Solanum nigrum is a noxious weed in agricultural ecosystem that limits many crops’ production. The aim of the present study was to understand the level of genetic diversity and population structure of S. nigrum in China. A specific-locus amplified fragment (SLAF) sequencing method was conducted to detect single-nucleotide polymorphisms (SNPs) in the genomes of S. nigrum from 66 populations in China. A total of 616,533 high-quality SNPs were identified from 189,840 SLAFs, with an average sequencing depth of 10.59× fold and a Q30 value of 93% and a GC content of 42.78%. It showed a considerable amount of genetic diversity and genetic variability of S. nigrum among samples. The genetic differentiation of S. nigrum indicated that there was a low level of genetic differentiation (Fst < 0.1000) among geographical populations. A cluster analysis showed that populations of S. nigrum were divided into two subgroups, with some samples from adjacent position roughly clustered together, which showed some correlation between geographic origins. A population structure analysis suggested the 66 S. nigrum samples could have originated from three different genetic clusters. The Xinjiang site was the only location where all genetic clusters were found, which suggested these populations were genetically diverse. These results showed that there was a high degree of genetic diversity and low difference among the different geographical populations of S. nigrum. The results from the genetic structure of the SNP markers indicated that wide genetic variability exists among the population of S. nigrum in China, which may contribute to the adaptation and infestation of this weed species.

Black nightshade (Solanum nigrum L.) is one of the worst weeds in crop fields, and it spreads mainly by the dispersal of seeds. Temperature is one of the key environmental factors affecting seed germination. We investigated the seed germination response to temperature in six populations of S. nigrum from mid to northern China and derived mathematical models from germination data. The results showed that S. nigrum seeds exhibit distinct germination responses to temperature within the range of 15 to 35 °C. The optimum temperatures for the populations XJ1600, JL1697 and HLJ2134 were 30 °C, and those for the populations NMG1704, HN2160 and LN2209 were 25 °C, 20 °C and 15 °C, respectively. Based on the nonlinear fitting and thermal time models, the predicted base temperatures of the six populations ranged from 2.3 to 6.4 °C, and the required accumulated growing degree days (GDD) ranged from 50.3 to 106.0 °C·d. The base temperatures and the accumulated GDD for germination differed among populations, and there was a significant negative correlation. HLJ2134 population required a high base temperature and accumulated GDD for germination, indicating that it might highly adapted to a warmer and moister environment. Based on the different germination responses of S. nigrum populations to temperature, the thermal time model reflects an innate relationship between base temperature and accumulated GDD required for initiation of seed germination, which provides a better basis for predicting seedling emergence and the timing for optimal control of S. nigrum under field conditions.