Genome-scale Data Research Articles

Pseudoreplication in genomic-scale data sets.

In genomic-scale data sets, loci are closely packed within chromosomes and hence provide correlated information. Averaging across loci as if they were independent creates pseudoreplication, which reduces the effective degrees of freedom (df') compared to the nominal degrees of freedom, df. This issue has been known for some time, but consequences have not been systematically quantified across the entire genome. Here, we measured pseudoreplication (quantified by the ratio df'/df) for a common metric of genetic differentiation (FST ) and a common measure of linkage disequilibrium between pairs of loci (r2 ). Based on data simulated using models (SLiM and msprime) that allow efficient forward-in-time and coalescent simulations while precisely controlling population pedigrees, we estimated df' and df'/df by measuring the rate of decline in the variance of mean FST and mean r2 as more loci were used. For both indices, df' increases with Ne and genome size, as expected. However, even for large Ne and large genomes, df' for mean r2 plateaus after a few thousand loci, and a variance components analysis indicates that the limiting factor is uncertainty associated with sampling individuals rather than genes. Pseudoreplication is less extreme for FST , but df'/df ≤0.01 can occur in data sets using tens of thousands of loci. Commonly-used block-jackknife methods consistently overestimated var (FST ), producing very conservative confidence intervals. Predicting df' based on our modelling results as a function of Ne , L, S, and genome size provides a robust way to quantify precision associated with genomic-scale data sets.

DdRAD Sequencing Sheds Light on Low Interspecific and High Intraspecific mtDNA Divergences in Two Groups of Caddisflies

Abstract Large-scale global efforts on DNA barcoding have repeatedly revealed unexpected patterns of variability in mtDNA, including deep intraspecific divergences and haplotype sharing between species. Understanding the evolutionary causes behind these patterns calls for insights from the nuclear genome. While building a near-complete DNA barcode library of Finnish caddisflies, a case of barcode-sharing and some cases of deep intraspecific divergences were observed. In this study, the Apatania zonella (Zetterstedt, 1840) group and three Limnephilus Leach, 1815 species were studied using double digest RAD sequencing (ddRAD-seq), morphology, and DNA barcoding. The results support the present species boundaries in the A. zonella group species. A morphologically distinct but mitogenetically nondistinct taxon related to parthenogenetic Apatania hispida (Forsslund, 1930) got only weak support for its validity as a distinct species. The morphology and genomic-scale data do not indicate cryptic diversity in any of the three Limnephilus species despite the observed deep intraspecific divergences in DNA barcodes. This demonstrates that polymorphism in mtDNA may not reflect cryptic diversity, but mitonuclear discordance due to other evolutionary causes.

Phylogenomics of African radiation of Praomyini (Muridae: Murinae) rodents: First fully resolved phylogeny, evolutionary history and delimitation of extant genera

The tribe Praomyini is a diversified group including 64 species and eight extant rodent genera. They live in a broad spectrum of habitats across whole sub-Saharan Africa. Members of this tribe are often very abundant, they have a key ecological role in ecosystems, they are hosts of many potentially pathogenic microorganisms and comprise numerous agricultural pests. Although this tribe is well supported by both molecular and morphological data, its intergeneric relationships and the species contents of several genera are not yet fully resolved. Recent molecular data suggest that at least three genera in current sense are paraphyletic. However, in these studies the species sampling was sparse and the resolution of relationships among genera was poor, probably due to a fast radiation of the tribe dated to the Miocene and insufficient amount of genetic data. Here we used genomic scale data (395 nuclear loci = 610,965 bp long alignment and mitogenomes = 14,745 bp) and produced the first fully resolved species tree containing most major lineages of the Praomyini tribe (i.e. all but one currently delimited genera and major intrageneric clades). Results of a fossil-based divergence dating analysis suggest that the radiation started during the Messinian stage (ca. 7 Ma) and was likely linked to a fragmentation of the pan-African Miocene forest. Some lineages remained in the rain forests, while many others adapted to a broad spectrum of new open lowland and montane habitats that appeared at the beginning of Pliocene. Our analyses clearly confirmed the presence of three polyphyletic genera (Praomys, Myomyscus and Mastomys). We review current knowledge of these three genera and suggest corresponding taxonomic changes. To keep genera monophyletic, we propose taxonomic re-arrangements and delimit four new genera. Furthermore, we discovered a new highly divergent genetic lineage of Praomyini in southwestern Ethiopia, which is described as a new species and genus.

Abstract 3028: Integrative genomics reveals lncRNAs associated with pediatric cancer

Abstract Background: Long non-coding RNAs (lncRNAs) have emerged as key components of transcriptional and post-transcriptional gene regulation. Dysregulation of lncRNA expression has been widely observed in cancer and several lncRNAs are known to influence tumor initiation and progression. Despite this, the lncRNA landscape and regulatory networks across pediatric cancers remain relatively uncharted. Methods: To characterize the lncRNA landscape of pediatric cancers, we first curated RNA sequencing data for 1,044 pediatric leukemia and solid tumors from the Therapeutically Applicable Research To Generate Effective Treatments (TARGET) project to identify known and novel expressed lncRNAs. This data set included: 280 acute myeloid leukemia (AML), 190 acute B-cell leukemia (B-ALL), 244 acute T-cell leukemia (T-ALL), 121 Wilm's tumor (WT), 48 rhabdoid tumors (RT), and 161 neuroblastoma (NBL). Histotype-specific expression was assessed using the tau score. Whole genome sequencing (WGS) from 826 matched normal-tumor pairs was integrated to identify somatic copy number alterations (SCNAs) disrupting lncRNA expression. To further implicate cancer-relevant drivers of lncRNA expression, we used a unique combination of epigenetic data in pediatric cell lines, including ChIP-sequencing for cancer-specific transcription factors and genome-scale chromatin capture data. A global analysis of lncRNA function was performed using the lncMod method, in which expression data is modelled to identify lncRNA modulators that perturb transcription factor regulation of target genes. Functional prioritization of lncRNAs was obtained through integration of analyses per cancer. Biochemical assays in human-derived cell line models were utilized to validate the function of the top prioritized lncRNA in NBL. Results: We report a total of 2,657 robustly expressed lncRNAs across six pediatric cancers, including 1,142 lncRNAs exhibiting histotype-specific expression. SCNAs contributed to lncRNA dysregulation at a proportion comparable to protein coding genes. There were 207 (28%) lncRNAs in regions with SCNA that had significant expression dysregulation. LncMod analysis across the cancers revealed context-specific transcriptional gene networks per dysregulated lncRNA and enrichment for proliferation, metabolic, and DNA damage hallmarks. We further identified 547 cancer-associated lncRNAs in NBL based on upstream regulation via oncogenic transcription factors. The top-prioritized lncRNA, TBX2-AS1, was predicted to impact proliferation in NBL. Silencing of TBX2-AS1 using siRNAs achieved >90% knockdown in NBL cells and resulted in 46.6% decreased cell growth (p = 8.1 x 10-4). Conclusion: This study defines the lncRNA landscape across six pediatric cancers and provides a detailed catalog of how lncRNAs impact regulatory gene networks. These data serve as a robust resource for future hypothesis-driven mechanistic studies. Citation Format: Apexa Modi, Gonzalo Lopez, Karina L. Conkrite, Tsz Ching Leung, Sathvik Ramanan, Daphne Cheung, Chun Su, Matthew E. Johnson, Elisabetta Manduchi, Samantha Gadd, Jinghui Zhang, Malcolm A. Smith, Jaime M. Guidry Auvil, Daniela S. Gerhard, Soheil Meshinchi, Elizabeth J. Perlman, Stephen P. Hunger, John M. Maris, Andrew D. Wells, Struan F. Grant, Sharon J. Diskin. Integrative genomics reveals lncRNAs associated with pediatric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3028.

Museum genomics reveals the rapid decline and extinction of Australian rodents since European settlement

Australia has the highest historically recorded rate of mammalian extinction in the world, with 34 terrestrial species declared extinct since European colonization in 1788. Among Australian mammals, rodents have been the most severely affected by these recent extinctions; however, given a sparse historical record, the scale and timing of their decline remain unresolved. Using museum specimens up to 184 y old, we generate genomic-scale data from across the entire assemblage of Australian hydromyine rodents (i.e., eight extinct species and their 42 living relatives). We reconstruct a phylogenomic tree for these species spanning ∼5.2 million years, revealing a cumulative total of 10 million years (>10%) of unique evolutionary history lost to extinction within the past ∼150 y. We find no evidence for reduced genetic diversity in extinct species just prior to or during decline, indicating that their extinction was extremely rapid. This suggests that populations of extinct Australian rodents were large prior to European colonization, and that genetic diversity does not necessarily protect species from catastrophic extinction. In addition, comparative analyses suggest that body size and biome interact to predict extinction and decline, with larger species more likely to go extinct. Finally, we taxonomically resurrect a species from extinction, Gould's mouse (Pseudomys gouldii Waterhouse, 1839), which survives as an island population in Shark Bay, Western Australia (currently classified as Pseudomys fieldi Waite, 1896). With unprecedented sampling across a radiation of extinct and living species, we unlock a previously inaccessible historical perspective on extinction in Australia. Our results highlight the capacity of collections-based research to inform conservation and management of persisting species.

Genome Warehouse: A Public Repository Housing Genome-scale Data

The Genome Warehouse (GWH) is a public repository housing genome assembly data for a wide range of species and delivering a series of web services for genome data submission, storage, release, and sharing. As one of the core resources in the National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB; https://ngdc.cncb.ac.cn), GWH accepts both full and partial (chloroplast, mitochondrion, and plasmid) genome sequences with different assembly levels, as well as an update of existing genome assemblies. For each assembly, GWH collects detailed genome-related metadata of biological project, biological sample, and genome assembly, in addition to genome sequence and annotation. To archive high-quality genome sequences and annotations, GWH is equipped with a uniform and standardized procedure for quality control. Besides basic browse and search functionalities, all released genome sequences and annotations can be visualized with JBrowse. By May 21, 2021, GWH has received 19,124 direct submissions covering a diversity of 1108 species and has released 8772 of them. Collectively, GWH serves as an important resource for genome-scale data management and provides free and publicly accessible data to support research activities throughout the world. GWH is publicly accessible at https://ngdc.cncb.ac.cn/gwh.

The origin of human mutation in light of genomic data.

Despite years of active research into the role of DNA repair and replication in mutagenesis, surprisingly little is known about the origin of spontaneous human mutation in the germ line. With the advent of high-throughput sequencing, genome-scale data have revealed statistical properties of mutagenesis in humans. These properties include variation of the mutation rate and spectrum along the genome at different scales in relation to epigenomic features and dependency on parental age. Moreover, mutations originated in mothers are less frequent than mutations originated in fathers and have a distinct genomic distribution. Statistical analyses that interpret these patterns in the context of known biochemistry can provide mechanistic models of mutagenesis in humans.

Corrigendum to: Resolving the Early Divergence Pattern of Teleost Fish Using Genome-Scale Data

Corrigendum to: Resolving the Early Divergence Pattern of Teleost Fish Using Genome-Scale Data

Multi Locus View: an extensible web-based tool for the analysis of genomic data.

Tracking and understanding data quality, analysis and reproducibility are critical concerns in the biological sciences. This is especially true in genomics where next generation sequencing (NGS) based technologies such as ChIP-seq, RNA-seq and ATAC-seq are generating a flood of genome-scale data. However, such data are usually processed with automated tools and pipelines, generating tabular outputs and static visualisations. Interpretation is normally made at a high level without the ability to visualise the underlying data in detail. Conventional genome browsers are limited to browsing single locations and do not allow for interactions with the dataset as a whole. Multi Locus View (MLV), a web-based tool, has been developed to allow users to fluidly interact with genomics datasets at multiple scales. The user is able to browse the raw data, cluster, and combine the data with other analysis and annotate the data. User datasets can then be shared with other users or made public for quick assessment from the academic community. MLV is publically available at https://mlv.molbiol.ox.ac.uk.

Phylogenomic Subsampling and the Search for Phylogenetically Reliable Loci.

Phylogenomic subsampling is a procedure by which small sets of loci are selected from large genome-scale data sets and used for phylogenetic inference. This step is often motivated by either computational limitations associated with the use of complex inference methods or as a means of testing the robustness of phylogenetic results by discarding loci that are deemed potentially misleading. Although many alternative methods of phylogenomic subsampling have been proposed, little effort has gone into comparing their behavior across different data sets. Here, I calculate multiple gene properties for a range of phylogenomic data sets spanning animal, fungal, and plant clades, uncovering a remarkable predictability in their patterns of covariance. I also show how these patterns provide a means for ordering loci by both their rate of evolution and their relative phylogenetic usefulness. This method of retrieving phylogenetically useful loci is found to be among the top performing when compared with alternative subsampling protocols. Relatively common approaches such as minimizing potential sources of systematic bias or increasing the clock-likeness of the data are found to fare worse than selecting loci at random. Likewise, the general utility of rate-based subsampling is found to be limited: loci evolving at both low and high rates are among the least effective, and even those evolving at optimal rates can still widely differ in usefulness. This study shows that many common subsampling approaches introduce unintended effects in off-target gene properties and proposes an alternative multivariate method that simultaneously optimizes phylogenetic signal while controlling for known sources of bias.

Testing the Utility of Alternative Metrics of Branch Support to Address the Ancient Evolutionary Radiation of Tunas, Stromateoids, and Allies (Teleostei: Pelagiaria)

The use of high-throughput sequencing technologies to produce genome-scale data sets was expected to settle some long-standing controversies across the Tree of Life, particularly in areas where short branches occur at deep timescales. Instead, these data sets have often yielded many well-supported but conflicting topologies, and highly variable gene-tree distributions. A variety of branch-support metrics beyond the nonparametric bootstrap are now available to assess how robust a phylogenetic hypothesis may be, as well as new methods to quantify gene-tree discordance. We applied multiple branch-support metrics to a study of an ancient group of marine fishes (Teleostei: Pelagiaria) whose interfamilial relationships have proven difficult to resolve due to a rapid accumulation of lineages very early in its history. We analyzed hundreds of loci including published ultraconserved elements and newly generated exonic data along with their flanking regions to represent all 16 extant families for more than 150 out of 284 valid species in the group. Branch support was typically lower at inter- than intra-familial relationships regardless of the type of marker used. Several nodes that were highly supported with bootstrap had a very low site and gene-tree concordance, revealing underlying conflict. Despite this conflict, we were able to identify four consistent interfamilial clades, each comprised of two or three families. Combining exons with their flanking regions also produced increased branch lengths at the deep branches of the pelagiarian tree. Our results demonstrate the limitations of employing current metrics of branch support and species-tree estimation when assessing the confidence of ancient evolutionary radiations and emphasize the necessity to embrace alternative measurements to explore phylogenetic uncertainty and discordance in phylogenomic data sets.[Concatenation; exons; introns; phylogenomics; species-tree methods; target capture.].

The Translational Machine: A novel machine-learning approach to illuminate complex genetic architectures.

The Translational Machine (TM) is a machine learning (ML)-based analytic pipeline that translates genotypic/variant call data into biologically contextualized features that richly characterize complex variant architectures and permit greater interpretability and biological replication. It also reduces potentially confounding effects of population substructure on outcome prediction. The TM consists of three main components. First, replicable but flexible feature engineering procedures translate genome-scale data into biologically informative features that appropriately contextualize simple variant calls/genotypes within biological and functional contexts. Second, model-free, nonparametric ML-based feature filtering procedures empirically reduce dimensionality and noise of both original genotype calls and engineered features. Third, a powerful ML algorithm for feature selection is used to differentiate risk variant contributions across variant frequency and functional prediction spectra. The TM simultaneously evaluates potential contributions of variants operative under polygenic and heterogeneous models of genetic architecture. Our TM enables integration of biological information (e.g., genomic annotations) within conceptual frameworks akin to geneset-/pathways-based and collapsing methods, but overcomes some of these methods' limitations. The full TM pipeline is executed in R. Our approach and initial findings from its application to a whole-exome schizophrenia case-control data set are presented. These TM procedures extend the findings of the primary investigation and yield novel results.

Species limits in birds: Australian perspectives on interrelated challenges of allopatry, introgression of mitochondrial DNA, recent speciation, and selection

Abstract Four main challenges that can underpin ongoing, intransigent debates about species limits in birds are reviewed: allopatry (population subdivision vs. speciation), geographically widespread introgression of mitochondrial DNA (mtDNA), recent speciation, and selection. Examples from birds of the Australian region show how these challenges, their interplay, and the molecular-phenotypic discordance they generate can clarify or mislead species limits. Examples of how phylogenetic frameworks help reject or retain hypotheses of species limits under these challenges are given. Although mtDNA’s strengths and limitations are well known, an underappreciated limitation of mtDNA is geographically widespread introgression that homogenizes mtDNA diversity across species, subspecies, or population boundaries and across hundreds of kilometers. The resulting discordance between mtDNA and phenotype can be profound. If undetected, the setting of species limits and evolutionarily significant units are misled. An example shows how recent genomic analyses can detect and solve the problem. Other examples concern legacy mtDNA-only datasets. These are often essentially unfinished studies leaving residual uncertainty in species limits. Examples illustrate when the possibility of large-scale introgression across species boundaries needs to be considered, and how genomic scale data offer solutions. Researchers must carefully parse 3 questions: has there been introgression of mtDNA and, if so, which population genetics-based driver has caused introgression, and do species limits need altering? Understanding of allopatry, mtDNA introgression, recent speciation, and selection must be properly integrated if species limits are to be robustly understood and applied with maximum benefit in downstream applications such as conservation and management.

Genomic and anatomical comparisons of skin support independent adaptation to life in water by cetaceans and hippos

The macroevolutionary transition from terra firma to obligatory inhabitance of the marine hydrosphere has occurred twice in the history of Mammalia: Cetacea and Sirenia. In the case of Cetacea (whales, dolphins, and porpoises), molecular phylogenies provide unambiguous evidence that fully aquatic cetaceans and semiaquatic hippopotamids (hippos) are each other's closest living relatives. Ancestral reconstructions suggest that some adaptations to the aquatic realm evolved in the common ancestor of Cetancodonta (Cetacea+ Hippopotamidae). An alternative hypothesis is that these adaptations evolved independently in cetaceans and hippos. Here, we focus on the integumentary system and evaluate these hypotheses by integrating new histological data for cetaceans and hippos, the first genome-scale data for pygmy hippopotamus, and comprehensive genomic screens and molecular evolutionary analyses for protein-coding genes that have been inactivated in hippos and cetaceans. We identified eight skin-related genes that are inactivated in both cetaceans and hippos, including genes that are related to sebaceous glands, hair follicles, and epidermal differentiation. However, none of these genes exhibit inactivating mutations that are shared by cetaceans and hippos. Mean dates for the inactivation of skin genes in these two clades serve as proxies for phenotypic changes and suggest that hair reduction/loss, the loss of sebaceous glands, and changes to the keratinization program occurred ∼16 Ma earlier in cetaceans (∼46.5 Ma) than in hippos (∼30.5 Ma). These results, together with histological differences in the integument and prior analyses of oxygen isotopes from stem hippopotamids ("anthracotheres"), support the hypothesis that aquatic skin adaptations evolved independently in hippos and cetaceans.

Ultraconserved Elements Improve the Resolution of Difficult Nodes within the Rapid Radiation of Neotropical Sigmodontine Rodents (Cricetidae: Sigmodontinae).

Sigmodontine rodents (Cricetidae, Sigmodontinae) represent the second largest muroid subfamily and the most species-rich group of New World mammals, encompassing above 410 living species and ca. 87 genera. Even with advances on the clarification of sigmodontine phylogenetic relationships that have been made recently, the phylogenetic relationships among the 12 main groups of genera (i.e., tribes) remain poorly resolved, in particular among those forming the large clade Oryzomyalia. This pattern has been interpreted as consequence of a rapid radiation upon the group entrance into South America. Here, we attempted to resolve phylogenetic relationships within Sigmodontinae using target capture and high-throughput sequencing of ultraconserved elements (UCEs). We enriched and sequenced UCEs for 56 individuals and collected data from four already available genomes. Analyses of distinct data sets, based on the capture of 4634 loci, resulted in a highly resolved phylogeny consistent across different methods. Coalescent species-tree-based approaches, concatenated matrices, and Bayesian analyses recovered similar topologies that were congruent at the resolution of difficult nodes. We recovered good support for the intertribal relationships within Oryzomyalia; for instance, the tribe Oryzomyini appears as the sister taxa of the remaining oryzomyalid tribes. The estimates of divergence times agree with the results of previous studies. We inferred the crown age of the sigmodontine rodents at the end of the Middle Miocene, while the main lineages of Oryzomyalia appear to have radiated in a short interval during the Late Miocene. Thus, the collection of a genomic-scale data set with a wide taxonomic sampling provided resolution for the first time of the relationships among the main lineages of Sigmodontinae. We expect the phylogeny presented here will become the backbone for future systematic and evolutionary studies of the group.[Coalescent; Muroidea; Oryzomyalia; phylogenomics; polytomy; Rodentia; Sigmodontalia; species tree; UCEs.].

The Implications of Interrelated Assumptions on Estimates of Divergence Times and Rates of Diversification.

Phylogenies are increasingly being used as a basis to provide insight into macroevolutionary history. Here, we use simulation experiments and empirical analyses to evaluate methods that use phylogenies as a basis to make estimates of divergence times and rates of diversification. This is the first study to present a comprehensive assessment of the key variables that underpin analyses in this field-including substitution rates, speciation rates, and extinction, plus character sampling and taxon sampling. We show that in unrealistically simplistic cases (where substitution rates and speciation rates are constant, and where there is no extinction), increased character and taxon sampling lead to more accurate and precise parameter estimates. By contrast, in more complex but realistic cases (where substitution rates, speciation rates, and extinction rates vary), gains in accuracy and precision from increased character and taxon sampling are far more limited. The lack of accuracy and precision even occurs when using methods that are designed to account for more complex cases, such as relaxed clocks, fossil calibrations, and models that allow speciation rates and extinction rates to vary. The problem also persists when analyzing genomic scale data sets. These results suggest two interrelated problems that occur when the processes that generated the data are more complex. First, methodological assumptions are more likely to be violated. Second, limitations in the information content of the data become more important.[Divergence time estimation; diversification rates; macroevolution; phylogeny.].

Epigenetic Regulation of Claudin-1 in the Development of Ovarian Cancer Recurrence and Drug Resistance.

Over 21,000 women are diagnosed with ovarian cancer (OC) in the United States each year and over half that number succumb to this disease annually, often due to recurrent disease. A deeper understanding of the molecular events associated with recurrent disease is needed to identify potential targets. Using genome-scale DNA methylation and gene expression data for 16 matched primary-recurrent advanced stage serous epithelial OCs, we discovered that Claudin-1 (CLDN1), a tight junction protein, shows a stronger correlation between expression and methylation in recurrent versus primary OC at multiple CpG sites (R= –0.47 to −0.64 versus R= -0.32 to −0.57, respectively). An independent dataset showed that this correlation is stronger in tumors from short-term (<3y) survivors than in tumors from long-term (>7y) survivors (R= −0.41 to −0.46 versus R= 0.06 to −0.19, respectively). The presence of this inverse correlation in short-term survivors and recurrent tumors suggests an important role for this relationship and potential predictive value for disease prognosis. CLDN1 expression increased following pharmacologic inhibition of DNA methyltransferase activity (p< 0.001), thus validating the role of methylation in CLDN1 gene inhibition. CLDN1 knockdown enhanced chemosensitivity and suppressed cell proliferation, migration, and wound healing (p< 0.05). Stable CLDN1 knockdown in vivo resulted in reduced xenograft tumor growth but did not reach significance. Our results indicate that the relationship between CLDN1 methylation and expression plays an important role in OC aggressiveness and recurrence.

Resolving the Early Divergence Pattern of Teleost Fish Using Genome-Scale Data

Regarding the phylogenetic relationship of the three primary groups of teleost fishes, Osteoglossomorpha (bonytongues and others), Elopomorpha (eels and relatives), Clupeocephala (the remaining teleost fish), early morphological studies hypothesized the first divergence of Osteoglossomorpha, whereas the recent prevailing view is the first divergence of Elopomorpha. Molecular studies supported all the possible relationships of the three primary groups. This study analyzed genome-scale data from four previous studies: 1) 412 genes from 12 species, 2) 772 genes from 15 species, 3) 1,062 genes from 30 species, and 4) 491 UCE loci from 27 species. The effects of the species, loci, and models used on the constructed tree topologies were investigated. In the analyses of the data sets (1)–(3), although the first divergence of Clupeocephala that left the other two groups in a sister relationship was supported by concatenated sequences and gene trees of all the species and genes, the first divergence of Elopomorpha among the three groups was supported using species and/or genes with low divergence of sequence and amino-acid frequencies. This result corresponded to that of the UCE data set (4), whose sequence divergence was low, which supported the first divergence of Elopomorpha with high statistical significance. The increase in accuracy of the phylogenetic construction by using species and genes with low sequence divergence was predicted by a phylogenetic informativeness approach and confirmed by computer simulation. These results supported that Elopomorpha was the first basal group of teleost fish to have diverged, consistent with the prevailing view of recent morphological studies.

Resequencing of Microbial Isolates: A Lab Module to Introduce Novices to Command-Line Bioinformatics.

Familiarity with genome-scale data and the bioinformatic skills to analyze it have become essential for understanding and advancing modern biology and human health, yet many undergraduate biology majors are never exposed to hands-on bioinformatics. This paper presents a module that introduces students to applied bioinformatic analysis within the context of a research-based microbiology lab course. One of the most commonly used genomic analyses in biology is resequencing: determining the sequence of DNA bases in a derived strain of some organism, and comparing it to the known ancestral genome of that organism to better understand the phenotypic differences between them. Many existing CUREs — Course Based Undergraduate Research Experiences — evolve or select new strains of bacteria and compare them phenotypically to ancestral strains. This paper covers standardized strategies and procedures, accessible to undergraduates, for preparing and analyzing microbial whole-genome resequencing data to examine the genotypic differences between such strains. Wet-lab protocols and computational tutorials are provided, along with additional guidelines for educators, providing instructors without a next-generation sequencing or bioinformatics background the necessary information to incorporate whole-genome sequencing and command-line analysis into their class. This module introduces novice students to running software at the command-line, giving them exposure and familiarity with the types of tools that make up the vast majority of open-source scientific software used in contemporary biology. Completion of the module improves student attitudes toward computing, which may make them more likely to pursue further bioinformatics study.

Integrative transcription start site identification with iTiSS.

Many experimental approaches have been developed to identify transcription start sites (TSS) from genomic scale data. However, experiment specific biases lead to large numbers of false-positive calls. Here, we present our integrative approach iTiSS, which is an accurate and generic TSS caller for any TSS profiling experiment in eukaryotes, and substantially reduces the number of false positives by a joint analysis of several complementary datasets. iTiSS is platform independent and implemented in Java (v1.8) and is freely available at https://www.erhard-lab.de/software and https://github.com/erhard-lab/iTiSS. Supplementary data are available at Bioinformatics online.