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Abstract The continuous generation of multi-omics and phenotype data is propelling advancements in precision oncology. UCSCXenaShiny was developed as an interactive tool for exploring thousands of cancer datasets available on UCSC Xena. However, its capacity for comprehensive and personalized pan-cancer data analysis is being challenged by the growing demands. Here, we introduce UCSCXenaShiny v2, a milestone update through a variety of improvements. Firstly, by integrating multidimensional data and implementing adaptable sample settings, we create a suite of robust TPC (TCGA, PCAWG, CCLE) analysis pipelines. These pipelines empower users to conduct in-depth analyses of correlation, comparison, and survival in three modes: Individual, Pan-cancer and Batch screen. Additionally, the tool includes download interfaces that enable users to access diverse data and outcomes, several features also facilitate the joint analysis of drug sensitivity and multi-omics of cancer cell lines. UCSCXenaShiny v2 is an open-source R package and a web application, freely accessible at https://github.com/openbiox/UCSCXenaShiny .

Unmanned Aerial Vehicles (UAVs) have garnered widespread attention in reconnaissance and search operations due to their low cost and high flexibility. However, when multiple UAVs (multi-UAV) collaborate on these tasks, a limited communication range can restrict their efficiency. This paper investigates the problem of multi-UAV collaborative reconnaissance and search for static targets with a limited communication range (MCRS-LCR). To address communication limitations, we designed a communication and information fusion model based on belief maps and modeled MCRS-LCR as a multi-objective optimization problem. We further reformulated this problem as a decentralized partially observable Markov decision process (Dec-POMDP). We introduced episodic memory into the reinforcement learning framework, proposing the CNN-Semantic Episodic Memory Utilization (CNN-SEMU) algorithm. Specifically, CNN-SEMU uses an encoder–decoder structure with a CNN to learn state embedding patterns influenced by the highest returns. It extracts semantic features from the high-dimensional map state space to construct a smoother memory embedding space, ultimately enhancing reinforcement learning performance by recalling the highest returns of historical states. Extensive simulation experiments demonstrate that in reconnaissance and search tasks of various scales, CNN-SEMU surpasses state-of-the-art multi-agent reinforcement learning methods in episodic rewards, search efficiency, and collision frequency.

Parkinson's disease (PD) is a common neurological disorder of the brain. In recent years, there is increasing evidence that intestinal flora dysbiosis is closely related to the occurrence and development of PD. This suggests that intestinal microorganisms may be a new strategy for the treatment of PD. Probiotics are a group of active microorganisms that can colonize the host gut and play a beneficial role in the health of the body, and are of great significance to maintaining the intestinal microecological balance. Studies have shown that probiotics can effectively prevent and improve PD through the gut-brain axis, and the potential mechanisms of action include regulating intestinal microecology, alleviating inflammatory response and oxidative stress damage, and promoting the expression of neurotrophic factors. This article reviews the changes of intestinal flora in PD, the mechanisms of intestinal flora in the pathogenesis of PD, and the improvement effect and mechanisms of probiotics on PD-related symptoms, in order to provide a theoretical basis for probiotics to prevent and alleviate PD.

ABSTRACT Polymyxins exhibit antibacterial activity against various gram-negative bacteria. However, the regulatory mechanisms of polymyxin synthesis remain unclear. Here, Abh, AbrB3, and Spo0A of Paenibacillus polymyxa SC2 were found to bind to P pmx via DNA pull-down and electromagnetic mobility shift assays. Oxford Cup and liquid chromatography-mass spectrometry assays showed that antibacterial activity and polymyxin production increased in the Δabh strain. Overexpression of abh and abrB3 significantly decreased the antibacterial activity and polymyxin production. The transcription of pmxA determined via quantitative reverse transcription-PCR supported these results. Moreover, the mutation and complementation of spo0A revealed that Spo0A was an activator of polymyxin synthesis. Spo0A could bind to the abh promoter to activate abh expression. Spo0A could bind to the abrB3 promoter to inhibit abrB3 transcription and mitigate the inhibitory effect of AbrB3 on abh transcription. IMPORTANCE Polymyxins are considered the last line of defense against multidrug-resistant bacteria. The regulatory mechanism of polymyxin synthesis is poorly studied in Paenibacillus polymyxa. In this study, we found that Abh and AbrB3 negatively regulated, whereas Spo0A positively regulated polymyxin synthesis in P. polymyxa SC2. In addition, a regulatory relationship between Abh, AbrB3, and Spo0A was revealed, which regulate polymyxin synthesis via multiple regulatory mechanisms in P. polymyxa.

Genomic selection (GS) is a powerful tool for improving genetic gain in maize breeding. However, its routine application in large-scale breeding pipelines is limited by the high cost of genotyping platforms. Although sequencing-based and array-based genotyping platforms have been used for GS, few studies have compared prediction performance among platforms. In this study, we evaluated the predictabilities of four agronomic traits in 305 maize hybrids derived from 149 parental lines subjected to genotyping by sequencing (GBS), a 40K SNP array, and target sequence capture (TSC) using eight GS models. The GBS marker dataset yielded the highest predictabilities for all traits, followed by TSC and SNP array datasets. We investigated the effect of marker density and statistical models on predictability among genotyping platforms and found that 1K SNPs were sufficient to achieve comparable predictabilities to 10K and all SNPs, and BayesB, GBLUP, and RKHS performed well, while XGBoost performed poorly in most cases. We also selected significant SNP subsets using genome-wide association study (GWAS) analyses in three panels to predict hybrid performance. GWAS facilitated selecting effective SNP subsets for GS and thus reduced genotyping cost, but depended heavily on the GWAS panel. We conclude that there is still room for optimization of the existing SNP array, and using genotyping by target sequencing (GBTS) techniques to integrate a few functional markers identified by GWAS into the 1K SNP array holds great promise of being an effective strategy for developing desirable GS breeding arrays.

Cotton fiber quality-related traits, such as fiber length, fiber strength, and fiber elongation, are affected by complex mechanisms controlled by multiple genes. Determining the QTN-by-QTN interactions (QQIs) associated with fiber quality-related traits is therefore essential for accelerating the genetic enhancement of cotton breeding. In this study, a natural population of 1,245 upland cotton varieties with 1,122,352 SNPs was used for detecting the main-effect QTNs and QQIs using the 3V multi-locus random-SNP-effect mixed linear model (3VmrMLM) method. A total of 171 significant main-effect QTNs and 42 QQIs were detected, of which 22 were both main-effect QTNs and QQIs. Of the detected 42 QQIs, a total of 13 significant loci and 5 candidate genes were reported in previous studies. Among the three interaction types, the AD interaction type has a preference for the trait of FE. Additionally, the QQIs have a substantial impact on the enhancement predictability for fiber quality-related traits. The study of QQIs is crucial for elucidating the genetic mechanism of cotton fiber quality and enhancing breeding efficiency.

Cervical cancer is the second most malignant tumor among women of childbearing age, almost all cervical cancers are associated with high-risk (HR) human papillomavirus (HPV) persistent infection. HPV persistent infection and cell immortalization does not always cause cancer, but they increase risk and can lead to tumor formation and carcinogenesis in cooperation with other tumorigenic factors, and HR-HPV E6 oncoprotein is the mainly tumorigenic factors.E6 binds to the highly conserved sequence “LXXLL” of E6AP to form a heterodimer, which recruits and induces the degradation of tumor suppressor protein p53, trigger the immortalized transformation of infected cells, and induce its carcinogenicity. Therefore, the small molecule compounds, who can compete the conservative and stable binding pocket of E6-E6AP, may inhibited the carcinogenicity risk of HR-HPV E6, and HPV-16 is one of the most important HR-HPV.In this study, DOCK6, AutoDock Vina, Visual screen and GROMACS V4.5.7 were used to screen the candidate compounds from Specs library, and based on the pharmacokinetic properties and toxicity prediction by ADMSlab and ProtoX-II analytical tools, 20 E6-E6AP binding inhibition small molecule compounds were selected out. They were verified by molecular interactions, cell proliferation inhibition, apoptosis induction and p53/p21 protein content/expression on SiHa (HPV-16 infected line). Ultimately, compound 4 among them with good tumor suppressive potential was picked out, has the potential of medicine to HR-HPV related diseases.

Highlights 1. Verifying an entire native IPyA pathway of IAA synthesis in P. polymyxa. 2. Introducing heterologous IAM and IPyA pathways of IAA synthesis to P. polymyxa. 3. Selecting and analyzing a novel strong promoter P 04420 to express IAA synthesis genes.

Abstract Background The Alphapapillomavirus 9 (α-9 HPV) is a member of the Alphapapillomavirus genus and Papillomaviridae family. These viruses are almost all carcinogenic HPV, which is closely related to 75% of invasive cervical cancer worldwide, and has a high prevalence in Sichuan. The carcinogenic function is mainly realized by its E6 oncoprotein. Methods Cell samples were collected by cervical scraped for HPV detecting and typing. HPV-16, HPV-31, HPV-33, HPV-52, HPV-58 5 α-9 genus HPV subtype positive samples were selected, their E6 gene was sequenced and analyzed. The positive selection sites of HPV E6 genes were estimated by PAML 4.8 server. The secondary and tertiary structure of E6 protein were predicted by PSIPred and Swiss-model. The T-cell antigen epitopes of E6 protein were predicted by IEDB. Results α-9 HPV has a high prevalence in Sichuan, China. From 2012 to 2017, 18,067 cell cervical samples were collected, and 3135 were detected with α-9 HPV infection. Among which, 250 cases HPV-16 E6, 96 cases HPV-31 E6, 216 cases HPV-33 E6, 288 cases HPV-52 E6 and 405 cases HPV-58 E6 were successfully amplified, 17, 6, 6, 13, and 4 non-synonymous nucleotide mutations were respectively detected in HPV-16, 31, 33, 52, and 58 E6, 7 positive selection sites of α-9 HPV E6 were selected out (D32E of HPV-16 E6, K35N, K93N and R145I of HPV-33 E6, K93R of HPV-52 E6, K93N and R145K of HPV-58 E6). The structure and antigen epitopes of E6 protein with amino acid substitution differ from those of wild-type E6 protein, especially for the mutation located in the E6 positive selection site. Conclusions HPV E6 nucleotide non-synonymous mutation in the positive selection site influence the protein structure and decrease the antigen epitopes affinity of the E6 protein overall, making it more difficult for the HPV-infected cells to be detected by the immune system, and enhancing the HPV adaptability to the environment. Mutations influence the validity of HPV clinical diagnostic probes, the polymorphism analysis of α-9 HPV E6 enrich the data of HR-risk HPV in Sichuan China, and the detection probes designed with the polymorphism data in mind can improve the efficiency of clinical detection; Mutations influence epitopes affinity, the association of E6 polymorphism and epitope affinity can improve the design of therapeutic vaccine with good immunity and high generality antigen epitope; The above study all provide a good theoretical basis for the prevention and treatment of HPV-related diseases.

The multiple-sugar metabolism regulator (MsmR), a transcription factor belonging to the AraC/XylS family, participates in polysaccharide metabolism and virulence. However, the transcriptional regulatory mechanisms of MsmR1 in Paenibacillus polymyxa remain unclear. In this study, knocking out msmR1 was found to reduce polymyxin synthesis by the SC2-M1 strain. Chromatin immunoprecipitation assay with sequencing (ChIP-seq) revealed that most enriched pathway was that of carbohydrate metabolism. Additionally, electromobility shift assays (EMSA) confirmed the direct interaction between MsmR1 and the promoter regions of oppC3, sucA, sdr3, pepF, yycN, PPSC2_23180, pppL, and ydfp. MsmR1 stimulates polymyxin biosynthesis by directly binding to the promoter regions of oppC3 and sdr3, while also directly regulating sucA and influencing the citrate cycle (TCA cycle). In addition, MsmR1 directly activates pepF and was beneficial for spore and biofilm formation. These results indicated that MsmR1 could regulate carbohydrate and amino acid metabolism, and indirectly affect biological processes such as polymyxin synthesis, biofilm formation, and motility. Moreover, MsmR1 could be autoregulated. Hence, this study expand the current knowledge of MsmR1 and will be beneficial for the application of P. polymyxa SC2 in the biological control against the certain pathogens in pepper.

Abstract Background Variations in human papillomavirus (HPV) E6 and E7 have been shown to be closely related to the persistence of the virus and the occurrence and development of cervical cancer. Long control region (LCR) of HPV has been shown multiple functions on regulating viral transcription. In recent years, there have been reports on E6/E7/LCR of HPV-16 and HPV-58, but there are few studies on HPV-52, especially for LCR. In this study, we focused on gene polymorphism of the HPV-52 E6/E7/LCR sequences, assessed the effects of variations on the immune recognition of viral E6 and E7 antigens, predicted the effect of LCR variations on transcription factor binding sites and provided more basic date for further study of E6/E7/LCR in Chengdu, China. Methods LCR/E6/E7 of the HPV-52 were amplified and sequenced to do polymorphic and phylogenetic analysis. Sequences were aligned with the reference sequence by MEGA 7.0 to identify SNP. A neighbor-joining phylogenetic tree was constructed by MEGA 7.0, followed by the secondary structure prediction of the related proteins using PSIPRED 4.0. The selection pressure of E6 and E7 coding regions were estimated by Bayes empirical Bayes analysis of PAML 4.9. The HLA class-I and II binding peptides were predicted by the Immune Epitope Database server. The B cell epitopes were predicted by ABCpred server. Transcription factor binding sites in LCR were predicted by JASPAR database. Results 50 SNP sites (6 in E6, 10 in E7, 34 in LCR) were found. From the most variable to the least variable, the nucleotide variations were LCR > E7 > E6. Two deletions were found between the nucleotide sites 7387–7391 (TTATG) and 7698–7700 (CTT) in all samples. A deletion was found between the nucleotide sites 7287–7288 (TG) in 97.56% (40/41) of the samples. The combinations of all the SNP sites and deletions resulted in 12 unique sequences. As shown in the neighbor-joining phylogenetic tree, except for one belonging to sub-lineage C2, others sequences clustered into sub-lineage B2. No positive selection was observed in E6 and E7. 8 non-synonymous amino acid substitutions (including E3Q and K93R in the E6, and T37I, S52D, Y59D, H61Y, D64N and L99R in the E7) were potential affecting multiple putative epitopes for both CD4+ and CD8+ T-cells and B-cells. A7168G was the most variable site (100%) and the binding sites for transcription factor VAX1 in LCR. In addition, the prediction results showed that LCR had the high probability binding sites for transcription factors SOX9, FOS, RAX, HOXA5, VAX1 and SRY. Conclusion This study provides basic data for understanding the relation among E6/E7/LCR mutations, lineages and carcinogenesis. Furthermore, it provides an insight into the intrinsic geographical relatedness and biological differences of the HPV-52 variants, and contributes to further research on the HPV-52 therapeutic vaccine development.

Abstract Background Human papillomavirus type 39 associated with genital intraepithelial neoplasia and invasive cancers, has a high prevalence in Southwest China. HPV E6, E7 are two main papillomavirus oncoproteins, closely relate to the function of HPV immortalization, cell transformation, and carcinogenesis. L1 is the major capsid protein, can reflect the replication status of the virus in cells and the progression of cervical lesions. The purpose of this study is to reveal the prevalence of HPV 39 and the genetic polymorphisms of HPV39 based on E6, E7 and L1 gene in southwest China. Methods Cell samples were collected by cervical scraped for HPV detecting and typing, and HPV39 positive samples were selected out. Important E6, E7 and L1 genes of HPV39 were sequenced and analyzed for the study of HPV39 genetic polymorphisms. Phylogenetic trees were constructed by Maximum-likelihood and Kimura 2-parameters methods in Molecular Evolutionary Genetics Analysis version 6.0. The selection pressures of E6, E7 and L1 genes were estimated by Datamonkey web server. The secondary and three-dimensional structure of HPV39 E6, E7 proteins were created by sopma server and SWISS-MODEL software. Results 344 HPV39 positive samples were selected from 5718 HPV positive cell samples. Among HPV39 E6-E7 sequences, 20 single nucleotide mutations were detected, including 10 non-synonymous and 10 synonymous mutations; 26 single nucleotide mutations were detected in HPV39 L1 sequences, including 7 non-synonymous and 19 synonymous mutations respectively. 11 novel variants of HPV39 E6-E7 (5 in E6 and 6 in E7) and 14 novel variants of HPV39 L1 were identified in this study. A-branch was the most frequent HPV39 lineage in southwest China during our investigation. Selective pressure analysis showed that codon sites 26, 87, 151 in E6 and 75, 180, 222, 272, 284, 346, 356 in L1 were positively selected sites, as well as codon sites 45, 138, 309, 381 were negative selection sites in L1 gene, E7 has neither positive selection sites nor negative selection sites. A certain degree of secondary and three-dimensional structure dislocation was existed due to the non-synonymous mutations. Conclusions Amino acid substitution affected the secondary and three-dimensional structure of HPV39, and resulting in the differences of carcinogenic potential and biological functions as well as the immune response due to the antigen epitopes difference, the antigen epitopes with stronger adaptability in Southwest will be screened out based on the above research results for the later vaccine development. And gene polymorphism of HPV39 in Southwest China may improve the effectiveness of clinical test and vaccine design, specifically for women in Southwest China.

ABSTRACT A novel plant growth-promoting rhizobacterium (PGPR), which was designated strain BY2G20, was isolated from saline-alkaline soil in Dongying, China. Strain BY2G20 can grow at a NaCl range from 0 to 7% and a pH range from 7 to 9 and can prevent the growth of the phytopathogen Ralstonia solanacearum. Based on its phenotypic and genomic characteristics and phylogenetic analysis, strain BY2G20 represents a novel species of the genus Metabacillus, for which the name Metabacillus dongyingensis sp. nov. is proposed. Comparative genomic analysis of strain BY2G20 with its closely related species exhibited a high level of evolutionary plasticity derived by horizontal gene transfer, which facilitated adaptative evolution. Different evolutionary constraints have operated on the diverse functions of BY2G20, with the gene adapted to saline-alkaline ecosystems experiencing functional constraints. We determined the genetic properties of saline-alkaline tolerance and plant growth promotion, such as cation-proton antiporters, cation transporters, osmoprotectant synthesis and transport, H+-transporting F1F0-ATPase, indole-3-acetic acid production, and secondary metabolite synthesis. We also evaluated the effects of strain BY2G20 on the growth of Zea mays L. (maize) under salt stress. The physiological parameters of maize such as plant height, stem diameter, dry biomass, and fresh biomass were significantly higher after inoculating strain BY2G20 under salt stress, indicating that inoculation with BY2G20 enhanced the growth of maize in saline areas. This study demonstrates that M. dongyingensis sp. nov. BY2G20 is a potential candidate for organic agriculture biofertilizers in saline-alkaline areas. IMPORTANCE Plant growth and yield are adversely affected by soil salinity. PGPRs can promote plant growth and enhance plant tolerance to salt stress. In this study, a saline-alkaline tolerant PGPR strain BY2G20 was isolated from the rhizosphere of Ulmus pumila in Dongying, China. Strain BY2G20 represents a novel species within the genus Metabacillus based on phenotypic, genomic, and phylogenetic analysis. Genomic components have undergone different functional constraints, and the disparity in the evolutionary rate may be associated with the adaptation to a specific niche. Genomic analysis revealed numerous adaptive features of strain BY2G20 to a saline-alkaline environment and rhizosphere, especially genes related to salt tolerance, pH adaptability, and plant growth promotion. Our work also exhibited that inoculation of strain BY2G20 enhanced the growth of maize under salt stress. This study demonstrates that PGPRs play an important role in stimulating salt tolerance in plants and can be used as biofertilizers to enhance the growth of crops in saline-alkaline areas.

Nitrogen is one of the most important nutrients for rice growth and development. Breeding of nitrogen deficiency tolerance (NDT) variety is considered to be the most economic measure to solve the constrain of low nitrogen stress on grain yield in rice. An interconnected breeding (IB) population of 497 lines developed using Huanghuazhan (HHZ) as the recurrent parent and eight elite lines as the donor parents were tested for five traits including grain yield, biomass, harvest index, thousand grain weight, and spikelet fertility under two nitrogen treatments in three growing seasons. Association analysis using 7,388 bins generated by sequencing identified a total of 14, 14, and 12 QTLs for the five traits under low nitrogen (LN), normal nitrogen (NN), and LN/NN conditions, respectively, across three seasons. Favorable alleles were dissected for the 40 QTLs at the 10 NDT regions, and OM1723 was considered as the most important parent with the highest frequency of favorable alleles contributing to NDT-related traits. Six superior lines all showed significantly higher GY in LN environments and similar GY under NN environments except for H10. Substitution mapping using near-isogenic introgression lines delimited the qTGW2-1, which was identified on chromosome 2 under LN, NN, and LN/NN conditions into two QTLs, which were located in the two regions of about 200 and 350 kb with different favorable alleles. The bins 16, 1301, 1465, 1486, 3464, and 6249 harbored the QTLs for NDT detected in this study, and the QTLs/genes previously identified for NDT or nitrogen use efficiency (NUE) could be used for enhancing NDT and NUE by marker-assisted selection (MAS).

Accurate phenotype prediction of quantitative traits is paramount to enhanced plant research and breeding. Here, we report the accurate prediction of cotton fiber length, a typical quantitative trait, using 474 cotton (Gossypium ssp.) fiber length (GFL) genes and nine prediction models. When the SNPs/InDels contained in 226 of the GFL genes or the expressions of all 474 GFL genes was used for fiber length prediction, a prediction accuracy of r = 0.83 was obtained, approaching the maximally possible prediction accuracy of a quantitative trait. This has improved by 116%, the prediction accuracies of the fiber length thus far achieved for genomic selection using genome-wide random DNA markers. Moreover, analysis of the GFL genes identified 125 of the GFL genes that are key to accurate prediction of fiber length, with which a prediction accuracy similar to that of all 474 GFL genes was obtained. The fiber lengths of the plants predicted with expressions of the 125 key GFL genes were significantly correlated with those predicted with the SNPs/InDels of the above 226 SNP/InDel-containing GFL genes (r = 0.892, P = 0.000). The prediction accuracies of fiber length using both genic datasets were highly consistent across environments or generations. Finally, we found that a training population consisting of 100–120 plants was sufficient to train a model for accurate prediction of a quantitative trait using the genes controlling the trait. Therefore, the genes controlling a quantitative trait are capable of accurately predicting its phenotype, thereby dramatically improving the ability, accuracy, and efficiency of phenotype prediction and promoting gene-based breeding in cotton and other species.

Improving the salt-tolerance of direct-seeding rice at the seed germination stage is a major goal of breeders. Efficiently identifying salt tolerance loci will help researchers develop effective rice breeding strategies. In this study, six multi-locus genome-wide association studies (GWAS) methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, and ISIS EM-BLASSO) were applied to identify quantitative trait nucleotides (QTNs) for the salt tolerance traits of 478 rice accessions with 162,529 SNPs at the seed germination stage. Among the 371 QTNs detected by the six methods, 56 were identified by at least three methods. Among these 56 QTNs, 12, 6, 7, 4, 13, 12, and 12 were found to be associated with SSI-GI, SSI-VI, SSI-MGT, SSI-IR-24h, SSI-IR-48h, SSI-GR-5d, and SSI-GR-10d, respectively. Additionally, 66 candidate genes were identified in the vicinity of the 56 QTNs, and two of these genes (LOC_Os01g45760 and LOC_Os10g04860) are involved in auxin biosynthesis according to the enriched GO terms and KEGG pathways. This information will be useful for identifying the genes responsible for rice salt tolerance. A comparison of the six methods revealed that ISIS EM-BLASSO identified the most co-detected QTNs and performed best, with the smallest residual errors and highest computing speed, followed by FASTmrMLM, pLARmEB, mrMLM, pKWmEB, and FASTmrEMMA. Although multi-locus GWAS methods are superior to single-locus GWAS methods, their utility for identifying QTNs may be enhanced by adding a bin analysis to the models or by developing a hybrid method that merges the results from different methods.

Drought and low nitrogen are the most common abiotic stresses limiting rice productivity in the rainfed rice areas of Asia and Africa. Development and adoption of green super rice (GSR) varieties with greatly improved drought tolerance (DT) and low nitrogen tolerance (LNT) are the most efficient way to resolve this problem. In this study, using three sets of trait-specific introgression lines (ILs) in a Xian (indica) variety Huanghuazhan (HHZ) background, we identified nine DT-QTL and seven LNT-QTL by a segregation distortion approach and a genome-wide association study, respectively. Based on performances of DT and LNT and genotypes at the detected QTL, two ILs M79 and M387 with DT and LNT were selected for cross-making to validate the identified QTL and to develop DT and LNT rice lines by pyramiding two DT-QTL (qDT3.9 and qDT6.3) and two LNT-QTL (qGY1 and qSF8). Using four pairs of kompetitive allele specific PCR (KASP) SNP markers, we selected 66 F2 individuals with different combinations of the target DT- and LNT-QTL favorable alleles and they showed expected improvement in DT and/or LNT, which were further validated by the significant improvement in DT and/or LNT of their F3 progeny testing. Based on evaluation of pyramiding lines in F3 lines under drought, low nitrogen (LN) and normal conditions, four promising pyramiding lines having different QTL favorable alleles were selected, which showed significantly improved tolerances to drought and/or LN than HHZ and their IL parents. Our results demonstrated that trait-specific ILs could effectively connect QTL mapping and QTL pyramiding breeding, and designed QTL pyramiding (DQP) using ILs could be more effective in molecular rice breeding for complex quantitative traits.

Drought is the most important factor limiting rice yield in most rainfed areas of Asia and Africa. Four large BC2F2 populations consisted of 3,200 individuals, which were derived from crosses between an elite Geng variety, Jigeng88, and four donors from three different countries, were screened and progeny tested under severe drought stress, resulting in the development of 72 introgression lines (ILs) with significantly improved yield compared to the recurrent parent Jigeng88. These DT ILs plus four random populations (without drought selection population) from the same crosses were evaluated in replicated trials under both drought stress and non-stress conditions in two environments, and characterized with simple sequence repeat (SSR) markers to understand how directional selection was operating on the genetic variation of DT of rice. Thirteen DT QTLs of large effect were identified based on the significant allelic and genotypic frequency shits in the DT ILs by using the joint segregation distortion method. The 13 QTLs were validated by the genotypic differences at individual QTL in the random populations. Putative genetic networks consisting of 30 loci in 29 functional genetic units underlying DT were detected by X2 tests and non-random associations between or among DT loci in DT ILs from the four populations. Most large-effect DT QTLs were previously reported and located in the upstream of the genetic networks as putative regulators, and were either mapped to important regulatory genes for DT or drought responsiveness reported previously. In our study, five promising ILs with significantly improved yield were selected under both drought and normal irrigated conditions. The QTLs and their genetic networks underlying DT detected provided useful genetic information for further improving DT and yield using designed QTL pyramiding.

Low temperature stress is one of the major abiotic stresses limiting the productivity of Geng (japonica) rice grown the temperate regions as well as in tropical high lands worldwide. To develop rice varieties with improved cold tolerance (CT) at the reproductive stage, 84 BC2 CT introgression lines (ILs) were developed from five populations through backcross breeding. These CT ILs plus 310 random ILs from the same BC populations were used for dissecting genetic networks underlying CT in rice by detecting QTLs and functional genetic units (FGUs) contributing to CT. Seventeen major QTLs for CT were identified using five selective introgression populations and the method of segregation distortion. Of them, three QTLs were confirmed using the random populations and seven others locate in the regions with previously reported CT QTLs/genes. Using multi-locus probability tests and linkage disequilibrium (LD) analyses, 46 functional genetic units (FGUs) (37 single loci and 9 association groups or AGs) distributed in 37 bins (~20%) across the rice genome for CT were detected. Together, each of the CT loci (bins) was detected in 1.7 populations, including 18 loci detected in two or more populations. Putative genetic networks (multi-locus structures) underlying CT were constructed based on strong non-random associations between or among donor alleles at the unlinked CT loci/FGUs identified in the CT ILs, suggesting the presence of strong epistasis among the detected CT loci. Our results demonstrated the power and usefulness of using selective introgression for simultaneous improvement and genetic dissection of complex traits such as CT in rice.