Biology Reference
In-Depth Information
1
Introduction
To over half the world's population, rice is life. In 2011, rice was
harvested from approximately 160 million hectares of land with
over 460 million tons of milled rice produced and over 456 million
tons consumed, according to the United States Department of
Agriculture (as reported by IRRI at
http://ricestat.irri.org
,
accessed 27 April 2012). Prices for rice have risen to record highs
due to global demand in recent years, with rice constituting 19 %
of caloric intake worldwide [
1
]. In addition to its nutritional and
economic importance, rice has become an attractive model system
for cereal genomic research because of its relatively small genome
(~43 Mb), a high degree of genomic synteny with other cereal
crop plants, availability of tens of thousands of searchable insertion
lines (e.g., T-DNA, Tos17, Ds), compatibility with genetic trans-
formation, and availability of a sequenced genome that contains
approximately 32,000 genes [
2
]. However, at the time of sequenc-
ing, it was estimated that one-third of rice proteins had no known
function [
3
]. One of the major challenges in rice research is to fully
annotate the genome with a functional description for each protein
to provide a better understanding of rice traits.
Proteomics involves the study of proteins encoded by the
genome in a cell, tissue, or organism at a given time or under a
particular set of environmental conditions. The study of pro-
teomics is substantially more complex than genomics; the pro-
teome is dynamic and varies with environmental stresses or cellular
cues and, furthermore, proteins can be altered by numerous cel-
lular processes such as posttranslational modifi cations, splicing,
degradation, and proteolysis. Traditionally, proteomics has been
performed using a two-dimensional electrophoresis (2-DE) gel
approach, but with the development of techniques such as multidi-
mensional protein identifi cation technology (MudPIT) [
4
-
7
],
proteomics has seen rapid growth in shotgun techniques. This shift
has been encouraged by changes in mass spectrometry (MS) instru-
mentation, and driven by the need to analyze many more proteins
at a time. Shotgun proteomics is based on the identifi cation of
proteins from a complex mixture after separation in at least two
dimensions, at either the protein or the peptide level, prior to anal-
ysis by tandem MS (MS/MS).
Rice proteomics research has progressed rapidly over the past
decade. Increasing proteome coverage and improving genome
annotation continue to be a major concern [
8
,
9
], and identifi ca-
tion of posttranslational modifi cations has emerged as an area of
intense research [
10
]. Cataloguing rice proteins is a necessary task;
however, the fi eld of proteomics has moved beyond simple protein
identifi cation and is now driven to accurately and reliably quantify
the differences in protein abundance [
11
-
13
]. Plant proteomics
research has followed this trend accordingly; quantitation of
