Evolution of a domain conserved in microtubule-associated proteins of eukaryotes

The microtubule network, the major organelle of the eukaryotic cytoskeleton, is involved in cell division and differentiation but also with many other cellular functions. In plants, microtubules seem to be involved in the ordered deposition of cellulose microfibrils by a so far unknown mechanism. Microtubule-associated proteins (MAP) typically contain various domains targeting or binding proteins with different functions to microtubules. Here we have investigated a proposed microtubule-targeting domain, TPX2, first identified in the Kinesin-like protein 2 in Xenopus. A TPX2 containing microtubule binding protein, PttMAP20, has been recently identified in poplar tissues undergoing xylogenesis. Furthermore, the herbicide 2,6-dichlorobenzonitrile (DCB), which is a known inhibitor of cellulose synthesis, was shown to bind specifically to PttMAP20. It is thus possible that PttMAP20 may have a role in coupling cellulose biosynthesis and the microtubular networks in poplar secondary cell walls. In order to get more insight into the occurrence, evolution and potential functions of TPX2-containing proteins we have carried out bioinformatic analysis for all genes so far found to encode TPX2 domains with special reference to poplar PttMAP20 and its putative orthologs in other plants

GAM-NGS: genomic assemblies merger for next generation sequencing

Background: In recent years more than 20 assemblers have been proposed to tackle the hard task of assembling NGS data. A common heuristic when assembling a genome is to use several assemblers and then select the best assembly according to some criteria. However, recent results clearly show that some assemblers lead to better statistics than others on specific regions but are outperformed on other regions or on different evaluation measures. To limit these problems we developed GAM-NGS (Genomic Assemblies Merger for Next Generation Sequencing), whose primary goal is to merge two or more assemblies in order to enhance contiguity and correctness of both. GAM-NGS does not rely on global alignment: regions of the two assemblies representing the same genomic locus (called blocks) are identified through reads' alignments and stored in a weighted graph. The merging phase is carried out with the help of this weighted graph that allows an optimal resolution of local problematic regions.Results: GAM-NGS has been tested on six different datasets and compared to other assembly reconciliation tools. The availability of a reference sequence for three of them allowed us to show how GAM-NGS is a tool able to output an improved reliable set of sequences. GAM-NGS is also a very efficient tool able to merge assemblies using substantially less computational resources than comparable tools. In order to achieve such goals, GAM-NGS avoids global alignment between contigs, making its strategy unique among other assembly reconciliation tools.Conclusions: The difficulty to obtain correct and reliable assemblies using a single assembler is forcing the introduction of new algorithms able to enhance de novo assemblies. GAM-NGS is a tool able to merge two or more assemblies in order to improve contiguity and correctness. It can be used on all NGS-based assembly projects and it shows its full potential with multi-library Illumina-based projects. With more than 20 available assemblers it is hard to select the best tool. In this context we propose a tool that improves assemblies (and, as a by-product, perhaps even assemblers) by merging them and selecting the generating that is most likely to be correct

Kajian Bentuk Dan Sensitivitas Rumus Indeks Pi, Storet, Ccme Untuk Penentuan Status Mutu Perairan Sungai Tropis Di Indonesia (Assessment of the Forms and Sensitivity of the Index Formula Pi, Storet, Ccme for the Determination of Water Quality Status)

Metode-metode Pollution Index (USA), metode Storet (USA) dan metode CCME (Canada) adalah metode indeks kualitas air (IKA) untuk penentuan status mutu air. Dua yang pertama banyak digunakan praktisi lingkungan di Indonesia karena dirujuk dalam Keputusan Menteri Lingkungan Hidup No. 115/2013. Ketiganya dapat menghitung IKA dengan baku mutu kualitas air lokal sungai kajian. Mengingat negara penyusun metode tersebut berbeda kondisi lingkungannya dan masing-masing metode mempunyai faktor spesifik untuk menghitung IKA, maka perlu dikaji kesesuaian masing-masing metode untuk diterapkan di sungai tropis Indonesia. Masing-masing metode akan dikaji bentuk persamaan dan sensitivitasnya dengan menggunakan banyak parameter kualitas air dan menggunakan jumlah parameter kualitas air tertentu mengacu pada metode IKA yang dikembangkan di negara tropis lainnya. Kajian menggunakan data pemantauan “Prokasih” di sungai Gadjah Wong Yogyakarta tahun 1996/1997 - 2011/2012. Penelitian ini dilakukan dalam rangka menyusun metode IKA sungai tropis Indonesia pada umumnya dan di sungai Gadjah Wong khususnya serta program pengelolaan kualitas air untuk pengendalian pencemaran air sungai, dengan target konservasi air sungai yang multifungsi atau overall/general use(memenuhi kriteria kesehatan air baku, memenuhi kriteria estetika serta kriteria ekologi/aman bagi kehidupan di perairan). Hasil kajian menunjukkan bahwa dibandingkan 2 metode lainnya, metode CCME dinilai paling obyektif (secara statistik) menghitung IKA perairan sungai Gadjah Wong. CCME paling sensitif merespon dinamika indeks mutu air di setiap lokasi pemantauan, lebih universal untuk dapat diaplikasikan di luar negara penyusunnya. Namun untuk diaplikasikan di sungai Gadjah Wong, metode CCME perlu diadaptasi terhadap beberapa hal yaitu jumlah dan jenis parameter kualitas air yang dianggap signifikan, jumlah dan kelas mutu air. Adaptasi mempertimbangkan program pengendalian pencemaran air dan strategi operasional/manajemen aliran sungai yang ekologis dan berkelanjutan. Skor batas dan makna setiap kelas mutu air dalam IKA harus diverifikasi terhadap data lingkungan lain misal hasil biotilik ataupun bioassay sehingga status indeks kualitas air tidak bertentangan dengan kondisi biologi di sungai. Pelibatan parameter bakteriologi kualitas air (Escherichia Coli dan Total Coliform) serta Electric Conductivity/EC sebagai parameter kualitas air signifikan dalam metode IKA masih perlu dikaji lebih lanjut untuk pengembangan metode IKA khas perairan sungai di negara tropis Indonesia

Genome-Wide Survey for Biologically Functional Pseudogenes

According to current estimates there exist about 20,000 pseudogenes in a mammalian genome. The vast majority of these are disabled and nonfunctional copies of protein-coding genes which, therefore, evolve neutrally. Recent findings that a Makorin1 pseudogene, residing on mouse Chromosome 5, is, indeed, in vivo vital and also evolutionarily preserved, encouraged us to conduct a genome-wide survey for other functional pseudogenes in human, mouse, and chimpanzee. We identify to our knowledge the first examples of conserved pseudogenes common to human and mouse, originating from one duplication predating the human–mouse species split and having evolved as pseudogenes since the species split. Functionality is one possible way to explain the apparently contradictory properties of such pseudogene pairs, i.e., high conservation and ancient origin. The hypothesis of functionality is tested by comparing expression evidence and synteny of the candidates with proper test sets. The tests suggest potential biological function. Our candidate set includes a small set of long-lived pseudogenes whose unknown potential function is retained since before the human–mouse species split, and also a larger group of primate-specific ones found from human–chimpanzee searches. Two processed sequences are notable, their conservation since the human–mouse split being as high as most protein-coding genes; one is derived from the protein Ataxin 7-like 3 (ATX7NL3), and one from the Spinocerebellar ataxia type 1 protein (ATX1). Our approach is comparative and can be applied to any pair of species. It is implemented by a semi-automated pipeline based on cross-species BLAST comparisons and maximum-likelihood phylogeny estimations. To separate pseudogenes from protein-coding genes, we use standard methods, utilizing in-frame disablements, as well as a probabilistic filter based on Ka/Ks ratios