Project description:To improve our understanding of the organization and regulation of the wheat gene space, we established the first transcription map of a wheat chromosome (3B) by hybridizing the newly developed INRA GDEC Triticum aestivum NimbleGen 12x40k unigenes microarray with BAC pools from a new version of the 3B physical map as well as with cDNA probes from five tissues at three developmental stages each. By hybridizing the BAC pools with the wheat NimbleGen 40K unigenes chip we managed to map almost 3000 unigenes on the wheat chromosome 3B BACs and to study the organization of the wheat gene space along chromosome 3B. The sequences of the unigenes helped to perform functional and evolutionary analyses of these unigenes. By hybridizing the 15 cDNA samples from five organs at three developmental stages each we established the expression profiles of more than 32000 wheat unigenes. Particularly we focused on the expression of the unigenes mapped on wheat chromosome 3B to perform coexpression analyses.
Project description:Background Because of its size, allohexaploid nature and high repeat content, the wheat genome has always been perceived as too complex for efficient molecular studies. However, we recently constructed the first physical map of a wheat chromosome (3B). But gene mapping is still laborious in wheat because of high redundancy between the three homoeologous genomes. In contrast, in the closely related diploid species, barley, numerous gene-based markers have been developed. This study aims at combining the unique genomic resources developed in wheat and barley to decipher the organisation of gene space on wheat chromosome 3B. Results Three dimensional pools of the minimal tiling path of wheat chromosome 3B physical map were hybridized to a barley Agilent 15K expression microarray. This led to the identification of 738 barley genes with a homolog on wheat chromosome 3B. In addition, comparative analyses revealed that 68% of the genes identified were syntenic between the wheat chromosome 3B and barley chromosome 3H and 59% between wheat chromosome 3B and rice chromosome 1, together with some wheat-specific rearrangements. Finally, it indicated an increasing gradient of gene density from the centromere to the telomeres positively correlated with the number of genes clustered in islands on wheat chromosome 3B. Conclusion Our study shows that novel structural genomics resources now available in wheat and barley can be combined efficiently to overcome specific problems of genetic anchoring of physical contigs in wheat and to perform high-resolution comparative analyses with rice for deciphering the organisation of the wheat gene space.
Project description:A core task to understand the consequences of non-coding single nucleotide polymorphisms (SNP) is to identify their genotype specific binding of transcription factor (TF). Here, we generate a large-scale TF-SNP interaction map for a selection of 116 colorectal cancer (CRC) risk loci and validated TF binding to 10 putatively functional SNPs. Our data further revealed TF binding complexity adjacent to the 116 risk loci, adding an additional layer of understanding to regulatory networks associated with CRC relevant loci.
Project description:A core task to understand the consequences of non-coding single nucleotide polymorphisms (SNP) is to identify their genotype specific binding of transcription factor (TF). Here, we generate a large-scale TF-SNP interaction map for a selection of 116 colorectal cancer (CRC) risk loci and validated TF binding to 10 putatively functional SNPs. Our data further revealed TF binding complexity adjacent to the 116 risk loci, adding an additional layer of understanding to regulatory networks associated with CRC relevant loci.
Project description:To improve our understanding of the organization and evolution of the wheat gene space, we established the first map of genes of the wheat chromosome 1BL by hybridizing the newly developed INRA GDEC Triticum aestivum NimbleGen 12x40k unigenes microarray (A-MEXP-2314) with BAC pools from the 1BL physical map as well as with genomic DNA of the sorted chromosome 1BL. By hybridizing the BAC pools with the wheat NimbleGen 40K unigenes chip we managed to map almost 1615 unigenes on the wheat chromosome 1BL BACs. By hybridizing the genomic DNA of the 1BL sorted chromosome and by comparison with 454 sequences from the sorted chromosome 1BL, we confirmed the assignation of 1223 unigenes in individual BACs from the chromosome 1BL. This data allowed us to study the organization of the wheat gene space along chromosome 1BL. The sequences of the unigenes helped to perform synteny and evolutionary analyses of these unigenes.
Project description:To improve our understanding of the organization and evolution of the wheat gene space, we established the first map of genes of the wheat chromosome 1BS by hybridizing the newly developed INRA GDEC Triticum aestivum NimbleGen 12x40k unigenes microarray (A-MEXP-2314) with 3D-pools of MTP BACs of from the 1BS physical map. By hybridizing the BAC pools with the wheat NimbleGen 40K unigenes chip we managed to map almost 1063 unigenes on the wheat chromosome 1BS BACs. By comparison with 454 sequences and Illumina survey sequence contigs from the sorted chromosome 1BS, we confirmed the assignation of 849 unigenes in individual BACs from the chromosome 1BS. This data allowed us to study the organization of the wheat gene space along chromosome 1BS. The sequences of the unigenes helped to perform synteny and evolutionary analyses of these unigenes. DNA from MTP clones were pooled into 3D manner: library of MTP clones was stored in 17 plates of 384 wells (24 columns x 16 rows); plate1 pool consist of mixture of DNA from all MTP clones situated in plate 1, Row A pool consist of mixture of DNA from all MTP clones situated in Rows A (from all 17 plates, etc). The set of positive plate, column and row pools for the unigene (represented in microarray) allow to detect the list of putative positive clones (clones from the intersection of positive pools, cleaned using information on physical intersection clones based on clone fingerprints). Hence, all 57 experiments (17 for plate pools, 24 for column pools, and 16 for row pools) have the same experimental factor.
Project description:To improve the resources for map-based cloning and sequencing of the wheat genome, we established a physical map of the wheat chromosome 1BL with a high density of markers by hybridizing the newly developed INRA GDEC Triticum aestivum NimbleGen 12x17k ISBP microarray (A-MEXP-2312) with BAC pools from the 1BL physical map. Then, we managed to map 3912 ISBP on the wheat chromosome 1BL BACs. The values in the 'Factor Value[individual]' column represent the BAC pool that have been hybridized on the array. For example, the assay 1 correspond to the hybridization of a bulk of all DNA BAC of the plate 1 of the MTP (Minimum Tilling path) BAC library of the chromosome 1BL.
Project description:These SNP arrays were used to genotype hESCs and their corresponding matenal sample. Expression analysis of some of the SNPs located on the X chromosome was used to identify the pattern of X Chromosome inactivation in these human embryonic stem cells
Project description:Proteomic genotyping is the use of genetically variant peptides (GVPs), detected in a forensic protein sample, to infer the genotype of corresponding non-synonymous SNP alleles in the donor’s genome. This process does not depend on the presence of accessible or useable DNA in a sample. This makes proteomic genotyping an attractive alternative for analysis of problematic forensic samples, such as hair shafts, degraded bones or teeth, fingermarks, or sexual assault evidence. To demonstrate the concept in hair shafts, we developed an optimized sample processing protocol that could be used with high effectiveness on single hairs. This allows us to determine if the detected profiles of genetically variant peptides are robust and result in a consistent profile of inferred SNP alleles regardless of the chemical or biological history of the sample. Several real world scenarios have been evaluated. Here we include a study of four European subjects that had both pigmented and non-pigmented (or gray and non-gray) hair shafts. We tested whether (a) protein profiles change as a result of the loss of pigmentation and (b) these changes were reflected in the inferred genotype derived from detection of genetically variant peptides. Using this information, we can determine whether the resulting GVP profiles are more dependent on the biological context of pigmentation status or the underlying genotype.