Identification of chromosomal translocation hotspots via scan statistics

GWAS-based population genetic analysis identifies bZIP29 as a heterotic gene in maize

Understanding the role of heterotic genes in contributing to heterosis is essential for advancing hybrid breeding. We analyzed plant height (PH), ear height (EH), and transcriptomic data from a maize hybrid population. Genome-wide association studies (GWASs) revealed that dominance effects of quantitative trait loci (QTLs) play a significant role in hybrid traits and mid-parent heterosis. By integrating GWAS, expression GWAS (eGWAS), and module eGWAS analysis, we prioritized six candidate heterotic genes underlying six QTLs, including one QTL that spans the bZIP29 gene. In the hybrid population, bZIP29 exhibits additive expression and dominance effects for both hybrid traits and mid-parent heterosis, with its favorable allele correlating positively with PH and EH. bZIP29 demonstrates dominance or over-dominance patterns in hybrids derived from crosses between transgenic and wild-type lines, contingent upon its expression. A tsCUT&Tag assay revealed that bZIP29 protein binds directly to a gene regulated by its associated expression QTL (eQTL) and six genes within expression modules governed by its associated module-eQTLs (meQTLs). Regulatory networks involving bZIP29 are more extensive in hybrid subpopulations than in the parental population. This study offers insights into key heterotic genes and networks that underpin the robust growth of hybrid maize.

GWAS and eQTL analyses reveal genetic components influencing the key fiber yield trait lint percentage in upland cotton

Lint percentage is an important component of cotton yield traits and an important economic indicator of cotton production. The initial stage of fiber development is a critical developmental period that affects the lint percentage trait, but the genetic regulation of the initial stage of fiber development needs to be resolved. In this study, we used a genomewide association study (GWAS) to identify 11 quantitative trait loci (QTLs) related to lint percentage and identified a total of 13 859 expression QTL (eQTLs) through transcriptome sequencing of 312 upland cotton accessions. Candidate genes for improving the lint percentage trait were identified through transcriptome-wide association study (TWAS), colocalization analysis, and differentially expressed gene analysis. We located nine candidate genes through the TWAS, and prioritized two key candidate genes (Ghir_A12G025980 and Ghir_A12G025990) related to lint percentage through colocalization and differential expression analysis. We showed that two eQTL hotspots (Hot26 and Hot28) synergistically participate in regulating the biological pathways of fiber initiation and development. Additionally, we unlocked the potential of genomic variants in improving the lint percentage by aggregating favorable alleles in accessions. New accessions suitable for improving lint percentage were excavated.

Regulatory networks of coresident subgenomes during rapid fiber cell elongation in upland cotton

Cotton, an intriguing plant species shaped by polyploidization, evolution, and domestication, holds particular interest due to the complex mechanisms governing fiber traits across its two subgenomes. However, the regulatory elements or transcriptional networks between subgenomes during fiber elongation remain to be fully clarified. Here, we analyzed 1462 cotton fiber samples to reconstruct the gene-expression regulatory networks that influence fiber cell elongation. Inter-subgenome expression quantitative trait loci (eQTLs) largely dictate gene transcription, with a notable tendency for the D subgenome to regulate A-subgenome eGenes. This regulation reveals synchronized homoeologous gene expression driven by co-localized eQTLs and divergent patterns that diminish genetic correlations, thus leading to preferential expression in the A and D subgenomes. Hotspot456 emerged as a key regulator of fiber initiation and elongation, and artificial selection of trans-eQTLs in hotspot456 that positively regulate KCS1 has facilitated cell elongation. Experiments designed to clarify the roles of trans-eQTLs in improved fiber breeding confirmed the inhibition of GhTOL9 by a specific trans-eQTL via GhWRKY28, which negatively affects fiber elongation. We propose a model in which the GhWRKY28-GhTOL9 module regulates this process through the ESCRT (endosomal sorting complex required for transport) pathway. This research significantly advances our understanding of cotton's evolutionary and domestication processes and the intricate regulatory mechanisms that underlie significant plant traits.

Landscape of structural variants reveals insights for local adaptations in the Asian corn borer

Capturing the genetic diversity of different wild populations is crucial for unraveling the mechanisms of adaptation and establishing links between genome evolution and local adaptation. The Asian corn borer (ACB) moth has undergone natural selection during its adaptative evolution. However, structural variants (SVs), which play significant roles in these adaptation processes, have not been previously identified. Here, we constructed a multi-assembly graph pan-genome to highlight the importance of SVs in local adaptation. Our analysis revealed that the graph pan-genome contained 176.60 Mb (∼37.33%) of unique sequences. Subsequently, we performed an analysis of expression quantitative trait loci (QTLs) to explore the impact of SVs on gene expression regulation. Notably, through QTL mapping analysis, we identified the FTZ-F1 gene as a potential candidate gene associated with the traits of larval development rate. In sum, we explored the impact of SVs on the local adaptation of pests, therefore facilitating accelerated pest management strategies.

Structural variation reshapes population gene expression and trait variation in 2,105 Brassica napus accessions

Although individual genomic structural variants (SVs) are known to influence gene expression and trait variation, the extent and scale of SV impact across a species remain unknown. In the present study, we constructed a reference library of 334,461 SVs from genome assemblies of 16 representative morphotypes of neopolyploid Brassica napus accessions and detected 258,865 SVs in 2,105 resequenced genomes. Coupling with 5 tissue population transcriptomes, we uncovered 285,976 SV-expression quantitative trait loci (eQTLs) that associate with altered expression of 73,580 genes. We developed a pipeline for the high-throughput joint analyses of SV-genome-wide association studies (SV-GWASs) and transcriptome-wide association studies of phenomic data, eQTLs and eQTL-GWAS colocalization, and identified 726 SV-gene expression-trait variation associations, some of which were verified by transgenics. The pervasive SV impact on how SV reshapes trait variation was demonstrated with the glucosinolate biosynthesis and transport pathway. The study highlighting the impact of genome-wide and species-scale SVs provides a powerful methodological strategy and valuable resources for studying evolution, gene discovery and breeding.

Obesity increases genomic instability at DNA repeat-mediated endogenous mutation hotspots

Obesity is associated with increased cancer risk, yet the underlying mechanisms remain elusive. Obesity-associated cancers involve disruptions in metabolic and cellular pathways, which can lead to genomic instability. Repetitive DNA sequences capable of adopting alternative DNA structures (e.g., H-DNA) stimulate mutations and are enriched at mutation hotspots in human cancer genomes. However, it is not known if obesity impacts DNA repeat-mediated endogenous mutation hotspots. We address this gap by measuring mutation frequencies in obese and normal-weight transgenic reporter mice carrying either a control human B-DNA- or an H-DNA-forming sequence (from a translocation hotspot in c-MYC in Burkitt lymphoma). Here, we discover that H-DNA-induced DNA damage and mutations are elevated in a tissue-specific manner, and DNA repair efficiency is reduced in obese mice compared to those on the control diet. These findings elucidate the impact of obesity on cancer-associated endogenous mutation hotspots, providing mechanistic insight into the link between obesity and cancer.

SIV infection and ARV treatment reshape the transcriptional and epigenetic profile of naïve and memory T cells in vivo

Human and simian immunodeficiency viruses (HIV and SIV) are lentiviruses that reverse transcribe their RNA genome with subsequent integration into the genome of the target cell. How progressive infection and administration of antiretrovirals (ARVs) longitudinally influence the transcriptomic and epigenetic landscape of particular T cell subsets, and how these may influence the genetic location of integration are unclear. Here, we use RNAseq and ATACseq to study the transcriptomics and epigenetic landscape of longitudinally sampled naïve and memory CD4+ and CD8+ T cells in two species of non-human primates prior to SIV infection, during chronic SIV infection, and after administration of ARVs. We find that SIV infection leads to significant alteration to the transcriptomic profile of all T cell subsets that are only partially reversed by administration of ARVs. Epigenetic changes were more apparent in animals with longer periods of untreated SIV infection and correlated well with changes in corresponding gene expression. Known SIV integration sites did not vary due to SIV status but did contain more open chromatin in rhesus macaque memory T cells, and the expression of proteasome-related genes at the pre-SIV timepoint correlated with subsequent viremia.IMPORTANCEChronic inflammation during progressive human and simian immunodeficiency virus (HIV and SIV) infections leads to significant co-morbidities in infected individuals with significant consequences. Antiretroviral (ARV)-treated individuals also manifest increased levels of inflammation which are associated with increased mortalities. These data will help guide rational development of modalities to reduce inflammation observed in people living with HIV and suggest mechanisms underlying lentiviral integration site preferences.

Leaf morphology related genes revealed by integrating Pan-transcriptome, GWAS and eQTL analyses in a Liriodendron population

Leaf plays an indispensable role in plant development and growth. Although many known genes related to leaf morphology development have been identified, elucidating the complex genetic basis of leaf morphological traits remains a challenge. Liriodendron plants are common ornamental trees due to their unique leaf shapes, while the molecular mechanism underlying Liriodendron leaf morphogenesis has remained unknown. Herein, we firstly constructed a population-level pan-transcriptome of Liriodendron from 81 accessions to explore the expression presence or absence variations (ePAVs), global expression differences at the population level, as well as differentially expressed genes (DEGs) between the Liriodendron chinense and Liriodendron tulipifera accessions. Subsequently, we integrated a genome-wide association study (GWAS), expression quantitative trait loci (eQTL), and transcriptome-wide association study (TWAS) to identify candidate genes related to leaf morphology. Through GWAS analysis, we identified 18 and 17 significant allelic loci in the leaf size and leaf shape modules, respectively. In addition, we discerned 16 candidate genes in relation to leaf morphological traits via TWAS. Further, integrating the co-localization results of GWAS and eQTL, we determined two regulatory hotspot regions, hot88 and hot758, related to leaf size and leaf shape, respectively. Finally, co-expression analysis, eQTL, and linkage mapping together demonstrated that Lchi_4g10795 regulate their own expression levels through cis-eQTL to affect the expression of downstream genes and cooperatively participate in the development of Liriodendron leaf morphology. These findings will improve our understanding of the molecular regulatory mechanism of Liriodendron leaf morphogenesis and will also accelerate molecular breeding of Liriodendron.

Regulatory controls of duplicated gene expression during fiber development in allotetraploid cotton

Polyploidy complicates transcriptional regulation and increases phenotypic diversity in organisms. The dynamics of genetic regulation of gene expression between coresident subgenomes in polyploids remains to be understood. Here we document the genetic regulation of fiber development in allotetraploid cotton Gossypium hirsutum by sequencing 376 genomes and 2,215 time-series transcriptomes. We characterize 1,258 genes comprising 36 genetic modules that control staged fiber development and uncover genetic components governing their partitioned expression relative to subgenomic duplicated genes (homoeologs). Only about 30% of fiber quality-related homoeologs show phenotypically favorable allele aggregation in cultivars, highlighting the potential for subgenome additivity in fiber improvement. We envision a genome-enabled breeding strategy, with particular attention to 48 favorable alleles related to fiber phenotypes that have been subjected to purifying selection during domestication. Our work delineates the dynamics of gene regulation during fiber development and highlights the potential of subgenomic coordination underpinning phenotypes in polyploid plants.

Integration of eQTL and machine learning to dissect causal genes with pleiotropic effects in genetic regulation networks of seed cotton yield

The dissection of a gene regulatory network (GRN) that complements the genome-wide association study (GWAS) locus and the crosstalk underlying multiple agronomical traits remains a major challenge. In this study, we generate 558 transcriptional profiles of lint-bearing ovules at one day post-anthesis from a selective core cotton germplasm, from which 12,207 expression quantitative trait loci (eQTLs) are identified. Sixty-six known phenotypic GWAS loci are colocalized with 1,090 eQTLs, forming 38 functional GRNs associated predominantly with seed yield. Of the eGenes, 34 exhibit pleiotropic effects. Combining the eQTLs within the seed yield GRNs significantly increases the portion of narrow-sense heritability. The extreme gradient boosting (XGBoost) machine learning approach is applied to predict seed cotton yield phenotypes on the basis of gene expression. Top-ranking eGenes (NF-YB3, FLA2, and GRDP1) derived with pleiotropic effects on yield traits are validated, along with their potential roles by correlation analysis, domestication selection analysis, and transgenic plants.

Genomic innovation and regulatory rewiring during evolution of the cotton genus Gossypium

Phenotypic diversity and evolutionary innovation ultimately trace to variation in genomic sequence and rewiring of regulatory networks. Here, we constructed a pan-genome of the Gossypium genus using ten representative diploid genomes. We document the genomic evolutionary history and the impact of lineage-specific transposon amplification on differential genome composition. The pan-3D genome reveals evolutionary connections between transposon-driven genome size variation and both higher-order chromatin structure reorganization and the rewiring of chromatin interactome. We linked changes in chromatin structures to phenotypic differences in cotton fiber and identified regulatory variations that decode the genetic basis of fiber length, the latter enabled by sequencing 1,005 transcriptomes during fiber development. We showcase how pan-genomic, pan-3D genomic and genetic regulatory data serve as a resource for delineating the evolutionary basis of spinnable cotton fiber. Our work provides insights into the evolution of genome organization and regulation and will inform cotton improvement by enabling regulome-based approaches.

eQTLs play critical roles in regulating gene expression and identifying key regulators in rice

The regulation of gene expression plays an essential role in both the phenotype and adaptation of plants. Transcriptome sequencing enables simultaneous identification of exonic variants and quantification of gene expression. Here, we sequenced the leaf transcriptomes of 287 rice accessions from around the world and obtained a total of 177 853 high-quality single nucleotide polymorphisms after filtering. Genome-wide association study identified 44 354 expression quantitative trait loci (eQTLs), which regulate the expression of 13 201 genes, as well as 17 local eQTL hotspots and 96 distant eQTL hotspots. Furthermore, a transcriptome-wide association study screened 21 candidate genes for starch content in the flag leaves at the heading stage. HS002 was identified as a significant distant eQTL hotspot with five downstream genes enriched for diterpene antitoxin synthesis. Co-expression analysis, eQTL analysis, and linkage mapping together demonstrated that bHLH026 acts as a key regulator to activate the expression of downstream genes. The transgenic assay revealed that bHLH026 is an important regulator of diterpenoid antitoxin synthesis and enhances the disease resistance of rice. These findings improve our knowledge of the regulatory mechanisms of gene expression variation and complex regulatory networks of the rice genome and will facilitate genetic improvement of cultivated rice varieties.

Population-level transcriptomes reveal gene expression and splicing underlying cadmium accumulation in barley

Genetic variation is an important determinant of gene transcription, which in turn contributes to functional and phenotypic diversity. Identification of the genetic variants controlling gene expression and alternative splicing in crops responding to cadmium (Cd), an important issue for food safety and human health, is of great value to improve our understanding of Cd accumulation-related genes. Here we report an in-depth survey of population-level transcriptome variation of barley (Hordeum vulgare) core accessions under Cd exposure. We reveal marked transcriptomic changes in response to Cd exposure, and these are largely independent of tissues. A genome-wide association study (GWAS) revealed 59 498 expression quantitative trait loci (eQTLs) and 23 854 splicing quantitative trait loci (sQTLs), leading to a complex network that covers 66.6% of the expressed genes, including 68 metal transporter genes. On average, 41.0% of sQTLs overlapped with eQTLs across different tissues, indicating that these two dimensions of transcript variation are largely independent. Moreover, we found that 34.5% of GWAS QTLs that underlie 10 Cd accumulation traits in barley are co-localized with eQTLs and sQTLs, which could imply a mechanistic role of different genetic variants affecting gene expression and alternative splicing in these traits. This study highlights the role of distal and proximal genetic effects on gene expression, splicing, and phenotypic plasticity. We anticipate that our results on the genetic control of expression and splicing underlying Cd accumulation provide a bridge to better understand genetic variation and phenotypic diversity to elucidate the mechanisms underlying Cd accumulation in plants.

DNA replication timing directly regulates the frequency of oncogenic chromosomal translocations

Chromosomal translocations result from the joining of DNA double-strand breaks (DSBs) and frequently cause cancer. However, the steps linking DSB formation to DSB ligation remain undeciphered. We report that DNA replication timing (RT) directly regulates lymphomagenic Myc translocations during antibody maturation in B cells downstream of DSBs and independently of DSB frequency. Depletion of minichromosome maintenance complexes alters replication origin activity, decreases translocations, and deregulates global RT. Ablating a single origin at Myc causes an early-to-late RT switch, loss of translocations, and reduced proximity with the immunoglobulin heavy chain ( Igh ) gene, its major translocation partner. These phenotypes were reversed by restoring early RT. Disruption of early RT also reduced tumorigenic translocations in human leukemic cells. Thus, RT constitutes a general mechanism in translocation biogenesis linking DSB formation to DSB ligation.

Integration of eQTL Analysis and GWAS Highlights Regulation Networks in Cotton under Stress Condition

The genus Gossypium is one of the most economically important crops in the world. Here, we used RNA-seq to quantify gene expression in a collection of G. arboreum seedlings and performed eGWAS on 28,382 expressed genes. We identified a total of 30,089 eQTLs in 10,485 genes, of which >90% were trans-regulate target genes. Using luciferase assays, we confirmed that different cis-eQTL haplotypes could affect promoter activity. We found ~6600 genes associated with ~1300 eQTL hotspots. Moreover, hotspot 309 regulates the expression of 325 genes with roles in stem length, fresh weight, seed germination rate, and genes related to cell wall biosynthesis and salt stress. Transcriptome-wide association study (TWAS) identified 19 candidate genes associated with the cotton growth and salt stress response. The variation in gene expression across the population played an essential role in population differentiation. Only a small number of the differentially expressed genes between South China, the Yangtze River region, and the Yellow River region sites were located in different chromosomal regions. The eQTLs found across the duplicated gene pairs showed conservative cis- or trans- regulation and that the expression levels of gene pairs were correlated. This study provides new insights into the evolution of gene expression regulation in cotton, and identifies eQTLs in stress-related genes for use in breeding improved cotton varieties.

A combination of genome-wide and transcriptome-wide association studies reveals genetic elements leading to male sterility during high temperature stress in cotton

Global warming has reduced the productivity of many field-grown crops, as the effects of high temperatures can lead to male sterility in such plants. Genetic regulation of the high temperature (HT) response in the major crop cotton is poorly understood. We determined the functionality and transcriptomes of the anthers of 218 cotton accessions grown under HT stress. By analyzing transcriptome divergence and implementing a genome-wide association study (GWAS), we identified three thermal tolerance associated loci which contained 75 protein coding genes and 27 long noncoding RNAs, and provided expression quantitative trait loci (eQTLs) for 13 132 transcripts. A transcriptome-wide association study (TWAS) confirmed six causal elements for the HT response (three genes overlapped with the GWAS results) which are involved in protein kinase activity. The most susceptible gene, GhHRK1, was confirmed to be a previously uncharacterized negative regulator of the HT response in both cotton and Arabidopsis. These functional variants provide a new understanding of the genetic basis for HT tolerance in male reproductive organs.

Genome of Solanum pimpinellifolium provides insights into structural variants during tomato breeding

Solanum pimpinellifolium (SP) is the wild progenitor of cultivated tomato. Because of its remarkable stress tolerance and intense flavor, SP has been used as an important germplasm donor in modern tomato breeding. Here, we present a high-quality chromosome-scale genome sequence of SP LA2093. Genome comparison identifies more than 92,000 structural variants (SVs) between LA2093 and the modern cultivar, Heinz 1706. Genotyping these SVs in ~600 representative tomato accessions identifies alleles under selection during tomato domestication, improvement and modern breeding, and discovers numerous SVs overlapping genes known to regulate important breeding traits such as fruit weight and lycopene content. Expression quantitative trait locus (eQTL) analysis detects hotspots harboring master regulators controlling important fruit quality traits, including cuticular wax accumulation and flavonoid biosynthesis, and SVs contributing to these complex regulatory networks. The LA2093 genome sequence and the identified SVs provide rich resources for future research and biodiversity-based breeding.

Solanum pimpinellifolium (SP) is the progenitor of cultivated tomato and an important germplasm. Here, the authors assemble SP genome, identify structural variants (SVs) by comparing with modern cultivar, reveal SVs associated with important breeding traits, and detect SVs harboring master regulators of fruit quality traits.

Combined GWAS and eQTL analysis uncovers a genetic regulatory network orchestrating the initiation of secondary cell wall development in cotton

The cotton fibre serves as a valuable experimental system to study cell wall synthesis in plants, but our understanding of the genetic regulation of this process during fibre development remains limited. We performed a genome-wide association study (GWAS) and identified 28 genetic loci associated with fibre quality in allotetraploid cotton. To investigate the regulatory roles of these loci, we sequenced fibre transcriptomes of 251 cotton accessions and identified 15 330 expression quantitative trait loci (eQTL). Analysis of local eQTL and GWAS data prioritised 13 likely causal genes for differential fibre quality in a transcriptome-wide association study (TWAS). Characterisation of distal eQTL revealed unequal genetic regulation patterns between two subgenomes, highlighted by an eQTL hotspot (Hot216) that established a genome-wide genetic network regulating the expression of 962 genes. The primary regulatory role of Hot216, and specifically the gene encoding a KIP-related protein, was found to be the transcriptional regulation of genes responsible for cell wall synthesis, which contributes to fibre length by modulating the developmental transition from rapid cell elongation to secondary cell wall synthesis. This study uncovered the genetic regulation of fibre-cell development and revealed the molecular basis of the temporal modulation of secondary cell wall synthesis during plant cell elongation.

Genome-wide analysis of expression quantitative trait loci (eQTLs) reveals the regulatory architecture of gene expression variation in the storage roots of sweet potato

Dissecting the genetic regulation of gene expression is critical for understanding phenotypic variation and species evolution. However, our understanding of the transcriptional variability in sweet potato remains limited. Here, we analyzed two publicly available datasets to explore the landscape of transcriptomic variations and its genetic basis in the storage roots of sweet potato. The comprehensive analysis identified a total of 724,438 high-confidence single nucleotide polymorphisms (SNPs) and 26,026 expressed genes. Expression quantitative trait locus (eQTL) analysis revealed 4408 eQTLs regulating the expression of 3646 genes, including 2261 local eQTLs and 2147 distant eQTLs. Two distant eQTL hotspots were found with target genes significantly enriched in specific functional classifications. By combining the information from regulatory network analyses, eQTLs and association mapping, we found that IbMYB1-2 acts as a master regulator and is the major gene responsible for the activation of anthocyanin biosynthesis in the storage roots of sweet potato. Our study provides the first insight into the genetic architecture of genome-wide expression variation in sweet potato and can be used to investigate the potential effects of genetic variants on key agronomic traits in sweet potato.

RNA sequencing provides insights into the evolution of lettuce and the regulation of flavonoid biosynthesis

Different horticultural types of lettuce exhibit tremendous morphological variation. However, the molecular basis for domestication and divergence among the different horticultural types of lettuce remains unknown. Here, we report the RNA sequencing of 240 lettuce accessions sampled from the major horticultural types and wild relatives, generating 1.1 million single-nucleotide polymorphisms (SNPs). Demographic modeling indicates that there was a single domestication event for lettuce. We identify a list of regions as putative selective sweeps that occurred during domestication and divergence, respectively. Genome-wide association studies (GWAS) identify 5311 expression quantitative trait loci (eQTL) regulating the expression of 4105 genes, including nine eQTLs regulating genes associated with flavonoid biosynthesis. GWAS for leaf color detects six candidate loci responsible for the variation of anthocyanins in lettuce leaves. Our study provides a comprehensive understanding of the domestication and the accumulation of anthocyanins in lettuce, and will facilitate the breeding of cultivars with improved nutritional value.

Distant eQTLs and Non-coding Sequences Play Critical Roles in Regulating Gene Expression and Quantitative Trait Variation in Maize

A detailed understanding of genetic architecture of mRNA expression by millions of genetic variants is important for studying quantitative trait variation. In this study, we identified 1.25M SNPs with a minor allele frequency greater than 0.05 by combining reduced genome sequencing (GBS), high-density array technologies (600K), and previous deep RNA-sequencing data from 368 diverse inbred lines of maize. The balanced allelic frequencies and distributions in a relatively large and diverse natural panel helped to identify expression quantitative trait loci (eQTLs) associated with more than 18 000 genes (63.4% of tested genes). We found that distant eQTLs were more frequent (∼75% of all eQTLs) across the whole genome. Thirteen novel associated loci affecting maize kernel oil concentration were identified using the new dataset, among which one intergenic locus affected the kernel oil variation by controlling expression of three other known oil-related genes. Altogether, this study provides resources for expanding our understanding of cellular regulatory mechanisms of transcriptome variation and the landscape of functional variants within the maize genome, thereby enhancing the understanding of quantitative variations.

HIV-1 integration landscape during latent and active infection

The barrier to curing HIV-1 is thought to reside primarily in CD4(+) T cells containing silent proviruses. To characterize these latently infected cells, we studied the integration profile of HIV-1 in viremic progressors, individuals receiving antiretroviral therapy, and viremic controllers. Clonally expanded T cells represented the majority of all integrations and increased during therapy. However, none of the 75 expanded T cell clones assayed contained intact virus. In contrast, the cells bearing single integration events decreased in frequency over time on therapy, and the surviving cells were enriched for HIV-1 integration in silent regions of the genome. Finally, there was a strong preference for integration into, or in close proximity to, Alu repeats, which were also enriched in local hotspots for integration. The data indicate that dividing clonally expanded T cells contain defective proviruses and that the replication-competent reservoir is primarily found in CD4(+) T cells that remain relatively quiescent.