Reading TE leaves: New approaches to the identification of transposable element insertions

Abstract

Transposable elements (TEs) are a tremendous source of genome instability and genetic variation. Of particular interest to investigators of human biology and human evolution are retrotransposon insertions that are recent and/or polymorphic in the human population. As a consequence, the ability to assay large numbers of polymorphic TEs in a given genome is valuable. Five recent manuscripts each propose methods to scan whole human genomes to identify, map, and, in some cases, genotype polymorphic retrotransposon insertions in multiple human genomes simultaneously. These technologies promise to revolutionize our ability to analyze human genomes for TE-based variation important to studies of human variability and human disease. Furthermore, the approaches hold promise for researchers interested in nonhuman genomic variability. Herein, we explore the methods reported in the manuscripts and discuss their applications to aspects of human biology and the biology of other organisms.

Human Pavlovian fear conditioning conforms to probabilistic learning

“…We included a Rescorla-Wagner (RW) model [13] which in our paradigm makes similar predictions as a more general temporal difference rule [32]. A hybrid RW-Pearce-Hall model (HM) [33] which has been used to specifically explain SCR in threat learning, and augments the RW model with a notion of associability [14].…”

“…The RW model [13] specifies that US prediction ('associative strength') is updated according to a signed prediction error signal (i.e. the difference between the prediction on a given trial, x t and the observed sensory input, u t ), weighted by a fixed learning rate, η which is a subject-specific free parameter across both CS, such that such that 0< η <1: …”

“…Previous models proposed to explain Pavlovian threat learning are derived from classical reinforcement learning (RL) theory and build on Rescorla-Wagner (RW) [13] and Pearce-Hall (PH) [14] rules. Other studies suggested that a combination of these models best captures aversive learning [15,16] (hybrid model, HM).…”

Copy Number Variation in Transcriptionally Active Regions of Sexual and Apomictic Boechera Demonstrates Independently Derived Apomictic Lineages

“…Because of their deleterious effects, TE insertions are expected to be under purifying selection (Hollister and Gaut 2009), leading to lower levels of TEs in selfers compared with outcrossers (Morgan 2001;Lockton and Gaut 2010). Moreover, the mating system in plants has been shown to influence TE accumulation and distribution (Morgan 2001;Lockton and Gaut 2010), and there is evidence that genome size variability is influenced by TEs (Bennetzen et al 2005;Ray and Batzer 2011). In apomicts, TE accumulation has been implicated in the evolution of genomic regions that harbor apomixis factors (Akiyama et al 2004;Okada et al 2011) and is hypothesized to be a factor that contributes to eventual lineage extinction (Dolgin and Charlesworth 2006).…”

Functional characterization of piggyBat from the bat Myotis lucifugus unveils an active mammalian DNA transposon

“…Future studies shall focus on quantifying the level of piggyBat transposase expression in different bat tissues and examining whether host defense pathways known to repress retroelements in some mammals (e.g., small RNAs, DNA methylation) are operating to control piggyBat transposition. The recent development of high-throughput technologies to display and capture recent and de novo transposition events, both somatic and germ line, in organisms (38,39) should be readily applicable to estimate the frequency of piggyBat transposition in natural populations and to assess the amount of structural genomic variation mediated by recent and likely ongoing piggyBat activity.…”