Mobile introns shape the genetic diversity of their host genes

Self-splicing introns populate several highly conserved protein-coding genes in fungal and plant mitochondria. In fungi, many of these introns have retained their ability to spread to intron-free target sites, often assisted by intron-encoded endonucleases that initiate the homing process. Here, leveraging population genomic data from Saccharomyces cerevisiae, Schizosaccharomyces pombe, and Lachancea kluyveri, we expose non-random patterns of genetic diversity in exons that border self-splicing introns. In particular, we show that, in all three species, the density of single nucleotide polymorphisms increases as one approaches a mobile intron. Through multiple lines of evidence we rule out relaxed purifying selection as the cause of uneven nucleotide diversity. Instead, our findings implicate intron mobility as a direct driver of host gene diversity. We discuss two mechanistic scenarios that are consistent with the data: either endonuclease activity and subsequent error-prone repair have left a mutational footprint on the insertion environment of mobile introns or non-random patterns of genetic diversity are caused by exonic co-conversion, which occurs when introns spread to empty target sites via homologous recombination. Importantly, however, we show that exonic co-conversion can only explain diversity gradients near intron-exon boundaries if the conversion templates comes from outside the population. In other words, there must be pervasive and ongoing horizontal gene transfer of self-splicing introns into extant fungal populations.

An Entamoeba histolytica LINE/SINE Pair Inserts at Common Target Sites Cleaved by the Restriction Enzyme-Like LINE-Encoded Endonuclease

ABSTRACT The non-long-terminal-repeat (non-LTR) retrotransposons (also called long interspersed repetitive elements [LINEs]) are among the oldest retroelements. Here we describe the properties of such an element from a primitive protozoan parasite, Entamoeba histolytica, that infects the human gut. This 4.8-kb element, called EhLINE1, is present in about 140 copies dispersed throughout the genome. The element belongs to the R4 clade of non-LTR elements. It has a centrally located reverse transcriptase domain and a restriction enzyme-like endonuclease (EN) domain at the carboxy terminus. We have cloned and expressed a 794-bp fragment containing the EN domain in Escherichia coli. The purified protein could nick supercoiled pBluescript DNA to yield open circular and linear DNAs. The conserved PDX12-14D motif was required for activity. Genomic sequences flanking the sites of insertion of EhLINE1 and the putative partner short interspersed repetitive element (SINE), EhSINE1, were analyzed. Both elements resulted in short target site duplications (TSD) upon insertion. A common feature was the presence of a short T-rich stretch just upstream of the TSD in most insertion sites. By sequence analysis an empty target site in the E. histolytica genome, known to be occupied by EhSINE1, was identified. When a 176-bp fragment containing the empty site was used as a substrate for EN, it was prominently nicked on the bottom strand at the precise point of insertion of EhSINE1, showing that this SINE could use the LINE-encoded endonuclease for its insertion. The nick on the bottom strand was toward the right of the TSD, which is uncommon. The lack of strict target site-specificity of the restriction enzyme-like EN encoded by EhLINE1 is also exceptional. A model for retrotransposition of EhLINE1/SINE1 is presented.

Multivariate Poisson flows on Markov step processes

A Markov step process Z equipped with a possibly non-denumerable state space X can model a variety of queueing, communication and computer networks. The analysis of such networks can be facilitated if certain traffic flows consist of mutually independent Poisson processes with respective deterministic intensities λi (t). Accordingly, we define the multivariate counting process N = (N1, N2, · ·· Nc) induced by Z; a count in Ni occurs whenever Z jumps from x (χ into a (possibly empty) target set . We study N through the infinitesimal operator à of the augmented Markov process W = (Z, N), and the integral relationship connecting à with the transition operator Tt of W. It is then shown that Ni depends on a non-negative function ri defined on χ; ri (x) may be interpreted as the expected rate of increase in Ni, given that Z is in state x.A multivariate N is Poisson (i.e., composed of mutually independent Poisson streams Ni) if and only if simultaneous jumps are impossible in a certain sense, and if the conditional expectation E[ri (Z(t) | 𝒩i] = E[ri (Z(t))] for i = 1, 2, ···, c and each t ≧ 0, where 𝒩i is the σ-algebra σ{N(s), s ≦ t}. Necessary and sufficient conditions are also specified that, for each s ≦ t, the variates [Ni(t)-Ni(s)] are mutually independent Poisson distributed; this involves a weakened version of E[ri(Z(v)) | N(v) – N(u)] = E [ri(Z(v))] for i = 1, 2, ···, c and all 0 ≦ u ≦ v.It is shown that the above criteria are automatically met by the more stringent classical requirement that N(t) and Z(t) be independent for each t ≧ 0.

Multivariate Poisson flows on Markov step processes

A Markov step process Z equipped with a possibly non-denumerable state space X can model a variety of queueing, communication and computer networks. The analysis of such networks can be facilitated if certain traffic flows consist of mutually independent Poisson processes with respective deterministic intensities λ i (t). Accordingly, we define the multivariate counting process N = (N 1, N 2, · ·· N c) induced by Z; a count in Ni occurs whenever Z jumps from x (χ into a (possibly empty) target set . We study N through the infinitesimal operator à of the augmented Markov process W = (Z, N), and the integral relationship connecting à with the transition operator T t of W. It is then shown that Ni depends on a non-negative function ri defined on χ; ri (x) may be interpreted as the expected rate of increase in Ni , given that Z is in state x. A multivariate N is Poisson (i.e., composed of mutually independent Poisson streams N i ) if and only if simultaneous jumps are impossible in a certain sense, and if the conditional expectation E[r i (Z(t) | 𝒩 i ] = E[r i (Z(t))] for i = 1, 2, ···, c and each t ≧ 0, where 𝒩 i is the σ-algebra σ{N(s), s ≦ t}. Necessary and sufficient conditions are also specified that, for each s ≦ t, the variates [N i (t)-N i (s)] are mutually independent Poisson distributed; this involves a weakened version of E[r i (Z(v)) | N(v) – N(u)] = E [r i (Z(v))] for i = 1, 2, ···, c and all 0 ≦ u ≦ v. It is shown that the above criteria are automatically met by the more stringent classical requirement that N(t) and Z(t) be independent for each t ≧ 0.