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Nuclear compartments are prominent features of 3D chromatin organization, but sequencing depth limitations have impeded investigation at ultra fine-scale. CTCF loops are generally studied at a finer scale, but the impact of looping on proximal interactions remains enigmatic. Here, we critically examine nuclear compartments and CTCF loop-proximal interactions using a combination of in situ Hi-C at unparalleled depth, algorithm development, and biophysical modeling. Producing a large Hi-C map with 33 billion contacts in conjunction with an algorithm for performing principal component analysis on sparse, super massive matrices (POSSUMM), we resolve compartments to 500 bp. Our results demonstrate that essentially all active promoters and distal enhancers localize in the A compartment, even when flanking sequences do not. Furthermore, we find that the TSS and TTS of paused genes are often segregated into separate compartments. We then identify diffuse interactions that radiate from CTCF loop anchors, which correlate with strong enhancer-promoter interactions and proximal transcription. We also find that these diffuse interactions depend on CTCF’s RNA binding domains. In this work, we demonstrate features of fine-scale chromatin organization consistent with a revised model in which compartments are more precise than commonly thought while CTCF loops are more protracted. Ultra-deep mapping of genome organization uncovers precise nuclear compartments and diffuse CTCF loops. This work demonstrates that compartment domains segregate the 5′ and 3′ ends of genes and that CTCF loops create proximal structures.

The isolation or engineering of algal cells synthesizing high levels of medium-chain fatty acids (MCFAs) is attractive to mitigate the high clouding point of longer chain fatty acids in algal based biodiesel. To develop a more informed understanding of MCFA synthesis in photosynthetic microorganisms, we isolated several algae from Great Salt Lake and screened this collection for MCFA accumulation to identify strains naturally accumulating high levels of MCFA. A diatom, Chaetoceros sp. GSL56, accumulated particularly high levels of C14 (up to 40%), with the majority of C14 fatty acids allocated in triacylglycerols. Using whole cell transcriptome sequencing and de novo assembly, putative genes encoding fatty acid synthesis enzymes were identified. Enzymes from this Chaetoceros sp. were expressed in the cyanobacterium Synechococcus sp. PCC 7002 to validate gene function and to determine whether eukaryotic enzymes putatively lacking bacterial evolutionary control mechanisms could be used to improve MCFA production in this promising production strain. Replacement of the Synechococcus 7002 native FabH with a Chaetoceros ketoacyl-ACP synthase III increased MCFA synthesis up to fivefold. The level of increase is dependent on promoter strength and culturing conditions.

Photosynthetic microorganisms (PSMs) are promising candidates for biofuels because they do not directly compete with the food supply. However, significant improvements are still required to achieve economic feasibility. The high cost of PSM based biofuel production comes from deficiencies in biomass yields, cell recovery, fuel conversion and nutrient inputs. An algal biofuel production and processing pipeline advocated by the National Renewable Energy Laboratory proposes to overcome many of the difficulties associated with the conversion of biomass to fuels. In this approach, acid catalyzed pretreatment is used to release cellular constituents. The oils are then extracted with organic solvents and the remaining carbohydrates used in yeast fermentations to make alcohols. We demonstrate that the biomass residues collected after fermentation can be recycled back to algal cultures as the sole source of nitrogen, eliminating the need for new external supplies of nitrogen for subsequent culturing. The alga Scenedesmus acutus was selected after organism screening for its ability to utilize a diversity of exogenous organic nitrogen sources. The replacement of nitrate with biomass residues (or amino acids/yeast extracts) demonstrated that the protein-rich biomass residuals not only provided an effective nitrogen resource, but also improved overall biomass and lipid yields. Optimizing lipid production through metabolic engineering can improve energy densities in algal feedstocks and further reduce production costs. We studied lipid biosynthesis in an alga that we recently isolated from the Great Salt Lake (Utah), Chaetoceros sp. GSL56, which was shown to produce very high levels of medium chain fatty acids. Fatty acids in the C8-C14 range are industrially useful and are also ideal for biodiesel. Using whole cell transcriptome sequencing, genes encoding the fatty acid synthesis enzymes were identified in this alga and expression of a ketoacyl-ACP synthase in the cyanobacterium Synechococcus sp. PCC7002, a potential biofuel production strain, increased medium chain fatty acid production up to 10 fold. Genetic engineering of PSM cells for high lipid productivity often encounters the problem of carbon partitioning, which diverts carbon away from lipid biosynthesis. In the green alga Chlamydomonas reinhardtii, deletion of starch biosynthesis redirects carbon into lipid biosynthesis, but also attenuates photosynthesis by unknown mechanisms. The comparative analysis of central carbon metabolites, as well as quantifying the changes in major carbon sinks (carbohydrate, lipid and protein), in starchless mutants and control strains revealed the metabolic nodes blocked in carbon rerouting. These results suggest that the fatty acid synthase complex is blocked and should be targeted in future genetic engineering efforts. Photosynthetic studies conducted in starchless mutants revealed that linear electron transport was attenuated because of the absence of an appropriate carbon sink.

Megabase-scale intervals of active, gene-rich and inactive, gene-poor chromatin are known to segregate, forming the A and B compartments. Fine mapping of the contents of these A and B compartments has been hitherto impossible, owing to the extraordinary sequencing depths required to distinguish between the long-range contact patterns of individual loci, and to the computational complexity of the associated calculations. Here, we generate the largest published in situ Hi-C map to date, spanning 33 billion contacts. We also develop a computational method, dubbed PCA of Sparse, Super Massive Matrices (POSSUMM), that is capable of efficiently calculating eigenvectors for sparse matrices with millions of rows and columns. Applying POSSUMM to our Hi-C dataset makes it possible to assign loci to the A and B compartment at 500 bp resolution. We find that loci frequently alternate between compartments as one moves along the contour of the genome, such that the median compartment interval is only 12.5 kb long. Contrary to the findings in coarse-resolution compartment profiles, we find that individual genes are not uniformly positioned in either the A compartment or the B compartment. Instead, essentially all (95%) active gene promoters localize in the A compartment, but the likelihood of localizing in the A compartment declines along the body of active genes, such that the transcriptional termini of long genes (>60 kb) tend to localize in the B compartment. Similarly, essentially all active enhancers elements (95%) localize in the A compartment, even when the flanking sequences are comprised entirely of inactive chromatin and localize in the B compartment. These results are consistent with a model in which DNA-bound regulatory complexes give rise to phase separation at the scale of individual DNA elements. Competing Interest Statement The authors have declared no competing interest.

EndoC-βH1 is emerging as a critical human beta cell model to study the genetic and environmental etiologies of beta cell function, especially in the context of diabetes. Comprehensive knowledge of its molecular landscape is lacking yet required to fully take advantage of this model. Here, we report extensive chromosomal (spectral karyotyping), genetic (genotyping), epigenetic (ChIP-seq, ATAC-seq), chromatin interaction (Hi-C, Pol2 ChIA-PET), and transcriptomic (RNA-seq, miRNA-seq) maps of this cell model. Integrated analyses of these maps define known (e.g., PDX1, ISL1) and putative (e.g., PCSK1, mir-375) beta cell-specific chromatin interactions and transcriptional cis-regulatory networks, and identify allelic effects on cis-regulatory element use and expression. Importantly, comparative analyses with maps generated in primary human islets/beta cells indicate substantial preservation of chromatin looping, but also highlight chromosomal heterogeneity and fetal genomic signatures in EndoC-βH1. Together, these maps, and an interactive web application we have created for their exploration, provide important tools for the broad community in the design and success of experiments to probe and manipulate the genetic programs governing beta cell identity and (dys)function in diabetes.

EndoC- H1 is emerging as a critical human beta cell model to study the genetic and environmental etiologies of beta cell function, especially in the context of diabetes. Comprehensive knowledge of its molecular landscape is lacking yet required to fully take advantage of this model. Here, we report extensive chromosomal (spectral karyotyping), genetic (genotyping), epigenetic (ChIP-seq, ATAC-seq), chromatin interaction (Hi-C, Pol2 ChIA-PET), and transcriptomic (RNA-seq, miRNA-seq) maps of this cell model. Integrated analyses of these maps define known (e.g., PDX1, ISL1) and putative (e.g., PCSK1, mir-375) beta cell-specific chromatin interactions and transcriptional cis-regulatory networks, and identify allelic effects on cis-regulatory element use and expression. Importantly, comparative analyses with maps generated in primary human islets/beta cells indicate substantial preservation of chromatin looping, but also highlight chromosomal heterogeneity and fetal genomic signatures in EndoC- H1. Together, these maps, and an interactive web application we have created for their exploration, provide important tools for the broad community in the design and success of experiments to probe and manipulate the genetic programs governing beta cell identity and (dys)function in diabetes.

S722.3; 对云南省8个地方栽培木豆群体进行调查,对木豆株高、地径、冠幅、单株荚数、虫荚率、单株粒质量及百粒质量等数量性状变异进行分析,结果表明7个性状不论是群体间还是群体内个体间均存在丰富变异.性状相关性分析表明,单株粒质量与单株荚数呈高度正相关,与株高、地径呈弱正相关.单株荚数、虫荚百分率、百粒质量对产量构成贡献最大,通径系数分别为0.855 1、-0.237 4、0.179 9.若将三个性状相结合,选择单株荚数多、粒大、虫荚少的单株,则后代产量可望有明显增加,有可能育成高产高抗虫性品种.

Eight local cultivation pigeonpea populations in Yunnan province were investigated and analyzed on their variance in plant heigh,diameter of stem,canopy,pod numbers per plant,ratio of pod damaged by pests,seed weight per plant and other quantitative characters.Results showed many variances existed either among or within populations.The results showed a high degree of positive correlations between grain yield per plant and pod numbers per plant,but only low degree of positive correlations between grain yield per plant and plant height or stem diameter.There were no obvious correlations between grain yield per plant and other characters.Pod numbers per plant,ratio of pod damaged by pests and 100-seed weight gave the most contribution to seeds yield per plant; their path correlation coefficients were 0.855 1、-0.237 4、0.179 9 respectively.Choosing the plants with more pod numbers,larger seeds and lower pest-damaged ration in breeding program,would give opportunities to get new varieties with high grain yield and