Single molecule analysis of combinatorial splicing

Alternative splicing creates diverse mRNA isoforms from single genes and thereby enhances complexity of transcript structure and of gene function. We describe a method called spliceotyping, which translates combinatorial mRNA splicing patterns along transcripts into a library of binary strings of nucleic acid tags that encode the exon composition of individual mRNA molecules. The exon inclusion pattern of each analyzed transcript is thus represented as binary data, and the abundance of different splice variants is registered by counts of individual molecules. The technique is illustrated in a model experiment by analyzing the splicing patterns of the adenovirus early 1A gene and the beta actin reference transcript. The method permits many genes to be analyzed in parallel and it will be valuable for elucidating the complex effects of combinatorial splicing

Hot Nano-particles in Polar or Paramagnetic Liquids Interact as Monopoles.

When neutral nano-particles are heated or cooled in a polar liquid, they will interact with each other as if they carry an electrostatic charge that is proportional to the temperature difference between the particle and the surrounding fluid. The same should hold for suspensions liquids of asymmetric ferromagnetic particles, in which case the heated nano-particles should behave as magnetic monopoles. However, the analogy with electrostatics/magnetostatics is not complete: heated/cooled nano-particles do not move under the influence of an applied homogeneous field. They should, however, interact as monopoles with each other and should move in inhomogeneous fields.This is the author accepted manuscript. The final version is available from the American Chemical Society via https://doi.org/10.1021/acs.jpcb.6b0184

Post-zygotic Genetic Variation in Health and Disease

Post-zygotic genetic variation has previously been shown in healthy individuals and linked to various disorders. The definition of post-zygotic or somatic variation is the existence of genetically distinct populations of cells in a subject derived from a single zygote. Structural changes in the human genome are a major type of inter-individual genetic variation and copy number variation (CNV), involving changes in the copy number of genes, are one of the best studied category of structural genetic changes. In paper I we reported a pair of healthy female monozygotic (MZ) twins discordant for aneuploidy of chromosomes X and Y, contributing to the delineation of the frequency of somatic variation in MZ twins. It also illustrates the plasticity of the genome for tolerating large aberrations in healthy subjects. In paper II we showed age-related accumulation of copy number variation in the nuclear genomes in vivo for both megabase- and kilobase-range variants. Using age-stratified MZ twins and single-born subjects, we detected megabase-range aberrations in 3.4% of people ≥60 years old but not in individuals younger than 55 years. Moreover, the longitudinal analysis of subjects with aberrations suggests that the aberrant cell clones are not immortalized and disappear from circulation. We also showed that sorted blood cells display different genomic profiles.  The detected recurrent rearrangements are candidates for common age-related defects in blood cells. This work might help to describe the cause of an age-related decline in the number of cell clones in the blood, which is one of the hallmarks of immunosenescence. In paper III we described a variable number tandem repeat (VNTR) ~4 kb upstream of the IFNAR1 gene, which was somatically variable.  We detected 14 alleles displaying inter- and intra-individual variation. Further analyses indicated strong clustering of transcription factor binding sites within this region, suggesting an enhancer. This putative VNTR-based enhancer might influence the transcriptional regulation of neighboring cytokine receptor genes and the pathways they are involved in. These three studies stress the importance of research on post-zygotic variation in genetics. Furthermore, they emphasize that biobanks should consider sampling of multiple tissues to better address this issue in the genetic studies

Posttranscriptional down-regulation of small ribosomal subunit proteinscorrelates with reduction of 18S rRNA in RPS19 deficiency

Ribosomal protein S19 (RPS19) is mutated in patients with Diamond-Blackfan anemia (DBA). We hypothesized that decreased levels of RPS19 lead to a coordinated down-regulation of other ribosomal (r-)proteins at the subunit level. We show that small interfering RNA (siRNA) knock-down of RPS19 results in a relative decrease of small subunit (SSU) r-proteins (S20, S21 and S24) when compared to large subunit (LSU) r-proteins (L3, L9, L30 and L38). This correlates with a relative decrease in 18S rRNA with respect to 28S rRNA. The r-protein mRNA levels remain relatively unchanged indicating a post transcriptional regulation of r-proteins at the level of subunit formation

Graphical summary of variation in a presumptive regulatory VNTR containing region.

<p>Panel <b>A</b> shows an overview of approximately 2 Mb locus on 21q, around four genes encoding functionally related receptors; <i>IFNAR2</i>, <i>IL10Rβ</i>, <i>IFNAR1</i> and <i>IFNGR2</i>. Panel <b>B</b> is zooming on the position of the hypervariable region (HVR, red box), which is located approximately 4 kb upstream from the transcription start site of the <i>IFNAR1</i> gene and is flanked by CpG-islands (green boxes). The last three and the first three exons of <i>IL10Rβ</i>, and <i>IFNAR1</i>, respectively, are shown as grey boxes. Panel <b>C</b> is showing the size and position of HVR according to the most common allele (HVR1098, see below panel D) in relation to the CpG island. Positions of PCR and sequencing primers used in the analysis of the locus are also displayed. Yellow boxes indicate the position of the non-repetitive anchor 1 (A1) and anchor 2 (A2) sequences, that are immediately flanking the repeated segments and were used for alignments of sequence reads. Panel <b>D</b> shows a summary of eight HVR-alleles from the studied samples, which were identified based on Sanger sequencing results of PCR fragments sub-cloned in plasmids. The displayed alleles are ordered from longest to shortest according to size from anchor 1 (A1) to anchor 2 (A2) sequences. Summary of sizes for all 14 different HVR-alleles is shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067752#pone-0067752-t001" target="_blank">Table 1</a>. Sizes of fragments (in base pairs) are given between non-repetitive A1 and A2 sequences and between primers p1 and p8, which were used for PCR amplification from genomic DNA. Asterisk (*) indicates the most frequent allele (HVR1098), which is in agreement with the reference sequence according to NCBI sequence build 36.3. The allele frequency shown here is taking into account only the nine alleles, where the entire sequence could be unequivocally determined using Sanger sequencing. The most common variation encompasses the variable number of 32 base pair segments; i.e. indel 2, indel 3, indel 4, and indel 5. The latter indel 5 is composed of 6 repeated 32 base pair segments (HVR1066). However, there are also indels containing shorther segments; e.g. indel 1, indel 6 and indel 7. Panel <b>E</b> illustrates the positions of two of the four probes from Illumina beadchips, which are aligned onto the NCBI reference sequence for this locus (top sequence with an asterisk, representing HVR1098). The two probes shown here are from Illumina 610 SNP array; cnvi0010761 (green) and cnvi0010759 (blue). All four Illumina probes from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067752#pone-0067752-g001" target="_blank">Figure 1</a>, which were used for initial identification of variation in this region are located within hypervariable region. As shown here for two of these four probes, the probeA sequences (as called by Illumina and used for capturing of genomic DNA on beadchips) are shifted only by two bases. The core 32 bp repeat motif is shown in brackets.</p

Size and distribution of 14 HVR-alleles identified by sequencing and gel electrophoresis.

<p>The •/× indicate that the size of the allele was determined by both agarose gel images and sequencing, whereas filled circles (•) denote that the allele size was estimated from agarose gel images.</p><p>The two most common alleles (HVR1098 and HVR1700) are highlighted in bold and underlined text.</p><p>The sample indicated by a single asterisk (*) are from breast cancer patients. BL, PT and UM indicate peripheral blood DNA, primary breast tumor and healthy morphologically normal breast tissue from a patient affected with breast cancer, respectively.</p><p>The samples indicated by two asterisks (**) are monozygotic twin pairs.</p

Summary of validation of somatic variation in the <i>IFNAR1</i> locus.

<p>Summary of Illumina SNP genotyping, which suggested structural variation within the hypevariable region and results from subsequent confirmation using Sanger sequencing and agarose gel electrophoresis. One (*) and two (**) asterisks after the subject ID indicate patients with breast cancer and pairs of monozygotic twins, respectively. BL, UM and PT stand for DNA from peripheral blood cells, healthy morphologically normal breast tissue from a patient affected with breast cancer and primary breast tumor, respectively. “Seq” indicate that the somatic mosaicism was verified by Sanger sequencing while “Gel” shows that it was confirmed by estimation of allele sizes from agarose gel.</p

Variable length of alleles within hypervariable region showing post-zygotic variation.

<p>Panel <b>A</b> shows post-zygotic mosaicism in healthy and phenotypically concordant monozygotic twin pair 148341/148342, with five alleles observed in twin 148341, and three alleles present in co-twin 148342. Similarly, panel <b>B</b> displays post-zygotic variation in another monozygotic twin pair 004_01/004_02. In total 5 different alleles are shown on this gel and only one of them is overlapping between both twins. Panel <b>C</b> illustrates post-zygotic mosaicism in breast cancer patient SK58. There are three different alleles in DNA from morphologically normal breast tissue (UM), two alleles in blood cells (BL) and three alleles in primary tumor (PT). In panels <b>A</b>, <b>B</b> and <b>C</b>, Taq DNA polymerase was used for initial PCR amplification from genomic DNA, as indicated by suffix “T” in the ID of each plasmid clone. In panel <b>D</b>, Phusion DNA polymerase confirmed post-zygotic mosaicism in monozygotic twin pair 148341/148342, as indicated by suffix “Ph” in the ID of each plasmid clone. The length of inserts in all plasmid clones was estimated after EcoRI digestion releasing the insert, and using 1% agarose gel. BL, PT and UM indicate peripheral blood DNA, primary breast tumor and healthy morphologically normal breast tissue from a patient affected with breast cancer, respectively.</p

The frequency distribution of the 14 alleles identified for the hypervariable region.

<p>The white bars represent alleles defined by both agarose gels and Sanger sequencing. The grey bars denote alleles that were characterized by estimation of their sizes from agarose gels. All alleles were defined based on the analysis between primers 1 and 8 (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067752#pone-0067752-g002" target="_blank">Fig. 2</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067752#pone-0067752-t001" target="_blank">Table 1</a>).</p