Next generation sequencing-data analysis for cellulose- and Xylan-degrading enzymes from POME metagenome = Analisis data-penjujukan generasi seterusnya bagi enzim selulosa dan xilan mendegradasi daripada metagenom POME

Metagenomic DNA library from palm oil mill effluent (POME) was constructed and subjected to high-throughput screening to find genes encoding cellulose- and xylan-degrading enzymes. DNA of 30 positive fosmid clones were sequenced with next generation sequencing technology and the raw data (short inse...

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Main Authors: Ben Belgacem, Farah Fadwa, Mat Isa, Mohd Nor, Abdelrahim, Muhammad Alfatih Muddathir, Tumian, Afidalina, Noorbatcha, Ibrahim Ali, Mohd. Salleh, Hamzah
Format: Article
Language:English
English
English
Published: Penerbit Universiti Kebangsaan Malaysia 2018
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Online Access:http://irep.iium.edu.my/69220/1/69220_Next%20Generation%20Sequencing-Data%20Analysis.pdf
http://irep.iium.edu.my/69220/13/69220%20Next%20Generation%20Sequencing-Data%20Analysis%20SCOPUS.pdf
http://irep.iium.edu.my/69220/7/69220%20Next%20Generation%20Sequencing-Data%20Analysis%20WOS%20%281%29.pdf
http://irep.iium.edu.my/69220/
http://www.ukm.my/jsm/pdf_files/SM-PDF-47-12-2018/03%20Farah%20Fadwa%20Benbelgacem.pdf
http://dx.doi.org/10.17576/jsm-2018-4712-03
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Institution: Universiti Islam Antarabangsa Malaysia
Language: English
English
English
id my.iium.irep.69220
record_format dspace
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
English
topic TP248.13 Biotechnology
spellingShingle TP248.13 Biotechnology
Ben Belgacem, Farah Fadwa
Mat Isa, Mohd Nor
Abdelrahim, Muhammad Alfatih Muddathir
Tumian, Afidalina
Noorbatcha, Ibrahim Ali
Mohd. Salleh, Hamzah
Next generation sequencing-data analysis for cellulose- and Xylan-degrading enzymes from POME metagenome = Analisis data-penjujukan generasi seterusnya bagi enzim selulosa dan xilan mendegradasi daripada metagenom POME
description Metagenomic DNA library from palm oil mill effluent (POME) was constructed and subjected to high-throughput screening to find genes encoding cellulose- and xylan-degrading enzymes. DNA of 30 positive fosmid clones were sequenced with next generation sequencing technology and the raw data (short insert-paired) was analyzed with bioinformatic tools. First, the quality of 64,821,599 reverse and forward sequences of 101 bp length raw data was tested using Fastqc and SOLEXA. Then, raw data filtering was carried out by trimming low quality values and short reads and the vector sequences were removed and again the output was checked and the trimming was repeated until a high quality read sets was obtained. The second step was the de novo assembly of sequences to reconstruct 2900 contigs following de Bruijn graph algorithm. Pre-assembled contigs were arranged in order, the distances between contigs were identified and oriented with SSPACE, where 2139 scaffolds have been reconstructed. 16,386 genes have been identified after gene prediction using Prodigal and putative ID assignment with Blastp vs NR protein. The acceptable strategy to handle metagenomic NGS-data in order to detect known and potentially unknown genes is presented and we showed the computational efficiency of de Bruijn graph algorithm of de novo assembly to 21 bioprospect genes encoding cellulose-degrading enzymes and 6 genes encoding xylan-degrading enzymes of 30.3% to 100% identity percentage. ********************************************************** Sebuah pangkalan data yang menyimpan DNA metagenom daripada efluen kilang minyak kelapa sawit telah dibina dan disaring dengan menggunakan kaedah penyaringan berskala besar untuk mencari enzim selulosa dan xilan. DNA daripada fosmid berklon positif telah disusun dengan menggunakan teknologi penjujukan berskala besar dan data mentah (dalam susunan pendek berpasangan) telah dianalisis dengan kaedah bioinformatik. Pertama, kualiti susunan 64,821,599 balikan dan ke depan sebanyak 101 bp panjang data mentah telah diuji menggunakan Fastqc dan SOLEXA. Kemudian, penyaringan data mentah dilakukan dengan memotong susunan yang berkualiti rendah dan pendek. Malah, vektor juga telah dikeluarkan dan susunan output telah diperiksa dan ditrim berulang kali sehingga set bacaan berkualiti tinggi diperoleh. Langkah kedua adalah himpunan de novo iaitu untuk menyusun semula 2900 contigs mengikut algoritma graf de Bruijn. Contigs awal sebelum himpunan telah diatur mengikut susunan, jarak antara contigs telah dikenal pasti berorientasikan SSPACE dengan 2139 perancah telah dibina. 16,386 gen telah dikenal pasti selepas kaedah peramalan gen menggunakan Prodigal dan penugasan ID putatif dengan Blastp vs protein NR. Strategi yang betul dalam mengendalikan data NGS-metagenom untuk mengesan gen-gen yang diketahui dan juga yang berpotensi tetapi masih belum diketahui telah ditunjukkan. Dalam kajian ini, kami menunjukkan kecekapan pengiraan komputer berdasarkan algoritma graf himpunan de Bruijn de novo kepada bioprospek 21 gen yang mengekodkan enzim selulosa dan 6 gen yang mengekod enzim xilan daripada 30.3% kepada 100% peratusan identiti yang serupa.
format Article
author Ben Belgacem, Farah Fadwa
Mat Isa, Mohd Nor
Abdelrahim, Muhammad Alfatih Muddathir
Tumian, Afidalina
Noorbatcha, Ibrahim Ali
Mohd. Salleh, Hamzah
author_facet Ben Belgacem, Farah Fadwa
Mat Isa, Mohd Nor
Abdelrahim, Muhammad Alfatih Muddathir
Tumian, Afidalina
Noorbatcha, Ibrahim Ali
Mohd. Salleh, Hamzah
author_sort Ben Belgacem, Farah Fadwa
title Next generation sequencing-data analysis for cellulose- and Xylan-degrading enzymes from POME metagenome = Analisis data-penjujukan generasi seterusnya bagi enzim selulosa dan xilan mendegradasi daripada metagenom POME
title_short Next generation sequencing-data analysis for cellulose- and Xylan-degrading enzymes from POME metagenome = Analisis data-penjujukan generasi seterusnya bagi enzim selulosa dan xilan mendegradasi daripada metagenom POME
title_full Next generation sequencing-data analysis for cellulose- and Xylan-degrading enzymes from POME metagenome = Analisis data-penjujukan generasi seterusnya bagi enzim selulosa dan xilan mendegradasi daripada metagenom POME
title_fullStr Next generation sequencing-data analysis for cellulose- and Xylan-degrading enzymes from POME metagenome = Analisis data-penjujukan generasi seterusnya bagi enzim selulosa dan xilan mendegradasi daripada metagenom POME
title_full_unstemmed Next generation sequencing-data analysis for cellulose- and Xylan-degrading enzymes from POME metagenome = Analisis data-penjujukan generasi seterusnya bagi enzim selulosa dan xilan mendegradasi daripada metagenom POME
title_sort next generation sequencing-data analysis for cellulose- and xylan-degrading enzymes from pome metagenome = analisis data-penjujukan generasi seterusnya bagi enzim selulosa dan xilan mendegradasi daripada metagenom pome
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2018
url http://irep.iium.edu.my/69220/1/69220_Next%20Generation%20Sequencing-Data%20Analysis.pdf
http://irep.iium.edu.my/69220/13/69220%20Next%20Generation%20Sequencing-Data%20Analysis%20SCOPUS.pdf
http://irep.iium.edu.my/69220/7/69220%20Next%20Generation%20Sequencing-Data%20Analysis%20WOS%20%281%29.pdf
http://irep.iium.edu.my/69220/
http://www.ukm.my/jsm/pdf_files/SM-PDF-47-12-2018/03%20Farah%20Fadwa%20Benbelgacem.pdf
http://dx.doi.org/10.17576/jsm-2018-4712-03
_version_ 1643619835166326784
spelling my.iium.irep.692202019-07-15T01:47:57Z http://irep.iium.edu.my/69220/ Next generation sequencing-data analysis for cellulose- and Xylan-degrading enzymes from POME metagenome = Analisis data-penjujukan generasi seterusnya bagi enzim selulosa dan xilan mendegradasi daripada metagenom POME Ben Belgacem, Farah Fadwa Mat Isa, Mohd Nor Abdelrahim, Muhammad Alfatih Muddathir Tumian, Afidalina Noorbatcha, Ibrahim Ali Mohd. Salleh, Hamzah TP248.13 Biotechnology Metagenomic DNA library from palm oil mill effluent (POME) was constructed and subjected to high-throughput screening to find genes encoding cellulose- and xylan-degrading enzymes. DNA of 30 positive fosmid clones were sequenced with next generation sequencing technology and the raw data (short insert-paired) was analyzed with bioinformatic tools. First, the quality of 64,821,599 reverse and forward sequences of 101 bp length raw data was tested using Fastqc and SOLEXA. Then, raw data filtering was carried out by trimming low quality values and short reads and the vector sequences were removed and again the output was checked and the trimming was repeated until a high quality read sets was obtained. The second step was the de novo assembly of sequences to reconstruct 2900 contigs following de Bruijn graph algorithm. Pre-assembled contigs were arranged in order, the distances between contigs were identified and oriented with SSPACE, where 2139 scaffolds have been reconstructed. 16,386 genes have been identified after gene prediction using Prodigal and putative ID assignment with Blastp vs NR protein. The acceptable strategy to handle metagenomic NGS-data in order to detect known and potentially unknown genes is presented and we showed the computational efficiency of de Bruijn graph algorithm of de novo assembly to 21 bioprospect genes encoding cellulose-degrading enzymes and 6 genes encoding xylan-degrading enzymes of 30.3% to 100% identity percentage. ********************************************************** Sebuah pangkalan data yang menyimpan DNA metagenom daripada efluen kilang minyak kelapa sawit telah dibina dan disaring dengan menggunakan kaedah penyaringan berskala besar untuk mencari enzim selulosa dan xilan. DNA daripada fosmid berklon positif telah disusun dengan menggunakan teknologi penjujukan berskala besar dan data mentah (dalam susunan pendek berpasangan) telah dianalisis dengan kaedah bioinformatik. Pertama, kualiti susunan 64,821,599 balikan dan ke depan sebanyak 101 bp panjang data mentah telah diuji menggunakan Fastqc dan SOLEXA. Kemudian, penyaringan data mentah dilakukan dengan memotong susunan yang berkualiti rendah dan pendek. Malah, vektor juga telah dikeluarkan dan susunan output telah diperiksa dan ditrim berulang kali sehingga set bacaan berkualiti tinggi diperoleh. Langkah kedua adalah himpunan de novo iaitu untuk menyusun semula 2900 contigs mengikut algoritma graf de Bruijn. Contigs awal sebelum himpunan telah diatur mengikut susunan, jarak antara contigs telah dikenal pasti berorientasikan SSPACE dengan 2139 perancah telah dibina. 16,386 gen telah dikenal pasti selepas kaedah peramalan gen menggunakan Prodigal dan penugasan ID putatif dengan Blastp vs protein NR. Strategi yang betul dalam mengendalikan data NGS-metagenom untuk mengesan gen-gen yang diketahui dan juga yang berpotensi tetapi masih belum diketahui telah ditunjukkan. Dalam kajian ini, kami menunjukkan kecekapan pengiraan komputer berdasarkan algoritma graf himpunan de Bruijn de novo kepada bioprospek 21 gen yang mengekodkan enzim selulosa dan 6 gen yang mengekod enzim xilan daripada 30.3% kepada 100% peratusan identiti yang serupa. Penerbit Universiti Kebangsaan Malaysia 2018 Article PeerReviewed application/pdf en http://irep.iium.edu.my/69220/1/69220_Next%20Generation%20Sequencing-Data%20Analysis.pdf application/pdf en http://irep.iium.edu.my/69220/13/69220%20Next%20Generation%20Sequencing-Data%20Analysis%20SCOPUS.pdf application/pdf en http://irep.iium.edu.my/69220/7/69220%20Next%20Generation%20Sequencing-Data%20Analysis%20WOS%20%281%29.pdf Ben Belgacem, Farah Fadwa and Mat Isa, Mohd Nor and Abdelrahim, Muhammad Alfatih Muddathir and Tumian, Afidalina and Noorbatcha, Ibrahim Ali and Mohd. Salleh, Hamzah (2018) Next generation sequencing-data analysis for cellulose- and Xylan-degrading enzymes from POME metagenome = Analisis data-penjujukan generasi seterusnya bagi enzim selulosa dan xilan mendegradasi daripada metagenom POME. Sains Malaysiana, 42 (12). pp. 2951-2960. ISSN 0126-6039 http://www.ukm.my/jsm/pdf_files/SM-PDF-47-12-2018/03%20Farah%20Fadwa%20Benbelgacem.pdf http://dx.doi.org/10.17576/jsm-2018-4712-03