The differentially expressed mRNA and circRNA parental genes were enriched in the Wnt signaling pathway (adipogenesis), the transition between fast and slow fibers (myogenic differentiation), and alanine, aspartate and glutamate metabolism (pork flavor). The potential lncRNAs/circRNAs-miRNAs-mRNAs regulatory networks shared MYOD1, PPARD, miR-423-5p and miR-874, which were associated with skeletal muscle muscular proliferation, differentiation/regeneration and adipogenesis. Taken together, these differentially expressed non-coding RNAs may be involved in the molecular basis of muscle traits, acting as the competing endogenous RNA (ceRNA) for miRNAs.Circular RNA (circRNA) and long non-coding RNA (lncRNA) are known to participate in adipogenesis and myogenic differentiation, but their impact on porcine muscle traits is not well understood. We compared their expressional profiles in the longissimus dorsi muscle of Chinese Huainan pigs  and Western commercial Duroc × (Landrace × Yorkshire)  pigs, and 854 mRNAs, 233 lncRNAs, and 66 circRNAs ( In the pork industry, meat quality is an important economic trait, including the color, marbling, intramuscular fat (IMF) content, and firmness . By its MEF2C) [COL3A1) [NCOA3), fatty acid binding protein 4 (FABP4) and peroxisome proliferator-activated receptor gamma (PPARG) expressions and reduced preadipocyte differentiation [FoxO1) regulated platelet-derived growth factor receptor alpha (PDGFRα) and promoted IMF deposition through the Erk signaling pathway [PRC2) [MYOD1), reduced the accumulation of myogenic marker genes and played a role in controlling muscle differentiation [PU.1  proviral integration oncogene spi1) mRNA, PU.1 AS lncRNA (vs. its mRNA translation) promoted adipogenesis [Advances in sequencing technology have revealed that the biological processes are regulated, not only by protein-coding RNA-(mRNA), but also by non-coding RNA (ncRNA), such as micro RNA (miRNA), long non-coding RNA (lncRNA), and circular RNA (circRNA). There have been several studies on how mRNA and miRNA affect the porcine muscle traits. For example, miR-23a was found to influence meat quality by reducing the composition of slow myosin heavy chain isoforms through myocyte enhancer factor 2C (MEF2C) . The miR[COL3A1) . In intrntiation . In porc pathway . It was  pathway . The ove pathway . There a pathway . Long no pathway . SYISL (y [PRC2) . LncRNAsntiation . By formogenesis .IGF1R) [BCLAF1) [c-JUN) and MEF2C via miR-203 [lipin 1) axis participated in the regulation of hepatic steatosis [Recently, there were several researches on the effect of circRNAs on the proliferation, differentiation, and migration of myoblast. For example, in rat, rno-circ_005717 (circDiaph3) promoted vascular smooth muscle cells (VSMCs) differentiation by up-regulated diaphanous-related formin-3 (DIAPH3) and supported its proliferation and migration by up-regulated insulin, such as the growth factor 1 receptor ([BCLAF1) . In chic miR-203 . In catt miR-203 . In the  miR-203 . The cirteatosis . In a gateatosis . From thAfter the redundant and low-quality reads were removed, 83.61 and 83.58 million clean reads were obtained from the LD muscles of HN and DLY pigs, respectively. The datasets were submitted to the National Center for Biotechnology Information Gene Expression Omnibus, with accession number GSE86919. In total, 9068 lncRNAs and 6988 circRNAs were identified in all chromosomes. Additionally, there were four circRNAs in mitochondrial DNA (mtDNA) a, includWe found 16,247 (86.5%) mRNAs, 4,859 (53.6%) lncRNAs, and 2,293 (32.8%) circRNAs that were shared by both HN and DLY pigs a. The avThe 18 DEMs associated with muscle growth and fatness are shown in MYOD1, Peroxisome Proliferator Activated Receptor Delta (PPARD), miR-423-5p and miR-874.As shown in MYOD1-related ceRNAs were measured by RT-qPCR  was up-regulated in the HN breed. These 18 genes included the genes that participated in muscle growth and development, such as MYOD1, FOS , and IFRD1 , and the genes associated with adipogenesis and lipid metabolism, such as SCD, INSIG1 (insulin induced gene 1) and LIPG . Meanwhile, in the GO analyses, the transition between fast and slow fibers for both DEMs and DECs was enriched. It is well known that the muscle fiber types have an influence on meat quality [In the GO analysis of DEMs, the genes associated with muscle traits were visible in Circos plots in  quality , for exa quality . Another quality . These rDDO) gene and circRNA_4504 from glutamine-fructose-6-phosphate transaminase 1 (GFPT1) were significantly up-regulated in HN pigs, which was consistent with the better taste of the native Chinese pigs, compared with the Western pigs [While alanine, aspartate and glutamate were the non-essential amino acids, they played key roles in the pork taste and flavor . In the ern pigs ,31. TOBF1) to genomic sites resembling the canonical Oct-Sox motif [PPARG2 promoter and increasing its transcription [EBF2) to stimulate the thermogenic gene program [smad7 (SMAD Family Member 7) and IGF2 (insulin-like growth factor 2) axes promote myoblast differentiation and muscle regeneration [TGF-β1) [PPARD) was shared by these two networks and was the target gene of three miRNAs, and these miRNAs targeted five lncRNAs and 16 circRNAs. Another shared gene was MYOD1, and two lncRNAs and three circRNAs act as its ceRNA via miR-296-5p. As reported, PPARD was the vital regulator in adipogenesis [MYOD1 was an important transcription factor during muscle development, so these ncRNAs may also participate in these processes by indirectly regulating the expressional level of PPARD and MYOD1. MiR-423-5p and miR-874 were shared by these two networks, and miR-423-5p targeted one lncRNA, four circRNAs and FOS. It was reported that miR-423-5p was involved in skeletal muscle development/regeneration [FOS was associated with porcine skeletal muscle fiber traits [PPAR signaling pathway and affected bovine fat deposition [LncRNAs participated in the regulation of different biological processes in different ways ,33. Firsox motif . Secondlcription . Brown f program . Thirdly program . Recentl program . The Lncneration . CircRNA[TGF-β1) . In thisogenesis  and lipiogenesis , and MYOneration , and FOSr traits . Similarposition , targeteMYOD1-related ceRNA network were preliminarily confirmed by qRT-PCR, and the results were consistent with RNA sequencing, but their functions and interactions needed further validation. RNA pulldown , ChIRP , and dual luciferase reporter systems  can be used to validate these DELs’ and DECs’ functions in relation to porcine meat quality.As for the economic considerations, an equal amount of the RNA sample from both the HN pigs and DLY pigs was pooled for sequencing. A similar approach was previously used in RNA sequencing ,47,48,49The experimental methods were performed in accordance with the guidelines of the Good Experimental Practices, adopted by the Institute of Animal Science. Additionally, all experimental protocols were approved by the Institute of Animal Science of the Henan Academy of Agricultural Sciences (code 2 May 2015).Six male HN and DLY pigs  were obtained from the Henan Xing Rui Agricultural and Animal Husbandry Technology Co., LTD in Henan province, China. These pigs were castrated under anesthesia , and they were housed under standard environmental conditions  and were fed a standard diet three times a day and watered ad libitum . All pig™, Carlsbad, CA, USA), according to the manufacturer’s instructions. DNase I  was used to remove the residual genomic DNA from the total RNA. Agarose gel electrophoresis, a Nano-Drop ND-2000 spectrophotometer , and an Agilent 2100 Bioanalyzer  were used to assess the integrity, purity, and quality of the isolated RNA. Samples with an RNA integrity number (RIN) value larger than eight were used for further analysis. For each breed, equal quantities of RNA, isolated from each individual, were pooled.The total RNA was isolated from the porcine LD muscle using TRIzol reagent  was removed from the DNA-free RNA using the Ribo-ZeroTM kit . Next, the DNA and rRNA-free RNA were used to create a library using the NEBNext Ultra Directional RNA Library Prep Kit for Illumina . The library was sequenced with a HiSeq 2500 instrument .http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and the NGS QC TOOLKIT (http://59.163.192.90:8080/ngsqctoolkit/) [ftp://ftp.ncbi.nlm.nih.gov/genomes/Sus_scrofa/). Cufflinks was used to perform the transcript assembly and abundance estimation [Clean data were obtained by removing the poor-quality bases and adapter sequences from the raw data using FASTQC (oolkit/) . TopHat2oolkit/)  was usedtimation .The pipelines for lncRNAs identification were as follows: (1) Transcripts that were merged or were similar to the known porcine mRNAs and other small RNAs  were removed using cuffcompare software . (2) TheAfter the clean reads were aligned to the porcine reference genome, the junctions of the unmapped reads were identified using a back-splice algorithm. Then, the Findcirc software was used to predict the circRNAs . The exphttp://bioconductor.org/packages/release/bioc/html/DESeq.html) was used to detect differentially expressed mRNAs (DEMs), circRNAs (DECs), and lncRNAs (DELs), with p < 0.05, adjp ≤ 1.00 and | log2FoldChange | >1. Gene Ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed for DEMs and DECs (using the DECs’ parent genes) using the DAVID tool, and p < 0.05 were considered significant [http://www.circos.ca/software).The DESeq software package (nificant . In the http://cytoscape.org/) [Recently, it was found that mRNAs and lncRNAs/circRNA with the same miRNA response elements (MREs) regulated each other’s expression by competitively binding to miRNAs. To determine the possible interactions between miRNA with mRNA, lncRNA and circRNA, the interactions between the porcine miRNA and the DEMs, DELs, and DECs were analyzed using the miRanda software . The porpe.org/) . In the MYOD1, including one miRNA (ssc-miR-296-5p), two lncRNAs (TCON_00034808 and TCON_00016662), and three circRNAs  were selected, and their expressional trends in the HN and DLY groups were validated by RT-qPCR. The RNA used in the validation was the same as that used in the Illumina sequencing. We used the PrimeScript RT reagent Kit, with the gDNA Eraser , to convert the total RNA to cDNA, with random hexamers  and stem-loop RT primers  [U6 (for miRNA) were used as endogenous controls. All primers used in RT-qPCR are shown in U6, which were purchased from RiboBio . Each qPCR reaction was performed in a 20 µL reaction mixture, including 20 ng template cDNA, 10 µL 2 × SYBR Premix Ex Taq™, and 10 µM forward and reverse primers. The PCR amplification included an initial denaturation step (95 °C for 30 s) and 40 cycles of 5 s at 95 °C and 30 s at 60 °C. Each qPCR experiment was performed in triplicate, and the relative RNA expression values were calculated using the 2−△△Ct method [According to the networks of lncRNA/circRNA-miRNA-mRNA, six nodes around the RiboBio) . Then, qt method . The datPPARD, MYOD1, etc.) via functional miRNAs . This study provided a new insight into the genetic basis of porcine muscle growth and fatness, and further investigations are necessary to validate the ceRNA mechanisms of ncRNAs and mRNAs.In conclusion, we compared the structural and expressional features of mRNAs, lncRNAs and circRNAs in the LD muscle of the Chinese HN and Western DLY pigs. The results showed that ncRNAs were abundant in the porcine LD muscle, and the bioinformatics analyses indicated that ncRNAs were involved in muscular proliferation, differentiation/regeneration and adipogenesis, acting as ceRNAs for vital transcription factors (such as


Archaeoglobus fulgidus sequence. We have solved the X-ray crystal structure of the complex of the A. fulgidus RNA bound to its cognate L7Ae protein. The RNA adopts a standard k-turn conformation that is specifically recognized by the L7Ae protein, so stabilizing the stem–loop. In-line probing of the natural-sequence UTR shows that the RNA is unstructured in the absence of L7Ae binding, but folds on binding the protein such that the ribosome binding site is occluded. Thus, L7Ae regulates its own translation by switching the conformation of the RNA to alter accessibility.A recent study has shown that archaeal L7Ae binds to a putative k-turn structure in the 5′-leader of the mRNA of its structural gene to regulate translation. To function as a regulator, the RNA should be unstructured in the absence of protein, but it should adopt a k-turn-containing stem–loop on binding L7Ae. Sequence analysis of UTR sequences indicates that their k-turn elements will be unable to fold in the absence of L7Ae, and we have demonstrated this experimentally in solution using FRET for the  Riboregulation takes many forms. It can be mediated by small RNA molecules (noncoding regulatory RNA), metabolites (in the riboswitches) or proteins. A number of ribosomal proteins are subject to autoregulation; a good example is the binding of bacterial S15 protein to a specific structure within the 5′ region of its mRNA to repress translation . L7Ae istrans-sugar-Hoogsteen G:A base pairs. The RNA can adopt one of two conformations; either a relatively extended structure similar to a typical 3-nt bulge, or a tightly kinked structure where the helical axis includes an angle of 50°  , which he of 50° . The kine of 50° . The maje of 50° . Whethere of 50° . Proteine of 50° , which be of 50° . Importae of 50°  or 15.5Ke of 50°  proteinse of 50°  and the e of 50° .Sulfolobus acidocaldarius, they performed a RIP-Seq analysis to provide the L7Ae-RNA interactome, and so identified over 100 RNA species that bind L7Ae in the cell, of which 59 were box C/D snoRNAs. This also included 32 mRNA species, one of which was the transcript of l7ae, the structural gene encoding L7Ae protein. Detailed analysis of the data indicated that the principal site of binding lay in the 5′-untranslated region (UTR) of the transcript, the sequence of which was consistent with the formation of a short stem–loop structure that contained a potential k-turn structure. The stem–loop overlapped with the ribosome binding site, suggesting a potential mechanism for translational regulation, and this was supported by reporter assays showing the down-regulation of translational in the presence of L7Ae. In a recent study, Randau and colleagues  obtainedArchaeoglobus fulgidus l7ae leader RNA, supporting the proposed regulatory mechanism.This suggests a mechanism of gene regulation in which the RNA structure of the transcript plays a key role. It seems probable that the 5′-UTR sequence would be unstructured and accessible to the translation machinery until bound by L7Ae. Thereupon the k-turn would fold to stabilize the stem–loop that would occlude the ribosome binding site. In this work we have sought to test two structural aspects of this model. First, in the absence of L7Ae the RNA should not fold into the kinked conformation k-turn, but rather should behave like the archaeal box C/D k-turn that is unfolded in the presence of metal ions. Second, when present L7Ae should bind so that the k-turn folds and a standard L7Ae-k-turn complex is formed. We have found that both of these criteria are met for the l7ae genes from six different archaeal species .The −1b:−1n sequence. Recently we have found that the −1b:−1n sequence that precedes the bulge can have a strong influence on ion-induced folding . SystemaIn general, these stem–loop structures appear to be of low intrinsic stability, especially at the elevated temperatures at which many of these thermophilic organisms live. In all cases, the C-helix has a limited number of Watson–Crick base pairs, and some of the sequences have few Watson–Crick base pairs following the G:A base pairs. If the stem–loop structures do form, we can ask how readily might the k-turn fold into its tightly kinked conformation in the absence of protein binding. We have previously studied this in some depth , and havThese rules appear to apply generally for all k-turns studied. Importantly, every k-turn that has been analyzed, irrespective of the 3b:3n or −1b:−1n sequences, undergoes folding into the kinked conformation on addition of L7Ae protein .l7ae URT k-turn sequences. With a single exception , none of the elements has 3b = C or 3n = G, and with that exception none is expected to fold well in response to metal ions. In addition, none of the six sequences has −1b:−1n = C:G, and two have G:C and one has C:A. The remaining three have −1b:−1n sequences whose folding properties have not been studied. Taken together, it is probable that all the sequences are unable to fold into a stable k-turn conformation in response to the addition of metal ions.Insofar as possible we have applied the above rules to the A. fulgidus l7ae UTR to explore this question. It has 3b:3n = A:U, and −1b:−1n = C:A, both of which prevent ion-induced folding in Kt-7  calculated using the acceptor normalization method (EFRET will increase.We studied the folding of this element using fluorescence resonance energy transfer (FRET). For this purpose we synthesized a dsRNA containing the central k-turn, extending the natural sequence to have C and NC arms of 12 and 13 bp, respectively , top. Thn method . If the 2+ ions or A. fulgidus L7Ae protein (AfL7Ae), and EFRET has been plotted as a function of ion or protein concentration (EFRET as a function of Mg2+ concentration (open circles) remains at a low value (<0.18) across the whole range of ionic concentration. In contrast, addition of L7Ae protein (closed circles) results in a marked increase in EFRET at stoichiometric concentration, reaching a plateau value of 0.6. This is the standard behavior of a k-turn that folds on binding a member of the L7Ae family of proteins  (The change in ID 4BW0) .Supplemental Fig. S3). The structure of a single k-turn bound to one molecule of AfL7Ae is shown in In the crystal lattice, three two-k-turn units adopted a triangular arrangement, with six L7Ae molecules bound to six k-turns  is a measure of the flexibility of the RNA at that point, allowing it to sample the in-line conformation. The results are shown in In addition to spectroscopic and crystallographic studies, we have investigated the structural change in the k-turn-carrying stem–loop structure formed by the  probing  as a funA. fulgidus L7Ae to the unmodified UTR sequence, the section corresponding to the stem regions became protected, and that corresponding to the loop exhibited enhanced reactivity. In contrast, the mutant sequence gave a rather different pattern of bands indicative of a different mode of binding and not consistent with the same stem–loop formation. We know from earlier work that at higher L7Ae concentration nonspecific binding can occur, that does not result in the standard k-turn conformation. From a functional point of view it is apparent that the ribosome binding site is reactive  in the mutant, but becomes protected in the L7Ae complex for the natural sequence. These results are consistent with the formation of the stem–loop structure in the natural 5′-UTR that is stabilized by binding of L7Ae to the k-turn structure, with a resulting occlusion of the ribosome binding site.In the absence of L7Ae protein, both wild-type and mutant RNAs exhibited uniform cleavage along their length, consistent with a largely single-stranded character. However, on addition of A. fulgidus L7Ae binds to the 5′-UTR of the mRNA of its structural gene, stabilizing the standard k-turn conformation that should occlude the ribosome binding site. In the absence of L7Ae protein, the stem–loop structure should be very unstable, as we demonstrate by in-line probing. This will be accentuated at the elevated temperature at which this thermophilic archaeon lives. Under these conditions, the equilibrium between unstructured RNA and the stem–loop will be heavily biased toward the open structure. Previous single-molecule studies from our laboratory are consistent with protein stabilization of k-turn structure occurring by conformational selection  will be unable to form k-turn structures in the absence of protein, so k-turn formation unaided by L7Ae binding cannot stabilize the stem–loop structure and translation can initiate until the k-turn elements are bound and folded by L7Ae. These elements were identified in both Crenarchaeota  and Euryarchaeota  that diverged very early in the evolution of life (>3 Gy ago) ( Gy ago) , so this Gy ago) . This to Gy ago) . In addi Gy ago) . It is tS. acidocaldarius, T. kodakarensis, a putative k-turn has been found in the mRNA of a bicistronic gene encoding the box C/D proteins NOP5 and fibrillarin  and Cy3  were attached to the 5′ termini of the oligonucleotides as phosphoramidites in the final cycle of the synthesis, as required.RNA oligonucleotides were synthesized using the solid-phase phosphoramidite chemistry implemented on an ABI-394 DNA/RNA synthesizer. The ribonucleotide phosphoramidites, Pac-A-CE, Ac-C-CE, iPr-Pac-G-CE, and U-CE, with a t-BDMS protecting groups. Thereafter, samples were cooled on ice for 10 min and 250 µL RNA quenching buffer (Glen Research) was added to stop the reaction. The oligonucleotides were then desalted by application to NAP-10 columns .RNA oligonucleotides were deprotected in 25% ethanol/ammonia solution for 3 h at room temperature and evaporated to dryness. They were redissolved in 115 µL DMSO (Sigma-Aldrich) to which was added 60 µL triethylamine (Sigma-Aldrich) and 75 µL 1 M triethylamine trihydrofluoride (Sigma-Aldrich), and incubated at 65°C for 2.5 h to remove the Oligoribonucleotides were purified by gel electrophoresis under denaturing conditions, using 20% acrylamide: bis-acrylamide (19:1) (Scientific Laboratory Supplies) electrophoresed in 90 mM Tris-borate (pH 8.5), 10 mM EDTA (TBE buffer) containing 7 M urea at 25 W for ∼3 h. Nucleic acids were visualized by UV shadowing and bands corresponding to full-length products were excised and electroeluted into 140 µL 8 M ammonium acetate in TBE at 150 V at room temperature. The RNA was then precipitated with ethanol.Fluorophore-labeled RNA was subjected to further purification by reversed-phase HPLC on a C18 column , using an acetonitrile gradient with an aqueous phase of 100 mM triethylammonium acetate (pH 7.0) (Fisher Scientific). Peak fractions were evaporated to dryness and resuspended in 120 µL ultrapure water.For FRET experiments, duplex species were prepared by mixing equimolar quantities of oligoribonucleotides and annealing in 90 mM Tris-borate (pH 8.5), 10 mM EDTA, and 25 mM NaCl by slow cooling from 95°C to 4°C. Hybridized RNA was purified by gel electrophoresis under nondenaturing conditions in 12% acrylamide: bis-acrylamide (29:1), in TBE, 25 mM NaCl, with buffer recirculation. Electrophoresis was performed at 150 V at 4°C for ∼6 h. Bands containing duplex RNA were excised from the gel and electroeluted into 140 µL 8 M ammonium acetate in TBE at 100 V at 4°C, followed by ethanol precipitation and air-drying at 4°C.A. fulgidus L7Ae cloned into a modified pET-Duet1 plasmid (Novagen) (Escherichia coli BL21-Gold (DE3) pLysS cells (Stratagene), and purified as reported previously (Novagen)  was expreviously .l7Ae 5′-UTR element k-turn sequence . Suitable samples were stored and subsequently used to measure full data sets on beamline I03 of Diamond Light Source (Harwell). Data were processed by XIA2 (A solution of 0.6 mM RNA (19 nt) and 0.6 mM L7Ae in 5 mM Tris-HCl (pH 8.0), 100 mM NaCl, 10 mM MgCl by XIA2 . The res by XIA2 . The cry by XIA2 , one andThe structure was determined by molecular replacement using the k-turn L7Ae complex model extracted from PDB 4BW0. The resulting electron density maps revealed the remaining RNA density and were built de novo on the basis of the difference map. Structural models were built in Coot  and refi2, 100 mM KCl were supplemented with 2.5–10 µM L7Ae where required. RNA was folded by exposure to 85°C for 1 min followed by slow cooling to 20°C. Samples were then incubated at 20°C for 40 h, after which gel electrophoresis loading buffer containing 7 M urea, 10 mM EDTA was added. Partial alkaline digest was performed by incubation of 100 pmol of Cy5-labeled RNA in 20 µL 50 mM Na2CO3 buffer (pH 9.0 at 20°C) at 90°C for 10 min. The reaction was terminated by addition of gel loading buffer at 0°C. Each Cy5-labeled RNA was subjected to cleavage by RNase T1. 100 pmol of RNA was incubated with 5 U RNase T1 in 10 µL 25 mM sodium citrate buffer (pH 5.0 at 20°C) containing 5 M urea, 0.5 mM EDTA for 10 min at 55°C. The reaction was terminated by addition of gel loading buffer. Samples were electrophoresed in a 20% polyacrylamide gel containing 7 M urea. RNA was visualized by using a Typhoon FLA 9500 fluorimager .In-line probing assays were performed as previously described . A totalCoordinates have been deposited in the Protein Data Bank with accession code 6HCT.Supplemental material is available for this article.


Dairy cows in Europe and the United States are increasingly housed indoors year-round. Even cows with pasture access are usually kept inside during the winter and around calving. However, animal welfare scientists and dairy consumers are concerned that full-time housing impacts cattle welfare. We investigated how pasture influences behavioral indicators of wellbeing. Using cow pedometers, we recorded 29 animals’ lying and walking activity during 18 days of pasture access and 18 days of indoor housing. Cattle at pasture had fewer lying bouts but longer lying times, indicating they were more comfortable and less restless. Lying behavior was also more synchronous outdoors, with most of the herd lying at the same time. These results indicate pasture provides a comfortable surface and reduces competition for lying space. Furthermore, cows at pasture walked farther, with potential benefits for their physical health and psychological wellbeing. Our findings contribute to the growing body of evidence that pasture access improves dairy cow welfare. As a society, we must decide whether full-time housing is a price worth paying for dairy products.χ21 = 27.51, p < 0.001), fewer lying bouts , longer lying bouts , and fewer transitions up or down . Herd lying behavior was also more synchronous at pasture . In addition, nightly step counts were higher in the PAS treatment than the PEN treatment . These results suggest pasture access improves dairy cow welfare by increasing comfort, reducing competition and boredom, and facilitating motivated behavior.Dairy cows are increasingly housed indoors, either year-round or for long stretches over the winter and around parturition. This may create health and welfare issues. In cattle, lying and walking are highly motivated, and herds synchronize lying behavior when they have comfortable surfaces and little competition for space. Lying and walking activity can, therefore, indicate good welfare. Using a repeated measures crossover design, we gave 29 Holstein–Friesian dairy cows 18 days of overnight pasture access (PAS treatment) and 18 days of indoor housing (PEN treatment). Accelerometers recorded their lying and locomotory behavior. We measured behavioral synchrony with Fleiss’ Kappa and analyzed the accelerometry data using linear mixed models. Compared to the PEN treatment, the PAS treatment had longer overnight lying durations ( As global consumer demand grows, dairy farming will continue to intensify . HousingHowever, full-time housing raises animal welfare concerns ,9,10. CoLying behavior is a key indicator of cow welfare ,37. In dAs well as impacting lying activity, indoor housing desynchronizes herd behavior in dairy cows ,52,53,54Locomotion also increases at pasture ,50,53,65To date, limited research has investigated the welfare impacts of restricted pasture access, where cows are fed indoors for part of the day ,73. MoreThis study was approved by Queen’s University Belfast’s School of Biological Sciences Animal Research Ethics Committee . In accordance with the Animals (Scientific Procedures) Act 1986, experimental procedures were described to a Home Office inspector beforehand and deemed not to require a license. Animal welfare was prioritized throughout.This study was carried out during summer 2018 at the Agri-Food and Biosciences Institute (AFBI), Hillsborough, County Down, Northern Ireland . The experiment involved 29 autumn-calving, lactating, Holstein–Friesian dairy cows . We performed a power analysis to determine sample size; an effect size of 0.5, significance level of 0.05, and power of 0.8 required 27 individuals. All subjects were kept at pasture prior to the study, but they were housed inside for eight weeks pre-testing to standardize conditions (see below). The indoor housing consisted of two adjoining pens (each 13.3 × 8.5 m). Both pens had 16 cubicles, fitted with rubber mats, and concrete standing and walking areas, cleaned by an automatic scraper system six times per day. The building was naturally ventilated, with no additional ventilators servicing the pens. Cows had ad libitum access to grass silage offered daily at approximately 09:00 via an open feed barrier along the front of each pen, and ad libitum access to fresh water. They were milked in a rotary parlor twice daily (06:30 and 15:00).Before the experiment, all 29 subjects were fitted with an IceTag . IceTags are commercially available hind-leg activity monitor sensors that distinguish lying from standing and record step counts using a tri-axial accelerometer . The herbage was generally high quality, although lower quality in the second period. Across the study, mean oven dry matter (DM) content was 226.8 (SD 27.8) g/kg, mean crude protein content was 216.5 (SD 24.2) g/kg DM, and mean metabolizable energy content was 11.4 MJ/kg DM . When the first period was complete, the cows swapped treatments and the procedure was repeated. The group at pasture first (PAS-first) had 14 study animals  and the group at pasture second (PAS-second) had 15 study animals . Including the three individuals without IceTags, both groups contained 16 cows in total. As part of a larger project, other welfare measures were collected during daytime housing, including performance in cognitive bias tasks, eye temperature, and health scores [Before the study, all 32 cows were housed in the indoor pens without pasture access for eight weeks. The pens were connected and the animals were managed as one group. When the experiment began, cows were pseudorandomly divided into two groups of 16  and the pens were visually isolated from each other using plywood sheeting. The experiment used a two-period crossover design with two concurrent treatments: 18 days of overnight pasture access (PAS) and 18 days of full-time housing (PEN) . Throughout the study, both groups were kept in the indoor pens with the same silage type from 10:00 to 16:00. Cows in the PEN treatment were also housed overnight, with ad libitum access to silage. Cows in the PAS treatment had 18 h of daily pasture access, from approximately 16:00 (post-afternoon milking) until 10:00 the next morning. This covered the main grazing times , daytime lying duration (h/daytime), number of lying bouts (bouts/24 h), lying bout duration , overnight transitions up or down (transitions/night), daytime transitions (transitions/daytime), and overnight step count (steps/night). Overnight data were analyzed from 16:30 to 09:30 and daytime data from 10:00 to 15:00, so effects of walking to and from pasture were eliminated. Lying duration was the total time the IceTag was horizontal, lying bouts were the duration from vertical to horizontal and back again, and steps were counted whenever cows lifted their tagged leg. Lying duration, transitions, and step counts were recorded in 15-min intervals; bout length data were only available per day. To measure synchrony, we classified cows as lying if they spent over half the 15-min interval lying (>449 s). We compared the binary lying data (either lying or not) between herd members within each interval. To our knowledge, this automated method is a novel way to assess behavioral synchrony (further detailed below).P-values were extracted using a Wald’s test, with p < 0.05 considered statistically significant. Data are presented as means ± standard error.We analyzed the data in R . Data were checked for normality by plotting histograms; transformations were applied where these improved the distribution. We fitted general linear mixed effects models (GLMMs) using maximum likelihood (ML), including all interactions. To improve the models’ fit to the data, we removed interactions in a stepwise fashion and selected models with the lowest Akaike information criterion (AIC) values. We re-ran these models using the restricted maximum likelihood (REML) approach. We fitted separate models for the following response variables: overnight and daytime lying duration, number of lying bouts, lying bout duration, overnight and daytime transitions, and overnight step count. The fixed effects were treatment, treatment order (either PAS first or second), and cow age , whilst cow ID and day number were random effects. Based on AIC values, we removed interactions from the models for overnight lying duration , number of lying bouts , overnight transitions , daytime lying duration , and overnight step count . Lying bout data included substantial outliers: the longest was 14.25 h, but the second longest was 7.77 h. As both values were from the same individual on consecutive days, we ran the bout models on both the original dataset and data within two SD of the mean. This did not change the significance level of any results, so only the original dataset model is reported. Because overnight step counts were positively skewed, we applied a square-root transformation to these data. Step counts are provided alongside walking distance, based on a stride length of 1.5 m .F), a test of inter-observer reliability for >2 raters [F > 0 indicates agreement greater than chance, KF = 0 indicates chance levels, and KF < 0 indicates disagreement greater than chance. Fleiss’ Kappa assumes independent data [F values for each treatment group and analyzed them as the response variable in a GLMM .We measured lying synchrony using Fleiss’ Kappa coefficient of agreement . Finally, we extracted step counts from 70,429 measurement intervals .We collected data from 29 cows across 36 days. However, the IceTags did not record every study day or 15-min interval for every subject, reducing the number of measurement days (number of cows × number of study days) and measurement intervals  available for analysis. For both overnight and daytime lying duration, we collected data from all individuals for every day (1044 measurement days). Overnight lying durations were compiled from 70,429 measurement intervals  and daytime lying durations were compiled from 20,759 measurement intervals . We gathered data on lying bout frequency and duration from 1034 measurement days (106 measurement days unrecorded). To measure transitions, we collected data for all subjects from every study day (1044 measurement days). Overnight transition data came from 70,429 measurement intervals  and daytime transition data came from 20,759 measurement intervals . For lying synchrony, we calculated 36 herd Kχ21 = 27.51, p < 0.001; χ21 = 0.94, p = 0.333), nor age , nor the treatment × treatment order interaction were significant . For daytime lying durations, there was no significant effect of treatment , treatment order , or age . There was a treatment × treatment order interaction . Daytime lying times increased with age at pasture, but decreased with age in indoor housing. Neither the group × age interaction  nor the three-way interaction reached significance .Cows with pasture access had significantly longer overnight lying durations than cows indoors  or duration of lying bouts . Age also had no effect on bout frequency  or length . However, there were significant treatment × treatment order interactions for number  and duration of lying bouts . Both groups had more and shorter lying bouts in their first treatment.PAS cows had fewer lying bouts than PEN cows  nor age affected transition frequency . Nonetheless, there was a treatment × treatment order interaction . In the PAS-first group, subjects transitioned more at pasture than inside, whereas PAS-second cows had fewer transitions at pasture. There was also a significant treatment × age interactions ; transition frequency increased with age in the PAS treatment and decreased with age in the PEN treatment. For daytime transitions, treatment , treatment order , and age were not significant , but the treatment × treatment order interaction persisted . There was no treatment × treatment order interaction .In terms of lying synchrony, Kχ21 = 2946.31, p < 0.001; χ21 = 9.68, p < 0.005). Step counts also decreased with age . Furthermore, the treatment × treatment order interaction was highly significant . PAS-first cows had a smaller increase in step count at pasture than PAS-second cows. The treatment × age interaction was also significant . At pasture, step counts decreased with age, whereas they increased with age indoors.Compared to the PEN treatment, overnight step counts were higher in the PAS treatment (PAS: 1548.45 ± 22.22 steps, 2.32 ± 0.03 km; PEN: 571.43 ± 9.76 steps, 0.86 ± 0.01 km; We investigated how pasture access and indoor housing affect dairy cows’ lying and walking behavior as indicators of their welfare. In a two-period repeated measures crossover experiment, we compared activity between these two management systems using accelerometers. Pasture access increased behaviors associated with wellbeing in cattle and reduced signs of discomfort, displacements, and poor health. Overnight lying durations were longer at pasture, whilst there was no difference in daytime lying durations when both groups were in indoor housing. Lying is a highly motivated behavior which is important for cow welfare, so our results support previous work that cattle are more comfortable at pasture ,40,41,43The lying data indicate that pasture provided a more comfortable surface than cubicles, and more lying space than fully-stocked indoor housing. Cows in the PAS treatment were less restless, with fewer but longer lying bouts, and fewer overnight transitions. Longer lying bouts reflect increased cow comfort . MoreoveOur findings also suggest boredom can be a welfare issue for cattle housed indoors. In animals, boredom is an aversive state that arises from general under-stimulation, rather than the frustration of any specific need or motivation . SubjectContrary to the overall lying results, both groups displayed signs of discomfort during the first testing period. The PAS-first group had longer daytime lying durations, more and shorter lying bouts, and more overnight transitions at pasture compared to indoor housing—results that were opposite to the PAS-second group. We attribute this to heat stress ,105. DesThe PAS treatment’s higher overnight step counts indicate that cows at pasture were healthier and satisfying a behavioral need, which indoor housing constrained. Previous studies have also found pasture access increases walking, because gait improves , feedingAs lying and walking behavior indicated welfare was better when cows had access to pasture, we hope future research identifies the factors responsible . This co® assessment protocol for dairy cattle [Nevertheless, going outdoors has health and welfare benefits, such as exposure to natural light . Exercisy cattle , Wagner y cattle  identifiy cattle .Finally, this study had several limitations. We did not control for grass intake in the PAS treatment, but diet influences cow behavior ,122. MorWe performed a repeated measures crossover experiment to determine how overnight pasture access affects behavioral indicators of dairy cow welfare. As predicted, lying durations were longer at pasture than in indoor housing. Herd lying behavior was also more synchronous outside, and partitioned into fewer but longer lying bouts, with fewer transitions up or down. This suggests pasture was a more comfortable lying surface, reduced competition for lying space, and allowed cows to lie when and where they wanted. However, we found several unexpected treatment × treatment order interactions. Cows that went outside first were more restless at pasture than in indoor housing. We attribute this to heat stress and recommend providing shelter at pasture, depending on local climatic conditions. Additionally, overnight step counts were higher in the pasture treatment, which may benefit cattle physically and psychologically. Reduced lying and walking durations also suggest boredom is an issue in indoor housing, as cows have nothing to do for much of the day. Collectively, our results indicate overnight pasture access improves dairy cattle welfare.


Sample storage for downstream RNA analysis can be challenging in some field settings, especially where access to cryogenic materials or refrigeration/freezer facilities are limited. This has limited RNA-based studies on African malaria vectors collected in the field. We evaluated RNA quality after storing mosquito samples in three different sample preservation media over a 4-week period. Storing mosquito specimens in cold (4°C) media significantly improved yields of intact RNA. Our results indicate commercially available products perform well in keeping RNA integrity as advertised. Moreover, absolute ethanol may be an economical alternative for sample preservation that can be utilized in some resource-limited settings. Several protocols have been published for preservation and extraction of genetic material from field collected samples4. Along with these protocols, there are products available to preserve nucleic acids from field collected specimens. These products include Allprotect Tissue Reagent  and RNAlater . These reagents can stabilize tissue samples to maintain RNA content for one (RNALater) to six months (AllProtect) at mildly cold (4°C) temperatures. The duration can be increased to over one year if samples are stored in colder (-20°C) temperatures.Samples to be used for downstream RNA analysis (e.g. RNA-Seq) are typically preserved by snap-freezing using liquid nitrogen or dry ice and then stored at -80°C until RNA extraction5. Unfortunately, the preservation of genetic material for expression studies based on field samples is difficult, and cryopreservation is often not possible. This is particularly applicable to field collections ofAnopheles mosquitoes, which are the prime vector of malaria parasites6 and exist in remote areas of Africa.Optimal preservation of field collected samples to be used for gene expression studies require high quality nucleic acid, requiring preservation and stabilization of the RNA moleculeAnopheles coluzzii mosquitoes from the UC Davis Vector Genetics Laboratory insectarium were subjected to various sample preservation conditions, as listed inA total of 54 laboratory-reared7.Following a four-week sample preservation period, RNA was extracted from each mosquito sample using the Qiagen AllPrep DNA/RNA Mini Kit  employing the manufacturer's protocol. The RNA concentration was measured using a Qubit RNA High Sensitivity kit and Qubit 2.0 instrument  using the manufacturer’s protocol. The RNA fragment size distribution was examined using the Agilent High Sensitivity RNA Analysis kit and TapeStation 4200 instrument , and the dominant peak size and proportion of long (>1000 bp) fragments were recorded. Typical RNA integrity number (RIN) which measures the 28S and 18S rRNA ratio was not used due to negligible 28S peaks, which is typical for insect RNA extractsscipy module version 1.2.08 in theJupyter notebook9 version 4.1. environment. Plots were generated using Matplotlib version 3.1.010.Mann-Whitney tests were conducted using theUnderlying data11. Preservation conditions that resulted in the highest concentration of longer RNA fragments (>1000 bp) were considered to be best for downstream genetic analysis, as opposed to those resulting in degraded RNA (fragment size < 1000 bp). As expected, storage at 4°C generally preserved RNA integrity better than 28°C. There were no significant differences in total RNA concentration or dominant peak size between samples stored in AllProtect™ or RNALater™ at either storage temperature  and proportion of long (>1000bp) RNA fragments (62.2–74.9%) among the three preservation media tested . The only significant difference was a lower concentration of RNA in ethanol compared with the other preservation solutions .Absolute ethanol did not preserve RNA integrity at 28°C, with only 16.9% (±10.1 STD) of RNA content composed of 1000 bp or longer fragments. However, the peak RNA fragment size for samples stored in absolute ethanol at 28°C was 869 bp (±73 STD) showing little variation  yet simiOverall, samples stored in RNAlater™ or AllProtect™ at 4°C provide satisfactory preservation of RNA content from field collected samples after 4 weeks in storage. Absolute ethanol may provide an economical alternative in resource-constrained field settings. Currently in the USA, AllProtect™ is available at ~$6.5/mL, RNAlater™ at $0.9-1.4/mL, and 200 proof lab grade ethanol at $0.1-0.6/mL. When stored at 4°C, absolute ethanol may be a viable alternative to commercially available products. Although RNA stored in ethanol at 28°C will degrade faster, it nonetheless maintained fragment sizes over 800 bp after 4 weeks in storage. Future evaluation of RNA quality utilizing real time PCR or RNA-seq may be necessary to elucidate whether ethanol is indeed an adequate sample preservation solution for RNA preservation. For practical applications, keeping specimens in a commercial RNA storage solution at 4°C maximizes maintenance of RNA integrity.https://doi.org/10.17605/OSF.IO/BRNPV11.Open Science Framework: Sample storage condition testing for RNA preservation.This project contains data on RNA source, storage, concentration, dominant peak size and quality from each sample assessed in this study.Creative Commons Attribution 4.0 International license (CC-BY 4.0).Data are available under the terms of the This article addresses the efficacy of commercially available RNA preservation media and absolute ethanol at two temperatures, room temperature (28°C) and cold (4°C). The article focuses upon a critical topic that is the success of preservation of samples for downstream RNA analysis, particularly to find a reliable source in limited field source settings. The outcome of this study has direct application to a number of fields, including the study of malaria vectors which are often collected in preservation limited settings with a complete lack of freezer facilities for long periods. This paper is a significant addition to the literature and has been addressed well. The selection of only a 4 week testing period is short, however, I feel the outcomes of this study can be immediately applied in a number of research fields, particularly research on mosquito disease vectors, as most field collections do not extend past such a period. By including absolute ethanol and a two RNA-preservative media options, this enables the covering of a cheaper and readily available option as well as other more stable, but more expensive and may be difficult to obtain, options for regions where snap-freezing is not an option.More specific comments: The authors covered the problem, objective and study highlights well in the abstract and state that absolute ethanol is a viable option in resource-limited settings.Anopheles coluzzii, 9 individuals and the 4 week period. This would be of interest to researchers who would replicate the methodology or adapt it for their sample and preservations needs. I commend the authors on including RNA concentration as well as fragment size distribution analysis, offering a comprehensive effect of the preservation method on RNA integrity. I can highly appreciate that this was a direct study for the preservation of malaria vectors in the field which is predominantly in resource limited regions. It would complement the methods to include reasoning on selection of insectary-reared The results of the study are clearly and concisely described, and significance provided. The most important results are communicated and basis for conclusions are of high standard. The figures are understandable and visually descriptive. It is excellent that the authors further include an expense comparison for the appreciation of the use of absolute ethanol in funding and resource limited studies, as well as highlight the need for further evaluation of the preservation methods for real time PCR and RNA-seq. Overall this is a worthy article which is a good addition to literature, and has direct application for RNA preservation.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. This is a useful methods paper to help clarify any misconceptions researchers might have about what is strictly necessary in order to preserve genomic specimens. I feel like this information could be highly useful for field researchers but also as information to help students just starting research projects. Overall, I don't have many comments to make. The sample size is somewhat small but appears statistically valid. The one thing that would have been really nice to see is a comparison of the study findings to RNA degradation under ideal conditions (-80) as well as with no preservation methods - just dry on the table.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.


We have previously developed and described a method for measuring RNA co-locations within cells, called Proximity RNA-seq, which promises insights into RNA expression, processing, storage and translation. Here, we describe transcriptome-wide proximity RNA-seq datasets obtained from human neuroblastoma SH-SY5Y cell nuclei. To aid future users of this method, we also describe and release our analysis pipeline, CloseCall, which maps cDNA to a custom transcript annotation and allocates cDNA-linked barcodes to barcode groups. CloseCall then performs Monte Carlo simulations on the data to identify pairs of transcripts, which are co-barcoded more frequently than expected by chance. Furthermore, derived co-barcoding frequencies for individual transcripts, dubbed valency, serve as proxies for RNA density or connectivity for that given transcript. We outline how this pipeline was applied to these sequencing datasets and openly share the processed data outputs and access to a virtual machine that runs CloseCall. The resulting data specify the spatial organization of RNAs and builds hypotheses for potential regulatory relationships between RNAs. Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11627397 Most protein-coding RNAs will be exported swiftly from nuclei. Some transcripts however reside within nuclei and are frequently localized in proximity of their encoding gene. This is achieved by chromatin retention through interactions between chromatin-bound proteins or the genome itself and the RNA molecule or by a very short half-life of the RNA and its prompt degradation in the close vicinity of the gene2. Such spatial restraints can have implications for RNAs regulating the expression of other genes, by limiting the number of accessible target genes in 3-dimensional space to the immediate neighbourhood of the regulatory RNA. For example, Xist RNA represses transcription specifically of one X chromosome thereby relying on the local retention to the X chromosome territory4. Malat1 and Neat1 are architectural, relatively stable, non-coding RNAs integral to membraneless and transcription-permissive bodies scattered throughout the nucleoplasm6. However, these structures are assembled co-transcriptionally at the gene loci of the respective non-coding RNAs8. The property of RNA and proteins to separate from surroundings and to form bodies to compartmentalize cellular tasks can further specify RNA localization but becomes detrimental for cells when mutations in molecules resident to such structures are acquired that lead to irreversible aggregation and disease states, as observed for example for RNA repeats9.The positioning of RNA molecules and the spatial organization of transcriptomes in cells is poorly understood to date. Nascent RNA emerges from its encoding gene during synthesis, and genome folding and gene positioning therefore determines the spatial point of origin for any RNA molecule. After completion of transcription and co-transcriptional processing, a molecule can diffuse freely in nuclei11. However, DNA-sparse nuclear regions frequently escape chromosome conformation measurements. For example, a major phase-separated compartment in the nucleus, the nucleolus, encompasses up to 10% of the nuclear volume but has been virtually invisible to HiC, due to the low overall genome but high repeat sequence content within these structures. To capture such DNA-sparse blind spots we devised Proximity RNA-seq, which identifies the co-localization of RNA pairs and groups through in-droplet barcoding of RNA molecules in subcellular, crosslinked particles. The method applied to nuclei identifies RNA-containing structures as exemplified by nucleoli and other bodies, estimates relative distances of transcripts to such cellular landmarks and provides a proxy of local RNA density as reported in the accompanying publication12.The elucidation of the spatial nuclear organization based on sequencing has been pushed forward by chromosome conformation capture HiChttps://osf.io/mwd73)13. The virtual machine, running a Linux operating system, has CloseCall and all its dependencies and genome files installed. Finally, we propose RNA network visualizations, which represent RNA-RNA proximities and RNA density.Here we describe the structure and characteristics of Proximity RNA-seq datasets obtained from human cell nuclei and provide further information on the analysis. In particular, we explain the rationales behind the computational steps and describe output files at different stages and the usage of the pipeline. Three biological replicates were separately generated and analysed before being merged into a large dataset in order to derive statistical significance estimates for RNA proximities through the comparison with Monte Carlo randomisations. The datasets can be re-analysed by the reader, and aid in building hypotheses on spatial RNA organization and regulation within cells. For users to become familiar with CloseCall, we set up a publicly accessible virtual machine and provide a test dataset  containing 10% fetal bovine serum (Hyclone) and Streptomycin, Penicillin (Thermo Fisher Scientific). Cells were crosslinked at 70–80% confluency. The culture medium of cells growing in a 15 cm dish was replaced by 19.8 ml pre-warmed 1x PBS, and 0.2 ml freshly prepared 10 mM ethylene glycolbis(succinimidylsuccinate)  in DMSO was added drop-wise for 1 mM final concentration. Cells were incubated for 10 min at 37 °C. 1.4 ml 16% formaldehyde (Agar Scientific) were subsequently added to the 15 cm dish for a final concentration of 1% and the incubation was extended for another 10 min at room temperature. To quench crosslinking 3.5 ml 1 M glycine were added and cells were scraped immediately and pelleted in a 50 ml falcon tube at 210 × g for 5 min at 4 °C. Cell pellets were washed once with 1x PBS supplemented with 125 mM glycine, once with 1x PBS only. Cell pellets were flash frozen in liquid nitrogen and stored at −80 °C until use.Cell pellets, processed as one pellet from a single 15 cm dish per tube, were thawed on ice in 1 ml 20 mM Tris pH 7.2, spun and resuspended in ice-cold 1.5 ml hypotonic lysis buffer  supplemented with 1x Complete, EDTA-free protease inhibitor cocktail (Roche Applied Science) and 0.5 units/µl SUPERase IN RNase inhibitor (Thermo Fisher Scientific). Cells resuspended in lysis buffer were incubated for 30 min on ice with occasional mixing. The homogenate was spun at 2 krpm for 5 min in a benchtop centrifuge at room temperature to enrich nuclei. Pelleted nuclei were then resuspended in SDS washing buffer  supplemented with inhibitors as listed for the lysis buffer and incubated for 10 min at room temperature in a thermoblock with constant mixing at 750 rpm. Then Triton X-100 was added for a final concentration of 1.7% and the incubation continued for 10 min. Nuclei were washed once in 10 mM Tris pH 7.2, 5 mM NaCl, 0.5 mM EDTA, 1% Triton X-100, supplemented with inhibitors as specified above, and once in the same buffer with only 0.05% Triton X-100. Nuclei were resuspend in 0.2 ml wash buffer with 0.05% Triton X-100 and sonicated in 15 ml falcon tubes using a bioruptor UCD-200 sonicator (Diagenode) with power set to medium and cycles of 10 seconds “on” followed by 10 seconds “off” at 8 °C. The integrity of nuclei was inspected after each sonication cycle by light microscopy and using trypan blue staining. Sonication was stopped once the large majority of nuclei were disrupted, usually after 3–5 cycles. Sonicated nuclear homogenates were flash frozen in liquid nitrogen and stored at −80 °C until use.To estimate RNA and DNA content and fragment length crosslinks in samples were reversed and nucleic acids purified. To extract DNA, 20 µl of nuclear homogenate were supplemented with the following reagents to final concentrations of 50 mM Tris pH 8.0, 50 mM NaCl, 2 mM EDTA, 0.2% SDS and with 5 µl proteinase K  for a total volume of 40 µl. DNA extraction mixes were first incubated for 4 hours at room temperature followed by 2 hours at 70 °C. 2 µl RNase A  was added and samples were incubated for 1 hour at 37 °C. DNA was then purified by phenol/chloroform extraction, followed by salt/isopropanol precipitation and resuspended in 10 µl nuclease-free water (Ambion). To extract RNA, the following reagents were added to 20 µl of nuclear homogenate to reach final concentrations of 100 mM sodium citrate pH 6.2, 2 mM EDTA, 0.2% SDS and supplemented with 5 µl proteinase K for a total volume of 40 µl. RNA extraction mixes were incubated for 4 hours at room temperature followed by 1 hour at 70 °C. 1 ml Trizol LS (Thermo Fisher Scientific) was added and RNA isolated according to the manufacturer’s manual and resuspended in 10 µl water. RNA and DNA content and fragment length were measured by a spectrophotometer (NanoDrop) and agarose gel electrophoresis.High-complexity barcode libraries on magnetic beads were generated by PCR amplification in emulsion droplets of individual random DNA barcode templates on beads with one of the two PCR primers immobilized.8 magnetic streptavidin beads  were transferred into a polypropylene tube (Treff), captured on a magnetic rack and washed in high salt buffer . The beads were then resuspended in 35 µl high salt buffer and 6 µl dual-biotin PCR primer R  was prepared on ice in a 1.5 ml DNA LoBind tube (Eppendorf) by combining 943 µl water, 128 µl 10x PCR buffer I , 25 µl dNTPs (stock: 25 mM dNTP each), 32 µl MgSO4 , 32 µl primer F (100 µM stock), 40 µl of 1 μM non-biotinylated primer R  and the sample was mixed by pipetting. The sample was incubated in a thermocycler for 2 min at 94 °C, 2 min at 80 °C, followed by incubations for 2 min at every degree from 75 °C to 61 °C, 10 min at 60 °C and 2 min at 55 °C, 50 °C and 45 °C. Beads were washed once in high salt buffer, resuspended in 1x Accuprime PCR buffer I, pre-warmed at 67 °C, and incubated for 3 minutes at 67 °C. The washes and incubations were repeated two more times. The fraction of barcoded beads was then determined by FACS with settings for APC 670/14 nm. Batches with 40–60% barcoded beads passed quality control.Random tails were then added to 3′ ends of barcodes in bulk reactions for each bead batch. First, unused primers on beads were digested by an exonuclease I treatment  at 37 °C for 90 min. Beads were then washed 1x in 1% SDS buffer, 1x in TLE buffer with 1% Triton X-100 and 1x in TTLEB. To remove untemplated adenosine overhangs added by Taq polymerase, beads were incubated for 30 min at 20 °C in 10 µl NEBNext End Repair Reaction Buffer, 5 µl NEBNext End Repair Enzyme Mix (NEB) and 85 µl water. Wash steps were repeated as outlined after exonuclease I treatment. Beads were then subjected to a T7 exonuclease treatment in 20 µl NEB 4 buffer, 10 µl T7 exonuclease (NEB) and 170 µl water for 15 min at 25 °C to generate single-stranded barcodes immobilized via their dual-biotinylated 3′ ends, which are inert to exonuclease activity. The same wash steps as described above were repeated. To add random bases to barcode ends on beads, a primer with a 5′ random overhang was hybridized to the primer sequence at the 3′ end of barcodes, and the overhang used as template to introduce 3′ random bases to barcodes. Beads were resuspended in a Pfx polymerase mix (Thermo Fisher Scientific) consisting of 10 µl 10x Platinum Pfx buffer, 84 µl water, 3 µl 10 mM nucleotides, 2 µl 50 mM MgSO4, 1 µl random tail primer  and 0.5 µl RNase A  in 5 µl 10x RNaseH buffer l (Thermo Fisher Scientific) and 43.5 µl water for 30 min at 37 °C. Beads were then washed as described above and resuspended in TTLEB.Two batches of beads were used for one Proximity RNA-seq experiment with nuclear homogenate equivalent to 50 ng of reverse-crosslinked and purified RNA. The beads were resuspended in 30 µl TTLEB and freshly prepared Actinomycin D (Sigma) in DMSO was added for a final concentration of 6 ng/µl to inhibit reverse transcriptase activity on DNA templates. Possible aggregates of beads were disrupted by extensive pipetting, followed by sonication using a bioruptor UCD-200 sonicator (Diagenode) with power set to medium for 2 cycles of 5 sec “on” followed by 5 sec “off”. A 160 µl reverse transcription (RT) mix  contained 32 µl 5X First-Strand Buffer, 8 µl 10 mM dNTP Mix (10 mM each nucleotide), 8 µl 0.1 M DTT, 2 µl RNase Inhibitor, 0.32 µl BSA for a final concentration of 0.04 µg/µl (NEB), 1.6 µl of MgCl3′ cDNA ends on beads were dGTP/ddGTP-tailed to provide complementarity for the C-tailed, second Illumina primer sequence. The first Illumina primer site is present as a flanking sequence 5′ to the barcode in random barcode templates. Beads were resuspended in 5 µl 10x TdT buffer (NEB), 5 µl cobalt chloride, 2.5 µl of 100 µM dGTP/ddGTP mix ), 5 µl TdT enzyme  and 32.5 µl water and incubated for 20 min at 37 °C. Beads were washed 1 × 1% SDS buffer, 1x in TLE buffer with 1% Triton X-100, 1x in 10 mM Tris pH 8.0, 0.5 M NaCl, 0.5 mM EDTA, 0.05% Triton X-100, 2x in TTLEB. cDNA was then amplified using Accuprime HiFi Taq pol (Thermo Fisher Scientific). Beads were resuspended in 5 µl 10x Accuprime buffer I, 42.5 µl water, 0.5 µl RP1_long primer ), generating a SAM format file of positions of barcode alignments on the reference barcode scaffold. The cases with multi-mapping of barcodes to the virtual barcode scaffold identified barcodes that derived from the same initial barcode sequence but likely acquired sequence changes throughout the experimental protocol or during sequencing. The positions on the virtual barcode scaffold that shared multi-mapped barcodes were collapsed into one barcode group.Barcodes were first trimmed to 20 bases by removing 3 bases at either end as we observed that sequences could be offset by typically one base. Barcodes with low-complexity sequence content, i.e. the same nucleotide 13 or more times in a 20 bp sequence, were discarded. Removal of low-complexity barcodes led to a reduction of the population of barcodes encompassing a very large, likely artifactual, group of transcripts. CloseCall furthermore applied a maximum barcode group size threshold. This threshold is determined by modelling the barcode group sizes as a Poisson distribution . Barcode groups of a size so large that they would have been expected to occur with a probability of less than 0.001 were removed from the dataset. In addition, the pipeline filtered out barcode sequences similar to adapter sequences. The extraction of the barcode sequence enables a transcript to be allocated to a particular nuclear RNA-containing particle. However, since sequencing errors in barcodes do occur, we expected occasional splitting of actual, proximal RNAs into separate barcode groups. To overcome this problem, a virtual barcode scaffold of all the sequenced barcodes was created. All unique, trimmed barcode sequences were concatenated into a single virtual barcode scaffold, with each individual barcode separated by a stretch of 24 undetermined nucleotides (i.e. Ns). CloseCall used the alignment tool Bowtie215 to map cDNA with default parameters and known splice-sites (GRCh38.78) to split reads across exon junctions. After mapping, reads were assigned to transcripts. The inherent ambiguous organization of transcriptomes required a custom curated transcriptome annotation and a series of priority rules for overlapping transcripts12. CloseCall takes as input an annotation feature file, a tab-delimited text file listing ENSEMBL Human Genome 38 (Ensembl 78) entries with chromosome, start position, end position, strand and feature name of all genes/transcripts. rRNA repeat sequences were masked (i.e. bases were replaced with Ns) in the reference genome FASTA file. Then, a 45S-pre-rRNA sequence was incorporated in our genome assembly as a separate chromosome. On mapping, rRNA reads now aligned uniquely to that chromosome. Other repeat classes were not N-masked in the input FASTA file, but rather the locations of these repeat elements were marked in the custom genome annotation file CloseCall takes as input. Reads multi-mapping to these regions were allowed by the pipeline. Specifically, these regions were: 5S, HY1, HY3, HY4, HY5, U1, U2, U3, U4, U5, U6, U7, U8, U13, U14, U17, BC200, tRNA , 7SLRNA and 7SK. The genomic coordinates of these elements were obtained from repeat masker, Human Genome 38, http://www.repeatmasker.org. Uniquely mapping reads and reads multi-mapping to any of the repeat classes included in the annotation are retained by CloseCall. Other multi-mapping reads are discarded. To enable consistent allocation of reads to genomic features, we developed a series of rules for read-to-transcript assignments. Firstly, repeat regions took priority, even if they overlapped with other features. Consequently, any read overlapping a gene and region defined as a repeat was assigned to the repeat. After defining repeat regions, the forward and reverse strands were processed independently. Thus, a feature allocation to the forward strand was not represented on the reverse strand at the same coordinates. Regions in which two or more features overlapped on the same strand were considered ambiguous and were left unclassified and removed from the annotation. However, features contained wholly within another feature were prioritised. In such cases, the internal feature is used to specify the region of overlap. For example, many small-nucleolar RNAs are contained within larger genes and form an abundant component of nuclear Proximity RNA-seq datasets. After annotation processing, CloseCall produces a tab-delimited text file of the genome annotation to be used subsequently by the pipeline. Using the mapped coordinates, reads were then allocated to their relevant feature. Each transcript is only represented once per subcellular particle and barcode group as it cannot be distinguished whether a single RNA molecule has been primed and reverse-transcribed multiple times at different positions along the molecule or whether multiple copies of the same transcript were present. Consequently, if multiple identically barcoded reads mapped to the same feature, this was recorded as one transcript observation called a proxy read. Using proxy reads for the comparison of the fractions of detected genes and of reads within genes, overlapping exons and in sense orientation to the annotation between all three experiments showed very similar results This file lists all barcoding and co-barcoding events obtained after performing the necessary mapping and quality control steps. It reports the barcode ID and transcript name and feature coordinates and serves as the Monte Carlo simulation input.Mapping and QC summary file (*anaconda_summary_results.txt)This file collates the key metrics into one file to allow the user to assess easily the quality of a Proximity RNA-seq dataset. The file reports the pipeline steps, such as the percentage of reads containing the fixed primer sequence, the number of unique barcode groups, the mapping efficiency and the degree of PCR duplication as shown in Table Monte Carlo Simulation file This file lists all the pairwise RNA proximities in a dataset, the frequency with which they occurred in the observed dataset and in the Monte Carlo simulations.Valency table The file lists each transcript and the number of times it was observed in barcode groups of size 1, 2, etc. Transcript valency is derived as described in the next section.12. The valency data is available on GEO, accession: GSE12973216, file: GSE129732_local_RNA_connectivity.xlsx, and lists valency 1, 2 and 3 z-scores for pool 2, 5 and 8 for each feature.The so-called valency is an estimate for transcript-specific RNA density or connectivity. Valency 1 represents the instances a transcript has been detected singly on a bead, valency 2 represents co-barcoding between two different transcripts on a bead, valency 3 stands for a total of 3 transcripts with the same barcode on a bead and so on. The Perl script feature_valency_distribution.pl uses the Simulation Formatted file, [*.simulation_formatted.txt.gz], and outputs a list containing each feature and the number of times it was observed as valency 1, valency 2 etc. We then selected transcripts with the sum of valency 1, 2 and 3 greater than 10 proxy reads. For each transcript, counts in valency 1, 2 and 3 were divided by the sum of all three valencies of that given transcript. Subsequently, the transcriptome-wide distributions of the three valencies were separately transformed into z-scores. Transcripts were then assigned to high and low valency classes, respectively. High valency transcripts were defined based on z-scores of valency 1 < 0 and a mean of valency 2 and 3 z-scores > 0. Low valency transcripts had z-scores of valency 1 > 0 and a mean of valency 2 and 3 z-scores < 0. Only transcripts assigned to high and low valency classes in pool 2, pool 5 and pool 8 Proximity RNA-seq datasets were retainedCorrelation coefficients between different Proximity RNA-seq datasets using the number of proxy reads or the number of detected co-barcoding events between two transcripts as variables, shown in Fig. 17 with valency assignments as a separate attribute file. Relative Entropy Optimization (EntOpt)18 on -log10 p values of RNA proximities was used for network layout. For each transcript the mean of valency 1, 2 and 3 was calculated for all three replicates . The average of the means then defined node size and colour. Node and edge size and colours are further specified in Fig. Pairwise RNA proximities with p value < = 0.1 were imported into Cytoscape 3.7.116.Sequenced data from Proximity RNA-seq experiments are available/stored on Gene Expression Omnibus accession: GSE129732The GEO entry provides sequencing data and the following processed output files: GSE129732_Monte_Carlo_Simulation_Results.txt.gz lists all frequencies of observed and simulated RNA pairs and simulation-derived p values, GSE129732_Pools_2_5_8_simulation_format_combined_file.txt.gz reports all barcoding and co-barcoding events, listing barcode ID, transcript name and coordinates, and GSE129732_local_RNA_connectivity.xlsx lists transcript-specific valency, i.e. RNA density or connectivity.Sequencing libraries p2, p5 and p8 are replicates from individual SH-SY5Y cell cultures. In Fig. 12, respectively, showed low correlation in co-barcoding to other samples. Pool 2, pool 5 and pool 8 were then merged and estimates of statistical significance for pairwise RNA proximities were derived through CloseCall Monte Carlo simulations.After data processing we first compared read quality and statistics of replicate datasets . The transcribed precursor is processed into mature 18S, 5.8S and 28S transcripts, which are then incorporated into ribosomal subunits Fig. . As expeets Fig. , presuma20, and two transcripts in the nucleoplasm more distal to nucleoli12. All pairwise associations (p <= 0.1) of the four transcripts were visualized as networks with edge line thickness indicating -log10 p values and node colours depicting valency, i.e. local RNA density or connectivity of transcripts . As expected, SNORD17 was found in proximity to high valency transcripts, mostly other snoRNAs, recapitulating the RNA composition and high RNA density of nucleoli . The following non-core Perl modules should also be installed: Math::Round, String::Approx (this may require libc6-dev), PDL::LiteF, PDL::Stats (for PDL::Stats::Distr), GD::Graph (which may require libgd-gd2-perl).The Perl Data Language (pdl).http://bowtie-bio.sourceforge.net/bowtie2).A recent version of the sequence aligner Bowtie2 (A recent version of HISAT2 (ccb.jhu.edu/software/hisat2)21A recent version the NGS contamination and multi-species screen tool FastQ Screenhttps://www.r-project.org)R (GNU Scientific Library (GSL). We recommend using GSL 2.4.CloseCall needs the appropriate working environment and installed software tools to operate. Alternatively, the virtual machine might be used (see below). A computer with the following setup should be able to run CloseCall.The CloseCall master script executes the pipeline sequentially. The mapping and QC component of the pipeline may be run by typing:perl CloseCall –map –config [configuration file] [FASTQ files]The paths to the (i) HISAT2 reference genome index files basename, (ii) annotation gene list file and the (iii) position of the splice sites should be stored in the configuration file, as shown in the example below.gene_list: /home/CloseCall/Data/human38_repeats_RNA45S5.txt.gzgenome: /home/CloseCall/Data/hg38_LSU_SSU_Masked_RNA45S5splice_sites: /home/CloseCall/Data/Hg38.78.hisat2_splices.txtOn a Grid Engine compute cluster, the MonteCarlo simulation may also be run via the Perl master script, with the command:perl CloseCall –simulations [number of simulations] [simulation formatted file]This will qsub the jobs to the compute cluster. To generate a random dataset, specify the additional option –random.Alternatively, the Monte Carlo simulation Jar file may be run directly with the command:java -jar anacondamontecarlo.jar [simulation formatted file] [number of simulations]To compare randomisations of the observed dataset against randomisations of one random dataset, i.e. the background distribution, run the command:perl multiple_testing_correction.pl –control [random Monte Carlo results] –results [real Monte Carlo results]To calculate the valency frequency distribution for each transcript, run the following command on the simulation formatted file of interest:perl feature_valency_distribution.pl [simulation formatted file]https://osf.io/mwd73/)13. To that site we have also uploaded the genome index files and annotation files required for processing the test dataset, or indeed other human proximity RNA-seq samples.So users may acquaint themselves with CloseCall, we have made available a virtual machine running the pipeline on a Linux operating system. All the CloseCall dependencies required for running the software have been installed on the virtual machine and there is also a test dataset, which, owing to its small size, may be processed quickly to allow users to become familiar with the various steps CloseCall undertakes when running. Having a working version of the pipeline should aid users in troubleshooting any difficulties they may have with setting up the software on their own computer. By comparing the results obtained after processing the test dataset using the virtual machine with the results generated when processing on an external device, it is possible for users to verify that their CloseCall setup is functioning correctly. The virtual machine can be obtained from the Open Science Framework website . VirtualBox allows an operating system, with all of its installed software, to run in a special environment on top of a user’s existing operating system. VirtualBox is compatible with Windows, Linux, Macintosh, and Solaris hosts and is freely available as Open Source Software under the terms of the GNU General Public License (GPL) version 2.The virtual machine should be run using the software VirtualBox (


C. elegans PVD neuron. Here we report that the actin-polymerizing proteins UNC-34(Ena/VASP), WSP-1(WASP), UNC-73(Trio), MIG-10(Lamellipodin) and the Arp2/3 complex effect dendrite retraction in the self-avoidance response mediated by UNC-6(Netrin). The paradoxical idea that actin polymerization results in shorter rather than longer dendrites is explained by our finding that NMY-1 (non-muscle myosin II) is necessary for retraction and could therefore mediate this effect in a contractile mechanism. Our results also show that dendrite length is determined by the antagonistic effects on the actin cytoskeleton of separate sets of effectors for retraction mediated by UNC-6(Netrin) versus outgrowth promoted by the DMA-1 receptor. Thus, our findings suggest that the dendrite length depends on an intrinsic mechanism that balances distinct modes of actin assembly for growth versus retraction.Dendrite growth is constrained by a self-avoidance response that induces retraction but the downstream pathways that balance these opposing mechanisms are unknown. We have proposed that the diffusible cue UNC-6(Netrin) is captured by UNC-40(DCC) for a short-range interaction with UNC-5 to trigger self-avoidance in the  C. elegans have suggested a model of self-avoidance in which the UNC-40/DCC receptor captures the diffusible cue UNC-6/Netrin at the tips of PVD dendrites where it interacts with the UNC-5 receptor on an opposing sister dendrite to induce retraction. Here we report genetic evidence that UNC-5-dependent retraction requires downstream actin polymerization. This finding evokes a paradox: How might actin polymerization drive both dendrite growth and retraction? We propose two answers: (1) Distinct sets of effectors are involved in actin assembly for growth vs retraction; (2) Non-muscle myosin interacts with a nascent actin assemblage to trigger retraction. Our results show that dendrite length depends on the balanced effects of specific molecular components that induce growth vs retraction.Neurons may extend highly branched dendrites to detect input over a broad receptive field. The formation of actin filaments may drive dendrite elongation. The architecture of the dendritic arbor also depends on mechanisms that limit expansion. For example, sister dendrites from a single neuron usually do not overlap due to self-avoidance. Although cell surface proteins are known to mediate self-avoidance, the downstream pathways that drive dendrite retraction in this phenomenon are largely unknown. Studies of the highly branched PVD sensory neuron in  C. elegans .–13.11–136/Netrin . Here weC. elegans to mediate axon guidance underscores the key role of the actin cytoskeleton in growth cone steering . Eac. EacPVD:VD::GFP)  9]. Sel. SelPVD:VD::GFP) . In the  contact , Fig 3D.endrites  [9]. Herunc-6 mutant in L4 stage animals  in PVD . PV. PVC. eln in PVD . These pn in PVD . Similarn in PVD . Our fintraction . Alternaact-4, or specific components (WRC and TIAM/GEF) that promote actin polymerization, suggest that dendritic outgrowth depends on actin assembly , NW434 , TV17,200  , CX1248 [KyEx3482(pdes-2::TBA-1::mCherry+coel::RFP)] [twnEx382] [Additional strains used in this study: NC1404 [l::RFP)] , CLP928 8::gfp)] .unc-34(gm104)V; wdIs52, NG324 , +/szT1 lon-2(e678) I; HR1184 [nmy-1(sb115) dpy-8(e130)/szT1 X], NC2726 , unc-73(rh40)]; wdIs52.Additional strains generated for this study: NC2580 wdEx1011 (pF49H12.4::myrUNC-5::GFP)], was produced by microinjection of plasmids pLSR18 (pF49H12.4::myrUNC-5::GFP), pmyo-2::mCherry and pCJS04 (pF49H12.4::mCherry).NC3284 [wdIs98 (pF49H12.4::ACT-1::GFP)] was produced by microinjection of plasmids pLSR03 (pF49H12.4::ACT-1::GFP) and pceh-22::GFP and integrated as previously described .NC3048 [wdEx967 (pF49H12.4::mCherry::UNC-34)] was obtained by microinjection of plasmids pCJS78(pF49H12.4::mCherry::UNC-34) and pmyo-2::mCherry.NC3085 [wdEx972 (pF49H12.4::LifeAct::GFP)] was acquired by microinjecting plasmids pLSR06 (pF49H12.4::LifeAct::GFP) and pmyo-2::mCherry.NC3090 [pF49H12.4::nmy-1(+) + pF49H12.4::nmy-1(-))] was obtained by microinjection of pLSR09 (pF49H12.4::nmy-1(+)), pLSR10 (pF49H12.4::nmy-1(-)), pmyo-2::mCherry and pCJS04 (pF49H12.4::mCherry)NC3029 [(wdEx969 (pF49H12.4::GFP::Linker::NMY-1)] was produced by microinjecting plasmids pLSR11 (pF49H12.4::GFP::Linker::NMY-1), pCJS04 (pF49H12.4::mCherry) and pmyo-2::mCherry.NC3087 [wdEx1009 (pF49H12.4::GFP::Linker::MLC-4DD) [NC3283] was obtained by microinjection of plasmids pLSR17 (pF49H12.4::GFP::Linker::MLC-4), pCJS04 (pF49H12.4::mCherry) and pmyo-2::mCherry.nmy-1 genomic region was amplified from pACP01 (pF49H12.4::NMY-1::mCherry) with overlapping regions corresponding to pCJS95 (pF49H12.4::GFP::CED-10::unc-10 3’UTR). We also PCR amplified pCJS95 with primers overlapping the nmy-1 genomic sequences to swap CED-10 with NMY-1. We then used the NEB site-directed mutagenesis kit to insert a 24-nucleotide glycine rich linker (see nmy-1. See We used the Clonetech in-fusion HD cloning kit (Cat # 638910) to build this plasmid. The nker see  67]. Th. Thnmy-1mlc-4 genomic region was amplified from wild-type (N2) DNA using primers with overlapping adapters complementary to pLSR11 (pF49H12.4::GFP::Linker::NMY-1). pLSR11 was amplified with primers containing adapter sequences complementary to mlc-4. The amplified fragments were combined for the infusion cloning to replace nmy-1 with mlc-4. We then used the NEB site directed mutagenesis kit to change MLC-4 codons for Serine 18 and Threonine 17 to nucleotide sequences that encode aspartatic acid (D). The resultant pLSR17 plasmid was confirmed by sequencing.We used the Clonetech in-fusion HD cloning kit (Cat # 638910) to construct this plasmid. The Animals were immobilized with 15 mM levamisole/ 0.05% tricaine and mounted on 2% agarose pads in M9 buffer as previously described . Z stackAnimals were immobilized with 0.4 mM levamisole and mounted on 10% agarose pads in M9 buffer. Z stack images were captured using a Hamamatsu sCMOS camera on a iSIM microscope  equipped with a 100X, 1.45 NA objective. Images were deconvolved and processed using Metamorph and Fiji/ImageJ.Animals were immobilized with 0.4mM levamisole and mounted on 10% agarose pads in M9 buffer. Volumes over time were captured using an automated TiE inverted fluorescence microscope platform with an X1 spinning disk head (Yokogawa) and DU-897 EM-CCD (Andor Technology), piezo-electric Z stage (Mad City Labs) and Apo TIRF 100x 1.49 NA oil immersion objective . Analysis of fluorescence intensity was accomplished using NIS-Elements and Fiji/Image J software.L2-L3 larvae were immobilized with 0.4mM levamisole and mounted on 10% agarose pads in M9 buffer for imaging with the spinning disk confocal microscope. Z-stacks of PVD dendrites were imaged at either 1 min or 1.30 minute intervals with the 100X 1.49 NA oil immersion objective. PVD dendrites  undergoing outgrowth with a succession of rapid extensions and retractions during the length of the time lapse videos were analyzed. NIS elements was used for measurements of LifeAct::GFP from a 1μm ROI at the tips of growing dendrites. In the same videos, fluorescence intensity was measured for an identical 1μm ROI of PVD branches  that were not undergoing outgrowth. Fluorescence intensity measurements for the outgrowth and no-outgrowth datasets were normalized against the maximum overall LifeAct::GFP value .Student’s t test was used for comparisons between 2 groups and ANOVA for comparisons between three or more groups with either Tukey posthoc or Bonferroni correction for multiple comparisons. Kolmogorov-Smirnov test was performed for comparisons between frequency distributions of 3° dendrite length and gaps between 3° dendrites Figs .S1 Methods(DOCX)Click here for additional data file.S1 Figunc-6 (B) L4-stage larvae. PVD morphology was visualized with PVD::GFP or PVD::mCherry markers. PVD cell body marked with an asterisk. (A) 1°, 2°, 3° and 4° dendritic branches and single axon (blue arrowhead) are denoted. (B) Red arrowheads point to overlaps between adjacent 3° dendrites that failed to self-avoid in unc-6 mutants. Scale bars are 5 μm. C) Summary of self-avoidance in 3° PVD dendrites denoting growth, contact and retraction. (D) Model of self-avoidance mechanism involving reciprocal contact-dependent repulsion mediated by UNC-6/Netrin and its receptors, UNC-40/DCC and UNC-5 [(A-B) Representative images and tracings of PVD sensory neurons in wild-type (A) and nd UNC-5 .(TIFF)Click here for additional data file.S2 Figunc-34, unc-73, wsp-1 and PVD::mCherry::UNC-34;unc-34. Defective 1° dendrites show altered alignment and/or extension defects. Mutations in unc-34 and unc-73 but not wsp-1 result in defective 1° dendrite outgrowth and fewer 2° dendrites. Note that expression of UNC-34::mCherry in PVD restores 3° self-avoidance (unc-34 mutant. Note premature termination of 1° dendrites (red arrowheads). (D) Representative image and drawing of PVD branching defects in a tiam-1/GEF mutant at the L4 stage. Scale bars are 10 μm. Mutant alleles are unc-34(gm104), unc-73(rh40), wsp-1 (gm324) and tiam-1(tm1556).Quantification of 1° dendrite outgrowth and (B) number of 2° dendrites in wild-type, voidance  but does(TIFF)Click here for additional data file.S3 Fig(A) Zeiss Airyscan images of PVD simultaneously labeled with PVD::LifeAct::GFP (green) and PVD::mCherry::UNC-34 (Magenta). Merge shown on right. Insets denote PVD dendrites (B). White arrows indicate 2°, 3°, and 4° dendrites. Scale bar is 10 μm.(TIFF)Click here for additional data file.S4 Figt-2) [Schematic (left) of adjacent 3° dendrites and representative time lapse series  of PVD::mCherry and PVD::LifeAct::GFP in 3° dendrites showing self-avoidance response (Condition 1). Point of contact is indicated by an asterisk and period of contact denoted with dashed blue outline. Scale bar is 10 μm. (B) Schematic depicting ROIs for fluorescence intensity measurements at the tips of adjacent (left vs right) 3° dendrites that undergo contact and at an adjacent non-contact (control) region. (C) Graphical representation of the change in fluorescence intensity at each time point vs that of 2 time intervals (t-2) before contact (t = 0); Measurements were normalized to fluorescence intensity at t-2 or (Ft-2) . Normali(TIFF)Click here for additional data file.S5 Fig(A-D) Fluorescent intensity traces wild-type PVD dendrites during 3° dendrite self-avoidance. Fluorescent intensity measurements of PVD::LifeAct::GFP and PVD::mCherry were acquired at either 1 min (A-B) or 1.3 min (C-D) intervals from a 1μm region at the tips of the growing and contacting left and right 3° dendrites . Measurements were normalized against the maximum intensity during a ~10 minute interval that includes at least one contact event. The gap between the left and right 3° dendrites undergoing contact was determined from the cytoplasmic mCherry signal and plotted against time. The period of contact  corresponds to a minimum value for the gap (0–0.14μm) between contacting left and right 3° dendrites. (E) Representation of 3° dendrites with color schemes to indicate left and right 3° dendrites and 1μm regions quantified.(TIFF)Click here for additional data file.S1 MovieImages of PVD::GFP were recorded (late L3-early L4) at 15 sec intervals with a 100X objective in a Nikon spinning disk microscope see . The len(MP4)Click here for additional data file.S2 MovieImages of PVD::GFP in the PVD::MYR::UNC-5 strain were recorded (late L3-early L4) at 15 sec intervals with a 100X objective in a Nikon spinning disk microscope see . The ent(MP4)Click here for additional data file.S3 MovieImages of PVD::mCherry (left) and PVD::LifeAct::GFP (right) and were collected at 1.3 min intervals with a 100 X objective in a Nikon spinning disk microscope see . The ent(MP4)Click here for additional data file.S4 MovieImages of PVD::mCherry (left) and PVD::LifeAct::GFP (right) and were collected at 1.3 min intervals with a 100 X objective in a Nikon spinning disk microscope see . The len(MP4)Click here for additional data file.S1 Data(ZIP)Click here for additional data file.