Natural mitochondrial DNA (mtDNA) mutations enable the inference of clonal relationships among cells. mtDNA can be profiled along with measures of cell state, but has not yet been combined with the massively parallel approaches needed to tackle the complexity of human tissue. Here, we introduce a high-throughput, droplet-based mitochondrial single-cell Assay for Transposase Accessible Chromatin with sequencing (mtscATAC-seq), a method that combines high-confidence mtDNA mutation calling in thousands of single cells with their concomitant high-quality accessible chromatin profile. This enables the inference of mtDNA heteroplasmy, clonal relationships, cell state, and accessible chromatin variation in individual cells. We reveal single-cell variation in heteroplasmy of a pathologic mtDNA variant, which we associate with intra-individual chromatin variability and clonal evolution. We clonally trace thousands of cells from cancers, linking epigenomic variability to subclonal evolution and infer cellular dynamics of differentiating hematopoietic cells in vitro and in vivo . Taken together, our approach enables the study of cellular population dynamics and clonal properties in vivo .

The innovative RTM-GWAS procedure provides a relatively thorough detection of QTL and their multiple alleles for germplasm population characterization, gene network identification, and genomic selection strategy innovation in plant breeding. The previous genome-wide association studies (GWAS) have been concentrated on finding a handful of major quantitative trait loci (QTL), but plant breeders are interested in revealing the whole-genome QTL-allele constitution in breeding materials/germplasm (in which tremendous historical allelic variation has been accumulated) for genome-wide improvement. To match this requirement, two innovations were suggested for GWAS: first grouping tightly linked sequential SNPs into linkage disequilibrium blocks (SNPLDBs) to form markers with multi-allelic haplotypes, and second utilizing two-stage association analysis for QTL identification, where the markers were preselected by single-locus model followed by multi-locus multi-allele model stepwise regression. Our proposed GWAS procedure is characterized as a novel restricted two-stage multi-locus multi-allele GWAS (RTM-GWAS, https://github.com/njau-sri/rtm-gwas ). The Chinese soybean germplasm population (CSGP) composed of 1024 accessions with 36,952 SNPLDBs (generated from 145,558 SNPs, with reduced linkage disequilibrium decay distance) was used to demonstrate the power and efficiency of RTM-GWAS. Using the CSGP marker information, simulation studies demonstrated that RTM-GWAS achieved the highest QTL detection power and efficiency compared with the previous procedures, especially under large sample size and high trait heritability conditions. A relatively thorough detection of QTL with their multiple alleles was achieved by RTM-GWAS compared with the linear mixed model method on 100-seed weight in CSGP. A QTL-allele matrix (402 alleles of 139 QTL × 1024 accessions) was established as a compact form of the population genetic constitution. The 100-seed weight QTL-allele matrix was used for genetic characterization, candidate gene prediction, and genomic selection for optimal crosses in the germplasm population.

Determining mitochondrial genomes is important for elucidating vital activities of seed plants. Mitochondrial genomes are specific to each plant species because of their variable size, complex structures and patterns of gene losses and gains during evolution. This complexity has made research on the soybean mitochondrial genome difficult compared with its nuclear and chloroplast genomes. The present study helps to solve a 30-year mystery regarding the most complex mitochondrial genome structure, showing that pairwise rearrangements among the many large repeats may produce an enriched molecular pool of 760 circles in seed plants. The soybean mitochondrial genome harbors 58 genes of known function in addition to 52 predicted open reading frames of unknown function. The genome contains sequences of multiple identifiable origins, including 6.8 kb and 7.1 kb DNA fragments that have been transferred from the nuclear and chloroplast genomes, respectively, and some horizontal DNA transfers. The soybean mitochondrial genome has lost 16 genes, including nine protein-coding genes and seven tRNA genes; however, it has acquired five chloroplast-derived genes during evolution. Four tRNA genes, common among the three genomes, are derived from the chloroplast. Sizeable DNA transfers to the nucleus, with pericentromeric regions as hotspots, are observed, including DNA transfers of 125.0 kb and 151.6 kb identified unambiguously from the soybean mitochondrial and chloroplast genomes, respectively. The soybean nuclear genome has acquired five genes from its mitochondrial genome. These results provide biological insights into the mitochondrial genome of seed plants, and are especially helpful for deciphering vital activities in soybean.

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Annual wild soybean (Glycine soja Sieb. et Zucc.) is believed to be a potential gene source for future soybean improvement in coping with the world climate change for food security. To evaluate the wild soybean genetic diversity and differentiation, we analyzed allelic profiles at 60 simple-sequence repeat (SSR) loci and variation of eight morph-biological traits of a representative sample with 196 accessions from the natural growing area in China. For comparison, a representative sample with 200 landraces of Chinese cultivated soybean was included in this study. The SSR loci produced 1,067 alleles (17.8 per locus) with a mean gene diversity of 0.857 in the wild sample, which indicated the genetic diversity of G. soja was much higher than that of its cultivated counterpart (total 826 alleles, 13.7 per locus, mean gene diversity 0.727). After domestication, the genetic diversity of the cultigens decreased, with its 65.5% alleles inherited from the wild soybean, while 34.5% alleles newly emerged. AMOVA analysis showed that significant variance did exist among Northeast China, Huang-Huai-Hai Valleys and Southern China subpopulations. UPGMA cluster analysis indicated very significant association between the geographic grouping and genetic clustering, which demonstrated the geographic differentiation of the wild population had its relevant genetic bases. In comparison with the other two subpopulations, the Southern China subpopulation showed the highest allelic richness, diversity index and largest number of specific-present alleles, which suggests Southern China should be the major center of diversity for annual wild soybean.

Here we describe TRACE (T7 polymerase-driven continuous editing), a method that enables continuous, targeted mutagenesis in human cells using a cytidine deaminase fused to T7 RNA polymerase. TRACE induces high rates of mutagenesis over multiple cell generations in genes Reprints and permissions information is available at www.nature.com/reprints.

Seed size and shape are important traits determining yield and quality in soybean. However, the genetic mechanism and genes underlying these traits remain largely unexplored. In this regard, this study used two related recombinant inbred line (RIL) populations (ZY and K3N) evaluated in multiple environments to identify main and epistatic-effect quantitative trait loci (QTLs) for six seed size and shape traits in soybean. A total of 88 and 48 QTLs were detected through composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively, and 15 QTLs were common among both methods; two of them were major (R2 > 10%) and novel QTLs (viz., qSW-1-1ZN and qSLT-20-1K3N). Additionally, 51 and 27 QTLs were identified for the first time through CIM and MCIM methods, respectively. Colocalization of QTLs occurred in four major QTL hotspots/clusters, viz., “QTL Hotspot A”, “QTL Hotspot B”, “QTL Hotspot C”, and “QTL Hotspot D” located on Chr06, Chr10, Chr13, and Chr20, respectively. Based on gene annotation, gene ontology (GO) enrichment, and RNA-Seq analysis, 23 genes within four “QTL Hotspots” were predicted as possible candidates, regulating soybean seed size and shape. Network analyses demonstrated that 15 QTLs showed significant additive x environment (AE) effects, and 16 pairs of QTLs showing epistatic effects were also detected. However, except three epistatic QTLs, viz., qSL-13-3ZY, qSL-13-4ZY, and qSW-13-4ZY, all the remaining QTLs depicted no main effects. Hence, the present study is a detailed and comprehensive investigation uncovering the genetic basis of seed size and shape in soybeans. The use of a high-density map identified new genomic regions providing valuable information and could be the primary target for further fine mapping, candidate gene identification, and marker-assisted breeding (MAB).

Plant height (PH) and the number of nodes on the main stem (NN) serve as major plant architecture traits affecting soybean seed yield. Although many quantitative trait loci for the two traits have been reported, their genetic controls at different developmental stages in soybeans remain unclear. Here, 368 soybean breeding lines were genotyped using 62,423 single nucleotide polymorphism (SNP) markers and phenotyped for the two traits at three different developmental stages over two locations in order to identify their quantitative trait nucleotides (QTNs) using compressed mixed linear model (CMLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) approaches. As a result, 11 and 13 QTNs were found by CMLM to be associated with PH and NN, respectively. Among these QTNs, 8, 3, and 4 for PH and 6, 6, and 8 for NN were found at the three stages, and 3 and 6 were repeatedly detected for PH and NN. In addition, 34 and 30 QTNs were found by mrMLM to be associated with PH and NN, respectively. Among these QTNs, 11, 13, and 16 for PH and 11, 15, and 8 for NN were found at the three stages. A majority of these QTNs overlapped with the previously reported loci. Moreover, one QTN within the known E2 locus for flowering time was detected for the two traits at all three stages, and another that overlapped with the Dt1 locus for stem growth habit was also identified for the two traits at the mature stage. This may explain the highly significant correlation between the two traits. Our findings provide evidence for mixed major plus polygenes inheritance for dynamic traits and an extended understanding of their genetic architecture for molecular dissection and breeding utilization in soybeans.