The process of plant fertilization provides an outstanding example of refined control of gene expression. During this elegant process, subtle communication occurs between neighboring cells, based on chemical signals, that induces cellular mechanisms of patterning and growth. Having faced an immediate issue of self-incompatibility responses, the pathway to fertilization starts once the stigmatic cells recognize a compatible pollen grain, and it continues with numerous players interacting to affect pollen tube growth and the puzzling process of navigation along the transmitting tract. The pollen tube goes through a guidance process that begins with a preovular stage (i.e. prior to the influence of the target ovule), with interactions with factors from the transmitting tissue. In the subsequent ovular-guidance stage a specific relationship develops between the pollen tube and its target ovule. This stage is divided into the funicular and micropylar guidance steps, with numerous receptors working in signalling cascades. Finally, just after the pollen tube has passed beyond the synergids, fusion of the gametes occurs and the developing seed-the ultimate aim of the process-will start to mature. In this paper, we review the existing knowledge of the crucial biological processes involved in pollen-pistil interactions that give rise to the new seed.

DNA–protein interactions are essential for several molecular and cellular mechanisms, such as transcription, transcriptional regulation, DNA modifications, among others. For many decades scientists tried to unravel how DNA links to proteins, forming complex and vital interactions. However, the high number of techniques developed for the study of these interactions made the choice of the appropriate technique a difficult task. This review intends to provide a historical context and compile the methods that describe DNA–protein interactions according to the purpose of each approach, summarise the respective advantages and disadvantages and give some examples of recent uses for each technique. The final aim of this work is to help in deciding which technique to perform according to the objectives and capacities of each research team. Considering the DNA–binding proteins characterisation, filter binding assay and EMSA are easy in vitro methods that rapidly identify nucleic acid-protein binding interactions. To find DNA-binding sites, DNA-footprinting is indeed an easier, faster and reliable approach, however, techniques involving base analogues and base-site selection are more precise. Concerning binding kinetics and affinities, filter binding assay and EMSA are useful and easy methods, although SPR and spectroscopy techniques are more sensitive. Finally, relatively to genome-wide studies, ChIP–seq is the desired method, given the coverage and resolution of the technique. In conclusion, although some experiments are easier and faster than others, when designing a DNA–protein interaction study several concerns should be taken and different techniques may need to be considered, since different methods confer different precisions and accuracies.

Arabinogalactan proteins (AGPs) are hydroxyproline-rich glycoproteins containing a high proportion of carbohydrates, widely distributed in the plant kingdom and ubiquitously present in land plants. AGPs have long been suggested to play important roles in plant reproduction and there is already evidence that specific glycoproteins are essential for male and female gametophyte development, pollen tube growth and guidance, and successful fertilization. However, the functions of many of these proteins have yet to be uncovered, mainly due to the difficulty to study individual AGPs. In this work, we generated molecular tools to analyze the expression patterns of a subgroup of individual AGPs in different Arabidopsis tissues, focusing on reproductive processes. This study focused on six AGPs: four classical AGPs (AGP7, AGP25, AGP26, AGP27), one AG peptide (AGP24) and one chimeric AGP (AGP31). These AGPs were first selected based on their predicted expression patterns along the reproductive tissues from available RNA-seq data. Promoter analysis using β-glucuronidase fusions and qPCR in different Arabidopsis tissues allowed to confirm these predictions. AGP7 was mainly expressed in female reproductive tissues, more precisely in the style, funiculus, and integuments near the micropyle region. AGP25 was found to be expressed in the style, septum and ovules with higher expression in the chalaza and funiculus tissues. AGP26 was present in the ovules and pistil valves. AGP27 was expressed in the transmitting tissue, septum and funiculus during seed development. AGP24 was expressed in pollen grains, in mature embryo sacs, with highest expression at the chalazal pole and in the micropyle. AGP31 was expressed in the mature embryo sac with highest expression at the chalaza and, occasionally, in the micropyle. For all these AGPs a co-expression analysis was performed providing new hints on its possible functions. This work confirmed the detection in Arabidopsis male and female tissues of six AGPs never studied before regarding the reproductive process. These results provide novel evidence on the possible involvement of specific AGPs in plant reproduction, as strong candidates to participate in pollen-pistil interactions in an active way, which is significant for this field of study.

Quantitative real-time polymerase chain reaction (qPCR) is a widely used method to analyse the gene expression pattern in the reproductive tissues along with detecting gene levels in mutant backgrounds. This technique requires stable reference genes to normalise the expression level of target genes. Nonetheless, a considerable number of publications continue to present qPCR results normalised to a single reference gene and, to our knowledge, no comparative evaluation of multiple reference genes has been carried out in specific reproductive tissues of Arabidopsis thaliana. Herein, we assessed the expression stability levels of ten candidate reference genes (UBC9, ACT7, GAPC-2, RCE1, PP2AA3, TUA2, SAC52, YLS8, SAMDC and HIS3.3) in two conditional sets: one across flower development and the other using inflorescences from different genotypes. The stability analysis was performed using the RefFinder tool, which combines four statistical algorithms (geNorm, NormFinder, BestKeeper and the comparative ΔCt method). Our results showed that RCE1, SAC52 and TUA2 had the most stable expression in different flower developmental stages while YLS8, HIS3.3 and ACT7 were the top-ranking reference genes for normalisation in mutant studies. Furthermore, we validated our results by analysing the expression pattern of genes involved in reproduction and examining the expression of these genes in published mutant backgrounds. Overall, we provided a pool of appropriate reference genes for expression studies in reproductive tissues of A. thaliana, which will facilitate further gene expression studies in this context. More importantly, we presented a framework that will promote a consistent and accurate analysis of gene expression in any scientific field. Simultaneously, we highlighted the relevance of clearly defining and describing the experimental conditions associated with qPCR to improve scientific reproducibility.