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1.  The sequence and de novo assembly of the giant panda genome 
Li, Ruiqiang | Fan, Wei | Tian, Geng | Zhu, Hongmei | He, Lin | Cai, Jing | Huang, Quanfei | Cai, Qingle | Li, Bo | Bai, Yinqi | Zhang, Zhihe | Zhang, Yaping | Wang, Wen | Li, Jun | Wei, Fuwen | Li, Heng | Jian, Min | Li, Jianwen | Zhang, Zhaolei | Nielsen, Rasmus | Li, Dawei | Gu, Wanjun | Yang, Zhentao | Xuan, Zhaoling | Ryder, Oliver A. | Leung, Frederick Chi-Ching | Zhou, Yan | Cao, Jianjun | Sun, Xiao | Fu, Yonggui | Fang, Xiaodong | Guo, Xiaosen | Wang, Bo | Hou, Rong | Shen, Fujun | Mu, Bo | Ni, Peixiang | Lin, Runmao | Qian, Wubin | Wang, Guodong | Yu, Chang | Nie, Wenhui | Wang, Jinhuan | Wu, Zhigang | Liang, Huiqing | Min, Jiumeng | Wu, Qi | Cheng, Shifeng | Ruan, Jue | Wang, Mingwei | Shi, Zhongbin | Wen, Ming | Liu, Binghang | Ren, Xiaoli | Zheng, Huisong | Dong, Dong | Cook, Kathleen | Shan, Gao | Zhang, Hao | Kosiol, Carolin | Xie, Xueying | Lu, Zuhong | Zheng, Hancheng | Li, Yingrui | Steiner, Cynthia C. | Lam, Tommy Tsan-Yuk | Lin, Siyuan | Zhang, Qinghui | Li, Guoqing | Tian, Jing | Gong, Timing | Liu, Hongde | Zhang, Dejin | Fang, Lin | Ye, Chen | Zhang, Juanbin | Hu, Wenbo | Xu, Anlong | Ren, Yuanyuan | Zhang, Guojie | Bruford, Michael W. | Li, Qibin | Ma, Lijia | Guo, Yiran | An, Na | Hu, Yujie | Zheng, Yang | Shi, Yongyong | Li, Zhiqiang | Liu, Qing | Chen, Yanling | Zhao, Jing | Qu, Ning | Zhao, Shancen | Tian, Feng | Wang, Xiaoling | Wang, Haiyin | Xu, Lizhi | Liu, Xiao | Vinar, Tomas | Wang, Yajun | Lam, Tak-Wah | Yiu, Siu-Ming | Liu, Shiping | Zhang, Hemin | Li, Desheng | Huang, Yan | Wang, Xia | Yang, Guohua | Jiang, Zhi | Wang, Junyi | Qin, Nan | Li, Li | Li, Jingxiang | Bolund, Lars | Kristiansen, Karsten | Wong, Gane Ka-Shu | Olson, Maynard | Zhang, Xiuqing | Li, Songgang | Yang, Huanming | Wang, Jian | Wang, Jun
Nature  2009;463(7279):311-317.
Using next-generation sequencing technology alone, we have successfully generated and assembled a draft sequence of the giant panda genome. The assembled contigs (2.25 gigabases (Gb)) cover approximately 94% of the whole genome, and the remaining gaps (0.05 Gb) seem to contain carnivore-specific repeats and tandem repeats. Comparisons with the dog and human showed that the panda genome has a lower divergence rate. The assessment of panda genes potentially underlying some of its unique traits indicated that its bamboo diet might be more dependent on its gut microbiome than its own genetic composition. We also identified more than 2.7 million heterozygous single nucleotide polymorphisms in the diploid genome. Our data and analyses provide a foundation for promoting mammalian genetic research, and demonstrate the feasibility for using next-generation sequencing technologies for accurate, cost-effective and rapid de novo assembly of large eukaryotic genomes.
doi:10.1038/nature08696
PMCID: PMC3951497  PMID: 20010809
2.  Transcriptome-Mining for Single-Copy Nuclear Markers in Ferns 
PLoS ONE  2013;8(10):e76957.
Background
Molecular phylogenetic investigations have revolutionized our understanding of the evolutionary history of ferns—the second-most species-rich major group of vascular plants, and the sister clade to seed plants. The general absence of genomic resources available for this important group of plants, however, has resulted in the strong dependence of these studies on plastid data; nuclear or mitochondrial data have been rarely used. In this study, we utilize transcriptome data to design primers for nuclear markers for use in studies of fern evolutionary biology, and demonstrate the utility of these markers across the largest order of ferns, the Polypodiales.
Principal Findings
We present 20 novel single-copy nuclear regions, across 10 distinct protein-coding genes: ApPEFP_C, cryptochrome 2, cryptochrome 4, DET1, gapCpSh, IBR3, pgiC, SQD1, TPLATE, and transducin. These loci, individually and in combination, show strong resolving power across the Polypodiales phylogeny, and are readily amplified and sequenced from our genomic DNA test set (from 15 diploid Polypodiales species). For each region, we also present transcriptome alignments of the focal locus and related paralogs—curated broadly across ferns—that will allow researchers to develop their own primer sets for fern taxa outside of the Polypodiales. Analyses of sequence data generated from our genomic DNA test set reveal strong effects of partitioning schemes on support levels and, to a much lesser extent, on topology. A model partitioned by codon position is strongly favored, and analyses of the combined data yield a Polypodiales phylogeny that is well-supported and consistent with earlier studies of this group.
Conclusions
The 20 single-copy regions presented here more than triple the single-copy nuclear regions available for use in ferns. They provide a much-needed opportunity to assess plastid-derived hypotheses of relationships within the ferns, and increase our capacity to explore aspects of fern evolution previously unavailable to scientific investigation.
doi:10.1371/journal.pone.0076957
PMCID: PMC3792871  PMID: 24116189
3.  Phylogeny and evolutionary history of glycogen synthase kinase 3/SHAGGY-like kinase genes in land plants 
Background
GSK3 (glycogen synthase kinase 3) genes encode signal transduction proteins with roles in a variety of biological processes in eukaryotes. In contrast to the low copy numbers observed in animals, GSK3 genes have expanded into a multi-gene family in land plants (embryophytes), and have also evolved functions in diverse plant specific processes, including floral development in angiosperms. However, despite previous efforts, the phylogeny of land plant GSK3 genes is currently unclear. Here, we analyze genes from a representative sample of phylogenetically pivotal taxa, including basal angiosperms, gymnosperms, and monilophytes, to reconstruct the evolutionary history and functional diversification of the GSK3 gene family in land plants.
Results
Maximum Likelihood phylogenetic analyses resolve a gene tree with four major gene duplication events that coincide with the emergence of novel land plant clades. The single GSK3 gene inherited from the ancestor of land plants was first duplicated along the ancestral branch to extant vascular plants, and three subsequent duplications produced three GSK3 loci in the ancestor of euphyllophytes, four in the ancestor of seed plants, and at least five in the ancestor of angiosperms. A single gene in the Amborella trichopoda genome may be the sole survivor of a sixth GSK3 locus that originated in the ancestor of extant angiosperms. Homologs of two Arabidopsis GSK3 genes with genetically confirmed roles in floral development, AtSK11 and AtSK12, exhibit floral preferential expression in several basal angiosperms, suggesting evolutionary conservation of their floral functions. Members of other gene lineages appear to have independently evolved roles in plant reproductive tissues in individual taxa.
Conclusions
Our phylogenetic analyses provide the most detailed reconstruction of GSK3 gene evolution in land plants to date and offer new insights into the origins, relationships, and functions of family members. Notably, the diversity of this “green” branch of the gene family has increased in concert with the increasing morphological and physiological complexity of land plant life forms. Expression data for seed plants indicate that the functions of GSK3 genes have also diversified during evolutionary time.
doi:10.1186/1471-2148-13-143
PMCID: PMC3710211  PMID: 23834366
GSK3; Land plant evolution; Gene duplication; Gene expression
4.  Identification of Hepatotropic Viruses from Plasma Using Deep Sequencing: A Next Generation Diagnostic Tool 
PLoS ONE  2013;8(4):e60595.
We conducted an unbiased metagenomics survey using plasma from patients with chronic hepatitis B, chronic hepatitis C, autoimmune hepatitis (AIH), non-alcoholic steatohepatitis (NASH), and patients without liver disease (control). RNA and DNA libraries were sequenced from plasma filtrates enriched in viral particles to catalog virus populations. Hepatitis viruses were readily detected at high coverage in patients with chronic viral hepatitis B and C, but only a limited number of sequences resembling other viruses were found. The exception was a library from a patient diagnosed with hepatitis C virus (HCV) infection that contained multiple sequences matching GB virus C (GBV-C). Abundant GBV-C reads were also found in plasma from patients with AIH, whereas Torque teno virus (TTV) was found at high frequency in samples from patients with AIH and NASH. After taxonomic classification of sequences by BLASTn, a substantial fraction in each library, ranging from 35% to 76%, remained unclassified. These unknown sequences were assembled into scaffolds along with virus, phage and endogenous retrovirus sequences and then analyzed by BLASTx against the non-redundant protein database. Nearly the full genome of a heretofore-unknown circovirus was assembled and many scaffolds that encoded proteins with similarity to plant, insect and mammalian viruses. The presence of this novel circovirus was confirmed by PCR. BLASTx also identified many polypeptides resembling nucleo-cytoplasmic large DNA viruses (NCLDV) proteins. We re-evaluated these alignments with a profile hidden Markov method, HHblits, and observed inconsistencies in the target proteins reported by the different algorithms. This suggests that sequence alignments are insufficient to identify NCLDV proteins, especially when these alignments are only to small portions of the target protein. Nevertheless, we have now established a reliable protocol for the identification of viruses in plasma that can also be adapted to other patient samples such as urine, bile, saliva and other body fluids.
doi:10.1371/journal.pone.0060595
PMCID: PMC3629200  PMID: 23613733
5.  Evaluating Methods for Isolating Total RNA and Predicting the Success of Sequencing Phylogenetically Diverse Plant Transcriptomes 
PLoS ONE  2012;7(11):e50226.
Next-generation sequencing plays a central role in the characterization and quantification of transcriptomes. Although numerous metrics are purported to quantify the quality of RNA, there have been no large-scale empirical evaluations of the major determinants of sequencing success. We used a combination of existing and newly developed methods to isolate total RNA from 1115 samples from 695 plant species in 324 families, which represents >900 million years of phylogenetic diversity from green algae through flowering plants, including many plants of economic importance. We then sequenced 629 of these samples on Illumina GAIIx and HiSeq platforms and performed a large comparative analysis to identify predictors of RNA quality and the diversity of putative genes (scaffolds) expressed within samples. Tissue types (e.g., leaf vs. flower) varied in RNA quality, sequencing depth and the number of scaffolds. Tissue age also influenced RNA quality but not the number of scaffolds ≥1000 bp. Overall, 36% of the variation in the number of scaffolds was explained by metrics of RNA integrity (RIN score), RNA purity (OD 260/230), sequencing platform (GAIIx vs HiSeq) and the amount of total RNA used for sequencing. However, our results show that the most commonly used measures of RNA quality (e.g., RIN) are weak predictors of the number of scaffolds because Illumina sequencing is robust to variation in RNA quality. These results provide novel insight into the methods that are most important in isolating high quality RNA for sequencing and assembling plant transcriptomes. The methods and recommendations provided here could increase the efficiency and decrease the cost of RNA sequencing for individual labs and genome centers.
doi:10.1371/journal.pone.0050226
PMCID: PMC3504007  PMID: 23185583
6.  A genome triplication associated with early diversification of the core eudicots 
Genome Biology  2012;13(1):R3.
Background
Although it is agreed that a major polyploidy event, gamma, occurred within the eudicots, the phylogenetic placement of the event remains unclear.
Results
To determine when this polyploidization occurred relative to speciation events in angiosperm history, we employed a phylogenomic approach to investigate the timing of gene set duplications located on syntenic gamma blocks. We populated 769 putative gene families with large sets of homologs obtained from public transcriptomes of basal angiosperms, magnoliids, asterids, and more than 91.8 gigabases of new next-generation transcriptome sequences of non-grass monocots and basal eudicots. The overwhelming majority (95%) of well-resolved gamma duplications was placed before the separation of rosids and asterids and after the split of monocots and eudicots, providing strong evidence that the gamma polyploidy event occurred early in eudicot evolution. Further, the majority of gene duplications was placed after the divergence of the Ranunculales and core eudicots, indicating that the gamma appears to be restricted to core eudicots. Molecular dating estimates indicate that the duplication events were intensely concentrated around 117 million years ago.
Conclusions
The rapid radiation of core eudicot lineages that gave rise to nearly 75% of angiosperm species appears to have occurred coincidentally or shortly following the gamma triplication event. Reconciliation of gene trees with a species phylogeny can elucidate the timing of major events in genome evolution, even when genome sequences are only available for a subset of species represented in the gene trees. Comprehensive transcriptome datasets are valuable complements to genome sequences for high-resolution phylogenomic analysis.
doi:10.1186/gb-2012-13-1-r3
PMCID: PMC3334584  PMID: 22280555
7.  The diploid genome sequence of an Asian individual 
Nature  2008;456(7218):60-65.
Here we present the first diploid genome sequence of an Asian individual. The genome was sequenced to 36-fold average coverage using massively parallel sequencing technology. We aligned the short reads onto the NCBI human reference genome to 99.97% coverage, and guided by the reference genome, we used uniquely mapped reads to assemble a high-quality consensus sequence for 92% of the Asian individual's genome. We identified approximately 3 million single-nucleotide polymorphisms (SNPs) inside this region, of which 13.6% were not in the dbSNP database. Genotyping analysis showed that SNP identification had high accuracy and consistency, indicating the high sequence quality of this assembly. We also carried out heterozygote phasing and haplotype prediction against HapMap CHB and JPT haplotypes (Chinese and Japanese, respectively), sequence comparison with the two available individual genomes (J. D. Watson and J. C. Venter), and structural variation identification. These variations were considered for their potential biological impact. Our sequence data and analyses demonstrate the potential usefulness of next-generation sequencing technologies for personal genomics.
doi:10.1038/nature07484
PMCID: PMC2716080  PMID: 18987735
8.  Gene conversion in the rice genome 
BMC Genomics  2008;9:93.
Background
Gene conversion causes a non-reciprocal transfer of genetic information between similar sequences. Gene conversion can both homogenize genes and recruit point mutations thereby shaping the evolution of multigene families. In the rice genome, the large number of duplicated genes increases opportunities for gene conversion.
Results
To characterize gene conversion in rice, we have defined 626 multigene families in which 377 gene conversions were detected using the GENECONV program. Over 60% of the conversions we detected were between chromosomes. We found that the inter-chromosomal conversions distributed between chromosome 1 and 5, 2 and 6, and 3 and 5 are more frequent than genome average (Z-test, P < 0.05). The frequencies of gene conversion on the same chromosome decreased with the physical distance between gene conversion partners. Ka/Ks analysis indicates that gene conversion is not tightly linked to natural selection in the rice genome. To assess the contribution of segmental duplication on gene conversion statistics, we determined locations of conversion partners with respect to inter-chromosomal segment duplication. The number of conversions associated with segmentation is less than ten percent. Pseudogenes in the rice genome with low similarity to Arabidopsis genes showed greater likelihood for gene conversion than those with high similarity to Arabidopsis genes. Functional annotations suggest that at least 14 multigene families related to disease or bacteria resistance were involved in conversion events.
Conclusion
The evolution of gene families in the rice genome may have been accelerated by conversion with pseudogenes. Our analysis suggests a possible role for gene conversion in the evolution of pathogen-response genes.
doi:10.1186/1471-2164-9-93
PMCID: PMC2277409  PMID: 18298833
9.  A cross-species alignment tool (CAT) 
BMC Bioinformatics  2007;8:349.
Background
The main two sorts of automatic gene annotation frameworks are ab initio and alignment-based, the latter splitting into two sub-groups. The first group is used for intra-species alignments, among which are successful ones with high specificity and speed. The other group contains more sensitive methods which are usually applied in aligning inter-species sequences.
Results
Here we present a new algorithm called CAT (for Cross-species Alignment Tool). It is designed to align mRNA sequences to mammalian-sized genomes. CAT is implemented using C scripts and is freely available on the web at .
Conclusions
Examined from different angles, CAT outperforms other extant alignment tools. Tested against all available mouse-human and zebrafish-human orthologs, we demonstrate that CAT combines the specificity and speed of the best intra-species algorithms, like BLAT and sim4, with the sensitivity of the best inter-species tools, like GeneWise.
doi:10.1186/1471-2105-8-349
PMCID: PMC2082505  PMID: 17880681
10.  Identification and characterization of insect-specific proteins by genome data analysis 
BMC Genomics  2007;8:93.
Background
Insects constitute the vast majority of known species with their importance including biodiversity, agricultural, and human health concerns. It is likely that the successful adaptation of the Insecta clade depends on specific components in its proteome that give rise to specialized features. However, proteome determination is an intensive undertaking. Here we present results from a computational method that uses genome analysis to characterize insect and eukaryote proteomes as an approximation complementary to experimental approaches.
Results
Homologs in common to Drosophila melanogaster, Anopheles gambiae, Bombyx mori, Tribolium castaneum, and Apis mellifera were compared to the complete genomes of three non-insect eukaryotes (opisthokonts) Homo sapiens, Caenorhabditis elegans and Saccharomyces cerevisiae. This operation yielded 154 groups of orthologous proteins in Drosophila to be insect-specific homologs; 466 groups were determined to be common to eukaryotes (represented by three opisthokonts). ESTs from the hemimetabolous insect Locust migratoria were also considered in order to approximate their corresponding genes in the insect-specific homologs. Stress and stimulus response proteins were found to constitute a higher fraction in the insect-specific homologs than in the homologs common to eukaryotes.
Conclusion
The significant representation of stress response and stimulus response proteins in proteins determined to be insect-specific, along with specific cuticle and pheromone/odorant binding proteins, suggest that communication and adaptation to environments may distinguish insect evolution relative to other eukaryotes. The tendency for low Ka/Ks ratios in the insect-specific protein set suggests purifying selection pressure. The generally larger number of paralogs in the insect-specific proteins may indicate adaptation to environment changes. Instances in our insect-specific protein set have been arrived at through experiments reported in the literature, supporting the accuracy of our approach.
doi:10.1186/1471-2164-8-93
PMCID: PMC1852559  PMID: 17407609
11.  TreeFam: a curated database of phylogenetic trees of animal gene families 
Nucleic Acids Research  2005;34(Database issue):D572-D580.
TreeFam is a database of phylogenetic trees of gene families found in animals. It aims to develop a curated resource that presents the accurate evolutionary history of all animal gene families, as well as reliable ortholog and paralog assignments. Curated families are being added progressively, based on seed alignments and trees in a similar fashion to Pfam. Release 1.1 of TreeFam contains curated trees for 690 families and automatically generated trees for another 11 646 families. These represent over 128 000 genes from nine fully sequenced animal genomes and over 45 000 other animal proteins from UniProt; ∼40–85% of proteins encoded in the fully sequenced animal genomes are included in TreeFam. TreeFam is freely available at and .
doi:10.1093/nar/gkj118
PMCID: PMC1347480  PMID: 16381935
12.  ReAS: Recovery of Ancestral Sequences for Transposable Elements from the Unassembled Reads of a Whole Genome Shotgun 
PLoS Computational Biology  2005;1(4):e43.
We describe an algorithm, ReAS, to recover ancestral sequences for transposable elements (TEs) from the unassembled reads of a whole genome shotgun. The main assumptions are that these TEs must exist at high copy numbers across the genome and must not be so old that they are no longer recognizable in comparison to their ancestral sequences. Tested on the japonica rice genome, ReAS was able to reconstruct all of the high copy sequences in the Repbase repository of known TEs, and increase the effectiveness of RepeatMasker in identifying TEs from genome sequences.
Synopsis
Transposable elements (TEs) are a major component of the genomes of multicellular organisms. They are parasitic creatures that invade the genome, insert multiple copies of themselves, and then die. All we see now are the decayed remnants of their ancestral sequences. Reconstruction of these ancestral sequences can bring dead TEs back to life. Algorithms for detecting TEs compare present-day sequences to a library of ancestral sequences. Unknown to many, pervasive use of whole genome shotgun (WGS) methods in large-scale sequencing have made TE reconstructions increasingly problematic. To minimize assembly errors, WGS methods must reject the highly repetitive sequences that characterize most TEs, especially the most recent TEs, which are the least diverged from their ancestral sequences (and most informative for reconstruction). This is acceptable to many, because the most important parts of the genes are not repetitive, but for the TE aficionados, it is a problem. ReAS is a novel algorithm that does TE reconstruction using only the unassembled reads of a WGS. Tested against the WGS for japonica rice, it is shown to produce a library that is superior to the manually curated Repbase database of known ancestral TEs.
doi:10.1371/journal.pcbi.0010043
PMCID: PMC1232128  PMID: 16184192
13.  BGI-RIS: an integrated information resource and comparative analysis workbench for rice genomics 
Nucleic Acids Research  2004;32(Database issue):D377-D382.
Rice is a major food staple for the world’s population and serves as a model species in cereal genome research. The Beijing Genomics Institute (BGI) has long been devoting itself to sequencing, information analysis and biological research of the rice and other crop genomes. In order to facilitate the application of the rice genomic information and to provide a foundation for functional and evolutionary studies of other important cereal crops, we implemented our Rice Information System (BGI-RIS), the most up-to-date integrated information resource as well as a workbench for comparative genomic analysis. In addition to comprehensive data from Oryza sativa L. ssp. indica sequenced by BGI, BGI-RIS also hosts carefully curated genome information from Oryza sativa L. ssp. japonica and EST sequences available from other cereal crops. In this resource, sequence contigs of indica (93-11) have been further assembled into Mbp-sized scaffolds and anchored onto the rice chromosomes referenced to physical/genetic markers, cDNAs and BAC-end sequences. We have annotated the rice genomes for gene content, repetitive elements, gene duplications (tandem and segmental) and single nucleotide polymorphisms between rice subspecies. Designed as a basic platform, BGI-RIS presents the sequenced genomes and related information in systematic and graphical ways for the convenience of in-depth comparative studies (http://rise.genomics.org.cn/).
doi:10.1093/nar/gkh085
PMCID: PMC308819  PMID: 14681438
14.  The Genomes of Oryza sativa: A History of Duplications 
Yu, Jun | Wang, Jun | Lin, Wei | Li, Songgang | Li, Heng | Zhou, Jun | Ni, Peixiang | Dong, Wei | Hu, Songnian | Zeng, Changqing | Zhang, Jianguo | Zhang, Yong | Li, Ruiqiang | Xu, Zuyuan | Li, Shengting | Li, Xianran | Zheng, Hongkun | Cong, Lijuan | Lin, Liang | Yin, Jianning | Geng, Jianing | Li, Guangyuan | Shi, Jianping | Liu, Juan | Lv, Hong | Li, Jun | Wang, Jing | Deng, Yajun | Ran, Longhua | Shi, Xiaoli | Wang, Xiyin | Wu, Qingfa | Li, Changfeng | Ren, Xiaoyu | Wang, Jingqiang | Wang, Xiaoling | Li, Dawei | Liu, Dongyuan | Zhang, Xiaowei | Ji, Zhendong | Zhao, Wenming | Sun, Yongqiao | Zhang, Zhenpeng | Bao, Jingyue | Han, Yujun | Dong, Lingli | Ji, Jia | Chen, Peng | Wu, Shuming | Liu, Jinsong | Xiao, Ying | Bu, Dongbo | Tan, Jianlong | Yang, Li | Ye, Chen | Zhang, Jingfen | Xu, Jingyi | Zhou, Yan | Yu, Yingpu | Zhang, Bing | Zhuang, Shulin | Wei, Haibin | Liu, Bin | Lei, Meng | Yu, Hong | Li, Yuanzhe | Xu, Hao | Wei, Shulin | He, Ximiao | Fang, Lijun | Zhang, Zengjin | Zhang, Yunze | Huang, Xiangang | Su, Zhixi | Tong, Wei | Li, Jinhong | Tong, Zongzhong | Li, Shuangli | Ye, Jia | Wang, Lishun | Fang, Lin | Lei, Tingting | Chen, Chen | Chen, Huan | Xu, Zhao | Li, Haihong | Huang, Haiyan | Zhang, Feng | Xu, Huayong | Li, Na | Zhao, Caifeng | Li, Shuting | Dong, Lijun | Huang, Yanqing | Li, Long | Xi, Yan | Qi, Qiuhui | Li, Wenjie | Zhang, Bo | Hu, Wei | Zhang, Yanling | Tian, Xiangjun | Jiao, Yongzhi | Liang, Xiaohu | Jin, Jiao | Gao, Lei | Zheng, Weimou | Hao, Bailin | Liu, Siqi | Wang, Wen | Yuan, Longping | Cao, Mengliang | McDermott, Jason | Samudrala, Ram | Wang, Jian | Wong, Gane Ka-Shu | Yang, Huanming
PLoS Biology  2005;3(2):e38.
We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family.
Comparative genome sequencing of indica and japonica rice reveals that duplication of genes and genomic regions has played a major part in the evolution of grass genomes
doi:10.1371/journal.pbio.0030038
PMCID: PMC546038  PMID: 15685292

Results 1-14 (14)