Gossypium hirsutum has proven difficult to sequence owing to its complex allotetraploid (AtDt) genome. Here we produce a draft genome using 181-fold paired-end sequences assisted by fivefold BAC-to-BAC sequences and a high-resolution genetic map. In our assembly 88.5% of the 2,173-Mb scaffolds, which cover 89.6%∼96.7% of the AtDt genome, are anchored and oriented to 26 pseudochromosomes. Comparison of this G. hirsutum AtDt genome with the already sequenced diploid Gossypium arboreum (AA) and Gossypium raimondii (DD) genomes revealed conserved gene order. Repeated sequences account for 67.2% of the AtDt genome, and transposable elements (TEs) originating from Dt seem more active than from At. Reduction in the AtDt genome size occurred after allopolyploidization. The A or At genome may have undergone positive selection for fiber traits. Concerted evolution of different regulatory mechanisms for Cellulose synthase (CesA) and 1-Aminocyclopropane-1-carboxylic acid oxidase1 and 3 (ACO1,3) may be important for enhanced fiber production in G. hirsutum.

Corona Virus Disease 2019 (COVID-19) is a recently emerged life-threatening disease caused by SARS-CoV-2. Real- time fluorescent PCR (RT-PCR) is the clinical standard for SARS-CoV-2 nucleic acid detection. To detect SARS-CoV-2 early and control the disease spreading on time, a faster and more convenient method for SARS-CoV-2 nucleic acid detecting, RT-LAMP method (reverse transcription loop-mediated isothermal amplification) was developed. RNA reverse transcription and nucleic acid amplification were performed in one step at 63 ℃ isothermal conditions, and the results can be obtained within 30 minutes. ORF1ab gene, E gene and N gene were detected at the same time. ORF1ab gene was very specific and N gene was very sensitivity, so they can guarantee both sensitivity and specificity for SARS-CoV-2. The sensitivity of RT-LAMP assay is similar to RT-PCR, and specificity was 99% as detecting 208 clinical specimens. The RT-LAMP assay reported here has the advantages of rapid amplification, simple operation, and easy detection, which is useful for the rapid and reliable clinical diagnosis of SARS-CoV-2.

The present study aimed to determine the differences in gut microbiota between patients with chronic kidney disease (CKD) and healthy controls (HC) and search for better microbial biomarkers associated with CKD. The 16S rRNA gene sequencing approach was used to investigate the differences in gut microbiota between the CKD and HC groups. The study found that 12 phylotypes were overrepresented in the CKD group and 19 in the HC group at the genus level. Furthermore, genera Lachnospira and Ruminococcus_gnavus performed the best in differentiating between HC and CKD populations. In addition, this novel study found that the genera Holdemanella, Megamonas, Prevotella 2, Dielma, and Scardovia were associated with the progression of CKD and hemodialysis. In conclusion, the composition of gut microbiota was different in CKD populations compared with healthy populations, and Lachnospira and R._gnavus were better microbial biomarkers. In addition, five phylotypes, including Holdemanella, Megamonas, Prevotella2, Dielma, and Scardovia, served as an indicator of the progression of CKD and hemodialysis. However, large-scale prospective studies should be performed to identify the reliability of the set of these phylotypes as biomarkers.