Looking for therapeutic antibodies in next-generation sequencing repositories

ABSTRACT

Recently it has become possible to query the great diversity of natural antibody repertoires using next-generation sequencing (NGS). These methods are capable of producing millions of sequences in a single experiment. Here we compare clinical-stage therapeutic antibodies to the ~1b sequences from 60 independent sequencing studies in the Observed Antibody Space database, which includes antibody sequences from NGS analysis of immunoglobulin gene repertoires. Of 242 post-Phase 1 antibodies, we found 16 with sequence identity matches of 95% or better for both heavy and light chains. There are also 54 perfect matches to therapeutic CDR-H3 regions in the NGS outputs, suggesting a nontrivial amount of convergence between naturally observed sequences and those developed artificially. This has potential implications for both the legal protection of commercial antibodies and the discovery of antibody therapeutics.     

jMHC: software assistant for multilocus genotyping of gene families using next-generation amplicon sequencing

Genotyping of multilocus gene families, such as the major histocompatibility complex (MHC), may be challenging because of problems with assigning alleles to loci and copy number variation among individuals. Simultaneous amplification and genotyping of multiple loci may be necessary, and in such cases, next-generation deep amplicon sequencing offers a great promise as a genotyping method of choice. Here, we describe jMHC, a computer program developed for analysing and assisting in the visualization of deep amplicon sequencing data. Software operates on FASTA files; therefore, output from any sequencing technology may be used. jMHC was designed specifically for MHC studies but it may be useful for analysing amplicons derived from other multigene families or for genotyping other polymorphic systems. The program is written in Java with user-friendly graphical interface (GUI) and can be run on Microsoft Windows, Linux OS and Mac OS.     

基于新一代高通量测序的环境微生物转录组学研究进展

环境微生物转录组学是一门新兴学科,它以复杂环境样品中的微生物mRNA为研究对象,利用近年兴起的RNA-Seq高通量测序技术,在整体水平上对环境微生物的基因表达水平和调控规律进行研究.本文概述了环境微生物转录组研究从样品的采集保存、RNA提取、mRNA的富集、cDNA合成直到高通量测序及数据分析的基本流程.总结了该技术面临的主要瓶颈:环境样品mRNA含量低、腐植酸等干扰杂质多、rRNA去除程度有限.针对RNA的提取、纯化以及mRNA的富集这些重点步骤,详细阐述了近年来在提高mRNA的得率与纯度上的方法学进展.重点介绍了高通量测序数据的处理及分析方法,从测序数据的质量控制、序列组装、rRNA的鉴定及去除、功能基因注释及分类到差异表达基因的鉴定.最后总结了近年来环境微生物转录组学在新基因的发现、不同环境条件下微生物的基因表达及调控规律研究、有机物的代谢路径分析等3个主要研究领域的广泛应用.随着测序技术及生物信息学分析工具的发展进步,环境微生物转录组学将具有更广阔的应用前景.     

新一代测序技术在植物转录组研究中的应用

随着DNA测序技术的发展,新一代测序技术以其高通量、低成本的特点,成为越来越多的生物学研究者在开展工作时的首选。在所有的新一代测序技术中,454测序系统是最早实现商业化且发展相对成熟的一种,目前被广泛的应用于各个领域的生物学研究中。文章以454测序系统为例,综述了新一代测序系统的原理、优缺点,及其在植物转录组研究中的应用,并对其在植物研究领域中可能的发展应用方向进行了展望。     

Evolutionary insight from whole-genome sequencing of experimentally evolved microbes

Experimental evolution (EE) combined with whole‐genome sequencing (WGS) has become a compelling approach to study the fundamental mechanisms and processes that drive evolution. Most EE‐WGS studies published to date have used microbes, owing to their ease of propagation and manipulation in the laboratory and relatively small genome sizes. These experiments are particularly suited to answer long‐standing questions such as: How many mutations underlie adaptive evolution, and how are they distributed across the genome and through time? Are there general rules or principles governing which genes contribute to adaptation, and are certain kinds of genes more likely to be targets than others? How common is epistasis among adaptive mutations, and what does this reveal about the variety of genetic routes to adaptation? How common is parallel evolution, where the same mutations evolve repeatedly and independently in response to similar selective pressures? Here, we summarize the significant findings of this body of work, identify important emerging trends and propose promising directions for future research. We also outline an example of a computational pipeline for use in EE‐WGS studies, based on freely available bioinformatics tools.     

Milk microbiome signatures of subclinical mastitis-affected cattle analysed by shotgun sequencing

Aims: Metagenomic analysis of milk samples collected from Kankrej, Gir (Bos indicus) and crossbred (Bos taurus × B. indicus) cattle harbouring subclinical mastitis was carried out by next‐generation sequencing 454 GS‐FLX technology to elucidate the microbial community structure of cattle milk. Methods and Results: Milk samples from Kankrej, Gir and crossbred cattle were subjected to metagenomic profiling by pyrosequencing. The Metagenomic analysis produced 63·07, 11·09 and 7·87 million base pairs (Mb) of sequence data, assembled in 264 798, 56 114 and 36 762 sequences with an average read length of 238, 197 and 214 nucleotides in Kankrej, Gir and crossbred cattle, respectively. Phylogenetic and metabolic profiles by the web‐based tool MG‐RAST revealed that the members of Enterobacteriales were predominant in mastitic milk followed by Pseudomonadales, Bacillales and Lactobacillales. Around 56 different species with varying abundance were detected in the subclinically infected milk. Escherichia coli was found to be the most predominant species in Kankrej and Gir cattle followed by Pseudomonas aeruginosa, Pseudomonas mendocina, Shigella flexneri and Bacillus cereus. In crossbred cattle, Staphylococcus aureus followed by Klebsiella pneumoniae, Staphylococcus epidermidis and E. coli were detected in descending order. Metabolic profiling indicated fluoroquinolones, methicillin, copper, cobalt–zinc–cadmium as the groups of antibiotics and toxic compounds to which the organisms showed resistance. Sequences indicating potential of organisms exhibiting multidrug resistance against antibiotics and resistance to toxic compounds were also present. Interestingly, presence of bacteriophages against Staph. aureus, E. coli, Enterobacter and Yersinia species was also observed. Conclusions: The analysis identified potential infectious organisms in mastitis, resistance of organisms to antibiotics and chemical compounds and the natural resistance potential of dairy cows. Significance and Impact of the Study: The findings of this study may help in formulating strategies for the prevention and treatment of mastitis in dairy animals and consequently in reducing economic losses incurred because of it.     

Development and characterization of polymorphic microsatellite markers for Neolitsea sericea using Illumina paired‐end draft sequencing data

Simple sequence repeat (SSR) markers were developed and characterized for Neolitsea sericea (Bl.) Koidz. (Lauraceae). Out of 196 designed primer pairs, a total of 144 pairs showed amplification, of which 44 had clear and stable chromatograms. Polymorphism of these 44 loci was tested using 32 individuals sampled from a single population of N. sericea. The number of alleles and the polymorphism information content varied from 3 to 12 and 0.271 to 0.853, respectively. A significant departure from the Hardy‐Weinberg equilibrium was observed in one of the 44 loci. These SSR markers are useful for population genetic studies and parentage analysis in N. sericea, which is one of the most common evergreen species in coastal Pinus thunbergii forests in central‐western Japan.     

Museum genomics: low-cost and high-accuracy genetic data from historical specimens

Natural history collections are unparalleled repositories of geographical and temporal variation in faunal conditions. Molecular studies offer an opportunity to uncover much of this variation; however, genetic studies of historical museum specimens typically rely on extracting highly degraded and chemically modified DNA samples from skins, skulls or other dried samples. Despite this limitation, obtaining short fragments of DNA sequences using traditional PCR amplification of DNA has been the primary method for genetic study of historical specimens. Few laboratories have succeeded in obtaining genome-scale sequences from historical specimens and then only with considerable effort and cost. Here, we describe a low-cost approach using high-throughput next-generation sequencing to obtain reliable genome-scale sequence data from a traditionally preserved mammal skin and skull using a simple extraction protocol. We show that single-nucleotide polymorphisms (SNPs) from the genome sequences obtained independently from the skin and from the skull are highly repeatable compared to a reference genome.     

RAD in the realm of next-generation sequencing technologies

The first North American RAD Sequencing and Genomics Symposium, sponsored by Floragenex (http://www.floragenex.com/radmeeting/), took place in Portland, Oregon (USA) on 19 April 2011. This symposium was convened to promote and discuss the use of restriction-site-associated DNA (RAD) sequencing technologies. RAD sequencing is one of several strategies recently developed to increase the power of data generated via short-read sequencing technologies by reducing their complexity (Baird et al. 2008; Huang et al. 2009; Andolfatto et al. 2011; Elshire et al. 2011). RAD sequencing, as a form of genotyping by sequencing, has been effectively applied in genetic mapping and quantitative trait loci (QTL) analyses in a range of organisms including nonmodel, genetically highly heterogeneous organisms (Table 1; Baird et al. 2008; Baxter et al. 2011; Chutimanitsakun et al. 2011; Pfender et al. 2011). RAD sequencing has recently found applications in phylogeography (Emerson et al. 2010) and population genomics (Hohenlohe et al. 2010). Considering the diversity of talks presented during this meeting, more developments are to be expected in the very near future.     

BIGpre: a quality assessment package for next-generation sequencing data

The emergence of next-generation sequencing (NGS) technologies has significantly improved sequencing throughput and reduced costs. However, the short read length, duplicate reads and massive volume of data make the data processing much more difficult and complicated than the first-generation sequencing technology. Although there are some software packages developed to assess the data quality, those packages either are not easily available to users or require bioinformatics skills and computer resources. Moreover, almost all the quality assessment software currently available didn’t taken into account the sequencing errors when dealing with the duplicate assessment in NGS data. Here, we present a new user-friendly quality assessment software package called BIGpre, which works for both Illumina and 454 platforms. BIGpre contains all the functions of other quality assessment software, such as the correlation between forward and reverse reads, read GC-content distribution, and base Ns quality. More importantly, BIGpre incorporates associated programs to detect and remove duplicate reads after taking sequencing errors into account and trimming low quality reads from raw data as well. BIGpre is primarily written in Perl and integrates graphical capability from the statistics package R. This package produces both tabular and graphical summaries of data quality for sequencing datasets from Illumina and 454 platforms. Processing hundreds of millions reads within minutes, this package provides immediate diagnostic information for user to manipulate sequencing data for downstream analyses. BIGpre is freely available at http://bigpre.sourceforge.net/.     

An assembly and alignment-free method of phylogeny reconstruction from next-generation sequencing data

Background

Next-generation sequencing technologies are rapidly generating whole-genome datasets for an increasing number of organisms. However, phylogenetic reconstruction of genomic data remains difficult because de novo assembly for non-model genomes and multi-genome alignment are challenging.

Results

To greatly simplify the analysis, we present an Assembly and Alignment-Free (AAF) method (https://sourceforge.net/projects/aaf-phylogeny) that constructs phylogenies directly from unassembled genome sequence data, bypassing both genome assembly and alignment. Using mathematical calculations, models of sequence evolution, and simulated sequencing of published genomes, we address both evolutionary and sampling issues caused by direct reconstruction, including homoplasy, sequencing errors, and incomplete sequencing coverage. From these results, we calculate the statistical properties of the pairwise distances between genomes, allowing us to optimize parameter selection and perform bootstrapping. As a test case with real data, we successfully reconstructed the phylogeny of 12 mammals using raw sequencing reads. We also applied AAF to 21 tropical tree genome datasets with low coverage to demonstrate its effectiveness on non-model organisms.

Conclusion

Our AAF method opens up phylogenomics for species without an appropriate reference genome or high sequence coverage, and rapidly creates a phylogenetic framework for further analysis of genome structure and diversity among non-model organisms.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1647-5) contains supplementary material, which is available to authorized users.