Publisher's copyright statement:Additional information: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Dt, 0.56 × 10 -3 ) ( Fig. 1d and Supplementary Fig. 3). This shows that a large amount is associated with the development of the long fiber trait in cultivated cotton (Fig. 3b). 217Domestication has led to the transformation of cotton fiber from brown to white. 218To understand this phenomenon, we examined two homoeologous gene pairs only 219 subjected to domestication selection in the Dt, 4-COUMARATE:COA LIGASE (4CL) 220 and CHALCONE SYNTHASE (CHS), which encode enzymes involved in the 221 phenylpropanoid metabolic pathway ( Fig. 3c and Supplementary Fig. 6 Fig. 3c). These SNPs display reductions in nucleotide diversity that occurred 225 during domestication (Fig. 3c). Interestingly, we found that the two SNPs in the Fig. 8) 42 . We identified a total of 188,360 DNase I-hypersensitive 248 sites (DHSs) in cotton leaves and fibers, of which ca. 47% are common to both tissues 249 (Fig. 4a). DHSs were preferentially identified in chromosomal arms and 250 approximately half were detected in promoter and intergenic regions ( Fig. 4b and 251 Supplementary Fig. 9). We found DHSs are hypo-methylated, consistent with 252 previous studies 42 (Fig. 4c) H3K4me1 and inactive H3K9me2 (Fig. 4d). Intergenic DHSs were also found to 255 exhibit an enrichment of H3K4me3 and H3K27me3, but depletion of H3K9me2 and 256 no enrichment of H3K4me1 (Fig. 4e). As predicted, the patterns of chromatin 257 modification marks in cotton are different between genic and TE regions 258 ( Supplementary Fig. 10). In addition, genes with promoter DHSs are generally 259 expressed at a higher level in both tissues than those without promoter DHSs (Fig. 4f), 260 and tissue-specific promoter DHSs corresponded to higher levels of gene expression 261 ( Fig. 4g) Hi-C analysis was carried out using the TM-1 accession to characterize global 296 chromatin interactions. We generated 1.1 billion Hi-C paired-end reads, of which ca. possible Hi-C bias, HindIII fragments of less than 2 kb were merged to obtain 299 305,682 chromosomal anchor regions (Fig. 5a). On the basis of a high-quality 300 genome assembly of TM-1 (Supplementary Fig. 11), we used the Hi-C data to 301 characterize the cotton chromatin interactome (Supplementary Fig. 12) and ( Fig. 5b), but many topologically associated domain-like (TAD-like) regions were 305 identified (Fig. 5c, Supplementary Fig. 13 and Supplementary are less frequent at regions marked by H3K9me2 (Fig. 5d). (Fig. 5g). 320We...

BackgroundThe study of quantitative trait loci (QTL) in cotton (Gossypium spp.) is focused on traits of agricultural significance. Previous studies have identified a plethora of QTL attributed to fiber quality, disease and pest resistance, branch number, seed quality and yield and yield related traits, drought tolerance, and morphological traits. However, results among these studies differed due to the use of different genetic populations, markers and marker densities, and testing environments. Since two previous meta-QTL analyses were performed on fiber traits, a number of papers on QTL mapping of fiber quality, yield traits, morphological traits, and disease resistance have been published. To obtain a better insight into the genome-wide distribution of QTL and to identify consistent QTL for marker assisted breeding in cotton, an updated comparative QTL analysis is needed.ResultsIn this study, a total of 1,223 QTL from 42 different QTL studies in Gossypium were surveyed and mapped using Biomercator V3 based on the Gossypium consensus map from the Cotton Marker Database. A meta-analysis was first performed using manual inference and confirmed by Biomercator V3 to identify possible QTL clusters and hotspots. QTL clusters are composed of QTL of various traits which are concentrated in a specific region on a chromosome, whereas hotspots are composed of only one trait type. QTL were not evenly distributed along the cotton genome and were concentrated in specific regions on each chromosome. QTL hotspots for fiber quality traits were found in the same regions as the clusters, indicating that clusters may also form hotspots.ConclusionsPutative QTL clusters were identified via meta-analysis and will be useful for breeding programs and future studies involving Gossypium QTL. The presence of QTL clusters and hotspots indicates consensus regions across cultivated tetraploid Gossypium species, environments, and populations which contain large numbers of QTL, and in some cases multiple QTL associated with the same trait termed a hotspot. This study combines two previous meta-analysis studies and adds all other currently available QTL studies, making it the most comprehensive meta-analysis study in cotton to date.

With the development of technologies, such as big data, cloud computing, and the Internet of Things (IoT), digital twin is being applied in industry as a precision simulation technology from concept to practice. Further, simulation plays a very important role in the healthcare field, especially in research on medical pathway planning, medical resource allocation, medical activity prediction, etc. By combining digital twin and healthcare, there will be a new and efficient way to provide more accurate and fast services for elderly healthcare. However, how to achieve personal health management throughout the entire lifecycle of elderly patients, and how to converge the medical physical world and the virtual world to realize real smart healthcare, are still two key challenges in the era of precision medicine. In this paper, a framework of the cloud healthcare system is proposed based on digital twin healthcare (CloudDTH). This is a novel, generalized, and extensible framework in the cloud environment for monitoring, diagnosing and predicting aspects of the health of individuals using, for example, wearable medical devices, toward the goal of personal health management, especially for the elderly. CloudDTH aims to achieve interaction and convergence between medical physical and virtual spaces. Accordingly, a novel concept of digital twin healthcare (DTH) is proposed and discussed, and a DTH model is implemented. Next, a reference framework of CloudDTH based on DTH is constructed, and its key enabling technologies are explored. Finally, the feasibility of some application scenarios and a case study for real-time supervision are demonstrated.INDEX TERMS Digital twin, elderly healthcare, personal health management, cloud computing, precision medicine, interaction, convergence. I. INTRODUCTIONAccording to the latest statistics from the United Nations Department of Economic and Social Affairs, the elderly population is forecasted to be 2.1 billion in 2050, with the aging population in the developing regions growing faster than in the developed regions [1]. In the aging society of the future, it is projected that nearly 50% of medical resources will be The associate editor coordinating the review of this manuscript and approving it for publication was Tai-Hoon Kim.

Summary Gossypium hirsutum L. represents the largest source of textile fibre, and China is one of the largest cotton‐producing and cotton‐consuming countries in the world. To investigate the genetic architecture of the agronomic traits of upland cotton in China, a diverse and nationwide population containing 503 G. hirsutum accessions was collected for a genome‐wide association study (GWAS) on 16 agronomic traits. The accessions were planted in four places from 2012 to 2013 for phenotyping. The CottonSNP63K array and a published high‐density map based on this array were used for genotyping. The 503 G. hirsutum accessions were divided into three subpopulations based on 11 975 quantified polymorphic single‐nucleotide polymorphisms (SNPs). By comparing the genetic structure and phenotypic variation among three genetic subpopulations, seven geographic distributions and four breeding periods, we found that geographic distribution and breeding period were not the determinants of genetic structure. In addition, no obvious phenotypic differentiations were found among the three subpopulations, even though they had different genetic backgrounds. A total of 324 SNPs and 160 candidate quantitative trait loci (QTL) regions were identified as significantly associated with the 16 agronomic traits. A network was established for multieffects in QTLs and interassociations among traits. Thirty‐eight associated regions had pleiotropic effects controlling more than one trait. One candidate gene, Gh_D08G2376, was speculated to control the lint percentage (LP). This GWAS is the first report using high‐resolution SNPs in upland cotton in China to comprehensively investigate agronomic traits, and it provides a fundamental resource for cotton genetic research and breeding.

BackgroundCotton, with a large genome, is an important crop throughout the world. A high-density genetic linkage map is the prerequisite for cotton genetics and breeding. A genetic map based on simple polymerase chain reaction markers will be efficient for marker-assisted breeding in cotton, and markers from transcribed sequences have more chance to target genes related to traits. To construct a genome-wide, functional marker-based genetic linkage map in cotton, we isolated and mapped expressed sequence tag-simple sequence repeats (EST-SSRs) from cotton ESTs derived from the A1, D5, (AD)1, and (AD)2 genome.ResultsA total of 3177 new EST-SSRs developed in our laboratory and other newly released SSRs were used to enrich our interspecific BC1 genetic linkage map. A total of 547 loci and 911 loci were obtained from our EST-SSRs and the newly released SSRs, respectively. The 1458 loci together with our previously published data were used to construct an updated genetic linkage map. The final map included 2316 loci on the 26 cotton chromosomes, 4418.9 cM in total length and 1.91 cM in average distance between adjacent markers. To our knowledge, this map is one of the three most dense linkage maps in cotton. Twenty-one segregation distortion regions (SDRs) were found in this map; three segregation distorted chromosomes, Chr02, Chr16, and Chr18, were identified with 99.9% of distorted markers segregating toward the heterozygous allele. Functional analysis of SSR sequences showed that 1633 loci of this map (70.6%) were transcribed loci and 1332 loci (57.5%) were translated loci.ConclusionsThis map lays groundwork for further genetic analyses of important quantitative traits, marker-assisted selection, and genome organization architecture in cotton as well as for comparative genomics between cotton and other species. The segregation distorted chromosomes can be a guide to identify segregation distortion loci in cotton. The annotation of SSR sequences identified frequent and rare gene ontology items on each chromosome, which is helpful to discover functions of cotton chromosomes.