Repetitive elements may comprise over two-thirds of the human genome

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.

Figure 1. Principles of repeat identification using P-clouds.

A) True data distribution representing divergence within a TE family from a master element sequence (center). B) Consensus sequence based search throws away information by collapsing observed data to a single sequence. C) P-clouds clusters related high-abundance oligos, thus providing better coverage of sequence space.

Figure 2. P-clouds and RepeatMasker annotation of the repeat structure of the human genome.

Results are displayed as a percentage of the ungapped genome assembly length. A) Consensus results prior to this study indicate that <50% of the genome is repetitive (RepeatMasker). B) Analysis using P-clouds suggests more than two-thirds of the genome is repetitive or repeat-derived.

Figure 3. Percentage of previously-identified transposable elements annotated by P-clouds.

A) The percentage of nucleotides and repeats for each family or repeat classification group. B) The number of nucleotides annotated or missed.

Figure 4. Percentage of Alu elements in different Alu subfamilies not annotated by P-clouds analysis.

Displayed are elements for which no portion was annotated. The relative age of Alu subfamilies increases from left to right.

Figure 5. Percent detection success for fragments of known full-length SINE elements.

A) Alu regions. B) MIR regions. Identification success is displayed as a running average of 10 bp starting positions.

Figure 6. MIR element-specific P-clouds detect the short fragments that RepeatMasker cannot.

A) Predicted true distribution of MIR fragments in the human genome, using observed RepeatMasker results and RepeatMasker's sensitivity estimates from Figure 5B. B) Novel P-clouds annotations on the RepeatMasked portion of the human genome, minus predicted false positives from dinucleotide simulations (see text).