Cell genomicsPub Date : 2024-10-09Epub Date: 2024-09-11DOI: 10.1016/j.xgen.2024.100638
Kelsey E Johnson, Timothy Heisel, Mattea Allert, Annalee Fürst, Nikhila Yerabandi, Dan Knights, Katherine M Jacobs, Eric F Lock, Lars Bode, David A Fields, Michael C Rudolph, Cheryl A Gale, Frank W Albert, Ellen W Demerath, Ran Blekhman
{"title":"Human milk variation is shaped by maternal genetics and impacts the infant gut microbiome.","authors":"Kelsey E Johnson, Timothy Heisel, Mattea Allert, Annalee Fürst, Nikhila Yerabandi, Dan Knights, Katherine M Jacobs, Eric F Lock, Lars Bode, David A Fields, Michael C Rudolph, Cheryl A Gale, Frank W Albert, Ellen W Demerath, Ran Blekhman","doi":"10.1016/j.xgen.2024.100638","DOIUrl":"10.1016/j.xgen.2024.100638","url":null,"abstract":"<p><p>Human milk is a complex mix of nutritional and bioactive components that provide complete nourishment for the infant. However, we lack a systematic knowledge of the factors shaping milk composition and how milk variation influences infant health. Here, we characterize relationships between maternal genetics, milk gene expression, milk composition, and the infant fecal microbiome in up to 310 exclusively breastfeeding mother-infant pairs. We identified 482 genetic loci associated with milk gene expression unique to the lactating mammary gland and link these loci to breast cancer risk and human milk oligosaccharide concentration. Integrative analyses uncovered connections between milk gene expression and infant gut microbiome, including an association between the expression of inflammation-related genes with milk interleukin-6 (IL-6) concentration and the abundance of Bifidobacterium and Escherichia in the infant gut. Our results show how an improved understanding of the genetics and genomics of human milk connects lactation biology with maternal and infant health.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100638"},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602576/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142302297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cell genomicsPub Date : 2024-10-09DOI: 10.1016/j.xgen.2024.100633
Han Xiao, Linxuan Li, Meng Yang, Xinyi Zhang, Jieqiong Zhou, Jingyu Zeng, Yan Zhou, Xianmei Lan, Jiuying Liu, Ying Lin, Yuanyuan Zhong, Xiaoqian Zhang, Lin Wang, Zhongqiang Cao, Panhong Liu, Hong Mei, Mingzhi Cai, Xiaonan Cai, Ye Tao, Yunqing Zhu, Canqing Yu, Liqin Hu, Yu Wang, Yushan Huang, Fengxia Su, Ya Gao, Rui Zhou, Xun Xu, Huanming Yang, Jian Wang, Huanhuan Zhu, Aifen Zhou, Xin Jin
{"title":"Genetic analyses of 104 phenotypes in 20,900 Chinese pregnant women reveal pregnancy-specific discoveries.","authors":"Han Xiao, Linxuan Li, Meng Yang, Xinyi Zhang, Jieqiong Zhou, Jingyu Zeng, Yan Zhou, Xianmei Lan, Jiuying Liu, Ying Lin, Yuanyuan Zhong, Xiaoqian Zhang, Lin Wang, Zhongqiang Cao, Panhong Liu, Hong Mei, Mingzhi Cai, Xiaonan Cai, Ye Tao, Yunqing Zhu, Canqing Yu, Liqin Hu, Yu Wang, Yushan Huang, Fengxia Su, Ya Gao, Rui Zhou, Xun Xu, Huanming Yang, Jian Wang, Huanhuan Zhu, Aifen Zhou, Xin Jin","doi":"10.1016/j.xgen.2024.100633","DOIUrl":"10.1016/j.xgen.2024.100633","url":null,"abstract":"<p><p>Monitoring biochemical phenotypes during pregnancy is vital for maternal and fetal health, allowing early detection and management of pregnancy-related conditions to ensure safety for both. Here, we conducted a genetic analysis of 104 pregnancy phenotypes in 20,900 Chinese women. The genome-wide association study (GWAS) identified a total of 410 trait-locus associations, with 71.71% reported previously. Among the 116 novel hits for 45 phenotypes, 83 were successfully replicated. Among them, 31 were defined as potentially pregnancy-specific associations, including creatine and HELLPAR and neutrophils and ESR1, with subsequent analysis revealing enrichments in estrogen-related pathways and female reproductive tissues. The partitioning heritability underscored the significant roles of fetal blood, embryoid bodies, and female reproductive organs in pregnancy hematology and birth outcomes. Pathway analysis confirmed the intricate interplay of hormone and immune regulation, metabolism, and cell cycle during pregnancy. This study contributes to the understanding of genetic influences on pregnancy phenotypes and their implications for maternal health.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"4 10","pages":"100633"},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602630/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142402179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Novel insights into the genetic architecture of pregnancy glycemic traits from 14,744 Chinese maternities.","authors":"Huanhuan Zhu, Han Xiao, Linxuan Li, Meng Yang, Ying Lin, Jieqiong Zhou, Xinyi Zhang, Yan Zhou, Xianmei Lan, Jiuying Liu, Jingyu Zeng, Lin Wang, Yuanyuan Zhong, Xiaobo Qian, Zhongqiang Cao, Panhong Liu, Hong Mei, Mingzhi Cai, Xiaonan Cai, Zhuangyuan Tang, Liqin Hu, Rui Zhou, Xun Xu, Huanming Yang, Jian Wang, Xin Jin, Aifen Zhou","doi":"10.1016/j.xgen.2024.100631","DOIUrl":"10.1016/j.xgen.2024.100631","url":null,"abstract":"<p><p>Glycemic traits are critical indicators of maternal and fetal health during pregnancy. We performed genetic analysis for five glycemic traits in 14,744 Chinese pregnant women. Our genome-wide association study identified 25 locus-trait associations, including established links between gestational diabetes mellitus (GDM) and the genes CDKAL1 and MTNR1B. Notably, we discovered a novel association between fasting glucose during pregnancy and the ESR1 gene (estrogen receptor), which was validated by an independent study in pregnant women. The ESR1-GDM link was recently reported by the FinnGen project. Our work enhances the findings in East Asian populations and highlights the need for independent studies. Further analyses, including genetic correlation, Mendelian randomization, and transcriptome-wide association studies, provided genetic insights into the relationship between pregnancy glycemic traits and hypertension. Overall, our findings advance the understanding of genetic architecture of pregnancy glycemic traits, especially in East Asian populations.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"4 10","pages":"100631"},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602577/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142402181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cell genomicsPub Date : 2024-10-09Epub Date: 2024-09-23DOI: 10.1016/j.xgen.2024.100656
Julie Rojas, James Hose, H Auguste Dutcher, Michael Place, John F Wolters, Chris Todd Hittinger, Audrey P Gasch
{"title":"Comparative modeling reveals the molecular determinants of aneuploidy fitness cost in a wild yeast model.","authors":"Julie Rojas, James Hose, H Auguste Dutcher, Michael Place, John F Wolters, Chris Todd Hittinger, Audrey P Gasch","doi":"10.1016/j.xgen.2024.100656","DOIUrl":"10.1016/j.xgen.2024.100656","url":null,"abstract":"<p><p>Although implicated as deleterious in many organisms, aneuploidy can underlie rapid phenotypic evolution. However, aneuploidy will be maintained only if the benefit outweighs the cost, which remains incompletely understood. To quantify this cost and the molecular determinants behind it, we generated a panel of chromosome duplications in Saccharomyces cerevisiae and applied comparative modeling and molecular validation to understand aneuploidy toxicity. We show that 74%-94% of the variance in aneuploid strains' growth rates is explained by the cumulative cost of genes on each chromosome, measured for single-gene duplications using a genomic library, along with the deleterious contribution of small nucleolar RNAs (snoRNAs) and beneficial effects of tRNAs. Machine learning to identify properties of detrimental gene duplicates provided no support for the balance hypothesis of aneuploidy toxicity and instead identified gene length as the best predictor of toxicity. Our results present a generalized framework for the cost of aneuploidy with implications for disease biology and evolution.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100656"},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602619/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142333607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Phenome-wide association study in 25,639 pregnant Chinese women reveals loci associated with maternal comorbidities and child health.","authors":"Jintao Guo, Qiwei Guo, Taoling Zhong, Chaoqun Xu, Zhongmin Xia, Hongkun Fang, Qinwei Chen, Ying Zhou, Jieqiong Xie, Dandan Jin, You Yang, Xin Wu, Huanhuan Zhu, Ailing Hour, Xin Jin, Yulin Zhou, Qiyuan Li","doi":"10.1016/j.xgen.2024.100632","DOIUrl":"10.1016/j.xgen.2024.100632","url":null,"abstract":"<p><p>Phenome-wide association studies (PheWAS) have been less focused on maternal diseases and maternal-newborn comorbidities, especially in the Chinese population. To enhance our understanding of the genetic basis of these related diseases, we conducted a PheWAS on 25,639 pregnant women and 14,151 newborns in the Chinese Han population using ultra-low-coverage whole-genome sequence (ulcWGS). We identified 2,883 maternal trait-associated SNPs associated with 26 phenotypes, among which 99.5% were near established genome-wide association study (GWAS) loci. Further refinement delineated these SNPs to 442 unique trait-associated loci (TALs) predicated on linkage disequilibrium R<sup>2</sup> > 0.8, revealing that 75.6% demonstrated pleiotropy and 50.9% were located in genes implicated in analogous phenotypes. Notably, we discovered 21 maternal SNPs associated with 35 neonatal phenotypes, including two SNPs associated with identical complications in both mothers and children. These findings underscore the importance of integrating ulcWGS data to enrich the discoveries derived from traditional PheWAS approaches.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"4 10","pages":"100632"},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602594/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142402182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The loach haplotype-resolved genome and the identification of Mex3a involved in fish air breathing.","authors":"Bing Sun, Qingshan Li, Xinxin Xiao, Jianwei Zhang, Ying Zhou, Yuwei Huang, Jian Gao, Xiaojuan Cao","doi":"10.1016/j.xgen.2024.100670","DOIUrl":"10.1016/j.xgen.2024.100670","url":null,"abstract":"<p><p>Fish air breathing is crucial for the transition of vertebrates from water to land. So far, the genes involved in fish air breathing have not been well identified. Here, we performed gene enrichment analysis of positively selected genes (PSGs) in loach (Misgurnus anguillicaudatus, an air-breathing fish) in comparison to Triplophysa tibetana (a non-air-breathing fish), haplotype-resolved genome assembly of the loach, and gene evolutionary analysis of air-breathing and non-air-breathing fishes and found that the PSG mex3a originated from ancient air-breathing fish species. Deletion of Mex3a impaired loach air-breathing capacity by inhibiting angiogenesis through its interaction with T-box transcription factor 20. Mex3a overexpression significantly promoted angiogenesis. Structural analysis and point mutation revealed the critical role of the 201st amino acid in loach Mex3a for angiogenesis. Our findings innovatively indicate that the ancient mex3a is a fish air-breathing gene, which holds significance for understanding fish air breathing and provides a valuable resource for cultivating hypoxia-tolerant fish varieties.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"4 10","pages":"100670"},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602589/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142402184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cell genomicsPub Date : 2024-10-09DOI: 10.1016/j.xgen.2024.100669
Siyang Liu, Yanhong Liu, Yuqin Gu, Xingchen Lin, Huanhuan Zhu, Hankui Liu, Zhe Xu, Shiyao Cheng, Xianmei Lan, Linxuan Li, Mingxi Huang, Hao Li, Rasmus Nielsen, Robert W Davies, Anders Albrechtsen, Guo-Bo Chen, Xiu Qiu, Xin Jin, Shujia Huang
{"title":"Utilizing non-invasive prenatal test sequencing data for human genetic investigation.","authors":"Siyang Liu, Yanhong Liu, Yuqin Gu, Xingchen Lin, Huanhuan Zhu, Hankui Liu, Zhe Xu, Shiyao Cheng, Xianmei Lan, Linxuan Li, Mingxi Huang, Hao Li, Rasmus Nielsen, Robert W Davies, Anders Albrechtsen, Guo-Bo Chen, Xiu Qiu, Xin Jin, Shujia Huang","doi":"10.1016/j.xgen.2024.100669","DOIUrl":"10.1016/j.xgen.2024.100669","url":null,"abstract":"<p><p>Non-invasive prenatal testing (NIPT) employs ultra-low-pass sequencing of maternal plasma cell-free DNA to detect fetal trisomy. Its global adoption has established NIPT as a large human genetic resource for exploring genetic variations and their associations with phenotypes. Here, we present methods for analyzing large-scale, low-depth NIPT data, including customized algorithms and software for genetic variant detection, genotype imputation, family relatedness, population structure inference, and genome-wide association analysis of maternal genomes. Our results demonstrate accurate allele frequency estimation and high genotype imputation accuracy (R<sup>2</sup>>0.84) for NIPT sequencing depths from 0.1× to 0.3×. We also achieve effective classification of duplicates and first-degree relatives, along with robust principal-component analysis. Additionally, we obtain an R<sup>2</sup>>0.81 for estimating genetic effect sizes across genotyping and sequencing platforms with adequate sample sizes. These methods offer a robust theoretical and practical foundation for utilizing NIPT data in medical genetic research.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"4 10","pages":"100669"},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602596/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142402186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Identifying compound-protein interactions with knowledge graph embedding of perturbation transcriptomics.","authors":"Shengkun Ni, Xiangtai Kong, Yingying Zhang, Zhengyang Chen, Zhaokun Wang, Zunyun Fu, Ruifeng Huo, Xiaochu Tong, Ning Qu, Xiaolong Wu, Kun Wang, Wei Zhang, Runze Zhang, Zimei Zhang, Jiangshan Shi, Yitian Wang, Ruirui Yang, Xutong Li, Sulin Zhang, Mingyue Zheng","doi":"10.1016/j.xgen.2024.100655","DOIUrl":"10.1016/j.xgen.2024.100655","url":null,"abstract":"<p><p>The emergence of perturbation transcriptomics provides a new perspective for drug discovery, but existing analysis methods suffer from inadequate performance and limited applicability. In this work, we present PertKGE, a method designed to deconvolute compound-protein interactions from perturbation transcriptomics with knowledge graph embedding. By considering multi-level regulatory events within biological systems that share the same semantic context, PertKGE significantly improves deconvoluting accuracy in two critical \"cold-start\" settings: inferring targets for new compounds and conducting virtual screening for new targets. We further demonstrate the pivotal role of incorporating multi-level regulatory events in alleviating representational biases. Notably, it enables the identification of ectonucleotide pyrophosphatase/phosphodiesterase-1 as the target responsible for the unique anti-tumor immunotherapy effect of tankyrase inhibitor K-756 and the discovery of five novel hits targeting the emerging cancer therapeutic target aldehyde dehydrogenase 1B1 with a remarkable hit rate of 10.2%. These findings highlight the potential of PertKGE to accelerate drug discovery.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100655"},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602590/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142302298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cell genomicsPub Date : 2024-10-09Epub Date: 2024-09-23DOI: 10.1016/j.xgen.2024.100659
Canhui Cao, Miaochun Xu, Ye Wei, Ting Peng, Shitong Lin, Xiaojie Liu, Yashi Xu, Tian Chu, Shiyi Liu, Ping Wu, Bai Hu, Wencheng Ding, Li Li, Ding Ma, Peng Wu
{"title":"CXCR4 orchestrates the TOX-programmed exhausted phenotype of CD8<sup>+</sup> T cells via JAK2/STAT3 pathway.","authors":"Canhui Cao, Miaochun Xu, Ye Wei, Ting Peng, Shitong Lin, Xiaojie Liu, Yashi Xu, Tian Chu, Shiyi Liu, Ping Wu, Bai Hu, Wencheng Ding, Li Li, Ding Ma, Peng Wu","doi":"10.1016/j.xgen.2024.100659","DOIUrl":"10.1016/j.xgen.2024.100659","url":null,"abstract":"<p><p>Evidence from clinical trials suggests that CXCR4 antagonists enhance immunotherapy effectiveness in several cancers. However, the specific mechanisms through which CXCR4 contributes to immune cell phenotypes are not fully understood. Here, we employed single-cell transcriptomic analysis and identified CXCR4 as a marker gene in T cells, with CD8<sup>+</sup>PD-1<sup>high</sup> exhausted T (T<sub>ex</sub>) cells exhibiting high CXCR4 expression. By blocking CXCR4, the T<sub>ex</sub> phenotype was attenuated in vivo. Mechanistically, CXCR4-blocking T cells mitigated the T<sub>ex</sub> phenotype by regulating the JAK2-STAT3 pathway. Single-cell RNA/TCR/ATAC-seq confirmed that Cxcr4-deficient CD8<sup>+</sup> T cells epigenetically mitigated the transition from functional to exhausted phenotypes. Notably, clinical sample analysis revealed that CXCR4<sup>+</sup>CD8<sup>+</sup> T cells showed higher expression in patients with a non-complete pathological response. Collectively, these findings demonstrate the mechanism by which CXCR4 orchestrates CD8<sup>+</sup> T<sub>ex</sub> cells and provide a rationale for combining CXCR4 antagonists with immunotherapy in clinical trials.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100659"},"PeriodicalIF":11.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602566/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142333608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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