바이오인포매틱스 프로그램을 이용한 유전자 마커 선별 및 계통수 오류 평가 연구

학위논문(석사) -- 서울대학교대학원 : 자연과학대학 협동과정 생물정보학전공, 2021.8. 손현석.지속적으로 산출되는 엄청난 양의 생물학적 서열 데이터는 유기체 사이의 진화적 역사와 계통학적 관계(phylogenetic relationship)를 유추할 수 있는 기회를 제공한다. 이제 계통수 구축은 거의 모든 생물학 연구에서 수행되는 과정의 하나가 되었다. 여기서 계통정보학(phyloinformatics)은 계통수 생성 알고리즘과 진화적 모델 개발과 같은 기술적 또는 방법론적 연구를 중심으로 발전되어 왔다. 현재의 계통수 분석은 서열 데이터, 즉 유전적 마커를 이용하여 계통수를 생성함으로써 실제에 가까운 계통수를 추론하는 것을 목표로 한다. 그러나 유전적 마커를 비롯한 데이터의 크기가 기하급수적으로 증가하고 따라오는 계통수 분석의 정확성에 대한 의문이 점차 중요하게 다루어 지기 시작하면서 계통수의 정확성 및 신뢰성을 평가하기 위한 연구가 다수 이루어지고 있는 상황이다. 분자 시스템학 관점에서 계통수에 대한 정확성 평가는 두 가지 갈래로 나누어 접근할 수 있는데, 하나는 진화 조건, 분자데이터의 양과 같은 특정 환경 아래에서 계통 분석 알고리즘이 얼마나 잘 작동하는지를 다루는 것이고, 또 다른 하나는 특정 계통수를 얼마나 신뢰할 수 있는지에 집중하는 것이다. 그리고 데이터셋의 퀄리티 관점에서 신뢰할 만한 계통수를 획득하기 위해 계통수 분석을 수행한 후, 사용한 데이터셋과의 적절성을 평가하는 것도 중요하다. 대규모 데이터를 기본으로 취급하는 최근 계통수 분석에서 확률론적 오류의 가능성은 낮아졌지만, 시스템 오류의 가능성은 오히려 높아졌으므로, 계통수 정확성을 평가 및 개선하기 위해 계통 분석 결과 후에 데이터셋이 가지는 시스템 오류의 근원을 평가하는 것이 매우 중요한 과정이 되었기 때문이다. 이에 본 연구에서는 데이터 퀄리티 관점에서 계통수의 신뢰도 향상을 가져오기 위해 APSE (Assessment Program for Systematic Error, tentative)라는 프로그램을 개발하였다. APSE를 활용하면 분류군 특이적 상대적 구성 빈도 변이(RCFV)와 대칭적 왜곡값(skew)을 산출하여 염기서열의 구성적 편향성에 대한 정보를 얻고, 이를 통해 연구하고자 하는 데이터의 유전적 이질성(heterogeneity) 및 유전적 변이 편향성(mutational bias)을 추정할 수 있다. 뿐만 아니라 다양한 염기 그룹의 빈도, 변이에 의한 다수 치환을 의미하는 포화(saturation)와 공유 결측 데이터(shared missing data) 변수를 통해 시스템 오류를 유발할 수 있는 편향성 정보들을 계산하는 것이 가능하다. 또한, 시스템 성능을 평가하기 위해 다양한 유전자 마커 사이의 모순되는 계통수를 출력하고 있는, 특이적 예시(Terebelliformia, Daphniid, Glires)를 APSE에 적용하여 마커 데이터셋의 시스템 오류 평가와 그에 따라 선별된 마커 계통수의 정확성 추론에 대한 분석이 제대로 수행될 수 있음을 확인하였다. 따라서 향후 APSE는 시스템학적 관점에서 데이터 퀄리티에 집중하여 생성된 계통수가 보다 정확한 결과를 이끌어낼 수 있도록 사용자의 데이터와 계통수 사이의 정확성을 평가하는 역할을 할 것이고, 유전적 마커에 따라 오해의 소지가 있는 계통수가 출력되었을 때, 시스템 오류의 근원에 대한 철저한 분석과 해당 오류의 영향을 받은 데이터가 계통수에 주는 효과를 파악하는 일을 수행할 수 있을 것이라 기대한다.The steadily increasing volume of biological data with decisive phylogenetic relationship provides unparalleled opportunities in bioinformatics. Phylogenetics based on a large amount of datasets handling an evolutionary history and assigning the placement of taxa in a phylogeny establishes the tree of life. Constructing a phylogeny involving a phylogenetic analysis is implemented in most branches of biology and emphasizing the evolutionary history elucidates the phylogenetical background as a prerequisite interpreting a specific biological system, which is a biologically indispensable process. Due to the advent of computing and sequencing techniques as the phylogenetic approach, phyloinformatics has rapidly advanced at the technical and methodological levels along with phylogenetic reconstruction algorithm and evolutionary models. Unlike the classic approach using morphological data, modern phylogenetic analysis reconstructs a phylogeny using genetic information following the inference of phylogenetic tree from molecular data. Therefore, phylogeneticists have naturally dealt with questions concerning the accuracy of phylogenetic estimation and carried out studies on the reliability of phylogenies. In terms of molecular systematics, the concerns regarding the assessment of phylogenetic accuracy considering specific evolutionary conditions and the amount of molecular data implemented can now be divided into two types: how phylogenetic method works and how reliable it is under certain circumstances. Moreover, in terms of data quality, assessment for suitability of nuclear marker is required before the phylogenetic inference is performed for confident phylogeny. Recently, the probability of stochastic errors in phylogenetic estimation dealing with a large-scale datasets has decreased, while the probability of systematic errors has increased. Thus, before the implementation of phylogenetic reconstruction, the assessment of sources of systematic errors is indispensable for the improvement and estimation of phylogenetic accuracy. Assessment Program for Systematic Error (APSE) developed by this study will plays a key role in assessment between user datasets and phylogenies for improving the results of phylogenetic reconstruction in systematics and will be able to implement an analysis of the effect on data bearing systematic errors in a phylogeny after the misleading phylogenetic results are produced. This study with APSE will serve as the inference of phylogenetic accuracy and the assessment of systematic errors using an unresolved example showing the contradicting topologies between different gene markers in the same diversity group. Furthermore, by selectively grouping the properties of the existing systematic biases provided by the APSE, it proceeds in the direction of proposing a new protocol that can provide the best gene marker among candidate markers for a specific taxon.I. INTRODUCTION 1 1.1 Background of research 1 1.2 Necessity of research 20 1.3 Research objectives 22 II. MATERIALS AND METHODS 30 2.1 Datasets definition and data collection 30 2.2 Data processing and bioinformatics software used 33 2.3 Phylogenetic reconstruction and accuracy assessment 36 2.4 Software development environment and allowable data 37 2.5 Assessment of the systematic errors 38 III. RESULTS 45 3.1 Phylogenetic analysis results for incongruence between gene markers 45 3.2 Data-quality analysis using systematic errors 49 IV. DISCUSSION 79 4.1 Significance and implications of study 79 4.2 Application to bioinformatics research 80 4.3 Improvement and achievement 81 V. CONCLUSION AND SUMMARY 83 5.1 Conclusion 83 5.2 Summary 84 BIBLIOGRAPHY 87 ABSTRACT (KOREAN) 96석

Resolving tricky nodes in the tree of life through amino acid recoding

Genomic data allowed a detailed resolution of the Tree of Life, but ''tricky nodes'' such as the root of the animals remain unresolved. Genome-scale datasets are heterogeneous as genes and species are exposed to different pressures, and this can negatively impacts phylogenetic accuracy. We use simulated genomic- scale datasets and show that recoding amino acid data improves accuracy when the model does not account for the compositional heterogeneity of the amino acid alignment. We apply our findings to three datasets addressing the root of the animal tree, where the debate centers on whether sponges (Porifera) or comb jellies (Ctenophora) represent the sister of all other animals. We show that results from empirical data follow predictions from simulations and suggest that, at the least in phylogenies inferred from amino acid sequences, a placement of the ctenophores as sister to all the other animals is best explained as a tree reconstruction artifact

Sources of Signal in 62 Protein-Coding Nuclear Genes for Higher-Level Phylogenetics of Arthropods

BACKGROUND: This study aims to investigate the strength of various sources of phylogenetic information that led to recent seemingly robust conclusions about higher-level arthropod phylogeny and to assess the role of excluding or downweighting synonymous change for arriving at those conclusions. METHODOLOGY/PRINCIPAL FINDINGS: The current study analyzes DNA sequences from 68 gene segments of 62 distinct protein-coding nuclear genes for 80 species. Gene segments analyzed individually support numerous nodes recovered in combined-gene analyses, but few of the higher-level nodes of greatest current interest. However, neither is there support for conflicting alternatives to these higher-level nodes. Gene segments with higher rates of nonsynonymous change tend to be more informative overall, but those with lower rates tend to provide stronger support for deeper nodes. Higher-level nodes with bootstrap values in the 80% - 99% range for the complete data matrix are markedly more sensitive to substantial drops in their bootstrap percentages after character subsampling than those with 100% bootstrap, suggesting that these nodes are likely not to have been strongly supported with many fewer data than in the full matrix. Data set partitioning of total data by (mostly) synonymous and (mostly) nonsynonymous change improves overall node support, but the result remains much inferior to analysis of (unpartitioned) nonsynonymous change alone. Clusters of genes with similar nonsynonymous rate properties (e.g., faster vs. slower) show some distinct patterns of node support but few conflicts. Synonymous change is shown to contribute little, if any, phylogenetic signal to the support of higher-level nodes, but it does contribute nonphylogenetic signal, probably through its underlying heterogeneous nucleotide composition. Analysis of seemingly conservative indels does not prove useful. CONCLUSIONS: Generating a robust molecular higher-level phylogeny of Arthropoda is currently possible with large amounts of data and an exclusive reliance on nonsynonymous change

Systematic Error in Seed Plant Phylogenomics

Resolving the closest relatives of Gnetales has been an enigmatic problem in seed plant phylogeny. The problem is known to be difficult because of the extent of divergence between this diverse group of gymnosperms and their closest phylogenetic relatives. Here, we investigate the evolutionary properties of conifer chloroplast DNA sequences. To improve taxon sampling of Cupressophyta (non-Pinaceae conifers), we report sequences from three new chloroplast (cp) genomes of Southern Hemisphere conifers. We have applied a site pattern sorting criterion to study compositional heterogeneity, heterotachy, and the fit of conifer chloroplast genome sequences to a general time reversible + G substitution model. We show that non-time reversible properties of aligned sequence positions in the chloroplast genomes of Gnetales mislead phylogenetic reconstruction of these seed plants. When 2,250 of the most varied sites in our concatenated alignment are excluded, phylogenetic analyses favor a close evolutionary relationship between the Gnetales and Pinaceae—the Gnepine hypothesis. Our analytical protocol provides a useful approach for evaluating the robustness of phylogenomic inferences. Our findings highlight the importance of goodness of fit between substitution model and data for understanding seed plant phylogeny

The taming of an impossible child: a standardized all-in approach to the phylogeny of Hymenoptera using public database sequences

<p>Abstract</p> <p>Background</p> <p>Enormous molecular sequence data have been accumulated over the past several years and are still exponentially growing with the use of faster and cheaper sequencing techniques. There is high and widespread interest in using these data for phylogenetic analyses. However, the amount of data that one can retrieve from public sequence repositories is virtually impossible to tame without dedicated software that automates processes. Here we present a novel bioinformatics pipeline for downloading, formatting, filtering and analyzing public sequence data deposited in GenBank. It combines some well-established programs with numerous newly developed software tools (available at <url>http://software.zfmk.de/</url>).</p> <p>Results</p> <p>We used the bioinformatics pipeline to investigate the phylogeny of the megadiverse insect order Hymenoptera (sawflies, bees, wasps and ants) by retrieving and processing more than 120,000 sequences and by selecting subsets under the criteria of compositional homogeneity and defined levels of density and overlap. Tree reconstruction was done with a partitioned maximum likelihood analysis from a supermatrix with more than 80,000 sites and more than 1,100 species. In the inferred tree, consistent with previous studies, "Symphyta" is paraphyletic. Within Apocrita, our analysis suggests a topology of Stephanoidea + (Ichneumonoidea + (Proctotrupomorpha + (Evanioidea + Aculeata))). Despite the huge amount of data, we identified several persistent problems in the Hymenoptera tree. Data coverage is still extremely low, and additional data have to be collected to reliably infer the phylogeny of Hymenoptera.</p> <p>Conclusions</p> <p>While we applied our bioinformatics pipeline to Hymenoptera, we designed the approach to be as general as possible. With this pipeline, it is possible to produce phylogenetic trees for any taxonomic group and to monitor new data and tree robustness in a taxon of interest. It therefore has great potential to meet the challenges of the phylogenomic era and to deepen our understanding of the tree of life.</p

A new method for identifying site-specific evolutionary rates and its applications.

In this thesis, I discuss each stage in the development of a new method for identifying site specific evolutionary rates, from conception of the idea, through the implementation to its application to data. TIGER, or tree independent generation of evolutionary rates, is based largely around the works of LeQuesne (1989), Wilkinson (1998) and Pisani (2004) and the premise that sites in a multi-state character matrix could be scored based on the level of agreement it displays with the other sites. In these earlier studies, however, agreement was measured in binary manner: sites were either compatible with each other or they are not. TIGER allows various degrees of agreement to occur between two sites, allowing it to pick up more subtle signals in the data. After implementing the method into a software program, it could be applied to data. Using a combination of simulated and empirical datasets, TIGER was shown to produce desirable results. In particular, removal of sites identified by TIGER was shown to improve phylogenetic reconstruction of deeply diverging lineages and of taxa displaying compositional attraction. Additionally, TIGER was applied to a gene content matrix in order to identify HGT signals and integrated into the analysis of a current phylogenetic problem, the origin of the mitochondria. Although it is widely accepted that eukaryotes have a chimeric genome, the specific “parent” of the mitochondria is, as of yet, unclear. Previous studies have failed to reach agreement regarding this issue for a number of reasons. Exploration of the signals using TIGER and heterogeneous modelling reveal that multiple signals and compositional heterogeneity are among the biggest problems with datasets containing both mitochondrial and a-proteobacterial sequences

Biased gene conversion and GC-content evolution in the coding sequences of reptiles and vertebrates.

Mammalian and avian genomes are characterized by a substantial spatial heterogeneity of GC-content, which is often interpreted as reflecting the effect of local GC-biased gene conversion (gBGC), a meiotic repair bias that favors G and C over A and T alleles in high-recombining genomic regions. Surprisingly, the first fully sequenced nonavian sauropsid (i.e., reptile), the green anole Anolis carolinensis, revealed a highly homogeneous genomic GC-content landscape, suggesting the possibility that gBGC might not be at work in this lineage. Here, we analyze GC-content evolution at third-codon positions (GC3) in 44 vertebrates species, including eight newly sequenced transcriptomes, with a specific focus on nonavian sauropsids. We report that reptiles, including the green anole, have a genome-wide distribution of GC3 similar to that of mammals and birds, and we infer a strong GC3-heterogeneity to be already present in the tetrapod ancestor. We further show that the dynamic of coding sequence GC-content is largely governed by karyotypic features in vertebrates, notably in the green anole, in agreement with the gBGC hypothesis. The discrepancy between third-codon positions and noncoding DNA regarding GC-content dynamics in the green anole could not be explained by the activity of transposable elements or selection on codon usage. This analysis highlights the unique value of third-codon positions as an insertion/deletion-free marker of nucleotide substitution biases that ultimately affect the evolution of proteins

What is the phylogenetic signal limit from mitogenomes? The reconciliation between mitochondrial and nuclear data in the Insecta class phylogeny

Background: Efforts to solve higher-level evolutionary relationships within the class Insecta by using mitochondrial genomic data are hindered due to fast sequence evolution of several groups, most notably Hymenoptera, Strepsiptera, Phthiraptera, Hemiptera and Thysanoptera. Accelerated rates of substitution on their sequences have been shown to have negative consequences in phylogenetic inference. In this study, we tested several methodological approaches to recover phylogenetic signal from whole mitochondrial genomes. As a model, we used two classical problems in insect phylogenetics: The relationships within Paraneoptera and within Holometabola. Moreover, we assessed the mitochondrial phylogenetic signal limits in the deeper Eumetabola dataset, and we studied the contribution of individual genes. Results: Long-branch attraction (LBA) artefacts were detected in all the datasets. Methods using Bayesian inference outperformed maximum likelihood approaches, and LBA was avoided in Paraneoptera and Holometabola when using protein sequences and the site-heterogeneous mixture model CAT. The better performance of this method was evidenced by resulting topologies matching generally accepted hypotheses based on nuclear and/or morphological data, and was confirmed by cross-validation and simulation analyses. Using the CAT model, the order Strepsiptera was recovered as sister to Coleoptera for the first time using mitochondrial sequences, in agreement with recent results based on large nuclear and morphological datasets. Also the Hymenoptera-Mecopterida association was obtained, leaving Coleoptera and Strepsiptera as the basal groups of the holometabolan insects, which coincides with one of the two main competing hypotheses. For the Paraneroptera, the currently accepted non-monophyly of Homoptera was documented as a phylogenetic novelty for mitochondrial data. However, results were not satisfactory when exploring the entire Eumetabola, revealing the limits of the phylogenetic signal that can be extracted from Insecta mitogenomes. Based on the combined use of the five best topology-performing genes we obtained comparable results to whole mitogenomes, highlighting the important role of data quality. Conclusion: We show for the first time that mitogenomic data agrees with nuclear and morphological data for several of the most controversial insect evolutionary relationships, adding a new independent source of evidence to study relationships among insect orders. We propose that deeper divergences cannot be inferred with the current available methods due to sequence saturation and compositional bias inconsistencies. Our exploratory analysis indicates that the CAT model is the best dealing with LBA and it could be useful for other groups and datasets with similar phylogenetic difficulties