Why sequence all eukaryotes?

Life on Earth has evolved from initial simplicity to the astounding complexity we experience today. Bacteria and archaea have largely excelled in metabolic diversification, but eukaryotes additionally display abundant morphological innovation. How have these innovations come about and what constraints are there on the origins of novelty and the continuing maintenance of biodiversity on Earth? The history of life and the code for the working parts of cells and systems are written in the genome. The Earth BioGenome Project has proposed that the genomes of all extant, named eukaryotes-about 2 million species-should be sequenced to high quality to produce a digital library of life on Earth, beginning with strategic phylogenetic, ecological, and high-impact priorities. Here we discuss why we should sequence all eukaryotic species, not just a representative few scattered across the many branches of the tree of life. We suggest that many questions of evolutionary and ecological significance will only be addressable when whole-genome data representing divergences at all of the branchings in the tree of life or all species in natural ecosystems are available. We envisage that a genomic tree of life will foster understanding of the ongoing processes of speciation, adaptation, and organismal dependencies within entire ecosystems. These explorations will resolve long-standing problems in phylogenetics, evolution, ecology, conservation, agriculture, bioindustry, and medicine.

Standards recommendations for the Earth BioGenome Project.

A global international initiative, such as the Earth BioGenome Project (EBP), requires both agreement and coordination on standards to ensure that the collective effort generates rapid progress toward its goals. To this end, the EBP initiated five technical standards committees comprising volunteer members from the global genomics scientific community: Sample Collection and Processing, Sequencing and Assembly, Annotation, Analysis, and IT and Informatics. The current versions of the resulting standards documents are available on the EBP website, with the recognition that opportunities, technologies, and challenges may improve or change in the future, requiring flexibility for the EBP to meet its goals. Here, we describe some highlights from the proposed standards, and areas where additional challenges will need to be met.

Major Revisions in Pancrustacean Phylogeny and Evidence of Sensitivity to Taxon Sampling.

The clade Pancrustacea, comprising crustaceans and hexapods, is the most diverse group of animals on earth, containing over 80% of animal species and half of animal biomass. It has been the subject of several recent phylogenomic analyses, yet relationships within Pancrustacea show a notable lack of stability. Here, the phylogeny is estimated with expanded taxon sampling, particularly of malacostracans. We show small changes in taxon sampling have large impacts on phylogenetic estimation. By analyzing identical orthologs between two slightly different taxon sets, we show that the differences in the resulting topologies are due primarily to the effects of taxon sampling on the phylogenetic reconstruction method. We compare trees resulting from our phylogenomic analyses with those from the literature to explore the large tree space of pancrustacean phylogenetic hypotheses and find that statistical topology tests reject the previously published trees in favor of the maximum likelihood trees produced here. Our results reject several clades including Caridoida, Eucarida, Multicrustacea, Vericrustacea, and Syncarida. Notably, we find Copepoda nested within Allotriocarida with high support and recover a novel relationship between decapods, euphausiids, and syncarids that we refer to as the Syneucarida. With denser taxon sampling, we find Stomatopoda sister to this latter clade, which we collectively name Stomatocarida, dividing Malacostraca into three clades: Leptostraca, Peracarida, and Stomatocarida. A new Bayesian divergence time estimation is conducted using 13 vetted fossils. We review our results in the context of other pancrustacean phylogenetic hypotheses and highlight 15 key taxa to sample in future studies.

Convergent adaptation of true crabs (Decapoda: Brachyura) to a gradient of terrestrial environments.

For much of terrestrial biodiversity, the evolutionary pathways of adaptation from marine ancestors are poorly understood, and have usually been viewed as a binary trait. True crabs, the decapod crustacean infraorder Brachyura, comprise over 7,600 species representing a striking diversity of morphology and ecology, including repeated adaptation to non-marine habitats. Here, we reconstruct the evolutionary history of Brachyura using new and published sequences of 10 genes for 344 tips spanning 88 of 109 brachyuran families. Using 36 newly vetted fossil calibrations, we infer that brachyurans most likely diverged in the Triassic, with family-level splits in the late Cretaceous and early Paleogene. By contrast, the root age is underestimated with automated sampling of 328 fossil occurrences explicitly incorporated into the tree prior, suggesting such models are a poor fit under heterogeneous fossil preservation. We apply recently defined trait-by-environment associations to classify a gradient of transitions from marine to terrestrial lifestyles. We estimate that crabs left the marine environment at least seven and up to 17 times convergently, and returned to the sea from non-marine environments at least twice. Although the most highly terrestrial- and many freshwater-adapted crabs are concentrated in Thoracotremata, Bayesian threshold models of ancestral state reconstruction fail to identify shifts to higher terrestrial grades due to the degree of underlying change required. Lineages throughout our tree inhabit intertidal and marginal marine environments, corroborating the inference that the early stages of terrestrial adaptation have a lower threshold to evolve. Our framework and extensive new fossil and natural history datasets will enable future comparisons of non-marine adaptation at the morphological and molecular level. Crabs provide an important window into the early processes of adaptation to novel environments, and different degrees of evolutionary constraint that might help predict these pathways.

The HIV Latency Reversal Agent HODHBt Enhances NK Cell Effector and Memory-Like Functions by Increasing Interleukin-15-Mediated STAT Activation.

Elimination of human immunodeficiency virus (HIV) reservoirs is a critical endpoint to eradicate HIV. One therapeutic intervention against latent HIV is "shock and kill." This strategy is based on the transcriptional activation of latent HIV with a latency-reversing agent (LRA) with the consequent killing of the reactivated cell by either the cytopathic effect of HIV or the immune system. We have previously found that the small molecule 3-hydroxy-1,2,3-benzotriazin-4(3H)-one (HODHBt) acts as an LRA by increasing signal transducer and activator of transcription (STAT) factor activation mediated by interleukin-15 (IL-15) in cells isolated from aviremic participants. The IL-15 superagonist N-803 is currently under clinical investigation to eliminate latent reservoirs. IL-15 and N-803 share similar mechanisms of action by promoting the activation of STATs and have shown some promise in preclinical models directed toward HIV eradication. In this work, we evaluated the ability of HODHBt to enhance IL-15 signaling in natural killer (NK) cells and the biological consequences associated with increased STAT activation in NK cell effector and memory-like functions. We showed that HODHBt increased IL-15-mediated STAT phosphorylation in NK cells, resulting in increases in the secretion of CXCL-10 and interferon gamma (IFN-γ) and the expression of cytotoxic proteins, including granzyme B, granzyme A, perforin, granulysin, FASL, and TRAIL. This increased cytotoxic profile results in increased cytotoxicity against HIV-infected cells and different tumor cell lines. HODHBt also improved the generation of cytokine-induced memory-like NK cells. Overall, our data demonstrate that enhancing the magnitude of IL-15 signaling with HODHBt favors NK cell cytotoxicity and memory-like generation, and thus, targeting this pathway could be further explored for HIV cure interventions. IMPORTANCE Several clinical trials targeting the HIV latent reservoir with LRAs have been completed. In spite of a lack of clinical benefit, they have been crucial to elucidate hurdles that "shock and kill" strategies have to overcome to promote an effective reduction of the latent reservoir to lead to a cure. These hurdles include low reactivation potential mediated by LRAs, the negative influence of some LRAs on the activity of natural killer and effector CD8 T cells, an increased resistance to apoptosis of latently infected cells, and an exhausted immune system due to chronic inflammation. To that end, finding therapeutic strategies that can overcome some of these challenges could improve the outcome of shock and kill strategies aimed at HIV eradication. Here, we show that the LRA HODHBt also improves IL-15-mediated NK cell effector and memory-like functions. As such, pharmacological enhancement of IL-15-mediated STAT activation can open new therapeutic avenues toward an HIV cure.

COVID-19 biomarkers and their overlap with comorbidities in a disease biomarker data model.

In response to the COVID-19 outbreak, scientists and medical researchers are capturing a wide range of host responses, symptoms and lingering postrecovery problems within the human population. These variable clinical manifestations suggest differences in influential factors, such as innate and adaptive host immunity, existing or underlying health conditions, comorbidities, genetics and other factors-compounding the complexity of COVID-19 pathobiology and potential biomarkers associated with the disease, as they become available. The heterogeneous data pose challenges for efficient extrapolation of information into clinical applications. We have curated 145 COVID-19 biomarkers by developing a novel cross-cutting disease biomarker data model that allows integration and evaluation of biomarkers in patients with comorbidities. Most biomarkers are related to the immune (SAA, TNF-∝ and IP-10) or coagulation (D-dimer, antithrombin and VWF) cascades, suggesting complex vascular pathobiology of the disease. Furthermore, we observe commonality with established cancer biomarkers (ACE2, IL-6, IL-4 and IL-2) as well as biomarkers for metabolic syndrome and diabetes (CRP, NLR and LDL). We explore these trends as we put forth a COVID-19 biomarker resource (https://data.oncomx.org/covid19) that will help researchers and diagnosticians alike.

Deep Ancestral Introgression Shapes Evolutionary History of Dragonflies and Damselflies.

Introgression is an important biological process affecting at least 10% of the extant species in the animal kingdom. Introgression significantly impacts inference of phylogenetic species relationships where a strictly binary tree model cannot adequately explain reticulate net-like species relationships. Here, we use phylogenomic approaches to understand patterns of introgression along the evolutionary history of a unique, nonmodel insect system: dragonflies and damselflies (Odonata). We demonstrate that introgression is a pervasive evolutionary force across various taxonomic levels within Odonata. In particular, we show that the morphologically "intermediate" species of Anisozygoptera (one of the three primary suborders within Odonata besides Zygoptera and Anisoptera), which retain phenotypic characteristics of the other two suborders, experienced high levels of introgression likely coming from zygopteran genomes. Additionally, we find evidence for multiple cases of deep inter-superfamilial ancestral introgression. [Gene flow; Odonata; phylogenomics; reticulate evolution.].

HAPHPIPE: Haplotype Reconstruction and Phylodynamics for Deep Sequencing of Intrahost Viral Populations.

Deep sequencing of viral populations using next-generation sequencing (NGS) offers opportunities to understand and investigate evolution, transmission dynamics, and population genetics. Currently, the standard practice for processing NGS data to study viral populations is to summarize all the observed sequences from a sample as a single consensus sequence, thus discarding valuable information about the intrahost viral molecular epidemiology. Furthermore, existing analytical pipelines may only analyze genomic regions involved in drug resistance, thus are not suited for full viral genome analysis. Here, we present HAPHPIPE, a HAplotype and PHylodynamics PIPEline for genome-wide assembly of viral consensus sequences and haplotypes. The HAPHPIPE protocol includes modules for quality trimming, error correction, de novo assembly, alignment, and haplotype reconstruction. The resulting consensus sequences, haplotypes, and alignments can be further analyzed using a variety of phylogenetic and population genetic software. HAPHPIPE is designed to provide users with a single pipeline to rapidly analyze sequences from viral populations generated from NGS platforms and provide quality output properly formatted for downstream evolutionary analyses.

Omics community detection using multi-resolution clustering.

MOTIVATION: The discovery of biologically interpretable and clinically actionable communities in heterogeneous omics data is a necessary first step toward deriving mechanistic insights into complex biological phenomena. Here, we present a novel clustering approach, omeClust, for community detection in omics profiles by simultaneously incorporating similarities among measurements and the overall complex structure of the data. RESULTS: We show that omeClust outperforms published methods in inferring the true community structure as measured by both sensitivity and misclassification rate on simulated datasets. We further validated omeClust in diverse, multiple omics datasets, revealing new communities and functionally related groups in microbial strains, cell line gene expression patterns and fetal genomic variation. We also derived enrichment scores attributable to putatively meaningful biological factors in these datasets that can serve as hypothesis generators facilitating new sets of testable hypotheses. AVAILABILITY AND IMPLEMENTATION: omeClust is open-source software, and the implementation is available online at http://github.com/omicsEye/omeClust. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Dominant clade-featured SARS-CoV-2 co-occurring mutations reveal plausible epistasis: An in silico based hypothetical model.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved into eight fundamental clades with four of these clades (G, GH, GR, and GV) globally prevalent in 2020. To explain plausible epistatic effects of the signature co-occurring mutations of these circulating clades on viral replication and transmission fitness, we proposed a hypothetical model using in silico approach. Molecular docking and dynamics analyses showed the higher infectiousness of a spike mutant through more favorable binding of G614 with the elastase-2. RdRp mutation p.P323L significantly increased genome-wide mutations (p < 0.0001), allowing for more flexible RdRp (mutated)-NSP8 interaction that may accelerate replication. Superior RNA stability and structural variation at NSP3:C241T might impact protein, RNA interactions, or both. Another silent 5'-UTR:C241T mutation might affect translational efficiency and viral packaging. These four G-clade-featured co-occurring mutations might increase viral replication. Sentinel GH-clade ORF3a:p.Q57H variants constricted the ion-channel through intertransmembrane-domain interaction of cysteine(C81)-histidine(H57). The GR-clade N:p.RG203-204KR would stabilize RNA interaction by a more flexible and hypo-phosphorylated SR-rich region. GV-clade viruses seemingly gained the evolutionary advantage of the confounding factors; nevertheless, N:p.A220V might modulate RNA binding with no phenotypic effect. Our hypothetical model needs further retrospective and prospective studies to understand detailed molecular events and their relationship to the fitness of SARS-CoV-2.

Felsenstein Phylogenetic Likelihood.

In 1981, the Journal of Molecular Evolution (JME) published an article entitled "Evolutionary trees from DNA sequences: A maximum likelihood approach" by Joseph (Joe) Felsenstein (J Mol Evol 17:368-376, 1981). This groundbreaking work laid the foundation for the emerging field of statistical phylogenetics, providing a tractable way of finding maximum likelihood (ML) estimates of evolutionary trees from DNA sequence data. This paper is the second most cited (more than 9000 citations) in JME after Kimura's (J Mol Evol 16:111-120, 1980) seminal paper on a model of nucleotide substitution (with nearly 20,000 citations). On the occasion of the 50th anniversary of JME, we elaborate on the significance of Felsenstein's ML approach to estimating phylogenetic trees.

Mutated CEACAMs Disrupt Transforming Growth Factor Beta Signaling and Alter the Intestinal Microbiome to Promote Colorectal Carcinogenesis.

BACKGROUND & AIMS: We studied interactions among proteins of the carcinoembryonic antigen-related cell adhesion molecule (CEACAM) family, which interact with microbes, and transforming growth factor beta (TGFB) signaling pathway, which is often altered in colorectal cancer cells. We investigated mechanisms by which CEACAM proteins inhibit TGFB signaling and alter the intestinal microbiome to promote colorectal carcinogenesis. METHODS: We collected data on DNA sequences, messenger RNA expression levels, and patient survival times from 456 colorectal adenocarcinoma cases, and a separate set of 594 samples of colorectal adenocarcinomas, in The Cancer Genome Atlas. We performed shotgun metagenomic sequencing analyses of feces from wild-type mice and mice with defects in TGFB signaling (Sptbn1+/- and Smad4+/-/Sptbn1+/-) to identify changes in microbiota composition before development of colon tumors. CEACAM protein and its mutants were overexpressed in SW480 and HCT116 colorectal cancer cell lines, which were analyzed by immunoblotting and proliferation and colony formation assays. RESULTS: In colorectal adenocarcinomas, high expression levels of genes encoding CEACAM proteins, especially CEACAM5, were associated with reduced survival times of patients. There was an inverse correlation between expression of CEACAM genes and expression of TGFB pathway genes (TGFBR1, TGFBR2, and SMAD3). In colorectal adenocarcinomas, we also found an inverse correlation between expression of genes in the TGFB signaling pathway and genes that regulate stem cell features of cells. We found mutations encoding L640I and A643T in the B3 domain of human CEACAM5 in colorectal adenocarcinomas; structural studies indicated that these mutations would alter the interaction between CEACAM5 and TGFBR1. Overexpression of these mutants in SW480 and HCT116 colorectal cancer cell lines increased their anchorage-independent growth and inhibited TGFB signaling to a greater extent than overexpression of wild-type CEACAM5, indicating that they are gain-of-function mutations. Compared with feces from wild-type mice, feces from mice with defects in TGFB signaling had increased abundance of bacterial species that have been associated with the development of colon tumors, including Clostridium septicum, and decreased amounts of beneficial bacteria, such as Bacteroides vulgatus and Parabacteroides distasonis. CONCLUSION: We found expression of CEACAMs and genes that regulate stem cell features of cells to be increased in colorectal adenocarcinomas and inversely correlated with expression of TGFB pathway genes. We found colorectal adenocarcinomas to express mutant forms of CEACAM5 that inhibit TGFB signaling and increase proliferation and colony formation. We propose that CEACAM proteins disrupt TGFB signaling, which alters the composition of the intestinal microbiome to promote colorectal carcinogenesis.

ReQTL: identifying correlations between expressed SNVs and gene expression using RNA-sequencing data.

MOTIVATION: By testing for associations between DNA genotypes and gene expression levels, expression quantitative trait locus (eQTL) analyses have been instrumental in understanding how thousands of single nucleotide variants (SNVs) may affect gene expression. As compared to DNA genotypes, RNA genetic variation represents a phenotypic trait that reflects the actual allele content of the studied system. RNA genetic variation at expressed SNV loci can be estimated using the proportion of alleles bearing the variant nucleotide (variant allele fraction, VAFRNA). VAFRNA is a continuous measure which allows for precise allele quantitation in loci where the RNA alleles do not scale with the genotype count. We describe a method to correlate VAFRNA with gene expression and assess its ability to identify genetically regulated expression solely from RNA-sequencing (RNA-seq) datasets. RESULTS: We introduce ReQTL, an eQTL modification which substitutes the DNA allele count for the variant allele fraction at expressed SNV loci in the transcriptome (VAFRNA). We exemplify the method on sets of RNA-seq data from human tissues obtained though the Genotype-Tissue Expression (GTEx) project and demonstrate that ReQTL analyses are computationally feasible and can identify a subset of expressed eQTL loci. AVAILABILITY AND IMPLEMENTATION: A toolkit to perform ReQTL analyses is available at https://github.com/HorvathLab/ReQTL. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Inflammation in children with cystic fibrosis: contribution of bacterial production of long-chain fatty acids.

BACKGROUND: Cystic fibrosis (CF) affects >70,000 people worldwide, yet the microbiologic trigger for pulmonary exacerbations (PExs) remains unknown. The objective of this study was to identify changes in bacterial metabolic pathways associated with clinical status. METHODS: Respiratory samples were collected at hospital admission for PEx, end of intravenous (IV) antibiotic treatment, and follow-up from 27 hospitalized children with CF. Bacterial DNA was extracted and shotgun DNA sequencing was performed. MetaPhlAn2 and HUMAnN2 were used to evaluate bacterial taxonomic and pathway relative abundance, while DESeq2 was used to evaluate differential abundance based on clinical status. RESULTS: The mean age of study participants was 10 years; 85% received combination IV antibiotic therapy (beta-lactam plus a second agent). Long-chain fatty acid (LCFA) biosynthesis pathways were upregulated in follow-up samples compared to end of treatment: gondoate (p = 0.012), oleate (p = 0.048), palmitoleate (p = 0.043), and pathways of fatty acid elongation (p = 0.012). Achromobacter xylosoxidans and Escherichia sp. were also more prevalent in follow-up compared to PEx (p < 0.001). CONCLUSIONS: LCFAs may be associated with persistent infection of opportunistic pathogens. Future studies should more closely investigate the role of LCFA production by lung bacteria in the transition from baseline wellness to PEx in persons with CF. IMPACT: Increased levels of LCFAs are found after IV antibiotic treatment in persons with CF. LCFAs have previously been associated with increased lung inflammation in asthma. This is the first report of LCFAs in the airway of persons with CF. This research provides support that bacterial production of LCFAs may be a contributor to inflammation in persons with CF. Future studies should evaluate LCFAs as predictors of future PExs.

Earth BioGenome Project: Sequencing life for the future of life.

Increasing our understanding of Earth's biodiversity and responsibly stewarding its resources are among the most crucial scientific and social challenges of the new millennium. These challenges require fundamental new knowledge of the organization, evolution, functions, and interactions among millions of the planet's organisms. Herein, we present a perspective on the Earth BioGenome Project (EBP), a moonshot for biology that aims to sequence, catalog, and characterize the genomes of all of Earth's eukaryotic biodiversity over a period of 10 years. The outcomes of the EBP will inform a broad range of major issues facing humanity, such as the impact of climate change on biodiversity, the conservation of endangered species and ecosystems, and the preservation and enhancement of ecosystem services. We describe hurdles that the project faces, including data-sharing policies that ensure a permanent, freely available resource for future scientific discovery while respecting access and benefit sharing guidelines of the Nagoya Protocol. We also describe scientific and organizational challenges in executing such an ambitious project, and the structure proposed to achieve the project's goals. The far-reaching potential benefits of creating an open digital repository of genomic information for life on Earth can be realized only by a coordinated international effort.

Microbiome dynamics and genomic determinants of bovine mastitis.

The milk of lactating cows presents a complex ecosystem of interconnected microbial communities which can influence the pathophysiology of mastitis. We hypothesized possible dynamic shifts of microbiome composition and genomic features with different pathological conditions of mastitis (Clinical Mastitis; CM, Recurrent CM; RCM, Subclinical Mastitis; SCM). To evaluate this hypothesis, we employed whole metagenome sequencing (WMS) in 20 milk samples (CM, 5; RCM, 6; SCM, 4; H, 5) to unravel the microbiome dynamics, interrelation, and relevant metabolic functions. The WMS data mapped to 442 bacterial, 58 archaeal and 48 viral genomes with distinct variation in microbiome composition (CM > H > RCM > SCM). Furthermore, we identified a number of microbial genomic features, including 333, 304, 183 and 50 virulence factors-associated genes (VFGs) and 48, 31, 11 and 6 antibiotic resistance genes (ARGs) in CM, RCM, SCM, and H-microbiomes, respectively. We also detected different metabolic pathway and functional genes associated with mastitis pathogenesis. Therefore, profiling microbiome dynamics in different conditions of mastitis and associated microbial genomic features contributes to developing microbiome-based diagnostics and therapeutics for bovine mastitis.

Telescope: Characterization of the retrotranscriptome by accurate estimation of transposable element expression.

Characterization of Human Endogenous Retrovirus (HERV) expression within the transcriptomic landscape using RNA-seq is complicated by uncertainty in fragment assignment because of sequence similarity. We present Telescope, a computational software tool that provides accurate estimation of transposable element expression (retrotranscriptome) resolved to specific genomic locations. Telescope directly addresses uncertainty in fragment assignment by reassigning ambiguously mapped fragments to the most probable source transcript as determined within a Bayesian statistical model. We demonstrate the utility of our approach through single locus analysis of HERV expression in 13 ENCODE cell types. When examined at this resolution, we find that the magnitude and breadth of the retrotranscriptome can be vastly different among cell types. Furthermore, our approach is robust to differences in sequencing technology and demonstrates that the retrotranscriptome has potential to be used for cell type identification. We compared our tool with other approaches for quantifying transposable element (TE) expression, and found that Telescope has the greatest resolution, as it estimates expression at specific TE insertions rather than at the TE subfamily level. Telescope performs highly accurate quantification of the retrotranscriptomic landscape in RNA-seq experiments, revealing a differential complexity in the transposable element biology of complex systems not previously observed. Telescope is available at https://github.com/mlbendall/telescope.

The Evolution of Gene Expression Underlying Vision Loss in Cave Animals.

Dissecting the evolutionary genetic processes underlying eye reduction and vision loss in obligate cave-dwelling organisms has been a long-standing challenge in evolutionary biology. Independent vision loss events in related subterranean organisms can provide critical insight into these processes as well as into the nature of convergent loss of complex traits. Advances in evolutionary developmental biology have illuminated the significant role of heritable gene expression variation in the evolution of new forms. Here, we analyze gene expression variation in adult eye tissue across the freshwater crayfish, representing four independent vision-loss events in caves. Species and individual expression patterns cluster by eye function rather than phylogeny, suggesting convergence in transcriptome evolution in independently blind animals. However, this clustering is not greater than what is observed in surface species with conserved eye function after accounting for phylogenetic expectations. Modeling expression evolution suggests that there is a common increase in evolutionary rates in the blind lineages, consistent with a relaxation of selective constraint maintaining optimal expression levels. This is evidence for a repeated loss of expression constraint in the transcriptomes of blind animals and that convergence occurs via a similar trajectory through genetic drift.