TITLE: Survey of Misannotations and Pseudogenes in the Rice Genome
Author: Tanmay Prakash, Novi High School
Mentor: Kousuke Hanada and Shin-Han Shiu, Department of Plant Biology, Michigan
State University
Abstract
There are occasions where there are misannotations that sometimes are due to the
existence of pseudogenes. This makes it difficult to conduct accurate research with this
data. In the preliminary research, misannotations in the introns of Arabidopsis thaliana
(Arabidopsis Genome Initiative, 2000) have been assessed using the protein kinase
domains. The protein kinase family was chosen for pilot study because of its large size
with more than 1000 genes in Arabidopsis thaliana and thus large potential for finding
misannotations. No misannotations or pseudogenes were found. However, sequence with
significant similarities (BLAST E value < 1e-5) were found in the introns of 5
Arabidopsis genes. This is most likely due to the extensive analysis done on the
Arabidopsis Genome. I plan to identify the misannotations and those that are
pseudogenes in the rice introns. Doing this will improve the quality of the rice genome
annotations and thus the research done that utilizes the rice genome. It also provides
more pseudogenes to study such things as neutral selection.
Introduction
Pseudogenes are DNA sequences that no longer function but resemble the
functional genes they once were (Torrents et al., 2003). There are two types of
pseudogenes, processed and non-processed. Processed pseudogenes are formed by
retrotransposition and comprise most of the pseudogenes in mammals. Non-processed
pseudogenes are products of duplication of the entirety of portion of a segment of genes
followed by mutations. Because polyploidiszation (the process of having more one sets
of chromosomes) is common in plants, the majority of pseudogenes in plants are nonprocessed (Blanc and Wolfe, 2004).
Pseudogenes are mainly identified by the existence of premature stop codons or
frameshift (Zhang et al., 2004). They can also be identified by their lack of selective
pressure. In functional genes selective pressure results in mostly synonymous
substitutions (mutation in a codon that produces the same amino acid) (Torrents et al.,
2003). In pseudogenes, however, there is no selective pressure so substitutions can be
synonymous or nonsynonymous (mutations result in different amino acids). Based on
these properties, the rates of nonsynonymous (KA) and synonymous (KS) substitutions
can be used as a measure of selection pressure. Functional genes normally have KA/KS
values that are significantly less than one, a property that can be used to distinguish
functional and pseudogenes.
The annotation of a gene is the process of assigning its introns, exons, and untranslated regions. One common type of misannotation is labeling a pseudogene as
functional gene due to mis-assignment of introns, which is problematic because the
misannotated genes produce erroneous results if used for research. The proposed studies
focus on the pseudogenes that are misannotated introns (Figure 1, next page). If part of a
protein domain (folds of a protein that play a certain role and can appear in many
Figure 1 Possible Sequence Similarities
exon
intron
exon
exon
intron
domain
domain
Case 1
Case 2
exon
intron
exon
exon
domain
Case 3
exon
intron
exon
exon
intron
domain
domain
Case 4
Case 5
exon
different proteins) is found in the exons but not in the intron between the exons then for
the intron is likely correctly annotated (Figure1, Case 1). However, if an intron does
contains part of a protein domain and the flanking exons contain parts of the same
domain (Figure 1, Case 2), this intron is likely misannotated. If any stop codons are
found in the introns, the misannotation is a potential pseudogene. These criteria together
with an examination of signature of purifying selection will be used to accomplish the
objectives of my research.
Objectives
1. Identify any misannotated regions in rice introns. We plan to do identify the
misannotations in the rice introns by checking for sequence similarity to any
domains in the introns and then in the genes exons. If the sequence similarity to a
domain is found in the intron, then this region is a possible misannotation and
could be a pseudogene. By accomplishing this, we will have a more accurate
understanding of the genes analyzed. Also, working with misannotated sequences
could be disastrous for other research.
2. Check if the misannotated regions represent pseudogenes. We do this because
pseudogenes can hold a wealth of information, such as how neutral selection
works. In addition, locating pseudogenes can make future annotation easier and
present annotation more accurate. The pseudogenes will be found using the two
methods (a) premature stop codons, or frameshift mutations in the misannotated
genes and (b) signature of negative selection (KA/KS).
By using two independent methods to identify pseudogenes, a greater level of accuracy
can be achieved. I have carried out a pilot study on the protein kinase domain to
determine the feasibility of my planned approach with the exception of (2b). The results
are presented in the next section.
Preliminary Results
There are more than 8296 protein domains (Robert D. et al., 2006). The first
domain sequence checked was that of protein kinase. This is a family of over 1000 genes
in Arabidopsis (Arabidopsis Genome Initiative, 2000), which made it more likely to be
misannotated and a good test of the process that is to be used. The procedures followed
for the preliminary research are outlined in Figure 2
Figure 2 Automated Pipeline
Query
Rice Protein
Domain
Blastall
BLAST
search
Matching
genes
Subject
Database of
Rice Genome
Introns
Exons from
Matching
Genes
Formatdb
Exons formatted
into a database
Query
Rice Protein
Domain
Subject
Blastall
BLAST
search
Check KA/KS value
Possible Pseudogenes
Check for Stop
Codons and
Frameshift
Mutations
Possibly
Misannotated
Genes
To find the misannotated introns containing kinase domain sequences, I first
conducted searches to see if there was any sequence similarity to the protein kinase
domain in Arabidopsis thaliana introns with BLAST (Basic Local Alignment Search
Tool, Expected value < 1e-5, Altschul et al). For genes with intron matching kinase
domains, the exon flanking introns were then checked for sequence similarity to the
protein kinase domain with BLAST (E value < 1e-5). The results of the BLAST search
with the protein kinase domain and exons were also evaluated with a HMMER, a
program that searches for protein homology in amino acid sequences utilizing Hidden
Markov models, (Wistrand, Sonnhammer, 2005) search to get a better assessment on
whether there truly is a sequence similarity. There are five expected outcomes as shown
in Figure 1.
Among about 25,000 Arabidopsis genes, almost all belong to Case 1 with correct
annotations (Arabidopsis Genome Initiative, 2000). The AT3G45390.1 and
AT4G25390.2
89-348 (39 sequence similarities
in this region)
KPRO_MAIZE/534-812
141-461
KPRO_MAIZE/534-812
105-249
(one of the 39
similarities)
AT3G01830.2
KPRO_MAIZE/534-812
CDC15_YEAST/25-272
CDC5_YEAST/82-337
MOS_CERAE/60-338
MIL_AVIMH/82-339
M3K9_HUMAN/144-403
MKK1_YEAST/221-488
PHKG2_RAT/24-291
KPK2_PLAFK/111-364
STE7_YEAST/191-466
KIN1_SCHPO/125-395
MK04_HUMAN/20-312
KGP1_DROME/457-717
1040-276
1040-498
920-498
1040-498
758-498
1040-498
1040-498
1013-498
869-498
926-498
869-498
722-345
869-498
AT3G45390.1
KPRO_MAIZE/534-812
357-536
KPRO_MAIZE/534-812
2-229
BUR1_YEAST/60-366
351-411
AT1G24040.2
KPRO_MAIZE/534-812
1421-1221
AT1G24040.1
KPRO_MAIZE/534-812
1421-1221
Region of
Sequence
Similarity
Figure 3 Gene with sequence similarity to
the protein kinase domain in the introns
5’UTR
3’UTR
Coding Region
Intron
AT4G25390.2 genes resembled Case 4 and Case 5 of Figure 1 respectively with respect
to the protein kinase domain. The AT3G01830.2, AT1G24040.2, and AT1G24040.1
genes all resembled Case 3 of Figure 1 with respect to the protein kinase domain.
None of the five genes whose introns had sequence similarities to the protein
kinase domains had sequence similarities located as in Case 2 of Figure 1, so I didn’t find
any misannotations or pseudogenes. There are a substantial number of full-length cDNA
and ESTs for Arabidopsis thaliana and these sequences have been used to improve its
annotation significantly (Yamada et al., 2003 Science). Therefore, this is likely the reason
why I did not find any mis-annotated kinases.
Research Plan
The objectives of this project are to (1) find any misannotated regions in the introns of the
rice genome and (2) to check if the misannotated regions represent pseudogenes. Finding
any misannotated regions provides more accurate data for use by other researchers and
provides candidates for pseudogenes. Finding pseudogenes can help with future
annotations and can be used to study things like neutral selection. These objectives will
be completed by the following methods.
1. Find any misannotated regions in rice introns.
This is done using an automated pipeline I am developing (Figure 2) in UNIX that first
searches a domain against a database of what introns using BLAST (HMMER as well).
The genes whose introns match the domain have their exons put into a new database.
The domain is then searched against this database using HMMER. The queries and
databases for each next step will be extracted from the previous search results using
computer programs written in Perl using methods such as regular expression matching.
The necessary programs shall be run on the Calculon computer system in the Plant
Biology Department of Michigan State University. If an intron and its flanking exons
have matches to the same domain, an argument for a misannotation can be made. This
can also be analyzed for a possible pseudogene. If matches to the domain are found in
introns and non-flanking exons, or if a match to the domain is found in the intron but to a
different domain in the exons, the result will be further analyzed at a later time. This
processes will be repeated for 8296 domains from the Pfam database (Robert D. et al.,
2006).
2. Check if the misannotated regions represent pseudogenes
A computer will check the genes for premature stop codons, frameshift mutations and
signatures of negative selection using programs written in Perl in the introns that have
sequence similarity to a protein domain. The computer will look for “taa”, “tag” or “tga”
in a nucleotide sequence and an asterisk in an amino acid sequence to find the premature
stop codon in the introns that have sequence similarity to a protein domain.
The
frameshifts will be detected by searching for insertions or deletions the introns that have
sequence similarity to a protein domain using alignment methods. The signatures of
negative selection will be calculated by aligning the genes and then counting how many
synonymous and nonsynonymous substitutions there are and then using those numbers in
the formula to calculate the KA/KS value. If the KA/KS value is significantly less than 1,
the gene is most likely functional. If the KA/KS value is closer to 1, the gene may be a
pseudogene. Pseudogenes that are found will be posted on the homepage of Shiu Lab,
http://shiulab.plantbiology.msu.edu/wiki/index.php/Main_Page
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