Establishment of neomycin phosphotransferase II (<Emphasis Type="Italic">nptII</Emphasis>) selection for transformation of soybean somatic embryogenic cultures

Soybean transformation is limited by the lack of multiple efficient selectable marker systems. Biolistic transformation of somatic proliferative embryogenic cultures, one of the commonly used soybean transformation methods, relies largely on hygromycin phosphotransferase II (hptII) selection. The purpose of the present study was to establish another efficient selectable marker system to facilitate multiple gene transformations of soybean. We tested neomycin phosphotransferase II (nptII) that has been used successfully in cotyledonary node transformation, but with limited success in transformation of embryogenic cultures. Transgenic events were obtained using nptII with improved G418 selection without generating escapes. G418 selection required longer recovery and selection periods, and resulted in a lower efficiency of initial transformants compared to hygromycin selection. Six independent fertile transgenic plants were recovered using nptII and G418, a frequency similar to that obtained with hygromycin selection. Soybean embryogenic cultures co-transformed with the hptII and nptII markers showed resistance to both hygromycin B and G418, while regeneration and plant fertility were not adversely affected. The nptII will be useful as a second selectable marker for multiple gene transformations in basic and applied soybean research.     

Enhancing the frequency of somatic embryogenesis following <Emphasis Type="Italic">Agrobacterium</Emphasis>-mediated transformation of immature cotyledons of soybean [<Emphasis Type="Italic">Glycine max</Emphasis> (L.) Merrill.]

Summary A characteristic phenotype of highly embryogenic explants along with the location of embryogenesis- and transformation-competent cells/tissues on immature cotyledons of soybean [Glycine max (L.) Merrill.] under hygromycin selection was identified. This highly embryogenic immature cotyledon was characterized with emergence of somatic embryos and incidence of browning/necrotic tissues along the margins and collapsed tissues in the mid-region of an explant incubated upwards on the selection medium. The influences of various parameters on induction of somatic embryogenesis on immature cotyledons following Agrobacterium tumefaciens-mediated transformation and selection were investigated. Using cotyledon explants derived from immature embryos of 5–8 mm in length, a 1∶1 (v/v; bacterial cells to liquid D40 medium) concentration of bacterial suspension and 4-wk cocultivation period significantly increased the frequency of transgenic somatic embryos. Whereas, increasing the infection period of explants or subjecting explants to either wounding or acetosyringone treatments did not increase the frequency of transformation. An optimal selection regime was identified when inoculated immature cotyledons were incubated on either 10 or 25 mgl⁻¹ hygromycin for a 2-wk period, and then maintained on selection media containing 25 mgl⁻¹ hygromycin in subsequent selection periods. However, somatic embryogenesis was completely inhibited when inoculated immature cotyledons were incubated on a kanamycin selection medium. These findings clearly demonstrated that the tissue culture protocols for transformation of soybean should be established under both Agrobacterium and selection conditions.     

Tissue culture specificity of the tobacco ASA2 promoter driving hpt as a selectable marker for soybean transformation selection

This study was carried out to determine if the tobacco anthranilate synthase ASA2 2.3 kb promoter drives tissue culture specific expression and if it is strong enough to drive hpt (hygromycin phosphotransferase) gene expression at a level sufficient to allow selection of transformed soybean embryogenic culture lines. A number of transformed cell lines were selected showing that the promoter was strong enough. Northern blot analysis of plant tissues did not detect hpt mRNA in the untransformed control or in the ASA2-hpt plants except in developing seeds while hpt mRNA was detected in all tissues of the CaMV35S-hpt positive control line plants. However, when the more sensitive RT-PCR assay was used all tissues of the ASA2-hpt plants except roots and mature seeds were found to contain detectable hpt mRNA. Embryogenic tissue cultures initiated from the ASA2-hpt plants contained hpt mRNA detectable by both northern and RT-PCR analysis and the cultures were hygromycin resistant. Friable callus initiated from leaves of ASA2-hpt plants did in some cases contain hpt mRNA that was only barely detectable by northern hybridization even though the callus was very hygromycin resistant. Thus the ASA2 promoter is strong enough to drive sufficient hpt expression in soybean embryogenic cultures for hygromycin selection and only very low levels of expression were found in most plant tissues with none in mature seeds.     

Genomic consequences of selection and genome-wide association mapping in soybean

Background

Crop improvement always involves selection of specific alleles at genes controlling traits of agronomic importance, likely resulting in detectable signatures of selection within the genome of modern soybean (Glycine max L. Merr.). The identification of these signatures of selection is meaningful from the perspective of evolutionary biology and for uncovering the genetic architecture of agronomic traits.

Results

To this end, two populations of soybean, consisting of 342 landraces and 1062 improved lines, were genotyped with the SoySNP50K Illumina BeadChip containing 52,041 single nucleotide polymorphisms (SNPs), and systematically phenotyped for 9 agronomic traits. A cross-population composite likelihood ratio (XP-CLR) method was used to screen the signals of selective sweeps. A total of 125 candidate selection regions were identified, many of which harbored genes potentially involved in crop improvement. To further investigate whether these candidate regions were in fact enriched for genes affected by selection, genome-wide association studies (GWAS) were conducted on 7 selection traits targeted in soybean breeding (grain yield, plant height, lodging, maturity date, seed coat color, seed protein and oil content) and 2 non-selection traits (pubescence and flower color). Major genomic regions associated with selection traits overlapped with candidate selection regions, whereas no overlap of this kind occurred for the non-selection traits, suggesting that the selection sweeps identified are associated with traits of agronomic importance. Multiple novel loci and refined map locations of known loci related to these traits were also identified.

Conclusions

These findings illustrate that comparative genomic analyses, especially when combined with GWAS, are a promising approach to dissect the genetic architecture of complex traits.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1872-y) contains supplementary material, which is available to authorized users.     

FiGS: a filter-based gene selection workbench for microarray data

Background  

The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene selection methods are currently available and some of them have shown excellent performance, no single method can retain the best performance for all types of microarray datasets. It is desirable to use a comparative approach to find the best gene selection result after rigorous test of different methodological strategies for a given microarray dataset.     

Variation in DNA methylation patterns of grapevine somaclones (<Emphasis Type="Italic">Vitis vinifera L</Emphasis>.)

Background  

In traditional vine areas, the production should present a typicity that partly depends on the grapevine variety. Therefore, vine improvement is considered difficult because of the limited choice in the natural variability of the cultivars within the limits of their characteristics. A possibility to circumvent this problem is the use of somatic variability. In vitro somatic embryogenesis and organogenesis can lead to genotypic and phenotypic variations, described as somaclonal variation, that could be useful for the selection of improved grapevine genotypes.     

Parallel shifts in ecology and natural selection in an island lizard

Background  

Natural selection is a potent evolutionary force that shapes phenotypic variation to match ecological conditions. However, we know little about the year-to-year consistency of selection, or how inter-annual variation in ecology shapes adaptive landscapes and ultimately adaptive radiations. Here we combine remote sensing data, field experiments, and a four-year study of natural selection to show that changes in vegetation structure associated with a severe drought altered both habitat use and natural selection in the brown anole, Anolis sagrei.     

SNP identification and marker assay development for high-throughput selection of soybean cyst nematode resistance

Background

Soybean cyst nematode (SCN) is the most economically devastating pathogen of soybean. Two resistance loci, Rhg1 and Rhg4 primarily contribute resistance to SCN race 3 in soybean. Peking and PI 88788 are the two major sources of SCN resistance with Peking requiring both Rhg1 and Rhg4 alleles and PI 88788 only the Rhg1 allele. Although simple sequence repeat (SSR) markers have been reported for both loci, they are linked markers and limited to be applied in breeding programs due to accuracy, throughput and cost of detection methods. The objectives of this study were to develop robust functional marker assays for high-throughput selection of SCN resistance and to differentiate the sources of resistance.

Results

Based on the genomic DNA sequences of 27 soybean lines with known SCN phenotypes, we have developed Kompetitive Allele Specific PCR (KASP) assays for two Single nucleotide polymorphisms (SNPs) from Glyma08g11490 for the selection of the Rhg4 resistance allele. Moreover, the genomic DNA of Glyma18g02590 at the Rhg1 locus from 11 soybean lines and cDNA of Forrest, Essex, Williams 82 and PI 88788 were fully sequenced. Pairwise sequence alignment revealed seven SNPs/insertion/deletions (InDels), five in the 6th exon and two in the last exon. Using the same 27 soybean lines, we identified one SNP that can be used to select the Rhg1 resistance allele and another SNP that can be employed to differentiate Peking and PI 88788-type resistance. These SNP markers have been validated and a strong correlation was observed between the SNP genotypes and reactions to SCN race 3 using a panel of 153 soybean lines, as well as a bi-parental population, F₅–derived recombinant inbred lines (RILs) from G00-3213 x LG04-6000.

Conclusions

Three functional SNP markers (two for Rhg1 locus and one for Rhg4 locus) were identified that could provide genotype information for the selection of SCN resistance and differentiate Peking from PI 88788 source for most germplasm lines. The robust KASP SNP marker assays were developed. In most contexts, use of one or two of these markers is sufficient for high-throughput marker-assisted selection of plants that will exhibit SCN resistance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1531-3) contains supplementary material, which is available to authorized users.     

Feature selection and nearest centroid classification for protein mass spectrometry

Background  

The use of mass spectrometry as a proteomics tool is poised to revolutionize early disease diagnosis and biomarker identification. Unfortunately, before standard supervised classification algorithms can be employed, the "curse of dimensionality" needs to be solved. Due to the sheer amount of information contained within the mass spectra, most standard machine learning techniques cannot be directly applied. Instead, feature selection techniques are used to first reduce the dimensionality of the input space and thus enable the subsequent use of classification algorithms. This paper examines feature selection techniques for proteomic mass spectrometry.     

Green fluorescent protein as a visual selection marker for coffee transformation

The green fluorescent protein (GFP) was used as a visual selectable marker to produce transgenic coffee (Coffea canephora) plants following Agrobacterium-mediated transformation. The binary vector pBECKS 2000.7 containing synthetic gene for GFP (sgfp) S65T and the hygromycin phosphotransferase gene hph both controlled by 35S cauliflower mosaic virus CaMV35S promoters was used for transformation. Embryogenic cultures were initiated from hypocotyls and cotyledon leaves of in vitro grown seedlings and used as target material. Selection of transformed tissue was carried out using GFP visual selection as the sole screen or in combination with a low level of antibiotics (hygromycin 10 mg/L), and the efficiency was compared with antibiotics selection alone (hygromycin 30 mg/L). GFP selection reduced the time for transformed somatic embryos formation from 18 weeks on a hygromycin (30 mg/L) antibiotics containing medium to 8 weeks. Moreover, visual selection of GFP combined with low level of antibiotics selection improved the transformation efficiency and increased the number of transformed coffee plants compared to selection in the presence of antibiotics. Molecular analysis confirmed the presence of the sgfp-S65T coding region in the regenerated plants. Visual screening of transformed cells using GFP by Agrobacterium-mediated transformation techniques was found to be efficient and therefore has the potential for development of selectable marker-free transgenic coffee plants.     

Rabies virus glycoprotein expression in Drosophila S2 cells. I: Design of expression/selection vectors, subpopulations selection and influence of sodium butyrate and culture medium on protein expression

The cDNA encoding the rabies virus glycoprotein (RVGP) gene was cloned in expression plasmids under the control of the inductive metallothionein promoter. They were designed in order to bear or not a secretion signal (i) and a cDNA coding for the selection hygromycin. These vectors were transfected into S2 cells, cell populations selected and subpopulations were then obtained by reselection with hygromycin. Cell cultures were examined for kinetics of cell growth, detection of RVGP mRNA and expression of RVGP. All cell populations were shown to express the RVGP mRNA upon induction. S2MtRVGPHy cell population, transfected with one vector that contains RGPV gene and selection gene, was shown to express higher amounts of RVGP as evaluated by flow cytometry (52%) and ELISA (0.64 μg/10⁷ cells at day 7). Subpopulation selection allowed a higher RVGP expression, specially for the S2MtRVGPHy⁺ (5.5 μg/10⁷ cells at day 7). NaBu treatment leading to lower cell growth and higher RVGP expression allowed an even higher RVGP synthesis by S2MtRVGPHy⁺ (8.4 μg/10⁷ cells at day 7). SF900II medium leading to a higher S2MtRVGPHy⁺cell growth allowed a higher final RVGP synthesis in this cell culture. RVGP synthesis may be optimized by the expression/selection vectors design, cell subpopulations selection, chromatin exposure and culture medium employed.     

Sexual selection on cuticular hydrocarbons in the Australian field cricket, Teleogryllus oceanicus

Background  

Females in a wide range of taxa have been shown to base their choice of mates on pheromone signals. However, little research has focussed specifically on the form and intensity of selection that mate choice imposes on the pheromone signal. Using multivariate selection analysis, we characterise directly the form and intensity of sexual selection acting on cuticular hydrocarbons, chemical compounds widely used in the selection of mates in insects. Using the Australian field cricket Teleogryllus oceanicus as a model organism, we use three measures of male attractiveness to estimate fitness; mating success, the duration of courtship required to elicit copulation, and subsequent spermatophore attachment duration.     

Vacuum infiltration enhances the Agrobacterium-mediated genetic transformation in Indian soybean cultivars

For the first time we have developed a reliable and efficient vacuum infiltration-assisted Agrobacterium-mediated genetic transformation (VIAAT) protocol for Indian soybean cultivars and recovered fertile transgenic soybean plants through somatic embryogenesis. Immature cotyledons were used as an explant and three Agrobacterium tumefaciens strains (EHA 101, EHA 105, and KYRT 1) harbouring the binary vector pCAMBIA1301 were experimented in the co-cultivation. The immature cotyledons were pre-cultured in liquid somatic embryo induction medium prior to vacuum infiltration with the Agrobacterium suspension and co-cultivated for 3 days on co-cultivation medium containing 50 mg l^?1 citric acid, 100 µM acetosyringone, and 100 mg l^?1 l-cysteine. The transformed somatic embryos were selected in liquid somatic embryo induction medium containing 10 mg l^?1 hygromycin and the embryos were germinated in basal medium containing 20 mg l^?1 hygromycin. The presence and integration of the hpt II and gus genes into the soybean genome were confirmed by GUS histochemical assay, polymerase chain reaction, and Southern hybridization. Among the different combinations tested, high transformation efficiency (9.45 %) was achieved when immature cotyledons of cv. Pusa 16 were pre-cultured for 18 h and vacuum infiltrated with Agrobacterium tumefaciens KYRT 1 for 2 min at 750 mm of Hg. Among six Indian soybean cultivars tested, Pusa 16 showed highest transformation efficiency of 9.45 %. The transformation efficiency of this method (VIAAT) was higher than previously reported sonication-assisted Agrobacterium-mediated transformation. These results suggest that an efficient Agrobacterium-mediated transformation protocol for stable integration of foreign genes into soybean has been developed.     

GeneSrF and varSelRF: a web-based tool and R package for gene selection and classification using random forest

Background  

Microarray data are often used for patient classification and gene selection. An appropriate tool for end users and biomedical researchers should combine user friendliness with statistical rigor, including carefully avoiding selection biases and allowing analysis of multiple solutions, together with access to additional functional information of selected genes. Methodologically, such a tool would be of greater use if it incorporates state-of-the-art computational approaches and makes source code available.     

Gene selection and classification of microarray data using random forest

Background  

Selection of relevant genes for sample classification is a common task in most gene expression studies, where researchers try to identify the smallest possible set of genes that can still achieve good predictive performance (for instance, for future use with diagnostic purposes in clinical practice). Many gene selection approaches use univariate (gene-by-gene) rankings of gene relevance and arbitrary thresholds to select the number of genes, can only be applied to two-class problems, and use gene selection ranking criteria unrelated to the classification algorithm. In contrast, random forest is a classification algorithm well suited for microarray data: it shows excellent performance even when most predictive variables are noise, can be used when the number of variables is much larger than the number of observations and in problems involving more than two classes, and returns measures of variable importance. Thus, it is important to understand the performance of random forest with microarray data and its possible use for gene selection.     

Evolutionary algorithms for the selection of single nucleotide polymorphisms

Background  

Large databases of single nucleotide polymorphisms (SNPs) are available for use in genomics studies. Typically, investigators must choose a subset of SNPs from these databases to employ in their studies. The choice of subset is influenced by many factors, including estimated or known reliability of the SNP, biochemical factors, intellectual property, cost, and effectiveness of the subset for mapping genes or identifying disease loci. We present an evolutionary algorithm for multiobjective SNP selection.     

Gene selection with multiple ordering criteria

Background  

A microarray study may select different differentially expressed gene sets because of different selection criteria. For example, the fold-change and p-value are two commonly known criteria to select differentially expressed genes under two experimental conditions. These two selection criteria often result in incompatible selected gene sets. Also, in a two-factor, say, treatment by time experiment, the investigator may be interested in one gene list that responds to both treatment and time effects.     

The effect of co-cultivation and selection parameters on <Emphasis Type="Italic">Agrobacterium</Emphasis>-mediated transformation of Chinese soybean varieties

In the present study, an efficient Agrobacterium-mediated gene transformation system was developed for soybean [Glycine max (L.) Merrill] based on the examinations of several factors affecting plant transformation efficiency. Increased transformation efficiencies were obtained when the soybean cotyledonary node were inoculated with the Agrobacterium inoculum added with 0.02% (v/v) surfactant (Silwet L-77). The applications of Silwet L-77 (0.02%) during infection and l-cysteine (600 mg l⁻¹) during co-cultivation resulted in more significantly improved transformation efficiency than each of the two factors alone. The optimized temperature for infected explant co-cultivation was 22°C. Regenerated transgenic shoots were selected and produced more efficiently with the modified selection scheme (initiation on shoot induction medium without hygromycin for 7 days, with 3 mg l⁻¹ hygromycin for 10 days, 5 mg l⁻¹ hygromycin for another 10 days, and elongation on shoot elongation medium with 8 mg l⁻¹ hygromycin). Using the optimized system, we obtained 145 morphologically normal and fertile independent transgenic plants in five important Chinese soybean varieties. The transformation efficacies ranged from 3.8 to 11.7%. Stable integration, expression and inheritance of the transgenes were confirmed by molecular and genetic analysis. T₁ plants were analyzed and transmission of transgenes to the T₁ generation in a Mendelian fashion was verified. This optimized transformation system should be employed for efficient Agrobacterium-mediated soybean gene transformation.     

A stable gene selection in microarray data analysis

Background  

Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most significantly differentially expressed genes under different conditions, and it has been a central research focus. In general, a better gene selection method can improve the performance of classification significantly. One of the difficulties in gene selection is that the numbers of samples under different conditions vary a lot.     

Alternating evolutionary pressure in a genetic algorithm facilitates protein model selection

Background  

Automatic protein modelling pipelines are becoming ever more accurate; this has come hand in hand with an increasingly complicated interplay between all components involved. Nevertheless, there are still potential improvements to be made in template selection, refinement and protein model selection.