Bioinformatics Analysis Report

Running Header; Bioinformatics Analysis Report
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BIOCHEMISTRY REPORT

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Table of Contents
Abstract.................................................................................................................................................2
Introduction...........................................................................................................................................3
Methods.................................................................................................................................................3
Results...................................................................................................................................................5
Discussion.............................................................................................................................................9
References...........................................................................................................................................13

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Abstract
The bioinformatics tools serve as a compendium of data from different sources and literature.
The software work on distinct algorithms to carry out prediction based searches. This report
utilises the information of two transcribed sequences from four different online tools. The
sequence identification was carried out from NCBI BLAST. The sequence features and
protein summary was performed with the assistance of ENSEMBL and GENE CARDS. The
long non-coding RNA information was fetched from LNCRNADB. The two transcribed
sequences were identified as RACK1 mRNA (coding) and MALAT1 (lncRNA). They
showed 100% sequence identity from NCBI blast. Other relevant information was collected
from the rest of the mentioned tools. RACK1, being the regulatory component of 40S subunit
of ribosome, is extensively studied. On the contrary, MALAT1, although a very abundant
lncRNA in most of the tissues, has less information relative to RACK1. Long non-coding
RNAs are relatively less studied than their protein-coding counterparts, as they have been
recently discovered.

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Introduction
The human genome project and the ENCODE consortium opened the avenues to
explore the field of genomics, for the better understanding of the function of genes. The big
data generated by next generation sequencing is simplified and analysed using
bioinformatics. The variety of software tools run on different algorithms and are used to
understand the biological data. The bioinformatics is based on collecting the statistics from
the available literature, followed by computational modelling and solving the biological
problem using computational algorithms (Can, 2014). A plethora of novel transcripts, both
coding and non-coding, identified by next-generation sequencing are studied using
bioinformatics tools and based on the hypothetical predictions, they are functionally validated
in the lab.
The present study consists of an extensive research on two given transcribed
sequences using bioinformatics tools. The software’s used in this report are NCBI BLAST,
ENSEMBL, GENE CARDS and LNCRNADB. The two sequences are identified and
characterised as coding and non-coding. Sequence features are explored such as genomic
origin, transcript features such as CDS, UTRs, regulatory regions, translated sequence,
protein domains, interaction with other biomolecules and their relevant role in the cell.
Methods
We took two transcribed sequences as given in the assignment. The sequences were identified
and other features were found using the following methods.
1. Sequence Identification using NCBI BLAST: Basic Local Alignment Search Tool
is used to find similarity between sequences. It is an algorithm essential for
comparing biological sequences of amino acids and nucleotides of DNA. A BLAST
search enables comparison of sequence in the database and indentifies the sequences
which is similar to the sequence in the threshold set. It is used for DNA and proteins.
The given sequence is pasted in the BLAST search tool, BLAST is performed for
DNA and BLAST is for proteins. Upon submitting the query, the tool finds similar
sequences from the database to the submitted query sequence and calculates the
statistics of sequence homology. It provides links to matched sequence, which fetches