Project Proposal: AIMS - Bioinformatic approach to aid gene identification and characterisation in Arabidopsis thaliana - Evaluate and integrate the accuracy of Arabidopsis database INTRODUCTION: Arabidopsis thaliana is a model plant for research and has been used wisely to study many aspects of plant biology. There is significant amount of information about this plant in the database, such as fully sequenced and annotated genomic sequence, extensive expressional data and functional characterisation data. This project aims at using such information to aid gene identification. The project will focus on a specific region (between AGIs 18,500,000 & 19,800,000) on Chromosome V, where a gene involved in root development has been mapped. OBJECTIVES: The project has three types of objectives they are: 1) To identify all possible genes in the region and most importantly to check whether there are genes mis- or incorrectly-annotated using sequence analyses 2) To establish the expression patterns and regulations of the genes using available microarray data. 3) And literature search of evidence for the functional properties of the genes of their homologues. The analyses will help to build an integrated picture which shows the genes in the region together with their expression profiles and functional properties. Such information can be used to guide our experimental strategy towards the identification of the interested gene and will provide a case-study for using bioinformatics approach to aid traditional genetic approach in gene identification. Biological Background of Arabidopsis thaliana Arabidopsis thaliana is a unique among plant model organisms due to its short life Cycle (Heh and Bülow 2008 ) and... ... middle of paper ... ...S. Kaul, et al. (1999). "Sequence and analysis of chromosome 2 of the plant Arabidopsis thaliana." Nature 402(6763): 761-768. Meinke, D. W., J. M. Cherry, et al. (1998). "Arabidopsis thaliana: A Model Plant for Genome Analysis." Science 282(5389): 662-682. Rhee, S. Y., W. Beavis, et al. (2003). "The Arabidopsis Information Resource (TAIR): a model organism database providing a centralized, curated gateway to Arabidopsis biology, research materials and community." Nucl. Acids Res. 31(1): 224-228. Sato, S., H. Kotani, et al. (1997). "Structural Analysis of Arabidopsis thaliana Chromosome 5. I. Sequence Features of the 1.6 Mb Regions Covered by Twenty Physically Assigned P1 Clones." DNA Res 4(3): 215-219. Tabata, S., T. Kaneko, et al. (2000). "Sequence and analysis of chromosome 5 of the plant Arabidopsis thaliana." Nature 408(6814): 823-826.
Abstract: This paper analyzes whether or not gene mapping in Sordaria fimicola is affected by changes in environmental conditions. The main focus is on how temperature affects the recombination frequency of this organism. It is analyzed if under different environmental conditions wt x gray and wt x tan varies in their percentage crossing over. It is investigated how factors such as temperature and ultraviolet light have affected the gene to centromere distance in Sordaria.
Evidence has shown that the corn we know today is quite different from the first time it was domesticated in Mexico. Although researchers and the academic world acknowledge that corn began its world journey in Mexico, they are unsure as to the time and location of the earliest domestication (American Society of Plant Biologist). Through genetics, teosinte is found to be corn’s wild ancestor. Although the two do not look much alike, at a DNA level they are surprisingly alike, such as having the same number of chromosomes and a remarkably similar arrangement of genes (The University of Utah).
As a result of these factors, the flora has adapted to these conditions in a variety of ways including their shape, leaf type, root system, and color. One of the most prominent adapt...
Proteogenomics is a kind of science field that includes proteomics and genomics. Proteomic consists of protein sequence information and genomic consists of genome sequence information. It is used to annotate whole genome and protein coding genes. Proteomic data provides genome analysis by showing genome annotation and using of peptides that is gained from expressed proteins and it can be used to correct coding regions.Identities of protein coding regions in terms of function and sequence is more important than nucleotide sequences because protein coding genes have more function in a cell than other nucleotide sequences. Genome annotation process includes all experimental and computational stages.These stages can be identification of a gene ,function and structure of a gene and coding region locations.To carry out these processes, ab initio gene prediction methods can be used to predict exon and splice sites. Annotation of protein coding genes is very time consuming process ,therefore gene prediction methods are used for genome annotations. Some web site programs provides these genome annotations such as NCBI and Ensembl. These tools shows sequenced genomes and gives more accurate gene annotations. However, these tools may not explain the presence of a protein. Main idea of proteogenomic methods is to identify peptides in samples by using these tools and also with the help of mass spectrometry.Mass spectrometry searches translation of genome sequences rather than protein database searching. This method also annotate protein protein interactions.MS/MS data searching against translation of genome can determine and identify peptide sequences.Thus genome data can be understood by using genomic and transcriptomic information with this proteogenomic methods and tools. Many of proteomic information can be achieved by gene prediction algorithms, cDNA sequences and comparative genomics. Large proteomic datasets can be gained by peptide mass spectrophotometry for proteogenomics because it uses proteomic data to annotate genome. If there is genome sequence data for an organism or closely related genomes are present,proteogenomic tools can be used. Gained proteogenomic data provides comparing of these data between many related species and shows homology relationships among many species proteins to make annotations with high accuracy.From these studies, proteogenomic data demonstrates frame shifts regions, gene start sites and exon and intron boundaries , alternative splicing sites and its detection , proteolytic sites that is found in proteins, prediction of genes and post translational modification sites for protein.
Genes underpin the molecular basis of phenotypic variation among individuals. By identifying the position underlying gene via gene mapping, it is possible to uncover the evolutionary principles which account for phenotypic variations. In this practical, we associated ten simple sequence length polymorphism (SSLP) markers with three phenotypes to identify any possible association between a marker and certain phenotype in Arabidopsis. Those three phenotypes were: did the plant show flowering, did cell death observe in the plant and finally the rosette diameter. The first two phenotypes were qualitative traits scored with yes or no answer whereas the later was a quantitative phenotype with a continuous distribution and measured in centimeter.
The discovery of new techniques, as well as developing extensive genetic and physical maps have been the primary goals of the project. A detailed genetic map will enable scienti...
Genomics is undergoing rapid development from the analysis, mapping and sequencing of genomes to development about genome function. [Hieter and Boguski, 1997] Genomics looks at the analysis of DNA sequences whilst functional genomics is used to understand the relation of genes and proteins. [Fields et al., 1999] The analysis of genomes has more recently been divided into two groups; functional and structural genomics. Structural genomics is the first phase of genome analysis, which produces an organisms’ genetic, transcript and physical maps. [Hieter and Boguski, 1997] The purpose of structural genomics is the allocation of three-dimensional structures to proteomes; which has given a new viewpoint on protein families and folds, and domain structures within gene sequences. [Teichmann et al., 1999]
All the chromosome pairs line up in the centre of the cell along spindle fibres that pull to either side of the cell.
...nt the overlapping of cell. Furthermore we used toluidine blue to stain the samples so that the chromosomes can be observed clearly and finally cover slip was used in the experiment to flatten the tip of the onion root for better viewing.
DNA barcoding requires it to be standard, scalable and minimal. Plants’ low rate of nucleotide substitution in the mitochondrial gene has been the source of major debate regarding a plant’s code for its identity. CO1 has been the standard gene used fo...
Muller, Patrick Y., et al. "Short technical report processing of gene expression data generated by quantitative Real-Time RT-PCR." Biotechniques 32.6 (2002a): 1372-1379.
Wheat has 21 pairs of homologous chromosomes and seven homoeologous chromosome group, which possess high level of similarity (Feldman et al. 2012). There are various genetic changes such as elimination of low or high copy DNA sequences, elimination of rRNA and 5S RNA genes and intergenomic invasion of DNA sequences occur at the time of allopolyploidization which vacillate the speciation process (Feldman et al. 2012; Feldman et al. 2012). The ph locus present on 5BL play an important role in the genetic interaction between genomes (Feldman et al. 2012). It lead to the formation of bivalent; due to this reason wheat chromosomes behave like diploids during meiosis (Feldman et al. 2012).
Bioinformatics is very update with the information about the gene structure and function. It can locate a gene within a sequence as well as predict the structure and or function of a particular gene. By applying bioinformatics to understand different biological processes, it allows a more global perspective in design, to test hypotheses about a gene or a protein and as well as allowing us the ability to take advantage of upcoming technology.
Campbell, N. A. & J. B. Reece, 8th eds. (2008). Biology. San Francisco: Pearson Benjamin Cummings.
J. Losos, K. Mason, S. Singer, based on the work of P. Raven, & G. Johnson, Biology, 8th ed., (McGraw-Hill Education (Asia), Singapore, 2008), pp. 994-995.