Functional partitioning of transcriptional regulators by patterned charge blocks.

Components of transcriptional machinery are selectively partitioned into specific condensates, often mediated by protein disorder, yet we know little about how this specificity is achieved. Here, we show that condensates composed of the intrinsically disordered region (IDR) of MED1 selectively partition RNA polymerase II together with its positive allosteric regulators while excluding negative regulators. This selective compartmentalization is sufficient to activate transcription and is required for gene activation during a cell-state transition. The IDRs of partitioned proteins are necessary and sufficient for selective compartmentalization and require alternating blocks of charged amino acids. Disrupting this charge pattern prevents partitioning, whereas adding the pattern to proteins promotes partitioning with functional consequences for gene activation. IDRs with similar patterned charge blocks show similar partitioning and function. These findings demonstrate that disorder-mediated interactions can selectively compartmentalize specific functionally related proteins from a complex mixture of biomolecules, leading to regulation of a biochemical pathway.

m6A modification negatively regulates translation by switching mRNA from polysome to P-body via IGF2BP3.

In the cytoplasm, mRNAs are dynamically partitioned into translating and non-translating pools, but the mechanism for this regulation has largely remained elusive. Here, we report that m6A regulates mRNA partitioning between polysome and P-body where a pool of non-translating mRNAs resides. By quantifying the m6A level of polysomal and cytoplasmic mRNAs with m6A-LAIC-seq and m6A-LC-MS/MS in HeLa cells, we observed that polysome-associated mRNAs are hypo-m6A-methylated, whereas those enriched in P-body are hyper-m6A-methylated. Downregulation of the m6A writer METTL14 enhances translation by switching originally hyper-m6A-modified mRNAs from P-body to polysome. Conversely, by proteomic analysis, we identify a specific m6A reader IGF2BP3 enriched in P-body, and via knockdown and molecular tethering assays, we demonstrate that IGF2BP3 is both necessary and sufficient to switch target mRNAs from polysome to P-body. These findings suggest a model for the dynamic regulation of mRNA partitioning between the translating and non-translating pools in an m6A-dependent manner.

Checkpoint-mediated DNA polymerase ε exonuclease activity curbing counteracts resection-driven fork collapse.

DNA polymerase ε (Polε) carries out high-fidelity leading strand synthesis owing to its exonuclease activity. Polε polymerase and exonuclease activities are balanced, because of partitioning of nascent DNA strands between catalytic sites, so that net resection occurs when synthesis is impaired. In vivo, DNA synthesis stalling activates replication checkpoint kinases, which act to preserve the functional integrity of replication forks. We show that stalled Polε drives nascent strand resection causing fork functional collapse, averted via checkpoint-dependent phosphorylation. Polε catalytic subunit Pol2 is phosphorylated on serine 430, influencing partitioning between polymerase and exonuclease active sites. A phosphormimetic S430D change reduces exonucleolysis in vitro and counteracts fork collapse. Conversely, non-phosphorylatable pol2-S430A expression causes resection-driven stressed fork defects. Our findings reveal that checkpoint kinases switch Polε to an exonuclease-safe mode preventing nascent strand resection and stabilizing stalled replication forks. Elective partitioning suppression has implications for the diverse Polε roles in genome integrity maintenance.

Plasmid partitioning driven by collective migration of ParA between nucleoid lobes.

The ParABS system is crucial for the faithful segregation and inheritance of many bacterial chromosomes and low-copy-number plasmids. However, despite extensive research, the spatiotemporal dynamics of the ATPase ParA and its connection to the dynamics and positioning of the ParB-coated cargo have remained unclear. In this study, we utilize high-throughput imaging, quantitative data analysis, and computational modeling to explore the in vivo dynamics of ParA and its interaction with ParB-coated plasmids and the nucleoid. As previously observed, we find that F-plasmid ParA undergoes collective migrations ("flips") between cell halves multiple times per cell cycle. We reveal that a constricting nucleoid is required for these migrations and that they are triggered by a plasmid crossing into the cell half with greater ParA. Using simulations, we show that these dynamics can be explained by the combination of nucleoid constriction and cooperative ParA binding to the DNA, in line with the behavior of other ParA proteins. We further show that these ParA flips act to equally partition plasmids between the two lobes of the constricted nucleoid and are therefore important for plasmid stability, especially in fast growth conditions for which the nucleoid constricts early in the cell cycle. Overall, our work identifies a second mode of action of the ParABS system and deepens our understanding of how this important segregation system functions.

Protein structure and aggregation: a marriage of necessity ruled by aggregation gatekeepers.

Protein aggregation propensity is a pervasive and seemingly inescapable property of proteomes. Strikingly, a significant fraction of the proteome is supersaturated, meaning that, for these proteins, their native conformation is less stable than the aggregated state. Maintaining the integrity of a proteome under such conditions is precarious and requires energy-consuming proteostatic regulation. Why then is aggregation propensity maintained at such high levels over long evolutionary timescales? Here, we argue that the conformational stability of the native and aggregated states are correlated thermodynamically and that codon usage strengthens this correlation. As a result, the folding of stable proteins requires kinetic control to avoid aggregation, provided by aggregation gatekeepers. These unique residues are evolutionarily selected to kinetically favor native folding, either on their own or by coopting chaperones.

Low membrane fluidity triggers lipid phase separation and protein segregation in living bacteria.

All living organisms adapt their membrane lipid composition in response to changes in their environment or diet. These conserved membrane-adaptive processes have been studied extensively. However, key concepts of membrane biology linked to regulation of lipid composition including homeoviscous adaptation maintaining stable levels of membrane fluidity, and gel-fluid phase separation resulting in domain formation, heavily rely upon in vitro studies with model membranes or lipid extracts. Using the bacterial model organisms Escherichia coli and Bacillus subtilis, we now show that inadequate in vivo membrane fluidity interferes with essential complex cellular processes including cytokinesis, envelope expansion, chromosome replication/segregation and maintenance of membrane potential. Furthermore, we demonstrate that very low membrane fluidity is indeed capable of triggering large-scale lipid phase separation and protein segregation in intact, protein-crowded membranes of living cells; a process that coincides with the minimal level of fluidity capable of supporting growth. Importantly, the in vivo lipid phase separation is not associated with a breakdown of the membrane diffusion barrier function, thus explaining why the phase separation process induced by low fluidity is biologically reversible.

Significance tests for R2 of out-of-sample prediction using polygenic scores.

The coefficient of determination (R2) is a well-established measure to indicate the predictive ability of polygenic scores (PGSs). However, the sampling variance of R2 is rarely considered so that 95% confidence intervals (CI) are not usually reported. Moreover, when comparisons are made between PGSs based on different discovery samples, the sampling covariance of R2 is required to test the difference between them. Here, we show how to estimate the variance and covariance of R2 values to assess the 95% CI and p value of the R2 difference. We apply this approach to real data calculating PGSs in 28,880 European participants derived from UK Biobank (UKBB) and Biobank Japan (BBJ) GWAS summary statistics for cholesterol and BMI. We quantify the significantly higher predictive ability of UKBB PGSs compared to BBJ PGSs (p value 7.6e-31 for cholesterol and 1.4e-50 for BMI). A joint model of UKBB and BBJ PGSs significantly improves the predictive ability, compared to a model of UKBB PGS only (p value 3.5e-05 for cholesterol and 1.3e-28 for BMI). We also show that the predictive ability of regulatory SNPs is significantly enriched over non-regulatory SNPs for cholesterol (p value 8.9e-26 for UKBB and 3.8e-17 for BBJ). We suggest that the proposed approach (available in R package r2redux) should be used to test the statistical significance of difference between pairs of PGSs, which may help to draw a correct conclusion about the comparative predictive ability of PGSs.

Anion elements incorporation into corals skeletons: Experimental approach for biomineralization and paleo-proxies.

The elemental composition of coral skeletons provides important information for palaeoceanographic reconstructions and coral biomineralization. Partition of anions and their stable isotopes in coral skeleton enables the reconstruction of past seawater carbonate chemistry, paleo-CO2, and past climates. Here, we investigated the partition of B, S, As, Br, I, and Mo into the skeletons of two corals, Acropora cervicornis and Pocillopora damicornis, as a function of calcium and carbonate concentrations.* Anion-to-calcium ratio in the corals (An/CaCoral) were correlated with the equivalent ratios in the culturing seawater (An/CO32-SW). Negative intercepts of these relationships suggest a higher CO32- concentration in the coral extracellular calcifying fluid (ECF) relative to seawater, from which the skeleton precipitates. The enrichment factor of CO32- at the ECF was 2.5 for A. cervicornis and 1.9 for P. damicornis, consistent with their relative calcification rates. The CO32-ECF concentrations thus calculated are similar to those proposed by previous studies based on B/Ca coupled with δ11B, as well as by direct measurements using microsensors and fluorescent dyes. Rayleigh fractionation modeling demonstrates a uniform Ca utilization at various CaSW concentrations, providing further evidence that coral calcification occurs directly from a semiclosed seawater reservoir as reported previously. The partition coefficients reported in this study for B, S, As, Br, I, and Mo open up wide possibilities for past ocean chemistry reconstructions based on Br having long residence time (~160 Ma) in the ocean. Other elements like S, Mo, B, as well as pCO2 may also be calculated based on these elements in fossil coral.

Microtubule-mitochondrial attachment facilitates cell division symmetry and mitochondrial partitioning in fission yeast.

Association with microtubules inhibits the fission of mitochondria in Schizosaccharomyces pombe. Here, we show that this attachment of mitochondria to microtubules is an important cell-intrinsic factor in determining cell division symmetry. By comparing mutant cells that exhibited enhanced attachment and no attachment of mitochondria to microtubules (Dnm1Δ and Mmb1Δ, respectively), we show that microtubules in these mutants displayed aberrant dynamics compared to wild-type cells, which resulted in errors in nuclear positioning. This translated to cell division asymmetry in a significant proportion of both Dnm1Δ and Mmb1Δ cells. Asymmetric division in Dnm1Δ and Mmb1Δ cells resulted in unequal distribution of mitochondria, with the daughter cell that received more mitochondria growing faster than the other daughter cell. Taken together, we show the existence of homeostatic feedback controls between mitochondria and microtubules in fission yeast, which directly influence mitochondrial partitioning and, thereby, cell growth. This article has an associated First Person interview with the first author of the paper.

Tree-based subgroup discovery using electronic health record data: heterogeneity of treatment effects for DTG-containing therapies.

The rich longitudinal individual level data available from electronic health records (EHRs) can be used to examine treatment effect heterogeneity. However, estimating treatment effects using EHR data poses several challenges, including time-varying confounding, repeated and temporally non-aligned measurements of covariates, treatment assignments and outcomes, and loss-to-follow-up due to dropout. Here, we develop the subgroup discovery for longitudinal data algorithm, a tree-based algorithm for discovering subgroups with heterogeneous treatment effects using longitudinal data by combining the generalized interaction tree algorithm, a general data-driven method for subgroup discovery, with longitudinal targeted maximum likelihood estimation. We apply the algorithm to EHR data to discover subgroups of people living with human immunodeficiency virus who are at higher risk of weight gain when receiving dolutegravir (DTG)-containing antiretroviral therapies (ARTs) versus when receiving non-DTG-containing ARTs.

Distributed multi-objective optimization for SNP-SNP interaction detection.

The detection of complex interactions between single nucleotide polymorphisms (SNPs) plays a vital role in genome-wide association analysis (GWAS). The multi-objective evolutionary algorithm is a promising technique for SNP-SNP interaction detection. However, as the scale of SNP data further increases, the exponentially growing search space gradually becomes the dominant factor, causing evolutionary algorithm (EA)-based approaches to fall into local optima. In addition, multi-objective genetic operations consume significant amounts of time and computational resources. To this end, this study proposes a distributed multi-objective evolutionary framework (DM-EF) to identify SNP-SNP interactions on large-scale datasets. DM-EF first partitions the entire search space into several subspaces based on a space-partitioning strategy, which is nondestructive because it guarantees that each feasible solution is assigned to a specific subspace. Thereafter, each subspace is optimized using a multi-objective EA optimizer, and all subspaces are optimized in parallel. A decomposition-based multi-objective firework optimizer (DCFWA) with several problem-guided operators was designed. Finally, the final output is selected from the Pareto-optimal solutions in the historical search of each subspace. DM-EF avoids the preference for a single objective function, handles the heavy computational burden, and enhances the diversity of the population to avoid local optima. Notably, DM-EF is load-balanced and scalable because it can flexibly partition the space according to the number of available computational nodes and problem size. Experiments on both artificial and real-world datasets demonstrate that the proposed method significantly improves the search speed and accuracy.

Alx3 deficiency disrupts energy homeostasis, alters body composition, and impairs hypothalamic regulation of food intake.

The coordination of food intake, energy storage, and expenditure involves complex interactions between hypothalamic neurons and peripheral tissues including pancreatic islets, adipocytes, muscle, and liver. Previous research shows that deficiency of the transcription factor Alx3 alters pancreatic islet-dependent glucose homeostasis. In this study we carried out a comprehensive assessment of metabolic alterations in Alx3 deficiency. We report that Alx3-deficient mice exhibit decreased food intake without changes in body weight, along with reduced energy expenditure and altered respiratory exchange ratio. Magnetic resonance imaging reveals increased adiposity and decreased muscle mass, which was associated with markers of motor and sympathetic denervation. By contrast, Alx3-deficient mice on a high-fat diet show attenuated weight gain and improved insulin sensitivity, compared to control mice. Gene expression analysis demonstrates altered lipogenic and lipolytic gene profiles. In wild type mice Alx3 is expressed in hypothalamic arcuate nucleus neurons, but not in major peripheral metabolic organs. Functional diffusion-weighted magnetic resonance imaging reveals selective hypothalamic responses to fasting in the arcuate nucleus of Alx3-deficient mice. Additionally, altered expression of proopiomelanocortin and melanocortin-3 receptor mRNA in the hypothalamus suggests impaired regulation of feeding behavior. This study highlights the crucial role for Alx3 in governing food intake, energy homeostasis, and metabolic nutrient partitioning, thereby influencing body mass composition.

Auxin regulates source-sink carbohydrate partitioning and reproductive organ development in rice.

Carbohydrate partitioning between the source and sink tissues plays an important role in regulating plant growth and development. However, the molecular mechanisms regulating this process remain poorly understood. In this study, we show that elevated auxin levels in the rice dao mutant cause increased accumulation of sucrose in the photosynthetic leaves but reduced sucrose content in the reproductive organs (particularly in the lodicules, anthers, and ovaries), leading to closed spikelets, indehiscent anthers, and parthenocarpic seeds. RNA sequencing analysis revealed that the expression of AUXIN RESPONSE FACTOR 18 (OsARF18) and OsARF2 is significantly up- and down-regulated, respectively, in the lodicule of dao mutant. Overexpression of OsARF18 or knocking out of OsARF2 phenocopies the dao mutant. We demonstrate that OsARF2 regulates the expression of OsSUT1 through direct binding to the sugar-responsive elements (SuREs) in the OsSUT1 promoter and that OsARF18 represses the expression of OsARF2 and OsSUT1 via direct binding to the auxin-responsive element (AuxRE) or SuRE in their promoters, respectively. Furthermore, overexpression of OsSUT1 in the dao and Osarf2 mutant backgrounds could largely rescue the spikelets' opening and seed-setting defects. Collectively, our results reveal an auxin signaling cascade regulating source-sink carbohydrate partitioning and reproductive organ development in rice.

The generality of cryptic dietary niche differences in diverse large-herbivore assemblages.

Ecological niche differences are necessary for stable species coexistence but are often difficult to discern. Models of dietary niche differentiation in large mammalian herbivores invoke the quality, quantity, and spatiotemporal distribution of plant tissues and growth forms but are agnostic toward food plant species identity. Empirical support for these models is variable, suggesting that additional mechanisms of resource partitioning may be important in sustaining large-herbivore diversity in African savannas. We used DNA metabarcoding to conduct a taxonomically explicit analysis of large-herbivore diets across southeastern Africa, analyzing ∼4,000 fecal samples of 30 species from 10 sites in seven countries over 6 y. We detected 893 food plant taxa from 124 families, but just two families-grasses and legumes-accounted for the majority of herbivore diets. Nonetheless, herbivore species almost invariably partitioned food plant taxa; diet composition differed significantly in 97% of pairwise comparisons between sympatric species, and dissimilarity was pronounced even between the strictest grazers (grass eaters), strictest browsers (nongrass eaters), and closest relatives at each site. Niche differentiation was weakest in an ecosystem recovering from catastrophic defaunation, indicating that food plant partitioning is driven by species interactions, and was stronger at low rainfall, as expected if interspecific competition is a predominant driver. Diets differed more between browsers than grazers, which predictably shaped community organization: Grazer-dominated trophic networks had higher nestedness and lower modularity. That dietary differentiation is structured along taxonomic lines complements prior work on how herbivores partition plant parts and patches and suggests that common mechanisms govern herbivore coexistence and community assembly in savannas.

Moderate activity of RNA chaperone maximizes the yield of self-spliced pre-RNA in vivo.

CYT-19 is a DEAD-box protein whose adenosine-triphosphate (ATP)-dependent helicase activity facilitates the folding of group I introns in precursor RNA (pre-RNA) of Neurospora crassa (N. crassa). In the process, they consume a substantial amount of ATP. While much of the mechanistic insight into CYT-19 activity has been gained through the studies on the folding of Tetrahymena group I intron ribozyme, the more biologically relevant issue, namely the effect of CYT-19 on the self-splicing of pre-RNA, remains largely unexplored. Here, we employ a kinetic network model, based on the generalized iterative annealing mechanism (IAM), to investigate the relation between CYT-19 activity, rate of ribozyme folding, and the kinetics of the self-splicing reaction. The network rate parameters are extracted by analyzing the recent biochemical data for CYT-19-facilitated folding of Tetrahymena ribozyme. We then build extended models to explore the metabolism of pre-RNA. We show that the timescales of chaperone-mediated folding of group I ribozyme and self-splicing reaction compete with each other. As a consequence, in order to maximize the self-splicing yield of group I introns in pre-RNA, the chaperone activity must be sufficiently large to unfold the misfolded structures, but not too large to unfold the native structures prior to the self-splicing event. We discover that despite the promiscuous action on structured RNAs, the helicase activity of CYT-19 on group I ribozyme gives rise to self-splicing yields that are close to the maximum.

Dissecting the contributions of membrane affinity and bivalency of the spider venom protein DkTx to its sustained mode of TRPV1 activation.

The spider venom protein, double-knot toxin (DkTx), partitions into the cellular membrane and binds bivalently to the pain-sensing ion channel, TRPV1, triggering long-lasting channel activation. In contrast, its monovalent single knots membrane partition poorly and invoke rapidly reversible TRPV1 activation. To discern the contributions of the bivalency and membrane affinity of DkTx to its sustained mode of action, here, we developed diverse toxin variants including those containing truncated linkers between individual knots, precluding bivalent binding. Additionally, by appending the single-knot domains to the Kv2.1 channel-targeting toxin, SGTx, we created monovalent double-knot proteins that demonstrated higher membrane affinity and more sustained TRPV1 activation than the single-knots. We also produced hyper-membrane affinity-possessing tetra-knot proteins, (DkTx)2 and DkTx-(SGTx)2, that demonstrated longer-lasting TRPV1 activation than DkTx, establishing the central role of the membrane affinity of DkTx in endowing it with its sustained TRPV1 activation properties. These results suggest that high membrane affinity-possessing TRPV1 agonists can potentially serve as long-acting analgesics.

Metabolic priming in G6PDH isoenzyme-replaced tobacco lines improves stress tolerance and seed yields via altering assimilate partitioning.

We investigated the basis for better performance of transgenic Nicotiana tabacum plants with G6PDH-isoenzyme replacement in the cytosol (Xanthi::cP2::cytRNAi, Scharte et al., 2009). After six generations of selfing, infiltration of Phytophthora nicotianae zoospores into source leaves confirmed that defence responses (ROS, callose) are accelerated, showing as fast cell death of the infected tissue. Yet, stress-related hormone profiles resembled susceptible Xanthi and not resistant cultivar SNN, hinting at mainly metabolic adjustments in the transgenic lines. Leaves of non-stressed plants contained twofold elevated fructose-2,6-bisphosphate (F2,6P2 ) levels, leading to partial sugar retention (soluble sugars, starch) and elevated hexose-to-sucrose ratios, but also more lipids. Above-ground biomass lay in between susceptible Xanthi and resistant SNN, with photo-assimilates preferentially allocated to inflorescences. Seeds were heavier with higher lipid-to-carbohydrate ratios, resulting in increased harvest yields - also under water limitation. Abiotic stress tolerance (salt, drought) was improved during germination, and in floated leaf disks of non-stressed plants. In leaves of salt-watered plants, proline accumulated to higher levels during illumination, concomitant with efficient NADP(H) use and recycling. Non-stressed plants showed enhanced PSII-induction kinetics (upon dark-light transition) with little differences at the stationary phase. Leaf exudates contained 10% less sucrose, similar amino acids, but more fatty acids - especially in the light. Export of specific fatty acids via the phloem may contribute to both, earlier flowering and higher seed yields of the Xanthi-cP2 lines. Apparently, metabolic priming by F2,6P2 -combined with sustained NADP(H) turnover-bypasses the genetically fixed growth-defence trade-off, rendering tobacco plants more stress-resilient and productive.

Evaluation of heritability partitioning approaches in livestock populations.

BACKGROUND: Heritability partitioning approaches estimate the contribution of different functional classes, such as coding or regulatory variants, to the genetic variance. This information allows a better understanding of the genetic architecture of complex traits, including complex diseases, but can also help improve the accuracy of genomic selection in livestock species. However, methods have mainly been tested on human genomic data, whereas livestock populations have specific characteristics, such as high levels of relatedness, small effective population size or long-range levels of linkage disequilibrium. RESULTS: Here, we used data from 14,762 cows, imputed at the whole-genome sequence level for 11,537,240 variants, to simulate traits in a typical livestock population and evaluate the accuracy of two state-of-the-art heritability partitioning methods, GREML and a Bayesian mixture model. In simulations where a single functional class had increased contribution to heritability, we observed that the estimators were unbiased but had low precision. When causal variants were enriched in variants with low (< 0.05) or high (> 0.20) minor allele frequency or low (below 1st quartile) or high (above 3rd quartile) linkage disequilibrium scores, it was necessary to partition the genetic variance into multiple classes defined on the basis of allele frequencies or LD scores to obtain unbiased results. When multiple functional classes had variable contributions to heritability, estimators showed higher levels of variation and confounding between certain categories was observed. In addition, estimators from small categories were particularly imprecise. However, the estimates and their ranking were still informative about the contribution of the classes. We also demonstrated that using methods that estimate the contribution of a single category at a time, a commonly used approach, results in an overestimation. Finally, we applied the methods to phenotypes for muscular development and height and estimated that, on average, variants in open chromatin regions had a higher contribution to the genetic variance (> 45%), while variants in coding regions had the strongest individual effects (> 25-fold enrichment on average). Conversely, variants in intergenic or intronic regions showed lower levels of enrichment (0.2 and 0.6-fold on average, respectively). CONCLUSIONS: Heritability partitioning approaches should be used cautiously in livestock populations, in particular for small categories. Two-component approaches that fit only one functional category at a time lead to biased estimators and should not be used.

The dimensionality of infection networks among viruses infecting microbial eukaryotes and bacteria.

Diverse viruses and their hosts are interconnected through complex networks of infection, which are thought to influence ecological and evolutionary processes, but the principles underlying infection network structure are not well understood. Here we focus on network dimensionality and how it varies across 37 networks of viruses infecting eukaryotic phytoplankton and bacteria. We find that dimensionality is often strikingly low, with most networks being one- or two-dimensional, although dimensionality increases with network richness, suggesting that the true dimensionality of natural systems is higher. Low-dimensional networks generally exhibit a mixture of host partitioning among viruses and nestededness of host ranges. Networks of bacteria-infecting and eukaryote-infecting viruses possess comparable distributions of dimensionality and prevalence of nestedness, indicating that fundamentals of network structure are similar among domains of life and different viral lineages. The relative simplicity of many infection networks suggests that coevolutionary dynamics are often driven by a modest number of underlying mechanisms.

Systematic evaluation of B-cell clonal family inference approaches.

The reconstruction of clonal families (CFs) in B-cell receptor (BCR) repertoire analysis is a crucial step to understand the adaptive immune system and how it responds to antigens. The BCR repertoire of an individual is formed throughout life and is diverse due to several factors such as gene recombination and somatic hypermutation. The use of Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) using next generation sequencing enabled the generation of full BCR repertoires that also include rare CFs. The reconstruction of CFs from AIRR-seq data is challenging and several approaches have been developed to solve this problem. Currently, most methods use the heavy chain (HC) only, as it is more variable than the light chain (LC). CF reconstruction options include the definition of appropriate sequence similarity measures, the use of shared mutations among sequences, and the possibility of reconstruction without preliminary clustering based on V- and J-gene annotation. In this study, we aimed to systematically evaluate different approaches for CF reconstruction and to determine their impact on various outcome measures such as the number of CFs derived, the size of the CFs, and the accuracy of the reconstruction. The methods were compared to each other and to a method that groups sequences based on identical junction sequences and another method that only determines subclones. We found that after accounting for data set variability, in particular sequencing depth and mutation load, the reconstruction approach has an impact on part of the outcome measures, including the number of CFs. Simulations indicate that unique junctions and subclones should not be used as substitutes for CF and that more complex methods do not outperform simpler methods. Also, we conclude that different approaches differ in their ability to correctly reconstruct CFs when not considering the LC and to identify shared CFs. The results showed the effect of different approaches on the reconstruction of CFs and highlighted the importance of choosing an appropriate method.