Selenoprotein gene nomenclature

The human genome contains 25 genes coding for selenocysteine-containing proteins (selenoproteins). These proteins are involved in a variety of functions, most notably redox homeostasis. Selenoprotein enzymes with known functions are designated according to these functions: TXNRD1, TXNRD2, and TXNRD3 (thioredoxin reductases), GPX1, GPX2, GPX3, GPX4 and GPX6 (glutathione peroxidases), DIO1, DIO2, and DIO3 (iodothyronine deiodinases), MSRB1 (methionine-R-sulfoxide reductase 1) and SEPHS2 (selenophosphate synthetase 2). Selenoproteins without known functions have traditionally been denoted by SEL or SEP symbols. However, these symbols are sometimes ambiguous and conflict with the approved nomenclature for several other genes. Therefore, there is a need to implement a rational and coherent nomenclature system for selenoprotein-encoding genes. Our solution is to use the root symbol SELENO followed by a letter. This nomenclature applies to SELENOF (selenoprotein F, the 15 kDa selenoprotein, SEP15), SELENOH (selenoprotein H, SELH, C11orf31), SELENOI (selenoprotein I, SELI, EPT1), SELENOK (selenoprotein K, SELK), SELENOM (selenoprotein M, SELM), SELENON (selenoprotein N, SEPN1, SELN), SELENOO (selenoprotein O, SELO), SELENOP (selenoprotein P, SeP, SEPP1, SELP), SELENOS (selenoprotein S, SELS, SEPS1, VIMP), SELENOT (selenoprotein T, SELT), SELENOV (selenoprotein V, SELV) and SELENOW (selenoprotein W, SELW, SEPW1). This system, approved by the HUGO Gene Nomenclature Committee, also resolves conflicting, missing and ambiguous designations for selenoprotein genes and is applicable to selenoproteins across vertebrates

Agricultural soils: a sink or source of methane across the British Isles?

This study summarizes a large diverse dataset of methane (CH4) fluxes measured from agricultural sites across the British Isles. A total of 53,976 manual static chamber measurements from 27 different sites were investigated to determine the magnitude of CH4 fluxes from a variety of agricultural fields across the UK and Ireland. Our study shows that contrary to some studies, agricultural soils (both arable and grassland) are small net emitters of CH4 rather than sinks. Mean fluxes measured from arable and grassland sites (excluding fertiliser and tillage events) were 0.11 ± 0.06 and 0.19 ± 0.09 nmol m−2 s−1, respectively, and were not found to be significantly different (Welch t‐test, p = 0.17). Using the values reported in this study, we estimate that an annual emission of 0.16 and 0.09 Mt of CO2‐eq is expected from arable and grassland agricultural soils in the UK and Ireland (comparable to 0.3 and 0.7% of the current annual CH4 emission inventories, respectively). Where CH4 uptake occurs in soils, it is negligible compared to expected emissions of the application of animal manures and tillage events, which were both found to significantly increase CH4 emissions in the immediate few days to months after events. Our study highlights that there are significant differences in CH4 uptake and emissions between sites, and that these differences are partially the result of the moisture content of the soil (i.e., the aerobic status of the soil). We expect uptake of CH4 to be more prevalent in drier soils where volumetric water content does not exceed 35% and emissions to be exponentially greater where agricultural fields become waterlogged

Mouse BAC Ends Quality Assessment and Sequence Analyses

A large-scale BAC end-sequencing project at The Institute for Genomic Research (TIGR) has generated one of the most extensive sets of sequence markers for the mouse genome to date. With a sequencing success rate of >80%, an average read length of 485 bp, and ABI3700 capillary sequencers, we have generated 449,234 nonredundant mouse BAC end sequences (mBESs) with 218 Mb total from 257,318 clones from libraries RPCI-23 and RPCI-24, representing 15× clone coverage, 7% sequence coverage, and a marker every 7 kb across the genome. A total of 191,916 BACs have sequences from both ends providing 12× genome coverage. The average Q20 length is 406 bp and 84% of the bases have phred quality scores ≥ 20. RPCI-24 mBESs have more Q20 bases and longer reads on average than RPCI-23 sequences. ABI3700 sequencers and the sample tracking system ensure that > 95% of mBESs are associated with the right clone identifiers. We have found that a significant fraction of mBESs contains L1 repeats and ∼48% of the clones have both ends with ≥ 100 bp contiguous unique Q20 bases. About 3% mBESs match ESTs and > 70% of matches were conserved between the mouse and the human or the rat. Approximately 0.1% mBESs contain STSs. About 0.2% mBESs match human finished sequences and > 70% of these sequences have EST hits. The analyses indicate that our high-quality mouse BAC end sequences will be a valuable resource to the community

The Sinorhizobium fredii HH103 genome: a comparative analysis with S. fredii strains differing in their symbiotic behaviour with soybean

Vinardell JM, Acosta-Jurado S, Göttfert M, et al. The Sinorhizobium fredii HH103 genome: a comparative analysis with S. fredii strains differing in their symbiotic behaviour with soybean. Molecular Plant-Microbe Interactions. 2015;28(7):811-824.Sinorhizobium fredii HH103 is a fast-growing rhizobial strain infecting a broad range of legumes including both American and Asiatic soybeans. In this work we present the sequencing and annotation of the HH103 genome (7.25 Mb), consisting of one chromosome and six plasmids and representing the structurally most complex sinorhizobial genome sequenced so far. Comparative genomic analyses of S. fredii HH103 with strains USDA257 and NGR234 showed that the core genome of these three strains contains 4212 genes (61.7% of the HH103 genes). Synteny plot analysis revealed that the much larger chromosome of USDA257 (6.48 Mb) is co-linear to the HH103 (4.3 Mb) and NGR324 chromosomes (3.9 Mb). An additional region of the USDA257 chromosome of about 2 Mb displays similarity to plasmid pSfHH103e. Remarkable differences exist between HH103 and NGR234 concerning nod genes, flavonoid effect on surface polysaccharide production, and quorum-sensing systems. Furthermore a number of protein secretion systems have been found. Two genes coding for putative type III-secreted effectors not previously described in S. fredii, nopI and gunA, have been located on the HH103 genome. These differences could be important to understand the different symbiotic behaviour of S. fredii strains HH103, USDA257, and NGR234 with soybean