Genetic differentiation and phylogeography of rotifer Polyarthra dolichoptera and P. vulgaris populations between Southeastern China and eastern North America: High intercontinental differences

Genetic differentiations and phylogeographical patterns of small organisms may be shaped by spatial isolation, environmental gradients, and gene flow. However, knowledge about genetic differentiation of rotifers at the intercontinental scale is still limited. Polyarthra dolichoptera and P. vulgaris are cosmopolitan rotifers that are tolerant to environmental changes, offering an excellent model to address the research gap. Here, we investigated the populations in Southeastern China and eastern North America and evaluated the phylogeographical patterns from their geographical range sizes, geographic–genetic distance relationships and their responses to spatial‐environmental factors. Using the mitochondrial cytochrome c oxidase subunit I gene as the DNA marker, we analyzed a total of 170 individuals. Our results showed that some putative cryptic species, also known as entities were widely distributed, but most of them were limited to single areas. The divergence of P. dolichoptera and P. vulgaris indicated that gene flow between continents was limited while that within each continent was stronger. Oceanographic barriers do affect the phylogeographic pattern of rotifers in continental waters and serve to maintain genetic diversity in nature. The genetic distance of P. dolichoptera and P. vulgaris populations showed significant positive correlation with geographic distance. This might be due to the combined effects of habitat heterogeneity, long‐distance colonization, and oceanographic barriers. Furthermore, at the intercontinental scale, spatial distance had a stronger influence than environmental variables on the genetic differentiations of both populations. Wind‐ and animal‐mediated transport and even historical events of continental plate tectonics are potential factors for phylogeography of cosmopolitan rotifers.     

A Fast EM Algorithm for BayesA-Like Prediction of Genomic Breeding Values

Prediction accuracies of estimated breeding values for economically important traits are expected to benefit from genomic information. Single nucleotide polymorphism (SNP) panels used in genomic prediction are increasing in density, but the Markov Chain Monte Carlo (MCMC) estimation of SNP effects can be quite time consuming or slow to converge when a large number of SNPs are fitted simultaneously in a linear mixed model. Here we present an EM algorithm (termed “fastBayesA”) without MCMC. This fastBayesA approach treats the variances of SNP effects as missing data and uses a joint posterior mode of effects compared to the commonly used BayesA which bases predictions on posterior means of effects. In each EM iteration, SNP effects are predicted as a linear combination of best linear unbiased predictions of breeding values from a mixed linear animal model that incorporates a weighted marker-based realized relationship matrix. Method fastBayesA converges after a few iterations to a joint posterior mode of SNP effects under the BayesA model. When applied to simulated quantitative traits with a range of genetic architectures, fastBayesA is shown to predict GEBV as accurately as BayesA but with less computing effort per SNP than BayesA. Method fastBayesA can be used as a computationally efficient substitute for BayesA, especially when an increasing number of markers bring unreasonable computational burden or slow convergence to MCMC approaches.     

Deciphering the SUMO code in the kidney

SUMOylation of proteins is an important regulatory element in modulating protein function and has been implicated in the pathogenesis of numerous human diseases such as cancers, neurodegenerative diseases, brain injuries, diabetes, and familial dilated cardiomyopathy. Growing evidence has pointed to a significant role of SUMO in kidney diseases such as DN, RCC, nephritis, AKI, hypertonic stress and nephrolithiasis. Recently, emerging studies in podocytes demonstrated that SUMO might have a protective role against podocyte apoptosis. However, the SUMO code responsible for beneficial outcome in the kidney remains to be decrypted. Our recent experiments have revealed that the expression of both SUMO and SUMOylated proteins is appreciably elevated in hypoxia‐induced tubular epithelial cells (TECs) as well as in the unilateral ureteric obstruction (UUO) mouse model, suggesting a role of SUMO in TECs injury and renal fibrosis. In this review, we attempt to decipher the SUMO code in the development of kidney diseases by summarizing the defined function of SUMO and looking forward to the potential role of SUMO in kidney diseases, especially in the pathology of renal fibrosis and CKD, with the goal of developing strategies that maximize correct interpretation in clinical therapy and prognosis.     

Variation of phenotype,ploidy level,and organogenic potential of in vitro regenerated polyploids of <Emphasis Type=Italic>Pyrus communis</Emphasis>

A wide range of phenotypic variation was observed among neopolyploids obtained from the diploid pear cultivar ‘Fertility’ by in vitro colchicine treatment. The variant plantlets had alterations in leaf characteristics. Neopolyploids had significantly different ratios of leaf length to leaf width compared to the diploid control. Shoot regeneration from leaf explants and rooting ability from in vitro shoots of neopolyploids was examined. Regeneration frequencies of shoots from leaf explants of seven of the nine neopolyploids were significantly decreased compared to the diploid control. The organogenic potential of neopolyploids was highly genotype-dependent for both shoots and roots. Tetraploid clone 4x − 4 failed to regenerate shoots from leaf explants and the pentaploid clone 5x − 2 failed to root from in vitro shoots. The results suggest that polyploidization caused the decrease in or loss of in vitro organogenic potential. Regenerated shoots derived from neopolyploids showed different phenotypes, depending on the ploidy of the donor plant.     

A novel 62‐bp indel mutation in the promoter region of transforming growth factor‐beta 2 (TGFB2) gene is associated with body weight in chickens

Transforming growth factor‐beta 2 (encoded by TGFB2) is a growth factor that regulates a plethora of cellular functions. In this study, we sequenced the promoter and full‐length exon region of the chicken TGFB2 and found two mutations (g.‐640C>T and g.‐851_‐790del) within the promoter. The two polymorphisms were genotyped in 1030 pedigreed hens recorded for body weight at 7 (BW7), 9 (BW9), 11 (BW11), 13 (BW13), 17 (BW17) weeks old, egg weight at 36 weeks of age (EW36) and egg numbers from the age at first egg (AFE) to 40 weeks of age (EN40). Despite the fact that no mutations were found to have statistically significant genetic effects on egg production, the association results of growth traits showed that both g.‐640C>T and g.‐851_‐790del had significant effects on body weights and that both genotype g.‐640TT and g.‐851_‐790wt/wt were positive for body weight performance. Therefore, the polymorphisms of TGFB2, especially the g.‐851_‐790del mutation associated with body weight at almost all periods, could be potential useful genetic markers to improve the growth of Beijing You chickens.     

Establishment of Transfer Functions of the Pollen-Climatic Factors in Northern China and the Quantitative Climatic Reconstruction at DJ Core

The 2.4 meter-long core was extracted from the Diaojiao lake (41º18′N, 112º21′E) at the foot of the northern part of Daqingshan Mts. Pollen analysis from collections subsampled in the laboratory at 2 cm intervals, revealed plentiful pollen and spores from over 10 arboreal genera, including Pinus, Betula, Picea, Abies, Carpinus, Quercus, Ulmus and more than 20 non-arboreal genera, mainly of Artemisia, Labiatae, Nitraria, Polygonaceae, Ranunculus, Thalictrum, Umbel- liferae, Caryophyllaceae and Cyperaceae. Fern spores, aquatic pollen and algae were also observed in some parts of the core. The transfer functions were established by the stepwise regression analysis using the climatic factors and 13 pollen taxa. The different Fl and F2 value were used as the thresh- old value of F test (i. e. used for selecting and deleting factors). Each regressed equation was obtained from 70 times of calculations with a step-wise increase of 0.1 for Fl and F2 and those having the smallest regression deviation and the largest multiple correlation coefficient were the final four transfer functions. Substituting the pre-factor obtained from the stratigraphic sampled into the regression equations, the estimates of temperature and precipitation in January and in July, and annual mean temperature values could be calculated. Some climatic stages were inferred from total pollen influx and pollen percentage from the core using a transfer function: humid-cool (from 10 000 to 7 800 a BP), arid-cold (9 200 to 7 900 a BP), arid-warm (7 900 to 7 100 a BP), humid-warm (7 100 to 4 400 a BP), arid-warm (4 400 to 3 000 a BP), arid-cold (3 000 to 2 100 a BP). The highest annual mean temperature during Holocene was ca. 4 ℃ higher and the lowest was ca. 2 ℃ lower than the present temperature. Annual precipitation was 250 mm higher and 300 mm lower than the present.