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Genome

About: Genome is a research topic. Over the lifetime, 74231 publications have been published within this topic receiving 3819713 citations.


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Journal ArticleDOI
TL;DR: The nucleotide binding site (NBS) is a characteristic domain of many plant resistance gene products and its wide distribution in the plant kingdom and their prevalence in the Arabidopsis and rice genomes indicate that they are ancient, diverse and common in plants.
Abstract: The nucleotide binding site (NBS) is a characteristic domain of many plant resistance gene products. An increasing number of NBS-encoding sequences are being identified through gene cloning, PCR amplification with degenerate primers, and genome sequencing projects. The NBS domain was analyzed from 14 known plant resistance genes and more than 400 homologs, representing 26 genera of monocotyledonous, dicotyle-donous and one coniferous species. Two distinct groups of diverse sequences were identified, indicating divergence during evolution and an ancient origin for these sequences. One group was comprised of sequences encoding an N-terminal domain with Toll/Interleukin-1 receptor homology (TIR), including the known resistance genes, N, M, L6, RPP1 and RPP5. Surprisingly, this group was entirely absent from monocot species in searches of both random genomic sequences and large collections of ESTs. A second group contained monocot and dicot sequences, including the known resistance genes, RPS2, RPM1, I2, Mi, Dm3, Pi-B, Xa1, RPP8, RPS5 and Prf. Amino acid signatures in the conserved motifs comprising the NBS domain clearly distinguished these two groups. The Arabidopsis genome is estimated to contain approximately 200 genes that encode related NBS motifs; TIR sequences were more abundant and outnumber non-TIR sequences threefold. The Arabidopsis NBS sequences currently in the databases are located in approximately 21 genomic clusters and 14 isolated loci. NBS-encoding sequences may be more prevalent in rice. The wide distribution of these sequences in the plant kingdom and their prevalence in the Arabidopsis and rice genomes indicate that they are ancient, diverse and common in plants. Sequence inferences suggest that these genes encode a novel class of nucleotide-binding proteins.

775 citations

Journal ArticleDOI
27 May 2005-Science
TL;DR: Analysis of single-nucleotide polymorphisms in 774 genes indicates that 2 to 4% of these genes experienced artificial selection, and candidate selected genes with putative function in plant growth are clustered near quantitative trait loci that contribute to phenotypic differences between maize and teosinte.
Abstract: Domestication promotes rapid phenotypic evolution through artificial selection. We investigated the genetic history by which the wild grass teosinte (Zea mays ssp. parviglumis) was domesticated into modern maize (Z. mays ssp. mays). Analysis of single-nucleotide polymorphisms in 774 genes indicates that 2 to 4% of these genes experienced artificial selection. The remaining genes retain evidence of a population bottleneck associated with domestication. Candidate selected genes with putative function in plant growth are clustered near quantitative trait loci that contribute to phenotypic differences between maize and teosinte. If we assume that our sample of genes is representative, ∼1200 genes throughout the maize genome have been affected by artificial selection.

775 citations

Journal ArticleDOI
TL;DR: HiChIP of cohesin reveals multiscale genome architecture with greater signal-to-background ratios than those of in situ Hi-C and improves the yield of conformation-informative reads by over 10-fold and the input requirement over 100-fold relative to that of ChIA-PET.
Abstract: Genome conformation is central to gene control but challenging to interrogate. Here we present HiChIP, a protein-centric chromatin conformation method. HiChIP improves the yield of conformation-informative reads by over 10-fold and lowers the input requirement over 100-fold relative to that of ChIA-PET. HiChIP of cohesin reveals multiscale genome architecture with greater signal-to-background ratios than those of in situ Hi-C.

774 citations

Journal ArticleDOI
26 Oct 2018-Science
TL;DR: These chromatin accessibility profiles identify cancer- and tissue-specific DNA regulatory elements that enable classification of tumor subtypes with newly recognized prognostic importance, and identify distinct TF activities in cancer based on differences in the inferred patterns of TF-DNA interaction and gene expression.
Abstract: INTRODUCTION Cancer is one of the leading causes of death worldwide. Although the 2% of the human genome that encodes proteins has been extensively studied, much remains to be learned about the noncoding genome and gene regulation in cancer. Genes are turned on and off in the proper cell types and cell states by transcription factor (TF) proteins acting on DNA regulatory elements that are scattered over the vast noncoding genome and exert long-range influences. The Cancer Genome Atlas (TCGA) is a global consortium that aims to accelerate the understanding of the molecular basis of cancer. TCGA has systematically collected DNA mutation, methylation, RNA expression, and other comprehensive datasets from primary human cancer tissue. TCGA has served as an invaluable resource for the identification of genomic aberrations, altered transcriptional networks, and cancer subtypes. Nonetheless, the gene regulatory landscapes of these tumors have largely been inferred through indirect means. RATIONALE A hallmark of active DNA regulatory elements is chromatin accessibility. Eukaryotic genomes are compacted in chromatin, a complex of DNA and proteins, and only the active regulatory elements are accessible by the cell’s machinery such as TFs. The assay for transposase-accessible chromatin using sequencing (ATAC-seq) quantifies DNA accessibility through the use of transposase enzymes that insert sequencing adapters at these accessible chromatin sites. ATAC-seq enables the genome-wide profiling of TF binding events that orchestrate gene expression programs and give a cell its identity. RESULTS We generated high-quality ATAC-seq data in 410 tumor samples from TCGA, identifying diverse regulatory landscapes across 23 cancer types. These chromatin accessibility profiles identify cancer- and tissue-specific DNA regulatory elements that enable classification of tumor subtypes with newly recognized prognostic importance. We identify distinct TF activities in cancer based on differences in the inferred patterns of TF-DNA interaction and gene expression. Genome-wide correlation of gene expression and chromatin accessibility predicts tens of thousands of putative interactions between distal regulatory elements and gene promoters, including key oncogenes and targets in cancer immunotherapy, such as MYC , SRC , BCL2 , and PDL1 . Moreover, these regulatory interactions inform known genetic risk loci linked to cancer predisposition, nominating biochemical mechanisms and target genes for many cancer-linked genetic variants. Lastly, integration with mutation profiling by whole-genome sequencing identifies cancer-relevant noncoding mutations that are associated with altered gene expression. A single-base mutation located 12 kilobases upstream of the FGD4 gene, a regulator of the actin cytoskeleton, generates a putative de novo binding site for an NKX TF and is associated with an increase in chromatin accessibility and a concomitant increase in FGD4 gene expression. CONCLUSION The accessible genome of primary human cancers provides a wealth of information on the susceptibility, mechanisms, prognosis, and potential therapeutic strategies of diverse cancer types. Prediction of interactions between DNA regulatory elements and gene promoters sets the stage for future integrative gene regulatory network analyses. The discovery of hundreds of noncoding somatic mutations that exhibit allele-specific regulatory effects suggests a pervasive mechanism for cancer cells to manipulate gene expression and increase cellular fitness. These data may serve as a foundational resource for the cancer research community.

774 citations

Journal ArticleDOI
TL;DR: A high-throughput genome-based method for genotyping recombinant populations utilizing whole-genome resequencing data generated by the Illumina Genome Analyzer is developed and located a quantitative trait locus of large effect on plant height in a 100-kb region containing the rice "green revolution" gene.
Abstract: The next-generation sequencing technology coupled with the growing number of genome sequences opens the opportunity to redesign genotyping strategies for more effective genetic mapping and genome analysis. We have developed a high-throughput method for genotyping recombinant populations utilizing whole-genome resequencing data generated by the Illumina Genome Analyzer. A sliding window approach is designed to collectively examine genome-wide single nucleotide polymorphisms for genotype calling and recombination breakpoint determination. Using this method, we constructed a genetic map for 150 rice recombinant inbred lines with an expected genotype calling accuracy of 99.94% and a resolution of recombination breakpoints within an average of 40 kb. In comparison to the genetic map constructed with 287 PCR-based markers for the rice population, the sequencing-based method was approximately 20x faster in data collection and 35x more precise in recombination breakpoint determination. Using the sequencing-based genetic map, we located a quantitative trait locus of large effect on plant height in a 100-kb region containing the rice "green revolution" gene. Through computer simulation, we demonstrate that the method is robust for different types of mapping populations derived from organisms with variable quality of genome sequences and is feasible for organisms with large genome sizes and low polymorphisms. With continuous advances in sequencing technologies, this genome-based method may replace the conventional marker-based genotyping approach to provide a powerful tool for large-scale gene discovery and for addressing a wide range of biological questions.

773 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20242
20237,313
202214,209
20214,955
20205,080
20194,839