Multi-omics analysis of the ageing liver

This dissertation presents three manuscripts that originated from my work on the ageing liver. The first two manuscripts concentrate on integrative multi-omics ap-proaches, such as scATAC-seq and scRNA-seq, spatial transcriptomics, CUT&RUN sequencing and lipidomics. They reveal distinct ageing signatures within the murine liver, mainly in hepatocytes. The third manuscript introduces a new methodology for the analysis of spatial sequencing data, which was developed with the ageing liver as an intended application. The first manuscript, "Single-cell resolution unravels spatial alterations in metabo-lism, transcriptome, and epigenome of ageing liver", establishes how spatial loca-tion and microenvironmental changes impact the ageing trajectories of hepatocytes within liver tissue. Through the integration of spatial transcriptomics, single-cell ATAC- and RNA-seq, lipidomics, and functional assays, the study elucidates zonation-specific and age-related changes in the epigenome, transcriptome, and metabolic states. We identified a zonation-dependent shift in the epigenome and show that changing microenvironments within a tissue exert strong influences on their resident cells that can shape epigenetic, metabolic and phenotypic outputs. From a functional perspective, periportal hepatocytes exhibited diminished mitochondrial fitness, whereas pericentral hepatocytes demonstrated an increased accumulation of large lipid droplets. The second manuscript, "Ageing is associated with increased chromatin accessibil-ity and reduced polymerase pausing in liver", examines the chromatin landscape of the ageing liver by using CUT&RUN for RNA polymerase mapping, integrated with ATAC-seq, RNA-seq, and NET-seq. The study reveals an increase in chromatin accessi-bility at promoter regions as a characteristic of ageing, which is not accompanied by a corresponding increase in transcriptional output. Ageing is also found to be associated with a decrease in promoter-proximal pausing of RNA Polymerase II. Our observations suggest that alterations in transcriptional regulation associated with ageing may be due to decreased stability of the pausing complex. The third manuscript, "Dimension reduction by spatial components analysis im-proves pattern detection in multivariate spatial data", introduces SPACO, a new statistical approach designed to enhance pattern recognition in multivariate spatial sequencing data. SPACO stands out by focusing on gene co-regulation and maximising local covariance. It provides a more sensitive and accurate test for the identification of genes with a spatial expression pattern. Moreover, the use of spatial components for gene denoising by SPACO boosts the effective linkage of histological observations with gene expression patterns, even in high-noise conditions

Characterising the source of errors for metagenomic taxonomic classification

Characterising microbial communities enables a better understanding of their complexity and the contribution to the environment. Metagenomics has been a rapidly expanding field since the revolution of next generation sequencing began, and it has a wide range of application including for medicine, agriculture, forensics, archaeology and even domestic use [Sarkar et al., 2021, Holman et al., 2017, Khodakova et al.,2014, Santiago-Rodriguez et al., 2017, Vilanova et al., 2015]. Sequencing amplicon data, such as 16S rRNA, is now commonly used to characterise the microbiome in a variety of biological samples. However, their correct taxonomic identification still remains a challenge, and often short reads are identified, correctly or not, at several ranks of the taxonomic tree other than species or subspecies level. Every metagenomic study is designed for specific needs, and it is often complicated to find a suitable bioinformatics pipeline and reference database. There is currently a lack of systematic benchmarking of in-house methods for metagenomics. The work presented in this thesis aims to establish an approach for the in silico validation of 16S rRNA metagenomic data. A method to generate realistic in silico metagenome data that resembles project-specific sequencing data is presented, including a new process to generate synthetic negative controls for amplicon data, which can be employed regularly to assess the appropriateness and optimisation of methods for specific metagenomic projects. To aid the benchmarking process, new metrics have been defined based on a measure of taxonomic distance. A k-mer based method with the lowest common ancestor approach was selected to investigate a range of factors that influence meta-taxonomic classification success. It includes the comparison of database quality filtered at various levels, and as well as a comparison of different taxonomic annotation methodologies. The experimental findings reveal the importance of having highly curated taxonomic annotations of the genetic sequences in the database, and that a missing fraction of the tree of life can lead to misclassification of any related or unrelated organisms. In some cases, it is shown that longer reads can help to improve assignment, with mutations and sequencing errors having a relatively low negative impact. The marker gene 16S rRNA has well-defined conserved and variable regions, which help to distinguish species. Therefore, these regions were studied and also recalculated using information theory, to investigate which parts of the sequence are discriminative for metagenomic taxonomic identification. In addition, linguistics methods, Term Frequency — Inverse Document Frequency (TF-IDF) coupled with multinomial naive Bayes, is shown to provide understanding of genetic signatures and is applied to generate a new method to classify taxonomically metagenomics short reads. Biological samples were taken from cattle respiratory tract, DNA was extracted and sequenced to provide metagenomic data. Two sets of experiments were carried out, (i) to compare sampling and extraction methods and (ii) to characterise the microbial community observed in young cattle in the different lung lobes and nose. The data reveal that the composition of the microbial community observed is highly dependent on the sampling method

Single Cell Analysis of Chromatin Accessibility

The identity of each cell in the human body is established and maintained through distinct gene expression program, which is regulated in part by the chromatin accessibility. Until recently, our understanding of chromatin accessibility has depended largely upon bulk measurements in populations of cells. Recent advances in the sequencing techniques have allowed for the identification of open chromatin regions in single cells. During my Ph.D., I have developed and used single cell sequencing techniques to study the diverse gene regulatory programs underlie the different cell types in mammalian complex tissues. In chapter 1, colleague and I developed Single Nucleus Assay of Transpose Accessible Chromatin using Sequencing (snATAC-seq), a combinatorial barcoding-assisted single-cell assay for probing accessible chromatin in single cells. We then used snATAC-seq to generate an epigenomic atlas of early developing mouse brain. The high-level noise of each single cell chromatin accessibility profile and the large volume of the datasets pose unique computational challenges. In chapter 2, I developed a comprehensive bioinformatics software package called SnapATAC for analyzing large-scale single cell ATAC-seq dataset. SnapATAC resolves the heterogeneity in complex tissues and maps the trajectories of cellular states. As a demonstration of its utility, SnapATAC was applied to 55,592 single-nucleus ATAC-seq profiles from the mouse secondary motor cortex. To further determine the target genes of the distal regulatory elements identified using snATAC-seq in different cell types, in chapter 3, colleague and I developed PLAC-seq, a cost-efficient method that identifies the long-range chromatin interaction at kilobase resolution. PLAC-seq improves the efficiency of detecting chromatin conformation by over 10-fold and reduces the input requirement by nearly 100-fold compared to the prior techniques. Finally, to probe the in vivo function of the regulatory sequences, I present a high-throughput CRISPR screening method (CREST-seq) for the unbiased discovery and functional assessment of enhancer sequences in the human genome. We used it to interrogate the 2-Mb POU5F1 locus in human embryonic stem cells and discovered that sequences previously annotated as promoters of functionally unrelated genes can regulate the expression of POU5F1 from a long distance. We anticipate that these studies will help us understand the gene regulatory programs across diverse biological systems ranging from human disease to the evolution of species

The HBP1 tumor suppressor is a negative epigenetic regulator of MYCN driven neuroblastoma through interaction with the PRC2 complex

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The impact of paternal metabolic health on sperm DNA methylation and fetal growth

Low birth weight is associated with cardiovascular disease and T2DM in later life. Paternal obesity and T2DM have been associated with an increased risk of fathering low birthweight offspring. Obesity is associated with epigenetic changes in blood, but few studies have replicated DNA methylation differences found in obese subjects. Animal studies have shown that obesity and insulin resistance are associated with DNA methylation changes in sperm, which in turn could mediate intergenerational effects. Such findings are lacking in humans. My PhD explored the association between paternal metabolic traits and the birth weight of his offspring. I then investigated whether DNA methylation signatures in spermatozoa of obese fathers could underlie any observed association with his offspring birthweight. First, I performed a prospective cohort study of 500 mother-father-offspring trios to identify paternal metabolic traits associated with an increased risk of fathering low birth weight offspring. Out of 390 trios, including 64 obese men and 48 growth restricted offspring, I did not discover any significant paternal metabolic traits associated with fathering low-birthweight offspring. However, I found that paternal (own) birth weight is associated with the birth weight of his offspring. This suggests that paternal genetic factors are more influential in determining his offspring’s growth in utero than are factors acquired during his lifetime. Second, I performed a systematic review of studies that had investigated DNA methylation in human sperm. From this review, I summarised current knowledge and generated recommendations for future research. I then performed the largest characterisation of matched human sperm and blood samples to date using the most comprehensive DNA methylation profiling array, the MethylationEPIC array. Results showed that the DNA methylomes of sperm and blood are highly discordant and in effect completely uncorrelated. Future studies of intergenerational effects will have to study germ cells, rather than blood. Lastly, I attempted to validate previously-identified DNA methylation signatures associated with male obesity. Despite comparing 96 well-characterised obese men with 96 lean men, I was unable to replicate any previously identified differentially methylated CpG sites associated with obesity, in their blood. In a linear regression model, I identified two CpG sites, cg07037944 and cg26651978, as being suggestive of an association with BMI. These results will contribute to a larger cohort study of 1000 obese and 1000 lean men that aims to identify a robust and reproducible DNA methylation profile associated with obesity. In conclusion, this thesis did not prove my pre-determined hypotheses. However, it does present findings which advance our understanding of the intriguing possibility that acquired parental metabolic phenotype may influence offspring birthweight through intergenerational inheritance of epigenetic marks

Mapping transcriptional regulation of cell types and states using systems genetics in mouse

Complex traits are intricately intertwined with an organism's genome, a relationship underscored by the dynamic landscape of its transcriptome. Selective gene expression regulates cell type specialization and fluctuation of cell states. The development of RNA sequencing has facilitated the capture of the whole transcriptome of a given sample. However, a bulk approach obscures cell type heterogeneity, impeding the precise dissection of cell-specific effects, including those modulated by genotype, developmental stage, and disease state. In contrast, single-cell and single-nucleus RNA-seq preserves cellular identity, enabling a comprehensive mapping of gene expression across various cell types and states.Here, I describe my work in single-cell transcriptomics to characterize cell types and cell states in mouse. First, I present our long-read single-cell RNA-seq method, benchmarked in the C2C12 mouse myogenic system, which revealed cell type-specific isoform switching in key genes during myogenesis. Next, I characterize 5 mouse tissues at single-nucleus resolution during postnatal development using the ENCODE4 mouse dataset, where I used topic modeling to reveal cell type- and state-specific cellular programs. Lastly, I investigate the impact of genetic variation on gene expression across 8 diverse tissues from 8 mouse genotypes, pinpointing genotype- driven variation in specific celltypes in both wild-derived and classical lab strains. Together, these projects lay the groundwork for cohesive cell type and cell state annotation and comparative analyses, contributing to future characterization of these tissues in other contexts such as human diseases and hybrid mouse genotypes

Correction to: RNA Bioinformatics.

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Molecular Epidemiology towards Deciphering Underlying Mechanisms of Fatty Liver Disease

A substantial burden of illness and mortality worldwide is caused by fatty liver disease (FLD) and its complications, including type 2 diabetes (T2D), obesity, hypertension, NBHJY98and dyslipidemia. Among the FLD patients, the majority of fatty liver patients develop non-alcoholic fatty liver disease (NAFLD), which is the most common cause of chronic liver disease worldwide. Although there are no or few symptoms, a subpopulation can progress to end-stage liver disease or even liver cancer. Recently, a consensus by an international panel of experts recommended a change in name for NAFLD to metabolic dysfunction associated fatty liver disease (MAFLD). It does not only eliminate alcohol from both the name and definition. However, the underlying mechanism of FLD and how to early diagnose FLD are still not clear. Understanding the pathophysiology of FLD can help to facilitate the prevention and treatment strategies. In this thesis, I aim to provide novel insights into the molecular mechanisms of FLD through several omics approaches and integration of multi-omics, centering on genomics, transcriptomics, metabolomics, and gut microbiota.In Chapter 2, I found that in Rotterdam Study, lower sex hormone-binding globulin (SHBG) was associated with NAFLD both in men and women. Lower testosterone was associated with NAFLD among women. Similarly, the meta-analysis of 16 studies also indicated that there is no sex-specific association between SHBG and NAFLD. Moreover, men with NAFLD had lower testosterone levels than those without NAFLD, while women with NAFLD had higher testosterone levels than those without. In addition, men with NAFLD had lower estradiol levels than those without NAFLD.Chapter 3 focused on investigating the impact of klotho (KL) rs495392 C>A polymorphism on the histological severity of NAFLD. In Chapter 3.1, I found that carriage of the klotho rs495392 A allele, a variant commonly reported to be associated with liver diseases, had a protective effect on steatosis severity in Chinese patients. The effect on NAFLD was confirmed in the Rotterdam Study cohort. The findings also showed the association between serum vitamin D levels and NAFLD specifically in rs495392 A allele carriers, but not in non-carriers. Moreover, I found that the rs495392 A allele attenuated the detrimental impact of the PNPLA3 rs738409 G allele on the risk of severe NAFLD in the Chinese cohort.In Chapter 4, I mainly focused on exploring the epigenetic regulation of FLD and metabolic disorders. In Chapter 4.1, I found two recent epigenome-wide association studies conducted among large population-based cohorts that have reported the association between cg06690548 (SLC7A11) and FLD. Moreover, several studies have demonstrated the association between microRNAs (miRNAs) and FLD, in which miR-122, miR-34a, and miR-192 were recognized as the most relevant miRNAs as biomarkers for FLD. In Chapter 4.2, I found few circulating miRNAs correlated with various non-invasive markers of fatty liver, due to either non-alcoholic or alcohol FLD. The response to the editorial that commented on our paper can be found in Chapter 4.3. In Chapter 4.4, I found the relationship between plasma levels of miRNAs with obesity, body fat distribution, and fat mass using data from the Rotterdam Study. Interestingly, miR-193a-5p, the top obesity-associated miRNA was among the miRNAs I found to be significantly associated with FLD in Chapter 4.1.Finally, in Chapter 5 I explored the potential role of the gut microbiome in liver health and disease. Chapter 5.1, I found that lower microbial alpha diversity was associated with a higher prevalence of MAFLD. Three genera were significantly associated with MAFLD after the false discovery rate was corrected (q-valu