Current Genomics (v.10, #1)
High-Throughput Genomics Enhances Tomato Breeding Efficiency by A. Barone, A. Matteo, D. Carputo, L. Frusciante (1-9).
Tomato (Solanum lycopersicum) is considered a model plant species for a group of economically important crops, such as potato, pepper, eggplant, since it exhibits a reduced genomic size (950 Mb), a short generation time, and routine transformation technologies. Moreover, it shares with the other Solanaceous plants the same haploid chromosome number and a high level of conserved genomic organization. Finally, many genomic and genetic resources are actually available for tomato, and the sequencing of its genome is in progress. These features make tomato an ideal species for theoretical studies and practical applications in the genomics field. The present review describes how structural genomics assist the selection of new varieties resistant to pathogens that cause damage to this crop. Many molecular markers highly linked to resistance genes and cloned resistance genes are available and could be used for a high-throughput screening of multiresistant varieties. Moreover, a new genomics-assisted breeding approach for improving fruit quality is presented and discussed. It relies on the identification of genetic mechanisms controlling the trait of interest through functional genomics tools. Following this approach, polymorphisms in major gene sequences responsible for variability in the expression of the trait under study are then exploited for tracking simultaneously favourable allele combinations in breeding programs using high-throughput genomic technologies. This aims at pyramiding in the genetic background of commercial cultivars alleles that increase their performances. In conclusion, tomato breeding strategies supported by advanced technologies are expected to target increased productivity and lower costs of improved genotypes even for complex traits.
Comparative Analyses of Plant Transcription Factor Databases by Silvia Ramirez, Chhandak Basu (10-17).
Transcription factors (TFs) are proteinaceous complex, which bind to the promoter regions in the DNA and affect transcription initiation. Plant TFs control gene expressions and genes control many physiological processes, which in turn trigger cascades of biochemical reactions in plant cells. The databases available for plant TFs are somewhat abundant but all convey different information and in different formats. Some of the publicly available plant TF databases may be narrow, while others are broad in scopes. For example, some of the best TF databases are ones that are very specific with just one plant species, but there are also other databases that contain a total of up to 20 different plant species. In this review plant TF databases ranging from a single species to many will be assessed and described. The comparative analyses of all the databases and their advantages and disadvantages are also discussed.
The Role of Androgen Receptor Mutations in Prostate Cancer Progression by G. Brooke, C. Bevan (18-25).
Prostate tumour growth is almost always dependent upon the androgen receptor pathway and hence therapies aimed at blocking this signalling axis are useful tools in the management of this disease. Unfortunately such therapies invariably fail; and the tumour progresses to an and#x201C;androgen-independentand#x201D; stage. In such cases androgen receptor expression is almost always maintained and much evidence exists to suggest that it may still be driving growth. One mechanism by which the receptor is thought to remain active is mutation. This review summarises the present data on androgen receptor mutations in prostate cancer, and how such substitutions offer a growth advantage by affecting cofactor interactions or by reducing ligand specificity. Such alterations appear to have a subsequent effect upon gene expression suggesting that tumours may and#x201C;behaveand#x201D; differently dependent upon the ligand promoting growth and if a mutation is present.
Molecular Signature of HPV-Induced Carcinogenesis: pRb, p53 and Gene Expression Profiling by Agueda Buitrago-Perez, Guillermo Garaulet, Ana Vazquez-Carballo, Jesus Paramio, Ramon Garcia-Escudero (26-34).
The infection by mucosal human papillomavirus (HPV) is causally associated with tumor development in cervix and oropharynx. The mechanisms responsible for this oncogenic potential are mainly due to the product activities of two early viral oncogenes: E6 and E7. Although a large number of cellular targets have been described for both oncoproteins, the interaction with tumor suppressors p53 and retinoblastoma protein (pRb) emerged as the key functional activities. E6 degrades tumor suppressor p53, thus inhibiting p53-dependent functions, whereas E7 binds and degrades pRb, allowing the transcription of E2F-dependent genes. Since these two tumor suppressors exert their actions through transcriptional modulation, functional genomics has provided a large body of data that reflects the altered gene expression of HPVinfected cells or tissues. Here we will review the similarities and differences of these findings, and we also compare them with those obtained with transgenic mouse models bearing the deletion of some of the viral oncogene targets. The comparative analysis supports molecular evidences about the role of oncogenes E6 and E7 in the interference with the mentioned cellular functions, and also suggests that the mentioned transgenic mice can be used as models for HPV-associated diseases such as human cervical, oropharynx, and skin carcinomas.
MicroRNA Gene Networks in Oncogenesis by Alexandra Drakaki, Dimitrios Iliopoulos (35-41).
MicroRNAs are small non-coding RNAs that regulate gene expression at the transcriptional or posttranscriptional level. They are involved in cellular development, differentiation, proliferation and apoptosis and play a significant role in cancer. Examination of tumor-specific microRNA expression profiles has revealed widespread deregulation of these molecules in diverse cancers. Several studies have shown that microRNAs function either as tumor suppressor genes or oncogenes, whose loss or overexpression respectively has diagnostic and prognostic significance. It seems that microRNAs act as major regulators of gene expression. In this review, we discuss microRNAs' role in cancer and how microRNAs exert their functions through regulation of their gene targets. Bioinformatic analysis of putative miRNA binding sites has indicated several novel potential gene targets involved in apoptosis, angiogenesis and metastatic mechanisms. Matching computational prediction analysis together with microarray data seems the best method for microRNA gene target identification. MicroRNAs together with transcription factors generate a complex combinatorial code regulating gene expression. Thus, manipulation of microRNA-transcription factor gene networks may be provides a novel approach for developing cancer therapies.
MDM4 (MDMX) and its Transcript Variants by F. Mancini, G. Conza, F. Moretti (42-50).
MDM family proteins are crucial regulators of the oncosuppressor p53. Alterations of their gene status, mainly amplification events, have been frequently observed in human tumors. MDM4 is one of the two members of the MDM family. The human gene is located on chromosome 1 at q32-33 and codes for a protein of 490aa. In analogy to MDM2, besides the full-length mRNA several transcript variants of MDM4 have been identified. Almost all variants thus far described derive from a splicing process, both through canonical and aberrant splicing events. Some of these variants are expressed in normal tissues, others have been observed only in tumor samples. The presence of these variants may be considered a fine tuning of the function of the full-length protein, especially in normal cells. In tumor cells, some variants show oncogenic properties. This review summarizes all the different MDM4 splicing forms thus far described and their role in the regulation of the wild type protein function in normal and tumor cells. In addition, a description of the full-length protein structure with all known interacting proteins thus far identified and a comparison of the MDM4 variant structure with that of full-length protein are presented. Finally, a parallel between MDM4 and MDM2 variants is discussed.
Molecular Pathophysiology of Renal Tubular Acidosis by P. Pereira, D. Miranda, E. Oliveira, A. Simoes e Silva (51-59).
Renal tubular acidosis (RTA) is characterized by metabolic acidosis due to renal impaired acid excretion. Hyperchloremic acidosis with normal anion gap and normal or minimally affected glomerular filtration rate defines this disorder. RTA can also present with hypokalemia, medullary nephrocalcinosis and nephrolitiasis, as well as growth retardation and rickets in children, or short stature and osteomalacia in adults. In the past decade, remarkable progress has been made in our understanding of the molecular pathogenesis of RTA and the fundamental molecular physiology of renal tubular transport processes. This review summarizes hereditary diseases caused by mutations in genes encoding transporter or channel proteins operating along the renal tubule. Review of the molecular basis of hereditary tubulopathies reveals various loss-of-function or gain-of-function mutations in genes encoding cotransporter, exchanger, or channel proteins, which are located in the luminal, basolateral, or endosomal membranes of the tubular cell or in paracellular tight junctions. These gene mutations result in a variety of functional defects in transporter/channel proteins, including decreased activity, impaired gating, defective trafficking, impaired endocytosis and degradation, or defective assembly of channel subunits. Further molecular studies of inherited tubular transport disorders may shed more light on the molecular pathophysiology of these diseases and may significantly improve our understanding of the mechanisms underlying renal salt homeostasis, urinary mineral excretion, and blood pressure regulation in health and disease. The identification of the molecular defects in inherited tubulopathies may provide a basis for future design of targeted therapeutic interventions and, possibly, strategies for gene therapy of these complex disorders.
Using Free and Open-Source Bioconductor Packages to Analyze Array Comparative Genomics Hybridization (aCGH) Data by Simon Lin, Pan Du, Nadereh Jafari, Toru Ouchi (60-63).
Whole-genome array Comparative Genomics Hybridization (aCGH) can be used to scan chromosomes for deletions and amplifications. Because of the increased accessibility of many commercial platforms, a lot of cancer researchers have used aCGH to study tumorigenesis or to predict clinical outcomes. Each data set is typically in several hundred thousands to one million rows of hybridization measurements. Thus, statistical analysis is a key to unlock the knowledge obtained from an aCGH study. We review several free and open-source packages in Bioconductor and provide example codes to run the analysis. The analysis of aCGH data provides insights of genomic abnormalities of cancers.
Gene Clusters, Molecular Evolution and Disease: A Speculation by Leah Elizondo, Paymaan Jafar-Nejad, J. Clewing, Cornelius Boerkoel (64-75).
Traditionally eukaryotic genes are considered independently expressed under the control of their promoters and cis-regulatory domains. However, recent studies in worms, flies, mice and humans have shown that genes co-habiting a chromatin domain or and#x201C;genomic neighborhoodand#x201D; are frequently co-expressed. Often these co-expressed genes neither constitute part of an operon nor function within the same biological pathway. The mechanisms underlying the partitioning of the genome into transcriptional genomic neighborhoods are poorly defined. However, cross-species analyses find that the linkage among the co-expressed genes of these clusters is significantly conserved and that the expression patterns of genes within clusters have coevolved with the clusters. Such selection could be mediated by chromatin interactions with the nuclear matrix and long-range remodeling of chromatin structure. In the context of human disease, we propose that dysregulation of gene expression across genomic neighborhoods will cause highly pleiotropic diseases. Candidate genomic neighborhood diseases include the nuclear laminopathies, chromosomal translocations and genomic instability disorders, imprinting disorders of errant insulator function, syndromes from impaired cohesin complex assembly, as well as diseases of global covalent histone modifications and DNA methylation. The alteration of transcriptional genomic neighborhoods provides an exciting and novel model for studying epigenetic alterations as quantitative traits in complex common human diseases.