a-bioinformatics-pipeline-for-investigating-molecular-evolution-gene

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Distilling and reporting large datasets, such as whole genome or transcriptome data, is often a daunting task. One way to break down results is to focus ...

University of California, Irvine

Parasitism is a major ecological niche for a variety of nematodes. Multiple nematode lineages have specialized as pathogens, including deadly parasites of insects that are used in biological control. We have sequenced and analyzed the draft genomes and transcriptomes of the entomopathogenic nematode Steinernema carpocapsae and four congeners (S. scapterisci, S. monticolum, S. feltiae, and S. glaseri).

Comparative genomics of Steinernema reveals deeply conserved gene regulatory networks.

RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping. We highlight the challenges associated with each step. We discuss the analysis of small RNAs and the integration of RNA-seq with other functional genomics techniques. Finally, we discuss the outlook for novel technologies that are changing the state of the art in transcriptomics. 

A survey of best practices for RNA-seq data analysis.

Erratum to: A survey of best practices for RNA-seq data analysis.

Myoblasts are precursor skeletal muscle cells that differentiate into fused, multinucleated myotubes. Current single-cell microfluidic methods are not optimized for capturing very large, multinucleated cells such as myotubes. To circumvent the problem, we performed single-nucleus transcriptome analysis. Using immortalized human myoblasts, we performed RNA-seq analysis of single cells (scRNA-seq) and single nuclei (snRNA-seq) and found them comparable, with a distinct enrichment for long non-coding RNAs (lncRNAs) in snRNA-seq. We then compared snRNA-seq of myoblasts before and after differentiation. We observed the presence of mononucleated cells (MNCs) that remained unfused and analyzed separately from multi-nucleated myotubes. We found that while the transcriptome profiles of myoblast and myotube nuclei are relatively homogeneous, MNC nuclei exhibited significant heterogeneity, with the majority of them adopting a distinct mesenchymal state. Primary transcripts for microRNAs (miRNAs) that participate in skeletal muscle differentiation were among the most differentially expressed lncRNAs, which we validated using NanoString. Our study demonstrates that snRNA-seq provides reliable transcriptome quantification for cells that are otherwise not amenable to current single-cell platforms. Our results further indicate that snRNA-seq has unique advantage in capturing nucleus-enriched lncRNAs and miRNA precursors that are useful in mapping and monitoring differential miRNA expression during cellular differentiation.

Single-nucleus RNA-seq of differentiating human myoblasts reveals the extent of fate heterogeneity.

The reconstruction of gene regulatory networks underlying cell differentiation from high-throughput gene expression and chromatin data remains a challenge. Here, we derive dynamic gene regulatory networks for human myeloid differentiation using a 5-day time series of RNA-seq and ATAC-seq data. We profile HL-60 promyelocytes differentiating into macrophages, neutrophils, monocytes, and monocyte-derived macrophages. We find a rapid response in the expression of key transcription factors and lineage markers that only regulate a subset of their targets at a given time, which is followed by chromatin accessibility changes that occur later along with further gene expression changes. We observe differences between promyelocyte- and monocyte-derived macrophages at both the transcriptional and chromatin landscape level, despite using the same differentiation stimulus, which suggest that the path taken by cells in the differentiation landscape defines their end cell state. More generally, our approach of combining neighboring time points and replicates to achieve greater sequencing depth can efficiently infer footprint-based regulatory networks from long series data.

Dynamic Gene Regulatory Networks of Human Myeloid Differentiation.

T-cell development from hematopoietic progenitors depends on multiple transcription factors, mobilized and modulated by intrathymic Notch signaling. Key aspects of T-cell specification network architecture have been illuminated through recent reports defining roles of transcription factors PU.1, GATA-3, and E2A, their interactions with Notch signaling, and roles of Runx1, TCF-1, and Hes1, providing bases for a comprehensively updated model of the T-cell specification gene regulatory network presented herein. However, the role of lineage commitment factor Bcl11b has been unclear. We use self-organizing maps on 63 RNA-seq datasets from normal and perturbed T-cell development to identify functional targets of Bcl11b during commitment and relate them to other regulomes. We show that both activation and repression target genes can be bound by Bcl11b in vivo, and that Bcl11b effects overlap with E2A-dependent effects. The newly clarified role of Bcl11b distinguishes discrete components of commitment, resolving how innate lymphoid, myeloid, and dendritic, and B-cell fate alternatives are excluded by different mechanisms.

Bcl11b and combinatorial resolution of cell fate in the T-cell gene regulatory network.

Genetic and environmental factors interact during sensitive periods early in life to influence mental health and disease via epigenetic processes such as DNA methylation. However, it is not known if DNA methylation changes outside the brain provide an "epigenetic signature" of early-life experiences. Here, we used a novel intra-individual approach by testing DNA methylation from buccal cells of individual rats before and immediately after exposure to one week of typical or adverse life experience. We find that whereas inter-individual changes in DNA methylation reflect the effect of age, DNA methylation changes within paired DNA samples from the same individual reflect the impact of diverse neonatal experiences. Genes coding for critical cellular metabolic enzymes, ion channels, and receptors were more methylated in pups exposed to the adverse environment, predictive of their repression. In contrast, the adverse experience was associated with less methylation on genes involved in pathways of death and inflammation as well as cell-fate-related transcription factors, indicating their potential up-regulation. Thus, intra-individual methylome signatures indicate large-scale transcription-driven alterations of cellular fate, growth, and function.

Intra-individual methylomics detects the impact of early-life adversity.

The majority of the human genome is made of transposable elements, giving rise to interspaced repeats, including Long INterspersed Element-1s (LINE-1s or L1s). L1s are active human transposable elements involved in genomic diversity and evolution; however, they can also contribute to genomic instability and diseases. L1s require host factors to complete their life cycles, whereas the host has evolved numerous mechanisms to restrict L1-induced mutagenesis. Restriction mechanisms in somatic cells include methylation of the L1 promoter, anti-viral factors and RNA-mediated processes such as small RNAs. microRNAs (miRNAs or miRs) are small non-coding RNAs that post-transcriptionally repress multiple target genes often found in the same cellular pathways. We have recently established that miR-128 functions as a novel restriction factor inhibiting L1 mobilization in somatic cells. We have further demonstrated that miR-128 functions through a dual mechanism; by directly targeting L1 RNA for degradation and indirectly by inhibiting a cellular co-factor which L1 is dependent on to transpose to new genomic locations (TNPO1). Here, we add another piece to the puzzle of the enigmatic L1 lifecycle. We show that miR-128 also inhibits another key cellular factor, hnRNPA1 (heterogeneous nuclear ribonucleoprotein A1), by significantly reducing mRNA and protein levels through direct interaction with the coding sequence (CDS) of hnRNPA1 mRNA. In addition, we demonstrate that repression of hnRNPA1 using hnRNPA1-shRNA significantly decreases de novo L1 retro-transposition and that induced hnRNPA1 expression enhances L1 mobilization. Furthermore, we establish that hnRNPA1 is a functional target of miR-128. Finally, we determine that induced hnRNPA1 expression in miR-128-overexpressing cells can partly rescue the miR-128-induced repression of L1's ability to transpose to different genomic locations. Thus, we have identified an additional mechanism by which miR-128 represses L1 retro-transposition and mediates genomic stability.

miR-128 Restriction of LINE-1 (L1) Retrotransposition Is Dependent on Targeting hnRNPA1 mRNA.

Entomopathogenic nematodes from the genus  are lethal insect parasites that quickly kill their insect hosts with the help of their symbiotic bacteria.  is one of the most studied entomopathogens due to its broad lethality to diverse insect species and its effective commercial use as a biological control agent for insect pests, as well as a genetic model for studying parasitism, pathogenesis, and symbiosis. In this study, we used long-reads from the Pacific Biosciences platform and BioNano Genomics Irys system to assemble the most complete genome of the  ALL strain to date, comprising 84.5 Mb in 16 scaffolds, with an N50 of 7.36 Mb. The largest scaffold, with 20.9 Mb, was identified as chromosome X based on sex-specific genome sequencing. The high level of contiguity allowed us to characterize gene density, repeat content, and GC content. RNA-seq data from 17 developmental stages, spanning from embryo to adult, were used to predict 30,957 gene models. Using this improved genome, we performed a macrosyntenic analysis to  and  and found  chromosome X to be primarily orthologous to ' and ' chromosome II and IV. We also investigated the expansion of protein families and gene expression differences between adult male and female stage nematodes. This new genome and more accurate set of annotations provide a foundation for additional comparative genomic and gene expression studies within the  clade and across the Nematoda phylum.

Hybrid Assembly of the Genome of the Entomopathogenic Nematode  Identifies the X-Chromosome.

Intra-individual changes in methylome profiles: an epigenetic 'scar' of early-life adversity?

The evolution of opsin genes is of great interest because it can provide insight into the evolution of light detection and vision. An interesting group in which to study opsins is Cnidaria because it is a basal phylum sister to Bilateria with much visual diversity within the phylum. Hydra vulgaris (H. vulgaris) is a cnidarian with a plethora of genomic resources to characterize the opsin gene family. This eyeless cnidarian has a behavioral reaction to light, but it remains unknown which of its many opsins functions in light detection. Here, we used phylogenetics and RNA-seq to investigate the molecular evolution of opsin genes and their expression in H. vulgaris. We explored where opsin genes are located relative to each other in an improved genome assembly and where they belong in a cnidarian opsin phylogenetic tree. In addition, we used RNA-seq data from different tissues of the H. vulgaris adult body and different time points during regeneration and budding stages to gain insight into their potential functions.

Molecular evolution and expression of opsin genes in Hydra vulgaris.

The advancement of transcriptomic studies in plant parasitic nematodes will greatly benefit from the development of single-nematode RNA-seq methods. Since many plant parasitic nematodes are obligate parasites, it is often difficult to efficiently obtain sufficient amounts of nematodes for transcriptomic studies. Here we have adapted SMART-Seq2 for single-nematode RNA-seq requiring only an individual nematode for a sample replicate. This protocol provides a detailed step-by-step procedure of the RNA-seq workflow starting from lysis of the nematode to quantification of transcripts using a user-friendly online platform.

A Revised Adaptation of the Smart-Seq2 Protocol for Single-Nematode RNA-Seq.

Animals that are competent reservoirs of zoonotic pathogens commonly suffer little morbidity from the infections. To investigate mechanisms of this tolerance of infection, we used single-dose lipopolysaccharide (LPS) as an experimental model of inflammation and compared the responses of two rodents: , the white-footed deermouse and reservoir for the agents of Lyme disease and other zoonoses, and the house mouse  Four hours after injection with LPS or saline, blood, spleen, and liver samples were collected and subjected to transcriptome sequencing (RNA-seq), metabolomics, and specific reverse transcriptase quantitative PCR (RT-qPCR). Differential expression analysis was at the gene, pathway, and network levels. LPS-treated deermice showed signs of sickness similar to those of exposed mice and had similar increases in corticosterone levels and expression of interleukin 6 (IL-6), tumor necrosis factor, IL-1β, and C-reactive protein. By network analysis, the  response to LPS was characterized as cytokine associated, while the  response was dominated by neutrophil activity terms. In addition, dichotomies in the expression levels of arginase 1 and nitric oxide synthase 2 and of IL-10 and IL-12 were consistent with type M1 macrophage responses in mice and type M2 responses in deermice. Analysis of metabolites in plasma and RNA in organs revealed species differences in tryptophan metabolism. Two genes in particular signified the different phenotypes of deermice and mice: the Slpi and Ibsp genes. Key RNA-seq findings for  were replicated in older animals, in a systemic bacterial infection, and with cultivated fibroblasts. The findings indicate that  possesses several adaptive traits to moderate inflammation in its balancing of infection resistance and tolerance. Animals that are natural carriers of pathogens that cause human diseases commonly manifest little or no sickness as a consequence of infection. Examples include the deermouse, , which is a reservoir for Lyme disease and several other disease agents in North America, and some types of bats, which are carriers of viruses with pathogenicity for humans. Mechanisms of this phenomenon of infection tolerance and entailed trade-off costs are poorly understood. Using a single injection of lipopolysaccharide (LPS) endotoxin as a proxy for infection, we found that deermice differed from the mouse () in responses to LPS in several diverse pathways, including innate immunity, oxidative stress, and metabolism. Features distinguishing the deermice cumulatively would moderate downstream ill effects of LPS. Insights gained from the  model in the laboratory have implications for studying infection tolerance in other important reservoir species, including bats and other types of wildlife.

Ali Mortazavi

Department of Developmental and Cell Biology

University of California, Irvine

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq