Abstract:The enrichment of duplicate genes, and therefore paralogs (proteins coded by duplicate genes), in multicellular versus unicellular organisms enhances genomic functional innovation. This study quantitatively examined relationships among paralog enrichment, expression pattern diversification and multicellularity, aiming to better understand genomic basis of multicellularity. Paralog abundance in specific cells was compared with those in unicellular proteomes and the whole proteomes of multicellular organisms. Th… Show more
“…Our results (Fig. 6c ) show that, similar to what has been observed in Caenorhabditis elegans and human [ 40 ], variability in gene expression increases with the number of paralogs. Fig.…”
BackgroundLegumes are the third largest family of angiosperms and the second most important crop class. Legume genomes have been shaped by extensive large-scale gene duplications, including an approximately 58 million year old whole genome duplication shared by most crop legumes.ResultsWe report the genome and the transcription atlas of coding and non-coding genes of a Mesoamerican genotype of common bean (Phaseolus vulgaris L., BAT93). Using a comprehensive phylogenomics analysis, we assessed the past and recent evolution of common bean, and traced the diversification of patterns of gene expression following duplication. We find that successive rounds of gene duplications in legumes have shaped tissue and developmental expression, leading to increased levels of specialization in larger gene families. We also find that many long non-coding RNAs are preferentially expressed in germ-line-related tissues (pods and seeds), suggesting that they play a significant role in fruit development. Our results also suggest that most bean-specific gene family expansions, including resistance gene clusters, predate the split of the Mesoamerican and Andean gene pools.ConclusionsThe genome and transcriptome data herein generated for a Mesoamerican genotype represent a counterpart to the genomic resources already available for the Andean gene pool. Altogether, this information will allow the genetic dissection of the characters involved in the domestication and adaptation of the crop, and their further implementation in breeding strategies for this important crop.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-0883-6) contains supplementary material, which is available to authorized users.
“…Our results (Fig. 6c ) show that, similar to what has been observed in Caenorhabditis elegans and human [ 40 ], variability in gene expression increases with the number of paralogs. Fig.…”
BackgroundLegumes are the third largest family of angiosperms and the second most important crop class. Legume genomes have been shaped by extensive large-scale gene duplications, including an approximately 58 million year old whole genome duplication shared by most crop legumes.ResultsWe report the genome and the transcription atlas of coding and non-coding genes of a Mesoamerican genotype of common bean (Phaseolus vulgaris L., BAT93). Using a comprehensive phylogenomics analysis, we assessed the past and recent evolution of common bean, and traced the diversification of patterns of gene expression following duplication. We find that successive rounds of gene duplications in legumes have shaped tissue and developmental expression, leading to increased levels of specialization in larger gene families. We also find that many long non-coding RNAs are preferentially expressed in germ-line-related tissues (pods and seeds), suggesting that they play a significant role in fruit development. Our results also suggest that most bean-specific gene family expansions, including resistance gene clusters, predate the split of the Mesoamerican and Andean gene pools.ConclusionsThe genome and transcriptome data herein generated for a Mesoamerican genotype represent a counterpart to the genomic resources already available for the Andean gene pool. Altogether, this information will allow the genetic dissection of the characters involved in the domestication and adaptation of the crop, and their further implementation in breeding strategies for this important crop.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-0883-6) contains supplementary material, which is available to authorized users.
“…We downloaded the PhosphoSitePlus database (www.phosphosite.org) dataset and counted the number of unique experimentally verified substrates for each human protein kinases, revealing that human AKT1 has 215 unique substrates (45). As many other cell biology parameters (46)(47)(48)(49), the substrate count (K) of the human kinome follows the so-called scalefree distribution, i.e., P (k) ∝ K −α or log 2 (P (k) ) ∝ -α*log 2 (K), with P (K) as the portion of protein kinases with K unique substrates and α as a positive constant. This is illustrated in the linear relationship in a log-log plot (log 2 (P (k) vs. log 2 (K)) in Figure 3.…”
Section: Generation and Expression Of Mutant Akt1 Kinasementioning
The human kinome contains >500 protein kinases, and regulates up to 30% of all human proteins. Kinase study is currently hindered by a lack of in vivo analysis approaches, mainly due to two factors: our inability to distinguish the kinase reaction of interest from those of other members of the kinome in live cells and the cell impermeability of the ATP analogs. Herein, we aimed to overcome this issue by combining the widely used chemical genetic method developed by Dr. Kevan Shokat and colleagues with nanoparticle-mediated intracellular delivery of the ATP analog. The critical AKT1 protein kinase, which has been successfully studied with the Shokat method, was used as our initial prototype. Briefly, following the Shokat method, enlargement of the ATP binding pocket was performed by mutating the gate-keeper Methionine residue to a Glycine, prompting the mutant AKT1 to preferentially use the bulky ATP analog N 6 -Benzyl-ATP-γ-S (A*TPγS) and, thus, differentiating AKT1-catalyzed and other phosphorylation events. The LPC nanoparticle was used for efficient intracellular delivery of A*TPγS, overcoming the cell impermeability issue. We demonstrated that the mutant, but not the wild type, AKT1 was able to use the delivered A*TPγS for autophosphorylation as well as phosphorylating its substrates in live cells. Thus, an in vivo protein kinase analysis method has been developed. The strategy should be widely applicable to other protein kinases.
“…The distribution is long known to be un-even; a small number of miRNAs target extra-ordinarily high numbers of mRNAs, and a small number of mRNAs contain extra-ordinarily high numbers of binding sites (28). Using evolutionally conserved miRNA-target relationships in the TargetScan database (11), we showed that the miRNA binding site distribution pattern can be described quantitatively by the so-called scale-free relationship (P (k) ∝ (K+a) -α , with P (K) as the number of mRNAs containing K unique binding sites; a and α positive constants) (27), which is commonly seen in many domains of biology such as regulatory networks and protein family size distribution (29)(30)(31). This is shown in figure 1.…”
Section: The Mirna Binding Site Distribution Patternmentioning
The miRNA pathway consists of three segments -biogenesis, targeting and downstream regulatory effectors. How the cells control their activities remains incompletely understood. This study explored the intrinsically complex miRNA-mRNA targeting relationships, and suggested differential mechanistic control of the three segments. We first analyzed evolutionarily conserved sites for conserved miRNAs in the human transcriptome. Strikingly, AGO1, AGO2 and AGO3 are all among the top 14 mRNAs with highest numbers of unique conserved miRNA sites, and so is ANKRD52, the phosphatase regulatory subunit of the recently identified AGO phosphorylation cycle (AGOs, CSNK1A1, ANKRD52 and PPP6C). The mRNAs for TNRC6, which acts together with loaded AGO to channel miRNA-mediated regulation actions onto specific mRNAs, are also heavily miRNA-targeted. Moreover, mRNAs of the AGO phosphorylation cycle share much more than expected miRNA binding sites. In contrast, upstream miRNA biogenesis mRNAs do not display these characteristics, and neither do the downstream regulatory effector mRNAs. In a word, miRNAs heavily and directly feedbackregulate their targeting machinery mRNAs, but neither upstream biogenesis nor downstream regulatory effector mRNAs. The observation was then confirmed with experimentally determined miRNA-mRNA target relationships. In summary, our exploration of the miRNA-mRNA target relationship uncovers intensive, and specific, feedback auto-regulation of miRNA targeting activity directly by miRNAs themselves, i.e., segment-specific feedback autoregulation of miRNA pathway. Our results also suggest that the complexity of miRNA-mRNA targeting relationship -a defining feature of miRNA biology -should be a rich source for further functional exploration.
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