# Development and Maintenance of RepeatMasker

> **NIH NIH R01** · INSTITUTE FOR SYSTEMS BIOLOGY · 2020 · $490,561

## Abstract

Mammalian and most other eukaryotic genomes contain a large number of interspersed repeats (IRs), most
of which are copies of transposable elements (TEs) at varying levels of decay. Their presence complicates
many genome sequence analyses, but their accurate identification in an early analysis stage can reduce these
complications. In addition to their pervasiveness, over the last decades the research community has become
widely familiar with their enormous impact on genome activity and evolution.
 Every species has been exposed to a unique, complex set of TEs leaving recognizable copies from as long
ago as 300 million years to as recent as present day. These TEs are uncovered and reconstructed by de novo
discovery methods, often by our RepeatModeler tool, while their copies are then annotated by our
RepeatMasker software. De novo methods can create TE libraries at a reasonable pace, but the product is far
from the desired quality that can be reached by hand curation. With the recent explosive growth in sequenced
species, these finishing steps, perhaps never fully automatable, now form a severe bottleneck in genome
analyses due to a lack of manpower and expertise, while the results, especially when coming from different
research groups, lack consistency and suffer from redundancy. Furthermore, the annotation of genomes for
which high-quality libraries have been created is not keeping up with library improvements due to the
computational burden of re-analysis.
 In this proposal, we describe a plan to alleviate the problems of finishing new repeat libraries: we aim to
exploit the power of multi-species genome alignments, especially in revealing lineage-specific TEs, develop a
web-based workbench based on our TE library finishing tools and strategies, and crowdsource the most
laborious step through the use of gamification. In addition, we propose a new family-centric search strategy
and an incremental annotation approach to provide a tractable solution to the re-analysis problem while also
providing opportunities to improve the annotation quality.

## Key facts

- **NIH application ID:** 9905539
- **Project number:** 5R01HG002939-15
- **Recipient organization:** INSTITUTE FOR SYSTEMS BIOLOGY
- **Principal Investigator:** Arian Fredericus Anthonius Smit
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $490,561
- **Award type:** 5
- **Project period:** 2003-08-15 → 2021-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9905539

## Citation

> US National Institutes of Health, RePORTER application 9905539, Development and Maintenance of RepeatMasker (5R01HG002939-15). Retrieved via AI Analytics 2026-07-28 from https://api.ai-analytics.org/grant/nih/9905539. Licensed CC0.

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