Detrimental effects of duplicate reads and low complexity regions on RNA- and ChIP-seq data

Dysregulated expression of cholesterol biosynthetic genes in Alzheimer's disease alters epigenomic signatures of hippocampal neurons

Aging is the main risk factor of cognitive neurodegenerative diseases such as Alzheimer's disease, with epigenome alterations as a contributing factor. Here, we compared transcriptomic/epigenomic changes in the hippocampus, modified by aging and by tauopathy, an AD-related feature. We show that the cholesterol biosynthesis pathway is severely impaired in hippocampal neurons of tauopathic but not of aged mice pointing to vulnerability of these neurons in the disease. At the epigenomic level, histone hyperacetylation was observed at neuronal enhancers associated with glutamatergic regulations only in the tauopathy. Lastly, a treatment of tau mice with the CSP-TTK21 epi-drug that restored expression of key cholesterol biosynthesis genes counteracted hyperacetylation at neuronal enhancers and restored object memory. As acetyl-CoA is the primary substrate of both pathways, these data suggest that the rate of the cholesterol biosynthesis in hippocampal neurons may trigger epigenetic-driven changes, that may compromise the functions of hippocampal neurons in pathological conditions.

Mutant FUS induces chromatin reorganization in the hippocampus and alters memory processes

Cytoplasmic mislocalization of the nuclear Fused in Sarcoma (FUS) protein is associated to amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Cytoplasmic FUS accumulation is recapitulated in the frontal cortex and spinal cord of heterozygous Fus∆NLS/+ mice. Yet, the mechanisms linking FUS mislocalization to hippocampal function and memory formation are still not characterized. Herein, we show that in these mice, the hippocampus paradoxically displays nuclear FUS accumulation. Multi-omic analyses showed that FUS binds to a set of genes characterized by the presence of an ETS/ELK-binding motifs, and involved in RNA metabolism, transcription, ribosome/mitochondria and chromatin organization. Importantly, hippocampal nuclei showed a decompaction of the neuronal chromatin at highly expressed genes and an inappropriate transcriptomic response was observed after spatial training of Fus∆NLS/+ mice. Furthermore, these mice lacked precision in a hippocampal-dependent spatial memory task and displayed decreased dendritic spine density. These studies shows that mutated FUS affects epigenetic regulation of the chromatin landscape in hippocampal neurons, which could participate in FTD/ALS pathogenic events. These data call for further investigation in the neurological phenotype of FUS-related diseases and open therapeutic strategies towards epigenetic drugs.

Improved analysis of (e)CLIP data with RCRUNCH yields a compendium of RNA-binding protein binding sites and motifs

We present RCRUNCH, an end-to-end solution to CLIP data analysis for identification of binding sites and sequence specificity of RNA-binding proteins. RCRUNCH can analyze not only reads that map uniquely to the genome but also those that map to multiple genome locations or across splice boundaries and can consider various types of background in the estimation of read enrichment. By applying RCRUNCH to the eCLIP data from the ENCODE project, we have constructed a comprehensive and homogeneous resource of in-vivo-bound RBP sequence motifs. RCRUNCH automates the reproducible analysis of CLIP data, enabling studies of post-transcriptional control of gene expression.

SEAseq: a portable and cloud-based chromatin occupancy analysis suite

Background

Genome-wide protein-DNA binding is popularly assessed using specific antibody pulldown in Chromatin Immunoprecipitation Sequencing (ChIP-Seq) or Cleavage Under Targets and Release Using Nuclease (CUT&RUN) sequencing experiments. These technologies generate high-throughput sequencing data that necessitate the use of multiple sophisticated, computationally intensive genomic tools to make discoveries, but these genomic tools often have a high barrier to use because of computational resource constraints.

Results

We present a comprehensive, infrastructure-independent, computational pipeline called SEAseq, which leverages field-standard, open-source tools for processing and analyzing ChIP-Seq/CUT&RUN data. SEAseq performs extensive analyses from the raw output of the experiment, including alignment, peak calling, motif analysis, promoters and metagene coverage profiling, peak annotation distribution, clustered/stitched peaks (e.g. super-enhancer) identification, and multiple relevant quality assessment metrics, as well as automatic interfacing with data in GEO/SRA. SEAseq enables rapid and cost-effective resource for analysis of both new and publicly available datasets as demonstrated in our comparative case studies.

Conclusions

The easy-to-use and versatile design of SEAseq makes it a reliable and efficient resource for ensuring high quality analysis. Its cloud implementation enables a broad suite of analyses in environments with constrained computational resources. SEAseq is platform-independent and is aimed to be usable by everyone with or without programming skills. It is available on the cloud at https://platform.stjude.cloud/workflows/seaseq and can be locally installed from the repository at https://github.com/stjude/seaseq.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04588-z.

The life cycle-dependent transcriptional profile of the obligate intracellular amoeba symbiont Amoebophilus asiaticus

Free-living amoebae often harbor obligate intracellular bacterial symbionts. Amoebophilus (A.) asiaticus is a representative of a lineage of amoeba symbionts in the phylum Bacteroidota. Here, we analyse the transcriptome of A. asiaticus strain 5a2 at four time points during its infection cycle and replication within the Acanthamoeba host using RNA sequencing. Our results reveal a dynamic transcriptional landscape throughout different A. asiaticus life cycle stages. Many intracellular bacteria and pathogens utilize eukaryotic-like proteins (ELPs) for host cell interaction and the A. asiaticus 5a2 genome shows a particularly high abundance of ELPs. We show the expression of all genes encoding ELPs and found many ELPs to be differentially expressed. At the replicative stage of A. asiaticus, ankyrin repeat proteins and tetratricopeptide/Sel1-like repeat proteins were upregulated. At the later time points, high expression levels of a type 6 secretion system that likely prepares for a new infection cycle after lysing its host, were found. This study reveals comprehensive insights into the intracellular lifestyle of A. asiaticus and highlights candidate genes for host cell interaction. The results from this study have implications for other intracellular bacteria such as other amoeba-associated bacteria and the arthropod symbionts Cardinium forming the sister lineage of A. asiaticus.

Transcriptome-Wide Analyses Identify Dominant as the Predominantly Non-Conservative Alternative Splicing Inheritance Patterns in F1 Chickens

Transcriptome analysis has been used to investigate many economically traits in chickens; however, alternative splicing still lacks a systematic method of study that is able to promote proteome diversity, and fine-tune expression dynamics. Hybridization has been widely utilized in chicken breeding due to the resulting heterosis, but the dynamic changes in alternative splicing during this process are significant yet unclear. In this study, we performed a reciprocal crossing experiment involving the White Leghorn and Cornish Game chicken breeds which exhibit major differences in body size and reproductive traits, and conducted RNA sequencing of the brain, muscle, and liver tissues to identify the inheritance patterns. A total of 40 515 and 42 612 events were respectively detected in the brain and muscle tissues, with 39 843 observed in the liver; 2807, 4242, and 4538 events significantly different between two breeds were identified in the brain, muscle, and liver tissues, respectively. The hierarchical cluster of tissues from different tissues from all crosses, based on the alternative splicing profiles, suggests high tissue and strain specificity. Furthermore, a comparison between parental strains and hybrid crosses indicated that over one third of alternative splicing genes showed conserved patterns in all three tissues, while the second prevalent pattern was non-additive, which included both dominant and transgressive patterns; this meant that the dominant pattern plays a more important role than suppression. Our study provides an overview of the inheritance patterns of alternative splicing in layer and broiler chickens, to better understand post-transcriptional regulation during hybridization.

Conserved DNA sequence features underlie pervasive RNA polymerase pausing

Pausing of transcribing RNA polymerase is regulated and creates opportunities to control gene expression. Research in metazoans has so far mainly focused on RNA polymerase II (Pol II) promoter-proximal pausing leaving the pervasive nature of pausing and its regulatory potential in mammalian cells unclear. Here, we developed a pause detecting algorithm (PDA) for nucleotide-resolution occupancy data and a new native elongating transcript sequencing approach, termed nested NET-seq, that strongly reduces artifactual peaks commonly misinterpreted as pausing sites. Leveraging PDA and nested NET-seq reveal widespread genome-wide Pol II pausing at single-nucleotide resolution in human cells. Notably, the majority of Pol II pauses occur outside of promoter-proximal gene regions primarily along the gene-body of transcribed genes. Sequence analysis combined with machine learning modeling reveals DNA sequence properties underlying widespread transcriptional pausing including a new pause motif. Interestingly, key sequence determinants of RNA polymerase pausing are conserved between human cells and bacteria. These studies indicate pervasive sequence-induced transcriptional pausing in human cells and the knowledge of exact pause locations implies potential functional roles in gene expression.

Direct Nanopore Sequencing of mRNA Reveals Landscape of Transcript Isoforms in Apicomplexan Parasites

Alternative splicing is a widespread phenomenon in metazoans by which single genes are able to produce multiple isoforms of the gene product. However, this has been poorly characterized in apicomplexans, a major phylum of some of the most important global parasites. Efforts have been hampered by atypical transcriptomic features, such as the high AU content of Plasmodium RNA, but also the limitations of short-read sequencing in deciphering complex splicing events. In this study, we utilized the long read direct RNA sequencing platform developed by Oxford Nanopore Technologies to survey the alternative splicing landscape of Toxoplasma gondii and Plasmodium falciparum. We find that while native RNA sequencing has a reduced throughput, it allows us to obtain full-length or nearly full-length transcripts with comparable quantification to Illumina sequencing. By comparing these data with available gene models, we find widespread alternative splicing, particularly intron retention, in these parasites. Most of these transcripts contain premature stop codons, suggesting that in these parasites, alternative splicing represents a pathway to transcriptomic diversity, rather than expanding proteomic diversity. Moreover, alternative splicing rates are comparable between parasites, suggesting a shared splicing machinery, despite notable transcriptomic differences between the parasites. This study highlights a strategy in using long-read sequencing to understand splicing events at the whole-transcript level and has implications in the future interpretation of transcriptome sequencing studies.

IMPORTANCE We have used a novel nanopore sequencing technology to directly analyze parasite transcriptomes. The very long reads of this technology reveal the full-length genes of the parasites that cause malaria and toxoplasmosis. Gene transcripts must be processed in a process called splicing before they can be translated to protein. Our analysis reveals that these parasites very frequently only partially process their gene products, in a manner that departs dramatically from their human hosts.

Inheritance patterns of the transcriptome in hybrid chickens and their parents revealed by expression analysis

Although many phenotypic traits of chickens have been well documented, the genetic patterns of gene expression levels in chickens remain to be determined. In the present study, we crossed two chicken breeds, White Leghorn (WL) and Cornish (Cor), which have been selected for egg and meat production, respectively, for a few hundred years. We evaluated transcriptome abundance in the brain, muscle, and liver from the day-old progenies of pure-bred WL and Cor, and the hybrids of these two breeds, by RNA-Seq in order to determine the inheritance patterns of gene expression. Comparison among expression levels in the different groups revealed that most of the genes showed conserved expression patterns in all three examined tissues and that brain had the highest number of conserved genes, which indicates that conserved genes are predominantly important compared to others. On the basis of allelic expression analysis, in addition to the conserved genes, we identified the extensive presence of additive, dominant (Cor dominant and WL dominant), over-dominant, and under-dominant genes in all three tissues in hybrids. Our study is the first to provide an overview of inheritance patterns of the transcriptome in layers and broilers, and we also provide insights into the genetics of chickens at the gene expression level.

RNA-sequencing in ophthalmology research: considerations for experimental design and analysis

High-throughput, massively parallel sequence analysis has revolutionized the way that researchers design and execute scientific investigations. Vast amounts of sequence data can be generated in short periods of time. Regarding ophthalmology and vision research, extensive interrogation of patient samples for underlying causative DNA mutations has resulted in the discovery of many new genes relevant to eye disease. However, such analysis remains functionally limited. RNA-sequencing accurately snapshots thousands of genes, capturing many subtypes of RNA molecules, and has become the gold standard for transcriptome gene expression quantification. RNA-sequencing has the potential to advance our understanding of eye development and disease; it can reveal new candidates to improve our molecular diagnosis rates and highlight therapeutic targets for intervention. But with a wide range of applications, the design of such experiments can be problematic, no single optimal pipeline exists, and therefore, several considerations must be undertaken for optimal study design. We review the key steps involved in RNA-sequencing experimental design and the downstream bioinformatic pipelines used for differential gene expression. We provide guidance on the application of RNA-sequencing to ophthalmology and sources of open-access eye-related data sets.

Authentication and Assessment of Contamination in Ancient DNA

Contamination from both present-day humans and postmortem microbial sources is a common challenge in ancient DNA studies. Here we present a suite of tools to assist in the assessment of contamination in ancient DNA data sets. These tools perform standard tests of authenticity of ancient DNA data including detecting the presence of postmortem damage signatures in sequence alignments and quantifying the amount of present-day human contamination.

Allele-Specific Expression Analysis Does Not Support Sex Chromosome Inactivation on the Chicken Z Chromosome

Heterogametic sex chromosomes have evolved many times independently, and in many cases, the loss of functional genes from the sex-limited Y or W chromosome leaves only one functional gene copy on the corresponding X or Z chromosome in the heterogametic sex. Because gene dose often correlates with gene expression level, this difference in gene dose between males and females for X- or Z-linked genes in some cases has selected for chromosome-wide transcriptional dosage compensation mechanisms to counteract any reduction in expression in the heterogametic sex. These mechanisms are thought to restore the balance between sex-linked loci and the autosomal genes they interact with, and this also typically results in equal expression between the sexes. However, dosage compensation in many other species is incomplete, and in the case of birds average expression from males (ZZ) remains higher than in females (ZW). Interestingly, recent reports in chickens and related species have shown that the Z chromosome is expressed less in males than would be expected from two copies of the chromosome, and recent data from cell-based approaches on 11 loci in chicken have suggested that one Z chromosome is partially inactivated in males, in a mechanism thought to be homologous to X inactivation in therian mammals. In the present study, we use controlled crosses in three tissues to test for the presence of Z inactivation in males, which would be expected to bias transcription to the active gene copy (allele-specific expression). We show that for the vast majority of genes on the chicken Z chromosome, males express both parental alleles at statistically similar levels, indicating no Z chromosome inactivation. For those Z chromosome loci with detectable ASE in males, we show that the most likely cause is cis-regulatory variation, rather than Z chromosome inactivation. Taken together, our results indicate that unlike the X chromosome in mammals, Z inactivation does not affect an appreciable number of loci in chicken.

unitas: the universal tool for annotation of small RNAs

BACKGROUND

Next generation sequencing is a key technique in small RNA biology research that has led to the discovery of functionally different classes of small non-coding RNAs in the past years. However, reliable annotation of the extensive amounts of small non-coding RNA data produced by high-throughput sequencing is time-consuming and requires robust bioinformatics expertise. Moreover, existing tools have a number of shortcomings including a lack of sensitivity under certain conditions, limited number of supported species or detectable sub-classes of small RNAs.

RESULTS

Here we introduce unitas, an out-of-the-box ready software for complete annotation of small RNA sequence datasets, supporting the wide range of species for which non-coding RNA reference sequences are available in the Ensembl databases (currently more than 800). unitas combines high quality annotation and numerous analysis features in a user-friendly manner. A complete annotation can be started with one simple shell command, making unitas particularly useful for researchers not having access to a bioinformatics facility. Noteworthy, the algorithms implemented in unitas are on par or even outperform comparable existing tools for small RNA annotation that map to publicly available ncRNA databases.

CONCLUSIONS

unitas brings together annotation and analysis features that hitherto required the installation of numerous different bioinformatics tools which can pose a challenge for the non-expert user. With this, unitas overcomes the problem of read normalization. Moreover, the high quality of sequence annotation and analysis, paired with the ease of use, make unitas a valuable tool for researchers in all fields connected to small RNA biology.

Effect of method of deduplication on estimation of differential gene expression using RNA-seq

Background

RNA-seq is a useful tool for analysis of gene expression. However, its robustness is greatly affected by a number of artifacts. One of them is the presence of duplicated reads.

Results

To infer the influence of different methods of removal of duplicated reads on estimation of gene expression in cancer genomics, we analyzed paired samples of hepatocellular carcinoma (HCC) and non-tumor liver tissue. Four protocols of data analysis were applied to each sample: processing without deduplication, deduplication using a method implemented in SAMtools, and deduplication based on one or two molecular indices (MI). We also analyzed the influence of sequencing layout (single read or paired end) and read length. We found that deduplication without MI greatly affects estimated expression values; this effect is the most pronounced for highly expressed genes.

Conclusion

The use of unique molecular identifiers greatly improves accuracy of RNA-seq analysis, especially for highly expressed genes. We developed a set of scripts that enable handling of MI and their incorporation into RNA-seq analysis pipelines. Deduplication without MI affects results of differential gene expression analysis, producing a high proportion of false negative results. The absence of duplicate read removal is biased towards false positives. In those cases where using MI is not possible, we recommend using paired-end sequencing layout.

Preprocessing and Quality Control for Whole-Genome Sequences from the Illumina HiSeq X Platform

The advancement of high-throughput sequencing technologies enables sequencing of human genomes at steadily decreasing costs and increasing quality. Before variants can be analyzed, e.g., in association studies, the raw data obtained from the sequencer need to be preprocessed. These preprocessing steps include the removal of adapters, duplicates, and contaminations, alignment to a reference genome and the postprocessing of the alignment. All later steps, such as variant discovery, rely on high data quality and proper preprocessing, emphasizing the great importance of quality control. This chapter presents a workflow for preprocessing Illumina HiSeq X sequencing data. Code snippets are provided for illustrating all necessary steps, along with a brief description of the tools and underlying methods.

Next generation sequencing technology and genomewide data analysis: Perspectives for retinal research

The advent of high throughput next generation sequencing (NGS) has accelerated the pace of discovery of disease-associated genetic variants and genomewide profiling of expressed sequences and epigenetic marks, thereby permitting systems-based analyses of ocular development and disease. Rapid evolution of NGS and associated methodologies presents significant challenges in acquisition, management, and analysis of large data sets and for extracting biologically or clinically relevant information. Here we illustrate the basic design of commonly used NGS-based methods, specifically whole exome sequencing, transcriptome, and epigenome profiling, and provide recommendations for data analyses. We briefly discuss systems biology approaches for integrating multiple data sets to elucidate gene regulatory or disease networks. While we provide examples from the retina, the NGS guidelines reviewed here are applicable to other tissues/cell types as well.

Trimming of sequence reads alters RNA-Seq gene expression estimates

BACKGROUND

High-throughput RNA-Sequencing (RNA-Seq) has become the preferred technique for studying gene expression differences between biological samples and for discovering novel isoforms, though the techniques to analyze the resulting data are still immature. One pre-processing step that is widely but heterogeneously applied is trimming, in which low quality bases, identified by the probability that they are called incorrectly, are removed. However, the impact of trimming on subsequent alignment to a genome could influence downstream analyses including gene expression estimation; we hypothesized that this might occur in an inconsistent manner across different genes, resulting in differential bias.

RESULTS

To assess the effects of trimming on gene expression, we generated RNA-Seq data sets from four samples of larval Drosophila melanogaster sensory neurons, and used three trimming algorithms--SolexaQA, Trimmomatic, and ConDeTri-to perform quality-based trimming across a wide range of stringencies. After aligning the reads to the D. melanogaster genome with TopHat2, we used Cuffdiff2 to compare the original, untrimmed gene expression estimates to those following trimming. With the most aggressive trimming parameters, over ten percent of genes had significant changes in their estimated expression levels. This trend was seen with two additional RNA-Seq data sets and with alternative differential expression analysis pipelines. We found that the majority of the expression changes could be mitigated by imposing a minimum length filter following trimming, suggesting that the differential gene expression was primarily being driven by spurious mapping of short reads. Slight differences with the untrimmed data set remained after length filtering, which were associated with genes with low exon numbers and high GC content. Finally, an analysis of paired RNA-seq/microarray data sets suggests that no or modest trimming results in the most biologically accurate gene expression estimates.

CONCLUSIONS

We find that aggressive quality-based trimming has a large impact on the apparent makeup of RNA-Seq-based gene expression estimates, and that short reads can have a particularly strong impact. We conclude that implementation of trimming in RNA-Seq analysis workflows warrants caution, and if used, should be used in conjunction with a minimum read length filter to minimize the introduction of unpredictable changes in expression estimates.