Capturing single-copy nuclear genes,organellar genomes,and nuclear ribosomal DNA from deep genome skimming data for plant phylogenetics: A case study in Vitaceae

With the decreasing cost and availability of many newly developed bioinformatics pipelines, next-generation sequencing (NGS) has revolutionized plant systematics in recent years. Genome skimming has been widely used to obtain high-copy fractions of the genomes, including plastomes, mitochondrial DNA (mtDNA), and nuclear ribosomal DNA (nrDNA). In this study, through simulations, we evaluated the optimal (minimum) sequencing depth and performance for recovering single-copy nuclear genes (SCNs) from genome skimming data, by subsampling genome resequencing data and generating 10 data sets with different sequencing coverage in silico. We tested the performance of four data sets (plastome, nrDNA, mtDNA, and SCNs) obtained from genome skimming based on phylogenetic analyses of the Vitis clade at the genus level and Vitaceae at the family level, respectively. Our results showed that optimal minimum sequencing depth for high-quality SCNs assembly via genome skimming was about 10× coverage. Without the steps of synthesizing baits and enrichment experiments, coupled with incredibly low sequencing costs, we showcase that deep genome skimming (DGS) is as effective for capturing large data sets of SCNs as the widely used Hyb-Seq approach, in addition to capturing plastomes, mtDNA, and entire nrDNA repeats. DGS may serve as an efficient and economical alternative and may be superior to the popular target enrichment/Hyb-Seq approach.     

Using target capture to address conservation challenges: Population-level tracking of a globally-traded herbal medicine

The promotion of responsible and sustainable trade in biological resources is widely proposed as one solution to mitigate current high levels of global biodiversity loss. Various molecular identification methods have been proposed as appropriate tools for monitoring global supply chains of commercialized animals and plants. Here, we demonstrate the efficacy of target capture genomic barcoding in identifying and establishing the geographic origin of samples traded as Anacyclus pyrethrum, a medicinal plant assessed as globally vulnerable in the IUCN Red List of Threatened Species. Samples collected from national and international supply chains were identified through target capture sequencing of 443 low-copy nuclear makers and compared to results derived from genome skimming of plastome and DNA barcoding of standard plastid regions and ITS. Both target capture and genome skimming provided approximately 3.4 million reads per sample, but target capture largely outperformed standard plant barcodes and entire plastid genome sequences. We were able to discern the geographical origin of Anacyclus samples collected in Moroccan, Indian and Sri Lankan markets, differentiating between plant materials originally harvested from diverse populations in Algeria and Morocco. Dropping costs of analysing samples enables the potential of target capture to routinely identify commercialized plant species and determine their geographic origin. It promises to play an important role in monitoring and regulation of plant species in trade, supporting biodiversity conservation efforts, and in ensuring that plant products are unadulterated, contributing to consumer protection.     

Genome skimming by shotgun sequencing helps resolve the phylogeny of a pantropical tree family

Whole genome sequencing is helping generate robust phylogenetic hypotheses for a range of taxonomic groups that were previously recalcitrant to classical molecular phylogenetic approaches. As a case study, we performed a shallow shotgun sequencing of eight species in the tropical tree family Chrysobalanaceae to retrieve large fragments of high‐copy number DNA regions and test the potential of these regions for phylogeny reconstruction. We were able to assemble the nuclear ribosomal cluster (nrDNA), the complete plastid genome (ptDNA) and a large fraction of the mitochondrial genome (mtDNA) with approximately 1000×, 450× and 120× sequencing depth respectively. The phylogenetic tree obtained with ptDNA resolved five of the seven internal nodes. In contrast, the tree obtained with mtDNA and nrDNA data were largely unresolved. This study demonstrates that genome skimming is a cost‐effective approach and shows potential in plant molecular systematics within Chrysobalanaceae and other under‐studied groups.     

FIND:从下一代单端测序数据中快速查找Indel的方法

目的:针对下一代测序数据,尤其是单端测序数据,研究快速、准确查找Indel的方法。方法:先与全基因组参考序列进行快速比对,筛选出包含Indel的序列;再对这些序列进行双向的二次比对,确定Indel长度;最后借助长度信息在锁定范围内查找Indel的确切位置和相关信息。结果:本文成功构建FIND(Fast INDel detection system)系统,用于从单端测序数据中查找Indel信息。以模拟测序数据作为测试数据,在12X测试数据情况下,FIND的灵敏度和特异性分别为87.71%和99.66%,而且该性能还随着测序倍数的增加而提升。结论:充分利用比对过程获取的信息,在确定Indle长度的同时也确定出其大致位置,最终在局部范围内实现对单端测序数据中Indle的快速而准确的查找。     

Reprint of: Using nuclear gene data for plant phylogenetics: Progress and prospects

The paper reviews the current state of low and single copy nuclear markers that have been applied successfully in plant phylogenetics to date, and discusses case studies highlighting the potential of massively parallel high throughput or next-generation sequencing (NGS) approaches for molecular phylogenetic and evolutionary investigations. The current state, prospects and challenges of specific single- or low-copy plant nuclear markers as well as phylogenomic case studies are presented and evaluated.     

Using nuclear gene data for plant phylogenetics: Progress and prospects

The paper reviews the current state of low and single copy nuclear markers that have been applied successfully in plant phylogenetics to date, and discusses case studies highlighting the potential of massively parallel high throughput or next-generation sequencing (NGS) approaches for molecular phylogenetic and evolutionary investigations. The current state, prospects and challenges of specific single- or low-copy plant nuclear markers as well as phylogenomic case studies are presented and evaluated.     

Phylogenomic analyses reveal intractable evolutionary history of a temperate bamboo genus (Poaceae: Bambusoideae)

Shibataea is a genus of temperate bamboos(Poaceae:Bambusoideae)endemic to China,but little is known about its phylogenetic position and interspecific relationships.To elucidate the phylogenetic relationship of the bamboo genus Shibataea,we performed genome-scale phylogenetic analysis of all seven species and one variety of the genus using double digest restriction-site associated DNA sequencing(dd RAD-seq)and whole plastid genomes generated using genome skimming.Our phylogenomic analyses based on dd RAD-seq and plastome data congruently recovered Shibataea as monophyletic.The nuclear data resolved S.hispida as the earliest diverged species,followed by S.chinensis,while the rest of Shibataea can be further divided into two clades.However,the plastid and nuclear topologies conflict significantly.By comparing the results of network analysis and topologies reconstructed from different datasets,we identify S.kumasasa as the most admixed species,which may be caused by incomplete lineage sorting(ILS)or interspecific gene flow with four sympatric species.This study highlights the power of dd RAD and plastome data in resolving complex relationships in the intractable bamboo genus.     

Effects of GC Bias in Next-Generation-Sequencing Data on De Novo Genome Assembly

Next-generation-sequencing (NGS) has revolutionized the field of genome assembly because of its much higher data throughput and much lower cost compared with traditional Sanger sequencing. However, NGS poses new computational challenges to de novo genome assembly. Among the challenges, GC bias in NGS data is known to aggravate genome assembly. However, it is not clear to what extent GC bias affects genome assembly in general. In this work, we conduct a systematic analysis on the effects of GC bias on genome assembly. Our analyses reveal that GC bias only lowers assembly completeness when the degree of GC bias is above a threshold. At a strong GC bias, the assembly fragmentation due to GC bias can be explained by the low coverage of reads in the GC-poor or GC-rich regions of a genome. This effect is observed for all the assemblers under study. Increasing the total amount of NGS data thus rescues the assembly fragmentation because of GC bias. However, the amount of data needed for a full rescue depends on the distribution of GC contents. Both low and high coverage depths due to GC bias lower the accuracy of assembly. These pieces of information provide guidance toward a better de novo genome assembly in the presence of GC bias.     

Hybrid assembly of ultra-long Nanopore reads augmented with 10x-Genomics contigs: Demonstrated with a human genome

The 3rd generation of sequencing (3GS) technologies generate ultra-long reads (up to 1 Mb), which makes it possible to eliminate gaps and effectively resolve repeats in genome assembly. However, the 3GS technologies suffer from the high base-level error rates (15%–40%) and high sequencing costs. To address these issues, the hybrid assembly strategy, which utilizes both 3GS reads and inexpensive NGS (next generation sequencing) short reads, was invented. Here, we use 10×-Genomics® technology, which integrates a novel bar-coding strategy with Illumina® NGS with an advantage of revealing long-range sequence information, to replace common NGS short reads for hybrid assembly of long erroneous 3GS reads. We demonstrate the feasibility of integrating the 3GS with 10×-Genomics technologies for a new strategy of hybrid de novo genome assembly by utilizing DBG2OLC and Sparc software packages, previously developed by the authors for regular hybrid assembly. Using a human genome as an example, we show that with only 7× coverage of ultra-long Nanopore® reads, augmented with 10× reads, our approach achieved nearly the same level of quality, compared with non-hybrid assembly with 35× coverage of Nanopore reads. Compared with the assembly with 10×-Genomics reads alone, our assembly is gapless with slightly high cost. These results suggest that our new hybrid assembly with ultra-long 3GS reads augmented with 10×-Genomics reads offers a low-cost (less than ¼ the cost of the non-hybrid assembly) and computationally light-weighted (only took 109 calendar hours with peak memory-usage = 61GB on a dual-CPU office workstation) solution for extending the wide applications of the 3GS technologies.     

Systematic Design of 18S rRNA Gene Primers for Determining Eukaryotic Diversity in Microbial Consortia

High-throughput sequencing of ribosomal RNA gene (rDNA) amplicons has opened up the door to large-scale comparative studies of microbial community structures. The short reads currently produced by massively parallel sequencing technologies make the choice of sequencing region crucial for accurate phylogenetic assignments. While for 16S rDNA, relevant regions have been well described, no truly systematic design of 18S rDNA primers aimed at resolving eukaryotic diversity has yet been reported. Here we used 31,862 18S rDNA sequences to design a set of broad-taxonomic range degenerate PCR primers. We simulated the phylogenetic information that each candidate primer pair would retrieve using paired- or single-end reads of various lengths, representing different sequencing technologies. Primer pairs targeting the V4 region performed best, allowing discrimination with paired-end reads as short as 150 bp (with 75% accuracy at genus level). The conditions for PCR amplification were optimised for one of these primer pairs and this was used to amplify 18S rDNA sequences from isolates as well as from a range of environmental samples which were then Illumina sequenced and analysed, revealing good concordance between expected and observed results. In summary, the reported primer sets will allow minimally biased assessment of eukaryotic diversity in different microbial ecosystems.     

SMRT sequencing only de novo assembly of the sugar beet (Beta vulgaris) chloroplast genome

Background

Third generation sequencing methods, like SMRT (Single Molecule, Real-Time) sequencing developed by Pacific Biosciences, offer much longer read length in comparison to Next Generation Sequencing (NGS) methods. Hence, they are well suited for de novo- or re-sequencing projects. Sequences generated for these purposes will not only contain reads originating from the nuclear genome, but also a significant amount of reads originating from the organelles of the target organism. These reads are usually discarded but they can also be used for an assembly of organellar replicons. The long read length supports resolution of repetitive regions and repeats within the organelles genome which might be problematic when just using short read data. Additionally, SMRT sequencing is less influenced by GC rich areas and by long stretches of the same base.

Results

We describe a workflow for a de novo assembly of the sugar beet (Beta vulgaris ssp. vulgaris) chloroplast genome sequence only based on data originating from a SMRT sequencing dataset targeted on its nuclear genome. We show that the data obtained from such an experiment are sufficient to create a high quality assembly with a higher reliability than assemblies derived from e.g. Illumina reads only. The chloroplast genome is especially challenging for de novo assembling as it contains two large inverted repeat (IR) regions. We also describe some limitations that still apply even though long reads are used for the assembly.

Conclusions

SMRT sequencing reads extracted from a dataset created for nuclear genome (re)sequencing can be used to obtain a high quality de novo assembly of the chloroplast of the sequenced organism. Even with a relatively small overall coverage for the nuclear genome it is possible to collect more than enough reads to generate a high quality assembly that outperforms short read based assemblies. However, even with long reads it is not always possible to clarify the order of elements of a chloroplast genome sequence reliantly which we could demonstrate with Fosmid End Sequences (FES) generated with Sanger technology. Nevertheless, this limitation also applies to short read sequencing data but is reached in this case at a much earlier stage during finishing.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0726-6) contains supplementary material, which is available to authorized users.     

The De Novo Assembly of Mitochondrial Genomes of the Extinct Passenger Pigeon (Ectopistes migratorius) with Next Generation Sequencing

The information from ancient DNA (aDNA) provides an unparalleled opportunity to infer phylogenetic relationships and population history of extinct species and to investigate genetic evolution directly. However, the degraded and fragmented nature of aDNA has posed technical challenges for studies based on conventional PCR amplification. In this study, we present an approach based on next generation sequencing to efficiently sequence the complete mitochondrial genome (mitogenome) of two extinct passenger pigeons (Ectopistes migratorius) using de novo assembly of massive short (90 bp), paired-end or single-end reads. Although varying levels of human contamination and low levels of postmortem nucleotide lesion were observed, they did not impact sequencing accuracy. Our results demonstrated that the de novo assembly of shotgun sequence reads could be a potent approach to sequence mitogenomes, and offered an efficient way to infer evolutionary history of extinct species.     

Comparison of Hepatocellular Carcinoma miRNA Expression Profiling as Evaluated by Next Generation Sequencing and Microarray

MicroRNA (miRNA) expression profiling has proven useful in diagnosing and understanding the development and progression of several diseases. Microarray is the standard method for analyzing miRNA expression profiles; however, it has several disadvantages, including its limited detection of miRNAs. In recent years, advances in genome sequencing have led to the development of next-generation sequencing (NGS) technologies, which significantly advance genome sequencing speed and discovery. In this study, we compared the expression profiles obtained by next generation sequencing (NGS) with the profiles created using microarray to assess if NGS could produce a more accurate and complete miRNA profile. Total RNA from 14 hepatocellular carcinoma tumors (HCC) and 6 matched non-tumor control tissues were sequenced with Illumina MiSeq 50-bp single-end reads. Micro RNA expression profiles were estimated using miRDeep2 software. As a comparison, miRNA expression profiles for 11 out of 14 HCCs were also established by microarray (Agilent human microRNA microarray). The average total sequencing exceeded 2.2 million reads per sample and of those reads, approximately 57% mapped to the human genome. The average correlation for miRNA expression between microarray and NGS and subtraction were 0.613 and 0.587, respectively, while miRNA expression between technical replicates was 0.976. The diagnostic accuracy of HCC, p-value, and AUC were 90.0%, 7.22×10⁻⁴, and 0.92, respectively. In summary, NGS created an miRNA expression profile that was reproducible and comparable to that produced by microarray. Moreover, NGS discovered novel miRNAs that were otherwise undetectable by microarray. We believe that miRNA expression profiling by NGS can be a useful diagnostic tool applicable to multiple fields of medicine.     

Coverage-based consensus calling (CbCC) of short sequence reads and comparison of CbCC results to identify SNPs in chickpea (Cicer arietinum; Fabaceae), a crop species without a reference genome

? Premise of the study: Next-generation sequencing (NGS) technologies are frequently used for resequencing and mining of single nucleotide polymorphisms (SNPs) by comparison to a reference genome. In crop species such as chickpea (Cicer arietinum) that lack a reference genome sequence, NGS-based SNP discovery is a challenge. Therefore, unlike probability-based statistical approaches for consensus calling and by comparison with a reference sequence, a coverage-based consensus calling (CbCC) approach was applied and two genotypes were compared for SNP identification. ? Methods: A CbCC approach is used in this study with four commonly used short read alignment tools (Maq, Bowtie, Novoalign, and SOAP2) and 15.7 and 22.1 million Illumina reads for chickpea genotypes ICC4958 and ICC1882, together with the chickpea trancriptome assembly (CaTA). ? Key results: A nonredundant set of 4543 SNPs was identified between two chickpea genotypes. Experimental validation of 224 randomly selected SNPs showed superiority of Maq among individual tools, as 50.0% of SNPs predicted by Maq were true SNPs. For combinations of two tools, greatest accuracy (55.7%) was reported for Maq and Bowtie, with a combination of Bowtie, Maq, and Novoalign identifying 61.5% true SNPs. SNP prediction accuracy generally increased with increasing reads depth. ? Conclusions: This study provides a benchmark comparison of tools as well as read depths for four commonly used tools for NGS SNP discovery in a crop species without a reference genome sequence. In addition, a large number of SNPs have been identified in chickpea that would be useful for molecular breeding.     

An update on chloroplast genomes

Plant cells possess two more genomes besides the central nuclear genome: the mitochondrial genome and the chloroplast genome (or plastome). Compared to the gigantic nuclear genome, these organelle genomes are tiny and are present in high copy number. These genomes are less prone to recombination and, therefore, retain signatures of their age to a much better extent than their nuclear counterparts. Thus, they are valuable phylogenetic tools, giving useful information about the relative age and relatedness of the organisms possessing them. Unlike animal cells, mitochondrial genomes of plant cells are characterized by large size, extensive intramolecular recombination and low nucleotide substitution rates and are of limited phylogenetic utility. Chloroplast genomes, on the other hand, show resemblance to animal mitochondrial genomes in terms of phylogenetic utility and are more relevant and useful in case of plants. Conservation in gene order, content and lack of recombination make the plastome an attractive tool for plant phylogenetic studies. Their importance is reflected in the rapid increase in the availability of complete chloroplast genomes in the public databases. This review aims to summarize the progress in chloroplast genome research since its inception and tries to encompass all related aspects. Starting with a brief historical account, it gives a detailed account of the current status of chloroplast genome sequencing and touches upon RNA editing, ycfs, molecular phylogeny, DNA barcoding as well as gene transfer to the nucleus.     

Identification of Optimum Sequencing Depth Especially for De Novo Genome Assembly of Small Genomes Using Next Generation Sequencing Data

Next Generation Sequencing (NGS) is a disruptive technology that has found widespread acceptance in the life sciences research community. The high throughput and low cost of sequencing has encouraged researchers to undertake ambitious genomic projects, especially in de novo genome sequencing. Currently, NGS systems generate sequence data as short reads and de novo genome assembly using these short reads is computationally very intensive. Due to lower cost of sequencing and higher throughput, NGS systems now provide the ability to sequence genomes at high depth. However, currently no report is available highlighting the impact of high sequence depth on genome assembly using real data sets and multiple assembly algorithms. Recently, some studies have evaluated the impact of sequence coverage, error rate and average read length on genome assembly using multiple assembly algorithms, however, these evaluations were performed using simulated datasets. One limitation of using simulated datasets is that variables such as error rates, read length and coverage which are known to impact genome assembly are carefully controlled. Hence, this study was undertaken to identify the minimum depth of sequencing required for de novo assembly for different sized genomes using graph based assembly algorithms and real datasets. Illumina reads for E.coli (4.6 MB) S.kudriavzevii (11.18 MB) and C.elegans (100 MB) were assembled using SOAPdenovo, Velvet, ABySS, Meraculous and IDBA-UD. Our analysis shows that 50X is the optimum read depth for assembling these genomes using all assemblers except Meraculous which requires 100X read depth. Moreover, our analysis shows that de novo assembly from 50X read data requires only 6–40 GB RAM depending on the genome size and assembly algorithm used. We believe that this information can be extremely valuable for researchers in designing experiments and multiplexing which will enable optimum utilization of sequencing as well as analysis resources.