Repeat Annotation Service

What is Repeat Annotation?

Repeat Annotation is a crucial step in genome analysis, focused on identifying and characterizing repetitive sequences within genomic data. These repetitive elements, which can include transposable elements, tandem repeats, and other sequence motifs, often play significant roles in genome evolution, regulation, and structure. By accurately annotating these sequences, researchers can better understand the complexity of genomic architecture and the functional implications of repetitive DNA.

Classification of Repetitive Sequences

Transposable Elements (TEs):

• Class I: Retrotransposons: These elements move within the genome via an RNA intermediate. They include Long Interspersed Nuclear Elements (LINEs), Short Interspersed Nuclear Elements (SINEs), and Long Terminal Repeat (LTR) retrotransposons.
• Class II: DNA Transposons: These elements move directly through a "cut-and-paste" mechanism involving DNA intermediates, often contributing to genome rearrangements and mutations.

Figure 1. Types of TEs. LTR retrotransposons have a primer binding site (PBS), a polypurine tract (PPT), and may include an env gene. Non-LTR retrotransposons include LINEs with two ORFs and SINEs with no coding capacity. Autonomous helitrons encode a helicase and an RPA-like protein. (Letat, 2010)

Tandem Repeats:

• Microsatellites: Also known as Short Tandem Repeats (STRs), these consist of short, repeating units of 1-6 base pairs in length. They are highly polymorphic and used extensively in genetic mapping, population studies, and forensic analysis.
• Minisatellites: Larger than microsatellites, these repeats typically range from 10-60 base pairs. They are often found in telomeric regions and can play roles in gene regulation and chromosomal stability.
• Satellites: These are large blocks of tandemly repeated DNA found in heterochromatic regions of chromosomes, such as centromeres. They are crucial for maintaining chromosomal integrity during cell division.

Segmental Duplications: Large, duplicated regions of the genome that can span thousands to millions of base pairs. These duplications contribute to genomic diversity and evolution but are also associated with genomic disorders due to unequal crossing over.

Simple Sequence Repeats (SSRs): Repeated sequences of 1-6 nucleotides in length, commonly used as molecular markers in genetic studies.

Low-Complexity Regions: Regions of the genome with sequences that have a lower complexity than the surrounding DNA, often consisting of simple repeats. These regions can be challenging to annotate due to their repetitive nature.

Application of Repeat Annotation

• Genome Evolution Studies: Repeat Annotation reveals the dynamics of TEs and other repetitive sequences, providing insights into genome evolution and speciation.
• Functional Genomics: By identifying regulatory elements within repetitive regions, this analysis aids in understanding gene regulation mechanisms and their impact on gene expression.
• Comparative Genomics: Repeat content variation across species can highlight evolutionary changes and identify conserved elements crucial for species-specific traits.
• Disease Mechanism Research: Understanding the role of repetitive elements in genome instability, such as in cancer, helps uncover the underlying mechanisms of various diseases.
• Structural Variation Analysis: Repeat Annotation assists in identifying structural variants, including insertions, deletions, and duplications, which are often mediated by repetitive sequences.
• Agricultural Genomics: Annotating repeats in crop genomes aids in breeding programs by identifying regions linked to important traits, such as yield, disease resistance, and environmental adaptation.

CD Genomics Repeat Annotation Workflow

Sample Submission Guidelines

Bioinformatics Analysis Content

What Are the Advantages of Our Services?

Comprehensive Repeat Annotation Analysis

Our Repeat Annotation services offer an in-depth analysis of repetitive elements, including tandem repeats, interspersed repeats, and TEs, across the genome. Utilizing advanced tools such as RepeatMasker, RepeatModeler, and Tandem Repeats Finder, we accurately identify and classify various types of repeats, providing critical insights into genome architecture, evolution, and functional genomics.

Highly Specialized Analytical Pipelines

Our analytical pipelines are meticulously designed to handle the complexities of repeat-rich regions in large and complex genomes. We employ a combination of homology-based and de novo approaches to detect novel repeat elements, ensuring a comprehensive and precise annotation. These pipelines are optimized for high-throughput processing, allowing for the efficient analysis of large datasets, whether from whole-genome sequencing (WGS) or targeted sequencing projects.

Integration with Multi-Omics Data

We enhance our Repeat Annotation services by integrating them with multi-omics data, including transcriptomics, proteomics, and epigenomics. This integration allows us to investigate the regulatory roles of repetitive elements in gene expression, chromatin structure, and epigenetic modifications. By correlating repeat element activity with differential gene expression and epigenetic marks, we provide a more nuanced understanding of the functional significance of repeats in various biological contexts.

Advanced Bioinformatics Techniques

Our Repeat Annotation services are supported by state-of-the-art bioinformatics methodologies, including Hidden Markov Models (HMMs) for repeat family classification, and clustering algorithms for the discovery of novel repeat families. We also employ comparative genomics approaches to track the evolution and diversification of repeats across species, offering insights into genome plasticity and adaptive evolution.

Customizable and Scalable Solutions

Our Repeat Annotation services are designed with flexibility in mind, allowing for customization to suit the specific requirements of each project. Whether you're conducting a genome-wide analysis in a model organism or exploring repeat dynamics in non-model species, our scalable solutions are tailored to meet your research objectives. We provide options for deep annotation of specific repeat classes or comprehensive surveys of entire genomic landscapes, ensuring that our analyses align with your data and research goals.

Data Security and Compliance

The significance of data security in genomic research is well recognized. To address this, our systems are engineered to meet rigorous data protection standards. Client data is encrypted, securely stored, and processed in accordance with international regulations, including GDPR and HIPAA. This comprehensive data security strategy safeguards sensitive information and underscores our dedication to upholding the highest levels of trust and confidentiality in our collaborations.

What Does Repeat Annotation Show?

Example of Repeat Annotation Input Data

• Genome Sequence File: This FASTA file contains the complete DNA sequences of the organism's genome, serving as the primary input for repeat annotation.
  Example file: arabidopsis_genome.fasta
• Repeat Sequence Database: This file includes known repetitive elements used to identify and classify repeats within the genome sequence.
  Example file: Repbase20.05.fasta
• Annotation File: A GFF or BED file that provides coordinates and descriptions of known repetitive elements within the genome.
  Example file: repeats_annotation.gff3

TE Transcript Annotation

A comprehensive transcript annotation of TEs in Arabidopsis was conducted using sequencing data from the ddm1 rdr6 pol V triple mutant. This analysis provided 2188 transcript models corresponding to 1292 distinct TEs, highlighting transcription start sites (TSSs), splicing patterns, and polyadenylation sites. The majority of annotated TEs are Gypsy LTR retrotransposons, followed by DNA transposons like Mutator and EnSpm. The study confirmed that TE transcript annotation significantly enhances the alignment accuracy of TE sequences, as validated by independent RNA-seq data.

Figure 2. (A) Annotated features of TEs before and after this study. (B) Chromosomal locations of expressed TEs. (C) Alignment of Illumina RNA-seq reads to the 5′ edges of all TEs. (D) Alignment of TEs divided into expression categories based on sequencing data. (E) Comparison of TE alignment by 5′ edge versus annotated TSS. (Panda, 2020)

Repetitive Elements Analysis

The analysis of repetitive elements in the Callosobruchus maculatus genome revealed that repetitive sequences initially accounted for 70% of the assembly. Through manual curation, 83 of 89 unclassified repeat subfamilies were categorized into DNA transposons (67), LINEs (7), LTR retrotransposons (7), and satellite DNA (2). This reduced the proportion of unclassified repeats from 31% to 24%. Among classified repeats, DNA transposons were the most prevalent, covering 18% of the genome, followed by LINEs at 13% and LTR retrotransposons at 2.3%.

Figure 3. Repeat landscape of the C. maculatus genome. (Arnqvist, 2024)

Title: Characterization and functional annotation of nested transposable elements in eukaryotic genomes

Publication: Genomics

Main Methods: Repeat Annotation, Functional Annotation 

Abstract: This study examines the occurrence and evolutionary significance of TEs within eukaryotic genomes, focusing on the detection and characterization of nested TEs. Utilizing a comprehensive analysis of available genome sequences, we identified intact and nested TEs, quantifying the proportion and insertion bias of young nested elements. Our findings reveal a significant association between nested TEs and their host elements, particularly within regions of high TE density. Functional annotation and evolutionary analysis underscore the role of nested TEs in genome restructuring, gene expression regulation, and the emergence of novel genes. This study highlights the complex interactions between TEs and host genomes, providing new insights into genome evolution and the potential functions of nested TEs in various species.

Research Results:

Distribution of Nested TEs Across Species

An analysis across 36 eukaryotic species revealed notable variation in the distribution of nested TEs. On average, each species contained 19 nested TEs, with a higher concentration in Embryophyta (46.9 per species) compared to Coelomata (4.3 per species). Within this distribution, Gnathostomata and Poaceae stood out, harboring the majority of nested TEs, particularly in species such as Branchiostoma floridae and Equus caballus in the former, and rice (Oryza sativa) in the latter. Rice exhibited the highest density of nested TEs, with 482 instances, which constituted 14.3% of its total TEs. The study also found a significant preference for certain nested patterns, with En/spm-type DNA TEs frequently inserting into DNA/hAT TEs, and LTR/Gypsy-type TEs showing a bias toward Ty1/copia within the rice genome.

Figure 4. Number of nested TEs across various taxonomic classes, showing the ratio of nested TEs to the total TEs within each clade. (Gao, 2012)

Insertion Patterns of Nested TEs

The analysis of 802 nested TEs revealed distinct insertion preferences across various TE families. The majority (60.7%) of nested TEs were inserted into TIR DNA transposons, followed by 24.6% into LTRs and 10.2% into LINEs. A smaller proportion of insertions occurred in SINEs, MITEs, and Helitrons. Within the TIR DNA transposons, the TIR/hAT sub-family was predominantly targeted, with a significant number of TIR/En-Spm elements inserting into other TIR/hAT transposons. Similarly, LTR/Gypsy elements showed a preference for inserting into LTR/Copia, and LINE elements often inserted into other LINEs, particularly within the LINE/CR1 subfamily. These findings highlight a tendency for TEs to insert into host elements of the same type, particularly within DNA transposons and retrotransposons, indicating a level of specificity in TE nesting behavior.

Figure 5. (a) Statistical distribution of nested TE subclasses. Breakdown of TE superfamilies inserted into (b) TIR DNA transposons, (c) LINE elements, and (d) LTR retrotransposons. (Gao, 2012)

Distribution of Nested TEs Across Genomic Regions

The analysis of 802 nested TEs shows that most (94.6%) are inserted within gene-associated regions, primarily exons (60.4%) and introns (16.9%). DNA transposons predominantly target exons (71.9%), whereas retrotransposons are more evenly distributed between exons (46.1%) and introns (13.0%). These insertion patterns suggest that nested TEs frequently disrupt coding regions, which may impact gene function.

Figure 6: Illustration of nested TE distribution across various gene regions. (Gao, 2012)

Functional Annotation of Genes Containing Nested TEs

Functional annotation of 600 active genes containing nested TEs revealed diverse roles in cellular components, molecular functions, and biological processes. Most of these genes were associated with non-specific organelles, membrane-bounded vesicles, and the cytoplasm. Binding proteins were predominant in their molecular functions, particularly those involved in nucleic acid interactions. Metabolic processes, especially nitrogen and nucleic acid metabolism, were the most common biological activities. These findings suggest that nested TEs significantly influence gene function, particularly in metabolic pathways and cellular structure.

Figure 7. Depicts the functional annotation of nested TE genes across cellular components, molecular functions, and biological processes. (Gao, 2012)

Conclusion

The study underscores the substantial influence of nested TEs on genome evolution. These elements frequently insert into exonic and intronic regions, thereby affecting gene function. Functional annotation reveals that nested TEs are pivotal in crucial cellular processes, particularly in metabolism and structural integrity. Overall, this research enhances the understanding of the evolutionary and functional roles of TEs in eukaryotic genomes.

1. What is Repeat Annotation in genomics?

Repeat Annotation is the process of identifying and classifying repetitive DNA sequences within a genome. These repeats can include TEs, tandem repeats, and other repetitive sequences. Repeat Annotation is crucial for understanding genome structure, evolution, and function, as these elements can influence gene regulation, chromatin organization, and genome stability.

2. Why is Repeat Annotation important in genome analysis?

Repeat Annotation is essential because repetitive elements make up a significant portion of many genomes, especially in plants and animals. Accurately annotating these sequences is crucial for genome assembly, gene prediction, and understanding the evolutionary history of species. It also helps in identifying functional elements that may be involved in gene regulation or chromosomal rearrangements.

3. What tools are commonly used for Repeat Annotation?

Common tools for Repeat Annotation include RepeatMasker, RepeatModeler, and Tandem Repeats Finder. RepeatMasker uses a library of known repeat sequences to mask repetitive elements in the genome, while RepeatModeler identifies novel repeats. Tandem Repeats Finder is specifically designed to detect tandem repeat sequences, which are arrays of repeated DNA sequences found adjacent to each other.

4. Can Repeat Annotation be integrated with other genomic analyses?

Yes, Repeat Annotation can be integrated with other genomic analyses, such as gene expression profiling, epigenetic studies, and comparative genomics. This integration allows researchers to explore the functional roles of repetitive elements in gene regulation, chromatin structure, and species-specific genome evolution, providing a more comprehensive understanding of the genome.

5. What challenges are associated with Repeat Annotation?

Repeat Annotation can be challenging due to the high diversity and complexity of repetitive elements, particularly in large genomes with a high repeat content. Accurate annotation requires sophisticated tools and algorithms that can distinguish between different types of repeats and correctly classify novel elements. Additionally, repetitive sequences can complicate genome assembly and gene prediction, making their accurate annotation crucial.

6. How does Repeat Annotation contribute to understanding genome evolution?

Repeat Annotation provides insights into genome evolution by revealing how repetitive elements have contributed to genome expansion, rearrangements, and the creation of new genes. By comparing repeats across species, researchers can track the evolutionary history of these elements and understand their impact on genome structure and function over time.

7. What are the typical outputs of a Repeat Annotation analysis?

The typical outputs of a Repeat Annotation analysis include a list of identified repeat sequences, their classification (e.g., TEs, tandem repeats), and their genomic locations. The analysis may also provide information on the abundance and distribution of these repeats across the genome, as well as any novel repeats discovered during the analysis.

8. How does Repeat Annotation impact downstream genomic analyses?

Accurate Repeat Annotation is critical for downstream genomic analyses, such as gene prediction, variant calling, and comparative genomics. Misannotated repeats can lead to errors in gene models and genomic alignments, impacting the reliability of these analyses. Proper annotation ensures that repeats are correctly masked or accounted for, leading to more accurate and meaningful results.

References

1. Lerat, E. Identifying repeats and transposable elements in sequenced genomes: how to find your way through the dense forest of programs. Heredity. 2010, 104(5), 520–533.
2. Arnqvist, G.; et al. A chromosome-level assembly of the seed beetle Callosobruchus maculatus genome with annotation of its repetitive elements. G3 Genes|Genomes|Genetics. 2024, 14(2), jkad266.
3. Panda, K.; Slotkin, R. K. Long-Read cDNA Sequencing Enables a "Gene-Like" Transcript Annotation of Transposable Elements. The Plant Cell. 2020, 32(9), 2687–2698.
4. Gao, C.; et al. Characterization and functional annotation of nested transposable elements in eukaryotic genomes. Genomics. 2012, 100(4), 222-230.