Cytogenetic and genomic organization analyses of chloroplast DNA invasions in the nuclear genome of Asparagus officinalis L. provides signatures of evolutionary complexity and informativity in sex chromosome evolution.

BACKGROUND: The transfer of chloroplast DNA into nuclear genome is a common process in plants. These transfers form nuclear integrants of plastid DNAs (NUPTs), which are thought to be driving forces in genome evolution, including sex chromosome evolution. In this study, NUPTs in the genome of a dioecious plant Asparagus officinalis L. were systematically analyzed, in order to investigate the characteristics of NUPTs in the nuclear genome and the relationship between NUPTs and sex chromosome evolution in this species. RESULTS: A total of 3155 NUPT insertions were detected, and they represented approximated 0.06% of the nuclear genome. About 45% of the NUPTs were organized in clusters. These clusters were derived from various evolutionary events. The Y chromosome contained the highest number and largest proportion of NUPTs, suggesting more accumulation of NUPTs on sex chromosomes. NUPTs were distributed widely in all of the chromosomes, and some regions preferred these insertions. The highest density of NUPTs was found in a 47 kb region in the Y chromosome; more than 75% of this region was occupied by NUPTs. Further cytogenetic and sequence alignment analysis revealed that this region was likely the centromeric region of the sex chromosomes. On the other hand, the male-specific region of the Y chromosome (MSY) and the adjacent regions did not have NUPT insertions. CONCLUSIONS: These results indicated that NUPTs were involved in shaping the genome of A. officinalis through complicated process. NUPTs may play important roles in the centromere shaping of the sex chromosomes of A. officinalis, but were not implicated in MSY formation.

The application of MutMap in forward genetic studies based on whole-genome sequencing.

Classical forward genetic analysis relies on construction of complicated progeny populations and development of many molecular markers for linkage analysis in genetic mapping, which is both time- and cost-consuming. The recently developed MutMap is a new forward genetic approach based on high-throughput next-generation sequencing technologies. It is more efficient and affordable than traditional methods. Moreover, new extended methods based on MutMap have been developed: MutMap+, which is based on self-crossing; MutMap-Gap, which is used to recognize the causative variations occurring in genome gap regions; QTL-seq, a method similar to MutMap for mapping quantitative trait loci. These methods are free from constructing complicated mapping population, genetic hybridization and linkage information. They have greatly accelerated the identification of genetic elements associated with interested phenotypic variation. Here, we review the basic principles of MutMap, and discuss their future applications in next generation sequencing-based forward genetic mapping and crop improvement.

[Impacts of different alkaline soil on canopy spectral characteristics of overlying vegetation].

The relationship between alkalinity and pH of the soil, reflectance spectra and red-edge parameters of the sunflower canopy in different growth periods under different alkalinity soil were analyzed, respectively. The results showed that the spectral reflectance of the sunflower canopy in different stage under different alkalinity soil is the same as the spectral reflectance characters of the other greenery canopy. Along with the advancement of the sunflower growth period, sunflower canopy spectral reflectance increases gradually at different stages, the spectral reflectance is higher at flowering stage than 7-leaf stage and budding stage, and there exists a high reflection peak at 809nm at flowering period. At the same time, the spectral reflectance is affected by salinity-alkalinity stress at different stages, in the near infrared shortwave band, the spectral reflectance of the sunflower canopy in different stage increases with the decreases in soil alkalinity. When the derivatives are applied to determine the wavelength of the red-edge, there is a shift phenomenon of the red edge. The red edges were at 702-720 nm during every growth period of the sunflower. The "blue shift" phenomenon is also emerged for red edge position and red edge sloped with the increase in the soil alkalinity. Conversely, at the same growth periods, the red edge positions and red edge slope move to longer wave bands with the decrease in soil alkalinity. There is a "red shift" phenomenon before flowering period and "blue shift" phenomenon after flowering period for the red edge position and red edge slope of canopy spectrum at the same soil alkalinity. Respectively. The red edges at different growth stages of the sunflower show very significant positive correlation and quadratic polynomial to alkalinity and pH of the soil. Therefore, we thought used the red edge features of greenery could indicate the soil alkalization degree, it providing scientific basis for monitoring soil alkalization degree by remote sensing.

[Estimation of soil moisture and organic matter content in saline alkali farmland by using CARS algorithm combined with covariates]. / 利用CARS算法联合协变量估算盐碱农田土壤水分和有机质含量.

Rapid acquisition of the data of soil moisture content (SMC) and soil organic matter (SOM) content is crucial for the improvement and utilization of saline alkali farmland soil. Based on field measurements of hyperspectral reflectance and soil properties of farmland soil in the Hetao Plain, we used a competitive adaptive reweighted sampling algorithm (CARS) to screen sensitive bands after transforming the original spectral reflectance (Ref) into a standard normal variable (SNV). Strategies Ⅰ, Ⅱ, and Ⅲ were used to model the input variables of Ref, Ref SNV, Ref-SNV+ soil covariate (SC), and digital elevation model (DEM). We constructed SMC and SOM estimation models based on random forest (RF) and light gradient boosting machine (LightGBM), and then verified and compared the accuracy of the models. The results showed that after CARS screening, the sensitive bands of SMC and SOM were compressed to below 3.3% of the entire band, which effectively optimized band selection and reduced redundant spectral information. Compared with the LightGBM model, the RF model had higher accuracy in SMC and SOM estimation, and the input variable strategy Ⅲ was better than Ⅱ and Ⅰ. The introduction of auxiliary variables effectively improved the estimation ability of the model. Based on comprehensive analysis, the coefficient of determination (Rp2), root mean square error (RMSE), and relative analysis error (RPD) of the SMC estimation model validation based on strategy Ⅲ-RF were 0.63, 3.16, and 2.01, respectively. The SOM estimation models based on strategy Ⅲ-RF had Rp2, RMSE, and RPD of 0.93, 1.15, and 3.52, respectively. The strategy Ⅲ-RF model was an effective method for estimating SMC and SOM. Our results could provide a new method for the rapid estimation of soil moisture and organic matter content in saline alkali farmland.

Genome-wide analysis of transposable elements and satellite DNA in Humulus scandens, a dioecious plant with XX/XY1Y2 chromosomes.

Transposable elements (TEs) and satellite DNAs, two major categories of repetitive sequences, are expected to accumulate in non-recombining genome regions, including sex-linked regions, and contribute to sex chromosome evolution. The dioecious plant, Humulus scandens, can be used for studying the evolution of the XX/XY1Y2 sex chromosomes. In this study, we thoroughly examined the repetitive components of male and female H. scandens using next-generation sequencing data followed by bioinformatics analysis and florescence in situ hybridization (FISH). The H. scandens genome has a high overall repetitive sequence composition, 68.30% in the female and 66.78% in the male genome, with abundant long terminal repeat (LTR) retrotransposons (RTs), including more Ty3/Gypsy than Ty1/Copia elements, particularly two Ty3/Gypsy lineages, Tekay and Retand. Most LTR-RT lineages were found dispersed across the chromosomes, though CRM and Athila elements were predominately found within the centromeres and the pericentromeric regions. The Athila elements also showed clearly higher FISH signal intensities in the Y1 and Y2 chromosomes than in the X or autosomes. Three novel satellite DNAs were specifically distributed in the centromeric and/or telomeric regions, with markedly different distributions on the X, Y1, and Y2 chromosomes. Combined with FISH using satellite DNAs to stain chromosomes during meiotic diakinesis, we determined the synapsis pattern and distinguish pseudoautosomal regions (PARs). The results indicate that the XY1Y2 sex chromosomes of H. scandens might have originated from a centric fission event. This study improves our understanding of the repetitive sequence organization of H. scandens genome and provides a basis for further analysis of their chromosome evolution process.

Estimation of soil water and organic matter content in medium and low yield fields of Ningxia Yellow River Irrigation area based on hyperspectral information.

Accurately obtaining soil water and organic matter content is of great significance for improving soil qua-lity in croplands with medium to low yield. We explored the estimation effect of fractional order differentiation (FOD) combined with different spectral indices on soil water and organic matter content in medium and low yield croplands of Ningxia Yellow River Irrigation Area. After root mean square transformation of field measured hyperspectral reflectance, we used 0-2 FOD (with a step length of 0.25) to construct difference index (DI), ratio index (RI), product index (PI), sum index (SI), generalized difference index (GDI), and nitrogen planar domain index (NPDI) and to select the optimal spectral index based on the correlation coefficients between six spectral indices with soil water and organic matter contents. We constructed a model for estimating soil water and organic matter content based on partial least squares regression (PLSR) and support vector machine (SVM). The results showed that the correlation between soil water and organic matter content and spectral information was effectively improved after FOD transformation compared with the original spectrum, with maximum increases of 0.1785 and 0.1713, respectively. The soil water content sensitive bands were mainly in the range of 400-630 and 1350-1940 nm, while the sensitive bands of organic matter content were mainly at 460-850, 1530-1910, and 2060-2310 nm. The accuracy of SVM model was significantly higher than that of PLSR, and the soil water content estimation model based on 1.75-order NPDI-SVM reached the highest precision, with a validation determination coefficient (Rp2) of 0.970, root mean square error (RMSE) of 1.615, and relative percent deviation (RPD) of 4.211. The organic matter content estimation model based on 0.5 order DI-SVM had the best performance, with Rp2, RMSE and RPD of 0.983, 0.701 and 5.307, respectively. Our results could provide data and technological support for soil water and nutrient monitoring, quality improvement, and graphics creating in similar area with medium to low yield fields.

[Effects of different spectra types on the accuracy and correction of soil salt content inversion in Yinchuan Plain, China]. / ä¸åŒå ‰è°±ç±»åž‹å¯¹é“¶å·å¹³åŽŸåœŸå£¤å«ç›é‡åæ¼”ç²¾åº¦çš„å½±å“ä¸Žæ ¡æ­£.

Soil salinization is one of key drivers for the degradation of soil quality and yield in arable land. To accurately and quickly evaluate soil salt content in Yinchuan Plain, field and indoor hyperspectral data were processed with first order differential (FDR) transformation, then the feature bands were identified by stepwise regression (SR). Partial least squares regression (PLSR) and support vector machines (SVM) were used to build models, which were verified to figure out the optimal hyperspectral type for the study area. Moreover, segmented and global corrections were performed to process poor hyperspectral, aiming to improve the accuracy of soil salt content inversion. The results showed that the accuracy of soil salt content inversion model based on field hyperspectral data was 58.9% higher than that of the indoor hyperspectral data. The accuracy of the inversion was improved through the segmented and global correction of the indoor hyperspectral. We found that the segmented correction is more accurate for the PLSR model (Rc2=0.790, Rp2=0.633, RPD=1.64) and the global correction is more accurate for the SVM model (Rc2=0.927, Rp2=0.947, RPD=3.87). The SVM models' inversion accuracy was higher than that of PLSR, with the field hyperspectral model fitted the best, followed by the indoor hyperspectral processed with the global correction and the indoor hyperspectral processed with the segmented correction, while the indoor hyperspectral the worst. Our results suggest that field hyperspectral data could contribute to the quantitative inversion of soil salt content in Yinchuan Plain. The corrected indoor hyperspectral could significantly enhance the inversion accuracy of soil salt content, which could guarantee food security and ecological quality development.

[Spectral reflectance characteristics and modeling of typical Takyr Solonetzs water content].

Based on the analysis of the spectral reflectance of the typical Takyr Solonetzs soil in Ningxia, the relationship of soil water content and spectral reflectance was determined, and a quantitative model for the prediction of soil water content was constructed. The results showed that soil spectral reflectance decreased with the increasing soil water content when it was below the water holding capacity but increased with the increasing soil water content when it was higher than the water holding capacity. Soil water content presented significantly negative correlation with original reflectance (r), smooth reflectance (R), logarithm of reflectance (IgR), and positive correlation with the reciprocal of R and logarithm of reciprocal [lg (1/R)]. The correlation coefficient of soil water content and R in the whole wavelength was 0.0013, 0.0397 higher than r and lgR, respectively. Average correlation coefficient of soil water content with 1/R and [lg (1/R)] at the wavelength of 950-1000 nm was 0.2350 higher than that of 400-950 nm. The relationships of soil water content with the first derivate differential (R') , the first derivate differential of logarithm (lgR)' and the first derivate differential of logarithm of reciprocal [lg(1/R)]' were unstable. Base on the coefficients of r, lg(1/R), R' and (lgR)', different regression models were established to predict soil water content, and the coefficients of determination were 0.7610, 0.8184, 0.8524 and 0.8255, respectively. The determination coefficient for power function model of R'. reached 0.9447, while the fitting degree between the predicted value based on this model and on-site measured value was 0.8279. The model of R' had the highest fitted accuracy, while that of r had the lowest one. The results could provide a scientific basis for soil water content prediction and field irrigation in the Takyr Solonetzs region.

[Dynamic changes of land desertification landscape pattern in agriculture and pasturage interlaced zone of northern Shaanxi].

By using the 1986, 1993 and 2003 Landsat TM images and with the help of GIS, the dynamic changes of land desertification landscape pattern in agriculture and pasturage interlaced zone of northern Shaanxi in 1986-2003 were analyzed. The results showed that in the past 17 years, the desertification area in the zone decreased by 206,655.2 hm2, with the patches in landscape structure reduced and fragmentation abated. Fortunately, the desertification degree decreased obviously, and moderate and light desertification took the leading position. From 1986 to 2003, the spatial centroid of desertification landscape patches expanded southwestward and northeastward, giving serious threat to the ecological safety of the southeast and northeast loess gully and hilly areas.