ResearchPad - dwarfism https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[An improved 7K SNP array, the C7AIR, provides a wealth of validated SNP markers for rice breeding and genetics studies]]> https://www.researchpad.co/article/elastic_article_14581 Single nucleotide polymorphisms (SNPs) are highly abundant, amendable to high-throughput genotyping, and useful for a number of breeding and genetics applications in crops. SNP frequencies vary depending on the species and populations under study, and therefore target SNPs need to be carefully selected to be informative for each application. While multiple SNP genotyping systems are available for rice (Oryza sativa L. and its relatives), they vary in their informativeness, cost, marker density, speed, flexibility, and data quality. In this study, we report the development and performance of the Cornell-IR LD Rice Array (C7AIR), a second-generation SNP array containing 7,098 markers that improves upon the previously released C6AIR. The C7AIR is designed to detect genome-wide polymorphisms within and between subpopulations of O. sativa, as well as O. glaberrima, O. rufipogon and O. nivara. The C7AIR combines top-performing SNPs from several previous rice arrays, including 4,007 SNPs from the C6AIR, 2,056 SNPs from the High Density Rice Array (HDRA), 910 SNPs from the 384-SNP GoldenGate sets, 189 SNPs from the 44K array selected to add information content for elite U.S. tropical japonica rice varieties, and 8 trait-specific SNPs. To demonstrate its utility, we carried out a genome-wide association analysis for plant height, employing the C7AIR across a diversity panel of 189 rice accessions and identified 20 QTLs contributing to plant height. The C7AIR SNP chip has so far been used for genotyping >10,000 rice samples. It successfully differentiates the five subpopulations of Oryza sativa, identifies introgressions from wild and exotic relatives, and is useful for quantitative trait loci (QTL) and association mapping in diverse materials. Moreover, data from the C7AIR provides valuable information that can be used to select informative and reliable SNP markers for conversion to lower-cost genotyping platforms for genomic selection and other downstream applications in breeding.

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<![CDATA[Comparative transcriptome analysis provides insights into dwarfism in cherry tomato (Solanum lycopersicum var. cerasiforme)]]> https://www.researchpad.co/article/5c141ef4d5eed0c484d28ff7

Tomato, which can be eaten as a vegetable or fruit, is one of the most popular and nutritionally important crops around the world. Although most plants of the cherry tomato cultivar ‘Minichal’ have a normal phenotype, some plants have a stunted phenotype with reduced plant height, leaf size, and fruit size, as well as altered leaf and fruit shape. To investigate the molecular mechanisms underlying these differences, we generated RNA-seq libraries from pooled leaf samples of 10 normal (N) and 10 stunted (S) plants. Using the Illumina sequencing platform, we obtained a total of 115.45 million high-quality clean reads assembled into 35,216 genes and 35,216 transcripts. A total of 661 genes were differentially expressed between N and S plants. Of these, 420 differentially expressed genes (DEGs) were up-regulated, and 221 DEGs were down-regulated. The RNA-seq data were validated using quantitative reverse-transcription PCR. Enrichment analysis of DEGs using the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that the enriched pathways were involved in steroid biosynthesis, homologous recombination, and mismatch repair. Among these, three genes related to steroid biosynthesis, including 3BETAHSD/D2, DIM and DWF5 were down-regulated in S compared to N. Of these, DIM and DWF5 are known to be involved in brassinosteroid biosynthesis. Our results thus provide a useful insight into dwarfism in cherry tomato, and offer a platform for evaluating related species.

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<![CDATA[Hepatic gene body hypermethylation is a shared epigenetic signature of murine longevity]]> https://www.researchpad.co/article/5bff05fdd5eed0c484a340dc

Dietary, pharmacological and genetic interventions can extend health- and lifespan in diverse mammalian species. DNA methylation has been implicated in mediating the beneficial effects of these interventions; methylation patterns deteriorate during ageing, and this is prevented by lifespan-extending interventions. However, whether these interventions also actively shape the epigenome, and whether such epigenetic reprogramming contributes to improved health at old age, remains underexplored. We analysed published, whole-genome, BS-seq data sets from mouse liver to explore DNA methylation patterns in aged mice in response to three lifespan-extending interventions: dietary restriction (DR), reduced TOR signaling (rapamycin), and reduced growth (Ames dwarf mice). Dwarf mice show enhanced DNA hypermethylation in the body of key genes in lipid biosynthesis, cell proliferation and somatotropic signaling, which strongly correlates with the pattern of transcriptional repression. Remarkably, DR causes a similar hypermethylation in lipid biosynthesis genes, while rapamycin treatment increases methylation signatures in genes coding for growth factor and growth hormone receptors. Shared changes of DNA methylation were restricted to hypermethylated regions, and they were not merely a consequence of slowed ageing, thus suggesting an active mechanism driving their formation. By comparing the overlap in ageing-independent hypermethylated patterns between all three interventions, we identified four regions, which, independent of genetic background or gender, may serve as novel biomarkers for longevity-extending interventions. In summary, we identified gene body hypermethylation as a novel and partly conserved signature of lifespan-extending interventions in mouse, highlighting epigenetic reprogramming as a possible intervention to improve health at old age.

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<![CDATA[Elevated Fibroblast Growth Factor Signaling Is Critical for the Pathogenesis of the Dwarfism in Evc2/Limbin Mutant Mice]]> https://www.researchpad.co/article/5989da31ab0ee8fa60b849ac

Ellis-van Creveld (EvC) syndrome is a skeletal dysplasia, characterized by short limbs, postaxial polydactyly, and dental abnormalities. EvC syndrome is also categorized as a ciliopathy because of ciliary localization of proteins encoded by the two causative genes, EVC and EVC2 (aka LIMBIN). While recent studies demonstrated important roles for EVC/EVC2 in Hedgehog signaling, there is still little known about the pathophysiological mechanisms underlying the skeletal dysplasia features of EvC patients, and in particular why limb development is affected, but not other aspects of organogenesis that also require Hedgehog signaling. In this report, we comprehensively analyze limb skeletogenesis in Evc2 mutant mice and in cell and tissue cultures derived from these mice. Both in vivo and in vitro data demonstrate elevated Fibroblast Growth Factor (FGF) signaling in Evc2 mutant growth plates, in addition to compromised but not abrogated Hedgehog-PTHrP feedback loop. Elevation of FGF signaling, mainly due to increased Fgf18 expression upon inactivation of Evc2 in the perichondrium, critically contributes to the pathogenesis of limb dwarfism. The limb dwarfism phenotype is partially rescued by inactivation of one allele of Fgf18 in the Evc2 mutant mice. Taken together, our data uncover a novel pathogenic mechanism to understand limb dwarfism in patients with Ellis-van Creveld syndrome.

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<![CDATA[The Implicitome: A Resource for Rationalizing Gene-Disease Associations]]> https://www.researchpad.co/article/5989dacfab0ee8fa60bb5b9a

High-throughput experimental methods such as medical sequencing and genome-wide association studies (GWAS) identify increasingly large numbers of potential relations between genetic variants and diseases. Both biological complexity (millions of potential gene-disease associations) and the accelerating rate of data production necessitate computational approaches to prioritize and rationalize potential gene-disease relations. Here, we use concept profile technology to expose from the biomedical literature both explicitly stated gene-disease relations (the explicitome) and a much larger set of implied gene-disease associations (the implicitome). Implicit relations are largely unknown to, or are even unintended by the original authors, but they vastly extend the reach of existing biomedical knowledge for identification and interpretation of gene-disease associations. The implicitome can be used in conjunction with experimental data resources to rationalize both known and novel associations. We demonstrate the usefulness of the implicitome by rationalizing known and novel gene-disease associations, including those from GWAS. To facilitate the re-use of implicit gene-disease associations, we publish our data in compliance with FAIR Data Publishing recommendations [https://www.force11.org/group/fairgroup] using nanopublications. An online tool (http://knowledge.bio) is available to explore established and potential gene-disease associations in the context of other biomedical relations.

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<![CDATA[The Dwarf Phenotype in GH240B Mice, Haploinsufficient for the Autism Candidate Gene Neurobeachin, Is Caused by Ectopic Expression of Recombinant Human Growth Hormone]]> https://www.researchpad.co/article/5989db43ab0ee8fa60bd7645

Two knockout mouse models for the autism candidate gene Neurobeachin (Nbea) have been generated independently. Although both models have similar phenotypes, one striking difference is the dwarf phenotype observed in the heterozygous configuration of the GH240B model that is generated by the serendipitous insertion of a promoterless human growth hormone (hGH) genomic fragment in the Nbea gene. In order to elucidate this discrepancy, the dwarfism present in this Nbea mouse model was investigated in detail. The growth deficiency in Nbea+/− mice coincided with an increased percentage of fat mass and a decrease in bone mineral density. Low but detectable levels of hGH were detected in the pituitary and hypothalamus of Nbea+/− mice but not in liver, hippocampus nor in serum. As a consequence, several members of the mouse growth hormone (mGH) signaling cascade showed altered mRNA levels, including a reduction in growth hormone-releasing hormone mRNA in the hypothalamus. Moreover, somatotrope cells were less numerous in the pituitary of Nbea+/− mice and both contained and secreted significantly less mGH resulting in reduced levels of circulating insulin-like growth factor 1. These findings demonstrate that the random integration of the hGH transgene in this mouse model has not only inactivated Nbea but has also resulted in the tissue-specific expression of hGH causing a negative feedback loop, mGH hyposecretion and dwarfism.

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