用于蜜蜂和熊蜂肠道微生物分类的细菌16S rRNA数据库优化

蜜蜂和熊蜂是重要的传粉昆虫, 对农业生产及生态平衡的维持具有重要作用。近年来, 研究发现蜜蜂及熊蜂肠道内含有大量微生物, 其组成简单、特异。正常的肠道微生物群落对蜜蜂的生长、激素调节、致病菌抵抗等具有重要作用。随着高通量测序的发展, 研究者们也可快速获得传粉蜂肠道微生物组成, 这给生物多样性和物种保护及蜂类健康等的研究带来了便捷。但是由于蜜蜂和熊蜂肠道微生物群落均由特殊菌种组成, 目前的细菌16S rRNA数据库无法对其进行准确的分类, 并且部分东方蜜蜂(Apis cerana)特有的肠道微生物菌种缺乏16S rRNA序列信息。本文从来源于5个不同省份的东方蜜蜂肠道中分离得到在东方蜜蜂中普遍含有的Apibacter菌属纯菌, 获取其全长16S rRNA序列, 并对目前蜜蜂和熊蜂肠道的5个核心菌种的分类进行了综述, 对其分类和命名进行了修正。根据蜜蜂肠道微生物的明确分类, 在目前常用的SILVA细菌分类数据库基础之上对其进行了命名及分类优化, 并加入东方蜜蜂中普遍含有的Apibacter序列, 从而获得了优化数据库Bee Gut Microbiota-Database (BGM-Db)。通过1组东方蜜峰及1组西方蜜蜂(Apis mellifera)的肠道菌群高通量测序结果, 分析不同数据库的表现, 我们发现相比于SILVA和Ribosomal Database Project (RDP), BGM-Db对蜜蜂肠道16S rRNA高通量测序短序列实现了菌种级别的分类, 分辨率更高。     

16S rRNA测序技术在肠道微生物中的应用研究进展

16S rRNA测序是高通量测序依赖的肠道微生物研究方法之一,该方法可以对肠道微生物中的所有菌种进行精确定量,因此正逐渐成为研究肠道微生物菌种丰度变化的主流。肠道微生物16S rRNA测序的应用过程中有两个问题至关重要,一是如何根据需要选择测序方案;二是面对高通量测序得到的海量数据,如何进行生物信息学分析,以得到具有生物学意义的结果。从测序平台、测序片段、测序数据量的选择3个方面讨论了如何选择测序方案,并从序列聚类与注释、群落结构分析、关键分类单位的筛选与功能分析等方面对目前常用的生物信息学分析手段进行综述。     

中国人群肠道微生物鸟枪法宏基因组测序研究进展

肠道微生物与人类健康的相关性研究仍然是当前生命科学研究领域的前沿热点之一。不依赖培养的 16S rRNA基因高通量测序是当前的主要研究手段。但随着测序成本的降低和数据分析方法的日渐成熟,宏基因组鸟枪法测序因具有信息量更大、更全等优势,将逐渐成为今后一段时间内研究肠道微生物组的重要手段。美国在人类微生物组计划的资助下,对30 805份样品进行了肠道微生物宏基因测序分析。通过NCBI PubMed和SRA数据库检索,共发现72项研究收集了约10 000份中国人的肠道样品用于宏基因组测序。但到目前为止,仅56项研究进行了公开发表,其中与代谢性疾病相关的文献16篇,与感染和免疫性疾病相关的文献16篇,与心脑血管疾病相关的文献12篇。由于采样地点以北京、广州、上海等大城市为主,测序平台和测序分析方法均存在较大差异,且大部分研究仍以相关性分析为主,相关研究成果在临床疾病诊疗中所发挥的作用仍非常有限。规范采样方法、标准化测序平台和数据分析流程,开展多中心平行研究将有助于数据整合和比较分析。同时,结合使用转录组、蛋白质组和培养组学等多组学方法开展功能验证和分子作用机制研究,将有利于更好地将肠道微生物研究成果服务于临床疾病诊疗。     

DNA提取对微生物多样性测序分析的影响

运用高通量测序技术分析复杂样品中微生物种群的变化情况,已经成为目前微生物研究领域的热点问题之一。而微生物的样品准备,如DNA提取和16S可变区的扩增等,对于测序完成后的数据分析以及微生物原始群落组成的影响是至关重要的。采用国产试剂盒(天根土壤微生物基因组提取试剂盒)和进口试剂盒(MOBIO土壤微生物基因组提取试剂盒)分别对土壤样品和羊瘤胃食糜样品进行DNA提取。然后选取总DNA起始量为25ng,对16S V3可变区进行PCR扩增和文库构建,最后通过数据分析比较不同试剂盒提取的DNA对微生物多样性变化的影响,包括OTU数目、稀释曲线、微生物数量及物种种类等。研究发现,在相同DNA模板量和PCR条件下,进口试剂盒提取的DNA能够获得更多的微生物种类。     

DNA聚合酶对PacBio SMRT测序结果影响的评价

目的评估不同DNA聚合酶是否会对以16SrRNA全长为测序靶点的肠道微生物多样性研究结果产生影响。方法用美国太平洋公司的三代测序仪(PacBio single molecule real-time sequencing technology)对3份分别采用KAPA HiFi^TM HotStart DNA聚合酶和PCRBIO HotStart DNA聚合酶扩增的军犬粪便样品进行精确至"种"水平的测序分析。结果经配对Mann-Whitney U检验显示,不同DNA聚合酶扩增的同一样品在门、属和种水平上差异无统计学意义(P>0.05),然而在某些相对含量较少的操作分类单元(OTU)上,其扩增效率存在差异。经基于非加权UniFrac距离的非加权组平均法聚类分析和基于加权UniFrac距离的非参数多元方差分析发现不同DNA聚合酶扩增的同一样品其多样性差异无统计学意义(P>0.05)。结论 KAPA HiFi^TM HotStart DNA聚合酶和PCRBIO HotStart DNA聚合酶虽对模板DNA扩增存在一定的偏好性,但该偏好性不影响PacBio SMRT测序结果。     

北京地区四个豹猫亚种群肠道菌群的组成

野生动物的肠道微生物组成受食物资源和遗传属性的影响较大, 为了解北京地区小型猫科动物肠道菌群组成特点及其影响因素, 本研究通过扩增细菌16S rRNA的V3‒V4高变区进行高通量测序, 对云蒙山、云峰山、松山、百花山4个区域的豹猫(Prionailurus bengalensis)亚种群进行肠道菌群组成分析。结果表明, 在门水平上, 豹猫的肠道优势菌群主要由厚壁菌门(相对多度52.40%)、变形菌门(25.18%)、放线菌门(9.07%)、拟杆菌门(8.17%)和梭杆菌门(4.74%)组成。在属水平上, 相对多度最高的前5个属为假单胞菌属(Pseudomonas, 13.37%)、布劳特氏菌属(Blautia, 11.20%)、梭菌属(Clostridium_sensu_stricto_1, 9.10%)、消化梭菌属(Peptoclostridium, 8.62%)、乳杆菌属(Lactobacillus, 6.08%), 共约占总多度的50%。各区域豹猫亚种群的肠道菌群β多样性不存在显著差异, 松山区域的ACE指数和Chao 1指数与云蒙山和云峰山存在显著差异。鉴于松山亚种群的遗传结构与其他区域有所不同, 而4个区域的气候类型和豹猫食物构成相似性高, 推测该亚种群的肠道菌群主要受遗传结构分化的影响, 对此还需进一步研究。     

转基因鲤鱼与对照鲤肠道微生物群落差异研究

以转“全鱼”生长激素基因鲤(Cyprinus carpio L.)和野生对照鲤为对象, 采用454高通量测序技术对其肠道微生物16S rRNA基因进行测序并分析了3个不同发育阶段微生物群落结构的变化, 进而探讨了转基因鲤与对照鲤肠道微生物群落的差异。基于转基因鲤和对照鲤不同发育时期(6日龄、2月龄、5月龄)肠道微生物群落组成的DCA排序分析显示, 2月龄转基因鲤与对照鲤肠道微生物组成不同。Alpha多样性及均匀度都显示转基因鲤肠道微生物多样性高于对照鲤。从门水平的比较分析发现, 转基因鲤肠道中存在较多的厚壁菌门(Firmicutes)细菌, 而对照鲤中拟杆菌门(Bacteroidetes)细菌较多, 其中2月龄转基因鲤肠道内Bacteroidetes/Firmicutes比值低于对照鲤。研究结果表明, 在所分析的3个发育时期, 转基因鲤的肠道微生物组成与对照鲤相比发生了改变, 且在2月龄时存在差异。该研究为进一步揭示转基因鱼肠道微生物与宿主的相互影响和作用机制提供了很好的参考。     

16S rRNA基因高变区V4和V3−V4及测序深度对油藏细菌菌群分析的影响

【背景】16S rRNA基因测序是当前研究微生物群落组成及其分布的重要手段。【目的】揭示16S rRNA基因高变区V4 (515-806)和V3-V4 (338-806)及测序深度(1-2万条和10万条)对油藏微生物细菌群落组成和多样性分析的影响。【方法】所用油水样细菌16SrRNA基因拷贝数为(6.51±0.56)×108/L,16SrRNA基因V4区测序使用IlluminaMiSeqPE250测序平台,V3-V4区测序使用MiSeqPE300测序平台。【结果】测序深度达到1-2万条时,V4和V3-V4区测序文库覆盖率均达到99.6%以上,且具有较好的可重复性;V4区测序深度为1-2万和10万时,菌群α多样性指数受测序深度影响不显著;与V4区测序相比,同样测序深度(1-2万)下,V3-V4区测序获得的菌群α多样性指数有所降低。V4测序1-2万与10万获得的菌群中几乎未出现显著性差异微生物类群;同样测序深度(1-2万)下,V4与V3-V4测序相比,优势微生物类群Epsilonproteobacteria(51.37%:64.23%)和Deltaproteobacteria (17.96%:11.40%)相对丰度表现出显著差异。【结论】测序深度达到一定水平,增加测序深度会一定程度上影响菌群α多样性指数,对菌群β多样性分析的影响十分有限;同一测序深度下,V4区与V3-V4区测序获得的细菌菌群α多样性指数明显不同,部分优势微生物类群的相对丰度值之间具有显著性差异。鉴于测序读长的提升和测序成本降低,与V4区测序相比,V3-V4区测序在更低的测序深度下文库覆盖率更高,可提供更多用于反映物种亲缘关系的16S rRNA碱基信息,本文认为V3-V4区测序可作为当下菌群分析的首选区域。     

黎族人肠道微生物群落结构特征及其与饮食关联性

【目的】对采集自海南省白沙地区的黎族健康志愿者肠道菌群进行研究,旨在揭示黎族人肠道微生物群落结构特征及其与饮食的相关性。【方法】以海南省白沙黎族自治县征集的22名志愿者晨便为研究对象,应用基于16S r RNA基因V3–V4可变区的高通量测序技术测定其肠道菌群组成,并与其他民族肠道菌群进行比较分析,详细记录黎族22名志愿者的营养物质摄入情况,探索其肠道微生物群落结构特征及其与饮食的相关性。【结果】在门水平上,拟杆菌门(Bacteroidetes,58.96%)和硬壁菌门(Firmicutes,37.77%)在黎族志愿者肠道内含量最高;在属的水平上,普氏菌属(Prevotella,49.38%)在黎族健康志愿者肠道内含量最高。基于微生物群落α和β多样性的分析结果表明,黎族人肠道菌群与中国其他民族人群肠道菌群呈现出显著差异且α多样性显著低于其他民族,特征性差异菌属为:链型杆菌属(Catenibacterium)、普氏菌属(Prevotella)、巨型球菌属(Megasphaera)、巨单胞菌属(Megamonas)、考拉杆菌属(Phascolarctobacterium)和布劳特氏菌属(Blautia)。基于肠道核心微生物与营养物质相关性的研究显示,普氏粪杆菌(Faecalibacterium prausnitzii)与膳食纤维、Cu、Mg和Mn的摄入量呈现显著正相关,与脂肪和VB2的摄入量呈现显著负相关,而罗氏乳杆菌(Lactobacillus rogosae)与膳食纤维、Zn和Fe的摄入量呈显著正相关,与烟酸摄入量呈显著负相关。【结论】揭示了肠道微生物在不同地域和民族之间的差异,研究结果提供了一种通过膳食来优化菌群结构、调控宿主肠道微生态平衡的新思路。     

肠道菌群的性别二态性及其潜在影响机制

细菌16S rRNA测序产生的大量数据表明,性别或性类固醇会影响人类和啮齿类动物肠道细菌的分类学组成。肠道菌群多样性在婴儿期增加,五岁之后稳定下来,无明显性别差异;而不同生命时期(如青春期、更年期)或性腺切除术等因素均可导致肠道微生物组发生改变,提示肠道微生物中性别二态性差异由性类固醇水平所驱动,性类固醇水平差异可能通过影响肠道粘膜完整性通透性、结合肠道性激素受体、调节β-葡萄糖醛酸酶剂胆汁酸水平等方式影响肠道菌群。本文回顾了新近性别对动物和人类肠道菌群影响的相关研究,对其可能的机制进行综述。     

Shallow shotgun sequencing of the microbiome recapitulates 16S amplicon results and provides functional insights

Prevailing 16S rRNA gene-amplicon methods for characterizing the bacterial microbiome of wildlife are economical, but result in coarse taxonomic classifications, are subject to primer and 16S copy number biases, and do not allow for direct estimation of microbiome functional potential. While deep shotgun metagenomic sequencing can overcome many of these limitations, it is prohibitively expensive for large sample sets. Here we evaluated the ability of shallow shotgun metagenomic sequencing to characterize taxonomic and functional patterns in the faecal microbiome of a model population of feral horses (Sable Island, Canada). Since 2007, this unmanaged population has been the subject of an individual-based, long-term ecological study. Using deep shotgun metagenomic sequencing, we determined the sequencing depth required to accurately characterize the horse microbiome. In comparing conventional vs. high-throughput shotgun metagenomic library preparation techniques, we validate the use of more cost-effective laboratory methods. Finally, we characterize similarities between 16S amplicon and shallow shotgun characterization of the microbiome, and demonstrate that the latter recapitulates biological patterns first described in a published amplicon data set. Unlike for amplicon data, we further demonstrate how shallow shotgun metagenomic data provide useful insights regarding microbiome functional potential which support previously hypothesized diet effects in this study system.     

Improving the standards for gut microbiome analysis of fecal samples: insights from the field biology of Japanese macaques on Yakushima Island

Fecal DNA-based 16S ribosomal RNA (rRNA) gene sequencing using next-generation sequencers allows us to understand the dynamic gut microbiome adaptation of animals to their specific habitats. Conventional techniques of fecal microbiome analysis have been developed within the broad contexts defined by human biology; hence, many of these techniques are not immediately applicable to wild nonhuman primates. In order to establish a standard experimental protocol for the analysis of the gut microbiomes of wild animals, we selected the Japanese macaques (Macaca fuscata yakui) on Yakushima Island. We tested different protocols for each stage of fecal sample processing: storage, DNA extraction, and choice of the sequencing region in the bacterial 16S rRNA gene. We also analyzed the gut microbiome of captive Japanese macaques as the control. The comparison of samples obtained from identical macaques but subjected to different protocols showed that the tested storage methods (RNAlater and lysis buffer) produced effectively the same composition of bacterial operational taxonomic units (OTUs) as the standard frozen storage method, although the relative abundance of each OTU was quantitatively affected. Taxonomic assignment of the detected bacterial groups was also significantly affected by the region being sequenced, indicating that sequencing regions and the corresponding polymerase chain reaction (PCR) primer pairs for the 16S rRNA gene should be carefully selected. This study improves the current standard methods for microbiome analysis in wild nonhuman primates. Japanese macaques were shown to be a suitable model for understanding microbiome adaptation to various environments.     

Reproducibility and quantitation of amplicon sequencing-based detection

To determine the reproducibility and quantitation of the amplicon sequencing-based detection approach for analyzing microbial community structure, a total of 24 microbial communities from a long-term global change experimental site were examined. Genomic DNA obtained from each community was used to amplify 16S rRNA genes with two or three barcode tags as technical replicates in the presence of a small quantity (0.1% wt/wt) of genomic DNA from Shewanella oneidensis MR-1 as the control. The technical reproducibility of the amplicon sequencing-based detection approach is quite low, with an average operational taxonomic unit (OTU) overlap of 17.2%±2.3% between two technical replicates, and 8.2%±2.3% among three technical replicates, which is most likely due to problems associated with random sampling processes. Such variations in technical replicates could have substantial effects on estimating β-diversity but less on α-diversity. A high variation was also observed in the control across different samples (for example, 66.7-fold for the forward primer), suggesting that the amplicon sequencing-based detection approach could not be quantitative. In addition, various strategies were examined to improve the comparability of amplicon sequencing data, such as increasing biological replicates, and removing singleton sequences and less-representative OTUs across biological replicates. Finally, as expected, various statistical analyses with preprocessed experimental data revealed clear differences in the composition and structure of microbial communities between warming and non-warming, or between clipping and non-clipping. Taken together, these results suggest that amplicon sequencing-based detection is useful in analyzing microbial community structure even though it is not reproducible and quantitative. However, great caution should be taken in experimental design and data interpretation when the amplicon sequencing-based detection approach is used for quantitative analysis of the β-diversity of microbial communities.     

Comprehensive simulation of metagenomic sequencing data with non-uniform sampling distribution

Background: Metagenomic sequencing is a complex sampling procedure from unknown mixtures of many genomes. Having metagenome data with known genome compositions is essential for both benchmarking bioinformatics software and for investigating influences of various factors on the data. Compared to data from real microbiome samples or from defined microbial mock community, simulated data with proper computational models are better for the purpose as they provide more flexibility for controlling multiple factors. Methods: We developed a non-uniform metagenomic sequencing simulation system (nuMetaSim) that is capable of mimicking various factors in real metagenomic sequencing to reflect multiple properties of real data with customizable parameter settings. Results: We generated 9 comprehensive metagenomic datasets with different composition complexity from of 203 bacterial genomes and 2 archaeal genomes related with human intestine system. Conclusion: The data can serve as benchmarks for comparing performance of different methods at different situations, and the software package allows users to generate simulation data that can better reflect the specific properties in their scenarios.     

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

One of the major questions in microbial ecology is “who is there?” This question can be answered using various tools, but one of the long-lasting gold standards is to sequence 16S ribosomal RNA (rRNA) gene amplicons generated by domain-level PCR reactions amplifying from genomic DNA. Traditionally, this was performed by cloning and Sanger (capillary electrophoresis) sequencing of PCR amplicons. The advent of next-generation sequencing has tremendously simplified and increased the sequencing depth for 16S rRNA gene sequencing. The introduction of benchtop sequencers now allows small labs to perform their 16S rRNA sequencing in-house in a matter of days. Here, an approach for 16S rRNA gene amplicon sequencing using a benchtop next-generation sequencer is detailed. The environmental DNA is first amplified by PCR using primers that contain sequencing adapters and barcodes. They are then coupled to spherical particles via emulsion PCR. The particles are loaded on a disposable chip and the chip is inserted in the sequencing machine after which the sequencing is performed. The sequences are retrieved in fastq format, filtered and the barcodes are used to establish the sample membership of the reads. The filtered and binned reads are then further analyzed using publically available tools. An example analysis where the reads were classified with a taxonomy-finding algorithm within the software package Mothur is given. The method outlined here is simple, inexpensive and straightforward and should help smaller labs to take advantage from the ongoing genomic revolution.     

Comparison of large-insert,small-insert and pyrosequencing libraries for metagenomic analysis

The development of DNA sequencing methods for characterizing microbial communities has evolved rapidly over the past decades. To evaluate more traditional, as well as newer methodologies for DNA library preparation and sequencing, we compared fosmid, short-insert shotgun and 454 pyrosequencing libraries prepared from the same metagenomic DNA samples. GC content was elevated in all fosmid libraries, compared with shotgun and 454 libraries. Taxonomic composition of the different libraries suggested that this was caused by a relative underrepresentation of dominant taxonomic groups with low GC content, notably Prochlorales and the SAR11 cluster, in fosmid libraries. While these abundant taxa had a large impact on library representation, we also observed a positive correlation between taxon GC content and fosmid library representation in other low-GC taxa, suggesting a general trend. Analysis of gene category representation in different libraries indicated that the functional composition of a library was largely a reflection of its taxonomic composition, and no additional systematic biases against particular functional categories were detected at the level of sequencing depth in our samples. Another important but less predictable factor influencing the apparent taxonomic and functional library composition was the read length afforded by the different sequencing technologies. Our comparisons and analyses provide a detailed perspective on the influence of library type on the recovery of microbial taxa in metagenomic libraries and underscore the different uses and utilities of more traditional, as well as contemporary ‘next-generation'' DNA library construction and sequencing technologies for exploring the genomics of the natural microbial world.     

RiboFR-Seq: a novel approach to linking 16S rRNA amplicon profiles to metagenomes

16S rRNA amplicon analysis and shotgun metagenome sequencing are two main culture-independent strategies to explore the genetic landscape of various microbial communities. Recently, numerous studies have employed these two approaches together, but downstream data analyses were performed separately, which always generated incongruent or conflict signals on both taxonomic and functional classifications. Here we propose a novel approach, RiboFR-Seq (Ribosomal RNA gene flanking region sequencing), for capturing both ribosomal RNA variable regions and their flanking protein-coding genes simultaneously. Through extensive testing on clonal bacterial strain, salivary microbiome and bacterial epibionts of marine kelp, we demonstrated that RiboFR-Seq could detect the vast majority of bacteria not only in well-studied microbiomes but also in novel communities with limited reference genomes. Combined with classical amplicon sequencing and shotgun metagenome sequencing, RiboFR-Seq can link the annotations of 16S rRNA and metagenomic contigs to make a consensus classification. By recognizing almost all 16S rRNA copies, the RiboFR-seq approach can effectively reduce the taxonomic abundance bias resulted from 16S rRNA copy number variation. We believe that RiboFR-Seq, which provides an integrated view of 16S rRNA profiles and metagenomes, will help us better understand diverse microbial communities.     

Short-Read Assembly of Full-Length 16S Amplicons Reveals Bacterial Diversity in Subsurface Sediments

In microbial ecology, a fundamental question relates to how community diversity and composition change in response to perturbation. Most studies have had limited ability to deeply sample community structure (e.g. Sanger-sequenced 16S rRNA libraries), or have had limited taxonomic resolution (e.g. studies based on 16S rRNA hypervariable region sequencing). Here, we combine the higher taxonomic resolution of near-full-length 16S rRNA gene amplicons with the economics and sensitivity of short-read sequencing to assay the abundance and identity of organisms that represent as little as 0.01% of sediment bacterial communities. We used a new version of EMIRGE optimized for large data size to reconstruct near-full-length 16S rRNA genes from amplicons sheared and sequenced with Illumina technology. The approach allowed us to differentiate the community composition among samples acquired before perturbation, after acetate amendment shifted the predominant metabolism to iron reduction, and once sulfate reduction began. Results were highly reproducible across technical replicates, and identified specific taxa that responded to the perturbation. All samples contain very high alpha diversity and abundant organisms from phyla without cultivated representatives. Surprisingly, at the time points measured, there was no strong loss of evenness, despite the selective pressure of acetate amendment and change in the terminal electron accepting process. However, community membership was altered significantly. The method allows for sensitive, accurate profiling of the “long tail” of low abundance organisms that exist in many microbial communities, and can resolve population dynamics in response to environmental change.     

Benchmarking of 16S rRNA gene databases using known strain sequences

16S rRNA gene analysis is the most convenient and robust method for microbiome studies. Inaccurate taxonomic assignment of bacterial strains could have deleterious effects as all downstream analyses rely heavily on the accurate assessment of microbial taxonomy. The use of mock communities to check the reliability of the results has been suggested. However, often the mock communities used in most of the studies represent only a small fraction of taxa and are used mostly as validation of sequencing run to estimate sequencing artifacts. Moreover, a large number of databases and tools available for classification and taxonomic assignment of the 16S rRNA gene make it challenging to select the best-suited method for a particular dataset. In the present study, we used authentic and validly published 16S rRNA gene type strain sequences (full length, V3-V4 region) and analyzed them using a widely used QIIME pipeline along with different parameters of OTU clustering and QIIME compatible databases. Data Analysis Measures (DAM) revealed a high discrepancy in ratifying the taxonomy at different taxonomic hierarchies. Beta diversity analysis showed clear segregation of different DAMs. Limited differences were observed in reference data set analysis using partial (V3-V4) and full-length 16S rRNA gene sequences, which signify the reliability of partial 16S rRNA gene sequences in microbiome studies. Our analysis also highlights common discrepancies observed at various taxonomic levels using various methods and databases.     

Library preparation methods for next-generation sequencing: Tone down the bias

Next-generation sequencing (NGS) has caused a revolution in biology. NGS requires the preparation of libraries in which (fragments of) DNA or RNA molecules are fused with adapters followed by PCR amplification and sequencing. It is evident that robust library preparation methods that produce a representative, non-biased source of nucleic acid material from the genome under investigation are of crucial importance. Nevertheless, it has become clear that NGS libraries for all types of applications contain biases that compromise the quality of NGS datasets and can lead to their erroneous interpretation. A detailed knowledge of the nature of these biases will be essential for a careful interpretation of NGS data on the one hand and will help to find ways to improve library quality or to develop bioinformatics tools to compensate for the bias on the other hand. In this review we discuss the literature on bias in the most common NGS library preparation protocols, both for DNA sequencing (DNA-seq) as well as for RNA sequencing (RNA-seq). Strikingly, almost all steps of the various protocols have been reported to introduce bias, especially in the case of RNA-seq, which is technically more challenging than DNA-seq. For each type of bias we discuss methods for improvement with a view to providing some useful advice to the researcher who wishes to convert any kind of raw nucleic acid into an NGS library.