Analysis of gemini pollen 3 mutant suggests a broad function of AUGMIN in microtubule organization during sexual reproduction in Arabidopsis

In flowering plants, male gametes arise via meiosis of diploid pollen mother cells followed by two rounds of mitotic division. Haploid microspores undergo polar nuclear migration and asymmetric division at pollen mitosis I to segregate the male germline, followed by division of the germ cell to generate a pair of sperm cells. We previously reported two gemini pollen (gem) mutants that produced twin‐celled pollen arising from polarity and cytokinesis defects at pollen mitosis I in Arabidopsis. Here, we report an independent mutant, gem3, with a similar division phenotype and severe genetic transmission defects through pollen. Cytological analyses revealed that gem3 disrupts cell division during male meiosis, at pollen mitosis I and during female gametophyte development. We show that gem3 is a hypomorphic allele (aug6‐1) of AUGMIN subunit 6, encoding a conserved component in the augmin complex, which mediates microtubule (MT)‐dependent MT nucleation in acentrosomal cells. We show that MT arrays are disturbed in gem3/aug6‐1 during male meiosis and pollen mitosis I using fluorescent MT‐markers. Our results demonstrate a broad role for the augmin complex in MT organization during sexual reproduction, and highlight gem3/aug6‐1 mutants as a valuable tool for the investigation of augmin‐dependent MT nucleation and dynamics in plant cells.     

A statistical model of ChIA-PET data for accurate detection of chromatin 3D interactions

Identification of three-dimensional (3D) interactions between regulatory elements across the genome is crucial to unravel the complex regulatory machinery that orchestrates proliferation and differentiation of cells. ChIA-PET is a novel method to identify such interactions, where physical contacts between regions bound by a specific protein are quantified using next-generation sequencing. However, determining the significance of the observed interaction frequencies in such datasets is challenging, and few methods have been proposed. Despite the fact that regions that are close in linear genomic distance have a much higher tendency to interact by chance, no methods to date are capable of taking such dependency into account. Here, we propose a statistical model taking into account the genomic distance relationship, as well as the general propensity of anchors to be involved in contacts overall. Using both real and simulated data, we show that the previously proposed statistical test, based on Fisher''s exact test, leads to invalid results when data are dependent on genomic distance. We also evaluate our method on previously validated cell-line specific and constitutive 3D interactions, and show that relevant interactions are significant, while avoiding over-estimating the significance of short nearby interactions.     

Performance comparison of four exome capture systems for deep sequencing

Background

Recent developments in deep (next-generation) sequencing technologies are significantly impacting medical research. The global analysis of protein coding regions in genomes of interest by whole exome sequencing is a widely used application. Many technologies for exome capture are commercially available; here we compare the performance of four of them: NimbleGen’s SeqCap EZ v3.0, Agilent’s SureSelect v4.0, Illumina’s TruSeq Exome, and Illumina’s Nextera Exome, all applied to the same human tumor DNA sample.

Results

Each capture technology was evaluated for its coverage of different exome databases, target coverage efficiency, GC bias, sensitivity in single nucleotide variant detection, sensitivity in small indel detection, and technical reproducibility. In general, all technologies performed well; however, our data demonstrated small, but consistent differences between the four capture technologies. Illumina technologies cover more bases in coding and untranslated regions. Furthermore, whereas most of the technologies provide reduced coverage in regions with low or high GC content, the Nextera technology tends to bias towards target regions with high GC content.

Conclusions

We show key differences in performance between the four technologies. Our data should help researchers who are planning exome sequencing to select appropriate exome capture technology for their particular application.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-449) contains supplementary material, which is available to authorized users.     

Detection of base mutations in genomic DNA using denaturing gradient gel electrophoresis (DGGE) followed by transfer and hybridization with gene-specific probes

It has been shown that minor differences, such as single-base-pair substitutions between otherwise identical DNA fragments can result in altered melting behavior detectable by denaturing gradient gel electrophoresis (DGGE). Sequence variations in only a small DNA region within one locus can be detected using the previously described procedures. We have developed a method for the efficient Southern transfer of genomic DNA fragments from the denaturing gradient gels in order to be able to analyze larger regions in several loci for variation. The gels were made using polyacrylamide containing 2% low-geling-temperature agarose (LGT). The polyacrylamide gel (PAG) was crosslinked with a reversible crosslinker, and after electrophoresis the crosslinks were cleaved, the structure of the gel being maintained by the agarose. After this treatment of the denaturing gels, more than 90% of the DNA fragments could be transferred to nylon membranes by alkaline transfer, while electroblotting transferred only 10% of the DNA. Hybridization with gene-specific probes was then performed. We have used this technique to identify an RFLP in the COL1A2 gene in a human genomic DNA sample. The transfer technique described should make the use of DGGE more widely applicable since the genomic DNA fragments separated on one gel can be screened with several different probes, both cDNA and genomic probes.     

CellLineMiner: a knowledge portal for human cell lines

Experimental models of human tissues and disease phenotypes frequently rely upon immortalized cell lines, which are easily accessible and simple to use due to their infinite capability of cell division. For decades, cell lines have been used to investigate cellular mechanisms of disease and the efficacy of drugs, most prominently for human cancers. However, the large body of knowledge with respect to human cell lines exists primarily in an unstructured fashion, that is, as free text in the scientific literature. Here we present CellLineMiner, a novel text mining-based web database that provides a comprehensive view of human cell line knowledge. The application offers a simple search in all indexed cell lines, accompanied by a rapid display of all identified literature associations. The CellLineMiner is intended to serve as a knowledge resource companion to the cellular model systems used in biomedical research.

Availability

CellLineMiner is accessible at http://dev.pubgene.com/cellmine