A Method for Checking Genomic Integrity in Cultured Cell Lines from SNP Genotyping Data

<div><p>Genomic screening for chromosomal abnormalities is an important part of quality control when establishing and maintaining stem cell lines. We present a new method for sensitive detection of copy number alterations, aneuploidy, and contamination in cell lines using genome-wide SNP genotyping data. In contrast to other methods designed for identifying copy number variations in a single sample or in a sample composed of a mixture of normal and tumor cells, this new method is tailored for determining differences between cell lines and the starting material from which they were derived, which allows us to distinguish between normal and novel copy number variation. We implemented the method in the freely available BCFtools package and present results based on induced pluripotent stem cell lines obtained in the HipSci project.</p></div

Error rate by length in simulated data.

<p>Error rate by length in simulated data.</p

Input data for the polysomy method.

<p>Unscaled (A) and scaled (B-D) distributions of BAF values typical for the copy number states 2-4. In (C) we infer that 33% of the cells are aneuploid copy number 3, and in (D) we infer a sample with 20% contamination. The black line is the complete BAF distribution over 0 to 1 of which only part is modelled (shown in red); the green line is the best fit to the red part of the distribution. The model does not include the RR peak and including the AA peak is optional.</p

Reproducibility of polysomy results across different chips.

<p>Fraction of contaminating cells in the sample (red circles) and the fraction of cells with trisomies (green triangles) as estimated from the default (0.5M sites) and higher density chip (2.5M sites). All outliers in this figure are unconfirmed contaminations and chromosomes failing goodness of fit criteria as explained in the text.</p

The correlation of BAF and LRR values obtained in the validation experiment using the default chip (0.5M sites) and the high density chip (2.5M sites) on sample HPSI0713i-virz_2_QC1Hip.

<p>The central plot shows LRR correlation across the whole genome. The right hand plot shows LRR correlation across chromosome 17 which contains a large 40Mb duplication. The plots are 2-D histograms with hexagonal bins, logarithmic greyscale was used to indicate the number of markers in a bin.</p

Distribution of phosphosites with respect to secondary structure elements

<p><b>Copyright information:</b></p><p>Taken from "A systematic comparative and structural analysis of protein phosphorylation sites based on the mtcPTM database"</p><p>http://genomebiology.com/2007/8/5/R90</p><p>Genome Biology 2007;8(5):R90-R90.</p><p>Published online 23 May 2007</p><p>PMCID:PMC1929158.</p><p></p> The plots represent the frequency of occurrences of phosphorylated serine/threonine and tyrosine residues in the elements of secondary structure of the models as defined by Dictionary of Protein Secondary Structure (DSSP) [43]. The three sets shown as well as their color coding are identical to those from Figure 5

Buried residues whose phosphorylation state could affect local structural conformation

<p><b>Copyright information:</b></p><p>Taken from "A systematic comparative and structural analysis of protein phosphorylation sites based on the mtcPTM database"</p><p>http://genomebiology.com/2007/8/5/R90</p><p>Genome Biology 2007;8(5):R90-R90.</p><p>Published online 23 May 2007</p><p>PMCID:PMC1929158.</p><p></p> The figure shows several examples of buried residues whose phosphorylation may result in conformational rearrangements, including detachment of secondary structure elements from the protein domain. Unless stated otherwise, all the structures are shown differentially colored from their amino- (cold colors) to their carboxyl-termini (hot colors), with the regions whose conformation is predicted to be affected in gray, and the phosphosites in white space-filled representation. Structure of the human 7508A NBD1 domain [60] (Protein Data Bank [PDB]: 1xmi). Structure of the autoinhibited p47[62] (PDB: 1ng2). Structure of annexin-1 [64] (PDB: 1hm6). Other residues, namely T24, S27 and S28, that can also be phosphorylated, although they are not buried, are shown in gray. The region encircled is likely to be affected by phosphorylation of the enclosed amino acids, as described in the main text. Structure of the regulator of G-protein signaling 16 (unpublished data; PDB: 2bt2). Structure of the serine/threonine protein phosphatase PP1-β catalytic subunit [67] (PDB: 1s70). A PEG molecule is shown in red and the 130 kDa myosin-binding subunit of smooth muscle myosin phosphatase in white. Structure of DJ-1, a protein related to male fertility and Parkinson's disease [69] (PDB: 1ps4). Structure of the 60S ribosomal protein L7-A [70] (PDB: 1s1i). Structure of the elongation factor EEF1A [87] (PDB: 1f60), in which their individual domains are shown in blue (elongation factor Tu GTP-binding domain), cyan (elongation factor Tu domain 2), and green (elongation factor Tu carboxyl-terminal domain). The catalytic carboxyl-terminal domain of EEF1BA is shown in yellow. A list with additional details of the examples, including links to mtcPTM entries, can be found in Additional data file 2

A Genome-Wide Survey of Genetic Variation in Gorillas Using Reduced Representation Sequencing

<div><p>All non-human great apes are endangered in the wild, and it is therefore important to gain an understanding of their demography and genetic diversity. Whole genome assembly projects have provided an invaluable foundation for understanding genetics in all four genera, but to date genetic studies of multiple individuals within great ape species have largely been confined to mitochondrial DNA and a small number of other loci. Here, we present a genome-wide survey of genetic variation in gorillas using a reduced representation sequencing approach, focusing on the two lowland subspecies. We identify 3,006,670 polymorphic sites in 14 individuals: 12 western lowland gorillas (<i>Gorilla gorilla gorilla</i>) and 2 eastern lowland gorillas (<i>Gorilla beringei graueri</i>). We find that the two species are genetically distinct, based on levels of heterozygosity and patterns of allele sharing. Focusing on the western lowland population, we observe evidence for population substructure, and a deficit of rare genetic variants suggesting a recent episode of population contraction. In western lowland gorillas, there is an elevation of variation towards telomeres and centromeres on the chromosomal scale. On a finer scale, we find substantial variation in genetic diversity, including a marked reduction close to the major histocompatibility locus, perhaps indicative of recent strong selection there. These findings suggest that despite their maintaining an overall level of genetic diversity equal to or greater than that of humans, population decline, perhaps associated with disease, has been a significant factor in recent and long-term pressures on wild gorilla populations.</p></div

Using BWT structures for reference-free querying of the 1000 Genomes sequence data

<p>Using BWT structures for reference-free querying of<br>the 1000 Genomes sequence data</p> <p> </p

Principal components analysis (PCA).

<p>A. PCA based on 123,591 polymorphic sites in 12 western lowland gorillas and two eastern lowland gorillas. Here, PC1 separates western gorillas from eastern gorillas. B. PCA based on 110,971 polymorphic sites in the 12 western lowland gorillas only.</p