Development of highly informative markers such as simple sequence repeats (SSR) for cultivar identification and germplasm characterization and management is essential for date palms genetic studies. The present study documents the development of SSR markers and assesses genetic relationships of commonly grown date palm (Phoenix dactylifera L.) cultivars in different geographical regions of Saudi Arabia. A total of 93 novel simple sequence repeat (SSR) markers were screened for their ability to detect polymorphism in date palm. Around 71% of genomic SSRs are dinucleotide, 25% trinucleotide, 3% tetranucleotide, and 1% pentanucleotide motives and show 100% polymorphism. The Unweighted Pair Group Method with Arithmetic Mean (UPGMA) cluster analysis illustrates that cultivars trend to group according to their class of maturity, region of cultivation, and fruit color. Analysis of molecular variations (AMOVA) reveals genetic variation among and within cultivars of 27% and 73%, respectively, according to the geographical distribution of the cultivars. Developed microsatellite markers are of additional value to date palm characterization, tools which can be used by researchers in population genetics, cultivar identification, as well as genetic resource exploration and management. The cultivars tested exhibited a significant amount of genetic diversity and could be suitable for successful breeding programs. Genomic sequences generated from this study are available at the National Center for Biotechnology Information (NCBI), Sequence Read Archive (Accession numbers. LIBGSS_039019).
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http://dx.doi.org/10.1007/978-1-4939-7159-6_24 | DOI Listing |
Bioinform Adv
November 2024
Department of Biology and Evolution of Marine Organisms (BEOM), Stazione Zoologica Anton Dohrn, Roma I-00198, Italy.
Motivation: Accurate sequence length profiling is essential in bioinformatics, particularly in genomics and proteomics. Existing tools like SeqKit and the Trinity toolkit provide basic sequence statistics but often fall short in offering comprehensive analytics and plotting options. For instance, SeqKit is a very complete and fast tool for sequence analysis, delivering useful metrics (e.
View Article and Find Full Text PDFAACE Clin Case Rep
August 2024
Department of Endocrinology, Endocrine Associates of West Village, New York City, New York.
Background/objective: Genetic causes of hypertriglyceridemia like familial chylomicronemia syndrome can be overlooked in everyday practice. We report a patient with a rare genetic mutation, highlighting the importance of genetic testing for timely diagnosis and prevention of complications.
Case Report: A 45-year-old Hispanic female presented with serum triglyceride levels of 749 mg/dL, refractory to rosuvastatin 10 mg daily and omega-3 ethyl esters 2 g daily.
Comput Biol Med
December 2024
KAM School of Life Sciences, Forman Christian College University, Lahore, Pakistan. Electronic address:
Classification of viruses carries important implications in terms of understanding their evolution and the designing of interventions. This study introduces ViroNia as a novel LSTM-based system specifically meant for high-accuracy classification of viral proteins. Although originally developed for generative tasks, LSTM architectures have been found to be highly efficient for classification tasks as well; the model demonstrates this capability.
View Article and Find Full Text PDFDiagn Microbiol Infect Dis
December 2024
Department of Molecular Epidemiology, National Institute of Malaria Research, Sector-8, Dwarka, Delhi 110077, India. Electronic address:
Microsatellites, or simple sequence repeats (SSRs), are short tandemly repeated DNA sequences widely dispersed throughout the genome. Their high variability, co-dominant inheritance, and ease of detection make them valuable genetic markers, frequently used to study genetic diversity, population structure, and evolutionary processes. In the context of malaria research, particularly with Plasmodium falciparum (P.
View Article and Find Full Text PDFNeural Netw
December 2024
Department of Automation, Tsinghua University, Beijing 100084, China. Electronic address:
Deep learning systems are prone to catastrophic forgetting when learning from a sequence of tasks, as old data from previous tasks is unavailable when learning a new task. To address this, some methods propose replaying data from previous tasks during new task learning, typically using extra memory to store replay data. However, it is not expected in practice due to memory constraints and data privacy issues.
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