Genomic analysis of the domestication and post-Spanish conquest evolution of the llama and alpaca

Background Despite their regional economic importance and being increasingly reared globally, the origins and evolution of the llama and alpaca remain poorly understood. Here we report reference genomes for the llama, and for the guanaco and vicuña (their putative wild progenitors), compare these with the published alpaca genome, and resequence seven individuals of all four species to better understand domestication and introgression between the llama and alpaca. Results Phylogenomic analysis confirms that the llama was domesticated from the guanaco and the alpaca from the vicuña. Introgression was much higher in the alpaca genome (36%) than the llama (5%) and could be dated close to the time of the Spanish conquest, approximately 500 years ago. Introgression patterns are at their most variable on the X-chromosome of the alpaca, featuring 53 genes known to have deleterious X-linked phenotypes in humans. Strong genome-wide introgression signatures include olfactory receptor complexes into both species, hypertension resistance into alpaca, and fleece/fiber traits into llama. Genomic signatures of domestication in the llama include male reproductive traits, while in alpaca feature fleece characteristics, olfaction-related and hypoxia adaptation traits. Expression analysis of the introgressed region that is syntenic to human HSA4q21, a gene cluster previously associated with hypertension in humans under hypoxic conditions, shows a previously undocumented role for PRDM8 downregulation as a potential transcriptional regulation mechanism, analogous to that previously reported at high altitude for hypoxia-inducible factor 1α. Conclusions The unprecedented introgression signatures within both domestic camelid genomes may reflect post-conquest changes in agriculture and the breakdown of traditional management practices

Genomic Analyses Reveal Mutational Signatures and Frequently Altered Genes in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers worldwide and the fourth most lethal cancer in China. However, although genomic studies have identified some mutations associated with ESCC, we know little of the mutational processes responsible. To identify genome-wide mutational signatures, we performed either whole-genome sequencing (WGS) or whole-exome sequencing (WES) on 104 ESCC individuals and combined our data with those of 88 previously reported samples. An APOBEC-mediated mutational signature in 47% of 192 tumors suggests that APOBEC-catalyzed deamination provides a source of DNA damage in ESCC. Moreover, PIK3CA hotspot mutations (c.1624G>A [p.Glu542Lys] and c.1633G>A [p.Glu545Lys]) were enriched in APOBEC-signature tumors, and no smoking-associated signature was observed in ESCC. In the samples analyzed by WGS, we identified focal (<100 kb) amplifications of CBX4 and CBX8. In our combined cohort, we identified frequent inactivating mutations in AJUBA, ZNF750, and PTCH1 and the chromatin-remodeling genes CREBBP and BAP1, in addition to known mutations. Functional analyses suggest roles for several genes (CBX4, CBX8, AJUBA, and ZNF750) in ESCC. Notably, high activity of hedgehog signaling and the PI3K pathway in approximately 60% of 104 ESCC tumors indicates that therapies targeting these pathways might be particularly promising strategies for ESCC. Collectively, our data provide comprehensive insights into the mutational signatures of ESCC and identify markers for early diagnosis and potential therapeutic targets

3DMGNet: 3D Model Generation Network Based on Multi-Modal Data Constraints and Multi-Level Feature Fusion

Due to the limitation of less information in a single image, it is very difficult to generate a high-precision 3D model based on the image. There are some problems in the generation of 3D voxel models, e.g., the information loss at the upper level of a network. To solve these problems, we design a 3D model generation network based on multi-modal data constraints and multi-level feature fusion, named as 3DMGNet. Moreover, 3DMGNet is trained by self-supervised method to achieve 3D voxel model generation from an image. The image feature extraction network (2DNet) and 3D feature extraction network (3D auxiliary network) are used to extract the features of the image and 3D voxel model. Then, feature fusion is used to integrate the low-level features into the high-level features in the 3D auxiliary network. To extract more effective features, each layer of the feature map in feature extraction network is processed by an attention network. Finally, the extracted features generate 3D models by a 3D deconvolution network. The feature extraction of 3D model and the generation of voxelization play an auxiliary role in the training of the whole network for the 3D model generation based on an image. Additionally, a multi-view contour constraint method is proposed, to enhance the effect of the 3D model generation. In the experiment, the ShapeNet dataset is adapted to prove the effect of the 3DMGNet, which verifies the robust performance of the proposed method

Effect of Combined Application of Slow-Release and Conventional Urea on Yield and Nitrogen Use Efficiency of Rice and Wheat under Full Straw Return

The effects of one-time basal application of different mixtures of slow-release urea (SRU) and conventional urea (CU) on yield and nitrogen use efficiency (NUE) of rice and wheat were investigated to determine the appropriate ratios of SRU to CU for one-time basal fertilization in a rice&ndash;wheat rotation farmland under full residue incorporation. A field plot experiment was used in this study. Six treatments were established as follows: CK (no nitrogen fertilizer applied), T0 (100% CU, 50% applied as basal fertilizer and 50% applied as jointing fertilizer), T3 (one-time basal application of SRU and CU mixture with 30% SRU), T5 (one-time basal application of SRU and CU mixture with 50% SRU), T7 (one-time basal application of SRU and CU mixture with 70% SRU), and T10 (one-time basal application of 100% SRU). The results showed that the combined application of SRU and CU increased the yields of rice and wheat. Treatment T7 resulted in the highest rice yield, and T3 resulted in the highest wheat yield, which were 25.6% and 29.4% higher, than those of treatment T0, respectively. Compared with treatment T0 (application of CU alone), the combined application of SRU and CU resulted in 27.4&ndash;96.5% and 22.8&ndash;57.1% higher NUE in rice and wheat, respectively

Effect of Combined Application of Slow-Release and Conventional Urea on Yield and Nitrogen Use Efficiency of Rice and Wheat under Full Straw Return

The effects of one-time basal application of different mixtures of slow-release urea (SRU) and conventional urea (CU) on yield and nitrogen use efficiency (NUE) of rice and wheat were investigated to determine the appropriate ratios of SRU to CU for one-time basal fertilization in a rice–wheat rotation farmland under full residue incorporation. A field plot experiment was used in this study. Six treatments were established as follows: CK (no nitrogen fertilizer applied), T0 (100% CU, 50% applied as basal fertilizer and 50% applied as jointing fertilizer), T3 (one-time basal application of SRU and CU mixture with 30% SRU), T5 (one-time basal application of SRU and CU mixture with 50% SRU), T7 (one-time basal application of SRU and CU mixture with 70% SRU), and T10 (one-time basal application of 100% SRU). The results showed that the combined application of SRU and CU increased the yields of rice and wheat. Treatment T7 resulted in the highest rice yield, and T3 resulted in the highest wheat yield, which were 25.6% and 29.4% higher, than those of treatment T0, respectively. Compared with treatment T0 (application of CU alone), the combined application of SRU and CU resulted in 27.4–96.5% and 22.8–57.1% higher NUE in rice and wheat, respectively

Genomic analyses reveal mutational signatures and frequently altered genes in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers world wide and the fourth most lethal cancer in China. However, although genomic studies have identified some mutations associated with ESCC, we know little of the mutational processes responsible. To identify genome-wide mutational signatures, we performed either whole-genome sequencing (WGS) or whole-exome sequencing (WES) on 104 ESCC individuals and combined our data with those of 88 previously reported samples. An APOBEC-mediated mutational signature in 47% of 192 tumors suggests that APOBEC-catalyzed deamination provides a source of DNA damage in ESCC. Moreover, PIK3CA hotspot mutations (c.1624G> A [p.Glu542Lys] and c.1633G>A [p.Glu545Lys]) were enriched in APOBEC-signature tumors, and no smoking associated signature was observed in ESCC. In the samples analyzed by WGS, we identified focal