The (r)evolution of SINE versus LINE distributions in primate genomes: Sex chromosomes are important

Abstract

The densities of transposable elements (TEs) in the human genome display substantial variation both within individual chromosomes and among chromosome types (autosomes and the two sex chromosomes). Finding an explanation for this variability has been challenging, especially in light of genome landscapes unique to the sex chromosomes. Here, using a multiple regression framework, we investigate primate Alu and L1 densities shaped by regional genome features and location on a particular chromosome type. As a result of our analysis, first, we build statistical models explaining up to 79% and 44% of variation in Alu and L1 element density, respectively. Second, we analyze sex chromosome versus autosome TE densities corrected for regional genomic effects. We discover that sex-chromosome bias in Alu and L1 distributions not only persists after accounting for these effects, but even presents differences in patterns, confirming preferential Alu integration in the male germline, yet likely integration of L1s in both male and female germlines or in early embryogenesis. Additionally, our models reveal that local base composition (measured by GC content and density of L1 target sites) and natural selection (inferred via density of most conserved elements) are significant to predicting densities of L1s. Interestingly, measurements of local double-stranded breaks (a 13-mer associated with genome instability) strongly correlate with densities of Alu elements; little evidence was found for the role of recombination-driven deletion in driving TE distributions over evolutionary time. Thus, Alu and L1 densities have been influenced by the combination of distinct local genome landscapes and the unique evolutionary dynamics of sex chromosomes.

Widespread occurrence of power-law distributions in inter-repeat distances shaped by genome dynamics

“…Ignoring the very small divergence values, the X/A ratios for the cow, opossum and dog genomes are larger than the ratios for chimpanzee, rat, mouse and human. Notice that X/A TE population ratios, expected purely on the basis of germline transmission, are only approximations of the really observed ones, which are also influenced by different chromosomal GC content, recombination rates and other factors (Kvikstad and Makova, 2010). We observe that genomes with a low X/A ratio, close to the value corresponding to paternal SINE transmission, exhibit a higher propensity for power-law formation.…”

“…It remains to be shown whether low recombinational propensity is related to the maternal SINE transmission in general, as indicated by the correlation between maternal transmission and scarceness of power-laws in inter-repeat distances. We did not perform an analogous study for L1 elements, as they accumulate on chromosome X due to selection related to their participation in the X-inactivation (Abrusan et al, 2008;Kvikstad and Makova, 2010).…”

The effects of chromatin organization on variation in mutation rates in the genome

“…Mutation rates not only differ between autosomes and the two sex chromosomes due to male mutation bias 10 , but also vary along individual chromosomes, a phenomenon termed regional variation in mutation rates (RViMR 3 ; reviewed in 4 ). RViMR was originally demonstrated for base substitutions 1-3,5 , but was soon extended to include small insertions 6 , small deletions 3,6 , and TE insertions 3,5,7,8,11 ( Figure 1 ). Moreover, a substantial co-variation has been found among rates of different mutation types 3,7,9 .…”

“…Insertion preferences of TEs are also determined in part by the genomic landscape. For instance, some of these same genomic landscape features plus recombination hotspot frequency, LINE target sequence frequency, and frequencies of the genome instability 13-mer and of the telomere hexamer ( Table 1 ) can account for 20% and 41% of the variability in insertion rates for young (human-specific) Alu s and L1s 8 , respectively. These landscape features also contribute to the preferences of ex vivo DNA transposon 11 and Alu 26 integrations.…”

“…However, studies built upon alignments among closely related primates showed distinct rates and patterns for different types of mutations 6,8,9,22 ( Table 1 ). Resolving these links between genomic features and mutation rates/patterns for distinct types of mutations assists in elucidating the causes of RViMR, thereby uncovering the intricacies of different mechanisms of mutagenesis.…”