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Abstract Background Trehalose-6-phosphate phosphatase (TPP) is an essential enzyme catalyzing trehalose synthesis, an important regulatory factor for plant development and stress response in higher plants. However, the TPP gene family in soybean has not been reported. Results A comprehensive analysis of the TPP gene family identified 18 GmTPPs classified into eight groups based on the phylogenetic relationships and the conservation of protein in six monocot and eudicot plants. The closely linked subfamilies had similar motifs and intron/exon numbers. Segmental duplication was the main driving force of soybean GmTPPs expansion. In addition, analysis of the cis-regulatory elements and promoter regions of GmTPPs revealed that GmTPPs regulated the response to several abiotic stresses. Moreover, RNA-seq and qRT-PCR analysis of the tissue-specific GmTPPs under different abiotic stresses revealed that most GmTPPs were associated with response to different stresses, including cold, drought, saline-alkali, and exogenous trehalose. Notably, exogenous trehalose treatment up-regulated the expression of most TPP genes under saline-alkali conditions while increasing the carbohydrate and trehalose levels and reducing reactive oxygen species (ROS) accumulation in soybean sprouts, especially in the saline-alkali tolerant genotype. Furthermore, the interaction network and miRNA target prediction revealed that GmTPPs interacted with abiotic stress response-related transcription factors. Conclusions The findings in this study lay a foundation for further functional studies on TPP-based breeding to improve soybean development and stress tolerance.

The NOAA IMS (Interactive Multisensor Snow and Ice Mapping System) is a blended snow and ice product based on active and passive satellite sensors, ground observation, and other auxiliary information, providing the daily cloud-free snow cover extent in the Northern Hemisphere (NH) and having great application potential in snow cover monitoring and research in the Tibetan Plateau (TP). However, accuracy assessment of products is crucial for various aspects of applications. In this study, Landsat-8 OLI images were used to evaluate and validate the accuracy of IMS products in snow cover monitoring on the TP. The results show that (1) average overall accuracy of IMS 4 km products is 76.0% and average mapping accuracy is 88.3%, indicating that IMS 4 km products are appropriate for large-scale snow cover monitoring on the TP. (2) IMS 4 km products tend to overestimate actual snow cover on the TP, with an average commission rate of 45.4% and omission rate of 11.7%, and generally present that the higher the proportion of snow-covered area, the lower the probability of omission rate and the higher the probability of commission rate. (3) Mapping accuracy of IMS 4 km snow cover on the TP generally is higher at the high altitudes, and commission and omission errors increase with the decrease of elevation. (4) Compared with less regional representativeness of ground observations, the spatial characteristics of snow cover based on high-resolution remote sensing data are much more detailed, and more reliable verification results can be obtained. (5) In addition to commission and omission error metrics, the overall accuracy and mapping accuracy based on the reference image instead of classified image can better reveal the general monitoring accuracy of IMS 4 km products on the TP area.

Snow cover plays a critical role in global energy and water cycles. Snow cover on the Tibetan Plateau (TP) provides vital water sources in western China and Himalayan regions, in addition to its weather and climate significance. The massive high mountain topography of the TP is the main condition for the presence and persistence of snow cover on the plateau at the mid-low latitudes of the Northern Hemisphere (NH). However, how the mountain topography controls snow-cover distribution on the TP remains largely unclear, and the relationship is not well quantified. Here, the spatial distribution and the topographic controls of snow cover on the TP are examined based on snow cover frequency (SCF) derived from MODIS snow cover product (MOD10A2 v005) and digital elevation model (DEM) data. The results show that snow cover on the TP is spatially unevenly distributed, and that it is characterized by rich snow and high SCF on the interior and the surrounding high mountain ranges, with less snow and low SCF in inland basins and river valleys. Snow cover on the TP presents elevation dependence: the higher the altitude, the higher the SCF, the longer the snow cover duration, and the more stable the intra-annual variation. The annual mean SCF below 3000 m above sea level (m a.s.l) is less than 4%, and it reaches 77% above 6000 m a.s.l. The intra-annual snow cover variation below 4000 m a.s.l features a unimodal distribution, while above 4000 m a.s.l it presents a bimodal distribution. The mean minimum SCF below 6000 m a.s.l occurs in summer, while above 6000 m a.s.l it occurs in winter. Due to differences in solar radiation and moisture condition caused by the mountain slope and aspect, the mean SCF generally increases with mountain slopes, and it is the highest on the north-facing aspect and the lowest on the south-facing aspect.

Many major river systems in Asia, such as the Yangtze, Yarlung Zangbo, Indus, Ganges and Salween originate in the Tibetan mountains and snow cover in Tibet provides substantial water resources for these rivers, in addition to its weather-related and climatic significance. The high mountain terrain of Tibet is the main condition that snow cover exists and persists at mid–low altitudes. However, the relationships between snow cover and topographic factors of the plateau have not been fully addressed. In this study, the overall spatial distribution of snow cover and the impacts of topography (elevation, aspect and slope) on snow cover distribution in Tibet were analyzed based on the MODIS snow cover product and digital elevation model (DEM) using GIS spatial analysis techniques. The results showed that (1) snow cover in Tibet is spatially very uneven and is characterized by rich snow and high SCF (snow cover frequency) on Nyainqentanglha mountain and the surrounding high mountains, with less snow and a low SCF in the southern Tibetan valley and central part of northern Tibet. (2) Snow cover in Tibet has a strong elevation dependence and a higher SCF corresponds well with high mountain ranges. The mean SCF below 2000 m above sea level (m a.s.l) was less than 4%, while above 6000 m a.s.l, it reached 75%. (3) Intra-annual snow cover distribution below 4000 m a.s.l was characterized by unimodal patterns, while above 4000 m a.s.l, it was characterized by bimodal patterns. The lowest SCF below 6000 m a.s.l occurred in summer, while above 6000 m it occurred in winter. (4) The mountain slope and aspect affect snow cover distribution through changing radiation and energy balances in the mountain regions. The mean SCF generally increased with mountain slopes, with the highest on the north-facing aspect and the lowest on the south-facing aspect.