Determinación de los procesos

Much of the work in this dissertation is explained and tested with the microarray data produced by scientists at Warwick Horticulture Research group at the Uni- versity of Warwick, UK. The experiment was performed to study the process of senescence in leaves of Arabidopsis thaliana over a period of time.

Arabidopsis thaliana (also known as thale cress, mouse-ear cress or Arabidop- sis) is a small garden weed type flowering plant. Although not an economically important plant, Arabidopsis has become popular as a model organism in plant biology due to its genome being one of the smallest among other plant genomes. It was also the first plant genome to be sequenced. Arabidopsis has several traits that make it a useful model for understanding the genetic, cellular, and molecular biology of flowering plants. Arabidopsis has a short life cycle of about 8-10 weeks

and it can grow about 50 cm in height in as little as 1cm3 of soil. The small

size and the rapid life cycle of the plant are advantageous for research. It can be grown in a small space and it produces many seeds. Each of these traits leads to Arabidopsis being a model plant organism for plant biologists.

The primary goal of the project undertaking the biological experiment ex- plained in the following sections was to understand the senescence process in leaves of Arabidopsis. Senescence is a term for the collective process that leads to the ageing and death of a plant or a plant part, like a leaf. In the case of animals, ageing and senescence are used interchangeably, but, in case of plants,

Figure 1.4: Arabidopsis plant.

senescence is well differentiated from ageing which is a passive time-dependent degenerative process. Senescence in a plant, on the other hand, is an internally regulated developmental process based on an adoptive mechanism, and the death is its consequence. The basic molecular mechanism of senescence both in plant and animal systems may be the same. Senescence can take place due to natural reasons, or due to environmental stress factors. The process involves expression of specific genes. As for example, plants undergo the process of leaf senescence to prepare for winter and recycle some of the valuable and scarce mineral nutrients. Leaf senescence is also a mechanism to get rid of old and photosynthetically less efficient leaves in the evergreen plants.

In Arabidopsis, leaf senescence is a programmed cell event responding to wide range of external and internal signals. The leaf senescence in Arabidopsis is con- trolled by age in a predictable manner. Each individual leaf has a similar lifespan

and therefore, leaves that develop later in life, will senesce later. In addition to age, plant hormones and environmental conditions can modulate the progression of leaf senescence [Sma94, Pes05]. The process, however, is not only concerned with death alone, but involves several events associated with massive mobiliza- tion of nutrients in a highly ordered and regulated manner from senescing leaves to new leaves, seeds and buds, thus contributing to the nutrient cycling. Many different genes show enhanced expressions during senescence process, and can help elucidate the underlying signalling pathways. Identification of the key genes and pathways can result in understanding the mechanisms that occur during the senescence process. Although, the leaf senescence alone can not explain the senes- cence process in the whole plant, but can provide vital clues for understanding senescence as a whole process.

1.6.1 Material Processing and Data Collection

The experiment was performed over 40 days with the following steps involved in the material processing and data collection stage.

ˆ Plant growth and leaf material acquisition: Arabidopsis plants (Columbia seed type also known as COL-0) were grown in a controlled environment at 20o_{C temperature , 70% relative humidity and 250µ mol m}−2_s−1 _light

intensity. The plants were subjected to long days with 16 hours of sunlight. The seventh leaf (leaf 7) on its emergence during the development of each plant was tagged with a cotton around it. Figure 1.5 (a) shows a cotton tagged leaf. The cotton tags would act as identifiers later in the experi- ment. Four such leaves were selected for harvesting purposes. After 19 days from sowing, when the leaf 7 was fully developed, it indicated the beginning of the time course. The biological replicates were harvested both in morning and evening (7h and 14h into light period) on every other day for next 22

days. Figure 1.5(b) shows the plant growth on day 1,15 and 19 since the data collection started. Figure 1.6 shows the development of leaf 7 from fully developed until fully senescent. This resulted in total 22 time point samples for each leaf.

(a) (b)

Figure 1.5:(a) Cotton tag around leaf 7 (b) The plant images on day 1, 15 and 19 since the data collection started. Leaf 7 is marked with an arrow.

Figure 1.6: Profiles of a leaf over 22 days during the senescence. The left most (first) profile shows a fully developed leaf and the profile was taken 19 days after sowing the plant.

ˆ RNA isolation and probe preparation: RNA was isolated from 4 individual leaves as separate biological replicates using the Triazol method (Invitrogen) followed by RNeasy column purification (Qiagen). RNA was amplified using a MessageAmp II (Ambion) and then labelled with Cy3 or Cy5 using reverse transcriptase (SuperScript II, Invitrogen). Each amplified RNA sample was labelled twice with Cy3 and twice with Cy5 giving 4 technical replicates for each leaf sample. Two Cy3 and Cy5 labelled samples (in 25% formamide,

5x SSC, 0.1% SDS and 0.5 mg ml−1 _{yeast tRNA) were mixed in different}

ˆ Hybridization: The microarrays used for analysis of the samples were Com- plete Arabidopsis Transcriptome Micro Arrays (CATMA). Each array con- tains 30,336 gene probes belonging to the genome of Arabidopsis. These arrays are produced by Warwick HRI using a sterile spotting machine. The

description of the machine and the array can be found in [LKB+_{07]. These}

arrays were hybridized with labelled samples at 42oC overnight. Slides were washed and then scanned using an Affymetrix 428 array scanner at 532nm (Cy3) and 635nm (Cy5).

1.6.2 Information Processing Array Scan Images Image Quantification Matrices Gene Expression Data Matrix Time Gene

Figure 1.7:Scanned images are read using Imagene to produce text files with details of signal intensity and other statistics for each gene in the image file. The text files are read to produce quantization matrices after adjusting the gene intensity. The quantization matrices are further combined using normalization method to produce the final gene expression matrix for further data analysis.

was performed using Imagene version 7 software (BioDiscovery, http://www.

biodiscovery.com/). Figure 1.7 presents a schematic diagram of obtaining a

final gene expression matrix from scanned image files. We have one scanned dig- ital image file (.tiff format) for each replicate at each time-point. The image files were read using the Imagene software to produce text files with signal intensity values for the genes, along with other statistics like background mean, median etc. The quantified values for all the replicates were further adjusted and combined to produce a final gene expression matrix. The process to produce the gene expres-

sion matrix from quantification matrices is called normalization. The expression

values in the final gene expression matrix will be used for the remaining stages in the information processing pipeline. The normalization step to produce the final gene expression matrix along with the other steps in the information processing stage are explained in greater details in later chapters.