종 및 복제수 변이 검출을 위한 차세대 염기서열 기술 기반 새로운 접근법의 적용

학위논문(박사) -- 서울대학교대학원 : 농업생명과학대학 농생명공학부(바이오모듈레이션전공), 2022. 8. 김희발.Next-generation sequencing (NGS) technologies have contributed to a diverse range of biological research areas: NGS-based studies have revealed previously unknown host-microbe interaction or have enabled effective genomic selection by discovering genetic variants that cause phenotypic changes during domestication. The accumulation of knowledge and new insights derived from NGS was possible because various approaches have been developed and applied according to the specific purpose for solving each biological problem. Novel approaches include targeted sequencing that produces only genomic regions of interest economically and the development of new algorithms that can efficiently analyze genomic big data. This doctoral dissertation, which consists of three studies, focuses on these novel approaches for NGS data analysis. The first study focuses on the development of a novel pipeline related to food quality and safety management. The second study focuses on the development of a database and an analysis tool for the activation of the use of novel marker in bacterial metabarcoding analysis with long-reads. The last study, although not a novel approach, focuses on the identification of copy number variation (CNV) in domesticated chicken, which is a relatively less studied genetic variant compared to a single nucleotide variant. Specifically, in chapter 1, background knowledge and research trends of metagenome analysis and identification of CNV are summarized. Chapter 2 describes the probiotic species detection pipeline using NGS data with the breadth of coverage. For the accuracy of determining the presence and absence of probiotic species in the product, a reference data set was established by selecting a representative strain for each species, and a threshold value for the breadth of coverage was defined. Regardless of the sequencing platform, the pipeline accurately detected the probiotic species contained in the product. Also, it was confirmed that the false-positive case was controlled completely, which was the problem in other read classification-based methods. Chapter 3 describes the construction of the 16S-ITS-23S rRNA operon database and tool for species-level bacterial community analysis. The advent of long-read sequencing platforms made it possible to use long markers for metabarcoding. In the bacterial community analysis, a taxonomic resolution was considerably improved up to the species-level by using 16S-ITS-23S rRNA operon sequences (~4300 bp), which has about 10 times longer than the previously used partial 16S rRNA sequences (~400 bp). However, curated databases and appropriate tools for rRNA operon analysis are still lacking. Therefore, to activate the 16S-ITS-23S rRNA operon sequence analysis, all bacterial genomes were collected from the National Center for Biotechnology Information (NCBI) and curated for the construction of the database. A user-friendly mapping-based analysis tool was also developed. Analysis of various mock and simulated samples using the database and tool showed promising results at the species level. In chapter 4, breed-specific CNV was identified in three chicken breeds: Rhode Island Red, Cornish, and White Leghorn. Red Jungle Fowl was used as a control group to explore CNV only found in domesticated breeds. The depth of coverage was used to identify CNV. And CNV regions were obtained for comparison between breeds. Based on CNVR, Cornish was closer to Rhode Island Red than White Leghorn. And functional annotation of domesticated CNVR revealed that mainly enriched terms involved in immune regulation, metabolism, and organ development. This dissertation presented that novel approaches to NGS data can yield a variety of biological insights. I expect that the analysis methods and databases which were constructed in this dissertation will contribute to various studies.유전학, 미생물학, 의학 등에서 널리 활용되고 있는 차세대 염기서열 분석 기술은 전에 알지 못했던 숙주-미생물 상호 작용에 대한 이해를 돕고, 가축화 유전자 탐색을 통해 유전체 선발을 위한 정보를 제공해주는 등 다양한 분야에서 지식을 누적시키고 새로운 수준의 통찰력을 제공하고 있다. 이러한 지식의 확장은 염기서열 분석 기술의 출현과 더불어 각 분야에서 목적에 맞게 다양한 접근 방법을 개발하고 응용하였기 때문에 가능하였다. 접근 방법의 다각화는 다양한 측면에서 이루어지는데 데이터 생산단계에서 표적 시퀀싱과 같이 염기서열 읽는 부위를 제한하여 보다 경제적으로 필요한 정보만을 생산하거나, 데이터 분석단계에서 효율적 분석을 위해 새로운 알고리즘이 탑재된 소프트웨어를 개발하는 등이 그 예이다. 본 논문은 이러한 접근 방법의 다각화에 초점을 맞추었으며 ‘차세대 염기서열을 이용한 검출’이라는 주제하에 세 가지의 연구로 이루어져 있다. 첫 번째 연구는 식품의 품질관리와 관련된 새로운 염기서열 분석 방법 개발에 관한 것이다. 두 번째 연구는 세균 메타바코딩 분석에서 새로운 마커 유전자 사용의 활성화를 위한 데이터베이스 구축 및 분석 방법 개발에 관한 것이다. 마지막으로 세 번째 연구는 기존에 개발된 복제수 변이 검출 방법을 통해 잘 알려지지 않은 가축화 된 닭의 복제수 변이 발굴에 관한 것이다. 구체적으로 총 4장으로 이루어진 본 논문의 제 1장에서는 메타게놈분석, 복제수 변이 검출 법 등 본 논문의 기본 배경지식 및 연구동향을 정리하였다. 제 2장에서는 참조서열에 서열 리드를 맵핑 할 때 생기는 커버리지 폭을 이용하여 프로바이오틱스 종 검출 파이프라인을 구축하였다. 제품 내 프로바이오틱스 종의 함유 유무를 보다 정확하게 판단하기 위하여 종마다 대표 균주를 선정하여 참조 데이터셋을 구축하였고, 새로운 미생물 동정 기준인 커버리지 폭에 대한 임계값을 제시, 검출에 사용하였다. 그 결과 시퀀싱 플랫폼과 상관없이 제품 내 함유된 종을 정확히 검출하였고 특히, 기존 서열 리드 분류 기반 파이프라인에서 문제가 된 위양성 케이스가 완벽하게 제어됨을 확인하였다. 제 3장에서는 종 (species) 수준의 세균 군집 분석을 위한 16S-ITS-23S rRNA 오페론 서열 데이터베이스 구축 및 이를 활용할 수 있는 소프트웨어 개발에 관하여 기술하였다. 수 천에서 수 십만 이상의 길이를 한 번에 읽을 수 있는 3세대 시퀀서의 출현으로 메타지노믹스 분야에서 기존 세균 군집 분석에 사용되던 16S rRNA 서열의 일부가 아닌 약 10배의 정보를 가지고 있는 16S-ITS-23S rRNA 오페론 서열의 사용이 가능해졌고 종 수준까지 분류 해상도가 크게 향상되었다. 본 연구에서는 높은 분류학적 해상도를 보이는 16S-ITS-23S rRNA 오페론 서열 분석의 활성화를 위해 미국 국립생물공학정보센터에서 모든 세균 유전체를 모아 큐레이션을 거쳐 16S-ITS-23S rRNA 오페론 서열 데이터베이스를 구축하였고 사용자 친화적인 맵핑 기반의 자동화 소프트웨어를 개발하였다. 또한 이를 활용한 다양한 모의 샘플 분석 결과 종 수준으로 매우 정확하게 분류함을 확인하였다. 제 4장에서는 로드아일랜드레드, 코니시, 화이트 레그혼 세 닭 품종에서 품종 특이적인 복제수 변이를 발굴하였다. 참조서열에 서열 리드를 맵핑 할 때 생기는 커버리지 깊이를 복제수 변이를 발굴에 사용하였으며, 야생종인 적색야계의 데이터를 대조군 삼아 가축화된 닭에서만 발견되는 복제수 변이를 정리하였다. 복제수 변이를 기준으로 코니시와 로드아일랜드레드가 화이트 레그혼 종 보다 서로 좀 더 가까움을 밝혔으며, 기관 발달, 면역조절, 대사와 관련된 유전자 부근에 복제수 변이가 많이 발굴됨을 확인하였다. 본 논문은 새로운 접근방식으로 염기서열 데이터를 분석하여 다양한 생물학적 통찰력을 얻을 수 있음을 보여주었으며, 구축된 분석 방법 및 데이터베이스는 여러 연구자들에게 도움이 될 것으로 기대한다.CHAPTER 1. LITERATURE REVIEW 1 1.1 Metagenomics 2 1.2 Copy Number Variation (CNV) 10 CHAPTER 2. ACCURATE AND STRICT IDENTIFICATION OF PROBIOTIC SPECIES BASED ON COVERAGE OF WHOLE-METAGENOME SHOTGUN SEQUENCING DATA 13 2.1 Abstract 14 2.2 Introduction 15 2.3 Material and methods 19 2.4 Results 32 2.5 Discussion 66 CHAPTER 3. MICROBIAL IDENTIFICATION USING RRNA OPERON REGION: DATABASE AND TOOL FOR METATAXONOMICS WITH LONG-READ SEQUENCE 72 3.1 Abstract 73 3.2 Introduction 75 3.3 Materials and Methods 79 3.4 Results 89 3.5 Discussion 126 CHAPTER 4. IDENTIFICATION OF COPY NUMBER VARIATION IN DOMESTIC CHICKEN USING WHOLE-GENOME SEQUENCING REVEALS EVIDENCE OF SELECTION IN THE GENOME 131 4.1 Abstract 132 4.2 Introduction 135 4.3 Materials and Methods 139 4.4 Results 144 4.5 Discussion 181 REFERENCES 187 국문초록 223박

PRINCE: Accurate approximation of the copy number of tandem repeats

Variable-Number Tandem Repeats (VNTR) are genomic regions where a short sequence of DNA is repeated with no space in between repeats. While a fixed set of VNTRs is typically identified for a given species, the copy number at each VNTR varies between individuals within a species. Although VNTRs are found in both prokaryotic and eukaryotic genomes, the methodology called multi-locus VNTR analysis (MLVA) is widely used to distinguish different strains of bacteria, as well as cluster strains that might be epidemiologically related and investigate evolutionary rates. We propose PRINCE (Processing Reads to Infer the Number of Copies via Estimation), an algorithm that is able to accurately estimate the copy number of a VNTR given the sequence of a single repeat unit and a set of short reads from a whole-genome sequence (WGS) experiment. This is a challenging problem, especially in the cases when the repeat region is longer than the expected read length. Our proposed method computes a statistical approximation of the local coverage inside the repeat region. This approximation is then mapped to the copy number using a linear function whose parameters are fitted to simulated data. We test PRINCE on the genomes of three datasets of Mycobacterium tuberculosis strains and show that it is more than twice as accurate as a previous method. An implementation of PRINCE in the Python language is freely available at https://github.com/WGS-TB/PythonPRINCE

Detection of copy number variations in rice using array-based comparative genomic hybridization

<p>Abstract</p> <p>Background</p> <p>Copy number variations (CNVs) can create new genes, change gene dosage, reshape gene structures, and modify elements regulating gene expression. As with all types of genetic variation, CNVs may influence phenotypic variation and gene expression. CNVs are thus considered major sources of genetic variation. Little is known, however, about their contribution to genetic variation in rice.</p> <p>Results</p> <p>To detect CNVs, we used a set of NimbleGen whole-genome comparative genomic hybridization arrays containing 718,256 oligonucleotide probes with a median probe spacing of 500 bp. We compiled a high-resolution map of CNVs in the rice genome, showing 641 CNVs between the genomes of the rice cultivars 'Nipponbare' (from <it>O. sativa </it>ssp. <it>japonica</it>) and 'Guang-lu-ai 4' (from <it>O. sativa </it>ssp. <it>indica</it>). The CNVs identified vary in size from 1.1 kb to 180.7 kb, and encompass approximately 7.6 Mb of the rice genome. The largest regions showing copy gain and loss are of 37.4 kb on chromosome 4, and 180.7 kb on chromosome 8. In addition, 85 DNA segments were identified, including some genic sequences. Contracted genes greatly outnumbered duplicated ones. Many of the contracted genes corresponded to either the same genes or genes involved in the same biological processes; this was also the case for genes involved in disease and defense.</p> <p>Conclusion</p> <p>We detected CNVs in rice by array-based comparative genomic hybridization. These CNVs contain known genes. Further discussion of CNVs is important, as they are linked to variation among rice varieties, and are likely to contribute to subspecific characteristics.</p

wuHMM: a robust algorithm to detect DNA copy number variation using long oligonucleotide microarray data

Copy number variants (CNVs) are currently defined as genomic sequences that are polymorphic in copy number and range in length from 1000 to several million base pairs. Among current array-based CNV detection platforms, long-oligonucleotide arrays promise the highest resolution. However, the performance of currently available analytical tools suffers when applied to these data because of the lower signal:noise ratio inherent in oligonucleotide-based hybridization assays. We have developed wuHMM, an algorithm for mapping CNVs from array comparative genomic hybridization (aCGH) platforms comprised of 385 000 to more than 3 million probes. wuHMM is unique in that it can utilize sequence divergence information to reduce the false positive rate (FPR). We apply wuHMM to 385K-aCGH, 2.1M-aCGH and 3.1M-aCGH experiments comparing the 129X1/SvJ and C57BL/6J inbred mouse genomes. We assess wuHMM's performance on the 385K platform by comparison to the higher resolution platforms and we independently validate 10 CNVs. The method requires no training data and is robust with respect to changes in algorithm parameters. At a FPR of <10%, the algorithm can detect CNVs with five probes on the 385K platform and three on the 2.1M and 3.1M platforms, resulting in effective resolutions of 24 kb, 2–5 kb and 1 kb, respectively

Genome dynamics of the human embryonic kidney 293 lineage in response to cell biology manipulations

The HEK293 human cell lineage is widely used in cell biology and biotechnology. Here we use whole-genome resequencing of six 293 cell lines to study the dynamics of this aneuploid genome in response to the manipulations used to generate common 293 cell derivatives, such as transformation and stable clone generation (293T); suspension growth adaptation (293S); and cytotoxic lectin selection (293SG). Remarkably, we observe that copy number alteration detection could identify the genomic region that enabled cell survival under selective conditions (i.c. ricin selection). Furthermore, we present methods to detect human/vector genome breakpoints and a user-friendly visualization tool for the 293 genome data. We also establish that the genome structure composition is in steady state for most of these cell lines when standard cell culturing conditions are used. This resource enables novel and more informed studies with 293 cells, and we will distribute the sequenced cell lines to this effect

Arvutuslikud meetodid DNA koopiaarvu määramiseks

Väitekirja elektrooniline versioon ei sisalda publikatsioone.DNA koopiaarvu variantideks või muutusteks nimetatakse selliseid erinevusi inimeste geneetilises materjalis, mille puhul mingi DNA lõigu koopiaarv on erinev oodatavast koopiaarvust kaks (üks koopia mingit kindlat DNA järjestust emalt päritud kromosoomil ja üks koopia isalt päritud kromosoomil). DNA koopiate vähenemist nimetatakse deletsiooniks ning vastavaid DNA variante nimetatakse deletsioonideks. DNA koopiate juurdetulemist nimetatakse duplitseerumiseks ning selliseid kahest suurema koopiaarvuga variante vastavalt duplikatsioonideks. Antud doktoritöös uuriti inimese DNA koopiaarvu variante, nende seotust erinevate haigustega ja nende tekkimise ja pärandumise eripärasid. Kasutades DNA mikrokiipe ehk geenikiipe uuriti esmalt kas ja millised DNA koopiaarvu muutused võivad olla seotud vaimse arengu mahajäämusega (VAM-ga). Uurides perekondasid, kus ühel või mitmel liikmel oli diagnoositud VAM, leiti mitmeid juba varem VAM-ga seostatud DNA koopiaarvu muutusi ning lisaks leiti ka mitmeid uusi DNA koopiaarvu variante, mille esinemine võib olla seotud VAM-e väljakujunemisega. Sarnane uuring viidi läbi ka korduva spontaanse raseduse katkemise probleemiga paaride ja naiste puhul. Võrreldes nende patsientide gruppi kuuluvate naiste DNA koopiaarvu muutusi ning nende sagedusi terveid emasid sisaldavate kontroll-grupi indiviidide omadega, leiti statistiliselt ja bioloogiliselt oluline erinevus muutunud koopiaarvuga DNA lõigus, mis sisaldab PDZD2 ja GOLPH3 geene ja kus esinevate duplikatsioonide „omamine“ suurendas naistel märkimisväärselt spontaanse raseduse katkemise ohtu. Doktoritöö viimases osas uuriti Tartu Ülikooli Eesti Geenivaramu ja rahvusvahelise HapMap projekti poolt kogutud tõsiste haigusteta inimestel esinevaid DNA koopiaarvu muutusi ja nende pärandumist perekondades. Selle uuringu üheks huvitavamaks tulemuseks oli deletsioonide alapärandumine vanematelt lastele ehk deletsioone kandvaid DNA regioone esines laste genoomides oluliselt vähem, kui normaalse Mendeliaalse (juhusliku) pärandumise korral oleks oodata võinud. Uurides duplikatsioonide regioone perekondades leiti aga, et kaks kolmandikku duplikatsioonides esinevatest DNA koopiatest ei olnud identsed (üksteise täpsed koopiad), vaid mõnevõrra erinevad, demonstreerides seniajani teadmata olnud alleelse varieeruvuse määra DNA duplikatsioonide regioonides.DNA copy number variation is a type of genetic variation in which case the number of copies of a particular region of a chromosome is altered from its normal state. In the non-repetitive portion of the human genome, the normal haploid copy number is one – one copy of each sequence per chromosome. Accordingly, the normal diploid copy number in humans is two – one copy inherited from both parents. A copy number variant (CNV) can result from either a loss of copies (most often called a deletion) or gain of copies (called a duplication or amplification). In this thesis we studied DNA copy number variation in human – how CNVs emerge and how they are inherited from parents to offspring. We also analysed CNVs in the context of few different diseases. By using DNA microarrays we first aimed to determine if CNVs are associated with mental retardation (MR). For this we studied not only index cases with MR but larger nuclear families, where we discovered several already MR-associated CNVs and also a few novel CNV regions that are possibly associated with predisposition to MR. Similar study was conducted in couples and females suffering from recurrent miscarriage. By comparing CNVs and their frequencies in the latter group to these of healthy mothers, we discovered a multi-copy duplication at 5p13.3 that disrupts PDZD2 and GOLPH3 genes and significantly increases maternal risk for pregnancy complications. In the last part of this thesis we studied how CNVs are inherited in Estonian nuclear families (22 trios and 12 families with multiple siblings) and in HapMap Yoruban trios. We determined that deletion-carrying chromosomal regions were observed in the offspring slightly less frequently than expected by random Mendelian inheritance. By analysing duplication-carrying chromosomal regions in these families, we discovered that in two-thirds of such regions the duplicated copies of the underlying DNA sequence were not exactly identical but somewhat different, allowing us to define alternative allelic copies within these copy number gain-carrying chromosomal regions and demonstrating extensive and to-date unmeasured allelic variability in multi-copy CNV regions of the human genome

Detection of copy number variation from array intensity and sequencing read depth using a stepwise Bayesian model

Abstract Background Copy number variants (CNVs) have been demonstrated to occur at a high frequency and are now widely believed to make a significant contribution to the phenotypic variation in human populations. Array-based comparative genomic hybridization (array-CGH) and newly developed read-depth approach through ultrahigh throughput genomic sequencing both provide rapid, robust, and comprehensive methods to identify CNVs on a whole-genome scale. Results We developed a Bayesian statistical analysis algorithm for the detection of CNVs from both types of genomic data. The algorithm can analyze such data obtained from PCR-based bacterial artificial chromosome arrays, high-density oligonucleotide arrays, and more recently developed high-throughput DNA sequencing. Treating parameters--e.g., the number of CNVs, the position of each CNV, and the data noise level--that define the underlying data generating process as random variables, our approach derives the posterior distribution of the genomic CNV structure given the observed data. Sampling from the posterior distribution using a Markov chain Monte Carlo method, we get not only best estimates for these unknown parameters but also Bayesian credible intervals for the estimates. We illustrate the characteristics of our algorithm by applying it to both synthetic and experimental data sets in comparison to other segmentation algorithms. Conclusions In particular, the synthetic data comparison shows that our method is more sensitive than other approaches at low false positive rates. Furthermore, given its Bayesian origin, our method can also be seen as a technique to refine CNVs identified by fast point-estimate methods and also as a framework to integrate array-CGH and sequencing data with other CNV-related biological knowledge, all through informative priors.</p