Realizing the potential of full-length transcriptome sequencing

The role of noncoding RNAs in Parkinson's disease: biomarkers and associations with pathogenic pathways

The discovery of various noncoding RNAs (ncRNAs) and their biological implications is a growing area in cell biology. Increasing evidence has revealed canonical and noncanonical functions of long and small ncRNAs, including microRNAs, long ncRNAs (lncRNAs), circular RNAs, PIWI-interacting RNAs, and tRNA-derived fragments. These ncRNAs have the ability to regulate gene expression and modify metabolic pathways. Thus, they may have important roles as diagnostic biomarkers or therapeutic targets in various diseases, including neurodegenerative disorders, especially Parkinson's disease. Recently, through diverse sequencing technologies and a wide variety of bioinformatic analytical tools, such as reverse transcriptase quantitative PCR, microarrays, next-generation sequencing and long-read sequencing, numerous ncRNAs have been shown to be associated with neurodegenerative disorders, including Parkinson's disease. In this review article, we will first introduce the biogenesis of different ncRNAs, including microRNAs, PIWI-interacting RNAs, circular RNAs, long noncoding RNAs, and tRNA-derived fragments. The pros and cons of the detection platforms of ncRNAs and the reproducibility of bioinformatic analytical tools will be discussed in the second part. Finally, the recent discovery of numerous PD-associated ncRNAs and their association with the diagnosis and pathophysiology of PD are reviewed, and microRNAs and long ncRNAs that are transported by exosomes in biofluids are particularly emphasized.

Comparative Analysis of PacBio and Oxford Nanopore Sequencing Technologies for Transcriptomic Landscape Identification of Penaeus monodon

With the advantages that long-read sequencing platforms such as Pacific Biosciences (Menlo Park, CA, USA) (PacBio) and Oxford Nanopore Technologies (Oxford, UK) (ONT) can offer, various research fields such as genomics and transcriptomics can exploit their benefits. Selecting an appropriate sequencing platform is undoubtedly crucial for the success of the research outcome, thus there is a need to compare these long-read sequencing platforms and evaluate them for specific research questions. This study aims to compare the performance of PacBio and ONT platforms for transcriptomic analysis by utilizing transcriptome data from three different tissues (hepatopancreas, intestine, and gonads) of the juvenile black tiger shrimp, Penaeus monodon. We compared three important features: (i) main characteristics of the sequencing libraries and their alignment with the reference genome, (ii) transcript assembly features and isoform identification, and (iii) correlation of the quantification of gene expression levels for both platforms. Our analyses suggest that read-length bias and differences in sequencing throughput are highly influential factors when using long reads in transcriptome studies. These comparisons can provide a guideline when designing a transcriptome study utilizing these two long-read sequencing technologies.

Isoform Age - Splice Isoform Profiling Using Long-Read Technologies

Alternative splicing (AS) of RNA is a key mechanism that results in the expression of multiple transcript isoforms from single genes and leads to an increase in the complexity of both the transcriptome and proteome. Regulation of AS is critical for the correct functioning of many biological pathways, while disruption of AS can be directly pathogenic in diseases such as cancer or cause risk for complex disorders. Current short-read sequencing technologies achieve high read depth but are limited in their ability to resolve complex isoforms. In this review we examine how long-read sequencing (LRS) technologies can address this challenge by covering the entire RNA sequence in a single read and thereby distinguish isoform changes that could impact RNA regulation or protein function. Coupling LRS with technologies such as single cell sequencing, targeted sequencing and spatial transcriptomics is producing a rapidly expanding suite of technological approaches to profile alternative splicing at the isoform level with unprecedented detail. In addition, integrating LRS with genotype now allows the impact of genetic variation on isoform expression to be determined. Recent results demonstrate the potential of these techniques to elucidate the landscape of splicing, including in tissues such as the brain where AS is particularly prevalent. Finally, we also discuss how AS can impact protein function, potentially leading to novel therapeutic targets for a range of diseases.

Long-read RNA sequencing reveals widespread sex-specific alternative splicing in threespine stickleback fish

Alternate isoforms are important contributors to phenotypic diversity across eukaryotes. Although short-read RNA-sequencing has increased our understanding of isoform diversity, it is challenging to accurately detect full-length transcripts, preventing the identification of many alternate isoforms. Long-read sequencing technologies have made it possible to sequence full-length alternative transcripts, accurately characterizing alternative splicing events, alternate transcription start and end sites, and differences in UTR regions. Here, we use Pacific Biosciences (PacBio) long-read RNA-sequencing (Iso-Seq) to examine the transcriptomes of five organs in threespine stickleback fish (Gasterosteus aculeatus), a widely used genetic model species. The threespine stickleback fish has a refined genome assembly in which gene annotations are based on short-read RNA sequencing and predictions from coding sequence of other species. This suggests some of the existing annotations may be inaccurate or alternative transcripts may not be fully characterized. Using Iso-Seq we detected thousands of novel isoforms, indicating many isoforms are absent in the current Ensembl gene annotations. In addition, we refined many of the existing annotations within the genome. We noted many improperly positioned transcription start sites that were refined with long-read sequencing. The Iso-Seq-predicted transcription start sites were more accurate and verified through ATAC-seq. We also detected many alternative splicing events between sexes and across organs. We found a substantial number of genes in both somatic and gonadal samples that had sex-specific isoforms. Our study highlights the power of long-read sequencing to study the complexity of transcriptomes, greatly improving genomic resources for the threespine stickleback fish.

Assessing conservation of alternative splicing with evolutionary splicing graphs

Understanding how protein function has evolved and diversified is of great importance for human genetics and medicine. Here, we tackle the problem of describing the whole transcript variability observed in several species by generalizing the definition of splicing graph. We provide a practical solution to construct parsimonious evolutionary splicing graphs where each node is a minimal transcript building block defined across species. We show a clear link between the functional relevance, tissue regulation, and conservation of alternative transcripts on a set of 50 genes. By scaling up to the whole human protein-coding genome, we identify a few thousand genes where alternative splicing modulates the number and composition of pseudorepeats. We have implemented our approach in ThorAxe, an efficient, versatile, robust, and freely available computational tool.

Next‑generation sequencing analysis reveals that MTH‑3, a novel curcuminoid derivative, suppresses the invasion of MDA‑MB‑231 triple‑negative breast adenocarcinoma cells

Triple‑negative breast cancer (TNBC) behaves aggressively in the invasive and metastatic states. Our research group recently developed a novel curcumin derivative, (1E,3Z,6E)-3-hydroxy-5-oxohepta-1,3,6-triene-1,7-diyl)bis(2‑methoxy-4,1‑phenylene)bis(3-hydroxy2-hydroxymethyl)-2‑methyl propanoate (MTH‑3), and previous studies showed that MTH‑3 inhibits TNBC proliferation and induces apoptosis in vitro and in vivo with a superior bioavailability and absorption than curcumin. In the present study, the effects of MTH‑3 on TNBC cell invasion were examined using various assays and gelatin zymography, and western blot analysis. Treatment with MTH‑3 inhibited MDA‑MB‑231 cell invasion and migration, as shown by Transwell assay, 3D spheroid invasion assay, and wound healing assay. The results of the gelatin zymography experiments revealed that MTH‑3 decreased matrix metalloproteinase‑9 activity. The potential signaling pathways were revealed by next‑generation sequencing analysis, antibody microarray analysis and western blot analysis. In conclusion, the results of the present study show that, MTH‑3 inhibited tumor cell invasion through the MAPK/ERK/AKT signaling pathway and cell cycle regulatory cascade, providing significant information about the potential molecular mechanisms of the effects of MTH‑3 on TNBC.

Evaluation of Oxford Nanopore MinION RNA-Seq Performance for Human Primary Cells

Transcript sequencing is a crucial tool for gaining a deep understanding of biological processes in diagnostic and clinical medicine. Given their potential to study novel complex eukaryotic transcriptomes, long-read sequencing technologies are able to overcome some limitations of short-read RNA-Seq approaches. Oxford Nanopore Technologies (ONT) offers the ability to generate long-read sequencing data in real time via portable protein nanopore USB devices. This work aimed to provide the user with the number of reads that should be sequenced, through the ONT MinION platform, to reach the desired accuracy level for a human cell RNA study. We sequenced three cDNA libraries prepared from poly-adenosine RNA of human primary cardiac fibroblasts. Since the runs were comparable, they were combined in a total dataset of 48 million reads. Synthetic datasets with different sizes were generated starting from the total and analyzed in terms of the number of identified genes and their expression levels. As expected, an improved sensitivity was obtained, increasing the sequencing depth, particularly for the non-coding genes. The reliability of expression levels was assayed by (i) comparison with PCR quantifications of selected genes and (ii) by the implementation of a user-friendly multiplexing method in a single run.

Integrated Signals of Jasmonates, Sugars, Cytokinins and Auxin Influence the Initial Growth of the Second Buds of Chrysanthemum after Decapitation

Decapitation is common in horticulture for altering plant architecture. The decapitation of chrysanthemum plants breaks apical dominance and leads to more flowers on lateral branches, resulting in landscape flowers with good coverage. We performed both third- and second-generation transcriptome sequencing of the second buds of chrysanthemum. This third-generation transcriptome is the first sequenced third-generation transcriptome of chrysanthemum, revealing alternative splicing events, lncRNAs, and transcription factors. Aside from the classic hormones, the expression of jasmonate-related genes changed because of this process. Sugars also played an important role in this process, with upregulated expression of sucrose transport-related and TPS genes. We constructed a model of the initial growth of the second buds after decapitation. Auxin export and sugar influx activated the growth of these buds, while the JA-Ile caused by wounding inhibited the expression of CycD genes from 0 h to 6 h. After wound recovery, cytokinins accumulated in the second buds and might have induced ARR12 expression to upregulate CycD gene expression from 6 h to 48 h, together with sugars. Therefore, jasmonates, cytokinins, sugars, and auxin work together to determine the fate of the buds of plants with short internodes, such as chrysanthemum.

Dynamics of the transcriptional landscape during human fetal testis and ovary development

STUDY QUESTION

Which transcriptional program triggers sex differentiation in bipotential gonads and downstream cellular events governing fetal testis and ovary development in humans?

SUMMARY ANSWER

The characterization of a dynamically regulated protein-coding and non-coding transcriptional landscape in developing human gonads of both sexes highlights a large number of potential key regulators that show an early sexually dimorphic expression pattern.

WHAT IS KNOWN ALREADY

Gonadal sex differentiation is orchestrated by a sexually dimorphic gene expression program in XX and XY developing fetal gonads. A comprehensive characterization of its non-coding counterpart offers promising perspectives for deciphering the molecular events underpinning gonad development and for a complete understanding of the etiology of disorders of sex development in humans.

STUDY DESIGN, SIZE, DURATION

To further investigate the protein-coding and non-coding transcriptional landscape during gonad differentiation, we used RNA-sequencing (RNA-seq) and characterized the RNA content of human fetal testis (N = 24) and ovaries (N = 24) from 6 to 17 postconceptional week (PCW), a key period in sex determination and gonad development.

PARTICIPANTS/MATERIALS, SETTING, METHODS

First trimester fetuses (6-12 PCW) and second trimester fetuses (13-14 and 17 PCW) were obtained from legally induced normally progressing terminations of pregnancy. Total RNA was extracted from whole human fetal gonads and sequenced as paired-end 2 × 50 base reads. Resulting sequences were mapped to the human genome, allowing for the assembly and quantification of corresponding transcripts.

MAIN RESULTS AND THE ROLE OF CHANCE

This RNA-seq analysis of human fetal testes and ovaries at seven key developmental stages led to the reconstruction of 22 080 transcripts differentially expressed during testicular and/or ovarian development. In addition to 8935 transcripts displaying sex-independent differential expression during gonad development, the comparison of testes and ovaries enabled the discrimination of 13 145 transcripts that show a sexually dimorphic expression profile. The latter include 1479 transcripts differentially expressed as early as 6 PCW, including 39 transcription factors, 40 long non-coding RNAs and 20 novel genes. Despite the use of stringent filtration criteria (expression cut-off of at least 1 fragment per kilobase of exon model per million reads mapped, fold change of at least 2 and false discovery rate adjusted P values of less than <1%), the possibility of assembly artifacts and of false-positive differentially expressed transcripts cannot be fully ruled out.

LARGE-SCALE DATA

Raw data files (fastq) and a searchable table (.xlss) containing information on genomic features and expression data for all refined transcripts have been submitted to the NCBI GEO under accession number GSE116278.

LIMITATIONS, REASONS FOR CAUTION

The intrinsic nature of this bulk analysis, i.e. the sequencing of transcripts from whole gonads, does not allow direct identification of the cellular origin(s) of the transcripts characterized. Potential cellular dilution effects (e.g. as a result of distinct proliferation rates in XX and XY gonads) may account for a few of the expression profiles identified as being sexually dimorphic. Finally, transcriptome alterations that would result from exposure to pre-abortive drugs cannot be completely excluded. Although we demonstrated the high quality of the sorted cell populations used for experimental validations using quantitative RT-PCR, it cannot be totally excluded that some germline expression may correspond to cell contamination by, for example, macrophages.

WIDER IMPLICATIONS OF THE FINDINGS

For the first time, this study has led to the identification of 1000 protein-coding and non-coding candidate genes showing an early, sexually dimorphic, expression pattern that have not previously been associated with sex differentiation. Collectively, these results increase our understanding of gonad development in humans, and contribute significantly to the identification of new candidate genes involved in fetal gonad differentiation. The results also provide a unique resource that may improve our understanding of the fetal origin of testicular and ovarian dysgenesis syndromes, including cryptorchidism and testicular cancers.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the French National Institute of Health and Medical Research (Inserm), the University of Rennes 1, the French School of Public Health (EHESP), the Swiss National Science Foundation [SNF n° CRS115_171007 to B.J.], the French National Research Agency [ANR n° 16-CE14-0017-02 and n° 18-CE14-0038-02 to F.C.], the Medical Research Council [MR/L010011/1 to P.A.F.] and the European Community's Seventh Framework Programme (FP7/2007-2013) [under grant agreement no 212885 to P.A.F.] and from the European Union's Horizon 2020 Research and Innovation Programme [under grant agreement no 825100 to P.A.F. and S.M.G.]. There are no competing interests related to this study.

Targeted transcriptome analysis using synthetic long read sequencing uncovers isoform reprograming in the progression of colon cancer

The characterization of human gene expression is limited by short read lengths, high error rates and large input requirements. Here, we used a synthetic long read (SLR) sequencing approach, LoopSeq, to generate accurate sequencing reads that span full length transcripts using standard short read data. LoopSeq identified isoforms from control samples with 99.4% accuracy and a 0.01% per-base error rate, exceeding the accuracy reported for other long-read technologies. Applied to targeted transcriptome sequencing from colon cancers and their metastatic counterparts, LoopSeq revealed large scale isoform redistributions from benign colon mucosa to primary colon cancer and metastatic cancer and identified several previously unknown fusion isoforms. Strikingly, single nucleotide variants (SNVs) occurred dominantly in specific isoforms and some SNVs underwent isoform switching in cancer progression. The ability to use short reads to generate accurate long-read data as the raw unit of information holds promise as a widely accessible approach in transcriptome sequencing.

Multi-omics data integration considerations and study design for biological systems and disease

With the advancement of next-generation sequencing and mass spectrometry, there is a growing need for the ability to merge biological features in order to study a system as a whole. Features such as the transcriptome, methylome, proteome, histone post-translational modifications and the microbiome all influence the host response to various diseases and cancers. Each of these platforms have technological limitations due to sample preparation steps, amount of material needed for sequencing, and sequencing depth requirements. These features provide a snapshot of one level of regulation in a system. The obvious next step is to integrate this information and learn how genes, proteins, and/or epigenetic factors influence the phenotype of a disease in context of the system. In recent years, there has been a push for the development of data integration methods. Each method specifically integrates a subset of omics data using approaches such as conceptual integration, statistical integration, model-based integration, networks, and pathway data integration. In this review, we discuss considerations of the study design for each data feature, the limitations in gene and protein abundance and their rate of expression, the current data integration methods, and microbiome influences on gene and protein expression. The considerations discussed in this review should be regarded when developing new algorithms for integrating multi-omics data.

Transcriptional Landscape of Vero E6 Cells during Early Swine Acute Diarrhea Syndrome Coronavirus Infection

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is a newly emerged and highly pathogenic virus that is associated with fatal diarrhea disease in piglets, causing significant economic losses to the pig industry. At present, the research on the pathogenicity and molecular mechanisms of host-virus interactions of SADS-CoV are limited and remain poorly understood. Here, we investigated the global gene expression profiles of SADS-CoV-infected Vero E6 cells at 12, 18, and 24 h post-infection (hpi) using the RNA-sequencing. As a result, a total of 3324 differentially expressed genes (DEG) were identified, most of which showed a down-regulated expression pattern. Functional enrichment analyses indicated that the DEGs are mainly involved in signal transduction, cellular transcription, immune and inflammatory response, and autophagy. Collectively, our results provide insights into the changes in the cellular transcriptome during early infection of SADS-CoV and may provide information for further study of molecular mechanisms.

Functional Annotation of a Full-Length Transcriptome and Identification of Genes Associated with Flower Development in Rhododendronsimsii (Ericaceae)

Rhododendronsimsii is one of the top ten famous flowers in China. Due to its historical value and high aesthetic, it is widely popular among Chinese people. Various colors are important breeding objectives in Rhododendron L. The understanding of the molecular mechanism of flower color formation can provide a theoretical basis for the improvement of flower color in Rhododendron L. To generate the R.simsii transcriptome, PacBio sequencing technology has been used. A total of 833,137 full-length non-chimeric reads were obtained and 726,846 high-quality full-length transcripts were found. Moreover, 40,556 total open reading frames were obtained; of which 36,018 were complete. In gene annotation analyses, 39,411, 18,565, 16,102 and 17,450 transcriptions were allocated to GO, Nr, KEGG and COG databases, correspondingly. To identify long non-coding RNAs (lncRNAs), we utilized four computational methods associated with Protein families (Pfam), Cooperative Data Classification (CPC), Coding Assessing Potential Tool (CPAT) and Coding Non Coding Index (CNCI) databases and observed 6170, 2265, 4084 and 1240 lncRNAs, respectively. Based on the results, most genes were enriched in the flavonoid biosynthetic pathway. The eight key genes on the anthocyanin biosynthetic pathway were further selected and analyzed by qRT-PCR. The F3'H and ANS showed an upward trend in the developmental stages of R. simsii. The highest expression of F3'5'H and FLS in the petal color formation of R. simsii was observed. This research provided a huge number of full-length transcripts, which will help to proceed genetic analyses of R.simsii. native, which is a semi-deciduous shrub.

Cross-species RNA-seq for deciphering host-microbe interactions

The human body is constantly exposed to microorganisms, which entails manifold interactions between human cells and diverse commensal or pathogenic bacteria. The cellular states of the interacting cells are decisive for the outcome of these encounters such as whether bacterial virulence programmes and host defence or tolerance mechanisms are induced. This Review summarizes how next-generation RNA sequencing (RNA-seq) has become a primary technology to study host-microbe interactions with high resolution, improving our understanding of the physiological consequences and the mechanisms at play. We illustrate how the discriminatory power and sensitivity of RNA-seq helps to dissect increasingly complex cellular interactions in time and space down to the single-cell level. We also outline how future transcriptomics may answer currently open questions in host-microbe interactions and inform treatment schemes for microbial disorders.

The Alter Retina: Alternative Splicing of Retinal Genes in Health and Disease

Alternative splicing of mRNA is an essential mechanism to regulate and increase the diversity of the transcriptome and proteome. Alternative splicing frequently occurs in a tissue- or time-specific manner, contributing to differential gene expression between cell types during development. Neural tissues present extremely complex splicing programs and display the highest number of alternative splicing events. As an extension of the central nervous system, the retina constitutes an excellent system to illustrate the high diversity of neural transcripts. The retina expresses retinal specific splicing factors and produces a large number of alternative transcripts, including exclusive tissue-specific exons, which require an exquisite regulation. In fact, a current challenge in the genetic diagnosis of inherited retinal diseases stems from the lack of information regarding alternative splicing of retinal genes, as a considerable percentage of mutations alter splicing or the relative production of alternative transcripts. Modulation of alternative splicing in the retina is also instrumental in the design of novel therapeutic approaches for retinal dystrophies, since it enables precision medicine for specific mutations.

Error correction enables use of Oxford Nanopore technology for reference-free transcriptome analysis

Oxford Nanopore (ONT) is a leading long-read technology which has been revolutionizing transcriptome analysis through its capacity to sequence the majority of transcripts from end-to-end. This has greatly increased our ability to study the diversity of transcription mechanisms such as transcription initiation, termination, and alternative splicing. However, ONT still suffers from high error rates which have thus far limited its scope to reference-based analyses. When a reference is not available or is not a viable option due to reference-bias, error correction is a crucial step towards the reconstruction of the sequenced transcripts and downstream sequence analysis of transcripts. In this paper, we present a novel computational method to error correct ONT cDNA sequencing data, called isONcorrect. IsONcorrect is able to jointly use all isoforms from a gene during error correction, thereby allowing it to correct reads at low sequencing depths. We are able to obtain a median accuracy of 98.9-99.6%, demonstrating the feasibility of applying cost-effective cDNA full transcript length sequencing for reference-free transcriptome analysis.

Transcript Isoform-Specific Estimation of Poly(A) Tail Length by Nanopore Sequencing of Native RNA

The poly(A) tail is a homopolymeric stretch of adenosine at the 3'-end of mature RNA transcripts and its length plays an important role in nuclear export, stability, and translational regulation of mRNA. Existing techniques for genome-wide estimation of poly(A) tail length are based on short-read sequencing. These methods are limited because they sequence a synthetic DNA copy of mRNA instead of the native transcripts. Furthermore, they can identify only a short segment of the transcript proximal to the poly(A) tail which makes it difficult to assign the measured poly(A) length uniquely to a single transcript isoform. With the introduction of native RNA sequencing by Oxford Nanopore Technologies, it is now possible to sequence full-length native RNA. A single long read contains both the transcript and the associated poly(A) tail, thereby making transcriptome-wide isoform-specific poly(A) tail length assessment feasible. We developed tailfindr-an R-based package for estimating poly(A) tail length from Oxford Nanopore sequencing data. In this chapter, we describe in detail the pipeline for transcript isoform-specific poly(A) tail profiling based on native RNA Nanopore sequencing-from library preparation to downstream data analysis with tailfindr.

Molecular assessment and transcriptome profiling of wild fish populations of Oryzias mekongensis and O. songkhramensis (Adrianichthyidae: Beloniformes) from Thailand

Among the fish of the genus Oryzias, two species are frequently used as model animals in biological research. In Thailand, Oryzias mekongensis is usually found in natural freshwater near the Mekong Basin in the northeast region, while O. songkhramensis inhabits the Songkhram Basin. For differential morphological identification, the coloured bands on the dorsal and ventral margins of the caudal fin are used to distinguish O. mekongensis from O. songkhramensis. However, these characteristics are insufficient to justify species differentiation, and little molecular evidence is available to supplement them. This study aimed to investigate the molecular population and transcriptome profiles of adult O. mekongensis and O. songkhramensis. In the molecular tree based on cytochrome b sequences, O. mekongensis exhibited four clades that were clearly distinguished from O. songkhramensis. Clade 1 of the O. mekongensis population was close to the Mekong River and lived in the eastern portion of the upper northeast region. Clade 2 was far from the Mekong River and inhabited the middle region of the Songkhram River. Clade 3 was positioned to the west of the Songkhram River, and clade 4 was to the south of the Songkhram River Basin. After RNA sequencing using an Illumina HiSeq 2500 platform, the gene category annotations hardly differentiated the species and were discussed in the text. Based on the present findings, population dispersal of these Oryzias species might be associated with geographic variations of the upper northeast region. Molecular genetics and transcriptome profiling might advance our understanding of the evolution of teleost fish.

Synthesizing Systems Biology Knowledge from Omics Using Genome-Scale Models

Omic technologies have enabled the complete readout of the molecular state of a cell at different biological scales. In principle, the combination of multiple omic data types can provide an integrated view of the entire biological system. This integration requires appropriate models in a systems biology approach. Here, genome-scale models (GEMs) are focused upon as one computational systems biology approach for interpreting and integrating multi-omic data. GEMs convert the reactions (related to metabolism, transcription, and translation) that occur in an organism to a mathematical formulation that can be modeled using optimization principles. A variety of genome-scale modeling methods used to interpret multiple omic data types, including genomics, transcriptomics, proteomics, metabolomics, and meta-omics are reviewed. The ability to interpret omics in the context of biological systems has yielded important findings for human health, environmental biotechnology, bioenergy, and metabolic engineering. The authors find that concurrent with advancements in omic technologies, genome-scale modeling methods are also expanding to enable better interpretation of omic data. Therefore, continued synthesis of valuable knowledge, through the integration of omic data with GEMs, are expected.

Centromere studies in the era of 'telomere-to-telomere' genomics

We are entering into an exciting era of genomics where truly complete, high-quality assemblies of human chromosomes are available end-to-end, or from 'telomere-to-telomere' (T2T). This technological advance offers a new opportunity to include endogenous human centromeric regions in high-resolution, sequence-based studies. These emerging reference maps are expected to reveal a new functional landscape in the human genome, where centromere proteins, transcriptional regulation, and spatial organization can be examined with base-level resolution across different stages of development and disease. Such studies will depend on innovative assembly methods of extremely long tandem repeats (ETRs), or satellite DNAs, paired with the development of new, orthogonal validation methods to ensure accuracy and completeness. This review reflects the progress in centromere genomics, credited by recent advancements in long-read sequencing and assembly methods. In doing so, I will discuss the challenges that remain and the promise for a new period of scientific discovery for satellite DNA biology and centromere function.

Single cell ecology

Cells are the building blocks of life, from single-celled microbes through to multi-cellular organisms. To understand a multitude of biological processes we need to understand how cells behave, how they interact with each other and how they respond to their environment. The use of new methodologies is changing the way we study cells allowing us to study them on minute scales and in unprecedented detail. These same methods are allowing researchers to begin to sample the vast diversity of microbes that dominate natural environments. The aim of this special issue is to bring together research and perspectives on the application of new approaches to understand the biological properties of cells, including how they interact with other biological entities. This article is part of a discussion meeting issue 'Single cell ecology'.