32 research outputs found
Genomic Diversity and Introgression in O. sativa Reveal the Impact of Domestication and Breeding on the Rice Genome
The domestication of Asian rice (Oryza sativa) was a complex process punctuated by episodes of introgressive hybridization among and between subpopulations. Deep genetic divergence between the two main varietal groups (Indica and Japonica) suggests domestication from at least two distinct wild populations. However, genetic uniformity surrounding key domestication genes across divergent subpopulations suggests cultural exchange of genetic material among ancient farmers.In this study, we utilize a novel 1,536 SNP panel genotyped across 395 diverse accessions of O. sativa to study genome-wide patterns of polymorphism, to characterize population structure, and to infer the introgression history of domesticated Asian rice. Our population structure analyses support the existence of five major subpopulations (indica, aus, tropical japonica, temperate japonica and GroupV) consistent with previous analyses. Our introgression analysis shows that most accessions exhibit some degree of admixture, with many individuals within a population sharing the same introgressed segment due to artificial selection. Admixture mapping and association analysis of amylose content and grain length illustrate the potential for dissecting the genetic basis of complex traits in domesticated plant populations.Genes in these regions control a myriad of traits including plant stature, blast resistance, and amylose content. These analyses highlight the power of population genomics in agricultural systems to identify functionally important regions of the genome and to decipher the role of human-directed breeding in refashioning the genomes of a domesticated species
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In vivo measurement of mid-infrared light scattering from human skin
Two mid-infrared light sources, a broadband source from a Fourier Transform Infrared Spectrometer (FTIR) and a pulsed Quantum Cascade (QC) Laser, are used to measure angle-resolved backscattering in vivo from human skin across a broad spectral range. Scattering profiles measured using the FTIR suggest limited penetration of the light into the skin, with most of the light interacting with the stratum corneum layer of the epidermis. Scattering profiles from the QC laser show modulation patterns with angle suggesting interaction with scattering centers in the skin. The scattering is attributed to interaction of the laser light with components such as collagen fibers and capillaries in the dermis layer of the skin
Chromosome segment substitution lines: a powerful tool for the Introgression of valuable genes from oryza wild species into cultivated rice (O. sativa)
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In vitro measurements of physiological glucose concentrations in biological fluids using mid-infrared spectroscopy
Mid-infrared transmission spectroscopy using broadband midinfrared or Quantum Cascade laser sources is used to predict glucose concentrations of aqueous and serum solutions containing physiologically relevant amounts of glucose (50-400 mg/dL). We employ partial least squares regression to generate a calibration model using a subset of the spectra taken and to predict concentrations from new spectra. Clinically accurate measurements with respect to a Clarke error grid were made for concentrations as low as 30 mg/dL, regardless of background solvent. These results are an important and encouraging step in the work towards developing a noninvasive in vivo glucose sensor in the mid-infrared
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Noninvasive in vivo glucose sensing on human subjects using mid-infrared light
Mid-infrared quantum cascade laser spectroscopy is used to noninvasively predict blood glucose concentrations of three healthy human subjects in vivo. We utilize a hollow-core fiber based optical setup for light delivery and collection along with a broadly tunable quantum cascade laser to obtain spectra from human subjects and use standard chemo-metric techniques (namely partial least squares regression) for prediction analysis. Throughout a glucose concentration range of 80-160 mg/dL, we achieve clinically accurate predictions 84% of the time, on average. This work opens a new path to a noninvasive in vivo glucose sensor that would benefit the lives of hundreds of millions of diabetics worldwide
