Estimating repeat spectra and genome length from low-coverage genome skims with RESPECT

Abstract

The cost of sequencing the genome is dropping at a much faster rate compared to assembling and finishing the genome. The use of lightly sampled genomes (genome-skims) could be transformative for genomic ecology, and results using k-mers have shown the advantage of this approach in identification and phylogenetic placement of eukaryotic species. Here, we revisit the basic question of estimating genomic parameters such as genome length, coverage, and repeat structure, focusing specifically on estimating the k-mer repeat spectrum. We show using a mix of theoretical and empirical analysis that there are fundamental limitations to estimating the k-mer spectra due to ill-conditioned systems, and that has implications for other genomic parameters. We get around this problem using a novel constrained optimization approach (Spline Linear Programming), where the constraints are learned empirically. On reads simulated at 1X coverage from 66 genomes, our method, REPeat SPECTra Estimation (RESPECT), had 2.2% error in length estimation compared to 27% error previously achieved. In shotgun sequenced read samples with contaminants, RESPECT length estimates had median error 4%, in contrast to other methods that had median error 80%. Together, the results suggest that low-pass genomic sequencing can yield reliable estimates of the length and repeat content of the genome. The RESPECT software will be publicly available at https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_shahab-2Dsarmashghi_RESPECT.git&d=DwIGAw&c=-35OiAkTchMrZOngvJPOeA&r=ZozViWvD1E8PorCkfwYKYQMVKFoEcqLFm4Tg49XnPcA&m=f-xS8GMHKckknkc7Xpp8FJYw_ltUwz5frOw1a5pJ81EpdTOK8xhbYmrN4ZxniM96&s=717o8hLR1JmHFpRPSWG6xdUQTikyUjicjkipjFsKG4w&e=.

De novo genome assembly and genome skims reveal LTRs dominate the genome of a limestone endemic Mountainsnail (Oreohelix idahoensis)

“…To understand how LTRs may be related to species divergence within Oreohelix, we compared repeat content estimated from genome skims, LTR insertion times, and Oreohelix species divergence estimates from a previous study [ 16 ] . Analysis of genome skims using RESPECT v. 1.0.0 [ 36 ] revealed O. idahoensis contains roughly 2–3 fold of high copy repetitive k-mers per million bases compared to a closely related smooth, non-limestone endemic O. s. strigosa and a distantly related smooth, non-limestone species O. jugalis (Table 3 ) . We estimated LTR insertion times by comparing divergence between LTR sister pairs using a previously established molluscan substitution rate (see Materials and Methods).…”

Measuring the Invisible: The Sequences Causal of Genome Size Differences in Eyebrights (Euphrasia) Revealed by k-mers

“…Another possibility is that our sequencing data did not contain a faithful representation of the genome contents of our samples due to some intrinsic bias in the library preparation or sequencing technology (Pfeiffer et al, 2018). It is also notable that different k-mer-based tools produce different genome size estimates, suggesting that some models are more accurate than others (Melsted and Halldórsson, 2014;Sarmashghi et al, 2021). Finally, there is also error associated with genome size estimates made with flow cytometry, most notably that certain dyes will bind to particular sequence motifs (Doležel et al, 1998), and that sizing is made indirectly relative to a reference standard (which is also subject to associated error).…”

De novo genome assembly and genome skims reveal LTRs dominate the genome of a limestone endemic Mountainsnail (Oreohelix idahoensis)

“…To understand how LTRs may be related to species divergence within Oreohelix, we compared repeat content estimated from genome skims, LTR insertion times, and Oreohelix species divergence estimates from a previous study [14]. Analysis of genome skims using RESPECT v. 1.0.0 [34] revealed O. idahoensis contains roughly 2-3 fold of high copy repetitive k-mers per million bases compared to a closely related smooth, non-limestone endemic O. s. strigosa and a distantly related smooth, non-limestone species O. jugalis (Table 3). We estimated LTR insertion times by comparing divergence between LTR sister pairs using a previously established molluscan substitution rate (see Materials and Methods).…”

“…Finally, we examined genome size estimates of the closely related O. s. strigosa and distantly related O. jugalis by analyzing k-mer counts of genome skims using RESPECT v.1.0.0 [34]. Genome size estimates were roughly 1.5 times greater for O. idahoensis genome skims compared to either smooth form species (~ 9 Gb :~6 Gb; Table 3).…”

“…Genome size estimates were roughly 1.5 times greater for O. idahoensis genome skims compared to either smooth form species (~ 9 Gb :~6 Gb; Table 3). While the speci c base pair estimates for genome size from genome skims may be off for all Oreohelix due to their relatively high repeat content [34], the relative differences in estimated genome size of O. idahoensis and other Oreohelix species is likely real given their stark differences in repetitive k-mer content.…”