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Transcriptome analysis and annotation: SNPs identified from single copy annotated unigenes of three polyploid blueberry crops.

Yunsheng WangMuhammad Qasim ShahidFozia GhouriSezai ErcişliFaheem Shehzad BalochFei Nie
Published in: PloS one (2019)
Blueberry is a kind of new rising popular perennial fruit with high healthful quality. It is of utmost importance to develop new blueberry varieties for different climatic zones to satisfy the demand of people in the world. Molecular marker assisted breeding is believed to be an ideal method for the development of new blueberry varieties for its shorter breeding cycle than the conventional breeding. Simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs) markers are widely used molecular tools for marker assisted breeding, which could be detected at large scale by the transcriptome sequencing. Here, we sequenced the leaves transcriptome of 19 rabbiteye (Vaccinium ashei Reade), 13 southern highbush (Vaccinium. corymbosum L × native southern Vaccinium Spp) and 22 cultivars of northern highbush blueberry (Vaccinium corymbosum L) by using next generation sequencing technologies. A total of 80.825 Gb clean data with an average of about 12.525 million reads per cultivar were obtained. We assembled 58,968, 55,973 and 53,887 unigenes by using the clean data from rabbiteye, southern highbush and northern highbush blueberry cultivars, respectively. Among these unigenes, 3599, 3495 and 3513 unigenes were detected as candidate resistance genes in three blueberry crops. Moreover, we identified more than 8756, 9020, and 9198 SSR markers from these unigenes, and 7665, 4861, 13,063 SNPs from the annotated single copy unigenes, respectively. The results will be helpful for the molecular genetics and association analysis of blueberry and the basic molecular information of pest and disease resistance of blueberry, and would also offer huge number of molecular tools for the marker assisted breeding to produce blueberry cultivars with different adaptive characteristics.
Keyphrases
  • genome wide
  • single cell
  • rna seq
  • gene expression
  • single molecule
  • healthcare
  • dna methylation
  • transcription factor
  • genome wide association
  • deep learning
  • social media