BackgroundArtificial selection played an important role in the origin of modern Glycine max cultivars from the wild soybean Glycine soja. To elucidate the consequences of artificial selection accompanying the domestication and modern improvement of soybean, 25 new and 30 published whole-genome re-sequencing accessions, which represent wild, domesticated landrace, and Chinese elite soybean populations were analyzed.ResultsA total of 5,102,244 single nucleotide polymorphisms (SNPs) and 707,969 insertion/deletions were identified. Among the SNPs detected, 25.5% were not described previously. We found that artificial selection during domestication led to more pronounced reduction in the genetic diversity of soybean than the switch from landraces to elite cultivars. Only a small proportion (2.99%) of the whole genomic regions appear to be affected by artificial selection for preferred agricultural traits. The selection regions were not distributed randomly or uniformly throughout the genome. Instead, clusters of selection hotspots in certain genomic regions were observed. Moreover, a set of candidate genes (4.38% of the total annotated genes) significantly affected by selection underlying soybean domestication and genetic improvement were identified.ConclusionsGiven the uniqueness of the soybean germplasm sequenced, this study drew a clear picture of human-mediated evolution of the soybean genomes. The genomic resources and information provided by this study would also facilitate the discovery of genes/loci underlying agronomically important traits.

BackgroundT89, a traditional Chinese medicine, has passed phase II, and is undergoing phase III clinical trials for treatment of ischemic cardiovascular disease by the US FDA. However, the role of T89 on isoproterenol (ISO)-induced cardiac injury is unknown. The present study aimed to explore the effect and underlying mechanism of T89 on ISO-induced cardiac injury.MethodsMale Sprague-Dawley rats received subcutaneous injection of ISO saline solution at 24 h intervals for the first 3 days and then at 48 h intervals for the next 12 days. T89 at dose of 111.6 and 167.4 mg/kg was administrated by gavage for 15 consecutive days. Rat survival rate, cardiac function evaluation, morphological observation, quantitative proteomics, and Western blotting analysis were performed.ResultsT89 obviously improved ISO-induced low survival rate, attenuated ISO-evoked cardiac injury, as evidenced by myocardial blood flow, heart function, and morphology. Quantitative proteomics revealed that the cardioprotective effect of T89 relied on the regulation of metabolic pathways, including glycolipid metabolism and energy metabolism. T89 inhibited the enhancement of glycolysis, promoted fatty acid oxidation, and restored mitochondrial oxidative phosphorylation by regulating Eno1, Mcee, Bdh1, Ces1c, Apoc2, Decr1, Acaa2, Cbr4, ND2, Cox 6a, Cox17, ATP5g, and ATP5j, thus alleviated oxidative stress and energy metabolism disorder and ameliorated cardiac injury after ISO. The present study also verified that T89 significantly restrained ISO-induced increase of HSP70/HSP40 and suppressed the phosphorylation of ERK, further restored the expression of CX43, confirming the protective role of T89 in cardiac hypertrophy. Proteomics data are available via ProteomeXchange with identifier PXD024641.ConclusionT89 reduced mortality and improves outcome in the model of ISO-induced cardiac injury and the cardioprotective role of T89 is correlated with the regulation of glycolipid metabolism, recovery of mitochondrial function, and improvement of myocardial energy.

Airborne microbiome alterations, an emerging global health concern, have been linked to anthropogenic activities in numerous studies. However, these studies have not reached a consensus. To reveal general trends, we conducted a meta-analysis using 3226 air samples from 42 studies, including 29 samples of our own. We found that samples in anthropogenic activity-related categories showed increased microbial diversity, increased relative abundance of pathogens, increased co-occurrence network complexity, and decreased positive edge proportions in the network compared with the natural environment category. Most of the above conclusions were confirmed using the samples we collected in a particular period with restricted anthropogenic activities. Additionally, unlike most previous studies, we used 15 human-production process factors to quantitatively describe anthropogenic activities. We found that microbial richness was positively correlated with fine particulate matter concentration, NH 3 emissions, and agricultural land proportion and negatively correlated with the gross domestic product per capita. Airborne pathogens showed preferences for different factors, indicating potential health implications. SourceTracker analysis showed that the human body surface was a more likely source of airborne pathogens than other environments. Our results advance the understanding of relationships between anthropogenic activities and airborne bacteria and highlight the role of airborne pathogens in public health.

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The sugarcane streak mosaic virus (SCSMV) is the most important disease in sugarcane produced in southern China. The SCSMV encoded protein 1 (P1SCSMV) is important in disease development, but little is known about its detailed functions in plant–virus interactions. Here, the differential accumulated proteins (DAPs) were identified in the heterologous expression of P1SCSMV via a potato virus X (PVX)-based expression system, using a newly developed four-dimensional proteomics approach. The data were evaluated for credibility and reliability using qRT-RCR and Western blot analyses. The physiological response caused by host factors that directly interacted with the PVX-encoded proteins was more pronounced for enhancing the PVX accumulation and pathogenesis in Nicotiana benthamiana. P1SCSMV reduced photosynthesis by damaging the photosystem II (PSII). Overall, P1SCSMV promotes changes in the physiological status of its host by up- or downregulating the expression of host factors that directly interact with the viral proteins. This creates optimal conditions for PVX replication and movement, thereby enhancing its accumulation levels and pathogenesis. Our investigation is the first to supply detailed evidence of the pathogenesis-enhancing role of P1SCSMV, which provides a deeper understanding of the mechanisms behind virus–host interactions.

BackgroundDuring the past decade, the development of high throughput nucleic sequencing and mass spectrometry analysis techniques have enabled the characterization of microbial communities through metagenomics, metatranscriptomics, metaproteomics and metabolomics data. To reveal the diversity of microbial communities and interactions between living conditions and microbes, it is necessary to introduce comparative analysis based upon integration of all four types of data mentioned above. Comparative meta-omics, especially comparative metageomics, has been established as a routine process to highlight the significant differences in taxon composition and functional gene abundance among microbiota samples. Meanwhile, biologists are increasingly concerning about the correlations between meta-omics features and environmental factors, which may further decipher the adaptation strategy of a microbial community.ResultsWe developed a graphical comprehensive analysis software named MetaComp comprising a series of statistical analysis approaches with visualized results for metagenomics and other meta-omics data comparison. This software is capable to read files generated by a variety of upstream programs. After data loading, analyses such as multivariate statistics, hypothesis testing of two-sample, multi-sample as well as two-group sample and a novel function—regression analysis of environmental factors are offered. Here, regression analysis regards meta-omic features as independent variable and environmental factors as dependent variables. Moreover, MetaComp is capable to automatically choose an appropriate two-group sample test based upon the traits of input abundance profiles. We further evaluate the performance of its choice, and exhibit applications for metagenomics, metaproteomics and metabolomics samples.ConclusionMetaComp, an integrative software capable for applying to all meta-omics data, originally distills the influence of living environment on microbial community by regression analysis. Moreover, since the automatically chosen two-group sample test is verified to be outperformed, MetaComp is friendly to users without adequate statistical training. These improvements are aiming to overcome the new challenges under big data era for all meta-omics data. MetaComp is available at: http://cqb.pku.edu.cn/ZhuLab/MetaComp/ and https://github.com/pzhaipku/MetaComp/.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1849-8) contains supplementary material, which is available to authorized users.

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