Fine Mapping of A QTL Locus (QNFSP07-1) And Analysis of Candidate Genes For Four-Seeded Pods In Soybean

The number of four-seeded pods is a quantitative trait in soybean [Glycine max (L.) Merr.] and is closely related to yield in terms of breeding. In this study, individuals with high ratio of four-seed pods which from chromosome segment substitution lines (CSSLs) that can be stably inherited were selected as the parent, and Suinong 14 (SN14) was used as recurrent parent to construct secondary mapping population via marker-assisted selection. The initial QTL mapping interval was 0.67 Mb and was located on Gm07. Based on the initial QTL mapping results, individuals that were heterozygous at the interval (36116118-37399738 bp) were screened, and the heterozygous individuals were subjected to inbreeding to obtain 13 F3 populations, with a target interval of 321 kb. Gene annotation was performed on the finely mapped interval, and 27 genes were obtained. Glyma.07G200900, Glyma.07G201200 were identified as candidate genes. qRT-PCR was used to measure the expression of the candidate genes at different developmental stages of soybean. The expression levels of the 2 candidate genes in terms of cell division (axillary buds, COTs, EMs) were higher than those in terms of cell expansion (MM, LM), and these genes play a positive regulatory role in the formation of four-seeded pods. Haplotype analysis shows that Glyma.07G201200 has two excellent haplotypes. Those results provide the information for gene map-based cloning and molecular marker assisted breeding of the number of four-seeded pod in soybean.

Fusion gene map of acute leukemia revealed by transcriptome sequencing of a consecutive cohort of 1000 cases in a single center

Fusion genes (FGs) are important genetic abnormalities in acute leukemias, but their variety and occurrence in acute leukemias remain to be systematically described. Whole transcriptome sequencing (WTS) provides a powerful tool for analyzing FGs. Here we report the FG map revealed by WTS in a consecutive cohort of 1000 acute leukemia cases in a single center, including 539 acute myeloid leukemia (AML), 437 acute lymphoblastic leukemia (ALL), and 24 mixed-phenotype acute leukemia (MPAL) patients. Bioinformatic analysis identified 792 high-confidence in-frame fusion events (296 distinct fusions) which were classified into four tiers. Tier A (pathogenic), B (likely pathogenic), and C (uncertain significance) FGs were identified in 61.8% cases of the total cohort (59.7% in AML, 64.5% in ALL, and 63.6% in MPAL). FGs involving protein kinase, transcription factor, and epigenetic genes were detected in 10.7%, 48.5%, and 15.1% cases, respectively. A considerable amount of novel FGs (82 in AML, 88 in B-ALL, 13 in T-ALL, and 9 in MPAL) was identified. This comprehensively described real map of FGs in acute leukemia revealed multiple FGs with clinical relevance that have not been previously recognized. WTS is a valuable tool and should be widely used in the routine diagnostic workup of acute leukemia.

Design and implementation of cancer patient survival prediction model based on ensemble learning method

To study the impact of genomics on cancer diseases, bioinformatics and integrated learning methods are used to conduct survival analysis on colon cancer and rectal cancer data in the cancer gene map database. Firstly, according to the significant expression and stability test, the long-chain non-coding RNA in the transcriptome that has a significant impact on clinical prognosis survival analysis was initially screened. Then use a random forest ensemble learning algorithm to train it to get a preliminary model. Finally, based on the optimized random survival forest model, the Cox regression model was once again integrated, and the risk values of the two were integrated. The RCCT (Random-Cox Combined to Survival) method was proposed to provide clinical decision-makers certain reference values.

Genome Survey Sequencing of Nomocharis forrestii, Assembly of Its Complete Chloroplast Genome and Analysis of Simple Sequence Repeat (SSR) Markers

Background: Nomocharis is a genus that is closely related to Lilium in the Liliaceae family. It’s useful to study the influence of the uplift of the Qinghai-Tibet Plateau on plants and their biological diversity. Nomocharis is a genus of such plants, and research on this genus will be especially informative, considering the genetic diversity of flowers. However, the genetic information of Nomocharis has not been fully elucidated. Results: To obtain a complete Nomocharis reference genome, the paper first performed a general survey. Next-generation sequencing (NGS) was utilized to perform de novo sequencing of the entire Nomocharis forrestii genome. In this study, the sequencing process yielded approximately 137.4 Gb of high-quality data, the total sequencing depth was approximately 63X, and the Q30 ratio was 91.95%; the estimated genome size was approximately 2.17 Gb; the repetitive sequence content was approximately 84.7%, the heterozygosity rate was 3.99%, and the estimated GC content of the genome was 43%. Furthermore, an annotated circular chloroplast gene map was generated, and a preliminary evolutionary analysis was performed. In addition, a total of 78,045 high-quality SSR markers were developed. Conclusion: Nomocharis forrestii has a 2.17 Gb heterozygous genome, its SSR markers are predominantly dinucleotides, and its chloroplast genome shows that Nomocharis forrestii and Lilium bakerianum have the highest homology followed by Lilium distichum. To the best of our knowledge, this report describes the first de novo whole-genome sequencing and assembly process to be performed for Nomocharis. The results of this study may provide new resources for the future genetic analysis and molecular breeding of Nomocharis.

Identification of differentially expressed circular RNAs in human nasopharyngeal carcinoma

BACKGROUND: Circular RNAs (circRNAs) are endogenous RNAs that have a covalent closed cycle configuration. circRNAs have been found to be differentially expressed in many human cancers. Therefore, circRNAs may be ideal biomarkers for the diagnosis and treatment of cancer. However, we know very little about the function of circRNAs in nasopharyngeal carcinoma (NPC). The purpose of this study was to evaluate the circRNA expression profiles in NPC. METHODS: We utilized high-throughput RNA sequencing (RNA-Seq) to evaluate the circRNA expression profile in NPC A total of 13,561 unique circRNA candidates were detected. Selection of aberrantly expressed circRNAs was carried out using a q-value of < 0.001 with a fold change of > 2.0 or < 0.5. We carried out Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses to identify the biological functions of differentially expressed circRNAs. Moreover, bioinformatics analyses were implemented to predict the effects between circRNAs and cancer-related microRNAs (miRNAs), and we used Cytoscape to build a cancer-related circRNA-miRNA target gene map. Finally, to verify dysregulated circRNAs, quantitative real-time PCR was utilized. RESULTS: In NPC tissues, we found that 73 circRNAs were downregulated and 59 were upregulated. The top 12 candidate circRNAs were selected from several vital NPC pathways such as the human papillomavirus and Epstein-Barr virus infection signaling pathways (hsa05165 and hsa05169, respectively), Hepatitis B (hsa05161), and the Ras signaling pathway (hsa04014). A network map of circRNA-miRNA interactions of 12 differentially expressed circRNAs was built. Hsa_circ_0007637 expression distinguished NPC tissues from paired healthy tissues and NPC cell lines (HNE1 6-10B, 5-8F, CNE-2, and so on) from a normal epithelial (NP460) cell line. CONCLUSIONS: In this study, we investigated the profiles of differentially expressed circRNAs in NPC, and our results show that hsa_circ_0007637 may be a biomarker for NPC and play a role in its development. This observation-based research identified dysregulated circRNAs in NPC, which may assist in the development of biomarkers for this disease. Further studies on the mechanisms and functions of these circRNAs may promote our understanding of NPC tumorigenesis.

Fetal cystic hygroma associated with terminal 2p25.1 duplication and terminal 3p25.3 deletion: Cytogenetic, fluorescent in situ hybridization and microarray familial characterization of two different chromosomal structural rearrangements

We report a prenatally diagnosed case of partial trisomy 2p and partial monosomy 3p, resulting from unbalanced translocation (2;3)(p25.1;p25.3) of paternal origin. Parents were non consanguineous Caucasians, with familial history of recurrent miscarriages on the father’s side. Detailed sonographic examination of the fetus showed a septated cystic hygroma measuring 6 mm at 13 weeks’ gestation. Karyotyping and fluorescent in situ hybridization (FISH) analysis of cultured amniotic fluid cells revealed an unbalanced translocation der(3)t(2;3)(p25.1; p25.3) and apparently balanced inv(3)(p13p25.3) in a fetus. Parental cytogenetic evaluation using karyotyping and FISH analysis showed the presence of both a balanced translocation and a paracentric inversion in father t(2;3) (p25.1;p25.3) inv(3)(p13p25.3). Microarray analysis showed a 11.6 Mb deletion at 3p26.3-p25.3 and duplication of 10.5 Mb at the 2p25.3-p25 region. The duplicated region at 2p25.1p25.3 contains 45 different genes, where 12 are reported as OMIM morbid genes with different phenotypical implications. The deleted region at 3p26.3-p25.3 contains 65 genes, out of which 27 are OMIM genes. Three of these (CNTN4, SETD5 and VHL) were curated by Clingene Dosage Gene Map and were given a high haplo-insufficiency score. Genes affected by the unbalanced translocation could have contributed to some specific phenotypic changes of the fetus in late pregnancy. The application of different cytogenetic methods was essential in our case, allowing the detection of different types of structural chromosomal aberrations and more thorough genetic counseling for future pregnancies.

Optimization of Tumor Gene Mapping Based on Visual Communication Design

In view of the high dimensionality of data needed to be processed by traditional tumor gene map, and the problem of redundant genes still exists, an optimization method of tumor gene map drawing based on visual communication design is proposed. Using a variety of detection methods to detect tumor genes and their products, according to the visual communication design and deep learning methods, select the appropriate tumor characteristic genes, analyze their applicability, in the low dimensional feature space representation samples, through the data set sample learning model, effectively express the level of gene difference, select the appropriate tumor characteristic genes, and achieve the optimization of tumor gene mapping. It also designs the control experiment, compares the optimized results with the traditional results, which confirm that the optimized gene map can greatly reduce the computational complexity.