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Publications (6)8.05 Total impact

  • Article: Exploring the diploid wheat ancestral A genome through sequence comparison at the high-molecular-weight glutenin locus region.
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    ABSTRACT: The polyploid nature of hexaploid wheat (T. aestivum, AABBDD) often represents a great challenge in various aspects of research including genetic mapping, map-based cloning of important genes, and sequencing and accurately assembly of its genome. To explore the utility of ancestral diploid species of polyploid wheat, sequence variation of T. urartu (A(u)A(u)) was analyzed by comparing its 277-kb large genomic region carrying the important Glu-1 locus with the homologous regions from the A genomes of the diploid T. monococcum (A(m)A(m)), tetraploid T. turgidum (AABB), and hexaploid T. aestivum (AABBDD). Our results revealed that in addition to a high degree of the gene collinearity, nested retroelement structures were also considerably conserved among the A(u) genome and the A genomes in polyploid wheats, suggesting that the majority of the repetitive sequences in the A genomes of polyploid wheats originated from the diploid A(u) genome. The difference in the compared region between A(u) and A is mainly caused by four differential TE insertion and two deletion events between these genomes. The estimated divergence time of A genomes calculated on nucleotide substitution rate in both shared TEs and collinear genes further supports the closer evolutionary relationship of A to A(u) than to A(m). The structure conservation in the repetitive regions promoted us to develop repeat junction markers based on the A(u) sequence for mapping the A genome in hexaploid wheat. Eighty percent of these repeat junction markers were successfully mapped to the corresponding region in hexaploid wheat, suggesting that T. urartu could serve as a useful resource for developing molecular markers for genetic and breeding studies in hexaploid wheat.
    MGG Molecular & General Genetics 09/2012; · 2.58 Impact Factor
  • Article: Annotation-based genome-wide SNP discovery in the large and complex Aegilops tauschii genome using next-generation sequencing without a reference genome sequence
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    ABSTRACT: Abstract Background Many plants have large and complex genomes with an abundance of repeated sequences. Many plants are also polyploid. Both of these attributes typify the genome architecture in the tribe Triticeae, whose members include economically important wheat, rye and barley. Large genome sizes, an abundance of repeated sequences, and polyploidy present challenges to genome-wide SNP discovery using next-generation sequencing (NGS) of total genomic DNA by making alignment and clustering of short reads generated by the NGS platforms difficult, particularly in the absence of a reference genome sequence. Results An annotation-based, genome-wide SNP discovery pipeline is reported using NGS data for large and complex genomes without a reference genome sequence. Roche 454 shotgun reads with low genome coverage of one genotype are annotated in order to distinguish single-copy sequences and repeat junctions from repetitive sequences and sequences shared by paralogous genes. Multiple genome equivalents of shotgun reads of another genotype generated with SOLiD or Solexa are then mapped to the annotated Roche 454 reads to identify putative SNPs. A pipeline program package, AGSNP, was developed and used for genome-wide SNP discovery in Aegilops tauschii-the diploid source of the wheat D genome, and with a genome size of 4.02 Gb, of which 90% is repetitive sequences. Genomic DNA of Ae. tauschii accession AL8/78 was sequenced with the Roche 454 NGS platform. Genomic DNA and cDNA of Ae. tauschii accession AS75 was sequenced primarily with SOLiD, although some Solexa and Roche 454 genomic sequences were also generated. A total of 195,631 putative SNPs were discovered in gene sequences, 155,580 putative SNPs were discovered in uncharacterized single-copy regions, and another 145,907 putative SNPs were discovered in repeat junctions. These SNPs were dispersed across the entire Ae. tauschii genome. To assess the false positive SNP discovery rate, DNA containing putative SNPs was amplified by PCR from AL8/78 and AS75 and resequenced with the ABI 3730 xl. In a sample of 302 randomly selected putative SNPs, 84.0% in gene regions, 88.0% in repeat junctions, and 81.3% in uncharacterized regions were validated. Conclusion An annotation-based genome-wide SNP discovery pipeline for NGS platforms was developed. The pipeline is suitable for SNP discovery in genomic libraries of complex genomes and does not require a reference genome sequence. The pipeline is applicable to all current NGS platforms, provided that at least one such platform generates relatively long reads. The pipeline package, AGSNP, and the discovered 497,118 Ae. tauschii SNPs can be accessed at (http://avena.pw.usda.gov/wheatD/agsnp.shtml).
    BMC Genomics. 01/2011;
  • Article: Physical mapping of a large plant genome using global high-information-content-fingerprinting: the distal region of the wheat ancestor Aegilops tauschii chromosome 3DS
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    ABSTRACT: Abstract Background Physical maps employing libraries of bacterial artificial chromosome (BAC) clones are essential for comparative genomics and sequencing of large and repetitive genomes such as those of the hexaploid bread wheat. The diploid ancestor of the D-genome of hexaploid wheat ( Triticum aestivum ), Aegilops tauschii , is used as a resource for wheat genomics. The barley diploid genome also provides a good model for the Triticeae and T. aestivum since it is only slightly larger than the ancestor wheat D genome. Gene co-linearity between the grasses can be exploited by extrapolating from rice and Brachypodium distachyon to Ae. tauschii or barley, and then to wheat. Results We report the use of Ae. tauschii for the construction of the physical map of a large distal region of chromosome arm 3DS. A physical map of 25.4 Mb was constructed by anchoring BAC clones of Ae. tauschii with 85 EST on the Ae. tauschii and barley genetic maps. The 24 contigs were aligned to the rice and B. distachyon genomic sequences and a high density SNP genetic map of barley. As expected, the mapped region is highly collinear to the orthologous chromosome 1 in rice, chromosome 2 in B. distachyon and chromosome 3H in barley. However, the chromosome scale of the comparative maps presented provides new insights into grass genome organization. The disruptions of the Ae. tauschii -rice and Ae. tauschii - Brachypodium syntenies were identical. We observed chromosomal rearrangements between Ae. tauschii and barley. The comparison of Ae. tauschii physical and genetic maps showed that the recombination rate across the region dropped from 2.19 cM/Mb in the distal region to 0.09 cM/Mb in the proximal region. The size of the gaps between contigs was evaluated by comparing the recombination rate along the map with the local recombination rates calculated on single contigs. Conclusions The physical map reported here is the first physical map using fingerprinting of a complete Triticeae genome. This study demonstrates that global fingerprinting of the large plant genomes is a viable strategy for generating physical maps. Physical maps allow the description of the co-linearity between wheat and grass genomes and provide a powerful tool for positional cloning of new genes.
    BMC Genomics. 01/2010;
  • Article: A new implementation of high-throughput five-dimensional clone pooling strategy for BAC library screening
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    ABSTRACT: Abstract Background A five-dimensional (5-D) clone pooling strategy for screening of bacterial artificial chromosome (BAC) clones with molecular markers utilizing highly-parallel Illumina GoldenGate assays and PCR facilitates high-throughput BAC clone and BAC contig anchoring on a genetic map. However, this strategy occasionally needs manual PCR to deconvolute pools and identify truly positive clones. Results A new implementation is reported here for our previously reported clone pooling strategy. Row and column pools of BAC clones are divided into sub-pools with 1~2× genome coverage. All BAC pools are screened with Illumina's GoldenGate assay and the BAC pools are deconvoluted to identify individual positive clones. Putative positive BAC clones are then further analyzed to find positive clones on the basis of them being neighbours in a contig. An exhaustive search or brute force algorithm was designed for this deconvolution and integrated into a newly developed software tool, FPCBrowser, for analyzing clone pooling data. This algorithm was used with empirical data for 55 Illumina GoldenGate SNP assays detecting SNP markers mapped on Aegilops tauschii chromosome 2D and Ae. tauschii contig maps. Clones in single contigs were successfully assigned to 48 (87%) specific SNP markers on the map with 91% precision. Conclusion A new implementation of 5-D BAC clone pooling strategy employing both GoldenGate assay screening and assembled BAC contigs is shown here to be a high-throughput, low cost, rapid, and feasible approach to screening BAC libraries and anchoring BAC clones and contigs on genetic maps. The software FPCBrowser with the integrated clone deconvolution algorithm has been developed and is downloadable at http://avena.pw.usda.gov/wheatD/fpcbrowser.shtml.
    BMC Genomics. 01/2010;
  • Article: Nucleotide diversity maps reveal variation in diversity among wheat genomes and chromosomes
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    ABSTRACT: Abstract Background A genome-wide assessment of nucleotide diversity in a polyploid species must minimize the inclusion of homoeologous sequences into diversity estimates and reliably allocate individual haplotypes into their respective genomes. The same requirements complicate the development and deployment of single nucleotide polymorphism (SNP) markers in polyploid species. We report here a strategy that satisfies these requirements and deploy it in the sequencing of genes in cultivated hexaploid wheat (Triticum aestivum, genomes AABBDD) and wild tetraploid wheat (Triticum turgidum ssp. dicoccoides, genomes AABB) from the putative site of wheat domestication in Turkey. Data are used to assess the distribution of diversity among and within wheat genomes and to develop a panel of SNP markers for polyploid wheat. Results Nucleotide diversity was estimated in 2114 wheat genes and was similar between the A and B genomes and reduced in the D genome. Within a genome, diversity was diminished on some chromosomes. Low diversity was always accompanied by an excess of rare alleles. A total of 5,471 SNPs was discovered in 1791 wheat genes. Totals of 1,271, 1,218, and 2,203 SNPs were discovered in 488, 463, and 641 genes of wheat putative diploid ancestors, T. urartu, Aegilops speltoides, and Ae. tauschii, respectively. A public database containing genome-specific primers, SNPs, and other information was constructed. A total of 987 genes with nucleotide diversity estimated in one or more of the wheat genomes was placed on an Ae. tauschii genetic map, and the map was superimposed on wheat deletion-bin maps. The agreement between the maps was assessed. Conclusions In a young polyploid, exemplified by T. aestivum, ancestral species are the primary source of genetic diversity. Low effective recombination due to self-pollination and a genetic mechanism precluding homoeologous chromosome pairing during polyploid meiosis can lead to the loss of diversity from large chromosomal regions. The net effect of these factors in T. aestivum is large variation in diversity among genomes and chromosomes, which impacts the development of SNP markers and their practical utility. Accumulation of new mutations in older polyploid species, such as wild emmer, results in increased diversity and its more uniform distribution across the genome.
    BMC Genomics. 01/2010;
  • Article: GenoProfiler: batch processing of high-throughput capillary fingerprinting data.
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    ABSTRACT: High-throughput content fingerprinting techniques employing capillary electrophoresis place new demands on the editing of fingerprint files for the downstream contig assembly program, FPC. A cross-platform software application, GenoProfiler, was developed for automated editing of sized fingerprinting profiles generated by the ABI Genetic Analyzers. The batch-processing module extracts the sized fragment information directly from the ABI raw trace files, or from data files exported from GeneMapper or other size calling software, removes the background noise and undesired fragments, and generates fragment size files compatible with the FPC software. AVAILABILITY: http://wheat.pw.usda.gov/PhysicalMapping/
    Bioinformatics 02/2007; 23(2):240-2. · 5.47 Impact Factor