@article {49764, title = {TIGRFAMs and Genome Properties in 2013.}, journal = {Nucleic Acids Res}, volume = {41}, year = {2013}, month = {2013 Jan}, pages = {D387-95}, abstract = {

TIGRFAMs, available online at http://www.jcvi.org/tigrfams is a database of protein family definitions. Each entry features a seed alignment of trusted representative sequences, a hidden Markov model (HMM) built from that alignment, cutoff scores that let automated annotation pipelines decide which proteins are members, and annotations for transfer onto member proteins. Most TIGRFAMs models are designated equivalog, meaning they assign a specific name to proteins conserved in function from a common ancestral sequence. Models describing more functionally heterogeneous families are designated subfamily or domain, and assign less specific but more widely applicable annotations. The Genome Properties database, available at http://www.jcvi.org/genome-properties, specifies how computed evidence, including TIGRFAMs HMM results, should be used to judge whether an enzymatic pathway, a protein complex or another type of molecular subsystem is encoded in a genome. TIGRFAMs and Genome Properties content are developed in concert because subsystems reconstruction for large numbers of genomes guides selection of seed alignment sequences and cutoff values during protein family construction. Both databases specialize heavily in bacterial and archaeal subsystems. At present, 4284 models appear in TIGRFAMs, while 628 systems are described by Genome Properties. Content derives both from subsystem discovery work and from biocuration of the scientific literature.

}, keywords = {Databases, Protein, Genome, Archaeal, Genome, Bacterial, Genomics, Internet, Markov chains, Molecular Sequence Annotation, Proteins, sequence alignment}, issn = {1362-4962}, doi = {10.1093/nar/gks1234}, author = {Haft, Daniel H and Selengut, Jeremy D and Richter, Roland A and Harkins, Derek and Basu, Malay K and Beck, Erin} } @article {38529, title = {TIGRFAMs and Genome Properties in 2013}, journal = {Nucleic acids researchNucleic Acids Research}, volume = {41}, year = {2013}, note = {http://www.ncbi.nlm.nih.gov/pubmed/23197656?dopt=Abstract}, type = {10.1093/nar/gks1234}, abstract = {TIGRFAMs, available online at http://www.jcvi.org/tigrfams is a database of protein family definitions. Each entry features a seed alignment of trusted representative sequences, a hidden Markov model (HMM) built from that alignment, cutoff scores that let automated annotation pipelines decide which proteins are members, and annotations for transfer onto member proteins. Most TIGRFAMs models are designated equivalog, meaning they assign a specific name to proteins conserved in function from a common ancestral sequence. Models describing more functionally heterogeneous families are designated subfamily or domain, and assign less specific but more widely applicable annotations. The Genome Properties database, available at http://www.jcvi.org/genome-properties, specifies how computed evidence, including TIGRFAMs HMM results, should be used to judge whether an enzymatic pathway, a protein complex or another type of molecular subsystem is encoded in a genome. TIGRFAMs and Genome Properties content are developed in concert because subsystems reconstruction for large numbers of genomes guides selection of seed alignment sequences and cutoff values during protein family construction. Both databases specialize heavily in bacterial and archaeal subsystems. At present, 4284 models appear in TIGRFAMs, while 628 systems are described by Genome Properties. Content derives both from subsystem discovery work and from biocuration of the scientific literature.}, keywords = {Databases, Protein, Genome, Archaeal, Genome, Bacterial, Genomics, Internet, Markov chains, Molecular Sequence Annotation, Proteins, sequence alignment}, author = {Haft, Daniel H. and J. Selengut and Richter, Roland A. and Harkins, Derek and Basu, Malay K. and Beck, Erin} } @article {49749, title = {Measuring differential gene expression by short read sequencing: quantitative comparison to 2-channel gene expression microarrays.}, journal = {BMC Genomics}, volume = {10}, year = {2009}, month = {2009}, pages = {221}, abstract = {

BACKGROUND: High-throughput cDNA synthesis and sequencing of poly(A)-enriched RNA is rapidly emerging as a technology competing to replace microarrays as a quantitative platform for measuring gene expression.

RESULTS: Consequently, we compared full length cDNA sequencing to 2-channel gene expression microarrays in the context of measuring differential gene expression. Because of its comparable cost to a gene expression microarray, our study focused on the data obtainable from a single lane of an Illumina 1 G sequencer. We compared sequencing data to a highly replicated microarray experiment profiling two divergent strains of S. cerevisiae.

CONCLUSION: Using a large number of quantitative PCR (qPCR) assays, more than previous studies, we found that neither technology is decisively better at measuring differential gene expression. Further, we report sequencing results from a diploid hybrid of two strains of S. cerevisiae that indicate full length cDNA sequencing can discover heterozygosity and measure quantitative allele-specific expression simultaneously.

}, keywords = {algorithms, DNA, Complementary, DNA, Fungal, Gene Expression Profiling, Oligonucleotide Array Sequence Analysis, Saccharomyces cerevisiae, sequence alignment, Sequence Analysis, DNA}, issn = {1471-2164}, doi = {10.1186/1471-2164-10-221}, author = {Bloom, Joshua S and Khan, Zia and Kruglyak, Leonid and Singh, Mona and Caudy, Amy A} } @article {49748, title = {A practical algorithm for finding maximal exact matches in large sequence datasets using sparse suffix arrays.}, journal = {Bioinformatics}, volume = {25}, year = {2009}, month = {2009 Jul 1}, pages = {1609-16}, abstract = {

MOTIVATION: High-throughput sequencing technologies place ever increasing demands on existing algorithms for sequence analysis. Algorithms for computing maximal exact matches (MEMs) between sequences appear in two contexts where high-throughput sequencing will vastly increase the volume of sequence data: (i) seeding alignments of high-throughput reads for genome assembly and (ii) designating anchor points for genome-genome comparisons.

RESULTS: We introduce a new algorithm for finding MEMs. The algorithm leverages a sparse suffix array (SA), a text index that stores every K-th position of the text. In contrast to a full text index that stores every position of the text, a sparse SA occupies much less memory. Even though we use a sparse index, the output of our algorithm is the same as a full text index algorithm as long as the space between the indexed suffixes is not greater than a minimum length of a MEM. By relying on partial matches and additional text scanning between indexed positions, the algorithm trades memory for extra computation. The reduced memory usage makes it possible to determine MEMs between significantly longer sequences.

AVAILABILITY: Source code for the algorithm is available under a BSD open source license at http://compbio.cs.princeton.edu/mems. The implementation can serve as a drop-in replacement for the MEMs algorithm in MUMmer 3.

}, keywords = {algorithms, Base Sequence, Genomics, sequence alignment, Sequence Analysis, DNA}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btp275}, author = {Khan, Zia and Bloom, Joshua S and Kruglyak, Leonid and Singh, Mona} } @article {49675, title = {Two alternatively spliced isoforms of the Arabidopsis SR45 protein have distinct roles during normal plant development.}, journal = {Plant Physiol}, volume = {150}, year = {2009}, month = {2009 Jul}, pages = {1450-8}, abstract = {

The serine-arginine-rich (SR) proteins constitute a conserved family of pre-mRNA splicing factors. In Arabidopsis (Arabidopsis thaliana), they are encoded by 19 genes, most of which are themselves alternatively spliced. In the case of SR45, the use of alternative 3{\textquoteright} splice sites 21 nucleotides apart generates two alternatively spliced isoforms. Isoform 1 (SR45.1) has an insertion relative to isoform 2 (SR45.2) that replaces a single arginine with eight amino acids (TSPQRKTG). The biological implications of SR45 alternative splicing have been unclear. A previously described loss-of-function mutant affecting both isoforms, sr45-1, shows several developmental defects, including defects in petal development and root growth. We found that the SR45 promoter is highly active in regions with actively growing and dividing cells. We also tested the ability of each SR45 isoform to complement the sr45-1 mutant by overexpression of isoform-specific green fluorescent protein (GFP) fusion proteins. As expected, transgenic plants overexpressing either isoform displayed both nuclear speckles and GFP fluorescence throughout the nucleoplasm. We found that SR45.1-GFP complements the flower petal phenotype, but not the root growth phenotype. Conversely, SR45.2-GFP complements root growth but not floral morphology. Mutation of a predicted phosphorylation site within the alternatively spliced segment, SR45.1-S219A-GFP, does not affect complementation. However, a double mutation affecting both serine-219 and the adjacent threonine-218 (SR45.1-T218A + S219A-GFP) behaves like isoform 2, complementing the root but not the floral phenotype. In conclusion, our study provides evidence that the two alternatively spliced isoforms of SR45 have distinct biological functions.

}, keywords = {Alternative Splicing, Amino Acid Sequence, Arabidopsis, Arabidopsis Proteins, Carrier Proteins, Flowers, Molecular Sequence Data, Mutation, Plant Roots, Protein Isoforms, Ribonucleoproteins, RNA-Binding Proteins, sequence alignment}, issn = {0032-0889}, doi = {10.1104/pp.109.138180}, author = {Zhang, Xiao-Ning and Mount, Stephen M} } @article {49676, title = {The draft genome of the transgenic tropical fruit tree papaya (Carica papaya Linnaeus).}, journal = {Nature}, volume = {452}, year = {2008}, month = {2008 Apr 24}, pages = {991-6}, abstract = {

Papaya, a fruit crop cultivated in tropical and subtropical regions, is known for its nutritional benefits and medicinal applications. Here we report a 3x draft genome sequence of {\textquoteright}SunUp{\textquoteright} papaya, the first commercial virus-resistant transgenic fruit tree to be sequenced. The papaya genome is three times the size of the Arabidopsis genome, but contains fewer genes, including significantly fewer disease-resistance gene analogues. Comparison of the five sequenced genomes suggests a minimal angiosperm gene set of 13,311. A lack of recent genome duplication, atypical of other angiosperm genomes sequenced so far, may account for the smaller papaya gene number in most functional groups. Nonetheless, striking amplifications in gene number within particular functional groups suggest roles in the evolution of tree-like habit, deposition and remobilization of starch reserves, attraction of seed dispersal agents, and adaptation to tropical daylengths. Transgenesis at three locations is closely associated with chloroplast insertions into the nuclear genome, and with topoisomerase I recognition sites. Papaya offers numerous advantages as a system for fruit-tree functional genomics, and this draft genome sequence provides the foundation for revealing the basis of Carica{\textquoteright}s distinguishing morpho-physiological, medicinal and nutritional properties.

}, keywords = {Arabidopsis, Carica, Contig Mapping, Databases, Genetic, Genes, Plant, Genome, Plant, Molecular Sequence Data, Plants, Genetically Modified, sequence alignment, Sequence Analysis, DNA, Transcription Factors, Tropical Climate}, issn = {1476-4687}, doi = {10.1038/nature06856}, author = {Ming, Ray and Hou, Shaobin and Feng, Yun and Yu, Qingyi and Dionne-Laporte, Alexandre and Saw, Jimmy H and Senin, Pavel and Wang, Wei and Ly, Benjamin V and Lewis, Kanako L T and Salzberg, Steven L and Feng, Lu and Jones, Meghan R and Skelton, Rachel L and Murray, Jan E and Chen, Cuixia and Qian, Wubin and Shen, Junguo and Du, Peng and Eustice, Moriah and Tong, Eric and Tang, Haibao and Lyons, Eric and Paull, Robert E and Michael, Todd P and Wall, Kerr and Rice, Danny W and Albert, Henrik and Wang, Ming-Li and Zhu, Yun J and Schatz, Michael and Nagarajan, Niranjan and Acob, Ricelle A and Guan, Peizhu and Blas, Andrea and Wai, Ching Man and Ackerman, Christine M and Ren, Yan and Liu, Chao and Wang, Jianmei and Wang, Jianping and Na, Jong-Kuk and Shakirov, Eugene V and Haas, Brian and Thimmapuram, Jyothi and Nelson, David and Wang, Xiyin and Bowers, John E and Gschwend, Andrea R and Delcher, Arthur L and Singh, Ratnesh and Suzuki, Jon Y and Tripathi, Savarni and Neupane, Kabi and Wei, Hairong and Irikura, Beth and Paidi, Maya and Jiang, Ning and Zhang, Wenli and Presting, Gernot and Windsor, Aaron and Navajas-P{\'e}rez, Rafael and Torres, Manuel J and Feltus, F Alex and Porter, Brad and Li, Yingjun and Burroughs, A Max and Luo, Ming-Cheng and Liu, Lei and Christopher, David A and Mount, Stephen M and Moore, Paul H and Sugimura, Tak and Jiang, Jiming and Schuler, Mary A and Friedman, Vikki and Mitchell-Olds, Thomas and Shippen, Dorothy E and dePamphilis, Claude W and Palmer, Jeffrey D and Freeling, Michael and Paterson, Andrew H and Gonsalves, Dennis and Wang, Lei and Alam, Maqsudul} } @article {49677, title = {Evolution of genes and genomes on the Drosophila phylogeny.}, journal = {Nature}, volume = {450}, year = {2007}, month = {2007 Nov 8}, pages = {203-18}, abstract = {

Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.

}, keywords = {Animals, Codon, DNA Transposable Elements, Drosophila, Drosophila Proteins, Evolution, Molecular, Gene Order, Genes, Insect, Genome, Insect, Genome, Mitochondrial, Genomics, Immunity, Multigene Family, Phylogeny, Reproduction, RNA, Untranslated, sequence alignment, Sequence Analysis, DNA, Synteny}, issn = {1476-4687}, doi = {10.1038/nature06341}, author = {Clark, Andrew G and Eisen, Michael B and Smith, Douglas R and Bergman, Casey M and Oliver, Brian and Markow, Therese A and Kaufman, Thomas C and Kellis, Manolis and Gelbart, William and Iyer, Venky N and Pollard, Daniel A and Sackton, Timothy B and Larracuente, Amanda M and Singh, Nadia D and Abad, Jose P and Abt, Dawn N and Adryan, Boris and Aguade, Montserrat and Akashi, Hiroshi and Anderson, Wyatt W and Aquadro, Charles F and Ardell, David H and Arguello, Roman and Artieri, Carlo G and Barbash, Daniel A and Barker, Daniel and Barsanti, Paolo and Batterham, Phil and Batzoglou, Serafim and Begun, Dave and Bhutkar, Arjun and Blanco, Enrico and Bosak, Stephanie A and Bradley, Robert K and Brand, Adrianne D and Brent, Michael R and Brooks, Angela N and Brown, Randall H and Butlin, Roger K and Caggese, Corrado and Calvi, Brian R and Bernardo de Carvalho, A and Caspi, Anat and Castrezana, Sergio and Celniker, Susan E and Chang, Jean L and Chapple, Charles and Chatterji, Sourav and Chinwalla, Asif and Civetta, Alberto and Clifton, Sandra W and Comeron, Josep M and Costello, James C and Coyne, Jerry A and Daub, Jennifer and David, Robert G and Delcher, Arthur L and Delehaunty, Kim and Do, Chuong B and Ebling, Heather and Edwards, Kevin and Eickbush, Thomas and Evans, Jay D and Filipski, Alan and Findeiss, Sven and Freyhult, Eva and Fulton, Lucinda and Fulton, Robert and Garcia, Ana C L and Gardiner, Anastasia and Garfield, David A and Garvin, Barry E and Gibson, Greg and Gilbert, Don and Gnerre, Sante and Godfrey, Jennifer and Good, Robert and Gotea, Valer and Gravely, Brenton and Greenberg, Anthony J and Griffiths-Jones, Sam and Gross, Samuel and Guigo, Roderic and Gustafson, Erik A and Haerty, Wilfried and Hahn, Matthew W and Halligan, Daniel L and Halpern, Aaron L and Halter, Gillian M and Han, Mira V and Heger, Andreas and Hillier, LaDeana and Hinrichs, Angie S and Holmes, Ian and Hoskins, Roger A and Hubisz, Melissa J and Hultmark, Dan and Huntley, Melanie A and Jaffe, David B and Jagadeeshan, Santosh and Jeck, William R and Johnson, Justin and Jones, Corbin D and Jordan, William C and Karpen, Gary H and Kataoka, Eiko and Keightley, Peter D and Kheradpour, Pouya and Kirkness, Ewen F and Koerich, Leonardo B and Kristiansen, Karsten and Kudrna, Dave and Kulathinal, Rob J and Kumar, Sudhir and Kwok, Roberta and Lander, Eric and Langley, Charles H and Lapoint, Richard and Lazzaro, Brian P and Lee, So-Jeong and Levesque, Lisa and Li, Ruiqiang and Lin, Chiao-Feng and Lin, Michael F and Lindblad-Toh, Kerstin and Llopart, Ana and Long, Manyuan and Low, Lloyd and Lozovsky, Elena and Lu, Jian and Luo, Meizhong and Machado, Carlos A and Makalowski, Wojciech and Marzo, Mar and Matsuda, Muneo and Matzkin, Luciano and McAllister, Bryant and McBride, Carolyn S and McKernan, Brendan and McKernan, Kevin and Mendez-Lago, Maria and Minx, Patrick and Mollenhauer, Michael U and Montooth, Kristi and Mount, Stephen M and Mu, Xu and Myers, Eugene and Negre, Barbara and Newfeld, Stuart and Nielsen, Rasmus and Noor, Mohamed A F and O{\textquoteright}Grady, Patrick and Pachter, Lior and Papaceit, Montserrat and Parisi, Matthew J and Parisi, Michael and Parts, Leopold and Pedersen, Jakob S and Pesole, Graziano and Phillippy, Adam M and Ponting, Chris P and Pop, Mihai and Porcelli, Damiano and Powell, Jeffrey R and Prohaska, Sonja and Pruitt, Kim and Puig, Marta and Quesneville, Hadi and Ram, Kristipati Ravi and Rand, David and Rasmussen, Matthew D and Reed, Laura K and Reenan, Robert and Reily, Amy and Remington, Karin A and Rieger, Tania T and Ritchie, Michael G and Robin, Charles and Rogers, Yu-Hui and Rohde, Claudia and Rozas, Julio and Rubenfield, Marc J and Ruiz, Alfredo and Russo, Susan and Salzberg, Steven L and Sanchez-Gracia, Alejandro and Saranga, David J and Sato, Hajime and Schaeffer, Stephen W and Schatz, Michael C and Schlenke, Todd and Schwartz, Russell and Segarra, Carmen and Singh, Rama S and Sirot, Laura and Sirota, Marina and Sisneros, Nicholas B and Smith, Chris D and Smith, Temple F and Spieth, John and Stage, Deborah E and Stark, Alexander and Stephan, Wolfgang and Strausberg, Robert L and Strempel, Sebastian and Sturgill, David and Sutton, Granger and Sutton, Granger G and Tao, Wei and Teichmann, Sarah and Tobari, Yoshiko N and Tomimura, Yoshihiko and Tsolas, Jason M and Valente, Vera L S and Venter, Eli and Venter, J Craig and Vicario, Saverio and Vieira, Filipe G and Vilella, Albert J and Villasante, Alfredo and Walenz, Brian and Wang, Jun and Wasserman, Marvin and Watts, Thomas and Wilson, Derek and Wilson, Richard K and Wing, Rod A and Wolfner, Mariana F and Wong, Alex and Wong, Gane Ka-Shu and Wu, Chung-I and Wu, Gabriel and Yamamoto, Daisuke and Yang, Hsiao-Pei and Yang, Shiaw-Pyng and Yorke, James A and Yoshida, Kiyohito and Zdobnov, Evgeny and Zhang, Peili and Zhang, Yu and Zimin, Aleksey V and Baldwin, Jennifer and Abdouelleil, Amr and Abdulkadir, Jamal and Abebe, Adal and Abera, Brikti and Abreu, Justin and Acer, St Christophe and Aftuck, Lynne and Alexander, Allen and An, Peter and Anderson, Erica and Anderson, Scott and Arachi, Harindra and Azer, Marc and Bachantsang, Pasang and Barry, Andrew and Bayul, Tashi and Berlin, Aaron and Bessette, Daniel and Bloom, Toby and Blye, Jason and Boguslavskiy, Leonid and Bonnet, Claude and Boukhgalter, Boris and Bourzgui, Imane and Brown, Adam and Cahill, Patrick and Channer, Sheridon and Cheshatsang, Yama and Chuda, Lisa and Citroen, Mieke and Collymore, Alville and Cooke, Patrick and Costello, Maura and D{\textquoteright}Aco, Katie and Daza, Riza and De Haan, Georgius and DeGray, Stuart and DeMaso, Christina and Dhargay, Norbu and Dooley, Kimberly and Dooley, Erin and Doricent, Missole and Dorje, Passang and Dorjee, Kunsang and Dupes, Alan and Elong, Richard and Falk, Jill and Farina, Abderrahim and Faro, Susan and Ferguson, Diallo and Fisher, Sheila and Foley, Chelsea D and Franke, Alicia and Friedrich, Dennis and Gadbois, Loryn and Gearin, Gary and Gearin, Christina R and Giannoukos, Georgia and Goode, Tina and Graham, Joseph and Grandbois, Edward and Grewal, Sharleen and Gyaltsen, Kunsang and Hafez, Nabil and Hagos, Birhane and Hall, Jennifer and Henson, Charlotte and Hollinger, Andrew and Honan, Tracey and Huard, Monika D and Hughes, Leanne and Hurhula, Brian and Husby, M Erii and Kamat, Asha and Kanga, Ben and Kashin, Seva and Khazanovich, Dmitry and Kisner, Peter and Lance, Krista and Lara, Marcia and Lee, William and Lennon, Niall and Letendre, Frances and LeVine, Rosie and Lipovsky, Alex and Liu, Xiaohong and Liu, Jinlei and Liu, Shangtao and Lokyitsang, Tashi and Lokyitsang, Yeshi and Lubonja, Rakela and Lui, Annie and MacDonald, Pen and Magnisalis, Vasilia and Maru, Kebede and Matthews, Charles and McCusker, William and McDonough, Susan and Mehta, Teena and Meldrim, James and Meneus, Louis and Mihai, Oana and Mihalev, Atanas and Mihova, Tanya and Mittelman, Rachel and Mlenga, Valentine and Montmayeur, Anna and Mulrain, Leonidas and Navidi, Adam and Naylor, Jerome and Negash, Tamrat and Nguyen, Thu and Nguyen, Nga and Nicol, Robert and Norbu, Choe and Norbu, Nyima and Novod, Nathaniel and O{\textquoteright}Neill, Barry and Osman, Sahal and Markiewicz, Eva and Oyono, Otero L and Patti, Christopher and Phunkhang, Pema and Pierre, Fritz and Priest, Margaret and Raghuraman, Sujaa and Rege, Filip and Reyes, Rebecca and Rise, Cecil and Rogov, Peter and Ross, Keenan and Ryan, Elizabeth and Settipalli, Sampath and Shea, Terry and Sherpa, Ngawang and Shi, Lu and Shih, Diana and Sparrow, Todd and Spaulding, Jessica and Stalker, John and Stange-Thomann, Nicole and Stavropoulos, Sharon and Stone, Catherine and Strader, Christopher and Tesfaye, Senait and Thomson, Talene and Thoulutsang, Yama and Thoulutsang, Dawa and Topham, Kerri and Topping, Ira and Tsamla, Tsamla and Vassiliev, Helen and Vo, Andy and Wangchuk, Tsering and Wangdi, Tsering and Weiand, Michael and Wilkinson, Jane and Wilson, Adam and Yadav, Shailendra and Young, Geneva and Yu, Qing and Zembek, Lisa and Zhong, Danni and Zimmer, Andrew and Zwirko, Zac and Jaffe, David B and Alvarez, Pablo and Brockman, Will and Butler, Jonathan and Chin, CheeWhye and Gnerre, Sante and Grabherr, Manfred and Kleber, Michael and Mauceli, Evan and MacCallum, Iain} } @article {49642, title = {Members of a large retroposon family are determinants of post-transcriptional gene expression in Leishmania.}, journal = {PLoS Pathog}, volume = {3}, year = {2007}, month = {2007 Sep 7}, pages = {1291-307}, abstract = {

Trypanosomatids are unicellular protists that include the human pathogens Leishmania spp. (leishmaniasis), Trypanosoma brucei (sleeping sickness), and Trypanosoma cruzi (Chagas disease). Analysis of their recently completed genomes confirmed the presence of non-long-terminal repeat retrotransposons, also called retroposons. Using the 79-bp signature sequence common to all trypanosomatid retroposons as bait, we identified in the Leishmania major genome two new large families of small elements--LmSIDER1 (785 copies) and LmSIDER2 (1,073 copies)--that fulfill all the characteristics of extinct trypanosomatid retroposons. LmSIDERs are approximately 70 times more abundant in L. major compared to T. brucei and are found almost exclusively within the 3{\textquoteright}-untranslated regions (3{\textquoteright}UTRs) of L. major mRNAs. We provide experimental evidence that LmSIDER2 act as mRNA instability elements and that LmSIDER2-containing mRNAs are generally expressed at lower levels compared to the non-LmSIDER2 mRNAs. The considerable expansion of LmSIDERs within 3{\textquoteright}UTRs in an organism lacking transcriptional control and their role in regulating mRNA stability indicate that Leishmania have probably recycled these short retroposons to globally modulate the expression of a number of genes. To our knowledge, this is the first example in eukaryotes of the domestication and expansion of a family of mobile elements that have evolved to fulfill a critical cellular function.

}, keywords = {3{\textquoteright} Untranslated Regions, Animals, Base Sequence, Biological Evolution, Down-Regulation, Gene Expression Regulation, Genome, Protozoan, Leishmania, Leishmania major, Molecular Sequence Data, Retroelements, RNA, Messenger, sequence alignment, Trypanosoma brucei brucei, Trypanosoma cruzi}, issn = {1553-7374}, doi = {10.1371/journal.ppat.0030136}, author = {Bringaud, Frederic and M{\"u}ller, Michaela and Cerqueira, Gustavo Coutinho and Smith, Martin and Rochette, Annie and el-Sayed, Najib M A and Papadopoulou, Barbara and Ghedin, Elodie} } @article {49679, title = {SplicePort--an interactive splice-site analysis tool.}, journal = {Nucleic Acids Res}, volume = {35}, year = {2007}, month = {2007 Jul}, pages = {W285-91}, abstract = {

SplicePort is a web-based tool for splice-site analysis that allows the user to make splice-site predictions for submitted sequences. In addition, the user can also browse the rich catalog of features that underlies these predictions, and which we have found capable of providing high classification accuracy on human splice sites. Feature selection is optimized for human splice sites, but the selected features are likely to be predictive for other mammals as well. With our interactive feature browsing and visualization tool, the user can view and explore subsets of features used in splice-site prediction (either the features that account for the classification of a specific input sequence or the complete collection of features). Selected feature sets can be searched, ranked or displayed easily. The user can group features into clusters and frequency plot WebLogos can be generated for each cluster. The user can browse the identified clusters and their contributing elements, looking for new interesting signals, or can validate previously observed signals. The SplicePort web server can be accessed at http://www.cs.umd.edu/projects/SplicePort and http://www.spliceport.org.

}, keywords = {Base Sequence, Chromosome mapping, Computational Biology, Computer simulation, DNA, Genome, HUMANS, Internet, Models, Genetic, Molecular Sequence Data, Pattern Recognition, Automated, RNA Splice Sites, sequence alignment, Sequence Analysis, DNA, User-Computer Interface}, issn = {1362-4962}, doi = {10.1093/nar/gkm407}, author = {Dogan, Rezarta Islamaj and Getoor, Lise and Wilbur, W John and Mount, Stephen M} } @article {38247, title = {Exopolysaccharide-associated protein sorting in environmental organisms: the PEP-CTERM/EpsH system. Application of a novel phylogenetic profiling heuristic}, journal = {BMC biologyBMC biology}, volume = {4}, year = {2006}, note = {http://www.ncbi.nlm.nih.gov/pubmed/16930487?dopt=Abstract}, type = {10.1186/1741-7007-4-29}, abstract = {BACKGROUND: Protein translocation to the proper cellular destination may be guided by various classes of sorting signals recognizable in the primary sequence. Detection in some genomes, but not others, may reveal sorting system components by comparison of the phylogenetic profile of the class of sorting signal to that of various protein families. RESULTS: We describe a short C-terminal homology domain, sporadically distributed in bacteria, with several key characteristics of protein sorting signals. The domain includes a near-invariant motif Pro-Glu-Pro (PEP). This possible recognition or processing site is followed by a predicted transmembrane helix and a cluster rich in basic amino acids. We designate this domain PEP-CTERM. It tends to occur multiple times in a genome if it occurs at all, with a median count of eight instances; Verrucomicrobium spinosum has sixty-five. PEP-CTERM-containing proteins generally contain an N-terminal signal peptide and exhibit high diversity and little homology to known proteins. All bacteria with PEP-CTERM have both an outer membrane and exopolysaccharide (EPS) production genes. By a simple heuristic for screening phylogenetic profiles in the absence of pre-formed protein families, we discovered that a homolog of the membrane protein EpsH (exopolysaccharide locus protein H) occurs in a species when PEP-CTERM domains are found. The EpsH family contains invariant residues consistent with a transpeptidase function. Most PEP-CTERM proteins are encoded by single-gene operons preceded by large intergenic regions. In the Proteobacteria, most of these upstream regions share a DNA sequence, a probable cis-regulatory site that contains a sigma-54 binding motif. The phylogenetic profile for this DNA sequence exactly matches that of three proteins: a sigma-54-interacting response regulator (PrsR), a transmembrane histidine kinase (PrsK), and a TPR protein (PrsT). CONCLUSION: These findings are consistent with the hypothesis that PEP-CTERM and EpsH form a protein export sorting system, analogous to the LPXTG/sortase system of Gram-positive bacteria, and correlated to EPS expression. It occurs preferentially in bacteria from sediments, soils, and biofilms. The novel method that led to these findings, partial phylogenetic profiling, requires neither global sequence clustering nor arbitrary similarity cutoffs and appears to be a rapid, effective alternative to other profiling methods.}, keywords = {Amino Acid Motifs, Amino Acid Sequence, bacteria, Bacterial Proteins, Biofilms, Genome, Bacterial, Markov chains, Molecular Sequence Data, Phylogeny, Polysaccharides, Bacterial, Protein Sorting Signals, Protein Transport, Seawater, sequence alignment, Soil Microbiology}, author = {Haft, Daniel H. and Paulsen, Ian T. and Ward, Naomi and J. Selengut} } @article {38287, title = {Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial "pan-genome"}, journal = {Proceedings of the National Academy of Sciences of the United States of AmericaProceedings of the National Academy of Sciences of the United States of America}, volume = {102}, year = {2005}, note = {http://www.ncbi.nlm.nih.gov/pubmed/16172379?dopt=Abstract}, type = {10.1073/pnas.0506758102}, abstract = {The development of efficient and inexpensive genome sequencing methods has revolutionized the study of human bacterial pathogens and improved vaccine design. Unfortunately, the sequence of a single genome does not reflect how genetic variability drives pathogenesis within a bacterial species and also limits genome-wide screens for vaccine candidates or for antimicrobial targets. We have generated the genomic sequence of six strains representing the five major disease-causing serotypes of Streptococcus agalactiae, the main cause of neonatal infection in humans. Analysis of these genomes and those available in databases showed that the S. agalactiae species can be described by a pan-genome consisting of a core genome shared by all isolates, accounting for approximately 80\% of any single genome, plus a dispensable genome consisting of partially shared and strain-specific genes. Mathematical extrapolation of the data suggests that the gene reservoir available for inclusion in the S. agalactiae pan-genome is vast and that unique genes will continue to be identified even after sequencing hundreds of genomes.}, keywords = {Amino Acid Sequence, Bacterial Capsules, Base Sequence, Gene expression, Genes, Bacterial, Genetic Variation, Genome, Bacterial, Molecular Sequence Data, Phylogeny, sequence alignment, Sequence Analysis, DNA, Streptococcus agalactiae, virulence}, author = {Tettelin, Herv{\'e} and Masignani, Vega and Cieslewicz, Michael J. and Donati, Claudio and Medini, Duccio and Ward, Naomi L. and Angiuoli, Samuel V. and Crabtree, Jonathan and Jones, Amanda L. and Durkin, A. Scott and DeBoy, Robert T. and Davidsen, Tanja M. and Mora, Marirosa and Scarselli, Maria and Margarit y Ros, Immaculada and Peterson, Jeremy D. and Hauser, Christopher R. and Sundaram, Jaideep P. and Nelson, William C. and Madupu, Ramana and Brinkac, Lauren M. and Dodson, Robert J. and Rosovitz, Mary J. and Sullivan, Steven A. and Daugherty, Sean C. and Haft, Daniel H. and J. Selengut and Gwinn, Michelle L. and Zhou, Liwei and Zafar, Nikhat and Khouri, Hoda and Radune, Diana and Dimitrov, George and Watkins, Kisha and O{\textquoteright}Connor, Kevin J. B. and Smith, Shannon and Utterback, Teresa R. and White, Owen and Rubens, Craig E. and Grandi, Guido and Madoff, Lawrence C. and Kasper, Dennis L. and Telford, John L. and Wessels, Michael R. and Rappuoli, Rino and Fraser, Claire M.} } @article {49683, title = {Reducing storage requirements for biological sequence comparison.}, journal = {Bioinformatics}, volume = {20}, year = {2004}, month = {2004 Dec 12}, pages = {3363-9}, abstract = {

MOTIVATION: Comparison of nucleic acid and protein sequences is a fundamental tool of modern bioinformatics. A dominant method of such string matching is the {\textquoteright}seed-and-extend{\textquoteright} approach, in which occurrences of short subsequences called {\textquoteright}seeds{\textquoteright} are used to search for potentially longer matches in a large database of sequences. Each such potential match is then checked to see if it extends beyond the seed. To be effective, the seed-and-extend approach needs to catalogue seeds from virtually every substring in the database of search strings. Projects such as mammalian genome assemblies and large-scale protein matching, however, have such large sequence databases that the resulting list of seeds cannot be stored in RAM on a single computer. This significantly slows the matching process.

RESULTS: We present a simple and elegant method in which only a small fraction of seeds, called {\textquoteright}minimizers{\textquoteright}, needs to be stored. Using minimizers can speed up string-matching computations by a large factor while missing only a small fraction of the matches found using all seeds.

}, keywords = {algorithms, Databases, Genetic, Information Storage and Retrieval, Numerical Analysis, Computer-Assisted, sequence alignment, Sequence Analysis}, issn = {1367-4803}, doi = {10.1093/bioinformatics/bth408}, author = {Roberts, Michael and Hayes, Wayne and Hunt, Brian R and Mount, Stephen M and Yorke, James A} } @article {38578, title = {X-ray crystal structure of the hypothetical phosphotyrosine phosphatase MDP-1 of the haloacid dehalogenase superfamily}, journal = {BiochemistryBiochemistry}, volume = {43}, year = {2004}, note = {http://www.ncbi.nlm.nih.gov/pubmed/15461449?dopt=Abstract}, type = {10.1021/bi0490688}, abstract = {The haloacid dehalogenase (HAD) superfamily is comprised of structurally homologous enzymes that share several conserved sequence motifs (loops I-IV) in their active site. The majority of HAD members are phosphohydrolases and may be divided into three subclasses depending on domain organization. In classes I and II, a mobile "cap" domain reorients upon substrate binding, closing the active site to bulk solvent. Members of the third class lack this additional domain. Herein, we report the 1.9 A X-ray crystal structures of a member of the third subclass, magnesium-dependent phosphatase-1 (MDP-1) both in its unliganded form and with the product analogue, tungstate, bound to the active site. The secondary structure of MDP-1 is similar to that of the "core" domain of other type I and type II HAD members with the addition of a small, 28-amino acid insert that does not close down to exclude bulk solvent in the presence of ligand. In addition, the monomeric oligomeric state of MDP-1 does not allow the participation of a second subunit in the formation and solvent protection of the active site. The binding sites for the phosphate portion of the substrate and Mg(II) cofactor are also similar to those of other HAD members, with all previously observed contacts conserved. Unlike other subclass III HAD members, MDP-1 appears to be equally able to dephosphorylate phosphotyrosine and closed-ring phosphosugars. Modeling of possible substrates in the active site of MDP-1 reveals very few potential interactions with the substrate leaving group. The mapping of conserved residues in sequences of MDP-1 from different eukaryotic organisms reveals that they colocalize to a large region on the surface of the protein outside the active site. This observation combined with the modeling studies suggests that the target of MDP-1 is most likely a phosphotyrosine in an unknown protein rather than a small sugar-based substrate.}, keywords = {Amino Acid Sequence, Animals, Binding Sites, Crystallography, X-Ray, HUMANS, Hydrogen-Ion Concentration, Hydrolases, Magnesium, Mice, Models, Molecular, Molecular Sequence Data, Phosphoprotein Phosphatases, Phosphotyrosine, Protein Phosphatase 1, Protein Structure, Quaternary, Protein Structure, Tertiary, sequence alignment, Solvents, Substrate Specificity}, author = {Peisach, Ezra and J. Selengut and Dunaway-Mariano, Debra and Allen, Karen N.} } @article {49685, title = {Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies.}, journal = {Nucleic Acids Res}, volume = {31}, year = {2003}, month = {2003 Oct 1}, pages = {5654-66}, abstract = {

The spliced alignment of expressed sequence data to genomic sequence has proven a key tool in the comprehensive annotation of genes in eukaryotic genomes. A novel algorithm was developed to assemble clusters of overlapping transcript alignments (ESTs and full-length cDNAs) into maximal alignment assemblies, thereby comprehensively incorporating all available transcript data and capturing subtle splicing variations. Complete and partial gene structures identified by this method were used to improve The Institute for Genomic Research Arabidopsis genome annotation (TIGR release v.4.0). The alignment assemblies permitted the automated modeling of several novel genes and >1000 alternative splicing variations as well as updates (including UTR annotations) to nearly half of the approximately 27 000 annotated protein coding genes. The algorithm of the Program to Assemble Spliced Alignments (PASA) tool is described, as well as the results of automated updates to Arabidopsis gene annotations.

}, keywords = {algorithms, Alternative Splicing, Arabidopsis, DNA, Complementary, Expressed Sequence Tags, Genome, Plant, Introns, Plant Proteins, RNA, Plant, sequence alignment, software, Transcription, Genetic, Untranslated Regions}, issn = {1362-4962}, author = {Haas, Brian J and Delcher, Arthur L and Mount, Stephen M and Wortman, Jennifer R and Smith, Roger K and Hannick, Linda I and Maiti, Rama and Ronning, Catherine M and Rusch, Douglas B and Town, Christopher D and Salzberg, Steven L and White, Owen} } @article {49631, title = {A new, expressed multigene family containing a hot spot for insertion of retroelements is associated with polymorphic subtelomeric regions of Trypanosoma brucei.}, journal = {Eukaryot Cell}, volume = {1}, year = {2002}, month = {2002 Feb}, pages = {137-51}, abstract = {

We describe a novel gene family that forms clusters in subtelomeric regions of Trypanosoma brucei chromosomes and partially accounts for the observed clustering of retrotransposons. The ingi and ribosomal inserted mobile element (RIME) non-LTR retrotransposons share 250 bp at both extremities and are the most abundant putatively mobile elements, with about 500 copies per haploid genome. From cDNA clones and subsequently in the T. brucei genomic DNA databases, we identified 52 homologous gene and pseudogene sequences, 16 of which contain a RIME and/or ingi retrotransposon inserted at exactly the same relative position. Here these genes are called the RHS family, for retrotransposon hot spot. Comparison of the protein sequences encoded by RHS genes (21 copies) and pseudogenes (24 copies) revealed a conserved central region containing an ATP/GTP-binding motif and the RIME/ingi insertion site. The RHS proteins share between 13 and 96\% identity, and six subfamilies, RHS1 to RHS6, can be defined on the basis of their divergent C-terminal domains. Immunofluorescence and Western blot analyses using RHS subfamily-specific immune sera show that RHS proteins are constitutively expressed and occur mainly in the nucleus. Analysis of Genome Survey Sequence databases indicated that the Trypanosoma brucei diploid genome contains about 280 RHS (pseudo)genes. Among the 52 identified RHS (pseudo)genes, 48 copies are in three RHS clusters located in subtelomeric regions of chromosomes Ia and II and adjacent to the active bloodstream form expression site in T. brucei strain TREU927/4 GUTat10.1. RHS genes comprise the remaining sequence of the size-polymorphic "repetitive region" described for T. brucei chromosome I, and a homologous gene family is present in the Trypanosoma cruzi genome.

}, keywords = {Amino Acid Sequence, Animals, Base Sequence, Cloning, Molecular, DNA Primers, DNA, Protozoan, Escherichia coli, Genes, Protozoan, Molecular Sequence Data, Multigene Family, Mutagenesis, Insertional, Phylogeny, Polymorphism, Genetic, Protozoan Proteins, Pseudogenes, Retroelements, sequence alignment, Sequence Homology, Amino Acid, Telomere, Trypanosoma brucei brucei, Trypanosoma cruzi}, issn = {1535-9778}, author = {Bringaud, Frederic and Biteau, Nicolas and Melville, Sara E and Hez, St{\'e}phanie and El-Sayed, Najib M and Leech, Vanessa and Berriman, Matthew and Hall, Neil and Donelson, John E and Baltz, Th{\'e}o} } @article {38368, title = {MDP-1 is a new and distinct member of the haloacid dehalogenase family of aspartate-dependent phosphohydrolases}, journal = {BiochemistryBiochemistry}, volume = {40}, year = {2001}, note = {http://www.ncbi.nlm.nih.gov/pubmed/11601995?dopt=Abstract}, abstract = {MDP-1 is a eukaryotic magnesium-dependent acid phosphatase with little sequence homology to previously characterized phosphatases. The presence of a conserved motif (Asp-X-Asp-X-Thr) in the N terminus of MDP-1 suggested a relationship to the haloacid dehalogenase (HAD) superfamily, which contains a number of magnesium-dependent acid phosphatases. These phosphatases utilize an aspartate nucleophile and contain a number of conserved active-site residues and hydrophobic patches, which can be plausibly aligned with conserved residues in MDP-1. Seven site-specific point mutants of MDP-1 were produced by modifying the catalytic aspartate, serine, and lysine residues to asparagine or glutamate, alanine, and arginine, respectively. The activity of these mutants confirms the assignment of MDP-1 as a member of the HAD superfamily. Detailed comparison of the sequence of the 15 MDP-1 sequences from various organisms with other HAD superfamily sequences suggests that MDP-1 is not closely related to any particular member of the superfamily. The crystal structures of several HAD family enzymes identify a domain proximal to the active site responsible for important interactions with low molecular weight substrates. The absence of this domain or any other that might perform the same function in MDP-1 suggests an "open" active site capable of interactions with large substrates such as proteins. This suggestion was experimentally confirmed by demonstration that MDP-1 is competent to catalyze the dephosphorylation of tyrosine-phosphorylated proteins.}, keywords = {Amino Acid Motifs, Amino Acid Sequence, Animals, Aspartic Acid, Catalytic Domain, HUMANS, Hydrolases, Mice, Molecular Sequence Data, Multigene Family, Mutagenesis, Site-Directed, Phosphoprotein Phosphatases, Protein Structure, Tertiary, Protein Tyrosine Phosphatases, Rats, Saccharomyces cerevisiae, sequence alignment, Sequence Homology, Amino Acid}, author = {J. Selengut} } @article {38110, title = {Analysis and prediction of functional sub-types from protein sequence alignments}, journal = {Journal of Molecular BiologyJournal of Molecular Biology}, volume = {303}, year = {2000}, type = {10.1006/jmbi.2000.4036}, abstract = {The increasing number and diversity of protein sequence families requires new methods to define and predict details regarding function. Here, we present a method for analysis and prediction of functional sub-types from multiple protein sequence alignments. Given an alignment and set of proteins grouped into sub-types according to some definition of function, such as enzymatic specificity, the method identifies positions that are indicative of functional differences by comparison of sub-type specific sequence profiles, and analysis of positional entropy in the alignment. Alignment positions with significantly high positional relative entropy correlate with those known to be involved in defining sub-types for nucleotidyl cyclases, protein kinases, lactate/malate dehydrogenases and trypsin-like serine proteases. We highlight new positions for these proteins that suggest additional experiments to elucidate the basis of specificity. The method is also able to predict sub-type for unclassified sequences. We assess several variations on a prediction method, and compare them to simple sequence comparisons. For assessment, we remove close homologues to the sequence for which a prediction is to be made (by a sequence identity above a threshold). This simulates situations where a protein is known to belong to a protein family, but is not a close relative of another protein of known sub-type. Considering the four families above, and a sequence identity threshold of 30 \%, our best method gives an accuracy of 96 \% compared to 80 \% obtained for sequence similarity and 74 \% for BLAST. We describe the derivation of a set of sub-type groupings derived from an automated parsing of alignments from PFAM and the SWISSPROT database, and use this to perform a large-scale assessment. The best method gives an average accuracy of 94 \% compared to 68 \% for sequence similarity and 79 \% for BLAST. We discuss implications for experimental design, genome annotation and the prediction of protein function and protein intra-residue distances.}, keywords = {prediction, protein function, protein structure, sequence alignment}, isbn = {0022-2836}, author = {Sridhar Hannenhalli and Russell, Robert B.} }