Inferring Microbial Gene Family Evolution Using Duplication-Transfer-Loss Reconciliation: Algorithms and Complexity

Gene families evolve through complex evolutionary events such as speciation, gene duplication, horizontal gene transfer, gene loss, etc., and reconstructing these evolutionary histories is an important problem in evolutionary biology with many important applications. Duplication-Transfer-Loss (DTL) reconciliation is among the most effective and most popular methods for studying gene family evolution, especially in microbes. DTL reconciliation takes as input a gene tree and a species tree and reconciles the two by postulating gene duplication, transfer, and loss events, showing the evolution of that gene family inside the species tree. The DTL reconciliation problem has been extensively studied, but existing problem formulations and algorithms have several limitations that affect the accuracy and applicability of DTL reconciliation in practice. In this thesis, we focus on addressing two of the most important limitations. The first limitation is that existing algorithms assume a fixed, binary gene tree topology and therefore cannot account for uncertainty in gene tree topologies, a common occurrence in practice. The second limitation is that all transfer events are assumed to be “additive”, i.e., they introduce a new gene into the recipient genome. It is well known, however, that transfer events can also be “replacing”, i.e., they can replace an existing gene in the recipient genome. To address the first limitation, we devise an extension of DTL reconciliation to non-binary gene trees and show that the resulting problem is NP-hard. We then provide fixed parameter and other exact and heuristic algorithms for this problem, and demonstrate their impact in practice on real and simulated data. For the second limitation, we propose and develop a new extended reconciliation framework, called the DTRL reconciliation framework, which models both additive and replacing transfers, and show that the resulting computational problem is NP-hard

RANGER-DTL 2.0: rigorous reconstruction of gene-family evolution by duplication, transfer and loss

© The Author(s) 2018. Published by Oxford University Press. RANGER-DTL 2.0 is a software program for inferring gene family evolution using Duplication-Transfer-Loss reconciliation. This new software is highly scalable and easy to use, and offers many new features not currently available in any other reconciliation program. RANGER-DTL 2.0 has a particular focus on reconciliation accuracy and can account for many sources of reconciliation uncertainty including uncertain gene tree rooting, gene tree topological uncertainty, multiple optimal reconciliations and alternative event cost assignments. RANGER-DTL 2.0 is open-source and written in C++ and Python

RANGER-DTL 2.0: rigorous reconstruction of gene-family evolution by duplication, transfer and loss

© The Author(s) 2018. Published by Oxford University Press. RANGER-DTL 2.0 is a software program for inferring gene family evolution using Duplication-Transfer-Loss reconciliation. This new software is highly scalable and easy to use, and offers many new features not currently available in any other reconciliation program. RANGER-DTL 2.0 has a particular focus on reconciliation accuracy and can account for many sources of reconciliation uncertainty including uncertain gene tree rooting, gene tree topological uncertainty, multiple optimal reconciliations and alternative event cost assignments. RANGER-DTL 2.0 is open-source and written in C++ and Python

Multi-Faceted Attributes of Salivary Cell-free DNA as Liquid Biopsy Biomarkers for Gastric Cancer Detection

BACKGROUND: Recent advances in circulating cell-free DNA (cfDNA) analysis from biofluids have opened new avenues for liquid biopsy (LB). However, current cfDNA LB assays are limited by the availability of existing information on established genotypes associated with tumor tissues. Certain cancers present with a limited list of established mutated cfDNA biomarkers, and thus, nonmutated cfDNA characteristics along with alternative biofluids are needed to broaden the available cfDNA targets for cancer detection. Saliva is an intriguing and accessible biofluid that has yet to be fully explored for its clinical utility for cancer detection. METHODS: In this report, we employed a low-coverage single stranded (ss) library NGS pipeline "Broad-Range cell-free DNA-Seq" (BRcfDNA-Seq) using saliva to comprehensively investigate the characteristics of salivary cfDNA (ScfDNA). The identification of cfDNA features has been made possible by applying novel cfDNA processing techniques that permit the incorporation of ultrashort, ss, and jagged DNA fragments. As a proof of concept using 10 gastric cancer (GC) and 10 noncancer samples, we examined whether ScfDNA characteristics, including fragmentomics, end motif profiles, microbial contribution, and human chromosomal mapping, could differentiate between these two groups. RESULTS: Individual and integrative analysis of these ScfDNA features demonstrated significant differences between the two cohorts, suggesting that disease state may affect the ScfDNA population by altering nuclear cleavage or the profile of contributory organism cfDNA to total ScfDNA. We report that principal component analysis integration of several aspects of salivary cell-free DNA fragmentomic profiles, genomic element profiles, end-motif sequence patterns, and distinct oral microbiome populations can differentiate the two populations with a p value of < 0.0001 (PC1). CONCLUSION: These novel features of ScfDNA characteristics could be clinically useful for improving saliva-based LB detection and the eventual monitoring of local or systemic diseases

Correction: Multi-faceted attributes of salivary cell-free DNA as liquid biopsy biomarkers for gastric cancer detection

The original article [1] contains errors in the attributions for the following co-authors: David Chia, David Elashoff, Liying Zhang, and Sung Kim. The corrected affiliations can be viewed in the authorship list of this Correction article

Multi-faceted attributes of salivary cell-free DNA as liquid biopsy biomarkers for gastric cancer detection

BackgroundRecent advances in circulating cell-free DNA (cfDNA) analysis from biofluids have opened new avenues for liquid biopsy (LB). However, current cfDNA LB assays are limited by the availability of existing information on established genotypes associated with tumor tissues. Certain cancers present with a limited list of established mutated cfDNA biomarkers, and thus, nonmutated cfDNA characteristics along with alternative biofluids are needed to broaden the available cfDNA targets for cancer detection. Saliva is an intriguing and accessible biofluid that has yet to be fully explored for its clinical utility for cancer detection.MethodsIn this report, we employed a low-coverage single stranded (ss) library NGS pipeline "Broad-Range cell-free DNA-Seq" (BRcfDNA-Seq) using saliva to comprehensively investigate the characteristics of salivary cfDNA (ScfDNA). The identification of cfDNA features has been made possible by applying novel cfDNA processing techniques that permit the incorporation of ultrashort, ss, and jagged DNA fragments. As a proof of concept using 10 gastric cancer (GC) and 10 noncancer samples, we examined whether ScfDNA characteristics, including fragmentomics, end motif profiles, microbial contribution, and human chromosomal mapping, could differentiate between these two groups.ResultsIndividual and integrative analysis of these ScfDNA features demonstrated significant differences between the two cohorts, suggesting that disease state may affect the ScfDNA population by altering nuclear cleavage or the profile of contributory organism cfDNA to total ScfDNA. We report that principal component analysis integration of several aspects of salivary cell-free DNA fragmentomic profiles, genomic element profiles, end-motif sequence patterns, and distinct oral microbiome populations can differentiate the two populations with a p value of < 0.0001 (PC1).ConclusionThese novel features of ScfDNA characteristics could be clinically useful for improving saliva-based LB detection and the eventual monitoring of local or systemic diseases

Multi-faceted attributes of salivary cell-free DNA as liquid biopsy biomarkers for gastric cancer detection

Abstract Background Recent advances in circulating cell-free DNA (cfDNA) analysis from biofluids have opened new avenues for liquid biopsy (LB). However, current cfDNA LB assays are limited by the availability of existing information on established genotypes associated with tumor tissues. Certain cancers present with a limited list of established mutated cfDNA biomarkers, and thus, nonmutated cfDNA characteristics along with alternative biofluids are needed to broaden the available cfDNA targets for cancer detection. Saliva is an intriguing and accessible biofluid that has yet to be fully explored for its clinical utility for cancer detection. Methods In this report, we employed a low-coverage single stranded (ss) library NGS pipeline “Broad-Range cell-free DNA-Seq” (BRcfDNA-Seq) using saliva to comprehensively investigate the characteristics of salivary cfDNA (ScfDNA). The identification of cfDNA features has been made possible by applying novel cfDNA processing techniques that permit the incorporation of ultrashort, ss, and jagged DNA fragments. As a proof of concept using 10 gastric cancer (GC) and 10 noncancer samples, we examined whether ScfDNA characteristics, including fragmentomics, end motif profiles, microbial contribution, and human chromosomal mapping, could differentiate between these two groups. Results Individual and integrative analysis of these ScfDNA features demonstrated significant differences between the two cohorts, suggesting that disease state may affect the ScfDNA population by altering nuclear cleavage or the profile of contributory organism cfDNA to total ScfDNA. We report that principal component analysis integration of several aspects of salivary cell-free DNA fragmentomic profiles, genomic element profiles, end-motif sequence patterns, and distinct oral microbiome populations can differentiate the two populations with a p value of < 0.0001 (PC1). Conclusion These novel features of ScfDNA characteristics could be clinically useful for improving saliva-based LB detection and the eventual monitoring of local or systemic diseases

Single-stranded pre-methylated 5mC adapters uncover the methylation profile of plasma ultrashort Single-stranded cell-free DNA

Whole-genome bisulfite sequencing (BS-Seq) measures cytosine methylation changes at single-base resolution and can be used to profile cell-free DNA (cfDNA). In plasma, ultrashort single-stranded cfDNA (uscfDNA, ∼50 nt) has been identified together with 167 bp double-stranded mononucleosomal cell-free DNA (mncfDNA). However, the methylation profile of uscfDNA has not been described. Conventional BS-Seq workflows may not be helpful because bisulfite conversion degrades larger DNA into smaller fragments, leading to erroneous categorization as uscfDNA. We describe the '5mCAdpBS-Seq' workflow in which pre-methylated 5mC (5-methylcytosine) single-stranded adapters are ligated to heat-denatured cfDNA before bisulfite conversion. This method retains only DNA fragments that are unaltered by bisulfite treatment, resulting in less biased uscfDNA methylation analysis. Using 5mCAdpBS-Seq, uscfDNA had lower levels of DNA methylation (∼15%) compared to mncfDNA and was enriched in promoters and CpG islands. Hypomethylated uscfDNA fragments were enriched in upstream transcription start sites (TSSs), and the intensity of enrichment was correlated with expressed&nbsp;genes&nbsp;of hemopoietic cells. Using tissue-of-origin deconvolution, we inferred that uscfDNA is derived primarily from eosinophils, neutrophils, and monocytes. As proof-of-principle, we show that characteristics of the methylation profile of uscfDNA can distinguish non-small cell lung carcinoma from non-cancer samples. The 5mCAdpBS-Seq workflow is recommended for any cfDNA methylation-based investigations