Prediction of wheat SPAD using integrated multispectral and support vector machines.

Rapidly obtaining the chlorophyll content of crop leaves is of great significance for timely diagnosis of crop health and effective field management. Multispectral imagery obtained from unmanned aerial vehicles (UAV) is being used to remotely sense the SPAD (Soil and Plant Analyzer Development) values of wheat crops. However, existing research has not yet fully considered the impact of different growth stages and crop populations on the accuracy of SPAD estimation. In this study, 300 materials from winter wheat natural populations in Xinjiang, collected between 2020 to 2022, were analyzed. UAV multispectral images were obtained in the experimental area, and vegetation indices were extracted to analyze the correlation between the selected vegetation indices and SPAD values. The input variables for the model were screened, and a support vector machine (SVM) model was constructed to estimate SPAD values during the heading, flowering, and filling stages under different water stresses. The aim was to provide a method for the rapid acquisition of winter wheat SPAD values. The results showed that the SPAD values under normal irrigation were higher than those under water restriction. Multiple vegetation indices were significantly correlated with SPAD values. In the prediction model construction of SPAD, the different models had high estimation accuracy under both normal irrigation and water limitation treatments, with correlation coefficients of predicted and measured values under normal irrigation in different environments the value of r from 0.59 to 0.81 and RMSE from 2.15 to 11.64, compared to RE from 0.10% to 1.00%; and under drought stress in different environments, correlation coefficients of predicted and measured values of r was 0.69-0.79, RMSE was 2.30-12.94, and RE was 0.10%-1.30%. This study demonstrated that the optimal combination of feature selection methods and machine learning algorithms can lead to a more accurate estimation of winter wheat SPAD values. In summary, the SVM model based on UAV multispectral images can rapidly and accurately estimate winter wheat SPAD value.

Metabolic engineering of commensal bacteria for gut butyrate delivery and dissection of host-microbe interaction.

An overwhelming number of studies have reported the correlation of decreased abundance of butyrate-producing commensals with a wide range of diseases. However, the molecular-level mechanisms whereby gut butyrate causally affects the host mucosal immunity and pathogenesis were poorly understood, hindered by the lack of efficient tools to control intestinal butyrate. Here we engineered a facultative anaerobic commensal bacterium to delivery butyrate at the intestinal mucosal surface, and implemented it to dissect the causal role of gut butyrate in regulating host intestinal homeostasis in a model of murine chronic colitis. Mechanistically, we show that gut butyrate protected against colitis and preserved intestinal mucosal homeostasis through its inhibiting effect on the key pyroptosis executioner gasdermin D (GSDMD) of colonic epithelium, via functioning as an HDAC3 inhibitor. Overall, our work presents a new avenue to build synthetic living delivery bacteria to decode causal molecules at the host-microbe interface with molecular-level insights.

Prediction of Chlorophyll Content in Multi-Temporal Winter Wheat Based on Multispectral and Machine Learning.

To obtain the canopy chlorophyll content of winter wheat in a rapid and non-destructive high-throughput manner, the study was conducted on winter wheat in Xinjiang Manas Experimental Base in 2021, and the multispectral images of two water treatments' normal irrigation (NI) and drought stress (DS) in three key fertility stages (heading, flowering, and filling) of winter wheat were obtained by DJI P4M unmanned aerial vehicle (UAV). The flag leaf chlorophyll content (CC) data of different genotypes in the field were obtained by SPAD-502 Plus chlorophyll meter. Firstly, the CC distribution of different genotypes was studied, then, 13 vegetation indices, combined with the Random Forest algorithm and correlation evaluation of CC, and 14 vegetation indices were used for vegetation index preference. Finally, preferential vegetation indices and nine machine learning algorithms, Ridge regression with cross-validation (RidgeCV), Ridge, Adaboost Regression, Bagging_Regressor, K_Neighbor, Gradient_Boosting_Regressor, Random Forest, Support Vector Machine (SVM), and Least absolute shrinkage and selection operator (Lasso), were preferentially selected to construct the CC estimation models under two water treatments at three different fertility stages, which were evaluated by correlation coefficient (r), root means square error (RMSE) and the normalized root mean square error (NRMSE) to select the optimal estimation model. The results showed that the CC values under normal irrigation were higher than those underwater limitation treatment at different fertility stages; several vegetation indices and CC values showed a highly significant correlation, with the highest correlation reaching.51; in the prediction model construction of CC values, different models under normal irrigation and water limitation treatment had high estimation accuracy, among which the model with the highest prediction accuracy under normal irrigation was at the heading stage. The highest precision of the model prediction under normal irrigation was in the RidgeCV model (r = 0.63, RMSE = 3.28, NRMSE = 16.2%) and the highest precision of the model prediction under water limitation treatment was in the SVM model (r = 0.63, RMSE = 3.47, NRMSE = 19.2%).

A Clustering Algorithm for Multi-Modal Heterogeneous Big Data With Abnormal Data.

The problems of data abnormalities and missing data are puzzling the traditional multi-modal heterogeneous big data clustering. In order to solve this issue, a multi-view heterogeneous big data clustering algorithm based on improved Kmeans clustering is established in this paper. At first, for the big data which involve heterogeneous data, based on multi view data analyzing, we propose an advanced Kmeans algorithm on the base of multi view heterogeneous system to determine the similarity detection metrics. Then, a BP neural network method is used to predict the missing attribute values, complete the missing data and restore the big data structure in heterogeneous state. Last, we ulteriorly propose a data denoising algorithm to denoise the abnormal data. Based on the above methods, we construct a framework namely BPK-means to resolve the problems of data abnormalities and missing data. Our solution approach is evaluated through rigorous performance evaluation study. Compared with the original algorithm, both theoretical verification and experimental results show that the accuracy of the proposed method is greatly improved.

Butyrate Suppresses Glucose Metabolism of Colorectal Cancer Cells via GPR109a-AKT Signaling Pathway and Enhances Chemotherapy.

Glycolysis inhibitors are promising therapeutic drugs for tumor treatment, which target the uniquely elevated glucose metabolism of cancer cells. Butyrate is a critical product of beneficial microbes in the colon, which exerts extraordinary anti-cancer activities. In particular, butyrate shows biased inhibitory effects on the cell growth of cancerous colonocytes, whereas it is the major energy source for normal colonocytes. Besides its roles as the histone deacetylases (HDACs) inhibitor and the ligand for G-protein coupled receptor (GPR) 109a, the influence of butyrate on the glucose metabolism of cancerous colonocytes and the underlying molecular mechanism are not fully understood. Here, we show that butyrate markedly inhibited glucose transport and glycolysis of colorectal cancer cells, through reducing the abundance of membrane GLUT1 and cytoplasmic G6PD, which was regulated by the GPR109a-AKT signaling pathway. Moreover, butyrate significantly promoted the chemotherapeutical efficacy of 5-fluorouracil (5-FU) on cancerous colonocytes, with exacerbated impairment of DNA synthesis efficiency. Our findings provide useful information to better understand the molecular basis for the impact of butyrate on the glucose metabolism of colorectal cancer cells, which would promote the development of beneficial metabolites of gut microbiota as therapeutical or adjuvant anti-cancer drugs.

Synonymous Mutations of Porcine Igf1r Extracellular Domain Affect Differentiation and Mineralization in MC3T3-E1 Cells.

Owing to the wide application of miniature pigs in biomedicine, the formation mechanism of its short stature must be elucidated. The insulin-like growth factor 1 receptor (IGF-1R), which receives signals through the extracellular domain (ECD) binding with ligands, is crucial in regulating cell growth and bone matrix mineralization. In this study, two haplotypes of Igf1r with four synonymous mutations in the coding sequences of IGF-1R ECD between large pigs (LP) and Bama pigs (BM) were stably expressed in the Igf1r-knockout MC3T3-E1 cells and named as MC3T3-LP cells (LP group) and MC3T3-BM cells (BM group), respectively. IGF-1R expression was lower in the BM group than in the LP group both in terms of transcription and translation levels, and IGF-1R expression inhibited cell proliferation. In addition, IGF-1R expression in the BM group promoted early-stage differentiation but delayed late-stage differentiation, which not only suppressed the expression of bone-related factors but also reduced alkaline phosphatase activity and calcium deposition. Moreover, different haplotypes of Igf1r changed the stability and conformation of the protein, further affecting the binding with IGF-1. Our data indicated that the four synonymous mutations of IGF1R ECD encoded by affect gene transcription and translation, thereby further leading to differences in the downstream pathways and functional changes of osteoblasts.

A SNP in the 3'UTR of the porcine IGF-1 gene interacts with miR-new14 to affect IGF-1 expression, proliferation and apoptosis of PK-15 cells.

The kidney of miniature pigs has been considered the most likely potential kidney source for patients needing kidney transplantation. Insulin-like growth factor 1 (IGF-1) is involved in regulating the growth of miniature pigs and inducing growth of kidneys. There are evidences showing that the SNPs in the 3'UTR of a gene may affect the gene expression by affecting the binding to a miRNA target site. In this study, one SNP (rs34142920) was screened in the IGF-1 3'UTR between 2 different body types of porcine breeds, Bama Xiang (BX) pigs, a miniature pig breed, and Large White (LW) pigs by sequencing. The secondary structure of the IGF-1 3'UTR mRNA containing the SNP in BX pigs is different from that of LW pigs. We then verified that there was a porcine miRNA (miR-new14) binding to this SNP in the 3'UTR of IGF-1 via cotransfecting the 3'UTR from the 2 breeds and miR-new14. We further found that the SNP downregulated mRNA and protein levels of IGF-1 by affecting the binding of miR-new14. To understand the function of miR-new14 in porcine kidney (PK-15) cells and its mechanism, cell proliferation and cell apoptosis assays were employed and results showed that proliferation viability of PK-15 cells was weakened and the apoptotic percentage of PK-15 cells was higher in the miR-new14 group. Porcine miRNA reduced the mRNA expression of AKT/ERK and protein levels of p-AKT/p-ERK. These results suggested that the expression of IGF-1 is influenced by this SNP and miR-new14 and that miR-new14 may suppress cell proliferation and promote cell apoptosis in PK-15 cells through regulating AKT and ERK signaling pathways, in which IGF-1 is involved.

Porcine IGF-1R synonymous mutations in the intracellular domain affect cell proliferation and alter kinase activity.

Miniature pigs are regarded as ideal organ donors for xenotransplantation into humans. Elucidating the formation mechanism of miniature pigs is important. The insulin-like growth factor 1 receptor (IGF-1R) is crucial in the regulation of cell proliferation and organismal growth. According to our previous research, the IGF-1R expression levels between large and miniature pigs showed different profiles in liver and muscle tissues. Here, five synonymous mutations of IGF-1R in the coding sequence (CDS) of intracellular domain (ICD) between large and miniature pigs were analysed by constructing expression vectors of two haplotypes and named pcDNA3.1-LP (with the CDS of IGF-1R ICD of Large White pigs, LP group) and pcDNA3.1-BM (with the CDS of IGF-1R ICD of Bama Xiang pigs, BM group). The IGF-1R of the BM group was expressed lower than that of the LP group in transcription, translation and autophosphorylation levels. The IGF-1R of the BM group also down-regulated the protein levels of p-AKT/p-ERK than that of the LP group. PK-15 and C2C12 cell proliferation were detected to further understand the function of the haplotype. Results showed that the proliferation viability of PK-15 and C2C12 cells weakened in the BM group. Moreover, the mRNA and protein stabilities of the BM group were higher than those of the LP group. Our data indicated that two haplotypes of IGF-1R CDS in ICD between large and miniature pigs altered IGF-1R expression and down-regulated AKT and ERK signalling pathways at translation levels, resulting in an inhibitory effect on PK-15 and C2C12 cell proliferation.

miR-140 inhibits porcine fetal fibroblasts proliferation by directly targeting type 1 insulin-like growth factor receptor and indirectly inhibiting type 1 insulin-like growth factor receptor expression via SRY-box 4.

OBJECTIVE: This study aimed to elucidate the effect of miR-140 on the proliferation of porcine fetal fibroblasts (PFFs) and identify the target genes of miR-140 in PFFs. METHODS: In this study, bioinformatics software was used to predict and verify target genes of miR-140. Quantitative polymerase chain reaction and western blot were used to detect the relationship between miR-140 and its target genes in PFFs. Dual luciferase reporter gene assays were performed to assess the interactions among miR-140, type 1 insulinlike growth factor receptor (IGF1R), and SRY-box 4 (SOX4). The effect of miR-140 on the proliferation of PFFs was measured by CCK-8 when PFFs were transfected with a miR-140 mimic or inhibitor. The transcription factor SOX4 binding to promoter of IGF1R was detected by chromatin immunoprecipitation assay (ChIP). RESULTS: miR-140 directly targeted IGF1R and inhibited proliferation of PFFs. Meanwhile, miR-140 targeted transcription factor SOX4 that binds to promoter of porcine IGF1R to indirectly inhibit the expression of IGF1R. In addition, miR-140 inhibitor promoted PFFs proliferation, which is abrogated by SOX4 or IGF1R knockdown. CONCLUSION: miR-140 inhibited PFFs proliferation by directly targeting IGF1R and indirectly inhibiting IGF1R expression via SOX4, which play an important role in the development of porcine fetal.

MicroRNA 322 Aggravates Dexamethasone-Induced Muscle Atrophy by Targeting IGF1R and INSR.

Dexamethasone (Dex) has been widely used as a potent anti-inflammatory, antishock, and immunosuppressive agent. However, high dose or long-term use of Dex is accompanied by side effects including skeletal muscle atrophy, whose underlying mechanisms remain incompletely understood. A number of microRNAs (miRNAs) have been shown to play key roles in skeletal muscle atrophy. Previous studies showed significantly increased miR-322 expression in Dex-treated C2C12 myotubes. In our study, the glucocorticoid receptor (GR) was required for Dex to increase miR-322 expression in C2C12 myotubes. miR-322 mimic or miR-322 inhibitor was used for regulating the expression of miR-322. Insulin-like growth factor 1 receptor (IGF1R) and insulin receptor (INSR) were identified as target genes of miR-322 using luciferase reporter assays and played key roles in Dex-induced muscle atrophy. miR-322 overexpression promoted atrophy in Dex-treated C2C12 myotubes and the gastrocnemius muscles of mice. Conversely, miR-322 inhibition showed the opposite effects. These data suggested that miR-322 contributes to Dex-induced muscle atrophy via targeting of IGF1R and INSR. Furthermore, miR-322 might be a potential target to counter Dex-induced muscle atrophy. miR-322 inhibition might also represent a therapeutic approach for Dex-induced muscle atrophy.

Association of SNPs in GnRH gene with sperm quality traits of Chinese water buffalo.

Hypothalamic gonadotropin-releasing hormone (GnRH) controls the activity of hypothalamic-pituitary-gonadal axis and plays a key role in the reproductive performance of animals. In this study, five single nucleotide polymorphisms (SNPs), namely g.991T > C, g.1041T > C g.3424T > C, g.3462C > A and g.3463Inde A, were detected in the GnRH gene of 162 water buffaloes by Sanger sequencing. Each SNP was associated with more than two sperm quality traits of ejaculate volume, sperm concentration, post-thaw sperm motility and sperm abnormality. g.3424T > C and g.3462C > A were related to these four traits and had a remarkable effect on ejaculate volume. The three other SNPs were related to sperm concentration, post-thaw sperm motility and sperm abnormality. Moreover, six haplotypes (H1: TCCAI, H2: CTTC-, H3: TCCCI, H4: CTTA-, H5: CCTA- and H6: CTCC-) composed of five SNPs comprising seven different combined genotypes were generated by linkage disequilibrium analysis. Statistics followed by one-way ANOVA indicated that water buffaloes with the haplotype combination H1H1 had the highest genotypic frequency, and those with the H4H4 haplotype combination had the highest ejaculate volume. The sperm concentration of those with haplotype combination H1H5 was higher than that of the other genotypes. In summary, our study showed a remarkable association between the SNPs of GnRH and sperm quality traits of Chinese water buffalo.

Interaction between CA repeat microsatellites and HIF1α regulated the transcriptional activity of porcine IGF1 promoter.

Insulin-like growth factor 1 (IGF1) is pivotal in the regulation of animal growth. Highly polymorphic CA repeat microsatellites have been identified in the IGF1 promoter region of different breeds of pigs. Previous studies showed that CA repeat microsatellites are associated with circulating IGF1 level. However, the mechanisms by which CA repeat microsatellites regulate IGF1 expression remain unclear. This study aimed to detect the association of CA repeat microsatellites with the transcriptional regulation of porcine IGF1 and the possible mechanisms. Results revealed that the number of CA repeats in porcine IGF1 promoter was 14-18, and a promoter with 14 or 15 CA repeats had a higher transcriptional activity (P < 0.01). Transcription factor hypoxia-inducible factor 1 subunit alpha (HIF1α) was confirmed to bind to the binding site upstream of CA repeat microsatellites. The microsatellites with 14 or 15 CA repeats were more sensitive to changes in the HIF1α expression level (P < 0.01). These results suggested that CA repeat microsatellites and HIF1α affected the transcriptional activity of each other in the regulation of IGF1 expression, thereby implying an interaction between them. Overall, this study provided novel evidence for elucidating the effects of CA repeat microsatellites on the transcriptional regulation of porcine IGF1.

Physical Mapping of Peroxidase Genes and Development of Functional Markers for TaPod-D1 on Bread Wheat Chromosome 7D.

Peroxidase (POD) activity in wheat (Triticum aestivum L.) grain influences natural carotenoid pigment content and is associated with the color of flour, and processing and product quality. Here, we report the molecular characterization and physical mapping of POD genes in bread wheat. The complete genomic DNA (gDNA) sequence of two POD genes (TaPod-A2 and TaPod-D1), and the partial gDNA sequence of two additional POD genes (TaPod-A3 and TaPod-B1) from wheat were characterized using in silico cloning and validated through laboratory experiments. Using a set of 21 nullisomic-tetrasomic (NT) lines, six group-7 ditelosomic (Dt) lines, and 38 group-7 deletion (Del) lines of Chinese Spring (CS), TaPod-A2 and TaPod-D1 were found to be physically located on 0.73-0.83 and on the most distal 0.39 fraction arm length (FL) of 7AS and 7DS in cv. CS, respectively; whereas, TaPod-A3 and TaPod-B1 were assigned to the 0.40-0.49 and 0.40-0.48 FL of 7AL and 7BL, respectively. Based on single nucleotide polymorphisms (SNPs) of two alleles at the TaPod-D1 locus, two functional markers POD-7D1 and POD-7D6 were developed, amplifying 540- and 640-bp, fragments in varieties with higher and lower POD activities, respectively. A total of 224 wheat varieties were analyzed and showed a significant association between the polymorphic fragments and POD activity using POD-7D1 and POD-7D6 markers. The analysis of variance (ANOVA) indicated the average POD activities of 115 varieties with TaPod-D1a were significantly lower than 109 varieties with TaPod-D1b (P < 0.01). This study provides useful information of the POD genes in bread wheat, insight into wheat genome synteny and structure, gene-specific markers, and contributes a valuable resource for quality improvement in wheat breeding programs.

A miR-511-binding site SNP in the 3'UTR of IGF-1 gene is associated with proliferation and apoptosis of PK-15 cells.

Insulin-like growth factor-1 (IGF-1) is a functional candidate gene for pig growth and development due to its crucial role in the growth axis of growth hormone-IGF-1. Considering that the 3' untranslated region (3'UTR) of gene may affect its expression, we analyzed the effect of a single-nucleotide polymorphism (SNP) (rs34142920, c.674C > T) on gene expression, cell proliferation, and apoptosis and the possible related molecular mechanisms in PK-15 cells. The SNP was found in the 3'UTR of IGF-1 in Bama Xiang pig in previous investigations. Results showed that the SNP was located at the target site binding to microRNA (miR-511). The 3'UTR of IGF-1 gene with C allele significantly downregulated the expression of IGF-1 gene compared with that of the gene with T allele by luciferase assay. miR-511 was transfected into porcine kidney cell line (PK-15 cells) to reveal its effects on cells and whether or not it targets IGF-1. The expression levels of IGF-1 at mRNA and protein levels were remarkably downregulated. miR-511 significantly inhibited cell proliferation and promoted cell apoptosis by downregulating the phosphorylation level of AKT and ERK1/2. This finding confirmed that miR-511 inhibits proliferation and promotes apoptosis by downregulating the IGF-1 in PK-15 cells.

GWAS Analysis and QTL Identification of Fiber Quality Traits and Yield Components in Upland Cotton Using Enriched High-Density SNP Markers.

It is of great importance to identify quantitative trait loci (QTL) controlling fiber quality traits and yield components for future marker-assisted selection (MAS) and candidate gene function identifications. In this study, two kinds of traits in 231 F6:8 recombinant inbred lines (RILs), derived from an intraspecific cross between Xinluzao24, a cultivar with elite fiber quality, and Lumianyan28, a cultivar with wide adaptability and high yield potential, were measured in nine environments. This RIL population was genotyped by 122 SSR and 4729 SNP markers, which were also used to construct the genetic map. The map covered 2477.99 cM of hirsutum genome, with an average marker interval of 0.51 cM between adjacent markers. As a result, a total of 134 QTLs for fiber quality traits and 122 QTLs for yield components were detected, with 2.18-24.45 and 1.68-28.27% proportions of the phenotypic variance explained by each QTL, respectively. Among these QTLs, 57 were detected in at least two environments, named stable QTLs. A total of 209 and 139 quantitative trait nucleotides (QTNs) were associated with fiber quality traits and yield components by four multilocus genome-wide association studies methods, respectively. Among these QTNs, 74 were detected by at least two algorithms or in two environments. The candidate genes harbored by 57 stable QTLs were compared with the ones associated with QTN, and 35 common candidate genes were found. Among these common candidate genes, four were possibly "pleiotropic." This study provided important information for MAS and candidate gene functional studies.

Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers.

KEY MESSAGE: We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay. Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai × Shi 4185 (D × S), Gaocheng 8901 × Zhoumai 16 (G × Z) and Linmai 2 × Zhong 892 (L × Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5-32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

A high-density genetic map of extra-long staple cotton (Gossypium barbadense) constructed using genotyping-by-sequencing based single nucleotide polymorphic markers and identification of fiber traits-related QTL in a recombinant inbred line population.

BACKGROUND: Gossypium barbadense (Sea Island, Egyptian or Pima cotton) cotton has high fiber quality, however, few studies have investigated the genetic basis of its traits using molecular markers. Genome complexity reduction approaches such as genotyping-by-sequencing have been utilized to develop abundant markers for the construction of high-density genetic maps to locate quantitative trait loci (QTLs). RESULTS: The Chinese G. barbadense cultivar 5917 and American Pima S-7 were used to develop a recombinant inbred line (RIL) population with 143 lines. The 143 RILs together with their parents were tested in three replicated field tests for lint yield traits (boll weight and lint percentage) and fiber quality traits (fiber length, fiber elongation, fiber strength, fiber uniformity and micronaire) and then genotyped using GBS to develop single-nucleotide polymorphism (SNP) markers. A high-density genetic map with 26 linkage groups (LGs) was constructed using 3557 GBS SNPs spanning a total genetic distance of 3076.23 cM at an average density of 1.09 cM between adjacent markers. A total of 42 QTLs were identified, including 24 QTLs on 12 LGs for fiber quality and 18 QTLs on 7 LGs for lint yield traits, with LG1 (9 QTLs), LG10 (7 QTLs) and LG14 (6 QTLs) carrying more QTLs. Common QTLs for the same traits and overlapping QTLs for different traits were detected. Each individual QTLs explained 0.97 to 20.7% of the phenotypic variation. CONCLUSIONS: This study represents one of the first genetic mapping studies on the fiber quality and lint yield traits in a RIL population of G. barbadense using GBS-SNPs. The results provide important information for the subsequent fine mapping of QTLs and the prediction of candidate genes towards map-based cloning and marker-assisted selection in cotton.

Porcine IGF1 synonymous mutation alter gene expression and protein binding affinity with IGF1R.

CONTEXT: Insulin like growth factor 1 (IGF1) is privotal in the regulation of animal growth and is a single-chain globular protein composed of B, C, A, and D regions, of which the C region is involved in maintaining high affinity binding to the IGF1 receptor (IGF1R). PURPOSE: In this study, significant expression differences between large pigs and miniature pigs were detected and only one synonymous SNP (c.258G>A) in the C region of the coding sequence of IGF1 gene was screened. The aim of this manuscript was to clear the function of the SNP and clarify the mechanism of its influnce. METHODS: The expression vectors contained A allele and G allele were constructed, and the expression assays of the two groups were determined by qRT-PCR and western blotting, then the stability assays of the mRNA and protein were carried out under the inhibitation of actinomycin D and cycloheximide, respectively. At last, the binding affinity of IGF1-G and IGF1-A with IGF1R were indicated by co-immunoprecipitation and double immunofluorescence labeling methods, the conformation difference was detected by differential immunodetection. RESULTS: The IGF1-G expressed higher than IGF1-A in both transcription and translation levels, and the mRNA and protein stabilities of IGF1-G were lower than IGF1-A (P < 0.05). Furthermore, the relative binding affinity of GG-genotype IGF1 with IGF1R was significantly higher than that of the AA-genotype IGF1 (P < 0.05), and there was a difference in the conformation of the IGF1 with two genotypes. CONCLUSION: Our findings indicated the synonymous mutation altered the IGF1 gene expression and confirmed the synonymous mutation affected the IGF1 folding and the interactions with the IGF1R preliminarily.

Genome-wide identification and analysis of the MADS-box gene family in bread wheat (Triticum aestivum L.).

The MADS-box genes encode transcription factors with key roles in plant growth and development. A comprehensive analysis of the MADS-box gene family in bread wheat (Triticum aestivum) has not yet been conducted, and our understanding of their roles in stress is rather limited. Here, we report the identification and characterization of the MADS-box gene family in wheat. A total of 180 MADS-box genes classified as 32 Mα, 5 Mγ, 5 Mδ, and 138 MIKC types were identified. Evolutionary analysis of the orthologs among T. urartu, Aegilops tauschii and wheat as well as homeologous sequences analysis among the three sub-genomes in wheat revealed that gene loss and chromosomal rearrangements occurred during and/or after the origin of bread wheat. Forty wheat MADS-box genes that were expressed throughout the investigated tissues and development stages were identified. The genes that were regulated in response to both abiotic stresses (i.e., phosphorus deficiency, drought, heat, and combined drought and heat) and biotic stresses (i.e., Fusarium graminearum, Septoria tritici, stripe rust and powdery mildew) were detected as well. A few notable MADS-box genes were specifically expressed in a single tissue and those showed relatively higher expression differences between the stress and control treatment. The expression patterns of considerable MADS-box genes differed from those of their orthologs in Brachypodium, rice, and Arabidopsis. Collectively, the present study provides new insights into the possible roles of MADS-box genes in response to stresses and will be valuable for further functional studies of important candidate MADS-box genes.

Genome-Wide Association of Stem Water Soluble Carbohydrates in Bread Wheat.

Water soluble carbohydrates (WSC) in stems play an important role in buffering grain yield in wheat against biotic and abiotic stresses; however, knowledge of genes controlling WSC is very limited. We conducted a genome-wide association study (GWAS) using a high-density 90K SNP array to better understand the genetic basis underlying WSC, and to explore marker-based breeding approaches. WSC was evaluated in an association panel comprising 166 Chinese bread wheat cultivars planted in four environments. Fifty two marker-trait associations (MTAs) distributed across 23 loci were identified for phenotypic best linear unbiased estimates (BLUEs), and 11 MTAs were identified in two or more environments. Liner regression showed a clear dependence of WSC BLUE scores on numbers of favorable (increasing WSC content) and unfavorable alleles (decreasing WSC), indicating that genotypes with higher numbers of favorable or lower numbers of unfavorable alleles had higher WSC content. In silico analysis of flanking sequences of trait-associated SNPs revealed eight candidate genes related to WSC content grouped into two categories based on the type of encoding proteins, namely, defense response proteins and proteins triggered by environmental stresses. The identified SNPs and candidate genes related to WSC provide opportunities for breeding higher WSC wheat cultivars.