Insects harbor a remarkable diversity of gut microbiomes critical for host survival, health, and fitness, but the mechanism of this structured symbiotic community remains poorly known, especially for the insect group consisting of many closely related species that inhabit the Qinghai-Tibet Plateau. Here, we firstly analyzed population-level 16S rRNA microbial dataset, comprising 11 Parnassius species covering 5 subgenera, from 14 populations mostly sampled in mountainous regions across northwestern-to-southeastern China, and meanwhile clarified the relative importance of multiple factors on gut microbial community structure and evolution. Our findings indicated that both host genetics and larval host plant modulated gut microbial diversity and community structure. Moreover, the effect analysis of host genetics and larval diet on gut microbiomes showed that host genetics played a critical role in governing the gut microbial beta diversity and the symbiotic community structure, while larval host plant remarkably influenced the functional evolution of gut microbiomes. These findings of the intimate insect-microbe-plant interactions jointly provide some new insights into the correlation among the host genetic background, larval host plant, the structure and evolution of gut microbiome, as well as the mechanisms of high-altitude adaptation in closely related species of this alpine butterfly group.

Heritable rumen microbiota is an important modulator of ruminant growth performance. However, no information exists to date on host genetics-rumen microbiota interactions and their association with phenotype in sheep. To solve this, we curated and analyzed whole-genome resequencing genotypes, 16S rumen-microbiota data, and longitudinal body weight (BW) phenotypes from 1150 sheep.
A variance component model indicated significant heritability of rumen microbial community diversity. Genome-wide association studies (GWAS) using microbial features as traits identified 411 loci-taxon significant associations (P < 10-8). We found a heritability of 39% for 180-day-old BW, while also the rumen microbiota likely played a significant role, explaining that 20% of the phenotypic variation. Microbiota-wide association studies (MWAS) and GWAS identified four marker genera (Bonferroni corrected P < 0.05) and five novel genetic variants (P < 10-8) that were significantly associated with BW. Integrative analysis identified the mediating role of marker genera in genotype influencing phenotype and unravelled that the same genetic markers have direct and indirect effects on sheep weight.
This study reveals a reciprocal interplay among host genetic variations, the rumen microbiota and the body weight traits of sheep. The information obtained provide insights into the diverse microbiota characteristics of rumen and may help in designing precision microbiota management strategies for controlling and manipulating sheep rumen microbiota to increase productivity. Video Abstract.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was varied in disease symptoms. We aim to explore the effect of host genetic factors and comorbidities on severe COVID-19 risk.
A total of 20,320 COVID-19 patients in the UK Biobank cohort were included. Genome-wide association analysis (GWAS) was used to identify host genetic factors in the progression of COVID-19 and a polygenic risk score (PRS) consisted of 86 SNPs was constructed to summarize genetic susceptibility. Colocalization analysis and Logistic regression model were used to assess the association of host genetic factors and comorbidities with COVID-19 severity. All cases were randomly split into training and validation set (1:1). Four algorithms were used to develop predictive models and predict COVID-19 severity. Demographic characteristics, comorbidities and PRS were included in the model to predict the risk of severe COVID-19. The area under the receiver operating characteristic curve (AUROC) was applied to assess the models\' performance.
We detected an association with rs73064425 at locus 3p21.31 reached the genome-wide level in GWAS (odds ratio: 1.55, 95% confidence interval: 1.36-1.78). Colocalization analysis found that two genes (SLC6A20 and LZTFL1) may affect the progression of COVID-19. In the predictive model, logistic regression models were selected due to simplicity and high performance. Predictive model consisting of demographic characteristics, comorbidities and genetic factors could precisely predict the patient\'s progression (AUROC = 82.1%, 95% CI 80.6-83.7%). Nearly 20% of severe COVID-19 events could be attributed to genetic risk.
In this study, we identified two 3p21.31 genes as genetic susceptibility loci in patients with severe COVID-19. The predictive model includes demographic characteristics, comorbidities and genetic factors is useful to identify individuals who are predisposed to develop subsequent critical conditions among COVID-19 patients.

The gut microbiota is a complex and diverse ecosystem comprised of trillions of microbes and plays an essential role in host\'s immunity, metabolism, and even behaviors. Environmental and host factors drive the huge variations in the gut microbiome among individuals. Here, we summarize accumulated evidences about host genetic effect on the gut microbial compositions with emphases on the correlation between host genetic kinship and the similarity of microbial compositions, heritability estimates of microbial taxa, and identification of genomic variants associated with the gut microbiome in pigs as well as in humans. A proportion of bacterial taxa have been reported to be heritable, and numerous variants associated with the diversity of the gut microbiota or specific taxa have been identified in both humans and pigs. LCT and ABO gene have been replicated in multiple studies, and its mechanism have been elucidated clearly. We also discuss the main advantages and challenges using pigs as experimental animals in exploring host genetic effect on the gut microbial composition and provided our insights on the perspectives in this area.

Mendelian susceptibility to mycobacterial diseases (MSMD) is a rare congenital immune deficiency characterized by susceptibility to weakly virulent mycobacteria. Loss-of-function (LOF) mutation of signal transducer and activator of transcription 1 (STAT1) is one of the common genetic causes of MSMD. In this study, we identified a patient who presented with multiple lymph node enlargements and multiple osteolytic disruptions. Mycobacterium gordonae infection was confirmed by metagenomic next-generation sequencing. Whole-exome sequencing identified a novel paternal heterozygous mutation in exon 22 of STAT1 (NM_007315.4, c.1892T>C, p.Val631Ala). This variant was confirmed pathogenic by multiple software predictions. Based on functional assays, STAT1 expression in STAT1V631A cells was not different from STAT1WT cells. But STAT1V631A mutation caused much lower activation of STAT1 when stimulated by interferon-γ (IFN-γ). Fluorescence localization analysis revealed that both STAT1V631A and STAT1WT proteins were located in the cytoplasm, and only a few STAT1V631A proteins were translocated to the nucleus in response to IFN-γ. These results suggest that STAT1V631A leads to LOF in IFN-γ-mediated mycobacterial immunity, resulting in MSMD. Treatment with antibiotics has achieved ideal disease control for this patient, and no adverse events occurred during follow-up. The STAT1 LOF deficiency is a genetic cause of MSMD, which should be considered in patients with mycobacterial disease, especially those with bone involvement.

Pork quality is a factor increasingly considered in consumer preferences for pork. The formation mechanisms determining meat quality are complicated, including endogenous and exogenous factors. Despite a lot of research on meat quality, unexpected variation in meat quality is still a major problem in the meat industry. Currently, gut microbiota and their metabolites have attracted increased attention in the animal breeding industry, and recent research demonstrated their significance in muscle fiber development and fat deposition. The purpose of this paper is to summarize the research on the effects of gut microbiota on pig muscle and fat deposition. The factors affecting gut microbiota composition will also be discussed, including host genetics, dietary composition, antibiotics, prebiotics, and probiotics. We provide an overall understanding of the relationship between gut microbiota and meat quality in pigs, and how manipulation of gut microbiota may contribute to increasing pork quality for human consumption.

Objective: This study aimed to explore the relationships between the common variants of R-spondin/Wnt signaling genes, gut microbiota composition, and osteoporosis (OP) risk in elderly Chinese Han population. Design: Dual-energy X-ray absorptiometry was used to obtain the OP-associated measurements at multiple skeleton sites among all 1,168 participants. Genotyping data was obtained by using the next-generation sequencing in the discovery stage (n = 400, 228 OP patients) and SNPscan technology in the replication stage (n = 768, 356 OP patients). Bioinformatic analysis was performed to provide more evidence for the genotype-OP associations. The 16S ribosomal RNA gene high-throughput sequencing technology was adopted to explore OP-associated gut microbiota variations. Results: The genetic variants of rs10920362 in the LGR6 gene (P-FDR = 1.19 × 10-6) and rs11178860 in the LGR5 gene (P-FDR = 1.51 × 10-4) were found to associate with OP risk significantly. Several microbial taxa were associated with the BMDs and T-scores at multiple skeleton sites. The associations between rs10920362 and BMD-associated microbiota maintained significance after adjusting confounders. The rs10920362 CT/TT genotype associated with a decreased relative abundance of Actinobacteria (β = -1.32, P < 0.001), Bifidobacteriaceae (β = -1.70, P < 0.001), and Bifidobacterium (β = -1.70, P < 0.001) compared to the CC genotype. Conclusion: Our findings suggested that the variants loci of LGR6 may be associate with OP pathogenesis via gut microbiota modifications. The relationship between host genetics and gut microbiome provides new perspectives about OP prevention and treatment.

Diet and host genetics influence the composition of intestinal microbiota, yet few studies have compared the function of intestinal microbiota in the diet- or genotype-induced lipid deposition, which limits our understanding of the role of intestinal bacteria in metabolic disorders. The lipid accumulation in wild-type zebrafish fed with control (CON) or high-fat (HF) diet and two gene-knockout zebrafish lines (cpt1b -/- or pparab -/-) fed with control diet was measured after a 4-week feeding experiment. The intestinal microbiota composition of these groups was investigated using 16S ribosomal RNA (rRNA) gene sequencing (DNA-based) and 16S rRNA sequencing (RNA-based). The HF diet or deficiency of two genes induced more weight gain and higher triglyceride content in the liver compared with their control group. 16S rRNA gene sequencing (DNA-based) indicated the decreased abundance of Proteobacteria in the HF group compared with CON, but there was no significant difference in bacterial α diversity among treatments. 16S rRNA sequencing (RNA-based) confirmed the decreased abundance of Proteobacteria and the bacterial α diversity in the HF group compared with CON. Deficiency of cpt1b or pparab showed less change in microbiota composition compared with their wild-type group. Intestinal microbiota of each group was transferred to germ-free zebrafish, and the quantification of Nile red staining indicated that the intestinal microbiota of the HF group induced more lipid accumulation compared with CON, whereas intestinal microbiota of cpt1b -/- and pparab -/- zebrafish did not. The results showed that RNA-based bacterial sequencing revealed more bacterial alteration than DNA-based bacterial sequencing. HF diet had a more dominant role in shaping gut microbiota composition to induce lipid accumulation compared with the gene-knockout of cpt1b or pparab in zebrafish, and the transplant of intestinal microbiota from HF-fed fish induced more lipid deposition in germ-free zebrafish. Together, these data suggested that a high-fat diet exerted a more dominant role over the deletion of cpt1b or pparab on the intestinal bacterial composition, which corresponded to lipid accumulation.

Understanding the micro-coevolution of the human gut microbiome with host genetics is challenging but essential in both evolutionary and medical studies. To gain insight into the interactions between host genetic variation and the gut microbiome, we analyzed both the human genome and gut microbiome collected from a cohort of 190 students in the same boarding college and representing 3 ethnic groups, Uyghur, Kazakh, and Han Chinese. We found that differences in gut microbiome were greater between genetically distinct ethnic groups than those genetically closely related ones in taxonomic composition, functional composition, enterotype stratification, and microbiome genetic differentiation. We also observed considerable correlations between host genetic variants and the abundance of a subset of gut microbial species. Notably, interactions between gut microbiome species and host genetic variants might have coordinated effects on specific human phenotypes. Bacteroides ovatus, previously reported to modulate intestinal immunity, is significantly correlated with the host genetic variant rs12899811 (meta-P = 5.55 × 10-5), which regulates the VPS33B expression in the colon, acting as a tumor suppressor of colorectal cancer. These results advance our understanding of the micro-coevolution of the human gut microbiome and their interactive effects with host genetic variation on phenotypic diversity.

Increasing evidence suggests that human gut microbiome plays an important role in variation of skeletal muscle mass (SMM). However, specific causal mechanistic relationship of human gut microbiome with SMM remains largely unresolved. Understanding the causal mechanistic relationship may provide a basis for novel interventions for loss of SMM. This study investigated whether human gut microbiome has a causal effect on SMM among Chinese community-dwelling healthy menopausal women.
Estimated SMM was derived from whole-body dual-energy X-ray absorptiometry. We performed integrated analyses on whole-genome sequencing, shotgun metagenomic sequencing, and serum short-chain fatty acids (SCFAs), as well as available host SMM measurements among community-dwelling healthy menopausal women (N = 482). We combined the results with summary statistics from genome-wide association analyses for human gut microbiome (N = 952) and SMM traits (N = 28 330). As a prerequisite for causality, we used a computational protocol that was proposed to measure correlations among gut metagenome, metabolome, and the host trait to investigate the relationship between human gut microbiome and SMM. Causal inference methods were applied to assess the potential causal effects of gut microbial features on SMM, through one-sample and two-sample Mendelian randomization (MR) analyses, respectively.
In metagenomic association analyses, the increased capacity for gut microbial synthesis of the SCFA butyrate was significantly associated with serum butyrate levels [Spearman correlation coefficient (SCC) = 0.13, P = 0.02] and skeletal muscle index (SCC = 0.084, P = 0.002). Of interest was the finding that two main butyrate-producing bacterial species were both positively associated with the increased capacity for gut microbial synthesis of butyrate [Faecalibacterium prausnitzii (SCC = 0.25, P = 6.6 × 10-7 ) and Butyricimonas virosa (SCC = 0.15, P = 0.001)] and for skeletal muscle index [F. prausnitzii (SCC = 0.16, P = 6.2 × 10-4 ) and B. virosa (SCC = 0.17, P = 2.4 × 10-4 )]. One-sample MR results showed a causal effect between gut microbial synthesis of the SCFA butyrate and appendicular lean mass (β = 0.04, 95% confidence interval 0.029 to 0.051, P = 0.003). Two-sample MR results further confirmed the causal effect between gut microbial synthesis of the SCFA butyrate and appendicular lean mass (β = 0.06, 95% confidence interval 0 to 0.13, P = 0.06).
Our results may help the future development of novel intervention approaches for preventing or alleviating loss of SMM.