Multiple reference genomes and transcriptomes for Arabidopsis thaliana
Xiangchao GanOliver StegleJonas BehrJoshua G. SteffenPhilipp DreweKatie L. HildebrandRune LyngsoeSebastian J. SchultheißEdward J. OsborneVipin T. SreedharanAndré KahlesRegina BohnertGéraldine JeanPaul DerwentPaul KerseyEric J. BelfieldNicholas P. HarberdEric KemenChristopher ToomajianPaula X. KoverRichard M. ClarkGunnar RätschRichard Mott
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Genetic differences between Arabidopsis thaliana accessions underlie the plant's extensive phenotypic variation, and until now these have been interpreted largely in the context of the annotated reference accession Col-0. Here we report the sequencing, assembly and annotation of the genomes of 18 natural A. thaliana accessions, and their transcriptomes. When assessed on the basis of the reference annotation, one-third of protein-coding genes are predicted to be disrupted in at least one accession. However, re-annotation of each genome revealed that alternative gene models often restore coding potential. Gene expression in seedlings differed for nearly half of expressed genes and was frequently associated with cis variants within 5 kilobases, as were intron retention alternative splicing events. Sequence and expression variation is most pronounced in genes that respond to the biotic environment. Our data further promote evolutionary and functional studies in A. thaliana, especially the MAGIC genetic reference population descended from these accessions.RNA-seq analysis has enabled the evaluation of transcriptional changes in many species including nonmodel organisms. However, in most species only a single reference genome is available and RNA-seq reads from highly divergent varieties are typically aligned to this reference. Here, we quantify the impacts of the choice of mapping genome in rice where three high-quality reference genomes are available. We aligned RNA-seq data from a popular productive rice variety to three different reference genomes and found that the identification of differentially expressed genes differed depending on which reference genome was used for mapping. Furthermore, the ability to detect differentially used transcript isoforms was profoundly affected by the choice of reference genome: Only 30% of the differentially used splicing features were detected when reads were mapped to the more commonly used, but more distantly related reference genome. This demonstrated that gene expression and splicing analysis varies considerably depending on the mapping reference genome, and that analysis of individuals that are distantly related to an available reference genome may be improved by acquisition of new genomic reference material. We observed that these differences in transcriptome analysis are, in part, due to the presence of single nucleotide polymorphisms between the sequenced individual and each respective reference genome, as well as annotation differences between the reference genomes that exist even between syntenic orthologs. We conclude that even between two closely related genomes of similar quality, using the reference genome that is most closely related to the species being sampled significantly improves transcriptome analysis.
Synteny
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Reference Genes
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High Throughput Sequencing (HTS) technologies are constantly improving and making genome sequencing more affordable. However, HTS sequencers can only produce short overlapping genome fragments that are erroneous and cover the sequenced genomes unevenly. These genome fragments are assembled based on their overlaps to produce larger contiguous sequences. Since de novo genome assembly is computationally intensive, some species have a reference genome used as a guide for assembling genome fragments from the same species or as a basis for comparative genomics methods. Yet, assembling a genome is an error-prone process depending on the quality of the sequencing data and the heuristics used during the assembly. Furthermore, analyses based on a reference are biased towards the reference. Finally, a single reference cannot reflect the dynamics and diversity of a population of genomes. Overcoming these issues requires to move away from the single-genome reference-centric paradigm and take advantage of the multiple sequenced genomes available for each species. For this purpose, pan-genomes were introduced as sets of genomes from different strains of the same species. A pan-genome is represented by a multi-genome index exploiting the similarity and redundancy of the genomes it contains. Still, pan-genomes are more difficult to analyze than single genomes because of the large amount of data to be stored and indexed.
Current data structures for pan-genome indexing do not fulfill all requirements for pan-genome analysis. Indeed, these data structures are often immutable while the size of a pan-genome grows constantly with newly sequenced genomes. Frequently, these data structures consider only assemblies as input, while unassembled genome fragments abound in databases. Also, indexing variants and similarities between the genomes of a pan-genome usually requires time and memory consuming algorithms such as sequence alignments. Sometimes, pan-genome analysis tools just assume variants and similarities are provided as input.
While data structures already exist for pan-genome indexing, no solution is currently proposed for genome fragment compression in a pan-genome context. Indeed, it is often of interest to transmit and store all genome fragments of a pan-genome. However, HTS-specific compression tools are not dynamic and cannot update a compressed archive of genome fragments with new fragments of a genome without decompression. Hence, those tools are poorly adapted to the transmission and storage of genome fragments in a pan-genome context.
In this thesis, we aim to provide scalable solutions for pan-genome indexing and storage. We first address the problem of pan-genome indexing by proposing a new alignment-free, reference-free and incremental data structure that considers genome fragments as well as assemblies in input: the Bloom Filter Trie (BFT). The BFT is a tree data structure representing a colored de Bruijn graph in which k-mers, words of length k from the input genomes, are associated with sets of colors representing the genomes in which they occur. The BFT makes extensive use of Bloom filters to navigate in the tree and optimize the graph traversal. A bursting method is employed to perform an efficient path and level compaction of the tree. We show that the BFT outperforms a data structure that has similar features but is based on an approximation of the set of indexed k-mers.
Secondly, we address the problem of genome fragments compression in a pan-genome context by proposing a new abstract data structure, the guided de Bruijn graph. It augments the de Bruijn graph with k-mer partitions such that the graph traversal is guided to reconstruct exactly the genome fragments when decompressing. Different techniques are proposed to optimize the storage of fragments in the graph and the partition encoding. We show that the BFT described previously has all features required to index a guided de Bruijn graph and is used in the implementation of our compression method named DARRC. The evaluation of DARRC on a large pan-genome dataset compared to state-of-the-art HTS-specific and general purpose compression tools shows a 30% compression ratio improvement over the second best performing tool of this evaluation.
Comparative Genomics
Hybrid genome assembly
Sequence assembly
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The recent advances in sequencing technology and bioinformatics have revolutionized genomic research, making the decoding of the genome an easier task. Genome sequences are currently available for many species, including cattle, sheep and river buffalo. The available reference genomes are very accurate, and they represent the best possible order of loci at this time. In cattle, despite the great accuracy achieved, a part of the genome has been sequenced but not yet assembled: these genome fragments are called unmapped fragments. In the present study, 20 unmapped fragments belonging to the Btau_4.0 reference genome have been mapped by FISH in cattle (<i>Bos taurus</i>, 2n = 60), sheep (<i>Ovis aries</i>, 2n = 54) and river buffalo (<i>Bubalus bubalis</i>, 2n = 50). Our results confirm the accuracy of the available reference genome, though there are some discrepancies between the expected localization and the observed localization. Moreover, the available data in the literature regarding genomic homologies between cattle, sheep and river buffalo are confirmed. Finally, the results presented here suggest that FISH was, and still is, a useful technology to validate the data produced by genome sequencing programs.
Bovine genome
Bubalus
Sequence assembly
Water buffalo
Ovis
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Next-generation sequencing (NGS) technologies have greatly promoted the genomic study of prokaryotes. However, highly fragmented assemblies due to short reads from NGS are still a limiting factor in gaining insights into the genome biology. Reference-assisted tools are promising in genome assembly, but tend to result in false assembly when the assigned reference has extensive rearrangements. Herein, we present GAAP, a genome assembly pipeline for scaffolding based on core-gene-defined Genome Organizational Framework (cGOF) described in our previous study. Instead of assigning references, we use the multiple-reference-derived cGOFs as indexes to assist in order and orientation of the scaffolds and build a skeleton structure, and then use read pairs to extend scaffolds, called local scaffolding, and distinguish between true and chimeric adjacencies in the scaffolds. In our performance tests using both empirical and simulated data of 15 genomes in six species with diverse genome size, complexity, and all three categories of cGOFs, GAAP outcompetes or achieves comparable results when compared to three other reference-assisted programs, AlignGraph, Ragout and MeDuSa. GAAP uses both cGOF and pair-end reads to create assemblies in genomic scale, and performs better than the currently available reference-assisted assembly tools as it recovers more assemblies and makes fewer false locations, especially for species with extensive rearranged genomes. Our method is a promising solution for reconstruction of genome sequence from short reads of NGS.
Sequence assembly
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The concept of pan-genome, which is the collection of all genomes from a population, has shown a great potential in genomics study, especially for crop sciences. The rice pan-genome constructed from the second-generation sequencing (SGS) data is about 270 Mb larger than Nipponbare , the rice reference genome (NipRG), but it is still disadvantaged by incompleteness and loss of genomic contexts. The third-generation sequencing (TGS) with long reads can help to construct better pan-genomes. In this paper, we report a high-quality rice pan-genome construction method by introducing a series of new steps to deal with the long-read data, including unmapped sequence block filtering, redundancy removing, and sequence block elongating. Compared to NipRG, the long-read sequencing-based pan-genome constructed from 105 rice accessions, which contains 604 Mb novel sequences, is much more comprehensive than the one constructed from ∼3000 rice genomes sequenced with short reads. The repetitive sequences are the main components of novel sequences, which partially explain the differences between the pan-genomes based on TGS and SGS. Adding six wild rice accessions, there are about 879 Mb novel sequences and 19,000 novel genes in the rice pan-genome in total. In addition, we have created high-quality reference genomes for all representative rice populations, including five gapless reference genomes. This study has made significant progress in our understanding of the rice pan-genome, and this pan-genome construction method for long-read data can be applied to accelerate a broad range of genomics studies.
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plant evolution
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With the release of high-quality reference genomes assembled by long reads from the third-generation sequencing technology, as well as extensive re-sequencing and population genetic analysis, researchers found that a single reference genome does not represent the diversity within a species. The missing sequences on the reference genome result in an incomplete population genetic polymorphism map. The emergence of pan-genome can well repair the deficiency of single reference genome, which include core genome (responsible for basic biological functions and the main phenotypic characteristics within a species) and the variable genome (related to the genetic diversity or biological characteristics). According to the core and variable genome proportion, the types of pan-genomes can be either open or closed. Here, we review the current exploring of pan-genome for a range of species, to discuss the characteristics of pan-genome in various biological groups. The pan-genome of mammals are more likely closed, while the pan-genomes of microbes, angiosperms, and some invertebrates are likely non-closed. It is possible to complete the reference genome and obtain complete variation information through the pan-genomic study, which will contribute to the study of molecular mechanism for genetic diversity and phenotypic evolution.随着三代测序组装的高质量参考基因组的陆续发布,以及大规模重测序和群体遗传学分析的广泛进行,研究人员发现来自单一个体的参考基因组远不能涵盖整个物种的所有遗传序列,大量缺失序列导致群体遗传变异图谱不完整,而构建来自多个个体的泛基因组能很好地解决这一缺陷,其研究内容包括负责基本生物学功能及该物种主要表型特征的核心基因组以及与物种的遗传多样性和个体独特性相关的可变基因组。根据核心和可变基因组所占比例的不同,泛基因组存在开放型和闭合型两种类型。本文主要综述了细菌、真菌和动植物的泛基因组学研究进展,讨论了其在各生物类群中的特征,其中哺乳动物泛基因组是相对闭合的,而目前已知的微生物、被子植物和部分低等动物的泛基因组倾向于开放,通过泛基因组的构建可以完善现有参考基因组并获取整个物种的完整变异信息,将有助于深入研究遗传多样性和表型变异产生的分子机制。.
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Brassica rapa
Comparative Genomics
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The human reference genome is an essential tool for studying human genomes. The standard reference genome is constructed from genomes of a few donors. The 1,000 genomes project has revealed a huge amount of genetic differences between diverse populations. It is therefore naturally questioned whether the standard reference genome can work well for all human genome studies or population-specific reference genomes are needed accordingly. In this paper, we present a pipeline for constructing and evaluating a population-specific reference genome. The pipeline was examined on building the Vietnamese reference genome from 100 Kinh Vietnamese genomes obtained from the 1,000 genomes project. Experiments showed that the resulting Vietnamese reference genome was better than the standard reference genome at analyzing Vietnamese genomic data. It helped improve the quality of short reads mapping and genotype calling for Vietnamese genomes. The pipeline is applicable for building and evaluating other population-specific reference genomes.
Vietnamese
1000 Genomes Project
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