Diploid A genome wheat species harbor immense genetic variability which has been targeted and proven useful in wheat improvement. Development and deployment of sequence-based markers has opened avenues for comparative analysis, gene transfer and marker assisted selection (MAS) using high throughput cost effective genotyping techniques. Chromosome 2A of wheat is known to harbor several economically important genes. The present study aimed at identification of genic sequences corresponding to full length cDNAs and mining of SSRs and ISBPs from 2A draft sequence assembly of hexaploid wheat cv. Chinese Spring for marker development. In total, 1029 primer pairs including 478 gene derived, 501 SSRs and 50 ISBPs were amplified in diploid A genome species Triticum monococcum and T. boeoticum identifying 221 polymorphic loci. Out of these, 119 markers were mapped onto a pre-existing chromosome 2A genetic map consisting of 42 mapped markers. The enriched genetic map constituted 161 mapped markers with final map length of 549.6 cM. Further, 2A genetic map of T. monococcum was anchored to the physical map of 2A of cv. Chinese Spring which revealed several rearrangements between the two species. The present study generated a highly saturated genetic map of 2A and physical anchoring of genetically mapped markers revealed a complex genetic architecture of chromosome 2A that needs to be investigated further.
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http://dx.doi.org/10.1007/s11033-020-05295-9 | DOI Listing |
Nat Commun
January 2025
Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Spatial protein expression technologies can map cellular content and organization by simultaneously quantifying the expression of >40 proteins at subcellular resolution within intact tissue sections and cell lines. However, necessary image segmentation to single cells is challenging and error prone, easily confounding the interpretation of cellular phenotypes and cell clusters. To address these limitations, we present STARLING, a probabilistic machine learning model designed to quantify cell populations from spatial protein expression data while accounting for segmentation errors.
View Article and Find Full Text PDFBMC Genomics
January 2025
Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, Shandong, 261325, China.
Background: The evolution and development of flowers are biologically essential and of broad interest. Maize and sorghum have similar morphologies and phylogeny while harboring different inflorescence architecture. The difference in flower architecture between these two species is likely due to spatiotemporal gene expression regulation, and they are a good model for researching the evolution of flower development.
View Article and Find Full Text PDFNat Med
January 2025
Department of Medicine, Memorial Sloan Kettering Cancer Center, New York City, NY, USA.
Nearly all pancreatic adenocarcinomas (PDAC) are genomically characterized by KRAS exon 2 mutations. Most patients with PDAC present with advanced disease and are treated with cytotoxic therapy. Genomic biomarkers prognostic of disease outcomes have been challenging to identify.
View Article and Find Full Text PDFNat Genet
January 2025
Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA.
Genome-wide association studies have identified approximately 200 genetic risk loci for breast cancer, but the causal variants and target genes are mostly unknown. We sought to fine-map all known breast cancer risk loci using genome-wide association study data from 172,737 female breast cancer cases and 242,009 controls of African, Asian and European ancestry. We identified 332 independent association signals for breast cancer risk, including 131 signals not reported previously, and for 50 of them, we narrowed the credible causal variants down to a single variant.
View Article and Find Full Text PDFJ Neurosci
January 2025
Leibniz Institute for Neurobiology (LIN), Department of Genetics of Learning and Memory, Magdeburg, 39118 Germany
For a proper representation of the causal structure of the world, it is adaptive to consider both evidence for and evidence against causality. To take punishment as an example, the causality of a stimulus is unlikely if there is a temporal gap before punishment is received, but causality is credible if the stimulus immediately precedes punishment. In contrast, causality can be ruled out if the punishment occurred first.
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