Use of polyethyleneimine polymer in cell culture as attachment factor and lipofection enhancer

Background  

Several cell lines and primary cultures benefit from the use of positively charged extracellular matrix proteins or polymers that enhance their ability to attach to culture plates. Polyethyleneimine is a positively charged polymer that has gained recent attention as a transfection reagent. A less known use of this cationic polymer as an attachment factor was explored with several cell lines.     

Relationship of aerobic and anaerobic parameters with 400 m front crawl swimming performance

The aims of the present study were to investigate the relationship of aerobic and anaerobic parameters with 400 m performance, and establish which variable better explains long distance performance in swimming. Twenty-two swimmers (19.1±1.5 years, height 173.9±10.0 cm, body mass 71.2±10.2 kg; 76.6±5.3% of 400 m world record) underwent a lactate minimum test to determine lactate minimum speed (LMS) (i.e., aerobic capacity index). Moreover, the swimmers performed a 400 m maximal effort to determine mean speed (S400m), peak oxygen uptake (V.O2PEAK) and total anaerobic contribution (C_ANA). The C_ANA was assumed as the sum of alactic and lactic contributions. Physiological parameters of 400 m were determined using the backward extrapolation technique (V.O2PEAK and alactic contributions of C_ANA) and blood lactate concentration analysis (lactic anaerobic contributions of C_ANA). The Pearson correlation test and backward multiple regression analysis were used to verify the possible correlations between the physiological indices (predictor factors) and S400m (independent variable) (p < 0.05). Values are presented as mean ± standard deviation. Significant correlations were observed between S400m (1.4±0.1 m·s^-1) and LMS (1.3±0.1 m·s^-1; r = 0.80), V.O2PEAK (4.5±3.9 L·min^-1; r = 0.72) and C_ANA (4.7±1.5 L·O₂; r= 0.44). The best model constructed using multiple regression analysis demonstrated that LMS and V.O2PEAK explained 85% of the 400 m performance variance. When backward multiple regression analysis was performed, C_ANA lost significance. Thus, the results demonstrated that both aerobic parameters (capacity and power) can be used to predict 400 m swimming performance.     

Pheno2Geno - High-throughput generation of genetic markers and maps from molecular phenotypes for crosses between inbred strains

Background

Genetic markers and maps are instrumental in quantitative trait locus (QTL) mapping in segregating populations. The resolution of QTL localization depends on the number of informative recombinations in the population and how well they are tagged by markers. Larger populations and denser marker maps are better for detecting and locating QTLs. Marker maps that are initially too sparse can be saturated or derived de novo from high-throughput omics data, (e.g. gene expression, protein or metabolite abundance). If these molecular phenotypes are affected by genetic variation due to a major QTL they will show a clear multimodal distribution. Using this information, phenotypes can be converted into genetic markers.

Results

The Pheno2Geno tool uses mixture modeling to select phenotypes and transform them into genetic markers suitable for construction and/or saturation of a genetic map. Pheno2Geno excludes candidate genetic markers that show evidence for multiple possibly epistatically interacting QTL and/or interaction with the environment, in order to provide a set of robust markers for follow-up QTL mapping.We demonstrate the use of Pheno2Geno on gene expression data of 370,000 probes in 148 A. thaliana recombinant inbred lines. Pheno2Geno is able to saturate the existing genetic map, decreasing the average distance between markers from 7.1 cM to 0.89 cM, close to the theoretical limit of 0.68 cM (with 148 individuals we expect a recombination every 100/148=0.68 cM); this pinpointed almost all of the informative recombinations in the population.

Conclusion

The Pheno2Geno package makes use of genome-wide molecular profiling and provides a tool for high-throughput de novo map construction and saturation of existing genetic maps. Processing of the showcase dataset takes less than 30 minutes on an average desktop PC. Pheno2Geno improves QTL mapping results at no additional laboratory cost and with minimum computational effort. Its results are formatted for direct use in R/qtl, the leading R package for QTL studies. Pheno2Geno is freely available on CRAN under “GNU GPL v3”. The Pheno2Geno package as well as the tutorial can also be found at: http://pheno2geno.nl.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0475-6) contains supplementary material, which is available to authorized users.     

Assessment of the effect of age at onset on linkage to bipolar disorder: evidence on chromosomes 18p and 21q

Previous evidence suggests that the inheritance of bipolar disorder (BP) may vary depending on the age at onset (AAO). Therefore, we sought to incorporate AAO as a covariate in linkage analyses of BP using two different methods, LODPAL and ordered-subset analysis (OSA), in genomewide scans of 150 multiplex pedigrees with 874 individuals. The LODPAL analysis identified two loci, on chromosomes 21q22.13 (LOD = 3.29; empirical chromosomewide P value = .009) and 18p11.2 (LOD = 2.83; empirical chromosomewide P = .05), with increased linkage among subjects who had early onset (AAO < or = 21 years) and later onset (AAO >21 years), respectively. The finding on 21q22.13 was significant at the chromosomewide level, even after correction for multiple testing. Moreover, a similar finding was observed in an independent sample of 65 pedigrees (LOD = 2.88; empirical chromosomewide P = .025). The finding on 18p11.2 was only nominally significant and was not observed in the independent sample. However, 18p11.2 emerged as one of the strongest regions in the OSA (LOD = 2.92; empirical P = .001), in which it was the only finding to meet chromosomewide levels of significance after correction for multiple testing. These results suggest that 21q22.13 and 18p11.2 may harbor genes that increase the risks for early-onset and later-onset forms of BP, respectively. There have been previous reports of linkage on 21q22.13 and 18p11.2, but the findings have not been consistent. This inconsistency may be due to differences in the AAO characteristics of the samples examined. Future studies to fine map susceptibility genes for BP on chromosomes 21q22.13 and 18p11.2 should take AAO into account.     

An AFLP-based genetic linkage map of Plasmodium chabaudi chabaudi

Background

Plasmodium chabaudi chabaudi can be considered as a rodent model of human malaria parasites in the genetic analysis of important characters such as drug resistance and immunity. Despite the availability of some genome sequence data, an extensive genetic linkage map is needed for mapping the genes involved in certain traits.

Methods

The inheritance of 672 Amplified Fragment Length Polymorphism (AFLP) markers from two parental clones (AS and AJ) of P. c. chabaudi was determined in 28 independent recombinant progeny clones. These, AFLP markers and 42 previously mapped Restriction Fragment Length Polymorphism (RFLP) markers (used as chromosomal anchors) were organized into linkage groups using Map Manager software.

Results

614 AFLP markers formed linkage groups assigned to 10 of 14 chromosomes, and 12 other linkage groups not assigned to known chromosomes. The genetic length of the genome was estimated to be about 1676 centiMorgans (cM). The mean map unit size was estimated to be 13.7 kb/cM. This was slightly less then previous estimates for the human malaria parasite, Plasmodium falciparum

Conclusion

The P. c. chabaudi genetic linkage map presented here is the most extensive and highly resolved so far available for this species. It can be used in conjunction with the genome databases of P. c chabaudi, P. falciparum and Plasmodium yoelii to identify genes underlying important phenotypes such as drug resistance and strain-specific immunity.     

Stress protein of cyanobacteria CP36: interaction with photoactive complexes and formation of supramolecular structures

Cyanobacterium Anacystis nidulans R2, Synechocystis sp. PCC 6803 (wild-type strain and mutants Delta2 and Delta3 lacking PSII and PSI, respectively), and Synechocystis sp. BO 9201 synthesize the pigment--protein complex CP36 (CPIV-4, CP43') under iron deficiency in the medium. Accumulation of CP36 is accompanied by structural reorganizations in the photosynthetic membranes. Integrating mean times of excitation relaxation (quenching) are 2.2 nsec (CP36), 1 nsec (PSI), and 420 psec (PSII in Fm state). The energy migration between CP36 and the photosystems can be described by a model of a one-layer ring of CP36 around core-complexes. The excitation from CP36 to PSI is transferred within <10 psec. The energy transfer from CP36 to PSII occurs during 170 psec. Cells with low content of CP36 probably contain only a latent fraction of unbound to phycobilisomes PSII which is the analog of PSIIbeta of higher plants. In PSI there are four binding sites for CP36 monomers per RC. PSII can bind up to 32 molecules of CP36 per RC. Cells with a large amount of CP36 contain monomer form of PSII core-complex which can bind eight tetramers of CP36 (8 binding sites). In conditions of iron deficiency only one monomer of a dimer PSII core-complex is destroyed and released chlorophyll is accumulated in CP36. Accumulation of CP36 in A. nidulans cells can be accompanied by membrane stacking which is similar to the stacking in chlorophyll b-containing organisms. The stacking can occur in the region of localization of PSII latent fraction bound to CP36. The membrane stacking shields PSII stromal surfaces from the aqueous phase for activation of electron transfer on the acceptor side of PSII.     

Phylogenetic relationships within the Alcidae (Charadriiformes: Aves) inferred from total molecular evidence

The Alcidae is a unique assemblage of Northern Hemisphere seabirds that forage by "flying" underwater. Despite obvious affinities among the species, their evolutionary relationships are unclear. We analyzed nucleotide sequences of 1,045 base pairs of the mitochondrial cytochrome b gene and allelic profiles for 37 allozyme loci in all 22 extant species. Trees were constructed on independent and combined data sets using maximum parsimony and distance methods that correct for superimposed changes. Alternative methods of analysis produced only minor differences in relationships that were supported strongly by bootstrapping or standard error tests. Combining sequence and allozyme data into a single analysis provided the greatest number of relationships receiving strong support. Addition of published morphological and ecological data did not improve support for any additional relationship. All analyses grouped species into six distinct lineages: (1) the dovekie (Alle alle) and auks, (2) guillemots, (3) brachyramphine murrelets, (4) synthliboramphine murrelets, (5) true auklets, and (6) the rhinoceros auklet (Cerorhinca monocerata) and puffins. The two murres (genus Uria) were sister taxa, and the black guillemot (Cepphus grylle) was basal to the other guillemots. The Asian subspecies of the marbled murrelet (Brachyramphus marmoratus perdix) was the most divergent brachyramphine murrelet, and two distinct lineages occurred within the synthliboramphine murrelets. Cassin's auklet (Ptychoramphus aleuticus) and the rhinoceros auklet were basal to the other auklets and puffins, respectively, and the Atlantic (Fratercula arctica) and horned (Fratercula corniculata) puffins were sister taxa. Several relationships among tribes, among the dovekie and auks, and among the auklets could not be resolved but resembled "star" phylogenies indicative of adaptive radiations at different depths within the trees.      

Genome scan meta-analysis of schizophrenia and bipolar disorder,part III: Bipolar disorder

Genome scans of bipolar disorder (BPD) have not produced consistent evidence for linkage. The rank-based genome scan meta-analysis (GSMA) method was applied to 18 BPD genome scan data sets in an effort to identify regions with significant support for linkage in the combined data. The two primary analyses considered available linkage data for “very narrow” (i.e., BP-I and schizoaffective disorder–BP) and “narrow” (i.e., adding BP-II disorder) disease models, with the ranks weighted for sample size. A “broad” model (i.e., adding recurrent major depression) and unweighted analyses were also performed. No region achieved genomewide statistical significance by several simulation-based criteria. The most significant P values (<.01) were observed on chromosomes 9p22.3-21.1 (very narrow), 10q11.21-22.1 (very narrow), and 14q24.1-32.12 (narrow). Nominally significant P values were observed in adjacent bins on chromosomes 9p and 18p-q, across all three disease models on chromosomes 14q and 18p-q, and across two models on chromosome 8q. Relatively few BPD pedigrees have been studied under narrow disease models relative to the schizophrenia GSMA data set, which produced more significant results. There was no overlap of the highest-ranked regions for the two disorders. The present results for the very narrow model are promising but suggest that more and larger data sets are needed. Alternatively, linkage might be detected in certain populations or subsets of pedigrees. The narrow and broad data sets had considerable power, according to simulation studies, but did not produce more highly significant evidence for linkage. We note that meta-analysis can sometimes provide support for linkage but cannot disprove linkage in any candidate region.     

Replication study supports evidence for linkage to 9p24 in obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) is a severe psychiatric illness that is characterized by intrusive and senseless thoughts and impulses (obsessions) and by repetitive behaviors (compulsions). Family, twin, and segregation studies support the presence of both genetic and environmental susceptibility factors, and the only published genome scan for OCD identified a candidate region on 9p24 at marker D9S288 that met criteria for suggestive significance (Hanna et al. 2002). In an attempt to replicate this finding, we genotyped 50 pedigrees with OCD, using microsatellite markers spanning the 9p24 candidate region, and analyzed the data, using parametric and nonparametric linkage analyses under both a narrow phenotype model (DSM-IV OCD definite; 41 affected sib pairs) and a broad phenotype model (DSM-IV OCD definite and probable; 50 affected sib pairs). Similar to what was described by Hanna et al. (2002), our strongest findings came with the dominant parameters and the narrow phenotype model: the parametric signal peaked at marker D9S1792 with an HLOD of 2.26 ( alpha =0.59), and the nonparametric linkage signal (NPL) peaked at marker D9S1813 with an NPL of 2.52 (P=.006). These findings are striking in that D9S1813 and D9S1792 lie within 0.5 cM (<350 kb) of the original 9p24 linkage signal at D9S288; furthermore, pedigree-based association analyses also implicated the 9p24 candidate region by identifying two markers (D9S288 and GATA62F03) with modest evidence (P=.046 and .02, respectively) for association.