Biology subjects

Zan, Y.

Publications and source records attributed to Zan, Y..

17 recordsLinked to original sources

bioRxiv2026

Phyllosphere and rhizosphere microbiomes empower Nicotiana tobacum complex traits dissection and prediction

Understanding how plant-associated microbiomes interact with host genome variation to influence agronomic traits is essential for advancing microbiomeassisted crop improvement. In this study, we characterized the phyllosphere and rhizosphere microbiomes of 164 diverse Nicotiana tabacum accessions using 16S rRNA sequencing and integrated these data with host genomic variation and 22 agronomic traits. The two microbiomes exhibited distinct taxonomic structures, diversity patterns, and predicted metabolic functions. Microbiome genomewide association studies identified extensive host genetic control over microbial abundance, including 49 shared genomic loci that explained nearly half of the heritable variation in both microbiomes. Microbiomewide association studies revealed biologically meaningful associations between specific ASVs and agronomic traits. However, network analysis demonstrated that microbial subcommunities, rather than individual taxa, contributed substantially to phenotypic variation. Then, colocalization analysis further identified genetic variants jointly influencing microbial abundance and metabolite traits, highlighting potential host-microbe-trait causal links. Incorporating microbiome data into genomic selection models, we successfully improved prediction accuracy for several traits, especially plant architecture and flowering. Together, this work provides a comprehensive populationlevel framework linking host genetics, microbiome composition, and agronomic traits in tobacco, offering new insights for microbiomeinformed breeding strategies.

plant biology↗

bioRxiv2025

Development and application of a genotyping by target sequencing SNP array panel in Salix suchowensis

Salix suchowensis is an important species of Salix, known for its rapid growth property and wide application in environmental construction, ecological restoration, wicker production, and biomass energy production. Due to its significance as a sustainable biological resource, S. suchowensis has been the centre of intensive breeding. However, rapid improvement of growth and biomass has been hindered by a lack of genomic resources. To address this limitation, we designed a genotyping by target sequencing SNP array panel to facilitate efficient genotyping. Using whole-genome resequencing data, a total of 39,076 SNPs were selected for the array panel, consisting of trait-associated SNPs, intragenic SNPs, and intergenic SNPs. This panel was validated by genotyping 550 new samples, demonstrating high call rates and effective capture of the population structure. Genome-wide association analysis identified 72 SNPs associated with plant height and ground diameter. Additionally, the array panel shows a high potential for genomic selection, with high prediction accuracy for various traits. These results highlight the efficiency of this panel in capturing genomic variations that are highly valuable for future genetic research and breeding applications.

genetics↗

bioRxiv2024

Natural genetic and transcriptomic variation in photosynthesis associated pathways contribute to adaptive traits variation in worldwide Arabidopsis thaliana population

Photosynthesis is the most important reaction underlying carbon fixation. Despite its potential in boosting carbon assimilation, nature variations underlying genes in photosynthesis pathway and their role in adaptive traits variation remains elusive. In this study, we investigated the genetic, transcriptomic variation of 1103 genes in photosynthesis associated pathways, including 82 photosynthesis core genes, 24 plastid-encoded RNA polymerase related genes, 2 nucleus-encoded RNA polymerase-related genes, 34 photomorphogenesis-related genes, 40 genes involved in transcription and translation (TAC) and 938 other nuclear-encoded chloroplast-targeted genes. By de novo assembling the chloroplast genomes of 28 representative accessions and leveraging whole-genome, transcriptome sequencing data from the 1001 Genome Project, we revealed extensive natural genetic and transcriptome variations these genes in worldwide Arabidopsis thaliana population. 34.0% of them were identified with regulatory variations in expression quantitative locus mapping (eQTL) mapping, including key components of Rubisco (RBCS1B, RBCS2B), and Rubisco activase (RCA). Genome-wide and transcriptome-wide association analysis (GWAS/TWAS) showed that these genetic and transcriptomic variations made considerable contribution to variation of adaptive traits. Overall, our study provides insight into the natural genetic variation of these genes among worldwide Arabidopsis thaliana accessions and their role in complex traits variation and adaptation.

plant biology↗

bioRxiv2024

Complex genetic architecture underlying the plasticity of tobacco leaf width provides insight into across-environment genomic prediction

Phenotypic plasticity refers to the ability of a given genotype to produce multiple phenotypes in response to changing environmental conditions. Understanding the genetic basis of phenotypic plasticity and developing predictive models for agronomic traits are crucial for future agricultural adaptation to climate change. In this study, we investigated the genetic basis of leaf width mean (LWm) and plasticity (LWp) in a tobacco multiparent advanced generation inter-cross (MAGIC) population which consisting of 594 individuals. We identified 14 quantitative trait loci (QTLs) significantly associated with LWm, 43 with LWp. Our findings suggest that dynamic changes in QTL effects across environments, along with polygenic effects, may underlie the genetic basis of leaf width plasticity. Among them, qLW14 was narrowed down to a 3 Mb structural variation region. When this fragment was deleted in tobacco, plants exhibited increased leaf width, but only under specific environmental conditions. This finding suggests that the key gene within qLW14 may act as a negative regulator of leaf width through interactions with specific environmental factors. By integrating genetic diversity, environments variation, and their interactions into a GEAI model, we were able to build a framework for cross-environment prediction, improving prediction accuracy by 8.7% when compared to traditional model. Overall, this study highlights the complex genetic basis underlying LWp, involving multiple alleles and genotype-environment interactions. These findings provide valuable insights into the role of phenotypic plasticity in plant adaptation to environmental changes.

genetics↗

bioRxiv2023

Comprehensive analyses of 1771 transcriptome from seven tissues enhance genetic and biological interpretations of maize complex traits

By analyzing 1771 RNA-seq datasets from seven tissues in a maize diversity panel, we explored the landscape of multi-tissue transcriptome variation and evolution patterns of tissue-specific genes, and built a comprehensive multi-tissue gene regulation atlas to understand the genetic regulation of maize complex trait. Using transcriptome-wide association analysis, we linked tissue-specific expression variation of 45 genes to variation of 11 agronomic traits. Through integrative analyses of tissue-specific gene regulatory variation with genome-wide association studies, we detected relevant tissue types and candidate genes for a number of agronomic traits, including leaf during the day for anthesis-silking interval (GRMZM2G093210), leaf during the day for kernel Zeinoxanthin level (GRMZM2G143202), and root for ear height (GRMZM2G700665), highlighting the contribution from tissue-specific gene expression to variation of agronomic trait. Our findings provide novel insights into the genetic and biological mechanisms underlying complex traits in maize, and the multi-tissue regulatory atlas serves as a primary source for biological interpretation, functional validation, and genomic improvement of maize.

genetics↗

bioRxiv2023

Polygenic basis of strong and rapid flowering time response to environment perturbations in wild Arabidopsis thaliana population

Despite the importance in understanding the impact of climate change, the genetics of rapid response to changing environments and its role in adaptive evolution remains elusive. Here, we studied flowering time response to environment changes using 514 Arabidopsis thaliana worldwide accessions with re-sequencing genomes and flowering time measurements from ten unique environments with variable temperature, drought, daylight and competition stresses. We revealed a polygenic basis of flowering time mean and plasticity, underpinned by 52 mean and plasticity QTL. Widespread interaction between mean QTL, polygenic background and surrounding environments considerably altered the amount of additive genetic variance and allelic effects of detected QTL. This caused variability in phenotype plasticity and across environment variation in genetic variance, resulting in rapid flowering time response to environment perturbations. In addition, the plastic alleles showed a higher correlation with the environment factors than that from randomly sampled alleles, suggesting a potential role in climate adaptation. We therefore proposed a polygenic interaction model, whereby large effect QTL and polygenic background simultaneously interacted with the surrounding environment, underlying rapid response to changing environments. Results from our study thus provided deeper insights into the genetics of plasticity, with potential benefit in genomic selection of crops in heterogeneous environments and predicting changes in species distribution and the evolutionary trajectory of wild populations.

genetics↗

bioRxiv2023

GenBank genomics highlight the genomic features, genetic diversity and regulation of morphological, metabolic and disease-resistance traits in Nicotiana tabacum

Nicotiana tabacum is a model organism in plant molecular and pathogenic research and has significant potential in the production of biofuels and active pharmaceutical compounds in synthetic biology. Because of the large allotetraploid genome of tobacco, its genomic features, genetic diversity and genetic regulation of many complex traits remain unknown. In this study, we present a nearly complete chromosome-scale assembly of N. tabacum and provide evidence that homoeologous exchange between subgenomes and epigenetic remodelling are likely mechanisms of genome stabilization and subgenome coordination following polyploidization. By leveraging GenBank-scale sequencing and phenotyping data from 5196 lines, geography at the continent scale, rather than types assigned on the basis of curing crop practices, was found to be the most important correlate of genetic structure. Using 178 marker{square}trait associations detected in genome-wide association analysis, a reference genotype-to-phenotype map was built for 39 morphological, developmental, and disease-resistance traits. A novel gene, auxin response factor 9 (Arf9), associated with wider leaves after being knocked out, was fine-mapped to a single nucleotide polymorphism (SNP). This point mutation alters the translated amino acid from Ala203 to Pro203, likely preventing homodimer formation during DNA binding. Our analysis also revealed signatures of positive and polygenic selection for multiple traits during the process of selective breeding. Overall, this study demonstrated the power of leveraging GenBank genomics to gain insights into the genomic features, genetic diversity, and regulation of complex traits in N. tabacum, laying a foundation for future research on plant functional genomics, crop breeding, and the production of biopharmaceuticals and biofuels.

genetics↗

bioRxiv2022

The pan-genome and local adaptation of Arabidopsis thaliana

Arabidopsis thaliana has been used as a model species for research in a diverse collection of plant species. However, previous studies based on single reference genomes and short-read sequencing data are restricted to detecting variable genes and large structural variation (SV) underlying local adaptation. Here we de novo assemble high-quality chromosomal genomes of 38 A. thaliana ecotypes (with 6 relict ones) using PacBio-HiFi long-read sequencing. From these newly assembled genomes, we annotate several thousand new genes through pan-genomic analysis in comparison to the previous reference genome. The identified variable genes are mainly enriched in and associated with ecological adaptation and this species substantially expands its gene repertoire for local adaptation. We construct a graph-based pan-genome and identify 62,525 SVs which overlap with 14,243 genes. These genes are enriched in multiple ecological adaptation functions, including secondary metabolic processes, enzyme regulation, and biotic/abiotic stimulus. For example, a 566 bp insertion in the promoter of the light-adaptation KNAT3 gene was specific to the high-altitude relict Tibet-0 ecotype. This SV reduces the expression level of KNAT3 and promotes A. thaliana adaptation to habitats high in light radiation. In addition, compared with the SNPs, the SVs identified in this study captured the missing heritability and we detected novel SV associations with environmental variables in their native range, highlighting the value of SVs in environmental adaptation. The genome resources presented here will help pinpoint genetic changes that include both SVs and the ecotype-specific genes for local adaptation of A. thaliana and increase our understanding of the molecular mechanisms in this model species to respond to varied habitats.

genomics↗

bioRxiv2022

Complex genetic architecture underlying the plasticity of maize agronomic traits

Phenotypic plasticity is the property of a given genotype to produce multiple phenotypes in response to changing environmental conditions. Understanding the genetic basis of phenotypic plasticity and establishing a predictive model is highly relevant for future agriculture under changing climate. Here, we report findings on the genetic basis of phenotypic plasticity for 23 complex traits using a maize diverse population, planted at five sites with distinct environmental conditions and genotyped with ~ 6.60 million SNPs. We found that altitude-related environmental factors were main drivers for across site variation in flowering time traits but not plant architecture and yield traits. For 23 traits, we detected 109 QTLs, of which 29 was for mean, 66 was for plasticity, and 14 for both parameters, besides, 80% of the QTLs were interreacted with the environment. The effects of several QTLs changed in magnitude or sign, driving variation in phenotype plasticity, and we further experimentally validated one plastic gene ZmTPS14.1 whose effect was likely mediated by the compensation effect of ZmSPL6 which was from the downstream pathway probably. By integrating genetic diversity, environmental variation, and their interaction in a joint model, we could provide site-specific predictions with increased accuracy by as much as 15.5%, 3.8%, and 4.4% for DTT, PH, and EW, respectively. Overall, we revealed a complex genetic architecture involving multiallelic, pleiotropy, and genotype by environment interaction underlying maize complex trait mean and plasticity variation. Our study thus provided novel insights into the dynamic genetic architectures of agronomic traits in response to changing environments, paving a practical route to precision agriculture.

genetics↗

bioRxiv2021

Low-coverage sequencing in a deep intercross of the Virginia body weight lines provides insight to the polygenic genetic architecture of growth: novel loci revealed by increased power and improved genome-coverage

Genetic dissection of highly polygenic traits is a challenge, in part due to the power necessary to confidently identify loci with minor effects. Experimental crosses are valuable resources for mapping such traits. Traditionally, genome-wide analyses of experimental crosses have targeted major loci using data from a single generation, often the F2, with additional, later generation individuals being generated for replication and fine-mapping. Here, we aim to confidently identify minor-effect loci contributing to the highly polygenic basis of the long-term, divergent bi-directional selection responses for 56-day body weight in the Virginia chicken lines. To achieve this, a powerful strategy was developed to make use of data from all generations (F2-F18) of an advanced intercross line, developed by crossing the low and high selected lines after 40 generations of selection. A cost-efficient low-coverage sequencing based approach was used to obtain high-confidence genotypes in 1Mb bins across 99.3% of the chicken genome for >3,300 intercross individuals. In total, 12 genome-wide significant and 10 additional suggestive QTL for 56-day body weight were mapped, with only two of these QTL reaching genome-wide, and one suggestive, significance in analyses of the F2 generation. Five of the significant, and four of the suggestive, QTL were among the 20 loci reaching a 20% FDR-threshold in previous analyses of data from generation F15. The novel, minor-effect QTL mapped here were generally mapped due to an overall increase in power by integrating data across generations, with minor contributions from increased genome-coverage and improved marker information content. Significant and suggestive QTL now explain >60% of the difference between the parental lines, three times more than the previously reported significant QTL. Making integrated use of all available samples from multiple generations in experimental crosses is now economically feasible using the low-cost, sequencing-based genotyping strategies outlined here. Our empirical results illustrate the value of this strategy for mapping novel minor-effect loci contributing to complex traits to provide a more confident, comprehensive view of the individual loci that form the genetic basis of the highly polygenic, long-term selection responses for 56-day body weight in the Virginia chicken lines.

genetics↗

bioRxiv2019

Yeast growth responses to environmental perturbations are associated with rewiring of large epistatic networks

The phenotypic effects of genetic polymorphisms often depend on the genetic and environmental context. Here, we explore how polymorphic loci in large interaction networks contribute to complex trait variation and in particular how genetic effects and network topologies are influenced by environmental perturbations. This was done by reanalysing a dataset of >4,000 haploid yeast segregants grown on 20 different media. In total, 130 epistatic loci were associated with growth in at least one environment. The across-environment interaction network defined by these loci explained 69 - 100% of the narrow sense heritability in the individual environments. Environmental changes often resulted in network hubs being connected and disconnected from their interactors, leading to changes in additive effects of individual loci, epistatic effects of multi-locus interactions and the total level of genetic variance in growth. The largest variation in genetic effects across environments was found for epistatic loci that were highly connected network hubs in some environments but not in others. In environments where loci were highly connected, the segregating alleles epistatically suppressed or released genetic effects from their interactors. In environments where they were lowly connected, the same alleles made small or no contributions to growth. Hub-loci thus often serve as modulators, influencing the phenotypic effects of environmentally specific sets of interacting effector genes, rather than being effectors themselves. These findings illustrate the importance of the interplay between large genetic interactions networks and the living environment, both for individual phenotypes and population level metrics of genetic variation.

genetics↗

bioRxiv2018

Genotyping by low-coverage whole-genome sequencing in intercross pedigrees from outbred founders: a cost efficient approach

BackgroundExperimental intercrosses between outbred founder populations are powerful resources for mapping loci contributing to complex traits (Quantitative Trait Loci or QTL). Here, we present an approach and accompanying software for high-resolution genotype imputation in such populations using whole-genome high coverage sequence data on founder individuals ([~]30x) and low coverage sequence data on intercross individuals ([~]0.4x). The method is illustrated in a large F2 pedigree between lines of chickens that have been divergently selected for 40 generations for the same trait (body weight at 8 weeks of age).\n\nResultsDescribed is how hundreds of individuals were whole-genome sequenced in a cost- and time-efficient manner using a Tn5-based library preparation protocol optimized for this application. In total, 7.6M markers segregated in this pedigree and 10.0 to 13.7% were informative for imputing the founder line genotypes within the F0-F2 families. The genotypes imputed from low coverage sequence data were consistent with the founder line genotypes estimated using SNP and microsatellite markers both at individual imputed sites (92%) and across the genome of individual chickens (93%). The resolution of the recombination breakpoints was high with 50% being resolved within <10kb.\n\nConclusionsA method for genotype imputation from low-coverage whole-genome sequencing in outbred intercrosses is described and evaluated. By applying it to an outbred chicken F2 cross it is illustrated that it provides high quality, high-resolution genotypes in a time and cost efficient manner.

genetics↗

bioRxiv2018

On the relationship between high-order linkage disequilibrium and epistasis

A plausible explanation for statistical epistasis revealed in genome wide association analyses is the presence of high order linkage disequilibrium (LD) between the genotyped markers tested for interactions and unobserved functional polymorphisms. Based on findings in experimental data, it has been suggested that high order LD might be a common explanation for statistical epistasis inferred between local polymorphisms in the same genomic region. Here, we empirically evaluate how prevalent high order LD is between local, as well as distal, polymorphisms in the genome. This could provide insights into whether we should account for this when interpreting results from genome wide scans for statistical epistasis. An extensive and strong genome wide high order LD was revealed between pairs of markers on the high density 250k SNP-chip and individual markers revealed by whole genome sequencing in the A. thaliana 1001-genomes collection. The high order LD was found to be more prevalent in smaller populations, but present also in samples including several hundred individuals. An empirical example illustrates that high order LD might be an even greater challenge in cases when the genetic architecture is more complex than the common assumption of bi-allelic loci. The example shows how significant statistical epistasis is detected for a pair of markers in high order LD with a complex multi allelic locus. Overall, our study illustrates the importance of considering also other explanations than functional genetic interactions when genome wide statistical epistasis is detected, in particular when the results are obtained in small populations of inbred individuals.

genetics↗

bioRxiv2017

Explorations of the polygenic genetic architecture of flowering time in the worldwide Arabidopsis thaliana population

As a locally adapted complex trait, flowering time in Arabidopsis thaliana has attracted much attention in genetics. Most studies have, however, focused on contributions by individual loci rather than the joint contributions by the large number of loci in the genetic architecture of flowering time to local and global adaptation. In an earlier study, we reported 46 loci associated with flowering time variation during growth at 10{degrees}C, 16{degrees}C or both in the 1,001-genomes collection of Arabidopsis thaliana accessions. Here, we explore how these loci together contribute to differences among genetically defined, and geographically divided, subpopulations across the native range of this species. Our approach was to define flowering time as a trait, and the measurements at 10 and 16 {degrees}C as two independent measurements of it. This facilitated explorations of the dynamics in the genetic architecture -which loci contribute and their effects- of flowering time across growth temperatures and their potential roles in local and global adaptation. The overall flowering time differences between populations could be explained by subtle changes in allele-frequencies and gradual changes in phenotype due to globally present alleles. More extreme local adaptations were on several occasions due to contributions by regional alleles with relatively large effects. About 2/3 of the 48 evaluated flowering time loci had similar effects on flowering time at 10{degrees}C and 16{degrees}C, while the remaining 1/3 had different effects in the two temperatures, suggesting an important contribution of gene by temperature interactions to this trait. There are also indications that co-evolution of functionally connected alleles in local populations has been important for local adaptation. Overall, this study provides deeper insights to the polygenic genetic basis of flowering time variation in Arabidopsis thaliana across a wide range of ecological habitats.\n\nAuthor SummaryMany genes can affect flowering time in Arabidopsis thaliana, but their contribution to natural flowering time variation in the worldwide population is largely unknown. We explored how 48 loci associated with flowering time, measured at 10{degrees}C and 16{degrees}C, or their difference, for the same wild collected 1,001-genomes Arabidopsis thaliana accessions together contribute to differences among the genetically defined and geographically divided subpopulations from the native species range. The overall flowering time differences among these subpopulations could be explained by the joint small effects of globally present alleles, suggesting an important contribution by polygenic adaptation for this trait. Most alleles with large effects on flowering were present only in some populations, facilitating more extreme local adaptations. Long-range LD was observed between genes in several biological pathways, indicating possible local adaptation via co-evolution of functionally connected polymorphisms. The genetic architecture of flowering time was also found to depend on the growth temperature. Most flowering time loci had similar effects on flowering time measured at 10{degrees}C and 16{degrees}C, but the effects of about 1/3 of them had effects that varied with temperature. Overall, new insights are provided to how the polygenic architecture of flowering time has facilitated its colonisation of a wide range of ecological habitats.

genetics↗

bioRxiv2017

A multi-locus association analysis method integrating phenotype and expression data reveals multiple novel associations to flowering time variation in wild-collected Arabidopsis thaliana

AO_SCPLOWBSTRACTC_SCPLOWWhen a species adapts to a new habitat, selection for the fitness traits often result in a confounding between genome-wide genotype and adaptive alleles. It is a major statistical challenge to detect such adaptive polymorphisms if the confounding is strong, or the effects of the adaptive alleles are weak. Here, we describe a novel approach to dissect polygenic traits in natural populations. First, candidate adaptive loci are identified by screening for loci that are directly associated to the trait or control the expression of genes known to affect it. Then, the multi-locus genetic architecture is inferred using a backward elimination association analysis across all the candidate loci using an adaptive false-discovery rate based threshold. Effects of population stratification are controlled by corrections for population structure in the pre-screening step and by simultaneously testing all candidate loci in the multi-locus model. We illustrate the method by exploring the polygenic basis of an important adaptive trait, flowering time in Arabidopsis thaliana, using public data from the 1,001 genomes project. Our method revealed associations between 33 (29) loci and flowering time at 10 (16){degrees}C in this collection of natural accessions, where standard genome wide association analysis methods detected 5 (3) loci. The 33 (29) loci explained approximately 55 (48)% of the total phenotypic variance of the respective traits. Our work illustrates how the genetic basis of highly polygenic adaptive traits in natural populations can be explored in much greater detail by using new multi-locus mapping approaches taking advantage of prior biological information as well as genome and transcriptome data.

genetics↗

bioRxiv2017

Separating an allele associated with late flowering and slow maturation of Arabidopsis thaliana from population structure

Genome-wide association analysis is a powerful tool to identify genomic loci underlying complex traits. However, the application in natural populations comes with challenges, especially power loss due to population stratification. Here, we introduce a bivariate analysis approach to a GWAS dataset of Arabidopsis thaliana. We demonstrate the efficiency of double-phenotype analysisto uncover hidden genetic loci masked by population structure via a series of simulations. In real data analysis, acommon allele, strongly confounded with population structure, is discovered to be associated with late flowering and slow maturation of the plant. The discovered genetic effect on flowering time is further replicated in independent datasets. Using Mendelian randomization analysis based on summary statistics from our GWAS and expression QTL scans, we predicted and replicated a candidate gene AT1G11560 that potentially causes this association. Further analysis indicates that this locusis co-selected with flowering-time-related genes. The discovered pleiotropic genotypephenotype map provides new insights into understanding the genetic correlation of complex traits.

genetics↗

bioRxiv2017

A complex multi-locus, multi-allelic genetic architecture underlying the long-term selection-response in the Virginia body weight line of chickens

The ability of a population to adapt to changes in their living conditions, whether in nature or captivity, often depends on polymorphisms in multiple genes across the genome. In-depth studies of such polygenic adaptations are difficult in natural populations, but can be approached using the resources provided by artificial selection experiments. Here, we dissect the genetic mechanisms involved in long-term selection responses of the Virginia chicken lines, populations that after 40 generations of divergent selection for 56-day body weight display a nine-fold difference in the selected trait. In the F15 generation of an intercross between the divergent lines, 20 loci explained more than 60% of the additive genetic variance for the selected trait. We focused particularly on seven major QTL and found that only two fine-mapped to single, bi-allelic loci; the other five contained linked loci, multiple alleles or were epistatic. This detailed dissection of the polygenic adaptations in the Virginia lines provides a deeper understanding of genome-wide mechanisms involved in the long-term selection responses. The results illustrate that long-term selection responses, even from populations with a limited genetic diversity, can be polygenic and influenced by a range of genetic mechanisms.

genetics↗