Volume 14, Issue 39 (5-2023)
rap 2023, 14(39): 131-138 |
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Elyasi Zarringhabaie1 G, Sadeghi M, Miraie Ashtiani S R. (2023). Comparison of some Alignment Software in the Analysis of Dairy Cows RNA-Seq Data. rap. 14(39), 131-138. doi:10.61186/rap.14.39.131
URL: http://rap.sanru.ac.ir/article-1-1323-en.html
URL: http://rap.sanru.ac.ir/article-1-1323-en.html
Department of Animal Science, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
Abstract: (786 Views)
Extended Abstract
Introduction and Objective: Due to the increasing use of next generation sequencing (NGS), it is necessary to use specialized algorithms and software to perform statistical analysis in order to identify functional genes. Alignment of reads with the reference genome is the first and most important step in most RNA-Seq data analysis programs, and the accuracy of downstream analyzes effectively depends on this step. Therefore, the aim of this research was to compare some different software for aligning the data obtained from total RNA sequencing on the reference genome.
Material and Methods: RNA-Seq data related to 54 Holstein dairy cows raised in industrial conditions were used to identify genes effective in fertility. The quality of the reads was determined by FastQC software and editing of low quality sequences was done using Trimmomatic software. The edited data were aligned with bovine reference genome using Bowtie2, Tophat2 and Hisat2 softwares. The total percentage of mapped reads, the percentage of mapped reads on one location in the reference genome, and the percentage of mapped reads on more than one location were calculated.
Results: The results showed that the most alignment was done on the cow reference genome using Tophat2 software. which mapped 94.197% of the From the total available reads, 94.197% and 92.526% were mapped on the reference genome by Tophat2 and Hisat2 software, respectively. The Hisat2 software had more allocation function and mapped 89.202% of the data to a specific position, while this parameter was 87.812% of the total sequences for Tophat2 software. From the total used sequences, only 3.324% and 6.385% of the sequences were aligned by Hisat2 and Tophat2 software respectively to more than one position of the reference genome. Bowtie2 software had low performance compared to other two software.
Conclusion: The comparison of RNA-Seq data alignment software on the reference genome showed that although the Hisat2 swas the best read mapping software but, Tophat2 software can also be used instead in RNA-seq data analysis. Meanwhile, Bowtie2 software is not very effective in relation to RNA-Seq data.
Introduction and Objective: Due to the increasing use of next generation sequencing (NGS), it is necessary to use specialized algorithms and software to perform statistical analysis in order to identify functional genes. Alignment of reads with the reference genome is the first and most important step in most RNA-Seq data analysis programs, and the accuracy of downstream analyzes effectively depends on this step. Therefore, the aim of this research was to compare some different software for aligning the data obtained from total RNA sequencing on the reference genome.
Material and Methods: RNA-Seq data related to 54 Holstein dairy cows raised in industrial conditions were used to identify genes effective in fertility. The quality of the reads was determined by FastQC software and editing of low quality sequences was done using Trimmomatic software. The edited data were aligned with bovine reference genome using Bowtie2, Tophat2 and Hisat2 softwares. The total percentage of mapped reads, the percentage of mapped reads on one location in the reference genome, and the percentage of mapped reads on more than one location were calculated.
Results: The results showed that the most alignment was done on the cow reference genome using Tophat2 software. which mapped 94.197% of the From the total available reads, 94.197% and 92.526% were mapped on the reference genome by Tophat2 and Hisat2 software, respectively. The Hisat2 software had more allocation function and mapped 89.202% of the data to a specific position, while this parameter was 87.812% of the total sequences for Tophat2 software. From the total used sequences, only 3.324% and 6.385% of the sequences were aligned by Hisat2 and Tophat2 software respectively to more than one position of the reference genome. Bowtie2 software had low performance compared to other two software.
Conclusion: The comparison of RNA-Seq data alignment software on the reference genome showed that although the Hisat2 swas the best read mapping software but, Tophat2 software can also be used instead in RNA-seq data analysis. Meanwhile, Bowtie2 software is not very effective in relation to RNA-Seq data.
Type of Study: Research |
Subject:
ژنتیک و اصلاح نژاد دام
Received: 2022/09/12 | Revised: 2023/05/30 | Accepted: 2022/12/18 | Published: 2023/05/30
Received: 2022/09/12 | Revised: 2023/05/30 | Accepted: 2022/12/18 | Published: 2023/05/30
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