Exploring the effects of assembly strategies on differential gene expression – A case study in a non-model crustacean species, the wild black tiger prawn (Penaeus monodon)

Author:

Nguyen Minh Thanh1,Tran Minh Nhut1,Le Thi Hong Tham1,Vo Thi Bao Chau1,Nguyen Hoang Khue Tu1,Tran Thi Hai Yen1,Nguyen Thanh Luan2,Elizur Abigail3,Ventura Tomer3,Nguyen Tuan Viet4,Vo Thu Thi Minh1

Affiliation:

1. International University, Vietnam National University HCM

2. Research Institute for Aquaculture No2

3. Centre for BioInnovation, University of the Sunshine Coast

4. Agriculture Victoria, AgriBio, Centre for AgriBiosciences

Abstract

Abstract

The Penaeus monodon genome became a subject for extended studies of several aspects of nutrition, growth, and reproduction. In this study, transcriptome from the hepatopancreas and ovary of wild-caught female broodstocks were generated by genome-guided (GG) and de novo (DN) assembly. We compared the effectiveness of these methods in terms of the number of transcripts and their annotations. We analyzed mapping features and differentially expressed genes (DEGs) using three estimation approaches: mapping reads against (i) a genome assembly of P. monodon (reference-based (RB)), transcriptome generated by (ii) GG, and (iii) DN assembly. DN had the highest percentage of mapping rates and annotated aligned reads, leading to 2.09 times more unigenes than GG assembly, with 49% of unigenes matching the blast search, compared to 39.66%. Furthermore, 69% of blasted unigenes from DN assembly were assigned GO terms in DN assembly, compared to 23.9% in GG. Additionally, DEGs identified of the two tissues by DN approach (820) surpassed the total number of DEGs identified by GG (488) and RB (117) approaches. In contrast, the GG approach identified the highest number of DEGs from our genes of interest (93.5%), followed by the DN (82.6%) and the RB (37.3%) approach. The DN assembly is ideal for transcript reconstruction and DEGs recovery, while the GG assembly generated an appropriate database for studying specific genes or sets of genes. We, therefore, recommend using a combination of DN and GG assemblies to improve differential gene expression analysis for non-model organisms with poorly resolved genome annotations.

Publisher

Springer Science and Business Media LLC

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