BARD1 germline variants induce haploinsufficiency and DNA repair defects in neuroblastoma.

BACKGROUND: High-risk neuroblastoma is a complex genetic disease that is lethal in more than 50% of patients despite intense multimodal therapy. Through genome-wide association studies (GWAS) and next-generation sequencing, we have identified common single nucleotide polymorphisms and rare, pathogenic or likely pathogenic germline loss-of-function variants in BARD1 enriched in neuroblastoma patients. The functional implications of these findings remain poorly understood. METHODS: We correlated BARD1 genotype with expression in normal tissues and neuroblastomas, along with the burden of DNA damage in tumors. To validate the functional consequences of germline pathogenic or likely pathogenic BARD1 variants, we used CRISPR-Cas9 to generate isogenic neuroblastoma (IMR-5) and control (RPE1) cellular models harboring heterozygous BARD1 loss-of-function variants (R112*, R150*, E287fs, and Q564*) and quantified genomic instability in these cells via next-generation sequencing and with functional assays measuring the efficiency of DNA repair. RESULTS: Both common and rare neuroblastoma-associated BARD1 germline variants were associated with lower levels of BARD1 mRNA and an increased burden of DNA damage. Using isogenic heterozygous BARD1 loss-of-function variant cellular models, we functionally validated this association with inefficient DNA repair. BARD1 loss-of-function variant isogenic cells exhibited reduced efficiency in repairing Cas9-induced DNA damage, ineffective RAD51 focus formation at DNA double-strand break sites, and enhanced sensitivity to cisplatin and poly (ADP-ribose) polymerase (PARP) inhibition both in vitro and in vivo. CONCLUSIONS: Taken together, we demonstrate that germline BARD1 variants disrupt DNA repair fidelity. This is a fundamental molecular mechanism contributing to neuroblastoma initiation that may have important therapeutic implications.

SHP2 Inhibition with TNO155 Increases Efficacy and Overcomes Resistance of ALK Inhibitors in Neuroblastoma.

Survival rates among patients with high-risk neuroblastoma remain low and novel therapies for recurrent neuroblastomas are required. ALK is commonly mutated in primary and relapsed neuroblastoma tumors and ALK tyrosine kinase inhibitors (TKI) are promising treatments for ALK-driven neuroblastoma; however, innate or adaptive resistance to single-agent ALK-TKIs remain a clinical challenge. Recently, SHP2 inhibitors have been shown to overcome ALK-TKI resistance in lung tumors harboring ALK rearrangements. Here, we have assessed the efficacy of the SHP2 inhibitor TNO155 alone and in combination with the ALK-TKIs crizotinib, ceritinib, or lorlatinib for the treatment of ALK-driven neuroblastoma using in vitro and in vivo models. In comparison to wild-type, ALK-mutant neuroblastoma cell lines were more sensitive to SHP2 inhibition with TNO155. Moreover, treatment with TNO155 and ALK-TKIs synergistically reduced cell growth and promoted inactivation of ALK and MAPK signaling in ALK-mutant neuroblastoma cells. ALK-mutant cells engrafted into larval zebrafish and treated with single agents or dual SHP2/ALK inhibitors showed reduced growth and invasion. In murine ALK-mutant xenografts, tumor growth was likewise reduced or delayed, and survival was prolonged upon combinatorial treatment of TNO155 and lorlatinib. Finally, we show that lorlatinib-resistant ALK-F1174L neuroblastoma cells harbor additional RAS-MAPK pathway alterations and can be resensitized to lorlatinib when combined with TNO155 in vitro and in vivo. Our results report the first evaluation of TNO155 in neuroblastoma and suggest that combinatorial inhibition of ALK and SHP2 could be a novel approach to treating ALK-driven neuroblastoma, potentially including the increasingly common tumors that have developed resistance to ALK-TKIs. SIGNIFICANCE: These findings highlight the translatability between zebrafish and murine models, provide evidence of aberrant RAS-MAPK signaling as an adaptive mechanism of resistance to lorlatinib, and demonstrate the clinical potential for SHP2/ALK inhibitor combinations for the treatment of ALK-mutant neuroblastoma, including those with acquired tolerance or potentially resistance to ALK-TKIs.

BARD1 germline variants induce haploinsufficiency and DNA repair defects in neuroblastoma.

Importance: High-risk neuroblastoma is a complex genetic disease that is lethal in 50% of patients despite intense multimodal therapy. Our genome-wide association study (GWAS) identified single-nucleotide polymorphisms (SNPs) within the BARD1 gene showing the most significant enrichment in neuroblastoma patients, and also discovered pathogenic (P) or likely pathogenic (LP) rare germline loss-of-function variants in this gene. The functional implications of these findings remain poorly understood. Objective: To define the functional relevance of BARD1 germline variation in children with neuroblastoma. Design: We correlated BARD1 genotype with BARD1 expression in normal and tumor cells and the cellular burden of DNA damage in tumors. To validate the functional consequences of rare germline P-LP BARD1 variants, we generated isogenic cellular models harboring heterozygous BARD1 loss-of-function (LOF) variants and conducted multiple complementary assays to measure the efficiency of DNA repair. Setting: (N/A). Participants: (N/A). Interventions/Exposures: (N/A). Main Outcomes and Measures: BARD1 expression, efficiency of DNA repair, and genome-wide burden of DNA damage in neuroblastoma tumors and cellular models harboring disease-associated BARD1 germline variants. Results: Both common and rare neuroblastoma associated BARD1 germline variants were significantly associated with lower levels of BARD1 mRNA and an increased burden of DNA damage. Using neuroblastoma cellular models engineered to harbor disease-associated heterozygous BARD1 LOF variants, we functionally validated this association with inefficient DNA repair. These BARD1 LOF variant isogenic models exhibited reduced efficiency in repairing Cas9-induced DNA damage, ineffective RAD51 focus formation at DNA doublestrand break sites, and enhanced sensitivity to cisplatin and poly-ADP ribose polymerase (PARP) inhibition. Conclusions and Relevance: Considering that at least 1 in 10 children diagnosed with cancer carry a predicted pathogenic mutation in a cancer predisposition gene, it is critically important to understand their functional relevance. Here, we demonstrate that germline BARD1 variants disrupt DNA repair fidelity. This is a fundamental molecular mechanism contributing to neuroblastoma initiation that may have important therapeutic implications, and these findings may also extend to other cancers harboring germline variants in genes essential for DNA damage repair. Key Points: Question: How do neuroblastoma patient BRCA1-associated RING domain 1 ( BARD1 ) germline variants impact DNA repair? Findings: Neuroblastoma-associated germline BARD1 variants disrupt DNA repair fidelity. Common risk variants correlate with decreased BARD1 expression and increased DNA double-strand breaks in neuroblastoma tumors and rare heterozygous loss-of-function variants induce BARD1 haploinsufficiency, resulting in defective DNA repair and genomic instability in neuroblastoma cellular models. Meaning: Germline variation in BARD1 contributes to neuroblastoma pathogenesis via dysregulation of critical cellular DNA repair functions, with implications for neuroblastoma treatment, risk stratification, and cancer predisposition.

Germline TP53 mutations undergo copy number gain years prior to tumor diagnosis.

Li-Fraumeni syndrome (LFS) is a hereditary cancer predisposition syndrome associated with germline TP53 pathogenic variants. Here, we perform whole-genome sequence (WGS) analysis of tumors from 22 patients with TP53 germline pathogenic variants. We observe somatic mutations affecting Wnt, PI3K/AKT signaling, epigenetic modifiers and homologous recombination genes as well as mutational signatures associated with prior chemotherapy. We identify near-ubiquitous early loss of heterozygosity of TP53, with gain of the mutant allele. This occurs earlier in these tumors compared to tumors with somatic TP53 mutations, suggesting the timing of this mark may distinguish germline from somatic TP53 mutations. Phylogenetic trees of tumor evolution, reconstructed from bulk and multi-region WGS, reveal that LFS tumors exhibit comparatively limited heterogeneity. Overall, our study delineates early copy number gains of mutant TP53 as a characteristic mutational process in LFS tumorigenesis, likely arising years prior to tumor diagnosis.

The clinical utility of integrative genomics in childhood cancer extends beyond targetable mutations.

We conducted integrative somatic-germline analyses by deeply sequencing 864 cancer-associated genes, complete genomes and transcriptomes for 300 mostly previously treated children and adolescents/young adults with cancer of poor prognosis or with rare tumors enrolled in the SickKids Cancer Sequencing (KiCS) program. Clinically actionable variants were identified in 56% of patients. Improved diagnostic accuracy led to modified management in a subset. Therapeutically targetable variants (54% of patients) were of unanticipated timing and type, with over 20% derived from the germline. Corroborating mutational signatures (SBS3/BRCAness) in patients with germline homologous recombination defects demonstrates the potential utility of PARP inhibitors. Mutational burden was significantly elevated in 9% of patients. Sequential sampling identified changes in therapeutically targetable drivers in over one-third of patients, suggesting benefit from rebiopsy for genomic analysis at the time of relapse. Comprehensive cancer genomic profiling is useful at multiple points in the care trajectory for children and adolescents/young adults with cancer, supporting its integration into early clinical management.

Association of presurgical circulating MicroRNAs with 1-year postsurgical pain reduction in spine facet osteoarthritis patients with lumbar spinal stenosis.

Purpose: Up to 30% of spine facet osteoarthritis patients with lumbar spinal stenosis (SF-OA â€‹+ â€‹LSS) have little to no improvement in their pain after surgery. Lack of meaningful improvement in pain following surgery provides a unique opportunity to identify specific predictive biomarker signatures that might be associated with the outcomes of surgical treatment. The objective of the present study was to determine whether a microRNA (miRNA) biomarker signature could be identified in presurgical blood plasma that corresponded with levels of SF-OA â€‹+ â€‹LSS patient post-surgical pain intensity one year later. Methods: RNA was extracted from baseline plasma of SF-OA â€‹+ â€‹LSS patients and prepared for miRNA sequencing. Statistical approaches were performed to identify differentially expressed miRNAs associated with reduced 1-year postsurgical pain (n â€‹= â€‹56). Using an integrated computational approach, we further created predicted gene and pathway networks for each identified miRNA. Results: We identified a panel of 4 circulating candidate miRNAs (hsa-miR-155-5p, hsa-let-7e-5p, hsa-miR-125a-5p, hsa-miR-99b-5p) with higher levels at presurgical baseline that were associated with greater changes in % NPRS20Δ, reflecting reduced pain intensity levels at one year. Genes encoding hsa-let-7e-5p, hsa-miR-125a-5p, and hsa-miR-99b-5p are part of an evolutionarily conserved miRNA cluster. Using integrated computational analyses, we showed that mammalian target of rapamycin, transforming growth factor-ß1 receptor, Wnt signaling, epithelial-mesenchymal transition regulators, and cholecystokinin signaling were enriched pathways of predicted gene targets. Conclusions: Taken together, our findings suggest that 4 presurgical baseline circulating miRNAs correlate with 1-year postsurgical SF-OA â€‹+ â€‹LSS patient pain intensity and represent possible candidate biomarker signature of surgical pain response.

Identification of a differential metabolite-based signature in patients with late-stage knee osteoarthritis.

Objective: Multiple disease phenotypes have been identified in knee osteoarthritis (OA) patients based on anthropometric, sociodemographic and clinical factors; however, differential systemic metabolite-based signatures in OA patients are not well understood. We sought to identify differential plasma metabolome signatures in a cross-sectional sample of late-stage knee OA patients. Methods: Plasma from 214 (56.5% female; mean age â€‹= â€‹67.58 years) non-diabetic, non-obese (BMI <30 â€‹kg/m2, mean â€‹= â€‹26.25 â€‹kg/m2), radiographic KL 3/4 primary knee OA patients was analyzed by metabolomics. Patients with post-traumatic OA and rheumatoid arthritis were excluded. Hierarchical clustering was used to identify patient clusters based on metabolite levels. A refined metabolite signature differentiating patient clusters was determined based on ≥ 10% difference, significance by FDR-adjusted t-test (q-value < 0.05), and random forests importance score ≥1, and analyzed by AUROC. Bioinformatics analysis was used to identify genes linked to ≥2 annotated metabolites. Associated enriched pathways (q â€‹< â€‹0.05) were determined. Results: Two patient clusters were determined based on the levels of 151 metabolites identified. Metabolite signature refinement found 24 metabolites could accurately predict cluster classification within the sample (AUC â€‹= â€‹0.921). Fifty-six genes were linked to at least 2 â€‹KEGG annotated metabolites. Pathway analysis found 26/56 genes were linked to enriched pathways including tRNA acylation and B-vitamin metabolism. Conclusion: This study demonstrates systemic metabolites can classify a cross-sectional cohort of OA patients into distinct clusters. Links between metabolites, genes and pathways can help determine biological differences between OA patients, potentially improving precision medicine and decision-making.

Lineage-defined leiomyosarcoma subtypes emerge years before diagnosis and determine patient survival.

Leiomyosarcomas (LMS) are genetically heterogeneous tumors differentiating along smooth muscle lines. Currently, LMS treatment is not informed by molecular subtyping and is associated with highly variable survival. While disease site continues to dictate clinical management, the contribution of genetic factors to LMS subtype, origins, and timing are unknown. Here we analyze 70 genomes and 130 transcriptomes of LMS, including multiple tumor regions and paired metastases. Molecular profiling highlight the very early origins of LMS. We uncover three specific subtypes of LMS that likely develop from distinct lineages of smooth muscle cells. Of these, dedifferentiated LMS with high immune infiltration and tumors primarily of gynecological origin harbor genomic dystrophin deletions and/or loss of dystrophin expression, acquire the highest burden of genomic mutation, and are associated with worse survival. Homologous recombination defects lead to genome-wide mutational signatures, and a corresponding sensitivity to PARP trappers and other DNA damage response inhibitors, suggesting a promising therapeutic strategy for LMS. Finally, by phylogenetic reconstruction, we present evidence that clones seeding lethal metastases arise decades prior to LMS diagnosis.

A slipped-CAG DNA-binding small molecule induces trinucleotide-repeat contractions in vivo.

In many repeat diseases, such as Huntington's disease (HD), ongoing repeat expansions in affected tissues contribute to disease onset, progression and severity. Inducing contractions of expanded repeats by exogenous agents is not yet possible. Traditional approaches would target proteins driving repeat mutations. Here we report a compound, naphthyridine-azaquinolone (NA), that specifically binds slipped-CAG DNA intermediates of expansion mutations, a previously unsuspected target. NA efficiently induces repeat contractions in HD patient cells as well as en masse contractions in medium spiny neurons of HD mouse striatum. Contractions are specific for the expanded allele, independently of DNA replication, require transcription across the coding CTG strand and arise by blocking repair of CAG slip-outs. NA-induced contractions depend on active expansions driven by MutSß. NA injections in HD mouse striatum reduce mutant HTT protein aggregates, a biomarker of HD pathogenesis and severity. Repeat-structure-specific DNA ligands are a novel avenue to contract expanded repeats.

Microbiome networks and change-point analysis reveal key community changes associated with cystic fibrosis pulmonary exacerbations.

Over 90% of cystic fibrosis (CF) patients die due to chronic lung infections leading to respiratory failure. The decline in CF lung function is greatly accelerated by intermittent and progressively severe acute pulmonary exacerbations (PEs). Despite their clinical impact, surprisingly few microbiological signals associated with PEs have been identified. Here we introduce an unsupervised, systems-oriented approach to identify key members of the microbiota. We used two CF sputum microbiome data sets that were longitudinally collected through periods spanning baseline health and PEs. Key taxa were defined based on three strategies: overall relative abundance, prevalence, and co-occurrence network interconnectedness. We measured the association between changes in the abundance of the key taxa and changes in patient clinical status over time via change-point detection, and found that taxa with the highest level of network interconnectedness tracked changes in patient health significantly better than taxa with the highest abundance or prevalence. We also cross-sectionally stratified all samples into the clinical states and identified key taxa associated with each state. We found that network interconnectedness most strongly delineated the taxa among clinical states, and that anaerobic bacteria were over-represented during PEs. Many of these anaerobes are oropharyngeal bacteria that have been previously isolated from the respiratory tract, and/or have been studied for their role in CF. The observed shift in community structure, and the association of anaerobic taxa and PEs lends further support to the growing consensus that anoxic conditions and the subsequent growth of anaerobic microbes are important predictors of PEs.

Constructing and Analyzing Microbiome Networks in R.

Microbiomes are complex microbial communities whose structure and function are heavily influenced by microbe-microbe and microbe-host interactions mediated by a range of mechanisms, all of which have been implicated in the modulation of disease progression and clinical outcome. Therefore, understanding the microbiome as a whole, including both the complex interplay among microbial taxa and interactions with their hosts, is essential for understanding the spectrum of roles played by microbiomes in host health, development, dysbiosis, and polymicrobial infections. Network theory, in the form of systems-oriented, graph-theoretical approaches, is an exciting holistic methodology that can facilitate microbiome analysis and enhance our understanding of the complex ecological and evolutionary processes involved. Using network theory, one can model and analyze a microbiome and all its complex interactions in a single network. Here, we describe in detail and step by step, the process of building, analyzing and visualizing microbiome networks from operational taxonomic unit (OTU) tables in R and RStudio, using several different approaches and extensively commented code snippets.

Rearrangement bursts generate canonical gene fusions in bone and soft tissue tumors.

Sarcomas are cancers of the bone and soft tissue often defined by gene fusions. Ewing sarcoma involves fusions between EWSR1, a gene encoding an RNA binding protein, and E26 transformation-specific (ETS) transcription factors. We explored how and when EWSR1-ETS fusions arise by studying the whole genomes of Ewing sarcomas. In 52 of 124 (42%) of tumors, the fusion gene arises by a sudden burst of complex, loop-like rearrangements, a process called chromoplexy, rather than by simple reciprocal translocations. These loops always contained the disease-defining fusion at the center, but they disrupted multiple additional genes. The loops occurred preferentially in early replicating and transcriptionally active genomic regions. Similar loops forming canonical fusions were found in three other sarcoma types. Chromoplexy-generated fusions appear to be associated with an aggressive form of Ewing sarcoma. These loops arise early, giving rise to both primary and relapse Ewing sarcoma tumors, which can continue to evolve in parallel.

Publisher Correction: An extracellular network of Arabidopsis leucine-rich repeat receptor kinases.

In this Letter, an incorrect version of the Supplementary Information file was inadvertently used, which contained several errors. The details of references 59-65 were missing from the end of the Supplementary Discussion section on page 4. In addition, the section 'Text 3. Y2H on ICD interactions' incorrectly referred to 'Extended Data Fig. 4d' instead of 'Extended Data Fig. 3d' on page 3. Finally, the section 'Text 4. Interaction network analysis' incorrectly referred to 'Fig. 1b and Extended Data Fig. 6' instead of 'Fig. 2b and Extended Data Fig. 7' on page 3. These errors have all been corrected in the Supplementary Information.

Epidemiology of Clonal Pseudomonas aeruginosa Infection in a Canadian Cystic Fibrosis Population.

RATIONALE: The extent of the genetic relatedness among Pseudomonas aeruginosa isolates and its impact on clinical outcomes in the cystic fibrosis (CF) population is poorly understood. OBJECTIVES: The objectives of this study were to determine the prevalence of clonal P. aeruginosa infection in Canada and to associate P. aeruginosa genotypes with clinical outcomes. METHODS: This was an observational study of adult and pediatric patients with CF across Canada. Isolates were typed using multilocus sequence typing. A clone was defined as sharing at least six of seven alleles. Genotyping results were associated with clinical outcomes, including forced expiratory volume in 1 second, body mass index, rate of pulmonary exacerbation, and death/transplant. RESULTS: A total of 1,537 P. aeruginosa isolates were genotyped to 403 unique sequence types (STs) in 402 individuals with CF. Although 39% of STs were shared, most were shared only among a small number of subjects, and the majority (79%) of the genetic diversity in P. aeruginosa isolates was observed between patients. There were no significant differences in clinical outcomes according to genotype. However, patients with a dynamic, changing ST infection pattern had both a steeper decline in forced expiratory volume in 1 second (-2.9% predicted change/yr, 95% confidence interval [CI] = -3.8 to -1.9 compared with 0.4, 95% CI = -0.3 to 1.0; P < 0.001) and body mass index (-1.0 percentile change/yr, 95% CI = -1.6 to -0.3 compared with -0.1, 95% CI = -0.7 to 0.5; P = 0.047) than those with a stable infection with the same ST. CONCLUSIONS: There was no widespread sharing of dominant clones in our CF population, and the majority of the genetic diversity in P. aeruginosa was observed between patients. Changing genotypes over time within an individual was associated with worse clinical outcomes.

An extracellular network of Arabidopsis leucine-rich repeat receptor kinases.

The cells of multicellular organisms receive extracellular signals using surface receptors. The extracellular domains (ECDs) of cell surface receptors function as interaction platforms, and as regulatory modules of receptor activation. Understanding how interactions between ECDs produce signal-competent receptor complexes is challenging because of their low biochemical tractability. In plants, the discovery of ECD interactions is complicated by the massive expansion of receptor families, which creates tremendous potential for changeover in receptor interactions. The largest of these families in Arabidopsis thaliana consists of 225 evolutionarily related leucine-rich repeat receptor kinases (LRR-RKs), which function in the sensing of microorganisms, cell expansion, stomata development and stem-cell maintenance. Although the principles that govern LRR-RK signalling activation are emerging, the systems-level organization of this family of proteins is unknown. Here, to address this, we investigated 40,000 potential ECD interactions using a sensitized high-throughput interaction assay, and produced an LRR-based cell surface interaction network (CSILRR) that consists of 567 interactions. To demonstrate the power of CSILRR for detecting biologically relevant interactions, we predicted and validated the functions of uncharacterized LRR-RKs in plant growth and immunity. In addition, we show that CSILRR operates as a unified regulatory network in which the LRR-RKs most crucial for its overall structure are required to prevent the aberrant signalling of receptors that are several network-steps away. Thus, plants have evolved LRR-RK networks to process extracellular signals into carefully balanced responses.

Disentangling Interactions in the Microbiome: A Network Perspective.

Microbiota are now widely recognized as being central players in the health of all organisms and ecosystems, and subsequently have been the subject of intense study. However, analyzing and converting microbiome data into meaningful biological insights remain very challenging. In this review, we highlight recent advances in network theory and their applicability to microbiome research. We discuss emerging graph theoretical concepts and approaches used in other research disciplines and demonstrate how they are well suited for enhancing our understanding of the higher-order interactions that occur within microbiomes. Network-based analytical approaches have the potential to help disentangle complex polymicrobial and microbe-host interactions, and thereby further the applicability of microbiome research to personalized medicine, public health, environmental and industrial applications, and agriculture.

Seasonal community succession of the phyllosphere microbiome.

The leaf microbiome is influenced by both biotic and abiotic factors. Currently, we know little about the relative importance of these factors in determining microbiota composition and dynamics. To explore this issue, we collected weekly leaf samples over a 98-day growing season from multiple cultivars of common bean, soybean, and canola planted at three locations in Ontario, Canada, and performed Illumina-based microbiome analysis. We find that the leaf microbiota at the beginning of the season is very strongly influenced by the soil microbiota but, as the season progresses, it differentiates, becomes significantly less diverse, and transitions to having a greater proportion of leaf-specific taxa that are shared among all samples. A phylogenetic investigation of communities by reconstruction of unobserved states imputation of microbiome function inferred from the taxonomic data found significant differences between the soil and leaf microbiome, with a significant enrichment of motility gene categories in the former and metabolic gene categories in the latter. A network co-occurrence analysis identified two highly connected clusters as well as subclusters of putative pathogens and growth-promoting bacteria. These data reveal some of the complex ecological dynamics that occur in microbial communities over the course of a growing season and highlight the importance of community succession.

Inferring explicit weighted consensus networks to represent alternative evolutionary histories.

BACKGROUND: The advent of molecular biology techniques and constant increase in availability of genetic material have triggered the development of many phylogenetic tree inference methods. However, several reticulate evolution processes, such as horizontal gene transfer and hybridization, have been shown to blur the species evolutionary history by causing discordance among phylogenies inferred from different genes. METHODS: To tackle this problem, we hereby describe a new method for inferring and representing alternative (reticulate) evolutionary histories of species as an explicit weighted consensus network which can be constructed from a collection of gene trees with or without prior knowledge of the species phylogeny. RESULTS: We provide a way of building a weighted phylogenetic network for each of the following reticulation mechanisms: diploid hybridization, intragenic recombination and complete or partial horizontal gene transfer. We successfully tested our method on some synthetic and real datasets to infer the above-mentioned evolutionary events which may have influenced the evolution of many species. CONCLUSIONS: Our weighted consensus network inference method allows one to infer, visualize and validate statistically major conflicting signals induced by the mechanisms of reticulate evolution. The results provided by the new method can be used to represent the inferred conflicting signals by means of explicit and easy-to-interpret phylogenetic networks.

Using directed phylogenetic networks to retrace species dispersal history.

Methods designed for inferring phylogenetic trees have been widely applied to reconstruct biogeographic history. Because traditional phylogenetic methods used in biogeographic reconstruction are based on trees rather than networks, they follow the strict assumption in which dispersal among geographical units have occurred on the basis of single dispersal routes across regions and are, therefore, incapable of modelling multiple alternative dispersal scenarios. The goal of this study is to describe a new method that allows for retracing species dispersal by means of directed phylogenetic networks obtained using a horizontal gene transfer (HGT) detection method as well as to draw parallels between the processes of HGT and biogeographic reconstruction. In our case study, we reconstructed the biogeographic history of the postglacial dispersal of freshwater fishes in the Ontario province of Canada. This case study demonstrated the utility and robustness of the new method, indicating that the most important events were south-to-north dispersal patterns, as one would expect, with secondary faunal interchange among regions. Finally, we showed how our method can be used to explore additional questions regarding the commonalities in dispersal history patterns and phylogenetic similarities among species.

Evolutionary mechanisms underlying the functional divergence of duplicate genes involved in vertebrates' circadian rhythm pathway.

Circadian rhythms, that are governed physiologically and behaviorally by endogenous clock, have been described in many species. Living organisms use this endogenous circadian clock to anticipate environmental transitions, perform activities at biologically advantageous times during the day, and undergo characteristic seasonal responses. Gene duplication is one of the most important mechanisms in the evolution of gene diversity. After duplication, one or both of duplicates can accumulate amino acid changes, thereby promoting functional divergence through the action of natural selection. The circadian system, like many other multigene families, has undergone this genetic revolution, and so circadian genes that are found in single copies in insects are duplicated in vertebrates. We analyzed six groups of genes involved in vertebrates' circadian rhythm pathway to find signatures of molecular evolutionary processes such as gene duplication, natural selection, recombination, and functional divergence. The obtained results, then, were used to determine what evolutionary forces have influenced the fates of duplicated genes of each group. We showed in this research that recombination has not been widespread during the evolution of circadian genes and that purifying selection has been the prominent natural pressure operating on circadian genes. We also showed that the evolution of circadian genes has been depended on gene duplication and functional divergence. Finally, we put forward models best describing the evolutionary fates of circadian duplicates.