The replicative lifespan-extending deletion of SGF73 results in altered ribosomal gene expression in yeast.

Sgf73, a core component of SAGA, is the yeast orthologue of ataxin-7, which undergoes CAG-polyglutamine repeat expansion leading to the human neurodegenerative disease spinocerebellar ataxia type 7 (SCA7). Deletion of SGF73 dramatically extends replicative lifespan (RLS) in yeast. To further define the basis for Sgf73-mediated RLS extension, we performed ChIP-Seq, identified 388 unique genomic regions occupied by Sgf73, and noted enrichment in promoters of ribosomal protein (RP)-encoding genes. Of 388 Sgf73 binding sites, 33 correspond to 5' regions of genes implicated in RLS extension, including 20 genes encoding RPs. Furthermore, half of Sgf73-occupied, RLS-linked RP genes displayed significantly reduced expression in sgf73Δ mutants, and double null strains lacking SGF73 and a Sgf73-regulated, RLS-linked RP gene exhibited no further increase in replicative lifespan. We also found that sgf73Δ mutants display altered acetylation of Ifh1, an important regulator of RP gene transcription. These findings implicate altered ribosomal protein expression in sgf73Δ yeast RLS and highlight altered acetylation as a pathway of relevance for SCA7 neurodegeneration

CrY2H-seq: a massively multiplexed assay for deep-coverage interactome mapping.

Broad-scale protein-protein interaction mapping is a major challenge given the cost, time, and sensitivity constraints of existing technologies. Here, we present a massively multiplexed yeast two-hybrid method, CrY2H-seq, which uses a Cre recombinase interaction reporter to intracellularly fuse the coding sequences of two interacting proteins and next-generation DNA sequencing to identify these interactions en masse. We applied CrY2H-seq to investigate sparsely annotated Arabidopsis thaliana transcription factors interactions. By performing ten independent screens testing a total of 36 million binary interaction combinations, and uncovering a network of 8,577 interactions among 1,453 transcription factors, we demonstrate CrY2H-seq's improved screening capacity, efficiency, and sensitivity over those of existing technologies. The deep-coverage network resource we call AtTFIN-1 recapitulates one-third of previously reported interactions derived from diverse methods, expands the number of known plant transcription factor interactions by three-fold, and reveals previously unknown family-specific interaction module associations with plant reproductive development, root architecture, and circadian coordination

Geo-Referenced, Abundance Calibrated Ocean Distribution of Chinook Salmon (Oncorhynchus tshawytscha) Stocks across the West Coast of North America

Understanding seasonal migration and localized persistence of populations is critical for effective species harvest and conservation management. Pacific salmon (genus Oncorhynchus) forecasting models predict stock composition, abundance, and distribution during annual assessments of proposed fisheries impacts. Most models, however, fail to account for the influence of biophysical factors on year-to-year fluctuations in migratory distributions and stock-specific survival. In this study, the ocean distribution and relative abundance of Chinook salmon (O. tshawytscha) stocks encountered in the California Current large marine ecosystem, U.S.A were inferred using catch-per-unit effort (CPUE) fisheries and genetic stock identification data. In contrast to stock distributions estimated through coded-wire-tag recoveries (typically limited to hatchery salmon), stock-specific CPUE provides information for both wild and hatchery fish. Furthermore, in contrast to stock composition results, the stock-specific CPUE metric is independent of other stocks and is easily interpreted over multiple temporal or spatial scales. Tests for correlations between stock-specific CPUE and stock composition estimates revealed these measures diverged once proportional contributions of locally rare stocks were excluded from data sets. A novel aspect of this study was collection of data both in areas closed to commercial fisheries and during normal, open commercial fisheries. Because fishing fleet efficiency influences catch rates, we tested whether CPUE differed between closed area (non-retention) and open area (retention) data sets. A weak effect was indicated for some, but not all, analyzed cases. Novel visualizations produced from stock-specific CPUE-based ocean abundance facilitates consideration of how highly refined, spatial and genetic information could be incorporated in ocean fisheries management systems and for investigations of biogeographic factors that influence migratory distributions of fish

Geo-Referenced, Abundance Calibrated Ocean Distribution of Chinook Salmon (Oncorhynchus tshawytscha) Stocks across the West Coast of North America

Understanding seasonal migration and localized persistence of populations is critical for effective species harvest and conservation management. Pacific salmon (genus Oncorhynchus) forecasting models predict stock composition, abundance, and distribution during annual assessments of proposed fisheries impacts. Most models, however, fail to account for the influence of biophysical factors on year-to-year fluctuations in migratory distributions and stock-specific survival. In this study, the ocean distribution and relative abundance of Chinook salmon (O. tshawytscha) stocks encountered in the California Current large marine ecosystem, U.S.A were inferred using catch-per-unit effort (CPUE) fisheries and genetic stock identification data. In contrast to stock distributions estimated through coded-wire-tag recoveries (typically limited to hatchery salmon), stock-specific CPUE provides information for both wild and hatchery fish. Furthermore, in contrast to stock composition results, the stock-specific CPUE metric is independent of other stocks and is easily interpreted over multiple temporal or spatial scales. Tests for correlations between stock-specific CPUE and stock composition estimates revealed these measures diverged once proportional contributions of locally rare stocks were excluded from data sets. A novel aspect of this study was collection of data both in areas closed to commercial fisheries and during normal, open commercial fisheries. Because fishing fleet efficiency influences catch rates, we tested whether CPUE differed between closed area (non-retention) and open area (retention) data sets. A weak effect was indicated for some, but not all, analyzed cases. Novel visualizations produced from stock-specific CPUE-based ocean abundance facilitates consideration of how highly refined, spatial and genetic information could be incorporated in ocean fisheries management systems and for investigations of biogeographic factors that influence migratory distributions of fish

Divergent life-history races do not represent Chinook salmon coast-wide: the importance of scale in Quaternary biogeography

The dynamic Quaternary geology of the Pacific Ring of Fire created substantial challenges for biogeography. Fish life history and population genetic variation were shaped by climate change, repeated formation and subsidence of ice sheets, sea-level change, volcanism and tectonics, isostatic rebound, and now human activities. It is widely recognized in Chinook salmon (Oncorhynchus tshawytscha) that parallel evolution and phenotypic plasticity have obscured range-wide patterns of life-history segregation with evolutionary lineage, yet the idea of the lineages themselves persists. We employed a large, internationally standardized, microsatellite data set to explore population structure at coast-wide scale and test for two divergent lineages, whether or not related to life history. We found at least 27 distinct lineages. However, relationships among groups were poorly resolved - essentially a star phylogeny. We found pervasive isolation by distance among groups, complicating cluster analysis. Only in the interior Columbia River (east of the Cascade Mountains) is there a deep genetic bifurcation that supports both the two-lineage hypothesis and the life-history segregation hypothesis. This broad-scale perspective helps reconcile different views of Chinook salmon phylogeography and life-history distribution.Keywords: Wire tag recoveries, North America, British Columbia, Reproductive isolation, Genetic popoulation structure, Columbia River Basin, Oncorhynchus Tshawytscha, Mitochondrial DNA variation, Pacific Salmon, Sockeye salmonThis is the publisher’s final pdf. The published article is copyrighted by NRC Research Press and can be found at: http://www.nrcresearchpress.com

Use of Genetic Stock Identification Data for Comparison of the Ocean Spatial Distribution, Size at Age, and Fishery Exposure of an Untagged Stock and Its Indicator: California Coastal versus Klamath River Chinook Salmon

Managing weak stocks in mixed-stock fisheries often relies on proxies derived from data-rich indicator stocks, although there have been limited tests of the appropriateness of such proxies. For example, full cohort reconstruction of tagged Klamath River fall-run Chinook Salmon Oncorhynchus tshawytscha of northern California enables the use of detailed models to inform management. Information gained from this stock is also used in the management of the untagged, threatened California Coastal Chinook Salmon (CCC) stock, where it is assumed that a cap on Klamath harvest rates effectively constrains impacts on CCC to acceptable levels. To evaluate use of this proxy, we used a novel approach based on genetic stock identification (GSI) data to compare the two stocks’ size at age and ocean distribution (as inferred from spatial variation in CPUE), two key factors influencing fishery exposure. We developed broadly applicable methods to account for both sampling and genetic assignment uncertainty in estimating total stock-specific catch from GSI data, and propagated this uncertainty into models quantifying variation in CPUE across space and time. We found that, in 2010, the stocks were similar in size at age early in the year (age 3 and age 4), but CCC fish were larger later in the year. The stocks appeared similarly distributed early in the year (2010) but more concentrated near their respective source rivers later in the year (2010 and 2011). If these results are representative, relative fishery impacts on the two stocks might scale similarly early in the year, but management changes later in the year could have differing impacts on the two stocks. This novel modeling approach is suited to evaluating the concordance between other data-limited stocks and their proxies, and can be broadly applied to estimate stock-specific harvest, and the uncertainty therein, using GSI in other systems

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Geo-Referenced, Abundance Calibrated Ocean Distribution of Chinook Salmon (<i>Oncorhynchus tshawytscha</i>) Stocks across the West Coast of North America

<div><p>Understanding seasonal migration and localized persistence of populations is critical for effective species harvest and conservation management. Pacific salmon (genus <i>Oncorhynchus</i>) forecasting models predict stock composition, abundance, and distribution during annual assessments of proposed fisheries impacts. Most models, however, fail to account for the influence of biophysical factors on year-to-year fluctuations in migratory distributions and stock-specific survival. In this study, the ocean distribution and relative abundance of Chinook salmon (<i>O</i>. <i>tshawytscha</i>) stocks encountered in the California Current large marine ecosystem, U.S.A were inferred using catch-per-unit effort (CPUE) fisheries and genetic stock identification data. In contrast to stock distributions estimated through coded-wire-tag recoveries (typically limited to hatchery salmon), stock-specific CPUE provides information for both wild and hatchery fish. Furthermore, in contrast to stock composition results, the stock-specific CPUE metric is independent of other stocks and is easily interpreted over multiple temporal or spatial scales. Tests for correlations between stock-specific CPUE and stock composition estimates revealed these measures diverged once proportional contributions of locally rare stocks were excluded from data sets. A novel aspect of this study was collection of data both in areas closed to commercial fisheries and during normal, open commercial fisheries. Because fishing fleet efficiency influences catch rates, we tested whether CPUE differed between closed area (non-retention) and open area (retention) data sets. A weak effect was indicated for some, but not all, analyzed cases. Novel visualizations produced from stock-specific CPUE-based ocean abundance facilitates consideration of how highly refined, spatial and genetic information could be incorporated in ocean fisheries management systems and for investigations of biogeographic factors that influence migratory distributions of fish.</p></div