Repetitive Elements May Comprise Over Two-Thirds of the Human Genome

TLDR

Transposable elements are typically identified by aligning to consensus sequences, a method that has previously classified about half of the human genome as transposable elements and low‑complexity repeats. The study investigates the discrepancy between this conventional approach and the newly developed P‑clouds method by comparing their ability to detect fragments of Alu and MIR SINEs. The authors introduced P‑clouds, a de novo oligonucleotide‑cloud strategy that identifies high‑abundance sequence clusters, and extended it with probabilistic annotation and element‑specific ESPs to uncover novel Alu and MIR elements. P‑clouds predicts an additional 840 Mbp of repeats, raising the repetitive fraction to 66–69 % of the genome, and the ESP analysis uncovered ~100 Mbp of novel Alu and MIR elements, confirming that conventional methods miss substantial repeat content and underscoring the need for probabilistic annotation.

Abstract

Transposable elements (TEs) are conventionally identified in eukaryotic genomes by alignment to consensus element sequences. Using this approach, about half of the human genome has been previously identified as TEs and low-complexity repeats. We recently developed a highly sensitive alternative de novo strategy, P-clouds, that instead searches for clusters of high-abundance oligonucleotides that are related in sequence space (oligo "clouds"). We show here that P-clouds predicts >840 Mbp of additional repetitive sequences in the human genome, thus suggesting that 66%–69% of the human genome is repetitive or repeat-derived. To investigate this remarkable difference, we conducted detailed analyses of the ability of both P-clouds and a commonly used conventional approach, RepeatMasker (RM), to detect different sized fragments of the highly abundant human Alu and MIR SINEs. RM can have surprisingly low sensitivity for even moderately long fragments, in contrast to P-clouds, which has good sensitivity down to small fragment sizes (∼25 bp). Although short fragments have a high intrinsic probability of being false positives, we performed a probabilistic annotation that reflects this fact. We further developed "element-specific" P-clouds (ESPs) to identify novel Alu and MIR SINE elements, and using it we identified ∼100 Mb of previously unannotated human elements. ESP estimates of new MIR sequences are in good agreement with RM-based predictions of the amount that RM missed. These results highlight the need for combined, probabilistic genome annotation approaches and suggest that the human genome consists of substantially more repetitive sequence than previously believed.