DNA secondary structures are associated with recombination in major Plasmodium falciparum variable surface antigen gene families

Many bacterial, viral and parasitic pathogens undergo antigenic variation to counter host immune defense mechanisms. In Plasmodium falciparum, the most lethal of human malaria parasites, switching of var gene expression results in alternating expression of the adhesion proteins of the Plasmodium falciparum-erythrocyte membrane protein 1 class on the infected erythrocyte surface. Recombination clearly generates var diversity, but the nature and control of the genetic exchanges involved remain unclear. By experimental and bioinformatic identification of recombination events and genome-wide recombination hotspots in var genes, we show that during the parasite’s sexual stages, ectopic recombination between isogenous var paralogs occurs near low folding free energy DNA 50-mers and that these sequences are heavily concentrated at the boundaries of regions encoding individual Plasmodium falciparum-erythrocyte membrane protein 1 structural domains. The recombinogenic potential of these 50-mers is not parasite-specific because these sequences also induce recombination when transferred to the yeast Saccharomyces cerevisiae. Genetic cross data suggest that DNA secondary structures (DSS) act as inducers of recombination during DNA replication in P. falciparum sexual stages, and that these DSS-regulated genetic exchanges generate functional and diverse P. falciparum adhesion antigens. DSS-induced recombination may represent a common mechanism for optimizing the evolvability of virulence gene families in pathogens

Runs of homozygosity in killer whale genomes provide a global record of demographic histories

Runs of homozygosity (ROH) occur when offspring inherit haplotypes that are identical by descent from each parent. Length distributions of ROH are informative about population history; specifically, the probability of inbreeding mediated by mating system and/or population demography. Here, we investigated whether variation in killer whale (Orcinus orca) demographic history is reflected in genome-wide heterozygosity and ROH length distributions, using a global data set of 26 genomes representative of geographic and ecotypic variation in this species, and two F1 admixed individuals with Pacific-Atlantic parentage. We first reconstructed demographic history for each population as changes in effective population size through time using the pairwise sequential Markovian coalescent (PSMC) method. We found a subset of populations declined in effective population size during the Late Pleistocene, while others had more stable demography. Genomes inferred to have undergone ancestral declines in effective population size, were autozygous at hundreds of short ROH (1.5 Mb) were found in low latitude populations, and populations of known conservation concern. These include a Scottish killer whale, for which 37.8% of the autosomes were comprised of ROH >1.5 Mb in length. The fate of this population, in which only two adult males have been sighted in the past five years, and zero fecundity over the last two decades, may be inextricably linked to its demographic history and consequential inbreeding depression

A synthetic system for expression of components of a bacterial microcompartment

In general, prokaryotes are considered to be single-celled organisms that lack internal membrane-bound organelles. However, many bacteria produce proteinaceous microcompartments that serve a similar purpose, i.e. to concentrate specific enzymic reactions together or to shield the wider cytoplasm from toxic metabolic intermediates. In this paper, a synthetic operon encoding the key structural components of a microcompartment was designed based on the genes for the Salmonella propanediol utilization (Pdu) microcompartment. The genes chosen included pduA, -B, -J, -K, -N, -T and -U, and each was shown to produce protein in an Escherichia coli chassis. In parallel, a set of compatible vectors designed to express non-native cargo proteins was also designed and tested. Engineered hexa-His tags allowed isolation of the components of the microcompartments together with co-expressed, untagged, cargo proteins. Finally, an in vivo protease accessibility assay suggested that a PduD-GFP fusion could be protected from proteolysis when co-expressed with the synthetic microcompartment operon. This work gives encouragement that it may be possible to harness the genes encoding a non-native microcompartment for future biotechnological applications

Taxonomic distribution of non-maize HiSeq 2000 reads from cDNA and DNA sets:

<p>(<b>a</b>) represents cDNA sample 935130, (<b>b</b>) represents cDNA sample 935230, and (<b>c</b>) represents a DNA shotgun sample from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050961#pone.0050961-Bannister1" target="_blank">[25]</a> 100,00 randomly sampled unmapped reads were used to perform BLAST searches and MEGAN was for taxonomic characterization of non-maize reference genome (non-B73) reads.</p

Histogram showing fragment length distribution of maize GS FLX sequence reads from 3 Arizonan DNA (FLX4-6) samples (blue) in comparison to 3 Arizonan cDNA (FLX1-3) samples (red).

<p>Histogram showing fragment length distribution of maize GS FLX sequence reads from 3 Arizonan DNA (FLX4-6) samples (blue) in comparison to 3 Arizonan cDNA (FLX1-3) samples (red).</p

Top 50 exon hits with functional annotation from cDNA (935130 and 935230) HiSeq 2000 maize reads (for a detailed version of the table see Supplementary Table S4).

<p>Top 50 exon hits with functional annotation from cDNA (935130 and 935230) HiSeq 2000 maize reads (for a detailed version of the table see Supplementary <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050961#pone.0050961.s010" target="_blank">Table S4</a>).</p

Kernel and sample information and names.

<p>A total of 6 kernels were utilized for either RNA or DNA extraction only, or co-extracted for DNA and RNA. After nucleic acids were co-extracted, samples were divided into 2 aliquots, and RNA samples were DNase treated and DNA samples were RNase treated (see Methods and Supplementary Methods S1), and labeled with unique sample names.</p