De Novo Transcriptomic Characterization Enables Novel Microsatellite Identification and Marker Development in Betta splendens.
Huapu ChenXiaomeng LiYaorong WangChunhua ZhuHai HuangWei YangGuang-Li LiPublished in: Life (Basel, Switzerland) (2021)
The wild populations of the commercially valuable ornamental fish species, Betta splendens, and its germplasm resources have long been threatened by habitat degradation and contamination with artificially bred fish. Because of the lack of effective marker resources, population genetics research projects are severely hampered. To generate genetic data for developing polymorphic simple sequence repeat (SSR) markers and identifying functional genes, transcriptomic analysis was performed. Illumina paired-end sequencing yielded 105,505,486 clean reads, which were then de novo assembled into 69,836 unigenes. Of these, 35,751 were annotated in the non-redundant, EuKaryotic Orthologous Group, Swiss-Prot, Kyoto Encyclopedia of Genes and Genomes and Gene Ontology databases. A total of 12,751 SSR loci were identified from the transcripts and 7970 primer pairs were designed. One hundred primer pairs were randomly selected for PCR validation and 53 successfully generated target amplification products. Further validation demonstrated that 36% (n = 19) of the 53 amplified loci were polymorphic. These data could not only enrich the genetic information for the identification of functional genes but also effectively facilitate the development of SSR markers. Such knowledge would accelerate further studies on the genetic variation and evolution, comparative genomics, linkage mapping and molecular breeding in B. splendens.
Keyphrases
- genome wide
- genetic diversity
- dna methylation
- bioinformatics analysis
- copy number
- single cell
- big data
- electronic health record
- climate change
- healthcare
- genome wide identification
- risk assessment
- high resolution
- quality improvement
- health risk
- rna seq
- single molecule
- machine learning
- drinking water
- human immunodeficiency virus
- mass spectrometry
- transcription factor
- heavy metals
- high throughput sequencing
- nucleic acid