Phylogeny Of Penaeid Shrimps And Population Genetic Structure Of The Green Tiger Prawn (Penaeus Semisulcatus) In Malaysian Waters
This study reports on the phylogeny of selected penaieds and population genetics of the commercially important Green Tiger Prawn (Penaeus semisulcatus) in the Malaysian waters. In the first part of this study, morphological shape variations among 12 species of family Penaeidae, mainly from northwest...
Saved in:
| 主要作者: | |
|---|---|
| 格式: | Thesis |
| 語言: | English |
| 出版: |
2019
|
| 主題: | |
| 在線閱讀: | http://eprints.usm.my/46631/1/Thesis-Post%20Viva24.pdf |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 總結: | This study reports on the phylogeny of selected penaieds and population genetics of the commercially important Green Tiger Prawn (Penaeus semisulcatus) in the Malaysian waters. In the first part of this study, morphological shape variations among 12 species of family Penaeidae, mainly from northwest coast of Peninsular Malaysia were investigated. This was achieved based on the Geometric Morphometrics (GM) of 18 homologous landmarks, analysed with Principal Component Analysis (PCA) and Canonical Variate Analysis (CVA) in Morpho J software. The shape variations was attributed to body shape, carapace head and telson tail among individuals. The first four components accounted for 76.24% and 78.47% for PCA and CVA, respectively. There is a tendency for closely related species to cluster together, although not absolutely consistent. To assess the phylogenetic signal, the morphometric data was mapped onto three phylogenetic trees (Neighbour Joining -NJ, Maximum Likelihood- ML and Bayesian Inference- BI) generated from the partial mitochondrial Cytochrome oxidase Subunit 1 (COI) on the same 12 species. Results revealed non significance (no phylogenetic signal) for NJ but significant phylogenetic signal (evolutionary significance) for ML and BI which suggest shape difference among all 12 penaeid prawn species was related to their evolutionary history. This discrepancy could be explained due to NJ tree are prone to errors when dealing with deeper divergence times, whereas ML and BI tree are ideal for phylogeny tree reconstruction which apply a model of sequence evolution on the data. |
|---|