DATABASE IN BRIEF
HUMAN MUTATION Database in Brief 32: E1948-E1958 (2010) Online
Received 1 July 2010; accepted revised manuscript 27 September 2010.
© 2010 WILEY-LISS, INC.
PRO-MINE: A Bioinformatics Repository and
Analytical Tool for TARDBP Mutations
Sofia Pinto1, Kristian Vlahoviček1*, and Emanuele Buratti2*
1Bioinform atics Group, Departm ent of Molecular Biology, Division of Biology, Faculty of Science, University of Zagreb, Croatia,
2International Centre for Genetic Engineering and Biotechnology (ICGEB), Trieste, Italy
*Correspondence to Kristian Vlahoviček (Phone: +385 14606276, E-mail: email@example.com) and Emanuele Buratti (Phone:
+39 040 3757316, E-mail: firstname.lastname@example.org)
Communicated by Mark H. Paalman
ABSTRACT: TDP-43 is a multifunctional RNA-binding protein found to be a major protein
component of intracellular inclusions found in neurodegenerative disorders such as Fronto
Temporal Lobar Degeneration, Amyotrophic Lateral Sclerosis, and Alzheimer Disease. PRO-
MINE (PROtein Mutations In NEurodegeneration) is a database populated with manually curated
data from the literature regarding all TDP-43/TDP43/TARDBP gene disease-associated mutations
identified to date. A web server interface has been developed to query the database and to provide
tools for the analysis of already reported or novel TDP-43 gene mutations. As is usually the case
with genetic association studies, assessing the potential impact of identified mutations is of crucial
importance, and in order to avoid prediction biases it is essential to compare the prediction results.
However, in most cases mutations have to be submitted separately to various prediction tools and
the individual results manually merged together afterwards. The implemented web server aims to
overcome the problem by providing simultaneous access to several prediction tools and by
displaying the results into a single output. Furthermore, the results are displayed together in a
comprehensive output for a more convenient analysis and are enriched with additional information
about mutations. In addition, our web server can also display the mutation(s) of interest within an
alignment of annotated TDP-43 protein sequences from different vertebrate species. In this way,
the degree of sequence conservation where the mutation(s) occur can be easily tracked and
visualized. The web server is freely available to researchers and can be accessed at
http://bioinfo.hr/pro-mine. ©2010 Wiley-Liss, Inc.
KEY WORDS: Neurodegeneration, TDP-43, TDP43, TARDBP, Alzheimer, Amyotrophic Lateral Sclerosis, ALS, Fronto
Temporal Lobar Degeneration, database
Genetic association studies aim to elucidate how single nucleotide polymorphisms (SNPs) may be related to a
genetic predisposition to develop disease. Non-synonymous single nucleotide polymorphisms are a type of SNPs
that result in a codon which codes for a different amino acid. Some of these polymorphisms are responsible for
many diseases as they may lead to appreciable changes in protein structure and function. Annotating and
TDP-43 Mutation Database E1949
distinguishing the polymorphisms that render the protein non-functional from those that do not is essential for the
study of disease-associated mutations. However, screening the pathogenicity for each identified SNP
experimentally is often a very laborious task that requires a considerable amount of time. To overcome this
challenge, several computational approaches for in silico predictions have been developed in recent years,
reviewed recently by Thusberg and Vihinen (Thusberg and Vihinen, 2009).
Nuclear factor TDP-43 (TDP43; HGNC-approved symbol TARDBP; MIM# 605078) is an example of a protein
with high SNP count. TDP-43 is a multifunctional RNA binding protein that plays a role in several cellular
processes such as transcription, pre-mRNA splicing, mRNA stability and mRNA transport (Buratti and Baralle,
2008; Buratti and Baralle, 2009; Chen-Plotkin et al., 2010). Recently, TDP-43 has also been found as the major
protein component of the intracellular inclusions occurring in the neuronal tissues of patients affected by a series
of neurodegenerative diseases which include Fronto Temporal Lobar Degeneration (FTLD-U), Amyotrophic
Lateral Sclerosis (ALS) (Geser et al., 2009; Neumann et al., 2006) and in a significant proportion of Alzheimer
Disease patients (Amador-Ortiz et al., 2007; Bigio, 2008; Rohn, 2008). In affected neurons, TDP-43 is abnormally
mislocalized to the cytoplasm, ubiquitinated, hyperphosphorylated and cleaved to generate C-terminal fragments
(Dormann et al., 2009; Hasegawa et al., 2008; Igaz et al., 2008; Neumann et al., 2009; Zhang et al., 2009). For a
detailed clinical view of TARDBP mutation carriers in the aforementioned diseases the reader is referred to the
Alzheimer Disease and Frontotemporal Dementia Mutation Database (http://www.molgen.ua.ac.be/ftdmutations)
and to the Amyotrophic Lateral Sclerosis Online genetic Database (http://alsod.iop.kcl.ac.uk).
In the beginning, the question was still open regarding the relative importance of this protein: should TDP-43
protein inclusions be considered as a simple pathological curiosity of these diseases or did it really play a role in
their origin and progression (Rothstein, 2007)? The recent development of several animal models, from simple
organisms to more complex ones, has clearly shown the pathological potential of both TDP-43 depletion and
overexpression in general (Feiguin et al., 2009; Hanson et al., 2010; Johnson et al., 2008; Kraemer et al., 2010; Li
et al., 2010; Lu et al., 2009; Sephton et al., 2010; Wils et al., 2010; Wu et al., 2010).
Another evidence that TDP-43 misregulation may be the cause of disease has been provided by several
genetic findings that have identified TDP-43 mutations in about 5% of the patients, as recently reviewed by
Pesiridis et al. (Pesiridis et al., 2009). With only two exceptions (p.Ala90Val and p.Asp169Gly) all disease-
associated mutations in human TDP-43 are localized in the C-terminal tail of the protein (a region that in hnRNP
proteins is usually associated with protein-protein interactions) and are all except p.Tyr374X characterized as
missense mutations (Figure 1). In this respect, it is important to note that all these mutations are dominant traits
and, until today, in the C-terminal tail no missense mutation has been found in healthy controls. At the moment,
very little is known about the role potentially played by these mutations. Nonetheless, expression of mutant forms
of this protein in Mus musculus (Wegorzewska et al., 2009), Rattus norvegicus (Zhou et al., 2010), Danio rerio
(Kabashi et al., 2010), Gallus gallus (Sreedharan et al., 2008), Saccharomyces cerevisiae (Johnson et al., 2009)
and neuronal cell lines (Barmada et al., 2010; Nonaka et al., 2009) can reproduce neurodegenerative effects similar
to those observed in human disease.
Figure 1. TDP-43 disease-associated mutations. The diagram shows the distribution of all missense mutations associated with
disease along the TDP-43 protein: all mutations are reported in the C-terminal tail of the protein with the exception of
p.Ala90Val and p.Asp169Gly (see Database and Analysis Tools section for details about the nomenclature used for mutations).
E1950 Pinto et al.
Here we present PRO-MINE (PROtein Mutations In NEurodegeneration), a manually curated mutation
repository providing detailed and updated information from the literature focusing on the potential functional
consequences of the TARDBP gene mutations.
We designed and implemented a user-friendly web interface aimed to facilitate the access to the database and to
integrate multiple prediction tools for the analysis of mutations. The results from the prediction tools are
automatically retrieved into a single output, greatly reducing the amount of time required when studying the effects
of mutations on protein. Furthermore, based on the fact that knowledge regarding the functional consequences of a
mutation can also be gained from sequence comparison, PRO-MINE also offers the possibility to display an
aligned set of protein sequences from several vertebrate species with the mutations of interest distinctly annotated.
PRO-MINE represents a novel approach and an advantage upon other existing tools and provides the proof of
concept for the need to generally integrate data with computational analytical tools in the study of mutations.
DATABASE AND ANALYSIS TOOLS
PRO-MINE is a relational database of published disease-associated mutations in human neurodegenerative
diseases, in particular focusing on the TARDBP gene.
The database was created using MySQL and consists of the following tables: mutations, genes and exons. The
entity relationships of the three tables are depicted in Figure 2. The conceptual scheme described was designed to
make easier future inclusion of other relevant genes and associated mutations. The database stores not only
information related to the mutations identified in the human TARDBP gene but also protein and genomic data
associated with the gene itself.
Figure 2. Entity relationship diagram of the PRO-MINE database. The scheme
illustrates the tables created for data storage (mutations, genes and exons) with the
respective attributes and how they are connected. The simple relationships between
the tables facilitate the possible expansion of the database to other proteins involved
An exhaustive manual review of the literature and public repository databases regarding TARDBP gene
mutations was performed. The result was a curated set of 43 mutations representing the most exhaustive to date
status of identified and characterized TDP-43 gene mutations, further referred to as ‘TDP-43 mutations core set’.
Relevant information concerning the mutations was, wherever available, extracted from the literature and included
in the mutations table. The information provided about a given mutation for each entry of the mutations table
includes: (1) the exon number where the mutation occurs; (2) clinical information related to the mutation such as
the number of patients where it was identified (in case of mutations found in different affected family members
only one patient for family was computed), the phenotype presented by the patients or the onset site of the disease;
(3) a brief description of observed experimental evidences on the functional consequences of the mutation on a
protein; and (4) references to original papers that reported the mutation as well as later studies. The mutation
nomenclature complies with the accepted guidelines proposed by the Human Genome Variation Society
TDP-43 Mutation Database E1951
(http://www.hgvs.org/mutnomen) and the variants numbering system is given on the protein level relative to the
amino acid reference sequence.
Protein sequences and genomic data stored in the genes and exons tables were retrieved from Ensembl (release
57 – Mar 2010) (Hubbard et al., 2009) through its Perl Application Program Interface. The set of protein sequences
comprises the human protein sequence encoded by the TARDBP gene (RefSeq NM_007375.3) and its orthologs
from six vertebrates: Pan troglodytes, Mus musculus, Rattus norvegicus, Gallus gallus, Xenopus tropicalis and
PRO-MINE web server interface implementation
The PRO-MINE web server is intended to facilitate the access to the data stored in the database and to provide
means for its analysis. The web server interface consists of dynamically generated HTML pages and was
developed using Perl CGI scripts (http://www.perl.com). The scripting programs run on Apache web server and
use MySQL (http://www.mysql.com) to retrieve and manage information stored in the database.
The PRO-MINE web server integrates four available software tools – NetPhos 2.0 (Blom et al., 1999),
PolyPhen (Ramensky et al., 2002), SIFT (Ng and Henikoff, 2003) and SNAP (Bromberg and Rost, 2007) – to
predict the pathological character of a mutation on a protein. The prediction tools were obtained as stand-alone
software packages (free for academic use) and integrated into the PRO-MINE web server with custom Perl scripts.
The integration of the prediction tools serves the purpose of providing researchers with a layout for a more
convenient and faster analysis of the results attained.
The four software tools use different models and features to predict the functional effect of mutations on
protein. NetPhos uses sequence and structure-based neural networks for predicting phosphorylation sites at serine,
threonine or tyrosine residues in protein sequences based on the premise that creation of new phosphoylation sites
or disruption of existing ones can alter the functionality of a protein. Although in normal conditions TARDBP does
not seem to be heavily phosphorylated, one of the distinguishing features of this disease-related protein is that it
becomes phosphorylated at several residues in the C-terminal region (Hasegawa et al., 2008; Neumann et al.,
2009). Therefore, prediction of phosphorylation sites should be taken into consideration because the aberrant
phosphorylation in the C-terminal region of TARDBP may be very important with regards to altering its
functionality. PolyPhen algorithm applies straightforward empirical rules to sequence-based, structural and
phylogenetic parameters describing the mutation. SIFT is an evolutionary-based approach which relies solely on
the information extracted from a multiple alignment of homologous proteins and the physical properties of amino
acids to calculate the probability that a mutation will be tolerated. Finally, SNAP combines information derived
from sequence homology and protein properties (secondary structure, solvent accessibility, etc) into neural
networks. The reason for the use of complementary approaches lies with different strengths and weaknesses of
various prediction algorithms, and in the absence of experimental evidence, the best strategy is to apply a
consensus decision among as many prediction tools as possible.
Besides these analysis tools available for user selection, PRO-MINE uses the multiple alignment software for
protein and nucleotide sequences – MUSCLE (Edgar, 2004) – in the internal pipeline. MUSCLE is employed in
the protein sequence annotation analytical tool to perform on-the-fly multiple alignments of homologous protein
Bioinformatics methods are of great help in elucidating the potential functional impact of mutations on protein
since they provide quick and accurate predictions. Nonetheless, each of the methods applies different features and
algorithms in the prediction analysis and, as a consequence, different results might arise. This poses a challenge for
the choice of the best method to utilize. As intuitively obvious, the best strategy to overcome this problem is to use
several prediction methods at the same time and to take into account all the results with the purpose of obtaining a
more reliable evaluation. However, manual inspection and analysis of the results from several bioinformatics tools
is a time-consuming procedure that requires parallel submission of the mutations of interest to each prediction
server separately and manual combining of the resulting predictions afterwards. Usually, these tools require
different input formatting and structure their output in different ways, and it is often impractical and time-
E1952 Pinto et al.
consuming for the user to collect the data and integrate it in the proper context. Also, knowledge discovery process
requires the researcher to use additional information sources and analysis tools.
In the PRO-MINE database and analysis server, the data and analysis tools are integrated in a user-friendly
interface in order to shift the focus of the researcher towards the problem and away from manual tasks of data
manipulation. Besides the manually curated database of known TDP-43 mutations, the analysis functions
implemented in PRO-MINE include: (a) prediction of mutational effects on protein function and (b) protein
sequence annotation with mutations. Details on the usage and currently available options are described below. The
developed web tool is freely available at: http://bioinfo.hr/pro-mine.
The web server accepts as input a list of mutations which can be typed directly into the query input box or
uploaded as a simple text file (Figure 3a). Mutation nomenclature should follow the standard protein mutation
format: XposY, where X and Y are the two amino acid variants (wild-type and mutant, respectively) and pos is the
position of the substitution in the sequence (e.g., M337V). The server also offers the possibility of using the TDP-
43 mutations core set by simply selecting the corresponding checkbox. Additionally, both fields can be used in
combination – an option that can be especially useful to compare new mutations with previously identified ones.
Prediction of mutational effects on protein function
By providing simultaneous access to several prediction tools, PRO-MINE renders the ability to obtain
predictions more efficiently and in comparatively less time than manually combining analysis results from
different sources. PRO-MINE integrates results from four separately selectable prediction tools (Figure 3b),
previously described in the Database and Analysis Tools section.
The results of the selected prediction tools are formatted and displayed in a single table, facilitating the
comparison of the different predictions. Predictions regarding the TDP-43 mutations core set are pre-computed to
avoid waiting time. Query results can also be viewed in plain text format or downloaded for further use.
Additionally to the predictions, for the TDP-43 mutations core set, selecting the mutation identifier opens a new
window displaying associated information such as clinical data about the patients presenting the mutation, a brief
description of observed experimental effects of the selected mutation on protein function and the literature
references reporting the mutation (see Database and Analysis Tools). An example of the results output for five
mutations is shown in Figure 4.
It should be stressed out that the validity of in silico predictions should always be assessed by further
experimental studies. For this reason, when known, observed experimental evidences on the functional
consequences of the TDP-43 mutations core set were collected and can be easily accessed (as shown in the pop-up
window in Figure 4).
The server offers two possibilities of use: the interactive use with results appearing in the web browser which
will be the choice for most analyses as the computation time is relatively short; and the off-line use with e-mail
report of the results which is recommended when a long list of mutations is submitted. In the latter case, the results
will not appear directly on the screen but a link pointing to the results will be sent to the submitted e-mail address.
A session identifier is assigned to each submitted job so that the results can be accessed at any time by following
the link provided in the e-mail. Moreover, the link allows the results to be easily shared with other researchers.
TDP-43 Mutation Database E1953
Figure 3. Screenshot of the PRO-MINE web server interface. A. Query input panel: mutations can be submitted
using the text box or by uploading a file; the checkbox must be selected to use the TDP-43 mutations core set.
B. Section to predict the potential effect of the entered mutations on protein function: the prediction tools can be
chosen from the list shown; an e-mail address can be provided to receive the results (this is a recommended
course of action since some of the predictions require a considerable amount of time to be processed). C.
Section to display aligned protein sequences from different species with annotated query mutations: a list of the
possible species to select is provided with the Homo sapiens option being permanently checked; it is also
offered the possibility to align only amino acid sequences encoded by individual exons by specifying the exons
numbers in the appropriate text box.
E1954 Pinto et al.
Figure 4. PRO-MINE output: prediction of mutational effects on protein function. In the table are displayed in
a comprehensive manner the predictions for five submitted mutations given by NetPhos, PolyPhen, SIFT and
SNAP. Each row of the table corresponds to the results of all selected web tools for a single mutation. Below
the table there is a link to view or save the results in plain text format. Selecting a mutation identifier opens a
pop-up window containing detailed data related to the mutation.
Protein sequence annotation with mutations
Multiple alignment of protein sequences from different species provides insight into the level of conservation of
an amino acid in a sequence position. Conserved positions are commonly associated with functionally important
sites and disease-related mutations frequently occur in those positions. Based on these considerations, an analytical
tool that aligns (see Database and Analysis Tools) and displays the TDP-43 protein sequences encoded by the
TDP-43 gene from different vertebrate species with the submitted mutations annotated was implemented.
The vertebrate species available include Homo sapiens, Pan troglodytes, Mus musculus, Rattus norvegicus,
Gallus gallus, Xenopus tropicalis and Danio rerio. The Homo sapiens option is checked by default and cannot be
unchecked while the other organisms are provided as choices (Figure 3c).
Alternatively to the complete protein sequence, the amino acid sequences encoded by the individual exons can
be aligned and displayed separately, in case a more detailed analysis is required. In this case, the ordinal numbers
of the exons intended to be analysed should be indicated in the appropriate text box (Figure 3c).
In the output display of the aligned sequences, coloured features are used to annotate the mutations and exon
boundaries, facilitating data interpretation. Placing the mouse pointer over an annotated mutation produces a
tooltip with information about the amino acid residues involved and the sequence position where the mutation
The described functionality offers a layout for a clear visualisation and analysis of protein sequence changes
among organisms in the positions where mutations occur and the distribution of the mutations along the protein
sequence. The alignment of the TDP-43 protein sequences from 3 species (Homo sapiens, Pan troglodytes and
Mus musculus) with the TDP-43 mutations core set annotated is shown as an example in Figure 5.
TDP-43 Mutation Database E1955
Figure 5. PRO-MINE output: protein sequence annotation with mutations. The aligned TDP-43 protein
sequences belonging to Homo sapiens, Pan troglodytes and Mus musculus are displayed. Marked in orange
colour characters are the amino acids involved in the TDP-43 mutations core set. Amino acids located in exons
boundaries are highlighted in blue or yellow, depending on whether the corresponding codon is part of one or
two exons, respectively. The rectangular tooltip is produced when the mouse is over a certain mutation and
displays, in order of appearance: the wild-type amino acid, the position in the protein sequence where the
mutation occurs and the mutant amino acid involved.
We plan to continue the development of PRO-MINE by extending it to other proteins and by improving its
Like TDP-43, mutations in many other genes have been found to be important in FTLD/ALS and have gained
the interest from the researchers, such as those identified recently in FUS gene (MIM# 137070) (Lagier-Tourenne
and Cleveland, 2009), and in the previously identified PGRN (MIM# 138945) (Gijselinck et al., 2008) and SOD1
genes (MIM# 147450) (Cleveland and Rothstein, 2001). Future work will include expanding the database to cover
these genes and eventually other genes encoding disease classes of proteins and their disease-associated mutations.
The database will be updated on a regular basis with newly available data.
Incorporating links into the results output to supplementary biological sources of relevance in the research of
mutations is part of the ongoing work. We also plan, having in view the flexibility enhancement of PRO-MINE, to
provide the possibility to submit not only mutations but also protein sequences as queries.
Finally, it will also be possible in future updates to expand the list of prediction tools available in PRO-MINE
as soon as they become publicly available.
PRO-MINE is a high-quality manually curated database of TARDBP gene mutations and a user-friendly web
tool for the automated analysis of known and novel mutations.
The developed web tool simplifies and enhances the time-consuming task of assessing the potential effects of
mutations on protein function by providing simultaneous retrieval and display of predictions from separate web
tools for a set of submitted mutations. Moreover, up-to-date information as well as visualisation tools are available
to complement and improve data evaluation.
E1956 Pinto et al.
PRO-MINE is presented here as a proof of concept for derived databases that combine curated datasets with
analytical tools in a single resource. Therefore, in future installations it is intended to broaden the use of the web
server by expanding the database to other genes involved in neurodegeneration.
We expect PRO-MINE to become a valuable tool in the study of disease-associated mutations as there is a
notable and current increasing interest in the mutation research.
The authors would like to thank Petar Jager for his great help with server configuration. EB is supported from a
grant by AriSLA. SP is supported from the EMBO Young Investigator Program Grant (Installation grant
1431/2006 to KV). We acknowledge the support from ICGEB collaborative research programme grant
CRP/CRO07-03 and Croatian MSES grant 119-0982913-1211.
Authors’ Contributions: SP created the database, designed and implemented the web server, made first draft
and wrote the manuscript. KV supervised the project and wrote the manuscript. EB suggested the project, collected
the data and wrote the manuscript. All authors read and approved the final version of the manuscript.
Amador-Ortiz C, Lin WL, Ahmed Z, Personett D, Davies P, Duara R, Graff-Radford NR, Hutton ML, Dickson DW. 2007.
TDP-43 immunoreactivity in hippocampal sclerosis and Alzheimer's disease. Ann Neurol 61:435-45.
Barmada SJ, Skibinski G, Korb E, Rao EJ, Wu JY, Finkbeiner S. 2010. Cytoplasmic mislocalization of TDP-43 is toxic to
neurons and enhanced by a mutation associated with familial amyotrophic lateral sclerosis. J Neurosci 30:639-49.
Bigio EH. 2008. TAR DNA-binding protein-43 in amyotrophic lateral sclerosis, frontotemporal lobar degeneration, and
Alzheimer disease. Acta Neuropathol 116:135-40.
Blom N, Gammeltoft S, Brunak S. 1999. Sequence and structure-based prediction of eukaryotic protein phosphorylation sites. J
Mol Biol 294:1351-62.
Bromberg Y, Rost B. 2007. SNAP: predict effect of non-synonymous polymorphisms on function. Nucleic Acids Res 35:3823-
Buratti E, Baralle FE. 2008. Multiple roles of TDP-43 in gene expression, splicing regulation, and human disease. Front Biosci
Buratti E, Baralle FE. 2009. The molecular links between TDP-43 dysfunction and neurodegeneration. Adv Genet 66:1-34.
Chen-Plotkin AS, Lee VM, Trojanowski JQ. 2010. TAR DNA-binding protein 43 in neurodegenerative disease. Nat Rev
Cleveland DW, Rothstein JD. 2001. From Charcot to Lou Gehrig: deciphering selective motor neuron death in ALS. Nat Rev
Dormann D, Capell A, Carlson AM, Shankaran SS, Rodde R, Neumann M, Kremmer E, Matsuwaki T, Yamanouchi K,
Nishihara M, Haass C. 2009. Proteolytic processing of TAR DNA binding protein-43 by caspases produces C-terminal
fragments with disease defining properties independent of progranulin. J Neurochem 110:1082-94.
Edgar RC. 2004. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792-
Feiguin F, Godena VK, Romano G, D'Ambrogio A, Klima R, Baralle FE. 2009. Depletion of TDP-43 affects Drosophila
motoneurons terminal synapsis and locomotive behavior. FEBS Lett 583:1586-92.
Geser F, Martinez-Lage M, Robinson J, Uryu K, Neumann M, Brandmeir NJ, Xie SX, Kwong LK, Elman L, McCluskey L,
Clark CM, Malunda J, Miller BL, Zimmerman EA, Qian J, Van Deerlin V, Grossman M, Lee VM, Trojanowski JQ. 2009.
Clinical and pathological continuum of multisystem TDP-43 proteinopathies. Arch Neurol 66:180-9.
Gijselinck I, Van Broeckhoven C, Cruts M. 2008. Granulin mutations associated with frontotemporal lobar degeneration and
related disorders: an update. Hum Mutat 29:1373-86.
TDP-43 Mutation Database E1957
.Hanson KA, Kim SH, Wassarman DA, Tibbetts RS. 2010. Ubiquilin modifies TDP-43 toxicity in a Drosophila model of
amyotrophic lateral sclerosis (ALS). J Biol Chem 285(15):11068-72.
Hasegawa M, Arai T, Nonaka T, Kametani F, Yoshida M, Hashizume Y, Beach TG, Buratti E, Baralle F, Morita M, Nakano I,
Oda T, Tsuchiya K, Akiyama H. 2008. Phosphorylated TDP-43 in frontotemporal lobar degeneration and amyotrophic
lateral sclerosis. Ann Neurol 64:60-70.
Hubbard TJ, Aken BL, Ayling S, Ballester B, Beal K, Bragin E, Brent S, Chen Y, Clapham P, Clarke L, Coates G, Fairley S,
Fitzgerald S, Fernandez-Banet J, Gordon L, Graf S, Haider S, Hammond M, Holland R, Howe K, Jenkinson A, Johnson N,
Kahari A, Keefe D, Keenan S, Kinsella R, Kokocinski F, Kulesha E, Lawson D, Longden I, Megy K, Meidl P, Overduin B,
Parker A, Pritchard B, Rios D, Schuster M, Slater G, Smedley D, Spooner W, Spudich G, Trevanion S, Vilella A, Vogel J,
White S, Wilder S, Zadissa A, Birney E, Cunningham F, Curwen V, Durbin R, Fernandez-Suarez XM, Herrero J, Kasprzyk
A, Proctor G, Smith J, Searle S, Flicek P. 2009. Ensembl 2009. Nucleic Acids Res 37(Database issue):D690-7.
Igaz LM, Kwong LK, Xu Y, Truax AC, Uryu K, Neumann M, Clark CM, Elman LB, Miller BL, Grossman M, McCluskey LF,
Trojanowski JQ, Lee VM. 2008. Enrichment of C-terminal fragments in TAR DNA-binding protein-43 cytoplasmic
inclusions in brain but not in spinal cord of frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Am J
Johnson BS, McCaffery JM, Lindquist S, Gitler AD. 2008. A yeast TDP-43 proteinopathy model: Exploring the molecular
determinants of TDP-43 aggregation and cellular toxicity. Proc Natl Acad Sci U S A 105:6439-44.
Johnson BS, Snead D, Lee JJ, McCaffery JM, Shorter J, Gitler AD. 2009. TDP-43 is intrinsically aggregation-prone, and
amyotrophic lateral sclerosis-linked mutations accelerate aggregation and increase toxicity. J Biol Chem 284:20329-39.
Kabashi E, Lin L, Tradewell ML, Dion PA, Bercier V, Bourgouin P, Rochefort D, Bel Hadj S, Durham HD, Velde CV,
Rouleau GA, Drapeau P. 2010. Gain and loss of function of ALS-related mutations of TARDBP (TDP-43) cause motor
deficits in vivo. Hum Mol Genet 19:671-683.
Kraemer BC, Schuck T, Wheeler JM, Robinson LC, Trojanowski JQ, Lee VM, Schellenberg GD. 2010. Loss of murine TDP-
43 disrupts motor function and plays an essential role in embryogenesis. Acta Neuropathol 119:409-419.
Lagier-Tourenne C, Cleveland DW. 2009. Rethinking ALS: the FUS about TDP-43. Cell 136:1001-4.
Li Y, Ray P, Rao EJ, Shi C, Guo W, Chen X, Woodruff EA, 3rd, Fushimi K, Wu JY. 2010. A Drosophila model for TDP-43
proteinopathy. Proc Natl Acad Sci U S A 107:3169-74.
Lu Y, Ferris J, Gao FB. 2009. Frontotemporal dementia and amyotrophic lateral sclerosis-associated disease protein TDP-43
promotes dendritic branching. Mol Brain 2:30.
Neumann M, Kwong LK, Lee EB, Kremmer E, Flatley A, Xu Y, Forman MS, Troost D, Kretzschmar HA, Trojanowski JQ,
Lee VM. 2009. Phosphorylation of S409/410 of TDP-43 is a consistent feature in all sporadic and familial forms of TDP-43
proteinopathies. Acta Neuropathol 117:137-49.
Neumann M, Sampathu DM, Kwong LK, Truax AC, Micsenyi MC, Chou TT, Bruce J, Schuck T, Grossman M, Clark CM,
McCluskey LF, Miller BL, Masliah E, Mackenzie IR, Feldman H, Feiden W, Kretzschmar HA, Trojanowski JQ, Lee VM.
2006. Ubiquitinated TDP-43 in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Science 314:130-3.
Ng PC, Henikoff S. 2003. SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res 31:3812-4.
Nonaka T, Kametani F, Arai T, Akiyama H, Hasegawa M. 2009. Truncation and pathogenic mutations facilitate the formation
of intracellular aggregates of TDP-43. Hum Mol Genet 18:3353-64.
Pesiridis GS, Lee VM, Trojanowski JQ. 2009. Mutations in TDP-43 link glycine-rich domain functions to amyotrophic lateral
sclerosis. Hum Mol Genet 18:R156-62.
Ramensky V, Bork P, Sunyaev S. 2002. Human non-synonymous SNPs: server and survey. Nucleic Acids Res 30:3894-900.
Rohn TT. 2008. Caspase-cleaved TAR DNA-binding protein-43 is a major pathological finding in Alzheimer's disease. Brain
Rothstein JD. 2007. TDP-43 in amyotrophic lateral sclerosis: Pathophysiology or patho-babel? Ann Neurol 61:382-4.
E1958 Pinto et al. Download full-text
Sephton CF, Good SK, Atkin S, Dewey CM, Mayer P, 3rd, Herz J, Yu G. 2010. TDP-43 Is a Developmentally Regulated
Protein Essential for Early Embryonic Development. J Biol Chem 285:6826-34.
Sreedharan J, Blair IP, Tripathi VB, Hu X, Vance C, Rogelj B, Ackerley S, Durnall JC, Williams KL, Buratti E, Baralle F, de
Belleroche J, Mitchell JD, Leigh PN, Al-Chalabi A, Miller CC, Nicholson G, Shaw CE. 2008. TDP-43 mutations in familial
and sporadic amyotrophic lateral sclerosis. Science 319:1668-72.
Thusberg J, Vihinen M. 2009. Pathogenic or not? And if so, then how? Studying the effects of missense mutations using
bioinformatics methods. Hum Mutat 30:703-14.
Wegorzewska I, Bell S, Cairns NJ, Miller TM, Baloh RH. 2009. TDP-43 mutant transgenic mice develop features of ALS and
frontotemporal lobar degeneration. Proc Natl Acad Sci U S A 106:18809-14.
Wils H, Kleinberger G, Janssens J, Pereson S, Joris G, Cuijt I, Smits V, Groote CC, Van Broeckhoven C, Kumar-Singh S.
2010. TDP-43 transgenic mice develop spastic paralysis and neuronal inclusions characteristic of ALS and frontotemporal
lobar degeneration. Proc Natl Acad Sci U S A 107:3858-63.
Wu LS, Cheng WC, Hou SC, Yan YT, Jiang ST, Shen CK. 2010. TDP-43, a neuro-pathosignature factor, is essential for early
mouse embryogenesis. Genesis 48:56-62.
Zhang YJ, Xu YF, Cook C, Gendron TF, Roettges P, Link CD, Lin WL, Tong J, Castanedes-Casey M, Ash P, Gass J,
Rangachari V, Buratti E, Baralle F, Golde TE, Dickson DW, Petrucelli L. 2009. Aberrant cleavage of TDP-43 enhances
aggregation and cellular toxicity. Proc Natl Acad Sci U S A 106:7607-12.
Zhou H, Huang C, Chen H, Wang D, Landel CP, Xia PY, Bowser R, Liu YJ, Xia XG. 2010. Transgenic rat model of
neurodegeneration caused by mutation in the TDP gene. PLoS Genet 6:e1000887.