45 research outputs found

    RNA-seq combined with a bulked-segregant analysis identifies candidate genes for the waxy coating on blueberry fruit

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    The most significant difference between blueberries with a light blue fruit color and black fruit color is the visible layer of an epicuticular waxy coating. This layer functions in disease defense and prevention of water loss. In this study, we constructed a northern-adapted rabbiteye hybrid breeding population, ‘Nocturne’ x T 300, which segregated for fruit color (light blue versus black). We screened this population and selected plants of each extreme phenotype, waxy- coated plants with light blue colored fruit versus non-waxy plants with black colored fruit, then isolated RNA from fruit tissue of each bulk, respectively. We sequenced the transcriptome of each bulk using RNA-seq, which resulted in a total of 167,093,354 reads for both libraries combined. We de novo assembled this data set into 171,678 contigs and used the assembled transcriptome as a reference for differential expression analysis using EdgeR. A total of 515 differentially expressed genes were identified with at least a four-fold difference in expression, and efforts were made to functionally annotate them using publicly available databases. From these, one excellent candidate ‘waxy’ gene has emerged, which we are investigating further

    High-Density Linkage Map Construction and QTL Identification in a Diploid Blueberry Mapping Population

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    Genotyping by sequencing approaches have been widely applied in major crops and are now being used in horticultural crops like berries and fruit trees. As the original and largest producer of cultivated blueberry, the United States maintains the most diverse blueberry germplasm resources comprised of many species of different ploidy levels. We previously constructed an interspecific mapping population of diploid blueberry by crossing the parent F1#10 (Vaccinium darrowii Fla4B × diploid V. corymbosum W85–20) with the parent W85–23 (diploid V. corymbosum). Employing the Capture-Seq technology developed by RAPiD Genomics, with an emphasis on probes designed in predicted gene regions, 117 F1 progeny, the two parents, and two grandparents of this population were sequenced, yielding 131.7 Gbp clean sequenced reads. A total of 160,535 single nucleotide polymorphisms (SNPs), referenced to 4,522 blueberry genome sequence scaffolds, were identified and subjected to a parent-dependent sliding window approach to further genotype the population. Recombination breakpoints were determined and marker bins were deduced to construct a high density linkage map. Twelve blueberry linkage groups (LGs) consisting of 17,486 SNP markers were obtained, spanning a total genetic distance of 1,539.4 cM. Among 18 horticultural traits phenotyped in this population, quantitative trait loci (QTLs) that were significant over at least 2 years were identified for chilling requirement, cold hardiness, and fruit quality traits of color, scar size, and firmness. Interestingly, in 1 year, a QTL associated with timing of early bloom, full bloom, petal fall, and early green fruit was identified in the same region harboring the major QTL for chilling requirement. In summary, we report here the first high density bin map of a diploid blueberry mapping population and the identification of several horticulturally important QTLs

    Autopolyploid inheritance and a heterozygous reciprocal translocation shape chromosome genetic behavior in tetraploid blueberry (Vaccinium corymbosum)

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    Understanding chromosome recombination behavior in polyploidy species is key to advancing genetic discoveries. In blueberry, a tetraploid species, the line of evidences about its genetic behavior still remain poorly understood, owing to the inter-specific, and inter-ploidy admixture of its genome and lack of in depth genome-wide inheritance and comparative structural studies. Here we describe a new high-quality, phased, chromosome-scale genome of a diploid blueberry, clone W85. The genome was integrated with cytogenetics and high-density, genetic maps representing six tetraploid blueberry cultivars, harboring different levels of wild genome admixture, to uncover recombination behavior and structural genome divergence across tetraploid and wild diploid species. Analysis of chromosome inheritance and pairing demonstrated that tetraploid blueberry behaves as an autotetraploid with tetrasomic inheritance. Comparative analysis demonstrated the presence of a reciprocal, heterozygous, translocation spanning one homolog of chr-6 and one of chr-10 in the cultivar Draper. The translocation affects pairing and recombination of chromosomes 6 and 10. Besides the translocation detected in Draper, no other structural genomic divergences were detected across tetraploid cultivars and highly inter-crossable wild diploid species. These findings and resources will facilitate new genetic and comparative genomic studies in Vaccinium and the development of genomic assisted selection strategy for this cro

    A reference-grade wild soybean genome

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    Efficient crop improvement depends on the application of accurate genetic information contained in diverse germplasm resources. Here we report a reference-grade genome of wild soybean accession W05, with a final assembled genome size of 1013.2 Mb and a contig N50 of 3.3 Mb. The analytical power of the W05 genome is demonstrated by several examples. First, we identify an inversion at the locus determining seed coat color during domestication. Second, a translocation event between chromosomes 11 and 13 of some genotypes is shown to interfere with the assignment of QTLs. Third, we find a region containing copy number variations of the Kunitz trypsin inhibitor (KTI) genes. Such findings illustrate the power of this assembly in the analysis of large structural variations in soybean germplasm collections. The wild soybean genome assembly has wide applications in comparative genomic and evolutionary studies, as well as in crop breeding and improvement programs

    A reference-grade wild soybean genome

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    Wild relatives of crop plants are invaluable germplasm for genetic improvement. Here, Xie et al. report a reference-grade wild soybean genome and show that it can be used to identify structural variation and refine quantitative trait loci

    A low-overhead, confidentiality-assured, and authenticated data acquisition framework for IoT

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    Silicon Era of Carbon-Based Life: Application of Genomics and Bioinformatics in Crop Stress Research

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    Abstract: Abiotic and biotic stresses lead to massive reprogramming of different life processes and are the major limiting factors hampering crop productivity. Omics-based research platforms allow for a holistic and comprehensive survey on crop stress responses and hence may bring forth better crop improvement strategies. Since high-throughput approaches generate considerable amounts of data, bioinformatics tools will play an essential role in storing, retrieving, sharing, processing, and analyzing them. Genomic and functional genomic studies in crops still lag far behind similar studies in humans and other animals. In this review, we summarize some useful genomics and bioinformatics resources available to crop scientists. In addition, we also discuss the major challenges and advancements in the “-omics ” studies, with an emphasis on their possible impacts on crop stress research and crop improvement

    Generative Steganographic Flow

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    Generative steganography (GS) is a new data hiding manner, featuring direct generation of stego media from secret data. Existing GS methods are generally criticized for their poor performances. In this paper, we propose a novel flow based GS approach -- Generative Steganographic Flow (GSF), which provides direct generation of stego images without cover image. We take the stego image generation and secret data recovery process as an invertible transformation, and build a reversible bijective mapping between input secret data and generated stego images. In the forward mapping, secret data is hidden in the input latent of Glow model to generate stego images. By reversing the mapping, hidden data can be extracted exactly from generated stego images. Furthermore, we propose a novel latent optimization strategy to improve the fidelity of stego images. Experimental results show our proposed GSF has far better performances than SOTA works.Comment: The accepted paper in ICME 202
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