2020
DOI: 10.1007/978-3-030-21270-4_5
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Transcriptome Resources Paving the Way for Lupin Crop Improvement

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Cited by 3 publications
(3 citation statements)
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“…To this end a range of genetic and genomic resources have been developed for NLL in recent years. These include the generation of bacterial artificial chromosome (BAC) libraries (Gao et al., 2011; Kasprzak et al., 2006), transcriptome datasets (reviewed in Kamphuis et al., 2020), cytogenetic maps (Bielski et al., 2020) and various genetic maps. In addition, a survey genome sequence was generated in 2013 for NLL (Yang et al., 2013), followed by the first comprehensive draft genome sequence coupled with a dense reference genetic map for the species (Hane et al., 2017).…”
Section: Introductionmentioning
confidence: 99%
“…To this end a range of genetic and genomic resources have been developed for NLL in recent years. These include the generation of bacterial artificial chromosome (BAC) libraries (Gao et al., 2011; Kasprzak et al., 2006), transcriptome datasets (reviewed in Kamphuis et al., 2020), cytogenetic maps (Bielski et al., 2020) and various genetic maps. In addition, a survey genome sequence was generated in 2013 for NLL (Yang et al., 2013), followed by the first comprehensive draft genome sequence coupled with a dense reference genetic map for the species (Hane et al., 2017).…”
Section: Introductionmentioning
confidence: 99%
“…Co-expression studies with LDC/CAO in lupin (and LDC in S. flavescens ) have identified a growing number of candidate genes involved in QA accumulation in as yet unknown ways. The candidate genes include transcription factors, transporters, and a range of potential genes likely involved in metabolite modification ( Han et al, 2015 ; Yang et al, 2017 ; Kroc et al, 2019 ; Plewiński et al, 2019 ; Kamphuis et al, 2020 ). For candidate genes identified in lupin, we have demonstrated that a mirabait transcript capture ( Chevreux et al, 2004 ) and assembly strategy is an efficient way to use existing resources to obtain transcripts for candidate genes.…”
Section: Discussionmentioning
confidence: 99%
“…These EST datasets were predominantly used to convert expressed sequences into gene‐based molecular markers. This was achieved through identifying either sequence or length‐based polymorphisms between expressed sequence reads of different lupin lines and converting these into polymerase chain reaction (PCR)‐based molecular markers (reviewed in detail in Kamphuis et al, 2020). They have been successfully employed to construct the first genetic maps in white lupin ( L. albus ) (Croxford et al, 2008; Phan et al, 2007) and yellow lupin ( L. luteus ) (Iqbal et al, 2019; Lichtin et al, 2020) as well as improve the density of genetic maps in narrow‐leafed lupin (NLL) (Fischer et al, 2015; Nelson et al, 2006, 2010).…”
Section: Overview Of Lupin Transcriptome Resources and Their Use In Prebreeding/breeding Activitiesmentioning
confidence: 99%