Mutagenesis is the only process by which unpredicted biological gene function can be identified. Despite that several macroalgal developmental mutants have been generated, their causal mutation was never identified, because experimental conditions were not gathered at that time. Today, progresses in macroalgal genomics and judicious choices of suitable genetic models make mutated gene identification possible. This article presents a comparative study of two methods aiming at identifying a genetic locus in the brown alga Ectocarpus siliculosus: positional cloning and Next-Generation Sequencing (NGS)-based mapping. Once necessary preliminary experimental tools were gathered, we tested both analyses on an Ectocarpus morphogenetic mutant. We show how a narrower localization results from the combination of the two methods. Advantages and drawbacks of these two approaches as well as potential transfer to other macroalgae are discussed.
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http://dx.doi.org/10.3389/fpls.2015.00068 | DOI Listing |
Int J Mol Sci
September 2024
Plant Breeding and Acclimatization Institute-National Research Institute, Radzików, 05-870 Błonie, Poland.
J Am Chem Soc
September 2024
Department of Biological and Chemical Sciences, New York Institute of Technology, New York, New York 10023, United States.
Despite the extensive use of next-generation sequencing (NGS) of RNA, simultaneous direct sequencing and quantitative mapping of multiple RNA nucleotide modifications remains challenging. Mass spectrometry (MS)-based sequencing can directly sequence all RNA modifications without being limited to specific ones, but it requires a perfect MS ladder that few tRNAs can provide. Here, we describe an MS ladder complementation sequencing approach (MLC-Seq) that circumvents the perfect ladder requirement, allowing de novo MS sequencing of full-length heterogeneous cellular tRNAs with multiple nucleotide modifications at single-nucleotide precision.
View Article and Find Full Text PDFJ Bioinform Comput Biol
June 2024
Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India.
A turning point in cancer research is the introduction of massively parallel sequencing technology which greatly reduced the cost and time for genome sequencing. This enhanced the scope for detecting and analyzing the role of structural alterations in cancer. However, certain bias exists in NGS-based approaches, which badly affects the CNV identification process.
View Article and Find Full Text PDFMol Plant
April 2024
State Key Laboratory of Vegetable Biobreeding, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology and Genetic Improvement of Tuber and Root Crop of Ministry of Agriculture and Rural Affairs, Sino-Dutch Joint Laboratory of Horticultural Genomics, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China. Electronic address:
Constructing inbred lines for self-incompatible species and species with long generation times is challenging, making the use of F outcross/segregating populations the main strategy for genetic studies of such species. However, there is a lack of dedicated algorithms/tools for rapid quantitative trait locus (QTL) mapping using the F populations. To this end, we have designed and developed an algorithm/tool called OcBSA specifically for QTL mapping of F populations.
View Article and Find Full Text PDFPlant Mol Biol
February 2024
Indian Institute of Pulses Research (IIPR), Uttar Pradesh, Kanpur, 208024, India.
Chickpea (Cicer arietinum) is a cool season grain legume experiencing severe yield loss during heat stress due to the intensifying climate changes and its associated gradual increase of mean temperature. Hence, understanding the genetic architecture regulating heat stress tolerance has emerged as an important trait to be addressed for enhancing yield and productivity of chickpea under heat stress. The present study is intended to identify the major genomic region(s) governing heat stress tolerance in chickpea.
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