Disconnection of Network Hubs Underlying the Executive Function Deficit in Patients with Ischemic Leukoaraiosis.

BACKGROUND: Cognitive impairment is the most common clinical manifestation of ischemic leukoaraiosis (ILA), but the underlying neurobiological pathways have not been well elucidated. Recently, it was thought that ILA is a "disconnection syndrome". Disorganized brain connectome were considered the key neuropathology underlying cognitive deficits in ILA patients. OBJECTIVE: We aimed to detect the disruption of network hubs in ILA patients using a new analytical method called voxel-based eigenvector centrality (EC) mapping. METHODS: Subjects with moderate to severe white matters hyperintensities (Fazekas score ≥3) and healthy controls (HCs) (Fazekas score = 0) were included in the study. The resting-state functional magnetic resonance imaging and the EC mapping approach were performed to explore the alteration of whole-brain network connectivity in ILA patients. RESULTS: Relative to the HCs, the ILA patients exhibited poorer cognitive performance in episodic memory, information processing speed, and executive function (all ps < 0.0125). Additionally, compared with HCs, the ILA patients had lower functional connectivity (i.e., EC values) in the medial parts of default-mode network (i.e., bilateral posterior cingulate gyrus and ventral medial prefrontal cortex [vMPFC]). Intriguingly, the functional connectivity strength at the right vMPFC was positively correlated with executive function deficit in the ILA patients. CONCLUSION: The findings suggested disorganization of the hierarchy of the default-mode regions within the whole-brain network in patients with ILA and advanced our understanding of the neurobiological mechanism underlying executive function deficit in ILA.

Genome-Wide Identification, Characterization and Experimental Expression Analysis of CNGC Gene Family in Gossypium.

Cyclic nucleotide-gated ion channels (CNGCs) are channel proteins for calcium ions, and have been reported to play important roles in regulating survival and environmental response of various plants. However, little is known about how the CNGC family works in Gossypium. In this study, 173 CNGC genes, which were identified from two diploid and five tetraploid Gossypium species, were classified into four groups by phylogenetic analysis. The collinearity results demonstrated that CNGC genes are integrally conservative among Gossypium species, but four gene losses and three simple translocations were detected, which is beneficial to analyzing the evolution of CNGCs in Gossypium. The various cis-acting regulatory elements in the CNGCs' upstream sequences revealed their possible functions in responding to multiple stimuli such as hormonal changes and abiotic stresses. In addition, expression levels of 14 CNGC genes changed significantly after being treated with various hormones. The findings in this study will contribute to understanding the function of the CNGC family in cotton, and lay a foundation for unraveling the molecular mechanism of cotton plants' response to hormonal changes.

Association of platelet-to-neutrophil ratios with 1-year outcome and mortality in patients with acute ischemic stroke.

BACKGROUND: Platelet-neutrophil crosstalk is being increasingly recognized as a driver of inflammation and thrombosis in patients with ischemic stroke. The aim of this study was to investigate the potential of PNR value in predicting the long-term prognosis and evaluate whether or not an available and routine blood cell biomarker could help predict the long-term neurological function and mortality in AIS patients. METHODS: A total of 718 patients with suspected acute ischemic stroke were involved and followed up for 1 year by standard telephone interview or reexamination. Kaplan-Meier curve, Univariate and Multivariate Cox Regression were analyzed using Statistical Packages for Social Sciences. RESULTS: ROC curve for PNR to evaluate 1-year outcomes was analyzed and the area under the curve (AUC) was 0.659 (P < 0.001). The cutoff point was observed at 38.30, with a sensitivity of 53.09 % and a specificity of 71.25 %. Moreover, patients in PNR ≤ 38.30 were more likely to have more serious NIHSS on admission, 1-year mRS and higher 1-year mortality (P < 0.001, respectively). The 1-year mortality in the low PNR group was significantly higher than that of the high PNR group (log-rank tests: P < 0.0001). Age, NIHSS, RBC and PNR were combined into model B which significantly increased the AUC value from 0.736 to 0.888 compared to model A (including Age, NIHSS and RBC). CONCLUSION: PNR may serve as a readily assessable biomarker for early predicting neurological deterioration and the long-term prognosis of AIS. The nomogram that included age, NIHSS, PNR and RBC may be a useful predictive tool for 1-year mortality.

Meta-Analysis on the Anesthetic Effects of Remifentanil plus Dexmedetomidine versus Remifentanil Alone in Cardiac Surgery.

In this study, we performed a meta-analysis to investigate the anesthesia effects of remifentanil plus dexmedetomidine versus remifentanil alone in cardiac surgery. Literature search was performed on PubMed, Web of Science, Embase, China Knowledge Infrastructure, Wanfang Data, and other databases for relevant literature published in English or Chinese before October 2021. A total of 17 studies, consisting of 1350 patients, were included in this study. Of these, 10 studies showed that remifentanil plus dexmedetomidine had a good anesthesia effect in cardiac surgery (OR = 3.61, 95% CI: 1.73, 7.52, P < 0.001), and 8 studies showed that the Ramsay score test of anesthesia (SMD = 0.88; 95% CI: -0.77, 2.53; P < 0.001) in the experimental group was better than that in the control group. In addition, changes in the hemodynamic heart rate (SMD = -0.74; 95% CI: -1.41, -0.07; P < 0.001) and mean arterial pressure (SMD = -0.18; 95% CI: -0.72, 0.36; P < 0.001) of the two groups of anesthesia were counted in 17 studies, which also showed that the anesthesia effect of remifentanil plus dexmedetomidine was good. Thus, remifentanil plus dexmedetomidine may be a more promising option for cardiac surgery anesthesia than remifentanil alone.

Identification and fine-mapping of a major QTL (PH1.1) conferring plant height in broomcorn millet (Panicum miliaceum).

The plant height of broomcorn millet (Panicum miliaceum) is a significant agronomic trait that is closely related to its plant architecture, lodging resistance, and final yield. However, the genes underlying the regulation of plant height in broomcorn millet are rarely reported. Here, an F2 population derived from a cross between a normal variety, "Longmi12," and a dwarf mutant, "Zhang778," was constructed. Genetic analysis for the F2 and F2:3 populations revealed that the plant height was controlled by more than one locus. A major quantitative trait locus (QTL), PH1.1, was preliminarily identified in chromosome 1 using bulked segregant analysis sequencing (BSA-seq). PH1.1 was fine-mapped to a 109-kb genomic region with 15 genes using a high-density map. Among them, longmi011482 and longmi011489, containing nonsynonymous variations in their coding regions, and longmi011496, covering multiple insertion/deletion sequences in the promoter regions, may be possible candidate genes for PH1.1. Three diagnostic markers closely linked to PH1.1 were developed to validate the PH1.1 region in broomcorn millet germplasm. These findings laid the foundation for further understanding of the molecular mechanism of plant height regulation in broomcorn millet and are also beneficial to the breeding program for developing new varieties with optimal height.

Natural variation of GhSI7 increases seed index in cotton.

KEY MESSAGE: qSI07.1, a major QTL for seed index in cotton, was fine-mapped to a 17.45-kb region, and the candidate gene GhSI7 was verified in transgenic plants. Improving production to meet human needs is a vital objective in cotton breeding. The yield-related trait seed index is a complex quantitative trait, but few candidate genes for seed index have been characterized. Here, a major QTL for seed index qSI07.1 was fine-mapped to a 17.45-kb region by linkage analysis and substitutional mapping. Only GhSI7, encoding the transcriptional regulator STERILE APETALA, was contained in the candidate region. Association test and genetic analysis indicated that an 845-bp-deletion in its intron was responsible for the seed index variation. Origin analysis revealed that this variation was unique in Gossypium hirsutum and originated from race accessions. Overexpression of GhSI7 (haplotype 2) significantly increased the seed index and organ size in cotton plants. Our findings provided a diagnostic marker for breeding and selecting cotton varieties with high seed index, and laid a foundation for further studies to understand the molecular mechanism of cotton seed morphogenesis.

Identification of small effect quantitative trait loci of plant architectural, flowering, and early maturity traits in reciprocal interspecific introgression population in cotton.

Plant architecture, flowering time and maturity traits are important determinants of yield and fiber quality of cotton. Genetic dissection of loci determining these yield and quality components is complicated by numerous loci with alleles conferring small differences. Therefore, mapping populations segregating for smaller numbers and sizes of introgressed segments is expected to facilitate dissection of these complex quantitative traits. At an advanced stage in the development of reciprocal advanced backcross populations from crosses between elite Gossypium hirsutum cultivar 'Acala Maxxa' (GH) and G. barbadense 'Pima S6' (GB), we undertook mapping of plant architectural traits, flowering time and maturity. A total of 284 BC4F1 and BC4F2 progeny rows, 120 in GH and 164 in GB background, were evaluated for phenotype, with only 4 and 3 (of 7) traits showing significant differences among progenies. Genotyping by sequencing yielded 3,186 and 3,026 SNPs, respectively, that revealed a total of 27 QTLs in GH background and 22 in GB, for plant height, days to flowering, residual flowering at maturity and maturity. More than of 90% QTLs identified in both backgrounds had small effects (%PV < 10), supporting the merit of this population structure to reduce background noise and small effect QTLs. Germplasm developed in this study may serve as potential pre-breeding material to develop improved cotton cultivars.

Collateral circulation detected by arterial spin labeling predicts outcome in acute ischemic stroke.

BACKGROUND: Robust collateral circulation is strongly associated with good outcomes in acute ischemic stroke (AIS). AIMS: To determine whether collateral circulation detected by arterial spin labeling (ASL) magnetic resonance imaging could predict good clinical outcome in AIS patients with 90 days follow-up. MATERIALS AND METHODS: Total 58 AIS patients with anterior circulation stroke were recruited. Collateral circulation was defined as arterial transit artifact in ASL images. Modified Rankin Scale (mRS), the Barthel Index, and National Institutes of Health Stroke Scale (NIHSS) were employed to evaluate neurological function for the baseline and 90 days follow-up. The percent changes of these scores were also calculated, respectively. Finally, a support vector classifier model of machine learning and receiver operating characteristic curve were employed to estimate the power of ASL collaterals (ASLcs) predicting the clinical outcome. RESULTS: Patients with ASLcs represented higher rate of good outcome (83.30% vs. 31.25%, p < .001) and lower follow-up mRS scores (p < .001), when compared to patients without ASLcs. There were significant differences for percent changes of mRS scores and NIHSS scores between these two groups. Further, the presence of ASLcs could predict good clinical outcome (OR, 1.54; 95% CI, 1.10-2.16), even after controlling for baseline NIHSS scores. The SVC model incorporating baseline NIHSS scores and ASLcs had significant predictive effect (accuracy, 79.3%; AUC, 0.806) on clinical prognosis for AIS patients. DISCUSSION: We targeted on the non-invasive assessment of collateral circulation using ASL technique and found that patients with ASLcs were more likely to have a good clinical outcome after AIS. This finding is of guiding significance for treatment selection and prognostic prediction. CONCLUSIONS: Early ASLcs assessment provides a good powerful tool to predict clinical outcome for AIS patients with 90 days follow-up.

Machine Learning-Based Model for Prediction of Hemorrhage Transformation in Acute Ischemic Stroke After Alteplase.

Hemorrhage transformation (HT) is the most dreaded complication of intravenous thrombolysis (IVT) in acute ischemic stroke (AIS). The prediction of HT after IVT is important in the treatment decision-making for AIS. We designed and compared different machine learning methods, capable of predicting HT in AIS after IVT. A total of 345 AIS patients who received intravenous alteplase between January 2016 and June 2021 were enrolled in this retrospective study. The demographic characteristics, clinical condition, biochemical data, and neuroimaging variables were included for analysis. HT was confirmed by head computed tomography (CT) or magnetic resonance imaging (MRI) within 48 h after IVT. Based on the neuroimaging results, all of the patients were divided into the non-HT group and the HT group. Then, the variables were applied in logistic regression (LR) and random forest (RF) algorithms to establish HT prediction models. To evaluate the accuracy of the machine learning models, the models were compared to several of the common scales used in clinics, including the multicenter stroke survey (MSS) score, safe implementation of treatments in stroke (SITS) score, and SEDAN score. The performance of these prediction models was evaluated using the receiver operating characteristic (ROC) curve (AUC). Forty-five patients had HT (13.0%) within 48 h after IVT. The ROC curve results showed that the AUCs of HT that were predicted by the RF model, LR model, MSS, SITS, and SEDAN scales after IVT were 0.795 (95% CI, 0.647-0.944), 0.703 (95% CI, 0.515-0.892), 0.657 (95% CI, 0.574-0.741), 0.660 (95% CI, 0.580-0.740) and 0.655 (95% CI, 0.571-0.739), respectively. The RF model performed better than the other models and scales. The top four most influential factors in the RF importance matrix plot were triglyceride, Lpa, the baseline NIHSS, and hemoglobin. The SHapley Additive exPlanation values made the RF prediction model clinically interpretable. In this study, an RF machine learning method was successfully established to predict HT in AIS patients after intravenous alteplase, which the sensitivity was 66.7%, and the specificity was 80.7%.

Identification of Candidate Genes for Lint Percentage and Fiber Quality Through QTL Mapping and Transcriptome Analysis in an Allotetraploid Interspecific Cotton CSSLs Population.

Upland cotton (Gossypium hirsutum) has long been an important fiber crop, but the narrow genetic diversity of modern G. hirsutum limits the potential for simultaneous improvement of yield and fiber quality. It is an effective approach to broaden the genetic base of G. hirsutum through introgression of novel alleles from G. barbadense with excellent fiber quality. In the present study, an interspecific chromosome segment substitution lines (CSSLs) population was established using G. barbadense cultivar Pima S-7 as the donor parent and G. hirsutum cultivar CCRI35 as the recipient parent. A total of 105 quantitative trait loci (QTL), including 85 QTL for fiber quality and 20 QTL for lint percentage (LP), were identified based on phenotypic data collected from four environments. Among these QTL, 25 stable QTL were detected in two or more environments, including four for LP, eleven for fiber length (FL), three for fiber strength (FS), six for fiber micronaire (FM), and one for fiber elongation (FE). Eleven QTL clusters were observed on nine chromosomes, of which seven QTL clusters harbored stable QTL. Moreover, eleven major QTL for fiber quality were verified through analysis of introgressed segments of the eight superior lines with the best comprehensive phenotypes. A total of 586 putative candidate genes were identified for 25 stable QTL associated with lint percentage and fiber quality through transcriptome analysis. Furthermore, three candidate genes for FL, GH_A08G1681 (GhSCPL40), GH_A12G2328 (GhPBL19), and GH_D02G0370 (GhHSP22.7), and one candidate gene for FM, GH_D05G1346 (GhAPG), were identified through RNA-Seq and qRT-PCR analysis. These results lay the foundation for understanding the molecular regulatory mechanism of fiber development and provide valuable information for marker-assisted selection (MAS) in cotton breeding.

Genome-wide identification of quantitative trait loci for morpho-agronomic and yield-related traits in foxtail millet (Setaria italica) across multi-environments.

Foxtail millet (Setaria italica) is an ideal model of genetic system for functional genomics of the Panicoideae crop. Identification of QTL responsible for morpho-agronomic and yield-related traits facilitates dissection of genetic control and breeding in cereal crops. Here, based on a Yugu1 × Longgu7 RIL population and genome-wide resequencing data, an updated linkage map harboring 2297 bin and 74 SSR markers was constructed, spanning 1315.1 cM with an average distance of 0.56 cM between adjacent markers. A total of 221 QTL for 17 morpho-agronomic and yield-related traits explaining 5.5 ~ 36% of phenotypic variation were identified across multi-environments. Of these, 109 QTL were detected in two to nine environments, including the most stable qLMS6.1 harboring a promising candidate gene Seita.6G250500, of which 70 were repeatedly identified in different trials in the same geographic location, suggesting that foxtail millet has more identical genetic modules under the similar ecological environment. One hundred-thirty QTL with overlapping intervals formed 22 QTL clusters. Furthermore, six superior recombinant inbred lines, RIL35, RIL48, RIL77, RIL80, RIL115 and RIL125 with transgressive inheritance and enrichment of favorable alleles in plant height, tiller, panicle morphology and yield related-traits were screened by hierarchical cluster. These identified QTL, QTL clusters and superior lines lay ground for further gene-trait association studies and breeding practice in foxtail millet.

Identification of the Neural Circuit Underlying Episodic Memory Deficit in Amnestic Mild Cognitive Impairment via Machine Learning on Gray Matter Volume.

Based on whole-brain gray matter volume (GMV), we used relevance vector regression to predict the Rey's Auditory Verbal Learning Test Delayed Recall (AVLT-DR) scores of individual amnestic mild cognitive impairment (aMCI) patient. The whole-brain GMV pattern could significantly predict the AVLT-DR scores (r = 0.54, p < 0.001). The most important GMV features mainly involved default-mode (e.g., posterior cingulate gyrus, angular gyrus, and middle temporal gyrus) and limbic systems (e.g., hippocampus and parahippocampal gyrus). Therefore, our results provide evidence supporting the idea that the episodic memory deficit in aMCI patients is associated with disruption of the default-mode and limbic systems.

Analyzing Quantitative Trait Loci for Fiber Quality and Yield-Related Traits From a Recombinant Inbred Line Population With Gossypium hirsutum Race palmeri as One Parent.

Fiber quality and yield-related traits are important agronomic traits in cotton breeding. To detect the genetic basis of fiber quality and yield related traits, a recombinant inbred line (RIL) population consisting of 182 lines was established from a cross between Gossypium hirsutum cultivar CCRI35 and G. hirsutum race palmeri accession TX-832. The RIL population was deeply genotyped using SLAF-seq and was phenotyped in six environments. A high-density genetic linkage map with 15,765 SNP markers and 153 SSR markers was constructed, with an average distance of 0.30 cM between adjacent markers. A total of 210 fiber quality quantitative trait loci (QTLs) and 73 yield-related QTLs were identified. Of the detected QTLs, 62 fiber quality QTLs and 10 yield-related QTLs were stable across multiple environments. Twelve and twenty QTL clusters were detected on the At and Dt subgenome, respectively. Twenty-three major QTL clusters were further validated through associated analysis and five candidate genes of four stable fiber quality QTLs were identified. This study revealed elite loci influencing fiber quality and yield and significant phenotypic selection regions during G. hirsutum domestication, and set a stage for future utilization of molecular marker assisted breeding in cotton breeding programs.

Genetic Identification and Transcriptome Analysis of Lintless and Fuzzless Traits in Gossypium arboreum L.

Cotton fibres, as single cells arising from the seed coat, can be classified as lint and fuzz according to their final length. Gossypium arboreum is a cultivated diploid cotton species and a potential donor of the A subgenome of the more widely grown tetraploid cottons. In this study, we performed genetic studies on one lintless and seven fuzzless G. arboreum accessions. Through association and genetic linkage analyses, a recessive locus on Chr06 containing GaHD-1 was found to be the likely gene underlying the lintless trait. GaHD-1 carried a mutation at a splicing acceptor site that resulted in alternative splicing and a deletion of 247 amino acid from the protein. The regions containing GaGIR1 and GaMYB25-like were found to be associated with fuzz development in G. arboreum, with the former being the major contributor. Comparative transcriptome analyses using 0-5 days post-anthesis (dpa) ovules from lintless, fuzzless, and normal fuzzy seed G. arboreum accessions revealed gene modules and hub genes potentially important for lint and fuzz initiation and development. Three significant modules and 26 hub genes associated with lint fibre initiation were detected by weighted gene co-expression network analysis. Similar analyses identified three vital modules and 10 hub genes to be associated with fuzz development. The findings in this study contribute to understanding the complex molecular mechanism(s) regulating fibre initiation and development and indicate that G. arboreum may have fibre developmental pathways different from tetraploid cotton. It also provides candidate genes for further investigation into modifying fibre development in G. arboreum.

QTL mapping of yield component traits on bin map generated from resequencing a RIL population of foxtail millet (Setaria italica).

BACKGROUND: Foxtail millet (Setaria italica) has been developed into a model genetical system for deciphering architectural evolution, C4 photosynthesis, nutritional properties, abiotic tolerance and bioenergy in cereal grasses because of its advantageous characters with the small genome size, self-fertilization, short growing cycle, small growth stature, efficient genetic transformation and abundant diverse germplasm resources. Therefore, excavating QTLs of yield component traits, which are closely related to aspects mentioned above, will further facilitate genetic research in foxtail millet and close cereal species. RESULTS: Here, 164 Recombinant inbreed lines from a cross between Longgu7 and Yugu1 were created and 1,047,978 SNPs were identified between both parents via resequencing. A total of 3413 bin markers developed from SNPs were used to construct a binary map, containing 3963 recombinant breakpoints and totaling 1222.26 cM with an average distance of 0.36 cM between adjacent markers. Forty-seven QTLs were identified for four traits of straw weight, panicle weight, grain weight per plant and 1000-grain weight. These QTLs explained 5.5-14.7% of phenotypic variance. Thirty-nine favorable QTL alleles were found to inherit from Yugu1. Three stable QTLs were detected in multi-environments, and nine QTL clusters were identified on Chromosome 3, 6, 7 and 9. CONCLUSIONS: A high-density genetic map with 3413 bin markers was constructed and three stable QTLs and 9 QTL clusters for yield component traits were identified. The results laid a powerful foundation for fine mapping, identifying candidate genes, elaborating molecular mechanisms and application in foxtail millet breeding programs by marker-assisted selection.

De novo transcriptome assembly and identification of genes related to seed size in common buckwheat (Fagopyrum esculentum M.).

Common buckwheat (Fagopyrum esculentum M.) belongs to the eudicot family Polygonaceae, Fagopyrum Mill, and its seeds have high nutritional value. The mechanism of seed development of common buckwheat remains unclear at the molecular level and no genes related to seed size have been identified. In this study, we performed genome-wide transcriptome sequencing and analysis using common buckwheat seeds at 5 days post anthesis (DPA) and 10 DPA from two cultivars (large-seeded and small-seeded). A total of 259,895 transcripts were assembled, resulting in 187,034 unigenes with average length of 1097 bp and N50 of 1538 bp. Based on gene expression profiles, 9127 differentially expressed genes (DEGs) were identified and analyzed in GO enrichment and KEGG analysis. In addition, genes related to seed size in the IKU pathway, ubiquitin-proteasome pathway, MAPK signaling pathway, TFs and phytohormones were identified and analyzed. AP2 and bZIP transcription factors, BR-signal and ABA were considered to be important regulators of seed size. This study provides a valuable genetic resource for future identification and functional analysis of candidate genes regulating seed size in common buckwheat and will be useful for improving seed yield in common buckwheat through molecular breeding in the future.

A high density SLAF-seq SNP genetic map and QTL for seed size, oil and protein content in upland cotton.

BACKGROUND: Cotton is a leading natural fiber crop. Beyond its fiber, cottonseed is a valuable source of plant protein and oil. Due to the much higher value of cotton fiber, there is less consideration of cottonseed quality despite its potential value. Though some QTL controlling cottonseed quality have been identified, few of them that warrant further study are known. Identifying stable QTL controlling seed size, oil and protein content is necessary for improvement of cottonseed quality. RESULTS: In this study, a recombinant inbred line (RIL) population was developed from a cross between upland cotton cultivars/lines Yumian 1 and M11. Specific locus amplified fragment sequencing (SLAF-seq) technology was used to construct a genetic map that covered 3353.15 cM with an average distance between consecutive markers of 0.48 cM. The seed index, together with kernel size, oil and protein content were further used to identify QTL. In total, 58 QTL associated with six traits were detected, including 13 stable QTL detected in all three environments and 11 in two environments. CONCLUSION: A high resolution genetic map including 7033 SNP loci was constructed through specific locus amplified fragment sequencing technology. A total of 13 stable QTL associated with six cottonseed quality traits were detected. These stable QTL have the potential for fine mapping, identifying candidate genes, elaborating molecular mechanisms of cottonseed development, and application in cotton breeding programs.

Over-expression of the red plant gene R1 enhances anthocyanin production and resistance to bollworm and spider mite in cotton.

Anthocyanins are a class of pigments ubiquitously distributed in plants and play roles in adoption to several stresses. The red plant gene (R1) promotes light-induced anthocyanin accumulation and red/purple pigmentation in cotton. Using 11 markers developed via genome resequencing, the R1 gene was located in an interval of approximately 136 kb containing three annotated genes. Among them, a PAP1 homolog, GhPAP1D (Gohir.D07G082100) displayed differential transcript level in the red- and green-plant leaves. GhPAP1D encoded a R2R3-MYB transcription factor and its over-expression resulted in increased anthocyanin accumulation in transgenic tobaccos and cottons. Dual luciferase assay indicated that GhPAP1D activated the promoters of several cotton anthocyanin structural genes in tobacco leaves. Importantly, we found that the GhPAP1D-overexpressing cotton leaves had increased resistance to both bollworm and spite mite. Our data demonstrated that GhPAP1D was the controlling gene of the red plant phenotype in cotton, and as the major anthocyanin regulator, this gene was potential to create transgenic cottons with resistance to a broad spectrum of herbivores.

A high density SLAF-SNP genetic map and QTL detection for fibre quality traits in Gossypium hirsutum.

BACKGROUND: Upland Cotton (Gossypium hirsutum) is a very important cash crop known for its high quality natural fiber. Recent advances in sequencing technologies provide powerful tools with which to explore the cotton genome for single nucleotide polymorphism marker identification and high density genetic map construction toward more reliable quantitative trait locus mapping. RESULTS: In the present study, a RIL population was developed by crossing a Chinese high fiber quality cultivar (Yumian 1) and an American high fiber quality line (CA3084), with distinct genetic backgrounds. Specific locus amplified fragment sequencing (SLAF-seq) technology was used to discover SNPs, and a genetic map containing 6254 SNPs was constructed, covering 3141.72 cM with an average distance of 0.5 cM between markers. A total of 95 QTL were detected for fiber quality traits in three environments, explaining 5.5-24.6% of the phenotypic variance. Fifty-five QTL found in multiple environments were considered stable QTL. Nine of the stable QTL were found in all three environments. We identified 14 QTL clusters on 13 chromosomes, each containing one or more stable QTL. CONCLUSION: A high-density genetic map of Gossypium hirsutum developed by using specific locus amplified fragment sequencing technology provides detailed mapping of fiber quality QTL, and identification of 'stable QTL' found in multiple environments. A marker-rich genetic map provides a foundation for fine mapping, candidate gene identification and marker-assisted selection of favorable alleles at stable QTL in breeding programs.

Natural variation in a CENTRORADIALIS homolog contributed to cluster fruiting and early maturity in cotton.

BACKGROUND: Plant architecture and the vegetative-reproductive transition have major impacts on the agronomic success of crop plants, but genetic mechanisms underlying these traits in cotton (Gossypium spp.) have not been identified. RESULTS: We identify four natural mutations in GoCEN-Dt associated with cluster fruiting (cl) and early maturity. The situ hybridization shows that GhCEN is preferentially expressed in cotton shoot apical meristems (SAM) of the main stem and axillary buds. Constitutive GhCEN-Dt overexpression suppresses the transition of the cotton vegetative apex to a reproductive shoot. Silencing GoCEN leads to early flowering and determinate growth, and in tetraploids causes the main stem to terminate in a floral bud, a novel phenotype that exemplifies co-adaptation of polyploid subgenomes and suggests new research and/or crop improvement approaches. Natural cl variations are enriched in cottons adapted to high latitudes with short frost-free periods, indicating that mutants of GoCEN have been strongly selected for early maturity. CONCLUSION: We show that the cotton gene GoCEN-Dt, a homolog of Antirrhinum CENTRORADIALIS, is responsible for determinate growth habit and cluster fruiting. Insight into the genetic control of branch and flower differentiation offers new approaches to develop early maturing cultivars of cotton and other crops with plant architecture appropriate for mechanical harvesting.