In silico cloning and chromosomal localization of EST sequences that are related to leaf senescence using nulli-tetrasomes in wheat

Abstract

Leaf senescence is a notably important trait that limits the yield and biomass accumulation of agronomic crops. Therefore, determining the chromosomal position of the expression sequence tags (ESTs) that are associated with leaf senescence is notably interesting in the manipulation of leaf senescence for crop improvement. A total of 32 ESTs that were previously identified during the delaying leaf senescence stage in the stay-green wheat cultivar CN17 were mapped to 42 chromosomes, a chloroplast, a mitochondrion, and a ribosome using in silico mapping. Then, we developed 19 pairs of primers based on these sequences and used them to determine the polymorphisms between the stay-green cultivars (CN12, CN17, and CN18) and the control cultivar MY11. Among the 19 pairs of primers, 5 pairs produced polymorphisms between the stay-green cultivar and the non-stay-green control. Further studies of Chinese Spring nullisomic-tetrasomics show that JK738991 is mapped to 3B, JK738983 is mapped to 5D, and JK738989 is mapped to 2A, 4A, and 3D. The other two ESTs, JK738994 and JK739003, were not assigned to a chromosome using the Chinese Spring nullisomic-tetrasomics, which indicates that these ESTs may be derived from rye DNA in the wide cross. In particular, the ESTs that produce polymorphisms are notably useful in identifying the stay-green cultivar using molecular marker-assisted selection. The results also suggest that the in silico mapping data, even from a comparison genomic analysis based on the homogeneous comparison, are useful at some points, but the data were not always reliable, which requires further investigation using experimental methods.

Differential effect of whole-ear shading after heading on the physiology, biochemistry and yield index of stay-green and non-stay-green wheat genotypes

“…The source/sink relationship is a dynamic balance [ 5 ], and a better understanding of this relationship using different wheat genotypes would contribute to both the elucidation of yield formation mechanisms and systematic yield improvement. Some authors have suggested that wheat genotypes that differ in both the onset and the speed of leaf senescence are ideal for analyzing the source/sink relationship [ 6 – 8 ].…”

Expressed sequence tag-based prediction of putative genes responsive to drought tolerance in rice (Oryza sativa) using in silico approach

“…A total of 10,746 ESTs or cDNA of Oryza sativaas on date 5.4.2021 that have been expressed under drought conditions were downloaded from the EST database of NCBI (www.ncbi.nlm.nih.gov). Later, redundant ESTs, low complexity sequence, vector sequence, genomic repeats were masked by EGassembler (Guo et al, 2015,Masoudi-Nejad et al, 2006. The CAP3 programme was used to aggregate the processed EST sequences into clusters (Huang & Madan 1999).…”

In-silico prediction of novel genes responsive to drought and salinity stress tolerance in bread wheat (Triticum aestivum)

“…There were 6,717 ESTs of T. aestivum obtained from the EST database in NCBI (www.ncbi.nlm.nih.gov) containing all the entries from the GenBank database of the EST or cDNA categories that have been expressed in drought and saline conditions until now. The ESTs were masked to exclude sequence parts that could cause incorrect clustering [15] and then were masked for genomic repeats, vector sequence, low complexity sequence (including poly-A tails), and sequencing artifacts by EGassembler [22]. The processed EST sequences were grouped into clusters using the CAP3 program [23].…”

“…Sequencing projects for ESTs have been performed for various organisms, creating millions of short, single-pass nucleotide-sequence reads, and are available from EST databases. Inclusive computational strategies have been advanced to regulate and analyze EST data for gene discovery, transcription, and functional annotation for products of a putative gene [15]. Similar studies on EST sequences have been performed on wheat for biotic stress and on Brassica rapa [16].…”