2021
DOI: 10.1186/s12870-021-02989-5
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Characterization of full-length transcriptome in Saccharum officinarum and molecular insights into tiller development

Abstract: Background Although extensive breeding efforts are ongoing in sugarcane (Saccharum officinarum L.), the average yield is far below the theoretical potential. Tillering is an important component of sugarcane yield, however, the molecular mechanism underlying tiller development is still elusive. The limited genomic data in sugarcane, particularly due to its complex and large genome, has hindered in-depth molecular studies. Results Herein, we generate… Show more

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Cited by 19 publications
(10 citation statements)
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“…Next-generation sequencing (NGS) technology has accelerated the genome sequencing and resequencing of polyploidy crops to determine molecular markers’ genetic and physical mapping in specific loci/genes. These identified markers may be used to conduct molecular marker-assisted selection (MAS) breeding or evaluate the genetic links between different accessions using genotyping technologies to improve agronomic traits. The evolution of transcriptome sequences has improved gene interpretation by providing insight into the domestication and control of gene function networks via gene expression and sequence patterns , for modern breeding and genome editing.…”
Section: Introductionmentioning
confidence: 99%
“…Next-generation sequencing (NGS) technology has accelerated the genome sequencing and resequencing of polyploidy crops to determine molecular markers’ genetic and physical mapping in specific loci/genes. These identified markers may be used to conduct molecular marker-assisted selection (MAS) breeding or evaluate the genetic links between different accessions using genotyping technologies to improve agronomic traits. The evolution of transcriptome sequences has improved gene interpretation by providing insight into the domestication and control of gene function networks via gene expression and sequence patterns , for modern breeding and genome editing.…”
Section: Introductionmentioning
confidence: 99%
“…We analyzed SSR on transcripts over 500 bp selected from new transcripts with MIcroSAtellite identification toolsoftware which could identify 7 types of SSR, they are Mono nucleotide (p1), Di nucleotide (p2), Tri nucleotide (p3), Tetra nucleotide (p4), Penta nucleotide (p5), Hexa nucleotide (p6), compound SSR (c) and compound SSR with overlapping positions (c*) [ 42 ]. It can be seen that there are significant differences in the number and density distribution of different types of SSR (Table 2 , Fig.…”
Section: Resultsmentioning
confidence: 99%
“…The prediction principle of this method was to use BLAST software (version 2.2.26) to compare the sequences in pairs. The alignment results met the following conditions: the lengths of both sequences were greater than 1000 bp, and contained two HSPs (High-scoring Segment Pairs) in the alignment; The AS gap was greater than 100 bp and at least 100 bp away from the end of 3′/5′; Allowing an overlap of 5 bp of the all alternative transcripts, then were considered as candidate AS events [ 28 ].…”
Section: Methodsmentioning
confidence: 99%