70% of these gene families (2,387), we were able to propose an improved phylogenetic tree consistent with both the molecular substitution distances and the local syntenic information. We show that these synteny-guided phylogenies are more congruent with the species tree, with sequence evolution and with expected expression conservation patterns than those produced by state-of-the-art methods. Finally, we show that synteny-guided gene trees emphasize contributions of WGD paralogs to evolutionary innovations in the teleost clade.

Population genetic models of GERP scores suggest pervasive turnover of constrained sites across mammalian evolution

Comparative genomic approaches have been used to identify sites where mutations are under purifying selection and of functional consequence by searching for sequences that are conserved across distantly related species. However, the performance of these approaches has not been rigorously evaluated under population genetic models. Further, short-lived functional elements may not leave a footprint of sequence conservation across many species. We use simulations to study how one measure of conservation, the Genomic Evolutionary Rate Profiling (GERP) score, relates to the strength of selection (N_es). We show that the GERP score is related to the strength of purifying selection. However, changes in selection coefficients or functional elements over time (i.e. functional turnover) can strongly affect the GERP distribution, leading to unexpected relationships between GERP and N_es. Further, we show that for functional elements that have a high turnover rate, adding more species to the analysis does not necessarily increase statistical power. Finally, we use the distribution of GERP scores across the human genome to compare models with and without turnover of sites where mutations are under purifying selection. We show that mutations in 4.51% of the noncoding human genome are under purifying selection and that most of this sequence has likely experienced changes in selection coefficients throughout mammalian evolution. Our work reveals limitations to using comparative genomic approaches to identify deleterious mutations. Commonly used GERP score thresholds miss over half of the noncoding sites in the human genome where mutations are under purifying selection.

One of the most significant and challenging tasks in modern genomics is to assess the functional consequences of a particular nucleotide change in a genome. A common approach to address this challenge prioritizes sequences that share similar nucleotides across distantly related species, with the rationale that mutations at such positions were deleterious and removed from the population by purifying natural selection. Our manuscript shows that one popular measure of sequence conservation, the GERP score, performs well at identifying selected mutations if mutations at a site were under selection across all of mammalian evolution. Changes in selection at a given site dramatically reduces the power of GERP to detect selected mutations in humans. We also combine population genetic models with the distribution of GERP scores at noncoding sites across the human genome to show that the degree of selection at individual sites has changed throughout mammalian evolution. Importantly, we demonstrate that at least 80 Mb of noncoding sequence under purifying selection in humans will not have extreme GERP scores and will likely be missed by modern comparative genomic approaches. Our work argues that new approaches, potentially based on genetic variation within species, will be required to identify deleterious mutations.

Novel phylogenetic methods are needed for understanding gene function in the era of mega-scale genome sequencing

Ongoing large-scale genome sequencing projects are forecasting a data deluge that will almost certainly overwhelm current analytical capabilities of evolutionary genomics. In contrast to population genomics, there are no standardized methods in evolutionary genomics for extracting evolutionary and functional (e.g. gene-trait association) signal from genomic data. Here, we examine how current practices of multi-species comparative genomics perform in this aspect and point out that many genomic datasets are under-utilized due to the lack of powerful methodologies. As a result, many current analyses emphasize gene families for which some functional data is already available, resulting in a growing gap between functionally well-characterized genes/organisms and the universe of unknowns. This leaves unknown genes on the 'dark side' of genomes, a problem that will not be mitigated by sequencing more and more genomes, unless we develop tools to infer functional hypotheses for unknown genes in a systematic manner. We provide an inventory of recently developed methods capable of predicting gene-gene and gene-trait associations based on comparative data, then argue that realizing the full potential of whole genome datasets requires the integration of phylogenetic comparative methods into genomics, a rich but underutilized toolbox for looking into the past.

Gene regulatory landscape of the sonic hedgehog locus in embryonic development

The organs of vertebrate species display a wide variety of morphology. A remaining challenge in evolutionary developmental biology is to elucidate how vertebrate lineages acquire distinct morphological features. Developmental programs are driven by spatiotemporal regulation of gene expression controlled by hundreds of thousands of cis-regulatory elements. Changes in the regulatory elements caused by the introduction of genetic variants can confer regulatory innovation that may underlie morphological novelties. Recent advances in sequencing technology have revealed a number of potential regulatory variants that can alter gene expression patterns. However, a limited number of studies demonstrate causal dependence between genetic and morphological changes. Regulation of Shh expression is a good model to understand how multiple regulatory elements organize tissue-specific gene expression patterns. This model also provides insights into how evolution of molecular traits, such as gene regulatory networks, lead to phenotypic novelty.

Autism-associated missense genetic variants impact locomotion and neurodevelopment in Caenorhabditis elegans

Autism spectrum disorder (ASD) involves thousands of alleles in over 850 genes, but the current functional inference tools are not sufficient to predict phenotypic changes. As a result, the causal relationship of most of these genetic variants in the pathogenesis of ASD has not yet been demonstrated and an experimental method prioritizing missense alleles for further intensive analysis is crucial. For this purpose, we have designed a pipeline that uses Caenorhabditis elegans as a genetic model to screen for phenotype-changing missense alleles inferred from human ASD studies. We identified highly conserved human ASD-associated missense variants in their C. elegans orthologs, used a CRISPR/Cas9-mediated homology-directed knock-in strategy to generate missense mutants and analyzed their impact on behaviors and development via several broad-spectrum assays. All tested missense alleles were predicted to perturb protein function, but we found only 70% of them showed detectable phenotypic changes in morphology, locomotion or fecundity. Our findings indicate that certain missense variants in the C. elegans orthologs of human CACNA1D, CHD7, CHD8, CUL3, DLG4, GLRA2, NAA15, PTEN, SYNGAP1 and TPH2 impact neurodevelopment and movement functions, elevating these genes as candidates for future study into ASD. Our approach will help prioritize functionally important missense variants for detailed studies in vertebrate models and human cells.

Origin and evolution of the Rax homeobox gene by comprehensive evolutionary analysis

Rax is one of the key transcription factors crucial for vertebrate eye development. In this study, we conducted comprehensive evolutionary analysis of Rax. We found that Bilateria and Cnidaria possess Rax, but Placozoa, Porifera, and Ctenophora do not, implying that the origin of the Rax gene dates back to the common ancestor of Cnidaria and Bilateria. The results of molecular phylogenetic and synteny analyses on Rax loci between jawed and jawless vertebrates indicate that segmental duplication of the Rax locus occurred in an early common ancestor of jawed vertebrates, resulting in two Rax paralogs in jawed vertebrates, Rax and Rax2. By analyzing 86 mammalian genomes from all four major groups of mammals, we found that at least five independent Rax2 gene loss events occurred in mammals. This study may provide novel insights into the evolution of the eye.

A genome alignment of 120 mammals highlights ultraconserved element variability and placenta-associated enhancers

BACKGROUND

Multiple alignments of mammalian genomes have been the basis of many comparative genomic studies aiming at annotating genes, detecting regions under evolutionary constraint, and studying genome evolution. A key factor that affects the power of comparative analyses is the number of species included in a genome alignment.

RESULTS

To utilize the increased number of sequenced genomes and to provide an accessible resource for genomic studies, we generated a mammalian genome alignment comprising 120 species. We used this alignment and the CESAR method to provide protein-coding gene annotations for 119 non-human mammals. Furthermore, we illustrate the utility of this alignment by 2 exemplary analyses. First, we quantified how variable ultraconserved elements (UCEs) are among placental mammals. Leveraging the high taxonomic coverage in our alignment, we estimate that UCEs contain on average 4.7%-15.6% variable alignment columns. Furthermore, we show that the center regions of UCEs are generally most constrained. Second, we identified enhancer sequences that are only conserved in placental mammals. We found that these enhancers are significantly associated with placenta-related genes, suggesting that some of these enhancers may be involved in the evolution of placental mammal-specific aspects of the placenta.

CONCLUSION

The 120-mammal alignment and all other data are available for analysis and visualization in a genome browser at https://genome-public.pks.mpg.de/and for download at https://bds.mpi-cbg.de/hillerlab/120MammalAlignment/.

Finding relationships among biological entities

Confusion over the concepts of “relationships” and “similarities” lies at the heart of many battles over the direction and intent of research projects. Here is a short story that demonstrates the difference between the two concepts: You look up at the clouds, and you begin to see the shape of a lion. The cloud has a tail, like a lion’s tale, and a fluffy head, like a lion’s mane. With a little imagination the mouth of the lion seems to roar down from the sky. You have succeeded in finding similarities between the cloud and a lion. If you look at a cloud and you imagine a tea kettle producing a head of steam and you recognize that the physical forces that create a cloud and the physical forces that produced steam from a heated kettle are the same, then you have found a relationship. Most popular classification algorithms operate by grouping together data objects that have similar properties or values. In so doing, they may miss finding the true relationships among objects. Traditionally, relationships among data objects are discovered by an intellectual process. In this chapter, we will discuss the scientific gains that come when we classify biological entities by relationships, not by their similarities.

Human protein-RNA interaction network is highly stable across mammals

BACKGROUND

RNA-binding proteins (RBPs) are crucial in modulating RNA metabolism in eukaryotes thereby controlling an extensive network of RBP-RNA interactions. Although previous studies on the conservation of RBP targets have been carried out in lower eukaryotes such as yeast, relatively little is known about the extent of conservation of the binding sites of RBPs across mammalian species.

RESULTS

In this study, we employ CLIP-seq datasets for 60 human RBPs and demonstrate that most binding sites for a third of these RBPs are conserved in at least 50% of the studied vertebrate species. Across the studied RBPs, binding sites were found to exhibit a median conservation of 58%, ~ 20% higher than random genomic locations, suggesting a significantly higher preservation of RBP-RNA interaction networks across vertebrates. RBP binding sites were highly conserved across primates with weak conservation profiles in birds and fishes. We also note that phylogenetic relationship between members of an RBP family does not explain the extent of conservation of their binding sites across species. Multivariate analysis to uncover features contributing to differences in the extents of conservation of binding sites across RBPs revealed RBP expression level and number of post-transcriptional targets to be the most prominent factors. Examination of the location of binding sites at the gene level confirmed that binding sites occurring on the 3' region of a gene are highly conserved across species with 90% of the RBPs exhibiting a significantly higher conservation of binding sites in 3' regions of a gene than those occurring in the 5'. Gene set enrichment analysis on the extent of conservation of binding sites to identify significantly associated human phenotypes revealed an enrichment for multiple developmental abnormalities.

CONCLUSIONS

Our results suggest that binding sites of human RBPs are highly conserved across primates with weak conservation profiles in lower vertebrates and evolutionary relationship between members of an RBP family does not explain the extent of conservation of their binding sites. Expression level and number of targets of an RBP are important factors contributing to the differences in the extent of conservation of binding sites. RBP binding sites on 3' ends of a gene are the most conserved across species. Phenotypic analysis on the extent of conservation of binding sites revealed the importance of lineage-specific developmental events in post-transcriptional regulatory network evolution.

The honey bee gut microbiota: strategies for study and characterization

Gut microbiota research is an emerging field that improves our understanding of the ecological and functional dynamics of gut environments. The honey bee gut microbiota is a highly rewarding community to study, as honey bees are critical pollinators of many crops for human consumption and produce valuable commodities such as honey and wax. Most significantly, unique characteristics of the Apis mellifera gut habitat make it a valuable model system. This review discusses methods and pipelines used in the study of the gut microbiota of Ap. mellifera and closely related species for four main purposes: identifying microbiota taxonomy, characterizing microbiota genomes (microbiome), characterizing microbiota-microbiota interactions and identifying functions of the microbial community in the gut. The purpose of this contribution is to increase understanding of honey bee gut microbiota, to facilitate bee microbiota and microbiome research in general and to aid design of future experiments in this growing field.

Long-read sequencing reveals intra-species tolerance of substantial structural variations and new subtelomere formation in C. elegans

Long-read sequencing technologies have contributed greatly to comparative genomics among species and can also be applied to study genomics within a species. In this study, to determine how substantial genomic changes are generated and tolerated within a species, we sequenced a C. elegans strain, CB4856, which is one of the most genetically divergent strains compared to the N2 reference strain. For this comparison, we used the Pacific Biosciences (PacBio) RSII platform (80×, N50 read length 11.8 kb) and generated de novo genome assembly to the level of pseudochromosomes containing 76 contigs (N50 contig = 2.8 Mb). We identified structural variations that affected as many as 2694 genes, most of which are at chromosome arms. Subtelomeric regions contained the most extensive genomic rearrangements, which even created new subtelomeres in some cases. The subtelomere structure of Chromosome VR implies that ancestral telomere damage was repaired by alternative lengthening of telomeres even in the presence of a functional telomerase gene and that a new subtelomere was formed by break-induced replication. Our study demonstrates that substantial genomic changes including structural variations and new subtelomeres can be tolerated within a species, and that these changes may accumulate genetic diversity within a species.

Improved measures for evolutionary conservation that exploit taxonomy distances

Selective pressures on protein-coding regions that provide fitness advantages can lead to the regions' fixation and conservation in genome duplications and speciation events. Consequently, conservation analyses relying on sequence similarities are exploited by a myriad of applications across all biosciences to identify functionally important protein regions. While very potent, existing conservation measures based on multiple sequence alignments are so pervasive that improvements to solutions of many problems have become incremental. We introduce a new framework for evolutionary conservation with measures that exploit taxonomy distances across species. Results show that our taxonomy-based framework comfortably outperforms existing conservation measures in identifying deleterious variants observed in the human population, including variants located in non-abundant sequence domains such as intrinsically disordered regions. The predictive power of our approach emphasizes that the phenotypic effects of sequence variants can be taxonomy-level specific and thus, conservation needs to be interpreted accordingly.

Information on protein sequence variability and conservation can be leveraged to identify functionally important regions. Here, the authors develop new conservation measures that exploit taxonomy distances and LIST, a tool for predicting deleteriousness of human variants.

Comparative genomic analysis of collagen gene diversity

Collagen gene family, comprising 30% of the total protein mass in mammals, is the major part of extracellular matrix. To understand the complexity of collagen gene family, detailed sequence, phylogenetic and synteny analyses of 44 collagen genes were performed. According to sequence analysis results, Fibril-associated collagen with interrupted triple helices (FACITs) were identified as the most recently evolved vertebrate-specific collagens while Fibril-forming collagens and Collagen VI, VII, XXVI, and XXVIII were the most ancient collagens, originating at the time of choanoflagellates. Network-forming collagens were entirely conserved from arthopods to homo sapiens, except one gene loss event. Of note, bird specific gene dispensability of COL1A1, COL3A1, COL5A3 and COL11A2 genes was observed in Fibril-forming collagens. According to phylogenetic analysis, gene duplications in collagen family occurred at variable time points during invertebrate to vertebrate evolution. However, majority of gene duplications in FACITs and network-forming collagens occurred at fish time point, suggesting large scale duplications at the root of vertebrate lineage. Lastly, synteny analysis identified 12 conserved blocks containing 27 collagen genes in vertebrate species. Interestingly, dysregulation of seven conserved blocks including block1 (COL11A1), block3 (COL3A1, COL5A2), block5 (COL6A5, COL6A6), block7 (COL1A2), block9 (COL4A1, COL4A2), block11 (COL6A1, COL6A2, COL18A1) and block12 (COL4A5, COL4A6) were also reported in different diseases including cancer. The current study revealed many critical insights into sequence, structural and functional diversity of collagen gene family. In future, by using this information we may be able to establish the clinical and pathological relevance of these conserved collagen blocks in different diseases.

Genome organisation and comparative genomics of four novel Wolbachia genome assemblies from Indian Drosophila host

Wolbachia has long been known to share an endosymbiotic relationship with its host as an obligate intracellular organism. Wolbachia diversity as different supergroups is found to be host-specific in most cases except a few, where the host species is seen to accommodate multiple strains. Besides, the Wolbachia genome must have undergone several changes in response to the evolving host genome in order to adapt and establish a strong association with its host, thus making a distinctive Wolbachia-host alliance. The present study focusses on four novel genome assembly and genome-wide sequence variations of Indian Wolbachia strains, i.e. wMel and wRi isolated from two different Drosophila hosts. The genome assembly has an average size of ~ 1.1 Mb and contains ~ 1100 genes, which is comparable with the previously sequenced Wolbachia genomes. The comparative genomics analysis of these genomes and sequence-wide comparison of some functionally significant genes, i.e. ankyrin repeats, Wsp and T4SS, highlight their sequence similarities and dissimilarities, further supporting the strain-specific association of Wolbachia to its host. Interestingly, some of the sequence variations are also found to be restricted to only Indian Wolbachia strains. Further analysis of prophage and their flanking regions in the Wolbachia genome reveals the presence of several functional genes which may assist the phage to reside inside the bacterial host, thus providing a trade-off for the endosymbiont-host association. Understanding this endosymbiont genome in different eco-geographical conditions has become imperative for the recent use of Wolbachia in medical entomology as a vector-control agent.

A quantitative framework for characterizing the evolutionary history of mammalian gene expression

The evolutionary history of a gene helps predict its function and relationship to phenotypic traits. Although sequence conservation is commonly used to decipher gene function and assess medical relevance, methods for functional inference from comparative expression data are lacking. Here, we use RNA-seq across seven tissues from 17 mammalian species to show that expression evolution across mammals is accurately modeled by the Ornstein–Uhlenbeck process, a commonly proposed model of continuous trait evolution. We apply this model to identify expression pathways under neutral, stabilizing, and directional selection. We further demonstrate novel applications of this model to quantify the extent of stabilizing selection on a gene's expression, parameterize the distribution of each gene's optimal expression level, and detect deleterious expression levels in expression data from individual patients. Our work provides a statistical framework for interpreting expression data across species and in disease.

Perspectives and applications of machine learning for evolutionary developmental biology

Evolutionary Developmental Biology (Evo-Devo) is an ever-expanding field that aims to understand how development was modulated by the evolutionary process. In this sense, "omic" studies emerged as a powerful ally to unravel the molecular mechanisms underlying development. In this scenario, bioinformatics tools become necessary to analyze the growing amount of information. Among computational approaches, machine learning stands out as a promising field to generate knowledge and trace new research perspectives for bioinformatics. In this review, we aim to expose the current advances of machine learning applied to evolution and development. We draw clear perspectives and argue how evolution impacted machine learning techniques.