PAIR: polymorphic Alu insertion recognition

Study of Transposable Elements and Their Genomic Impact

Transposable elements (TEs) have been considered traditionally as junk DNA, i.e., DNA sequences that despite representing a high proportion of genomes had no evident cellular functions. However, over the last decades, it has become undeniable that not only TE-derived DNA sequences have (and had) a fundamental role during genome evolution, but also TEs have important implications in the origin and evolution of many genomic disorders. This concise review provides a brief overview of the different types of TEs that can be found in genomes, as well as a list of techniques and methods used to study their impact and mobilization. Some of these techniques will be covered in detail in this Method Book.

PopAlu: population-scale detection of Alu polymorphisms

Alu elements are sequences of approximately 300 basepairs that together comprise more than 10% of the human genome. Due to their recent origin in primate evolution some Alu elements are polymorphic in humans, present in some individuals while absent in others. We present PopAlu, a tool to detect polymorphic Alu elements on a population scale from paired-end sequencing data. PopAlu uses read pair distance and orientation as well as split reads to identify the location and precise breakpoints of polymorphic Alus. Genotype calling enables us to differentiate between homozygous and heterozygous carriers, making the output of PopAlu suitable for use in downstream analyses such as genome-wide association studies (GWAS). We show on a simulated dataset that PopAlu calls Alu elements inserted and deleted with respect to a reference genome with high accuracy and high precision. Our analysis of real data of a human trio from the 1000 Genomes Project confirms that PopAlu is able to produce highly accurate genotype calls. To our knowledge, PopAlu is the first tool that identifies polymorphic Alu elements from multiple individuals simultaneously, pinpoints the precise breakpoints and calls genotypes with high accuracy.

Detecting Alu insertions from high-throughput sequencing data

High-throughput sequencing technologies have allowed for the cataloguing of variation in personal human genomes. In this manuscript, we present alu-detect, a tool that combines read-pair and split-read information to detect novel Alus and their precise breakpoints directly from either whole-genome or whole-exome sequencing data while also identifying insertions directly in the vicinity of existing Alus. To set the parameters of our method, we use simulation of a faux reference, which allows us to compute the precision and recall of various parameter settings using real sequencing data. Applying our method to 100 bp paired Illumina data from seven individuals, including two trios, we detected on average 1519 novel Alus per sample. Based on the faux-reference simulation, we estimate that our method has 97% precision and 85% recall. We identify 808 novel Alus not previously described in other studies. We also demonstrate the use of alu-detect to study the local sequence and global location preferences for novel Alu insertions.

Mobile element biology: new possibilities with high-throughput sequencing

Mobile elements comprise more than half of the human genome, but until recently their large-scale detection was time consuming and challenging. With the development of new high-throughput sequencing (HTS) technologies, the complete spectrum of mobile element variation in humans can now be identified and analyzed. Thousands of new mobile element insertions (MEIs) have been discovered, yielding new insights into mobile element biology, evolution, and genomic variation. Here, we review several high-throughput methods, with an emphasis on techniques that specifically target MEIs in humans. We highlight recent applications of these methods in evolutionary studies and in the analysis of somatic alterations in human normal and tumor tissues.