To detect functional somatic mutations in tumor samples, whole-exome sequencing (WES) is often used for its reliability and relative low cost. RNA-seq, while generally used to measure gene expression, can potentially also be used for identification of somatic mutations. However there has been little systematic evaluation of the utility of RNA-seq for identifying somatic mutations. Here, we develop and evaluate a pipeline for processing RNA-seq data from glioblastoma multiforme (GBM) tumors in order to identify somatic mutations. The pipeline entails the use of the STAR aligner 2-pass procedure jointly with MuTect2 from genome analysis toolkit (GATK) to detect somatic variants. Variants identified from RNA-seq data were evaluated by comparison against the COSMIC and dbSNP databases, and also compared to somatic variants identified by exome sequencing. We also estimated the putative functional impact of coding variants in the most frequently mutated genes in GBM. Interestingly, variants identified by RNA-seq alone showed better representation of GBM-related mutations cataloged by COSMIC. RNA-seq-only data substantially outperformed the ability of WES to reveal potentially new somatic mutations in known GBM-related pathways, and allowed us to build a high-quality set of somatic mutations common to exome and RNA-seq calls. Using RNA-seq data in parallel with WES data to detect somatic mutations in cancer genomes can thus broaden the scope of discoveries and lend additional support to somatic variants identified by exome sequencing alone. Cancer is among the leading causes of death worldwide, with 8.7 million deaths in 2015 . As a geThe actual cancer-driving mutations need to be differentiated from somatic passenger mutations caused by impaired DNA repair mechanisms, inherited or de novo germline mutations and neutral polymorphisms, and artefacts that can arise from sequencing errors, PCR or misalignment . MoreoveTo detect mutations in a tumor sample, whole exome sequencing (WES) has generally been favored over whole genome sequencing (WGS) for its relatively low cost, although dropping costs of WGS encourage its use for somatic mutation identification . Whole-tHere, we assessed the utility of RNA-seq for somatic mutation detection in glioblastoma multiforme (GBM), the most common and deadliest form of adult primary brain cancer. GBM shows a median overall survival of only 14–15 months . StandarWe developed a new pipeline to detect somatic mutations in RNA-seq data, combining RNA-seq alignment using a STAR 2-pass procedure with somatic mutation detection using MuTect2 for variant calling . Varianthttps://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001389.v1.p1). For GBM data from TCGA, BAM files resulting from alignment were downloaded from the Genomic Data Commons data portal and used directly in the subsequent analysis pipeline since they were already aligned with STAR. To evaluate variants, two databases were used: dbSNP (6 variants), and the COSMIC database v78  collected at St. David’s Medical Center  after written informed consent, in a study approved by the Institutional Review Boards of St. David’s Medical Center and of the University of Texas at Austin . For WES and RNA-seq, we used the exome capture kit NimbleGen SeqCap EZ  and the NEBNext small RNA kit , respectively. Sequencing was carried out at the NGS Core Facility of the MD Anderson Cancer Center Science Park on an Illumina HiSeq 2500. Data is available in dbGaP  is an optional step that improves variant calling by filtering out method-specific artefacts, by doing variant calling (MuTect2) on a set of normal samples . The samt_lod_fstar filter). homologous_mapping_event is a filter that detects homologous sequences and filters out variants falling into sequences that have three or more events observed in the tumor. clustered_events is a filter for clustered artifacts. str_contraction filters out variants from short tandem repeat regions. alt_allele_in_normal filters out variants if enough evidence is shown of its presence in the normal sample (NLOD threshold > 2.0). multi_event_alt_allele_in_normal filters out a variant when multiple events are detected at the same position in the matched-normal sample. germline_risk filters out variants that show sufficient evidence of being germline based on dbSNP, COSMIC and the matched-normal sample . panel_of_normals filters out variants present in at least two samples of the panel of normals.Based on the TLOD score, MuTect2 will reject a variant when a specific TLOD > 6.3 threshold is not reached, suggesting insufficient evidence of its presence in the tumor sample (ANNOVAR (v.2016Feb01)  was usedp > 0.05) or Deleterious (p < 0.05). Low scores typically occur in highly conserved regions that tend to be intolerant to most substitutions. On the contrary, unconserved regions tend to be more tolerant to AA changes. SIFT indel has been developed for scoring frameshifting indels  change is to use SIFT , which ug indels , which rFunctional analysis through hidden markov models (FATHMM v2.3) also uses homologous protein sequences to find the probability of an amino acid substitution at a given position. The algorithm relies on Hidden Markov models to compute probabilities, its final scores being a ratio between the probability of the wild-type and the mutant AA. The version used here  also incA set of 29 genes that were shown to be the most frequently mutated genes in GBM by a TCGA study on 91 GBM samples  was usedIn the majority of samples, RNA-seq showed fewer uniquely mapped reads than WES ; Fig. S1TLODfstar). Interestingly, TLOD scores of COSMIC variants were higher than non-COSMIC variants  by MuTect2 were higher in RNA-seq than WES for all TCGA samples . The oveAs expected, the RNA-seq/WES intersection was enriched in variants from coding regions (89.7% of coding variants), since both RNA-seq and WES query exons. RNA-seq data also showed an unexpected level of intronic/intergenic variants. Intronic mRNA reads could partly come from unspliced RNA (pre-mRNA). A previous study has indeed detected many intronic mRNA variants, which could come from inefficient splicing in cancer . On the In theory, heterozygous mutations would show an AF around 0.5. However, somatic mutations from cancer cells are expected to appear at lower frequencies, as tumor samples are heterogeneous and not pure clones. Moreover, CNVs can lead to gain/loss of chromosomes and/or duplications of genes . RNA-seqFor each of the three classes of variants—WES-only, Intersection and RNA-seq-only—we examined the proportion in different genomic regions , potentiThere were 63 genes with RNA-seq-only variants that were mutated in five or more tumors, and many genes from this group have been implicated in cancer . For exaThe SD01 GBM tumor sample had no corresponding matched normal to enable reliable distinction of somatic mutations from germline variants, so it presented unusual challenges. However, it is worthwhile to consider such samples because often, RNA-seq data may be available from a tumor without a corresponding matched normal sample. The total number of variant called in SD01 was much higher than the average TCGA sample (by 10.5-fold for RNA-seq and 17.7-fold for WES). SD01 had a similar number of aligned reads as the TCGA samples for both RNA-seq and WES, so the higher number of somatic variants could be in part due to the absence of matched-normal, the small panel of normals used and/or by a higher underlying mutation rate in this specific tumor. MuTect2 variant calling was carried out in tumor-only mode and only relied on TLOD values without distinction between somatic and germline variants. Many dbSNP variants were indeed observed . The disWe used the algorithms FATHMM and SIFT to evaluate the potential impact of somatic variants on protein function in cancer pathways . The FATHMM and SIFT score distributions showed a significant difference only for FATHMM scores between the Intersection and WES-only . Many RN−8). WES showed 101 reads at the same position, giving a probability of only 0.39 of at least one variant read occurring in the WES data . Interestingly, COSMIC has cataloged a different variant, L718M at the same position . The Y-axis shows the proportion of mutations.Click here for additional data file.10.7717/peerj.5362/supp-3Supplemental Information 3The intersection represents 0.15% of dbSNP (b147) variants and 1.65% of COSMIC (v78) variants.Click here for additional data file.10.7717/peerj.5362/supp-4Supplemental Information 4The Y-axis shows the proportion of variants indicated.Click here for additional data file.10.7717/peerj.5362/supp-5Supplemental Information 5The Y-axis shows the proportion of mutations by chromosome.Click here for additional data file.10.7717/peerj.5362/supp-6Supplemental Information 6(A) Proportion of reads before variant calling. (B) Mutation spectrum indicating the type of base substitution in total RNA-seq and WES data. (C) Total number of variants for TCGA samples (averaged over 15 samples). Types of variants are as in Click here for additional data file.


Diaphorina citri, is one of the most damaging pests of the Citrus genus because of its transmission of Huanglongbing, also known as Yellow Dragon disease. In this study, the next-generation sequencing technique was applied to research the ABC transporters of D. citri. Fifty-three ABC transporter genes were found in the RNA-Seq data, and among these ABC transporters, 4, 4, 5, 2, 1, 4, 18 and 15 ABC proteins belonged to the ABCA-ABCH subfamilies, respectively. Different expression profiles of 52 genes between imidacloprid-resistant and imidacloprid-susceptible strains were studied by qRT-PCR; 5 ABCGs and 4 ABCHs were significantly upregulated in the imidacloprid-resistant strain. In addition, five of the nine upregulated genes were widely expressed in adult tissues in spatial expression analysis. The results suggest that these genes may play key roles in this phenotype. In general, this study contributed to our current understanding of D. citri resistance to insecticides.The ATP-binding cassette (ABC) transporters exist in all living organisms and play major roles in various biological functions by transporting a wide variety of substrates across membranes. The functions of ABC transporters in drug resistance have been extensively studied in vertebrates; however, they are rarely characterized in agricultural pests. The Asian citrus psyllid,  The first one was found in prokaryotes. In humans, 48 ABC family members have been identified2. The majority of these proteins are membrane-bound primary active transporters that transport various molecules across all cell membranes by binding ATP3. Based on the components of their ATP-binding domain(s), also known as nucleotide-binding domains (NBDs), they are classified as ABC transporters. Each NBD contains three characteristic motifs: ABC signature C, Walker A box and Walker B box. The function of NBDs is to bind and hydrolyse ATP to provide energy for substrate transportation. In addition, the ABC transporters also contain a transmembrane domain (TMD) which usually consists of five to seven membrane helices and participates in the recognition of the substrates. Some eukaryotic ABC transporters are composed of 2 NBDs and 2 TMDs, known as full-transporters, whereas those with only 1 NBD and 1 TMD are called half-transporters. The latter require either homodimers or heterodimers to form a functional unit5. According to the homology of the NBD sequences, the ABC transporter family is classified into 8 subfamilies, named ABCA-ABCH.The ATP-binding cassette (ABC) transporter family is one of the largest families of membrane proteins and universally exists in all living organisms on Earth7. In arthropods, ABC transporters are usually associated with insecticide resistance by reducing toxic concentrations in cells/tissues10. For instance, ABCG4 correlates with Cry1Ac resistance in Plutella xylostella11. Some genes of the ABCB, ABCC, ABCD and ABCG subfamilies are upregulated in strains of Laodelphax striatellus resistant to chlorpyrifos, deltamethrin and imidacloprid12. ABC transporters  are involved in DDT resistance in Drosophila melanogaster13. In a study of the interaction between permethrin and verapamil (an inhibitor of ABC transporters) in Anopheles stephensi, the toxicity of permethrin is increased approximately 5-fold with the inhibition of ABC transporters; concurrently, the expression levels of ABCB6 and ABCG4 are significantly upregulated14. It has been reported that ABC transporters are associated with the transport and/or resistance to 27 different insecticides belonging to 9 distinct chemical classes of insecticides 16.In recent years, ABC transporters have received increasing attention regarding detoxification. In humans, the overexpression of various ABC transporters in cancer cells can efficiently remove the anticancer drugs from the cells, thus reducing the efficacy of drugs. The development of multidrug resistance (MDR) in cancer cells is one of the major reasons for the failure of cancer chemotherapyDiaphorina citri (Hemiptera: Psyllidae) feeds on citrus flush and transmits Candidatus Liberibacter asiaticus (CLas), a phloem-limited bacterium that infects citrus, that causes Huanglongbing, also known as citrus greening disease or Yellow Dragon disease, a destructive disease of citrus. At present, the application of pesticides is the main way to control the ACP18. However, the long-term use of chemical insecticide has led to the development of varying levels of resistance to almost all common insecticides in the populations of D. citri in many citrus producing areas21. The decreased insecticide sensitivity of D. citri was related to the increased activities of esterases (ESTs), glutathione S-transferases (GSTs), and cytochrome P450 monooxygenases (P450s)24. A recent study showed that four P450s, one GST, and one EST of D. citri were associated with imidacloprid resistance25.The Asian citrus psyllid (ACP), D. citri has not been determined. To identify the ABC transporter genes in D. citri, transcriptome analysis was applied in this study. In total, fifty-three ABC transporter genes were found, which were classified into eight subfamilies (A-H) by phylogenetic analysis. The detailed sequence comparisons of the eight subfamilies with other species  shed light on our understanding of the evolution of the ABC transporter family among the six species. In addition, the expression profiles of these genes in imidacloprid-susceptible and imidacloprid-resistant strains were analysed by qRT-PCR. Our results provide valuable information on the mechanism of insecticide resistance in D. citri, and will facilitate the elucidation of the functions of these genes in this citrus pest.The development of insecticide resistance seriously impacts the effectiveness of chemical control strategies. Therefore, it is necessary to comprehensively understand the mechanism of insecticide resistance. However, as xenobiotic transporters, the role of the ABC transporters in insecticide resistance in D. citri, including 52 unigenes with full-length open reading frame (ORF) sequences and the lengths of these ABC transporters ranged from 594 to 2413 amino acids , and all these genes or fragments can be matched with those identified from the transcriptome data  . DcABCA4 clustered with three insect ABCAs and then aligned with five human HsABCAs .Four ABCA transporters were identified in in DcABCA 2. This includes ABCA1, which transports intracellular cholesterol and phosphatide to lipid-poor apolipoprotein A-I (ApoA-I) to form high-density lipoprotein (HDL)27. The expression of ABCA1 in the hippocampus is positively associated with the severity of Alzheimer’s disease (AD)28. However, the role of the arthropod orthologues of these human ABCAs is currently unclear, but they might be related to lipid transport based on the high conservation of the structure. Injection of dsRNAs of TcABCA-9A and TcABCA-9B, results in approximately 30% mortality with severe defects in pupae and pharate adults of T. castaneum29.In humans, ABCA transporters play important functions in lipid transport and metabolismD. citri, four ABCB transporters were identified, and all of them are half-transporters that comprise one TMD and one NBD. In the phylogenetic tree 32. HsABCB8 is involved in protecting the mitochondrial genome through doxorubicin resistance33. HsABCB10 is an important player in the protection from oxidative stress34. D. melanogaster DmCG4225, a homologous gene of Homo sapiens HsABCB6 was associated with tolerance to cadmium35. DmCG3879 (MDR49) is involved in directing germ cell migration through controlling export of a Drosophila germ cell attractant in a signal peptide-independent manner36. The homologous gene of HsABCB7 in Aedes aegypti is involved in insecticide resistance37.In humans, HsABCB6-8 and HsABCB10 are four mitochondrial ATP-binding cassette transporters. HsABCB6 is associated with multiple cellular functions, including iron homeostasis and porphyrin transport, and is resistant to several cytotoxic agents39. Due to their functions, MRPs are the most well characterized in the ABC transporters subfamily C. All of the human ABCC transporter genes encode full ABC transporters; however, both full- and half-transporters were found in insects40. A human MRP can be classified as a “long” MRP or “short” MRP based on whether it contains a third N-terminal transmembrane domain (TMD0). If it contains a TMD0, it is considered to be a “long” MRP, ; on the contrary, the “short” MRPs include HsABCC4, HsABCC5, HsABCC11, and HsABCC1241. In insects, it has been reported that ABCC is involved in insecticide resistance; for instance, when the nymphs of Nilaparvata lugens are exposed to triazophos, the transcript level of an ABCC shows a significant increase42. In Pediculus humanus, silencing PhABCC4 by RNAi leads to an increased susceptibility to ivermectin43.The C subfamily ABC transporters in humans consist of cystic fibrosis transmembrane conductance regulator (CFTR), membrane-bound sulfonylurea receptors (SURs) and multidrug resistance-associated proteins (MRPs). CFTR (HsABCC7) acts as a chloride channel that is involved in regulating exocrine secretions. SURs  binds sulfonylurea and functions as regulators of potassium channels that play a role in modulating insulin secretion. MRPs (HsABCC1-6 and HsABCC10-12) are considered to be important transporters of xenobiotics due to their ability to transport a wide range of substrates D. citri, five ABCC transporter genes were identified; all genes contained full-length ORFs and encoded full ABC transporters , twenty-three T. urticae ABCCs, and T. castaneum TcABCC-9A. As an orthologue to human MRPs, DmCG6214 is an ATP-dependent, vanadate-sensitive organic anion transporter and transports developmentally significant hormones, such as ecdysteroid and juvenile hormone41. DcABCC2 cluster with three human MRPs , where HsABCC5 and HsABCC11 act as nucleoside transporters; however, the function of HsABCC12 is unknown44. DcABCC3 and DcABCC5 were placed in a large clade containing HsABCC4, a large cluster of T. urticae ABCCs, seven B. mori ABCCs, a cluster of T. castaneum ABCC5s, and ten D. melanogaster ABCCs. HsABCC4 has the ability to transport a wide variety of endogenous and xenobiotic organic anionic compounds out of the cell; these substrates also include molecules involved in cellular signaling2. DcABCC4 clustered with human HsABCC10, DmCG7806, BmABC010636, Tetur03g07840, Btabq004618.1, and TcABCC-4A, and this clade showed clear orthologous relationships. HsABCC10 is known as a drug-efflux pump because it is involved in the transport of amphipathic anions, leading to resistance to a variety of anticancer drugs45. In the transcriptomes of D. citri, the orthologues of CFTR and SUR are not identified.In rs Table , Fig. 2.rs Table , DcABCC146. Two ABCD transporter transcripts were identified in the transcriptomes of D. citri, both of which have full-length ORFs. The same number of ABCDs was also found in the genome of most other insects47  in eukaryotes, resulted in embryonic lethality and slow growth, suggesting that ABCE plays a role in the regulation of translation and transcription48. In humans, HsABCE1 has an important role in HIV-1 assembly49, and HsABCF1 (ABC50) is associated with promoting translation initiation50. In insects, injection of dsRNA specific for T. castaneum TcABCE-3A and TcABCF-2A, led to 100% mortality in the larvae of T. castaneum29.The ABCE and ABCF subfamilies are quite distinct from other ABC transporters because they only contain two linked NBDs and lack TMDs Fig. . In viewD. citri transcriptomes. Most eukaryotes only have one ABCE and three ABCF genes 51. However, full-transporters are widely present in fungi and plants53. The half-transporters have a reverse domain structure with an NBD at the N-terminus and a TMD at the C-terminus (NBD-TMD), while a functional transporter must be dimeric15. In humans, five ABCG transporter family genes have been identified. Among these HsABCGs, four HsABCGs except HsABCG2 were mainly involved in the transportation of dietary lipids, while HsABCG2  has a series of substrates, including anticancer drugs, and acts as an MRP54. Among invertebrates, D. melanogaster ABCG members were first characterized, including brown, scarlet, and white genes55.The ABCG transporter family is present in most metazoan species, fungi and plants. Based on the research of predecessors, ABCG half-transporters were only identified in metazoan species except one ABCG gene in D. citri and represent the largest ABC subfamily in D. citri, all of which possess full-length coding sequences and are in accord with half-transporters with the topology TMD–NBD. In the phylogenetic tree  clustered with potential orthologues of HsABCG1 and HsABCG4 in ABCG clades, where HsABCG1 is involved in regulating the output of cholesterol, while the function of HsABCG4 was not clear56. In humans, HsABCG5 and HsABCG8 form a functional heterodimer and play a role in removing plant sterols from the body56. In the phylogenetic tree, DcABCG9 and DcABCG10 were two orthologous genes of HsABCG5 and HsABCG8, and all the arthropod orthologues of HsABCG5/HsABCG8 showed a head-to-head arrangement, indicating that DcABCG9 and DcABCG10 may have similar functions as HsABCG5/HsABCG8. Six genes (DcABCG12-17) clustered with D. melanogaster white, scarlet, and brown and the orthologues of the other species. In D. melanogaster, white, scarlet, and brown are the best-characterized ABCG genes of arthropods, and scarlet or brown takes part in transporting pigment precursors in the Malpighian tubules and relates to the formation of compound eye colour58. D. melanogaster white mutants show a white-eye colour phenotype, and this phenomenon has also been confirmed in T. castaneum and B. mori59. However, white is also involved in resistance to pesticide, and downregulation of the white orthologues leads to increased Bt resistance in P. xylostella60. In D. citri, DcABCG17 is orthologous to white, DcABCG13 and DcABCG14 are orthologous to scarlet, and three genes  are orthologous to brown. DcABCG11 clustered with B. tabaci Btabq023890.1, T. castaneum TcABCG-8A, D. melanogaster DmCG3327, and T. urticae tetur17g02510. In D. melanogaster, DmCG3327  is capable of modulating the 20E response61, and a similar function has also been found in T. castaneum TcABCG-8A29. DcABCG6 clustered with T. castaneum TcABCG-4C, D. melanogaster DmCG3164, B. mori BmABC005202 and two orthologues of B. tabaci. In T. castaneum, TcABCG-4C-dsRNA injected larvae exhibited a rough cuticle as a consequence of desiccation and shrinkage and rapidly caused death during the quiescent stage, in addition, injection of TcABCG-4C-dsRNA into pre-pupae resulted in death at the pupal stage before the pupal-adult molt, while DmCG3164 performs a similar function in Drosophila62.Eighteen ABCG transporter family transcripts were identified in the transcriptomes of ree Fig. , eight DD. melanogaster and it was then reported that the ABCH subfamily was only found in arthropods, zebrafish Danio rerio and marine medaka Oryzias melastigma63. At present, the ABCH subfamily has not been identified in other species such as mammals, plants and fungi64. We identified fifteen DcABCH genes in the transcriptomes of D. citri, fourteen of them have the full-length ORF. In most insect species, only three ABCH members were found, including D. melanogaster, B. mori and T. castaneum which has an excellent genome sequence, however, a large number of ABCH members were found in three Hemiptera insects  and two species of arthropods (D. pulex and T. urticae)  Table . In the Helicoverpa armigera and Manduca sexta, when the larvae were fed with secondary metabolites, the expression of ABCH subfamily was induced to increase67. In D. melanogaster, cold hardening treatment resulted in a 2-fold increase in the expression level of DmCG3397068, both DmCG9990 null mutants and RNAi-mediated knockdown DmCG9990 are lethal69. In addition, DmCG9990 was also found to be associated with the formation of epidermal barrier70. In T. castaneum, injection of dsRNA specific for TcABCH-9C, the ortholog of DmCG9990, resulted in desiccation and 100% larval mortality and a significant reduction in fertility and the egg hatchability. Furthermore, TcABCH-9C dsRNA treated larvae showed a lack of lipids in the epicuticle, and based on these results, the authors inferred that TcABCH-9C was involved in transport of lipids to epicuticle and promoting the formation of waterproof barrier in epicuticle29. In a recent study, the ortholog of DmCG9990 in Locusta migratoria, LmABCH-9C, were borne out to be associated with transport of lipids to epicuticle and cuticle barrier formation in epicuticle71. In D. citri, DcABCH5 and DcABCH9 are orthologues of DmCG9990 and DmCG33970, respectively  showed high expression levels in the abdomen of adults  are widely expressed in adult tissues of 15. In D. citri, five ABCG transporters were significantly upregulated in imidacloprid-resistant strains, and similar upregulation of expression has also been reported in other insects. For instance, one ABCG transporter was upregulated in the imidacloprid-susceptible Leptinotarsa decemlineata72. Four ABCG transporters were up-regulated in imidacloprid-treated B. tabaci64. In addition to the ABCG transporter, four ABCH transporters were significantly upregulated in imidacloprid-resistant strains. In the green peach aphid, Myzus persicae, an ABCH was upregulated under the stress of pirimicarb73, suggesting that ABCH may also be involved in insecticide resistance in insects. The results indicated a potential implication of these genes in imidacloprid resistance. In addition, five of the nine upregulated genes  were expressed widely in adult tissues, which may demonstrate that the wide expression of ABC transporters may contribute to the transport of exogenous substances such as pesticides. Twenty-seven DcABCs were downregulated in resistant strains. Similarly in P. xylostella, Px006766 (PxABCF3) and Px013659 (PxABCA12) were downregulated in chlorpyrifos-resistant and fipronil-resistant strains51. This may indicate that not all ABCs are involved in detoxification and may be a physiological adaptation to long-term pesticide pressure.In arthropods, ABCB, ABCC and ABCG were the three most reported subfamilies associated with insecticide transport or resistance, and the index of insecticide transport or resistance is mainly based on their expression levelD. citri. In this study, fifty-three genes encoding ABC transporters were identified in D. citri using RNA-Seq and transcriptomic analysis. Among 8 subfamilies, ABCG and ABCH have more members in D. citri. Moreover, nine genes of these two subfamilies were upregulated in the imidacloprid-resistant strain of adult D. citri and five of them were expressed extensively in adult tissues. These results enrich the research content regarding the insecticide resistance mechanism in D. citri and will further facilitate our understanding of imidacloprid-resistance mechanisms in this pest.The major objective of this study was to identify the ATP-binding cassette transporter gene family in D. citri were used in this study: laboratory-susceptible strains and imidacloprid-resistant strains. The laboratory susceptible-strains were collected from Murraya exotica on the campus of South China Agricultural University, Guangzhou, Guangdong Province, China, in 2013, and this population was reared in the greenhouse without exposure to any insecticides. The imidacloprid-resistant strains originate from field populations in Guangzhou, Guangdong Province, China, in 2016, and then they were continuously exposed to imidacloprid to select the resistant strains. A 52.19-fold imidacloprid-resistant strain was obtained through 9 generations of continuous selection via the leaf dip method25. Both strains were kept rearing on M. exotica in a climate chamber  and a 14:10 h (light:dark) photoperiod.Two strains of http://www.insect-genome.com/data/Diaphorina_citri.transcript.fa.tar.gz)76. The raw data of the transcriptomes were submitted to the NCBI Short Read Archive (SRA) database (Submission ID: SRP139008) (https://www.ncbi.nlm.nih.gov/sra/SRP139008)76.The tissues of insects were dissected from 3-day-old adults of laboratory-susceptible strains. A total of 2000 antennas (including a modicum of tissues of heads), 200 heads (antennas removed), 150 thoraxes, 300 legs, 150 abdomens, and 1000 terminal abdomens  were collected from male adults, and the tissues from famale adults had equal numbers. Total RNA from each sample was extracted using TRIzol Reagent . Total RNA samples were quantified and assessed for quality by a NanoDrop 2000 . Transcriptome sequencing was performed on an Illumina HiSeq. 2500 platform , and a total of 143.37 Gb of raw data was acquired. After removing low-quality, adaptor and contaminating sequence reads, 137.22 Gb of clean reads was obtained. The clean data were assembled by Trinity, and 297,614 unigenes larger than 200 bp were obtained, the unigenes were submitted to InsectBase . The candidate ABC transporter genes were reconfirmed by BLASTx analysis with the non-redundant protein sequence (NR) of NCBI (http://www.ncbi.nlm.nih.gov/).The local blast program of BioEdit software was applied to identify candidate ABC transporter genes. The amino acid sequences of http://www.ncbi.nlm.nih.gov/). The ORFs of the genes in each subfamily were aligned using ClastalW to search alternative splicings to confirm the isoforms from the same gene. The NBD and TMD of each potential ABC transporter genes were verified by searching with the Pfam program (http://pfam.xfam.org/)78 and Conserved Domains (http://www.ncbi.nlm.nih.gov/)79. The domains were graphed with the illustrator program DOG 2.0.180. N-glycosylation sites and O-glycosylation sites were predicted using NetNGlyc 1.0  (http://www.cbs.dtu.dk/services/NetNGlyc/) and O-glycosylation81 (G-score > 0.5) (http://www.cbs.dtu.dk/services/NetOGlyc-3.1/) respectively.The open reading frames (ORFs) of the candidate ABC transporter genes were predicted using the ORF finder (D. citri ABCs within ABC classes (A-G), the amino acid sequences of NBDs of D. citri ABC transporters were used to resolve their phylogenetic relationships. When a protein had two NBDs, the N-terminal NBD was used. To analyse the evolutionary placement of ABC transporters in D. citri, comparison analyses among each subfamily of ABC transporters from D. citri, D. melanogaster, B. mori, T. castaneum, B. tabaci, and T. urticae were conducted, and the full-length protein sequences were subjected to phylogenetic analyses (Supplementary data). Sequences were aligned by the ClustalW alignment algorithm82, and MEGA6 was used to construct the neighbor-joining trees with the Poisson model and 1,000 bootstrap replicates83, the dendrograms were viewed in FigTree and edited in Adobe PhotoShop CS6.To classify the position of 84. The spatial expression of these ABC transporter genes was estimated using the Fragments Per Kilobase of transcript per Million fragments (FPKM) method, which is based on the number of uniquely mapped reads85. The FPKM values of each gene were transformed into log2 (RPKM + 1) values, and GraphPad Prism 7.01 was used to generate and visualize the expression profile.Gene expression levels for each tissue sample were estimated by RSEM (RNA-Seq by Expectation-Maximization) (v1.2.6)87. The gene-specific primers were designed by the Primer 3 program (http://elixir.ut.ee/Main/Services) . Three biological replicates were analysed for each experiment. A total of 120 ACP adults  from susceptible and resistant strains were used for qRT-PCR analysis, and three technical replicates were performed in each qRT-PCR reaction.The relative expression of ABC transporter mRNAs in imidacloprid-susceptible and imidacloprid-resistant strains was determined using quantitative real-time PCR (qRT-PCR) with SYBR-green fluorescence. Total RNA was extracted from two strains using TRIzol Reagent . The PrimeScript™ RT reagent Kit with gDNA Eraser  was used for cDNA synthesis, and two reference genes, namely, β-actin (XM_008473151) and α-tubulin (DQ675550), were used as internal controlsSupplementary informationDataset 1


Prebiotic chemistry, driven by changing environmental parameters provides canonical and a multitude of non-canonical nucleosides. This suggests that Watson-Crick base pairs were selected from a diverse pool of nucleosides in a pre-Darwinian chemical evolution process. LUCA is a hypothetical life form obtained from phylogenetic analysis from which all three kingdoms of life originated2. To our understanding, LUCA already possessed the capacity to synthesize specific building blocks such as amino acids, nucleotides and lipids1. While phylogenetics allow us to ascertain such information, any events that had occurred prior to LUCA’s emergence remain in the dark, leaving us with only the possibility of simulating plausible prebiotic scenarios in the laboratory.Life is a highly diverse phenomenon that occupies all conceivable geological niches on Earth. Its development is explained by Darwinian evolution, which must have begun with rudimentary “living” vesicles that at some point transitioned into what we call the last universal common ancestor (LUCA)3 is that RNA was present on the early Earth. RNA, however, is a complex molecule  to pyrite (FeS2)6. High-energy irradiation could also have initiated chemical reactions, particularly when we assume the absence of a shielding ozone layer. Since DNA and RNA are not stable under UV irradiation (λ < 300 nm), photocatalysis was probably more important for the formation of small reactive organic molecules. Without sophisticated DNA/RNA repair mechanisms, oligonucleotides could survive only in niches devoid of UV light7. It is safe to assume that UV light was a thread to early life.Prebiotic chemical processes likely occurred under conditions far away from defined laboratory chemistry. Today, Chemists use special glassware for their reactions and reactants are added step-wise in a tightly controlled manner, often in a protecting atmosphere and regularly in inert solvents. Concentration and temperature are controlled, and importantly, the reaction product is carefully isolated and purified before it is introduced into the next reaction. All of this was impossible on the early Earth. Prebiotic chemistry forces chemists therefore to think about robust reactions that proceed under “dirty” conditions. Reactions that are general enough that they tolerate different temperatures and concentrations, and that are selective enough to proceed even in mixtures are privileged in a prebiotic setting. They are driven by fluctuations of outside physico-chemical parameters such as day–night or seasonal cycles, which provide intermittent wet and dry conditions along with changing temperatures. Drying out could have triggered selective precipitation and crystallization, which leads to purification and concentration to enable successive reactions2 atmosphere composed also of H2O, CO2, H2 and CH4, electrical discharge converts N2 into NO8 which can be reduced to NH2OH and then into NH3. In addition, N2 reacts with CH4 under discharge conditions to give products including HCN, cyanamide and cyanoacetylene9. Under such electrical discharge conditions , but also a variety of RNA modifications5. Under special conditions, even amino acid modified purine nucleosides are generated. Most importantly all these modified purine bases are found today in contemporary RNA, thus strengthening the idea that non-canonical RNA bases are vestiges of our primordial anscestor11.Cyanamide, for example, can give different amidinium compounds by nucleophilic addition, which form low-melting organic salts with nitrosated malononitrile Fig. 5. We fou12. It is known that borates increase the yield of ribose13 and we are sure that with more time and research even better and more selective conditions will be found. We should also not forget that life could have begun with oligonucleotides composed of sugars other than ribose14. Even ribose can exist in a 5- or a 6-membered ring form. The 5-membered arrangement (furanosides) are what today constitute our RNA, but we know from A. Eschenmosers’ seminal work that the 6-membered pyranosidic RNA also produces wonderful double strands with selective base pairing15. It is a riddle, why the thermodynamically less favoured 5-membered furanosides were chosen to create life. One argument is that the 5-membered furanosides are more easily phosphorylated because they possess a very reactive primary hydroxyl group16. Such phosphorylation is needed to stitch the nucleosides together to enable strand formation17. Given that prebiotic RNA nucleosides and consequently RNA strands may have been structurally diverse, containing for example, amino acid modifications, we can envision that some had physico-chemical properties or catalytic properties that offered a survival advantage. Pre-Darwinian evolution may have acted first on molecules rather than living species to select the fittest, initially maybe just the most stable molecules or RNA strands (Fig. The use of ribose as a prebiotic starting material for nucleoside formation is sometimes criticised because no clear prebiotically plausible route to ribose has been found. We still believe that ribose was present on the early Earth and that we have simply to discover the right conditions. It is well known that formaldehyde and glycolaldehyde produce ribose in the formose reaction Fig. , but admnds Fig. . At some


We also evaluated whether SRH's relationship with SMCs is moderated by social capital. The association of SMC and social capital with poor SRH was investigated using multivariable logistic regression. Social capital , mild SMC , and moderate SMC  were found to be associated with poor SRH after adjustment for sociodemographic factors and depression in the initial regression model. SMC was found to have partial interaction effects with social capital which was included in the subsequent regression model. Unlike individuals with no SMC and mild SMC, those who reported moderate SMC did not show decreasing probabilities of poor SRH despite increasing levels of social capital. Nevertheless, this analysis suggests that social capital and SMC are independent predictors of poor SRH. Further research needs to be targeted at improving the understanding on how social capital and SMC moderate and interact with the perception of health in older adults.Subjective memory complaints (SMCs) and social capital were known to be related to self-rated health (SRH). Despite this, no studies have examined the potential interaction of SMC and social capital on SRH. Using data from a cross-sectional health survey of men and women aged 56 years and above ( SMC is common in the elderly, and its prevalence can be as high as up to 50% in older adults –3. The aon of AD . In someon of AD –12; howeon of AD . While non of AD . There ion of AD  and stroon of AD  because on of AD , where tSMC is also associated with poor self-rated health (SRH) –20. SRH Social capital is known for its positive relationship with SRH. Studies have consistently found that higher levels of social capital are associated with good SRH and vice versa , 29. SocLow- and middle-income countries (LMICs) are experiencing population ageing  and faciIn this study, we aim to examine the effects of social capital and SMC on SRH and to investigate if social capital has attenuating effects on SMC's relationship with SRH. The study was conducted in a semirural community setting among older aged adults in Malaysia.The study relies on a secondary analysis of cross-sectional data extracted from a database of older aged individuals who had previously completed a household survey including a health assessment.Participants were part of a larger cohort study in the South East Asia Community Observatory (SEACO), a health and demographic research surveillance site situated in Malaysia. Malaysia is a multiethnic middle-income country undergoing rapid population ageing and demographic transitions, but these developments were not balanced by adequate health and financial policies to reflect the needs resulting from these transitions . Full meSMC was measured using the memory item from the WHO Study on global AGEing and adult health (SAGE)  on a 5-pSRH was measured using the five-point rating scale from the WHOQOL-BREF  item: “HIn the absence of agreed, standardised measures of social capital, we have chosen to operationalise it in a way analogous to Kawachi et al. , who ideDepression is known to be correlated with SMC , 11 and Additional sociodemographic covariates included gender  and female), age (56–64 (reference group), 65–74, and 75 + years), ethnicity , Chinese, and Indian), marital status (not married (reference group) and married), education level , 6 years or less, above 6 years, and others (nonspecified)), and employment status (working (reference group), not working/unemployed, and retired/pension).The proportions of SRH status in each variable were reported as percent. Differences in the participant characteristics according to SRH status were tested using the chi-squared statistic. Binary logistic regression analyses were used to determine the associations between SMC and social capital with poor SRH. Two models were developed: Model 1 tested the association between SMC and social capital with SRH controlling for the sociodemographic covariates, age, ethnicity, gender, education, employment status, marital status, and depression. Model 2 added the measure of social capital and the interaction term of SMC and social capital. Results are reported as odds ratios (ORs) with 95% confidence intervals (95% CIs). The marginal analysis was used to assess and graphed to depict the effect of the interaction term  on the outcome of interest (poor SRH) while simultaneously adjusting for all other covariates in the model. All analyses were undertaken using STATA version 14.0 .The population sample, aged 56 years or older, comprised 6,829 participants. We excluded individuals with incomplete data for any of the variables, resulting in a final sample of 6,421 older adults. That is, only 6% of the total data set contained missing data. An analysis by gender identified no significant differences between those with and without missing data. A higher proportion of participants in the older age group of 75 years and above was also found to have more missing data. The possible implications of this are discussed later. The final analytical sample comprised 3,408 women (53.1%) and 3,013 men (46.9%).n = 2,177 and 22.8% moderate to extreme SMC; n = 1,461). Majority of the study population (more than 60%) reported more favourable values  in all the social capital variables. All the independent variables of interest  showed differences in proportions in the SRH groupings as well.p < 0.001).The results of the analysis show associations between SMC, social capital, and SRH in an older, semirural population from Malaysia. The greater an individual's social capital, the lower the odds of poor SRH. However, there are differences in the effects of social capital on the SMC groups. In the individuals with no SMC and mild SMC, while increasing social capital is associated with lower probability of poor SRH, the predicted probability of poor SRH remained higher in mild SMC in comparison with individuals who reported no SMC. These results are broadly consistent with earlier studies on the relationships of SMC with poor SRH , 60, andInteraction effects of social capital was only partial, only for the moderate SMC group, suggesting that the SMC levels of mild and moderate were distinct from one another . With hiDo you have any memory problems?”) based on a binary response of “yes” or “no” [The strengths of this study include large sample size which allowed the possibility of detecting small effect sizes and population representativeness. The sample size also allowed us to disaggregate the assessment of SMC into multiple levels. Other population studies have primarily assessed SMC . These kinds of differences have been observed in other research ; howeverNevertheless, the analysis does suggest that social capital and SMC are independent predictors of poor SRH. In the context of Malaysia and other LMICs experiencing population ageing, this has potentially important implications. SMC is common in older people. Family social support in LMICs has traditionally been expected to provide the main source of caregiving for the elderly  in the aSMC and social capital were found to be associated with poor SRH. However, in moderate SMC reporters, levels of social capital did not seem to positively affect the probability of poor SRH. Against the backdrop of the evolving social structure in LMICs, there is a need to better understand how social capital contributes to SRH in the elderly, particularly in the elderly who are SMC reporters.


Self-rated health (SRH) have been widely used as a valid indicator of health status at the population and individual level. We aimed to investigate the distribution and correlates of global SRH and age-comparative SRH in elderly Chinese.Survey of 57,693 men and 67,089 women aged 60 years and above was conducted in five rural  and five urban areas  in China between 2004 and 2008. Logistic regression models were used to calculate the relations of different factors with global SRH and age-comparative SRH.Among the participants, 38.33% reported their global SRH as good or excellent while 61.67% as fair or poor, and 17.70% reported better age-comparative SRH while 17.99% as worse. In the multivariate model, compared to women, men tended to report a good global SRH and better age-comparative SRH, urban residents tend to report good global SRH and better age-comparative SRH. The socioeconomic and health behavior factors that were associated with good global SRH and better age-comparative SRH (with varying strengths of association) included: high educational level, high household income, house ownership, quitting smoking by own choices, occasional and current alcohol drinking, overweight, and high physical activity level. The factors that were associated with poor global SRH and worse age-comparative SRH included: quitting smoking by illness, former drinking, underweight, and weight lost ≥2.5 kg in the previous year.We found a moderate level of good global SRH and a low level of better age-comparative SRH among elderly Chinese. We identified a number of demographic, socioeconomic and health behavior factors that were related to SRH measures. Our study emphasizes the importance of incorporating both global and age-comparative SRH measures in future studies, and considering gender inequalities and urban/rural disparity, as well as socioeconomic status and health behaviors as important modifiers of health. Self-rated health (SRH) is an indicator widely used to reflect a person’s general health condition and to measure health inequalities in epidemiology and public health survey. Self-health assessment is a cognitive process , and it As the most populous country in the world, population aging has become a serious social problem in China. It is estimated that the proportion of Chinese people aged 60 and above will reach 28% by 2040 . UnderstTherefore, using data from the China Kadoorie Biobank (CKB), we aimed to investigate the distribution and correlates of good global SRH and better age-comparative SRH in elderly Chinese.n = 388,108).The CKB study is a general population-based prospective cohort study of over 0.5 million participants from 10 diverse areas across China. The detailed study design, sampling strategy and characteristics of the study participants are previously reported . BrieflyIn the baseline survey, detailed information including general demographic characteristics, socioeconomic status, lifestyle factors, mental health and history of chronic diseases was collected by trained interviewers using a laptop-based direct data-entry system. Body height, weight, hip and waist circumference and blood pressures were measured by trained technicians.All the participants had complete data on the variables necessary for the current analysis except for 1 participants with missing values of body mass index (BMI). Therefore, this participant was excluded and a total of 124,782 participants were available for the final analysis. The study was approved by the ethical review committee of the Chinese Center for Disease Control and Prevention  and the Oxford Tropical Research Ethics Committee, University of Oxford (UK). Written informed consent forms were obtained from all participants.n = 5271, 4.22%) and “about the same”  for the second question when analyzing the correlates of age-comparative SRH.In this study, SRH status was assessed using the following two questions: 1) How is your current general health status: excellent, good, fair, or poor? 2) How is your current health status compared with someone of your age: better, about the same, worse, or don’t know? We treated the first question as global SRH and the second one as age-comparative SRH. The global SRH was categorized into two categories in the analyses: good  and poor . We excluded the participants who answer “don’t know” , marital status , education level , annual household income , and house ownership (yes or no).Lifestyle factors included cigarette smoking , alcohol consumption  and weight change during the past year . For former smokers, the main reason for cessation  was also asked. The physical activity level was calculated by adding up metabolic equivalent tasks (METs) for daily work or leisure activities, and was classified into sex-specific quartiles. BMI was calculated as weight in kilograms divided by the square of height in meters and categorized according to the Chinese classification : BMI < 1Seven types of comorbidities including cardiometabolic diseases , respiratory diseases , digestive diseases , musculoskeletal diseases , mental diseases , cancer and other diseases  were self-reported or measured at baseline. We have previously evaluated the relations of various comorbidities with global and age-comparative SRH measures in this cohort and the details were introduced elsewhere .Baseline characteristics by gender were presented by unadjusted means with standard deviations (SD) for continuous variables and unadjusted proportions for categorical variables, and compared using ANOVA and Chi-square tests for continuous and categorical variables, respectively. Logistic regression models were used to calculate the associations between different factors and SRH measures. The variables were adjusted in the following steps: model 1 included age, gender and study location (10 areas); model 2 additionally included social and economic indicators ; model 3 further added health behaviors  and baseline comorbidities. We also conducted a sensitivity analysis of including participants answering “about the same” for the age-comparative SRH, and multinomial logistic regression models were used for the three-category outcome.P value < 0.05 was considered as statistical significance.Stratified analyses were performed according to gender and residential area . Tests for interaction were conducted by adding interaction terms of the study factors and the stratifying variable in the final model. All analyses were performed using SAS 9.3 (SAS Institute Inc.), and a two-sided The baseline characteristics stratified by gender are presented in Table Table Similar findings were obtained in the stratified analyses by gender Table , althougTable In the stratified analyses by gender Table , older aIn the sensitivity analysis of including participants who answered “about the same” for the age-comparative SRH, the results did not change materially  and a low level of better age-comparative SRH (17.70%) among elderly Chinese. In general, men and urban residents were more likely to report good/better SRH compared to women and rural residents. People with high socioeconomic status  and health behaviors  were more likely to report good/better SRH, while people with underweight or significant weight loss in the past year were more likely to report poor/worse SRH. Age was positively associated with age-comparative SRH, indicating a survival advantage.Some previous studies have reported large variations in the level of good/excellent global SRH in Chinese populations, ranging from 25.2 to 47% in different studies , 25, 26.Most participants assessed their age-comparative SRH as “about the same” (60.09%), 17.70% as “better” and 17.99% as “worse”. Similar levels of age-comparative SRH were found in a study among 62,824 residents aged ≥65 years in Hong Kong (72.9% as “about the same” and 25.3% as “better”) . The ChiAmong the demographic variables, we found that older people were more likely to report better age-comparative SRH but similar global SRH, the results of age-comparative SRH were consistent with previous studies, but the results of global SRH were not entirely consistent with previous studies , 19, 20.The relations of marital status with SRH were not consistently reported in the literature , 18, 19,As for health behaviors, we found that healthy lifestyles  were associated with both good global SRH and better age-comparative SRH, although the associations were generally stronger for age-comparative SRH. We did not find significant association with current smoking, while the association with past smoking depended on the reason of quitting smoking. People who quitted smoking because of illness were less likely to report good SRH status, which may reflect the fact that they were in poor physical health status. In our study, people who quitted smoking by their own choices were more likely to report good SRH status, which may be because those individuals paid more attention to their lifestyles and health status. Current drinking was significantly associated with better SRH in our study, particularly for age-comparative SRH, which is consistent with another study in China . The reaIn our study, underweight was significantly associated with poor global SRH and worse age-comparative SRH, consistent with previous studies , 34. On The relations of most variables with the two SRH measures in different subgroups were in the same direction, but the effect sizes varied substantially. We found that socioeconomic status  and health behaviors (smoking and drinking status) had a stronger influence on global SRH and age-comparative SRH in men. Furthermore, socioeconomic status  had a stronger influence on global SRH and age-comparative SRH among rural residents, and health behaviors  had a stronger influence on global SRH and age-comparative SRH among urban residents. The results further confirm the impact of gender inequality and urban-rural economic differences on health, and emphasize the importance of healthy lifestyle to improve personal health among urban residents.For the correlates of the two SRH measures, our study further confirmed that older people tended to report better age-comparative SRH. Overall, the relations of different variables with the two SRH measures were in the same direction, but the effect sizes varied substantially. For example, the associations were generally stronger for age-comparative SRH with socioeconomic status (education level and household income), health behaviors . Although the exact mechanisms are unclear, our study indicated that future studies should incorporate both global and age-comparative SRH to provide complementary information.The strength of this study is that we used both global and age-comparative SRH measures as outcomes and the analyses covered a wide range of demographic, socioeconomic, and lifestyle factors. The study was based on a large and diverse population that provided us sufficient power to detect modest associations. However, several limitations should be noted. First, the study participants were not selected to represent the whole China, and the generalizability of the study findings should be cautious despite the large sample size. We did not include people aged 80 years and older, and again the generalizability to much older populations is unclear given that the age group over 80 years comprises large proportion of people with disability and poor health. However, our major findings of gender inequalities, urban/rural health divide, socioeconomic status and health behaviors as major correlates of health should still be valid and have important policy implications for the current Chinese society, and even for other populations undergoing nutrition and health transitions. Second, many variables were self-reported and the findings may be subject to residual confounding and recall bias if people with different SRH levels recalled things differently, although the participants were face-to-face interviewed by well-trained interviewers. Third, because of the large sample size, even modest effect size could be statistically significant, including the interaction tests; therefore, the results should be interpreted cautiously and we only discussed variables that showed relatively strong associations with the outcomes. Fourth, several factors which have been found to be associated with SRH in previous studies, such as functional ability, cognitive levels and social networks , 34, werWe found a moderate level of good global SRH and a low level of better age-comparative SRH among elderly Chinese. We identified a number of demographic, socioeconomic and health behaviors that were significantly associated with global and age-comparative SRH, with varying degrees and directions of effect estimates. Therefore, future studies should incorporate both global and age-comparative SRH to provide complementary information on the health status of the individuals and population. The significant differences between men and women, urban and rural residents in reporting SRH and the different correlates of SRH also indicate the importance of considering gender and urban/rural inequalities as the upstream determinants of health status. In addition, the consistent and strong impact of high socioeconomic status on SRH also provides evidence for reducing health inequity through social policy to achieve greater social and economic equality in society. Finally, our study also highlights the potential of improving personal and population health by modifiable behavior factors that include smoking cessation and regular exercise.


Recent studies have shown that tissue-specific transcriptomes contain multiple types of RNAs that are transcribed from intronic and intergenic sequences. The current study presents a tool for the discovery of transcribed, unannotated sequence elements from RNA-seq libraries. This RNA Element (RE) discovery algorithm (REDa) was applied to a spectrum of tissues and cells representing germline, embryonic, and somatic tissues and examined as a function of differentiation through the first set of cell divisions of human development. This highlighted extensive transcription throughout the genome, yielding previously unidentified human spermatogenic RNAs. Both exonic and novel X-chromosome REs were subject to robust meiotic sex chromosome inactivation, although an extensive de-repression occurred in the post-meiotic stages of spermatogenesis. Surprisingly, 2.4% of the 10,395 X chromosome exonic REs were present in mature sperm. Transcribed genomic repetitive sequences, including simple centromeric repeats, HERVE and HSAT1, were also shown to be associated with RE expression during spermatogenesis. These results suggest that pervasive intergenic repetitive sequence expression during human spermatogenesis may play a role in regulating chromatin dynamics. Repetitive REs switching repeat classes during differentiation upon fertilization and embryonic genome activation was evident. These dect.org)  and are ect.org) ,9.Both coding and non-coding RNAs play major roles in all cellular processes. In addition to protein-coding RNAs, at present, there are 48 different non-coding and pseudogene classes of RNA documented in the version 27 annotation of the Human Gencode. Approximately 40% of the annotated genes in Gencode correspond to long and short non-coding RNA genes . Non-codThe palette of RNAs appear enriched in certain specific tissues, with each providing a specialized function, e.g., brain—cognitive and functional system level control, and germline—stem cell—defining development . Their cWe have previously shown that unannotated transcripts corresponding to intronic and intergenic regions of the spermatogenic genome are comparatively abundant in human sperm ,28–30. TIn the current study, the RE discovery algorithm was applied from the perspective of the human male germ cell to blastocyst paradigm. A series of spermatogenesis and embryogenesis pattern specific intergenic human REs were identified, indicating that the transcriptome extends well-beyond the annotated genes, including those delivered at fertilization. Tissue-specific REs comprised of intronic and intergenic REs were uncovered and, in some cases, exon boundaries extended. Transcribed genomic repetitive sequences, such as simple repeats, HERVE, and HSAT1, were shown to be associated with RE expression during spermatogenesis, and may play a developmental stage specific role. Similarly, in the human embryo, MER73 was associated with RE transcription at the minor wave of zygotic genome activation and MLT2A1 and SVA-D expressed through the major wave during the transition to the embryonic genome. Overall, this study provides a deeper understanding of the dynamic transcriptome of human sperm, as well as uncovering the possible role of specific repetitive sequences in the spermatogenesis.+) sequences, where appropriate, with parameters ‘LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15’. Reads were aligned to the GRCh38 genome using HISAT2 (version 2.0.6), using the parameters ‘-p10 -max-seeds 30 -k 2’. Read coverage was provided to the RE discovery tool in bigwig format, generated by converting BAM files to bedgraph format, using the bedtools tool genomeCoverageBed, with the parameters ‘-split –bg’, and subsequently bigwig format, using the bedGraphToBigWig program (available from the UCSC Genome Browser utilities). The threshold parameter μ for RE discovery was set to 2.5 reads per million, to minimize their contribution of background noise. Novel REs from each study were combined using custom R commands, which merged overlapping novel REs, re-annotated the merged REs, and added the merged REs to the exonic REs, to produce a collective set of REs. The collective set of REs for the different samples is given in The current study used Gencode release 26 (for GRCh38) and the GRCh38 genome for RE discovery, which is detailed in Supplemental Appendix A. RNA-seq samples used in RE discovery are described in +) and total RNA libraries from oocyte through early embryonic development  was used to calculate differential expression between poly(Aelopment . The LMErrection .+) and total RNA libraries in sperm and testis tissue was determined using a fold-change (fold change +) sperm libraries , peak RE RPKM was 25 RPKM and subsequently used as an expression threshold . REs werExpression patterns across spermatogenic cell types were identified using the R package Mfuzz ,40–42. AREs were assigned as maternally transmitted to the zygote with median zygotic level >10 RPKM, sperm <2 RPKM and oocyte >25 RPKM. REs were assigned as paternally transmitted with moderate confidence with median zygotic level >10 RPKM, sperm >25 RPKM and oocyte <5 RPKM. REs were assigned as paternally transmitted with greatest confidence with median zygotic level >10 RPKM, sperm >25 RPKM and oocyte <2 RPKM.et al. dataset, which consisted of seven fertile human sperm samples, prepared using total RNA , version 3.10. The GeneRanker function (using Genomatix Eldorado version 12-2017) generated the ontological enrichment of signaling pathways.Ontological analysis was performed with the Genomatix software suite  selected and total RNA preparations. A database of REs across the different tissue and types was created by merging the novel REs from each study with the exonic and non-coding transcript REs  and Cufflinks (v2.2.1) to the RE approach for two random sperm samples and two male human cell lines. RNA-seq datasets from human cell lines, i.e. SRR020288 (h1 hESC) and SRR3192556 , provided independent datasets when testing the RE method. Using minimal thresholds of expression , the majority of expressed REs overlap locations of transcripts generated using transcript-building software. Across the four samples, 67–92% of ‘expressed’ REs overlap Stringtie results, and 81–90% overlap Cufflinks results at the above thresholds of expression . NotablyWith the function of the novel REs being unknown, we hypothesized that the novel REs may have regulatory roles. To assess this, REs were overlapped with a series of epigenetic marks and regulatory genomic sequences . For reg+) selected and Total RNAs from a range of cell types that capture the period from fertilization to early embryonic development from oocyte, zygote, 2-cell embryo, 4-cell embryo, 8-cell embryo and morula -selected RNAs from the human oocyte and various stages of early embryonic development, revealed a comparatively lower number of REs detected within the poly(A+) selected fraction -enrichment do not markedly differ -enrichment as compared to the Total RNA fractionation. This suggests that a population of Orphan REs belong to a larger, yet unknown set of polyadenylated transcripts. To determine if poly(A+) enrichment of Orphan REs reflected a specific class of genomic repeat, the distribution of repeats within the 150 poly(A+) enriched Orphan REs was assessed and is shown in Figure The RE discovery algorithm was developed to identify transcribed intergenic loci from RNA-seq data. Many novel loci (e.g. Near-exon and Orphan REs) were hypothesized to be derived from non-polyadenylated RNAs, since this class appears underrepresented in the genome and the GENCODE annotations. A series of poly enrichment was also assessed individually for human sperm and testis samples, providing the other half of the equation to early post-fertilization development. Poly(A+) enrichment has contrasting effects on exonic REs in spermatozoa and testis, with poly(A+) enrichment depleting and enriching exonic REs in sperm and testis, respectively. However, unlike embryos, novel REs are markedly enriched in sperm and testis Total RNA libraries, reflective of the relatively uncharacterized state of this cell type (+) enrichment does effectively reduce RNA library complexity, it does not appear to select for RNAs of any given biological function or pathway, with many GO terms shared in both the poly(A+)-enriched and Total RNA-enriched gene sets of the human embryo (The effect of poly(Aell type . Althougn embryo .RE expression throughout spermatogenesis was examined as a comparison to previously published patterns of whole transcript expression during the spermatogenic cycle42). The spermatogenic stages encompassed six cell types (Spermatogonia through Round Spermatids), isolated using laser capture microdissection . The spe,41 with Ontological analysis of the exonic and novel REs (with the exception of Orphan REs) showed that the most abundant REs in round spermatids were enriched for genes involved in organelle biogenesis and maintenance. This is in accord with the physiological changes occurring during spermiogenesis. REs that are abundant in both round spermatids and spermatozoa were enriched for TNF-alpha signaling, associated with maintaining a homeostatic state ,57. REs Meiotic sex chromosome inactivation (MSCI), the process by which genes located on the X-chromosome are repressed during meiosis, is essential for successful meiosis during human spermatogenesis . HoweverAs shown in Figure in vitro that human sperm deliver a cadre of RNAs upon fertilization (P = 8.36 × 10–8) and the Unc 51 Like Kinase (P = 1.47 × 10–3). RAN cycling is required for effective translocation of RNA and proteins across the nuclear pore. The human sperm REs contain RANGAP1, XPO7, XPO6, NUP210 and NUP214, as members of the nucleoporin complex. Interestingly others have shown that at least in embryonic stem cells, the nucleoporin complex may regulate parentally imprinted genes , those expressed during EGA are associated with protein metabolism (P = 4.90e–06), consistent with the energy and synthesis requirements of the early embryo.To identify differentially expressed REs, a linear model was applied to the single-cell oocyte and embryonic RNA-seq datasets ,80. DiffGenomic repetitive elements and small non-coding RNAs are thought to play a role in confrontation-consolidation of the maternal and paternal genomes after fertilization ,82. As nAlthough several studies have examined the influence of environment on epigenetic marks, such as DNA methylation, at genomic repeats in spermatozoa, much less is known about genomic repeat expression during spermatogenesis and if genomic repeats are in part driving spermatogenesis, perhaps through transcriptional regulation or chromosomal reorganization ,84. FourIn this study, we sought to enrich our understanding of the transcriptome across the human germ cell and early embryogenesis. To accomplish this, we interrogated publicly available RNA-seq datasets using a new method ‘REDa’ to identify novel RNA elements (REs). This method was used to detect REs in differentiating cells of the germline, embryonic cells, and somatic tissues. The RE discovery algorithm possesses a robust positive predictive value (PPV) , eliminaThe accuracy of the RE approach, which separates exons into individual units, rather than linking exons into a whole transcript, was tested by comparing expressed REs in testis libraries to the testis expression levels given by GTEx. At least 91% of gene names associated with testis-expressed exonic REs overlap with gene names expressed in GTEx testis tissue, suggesting that the RE approach can recapitulate the patterns designated in established expression databases. The accuracy of the RE approach was further tested on poly(A+) selected libraries, reiterating previous studies that indicate a reduction of transcript diversity and exon expression upon poly(A+) enrichment . The numIsoform discovery approaches, such as Cufflinks and Stringtie ,33, provThe transcriptome of the human male germline has largely been limited to the whole testis, with a few studies generating information from isolated germ cell populations from this mildly heterogeneous tissue. This contrasts with the mature mammalian spermatozoon, which is known to contain a complex transcript population and can be obtained in a relatively pure form ,100. As Relatively few paternal full-length RNAs are likely to be exclusively contributed to the embryo . Of noteAlthough few paternally derived zygotic RNAs are X-linked, the expression patterns of REs located on the X chromosome are congruent with the current paradigm of Meiotic sex chromosome inactivation (MSCI) and reactivation during spermatogenesis . The curThe mechanism(s) driving spermatogenesis may involve the use of repetitive sequences as regulators of transcription and/or chromatin states ,105,106.n) that resides within the inner nuclear compartment  enrichment, the sheer abundance of intergenic RNAs suggests that they play a large role in spermiogenesis. Of note, extensive expression of repetitive elements during spermatogenesis, suggests that perhaps these are driving spermatogenesis, while sperm-delivered repeat-derived RNAs may play more of a regulatory role in the human embryo.This study introduces a RE discovery algorithm (REDa) that identifies tissue and cell type specific expression in both exonic and intergenic REs. Expression patterns of REs were identified across human spermatogenesis, extending the current knowledge of the transcriptome in developing human sperm. In addition to observing considerable effects of poly(ASupplementary DataClick here for additional data file.


Randomized controlled trials (RCT) are widely used in clinical efficacy evaluation studies. Linear regression is a general method to evaluate treatment efficacy considering the existence of confounding variables. However, when residuals are not normally distributed, parameter estimation based on ordinary least squares (OLS) is inefficient. This study introduces an exponential squared loss (ESL) model to evaluate treatment effect. The proposed method provides robust estimation for non-normal data. Simulation results show that it outperforms ordinary least squares regression with contaminated data. In the mild cognitive impairment (MCI) efficacy evaluation study with traditional Chinese medicine, our method is applied to construct a linear efficacy evaluation model for the difference in Alzheimer’s disease assessment scale-cognitive (ADAS-cog) scores between the final and baseline records (ADASFA), with the existence of confounding factors and non- normal residuals. The results coincide with existing medical literatures. This proposed method overcomes the limitation of confounding variables and non-normal residuals in RCT efficacy studies. It outperforms OLS on estimation efficiency in situations where the percentage of non-normal contamination reaches 30%. These advantages make it a good method for real-world clinical studies. Alzheimer’s disease assessment scale-cognitive (ADAS-cog) subscale measures the progression of MCI in 11 relevant fields, namely spoken language ability, comprehension of spoken language, recall of test instructions, word-finding difficulty, following commands, naming, constructions, ideational praxis, orientation, word recall, and word recognition. Detailed information on ADAS-cog subscale can be found in Rosen et al.2.Mild cognitive impairment (MCI) is a syndrome defined as a cognitive decline, which may affect daily activities. The amnesic subtype of MCI has a high risk of progression to Alzheimer’s disease and could lead to a prodromal stage of this disorder4. The most intuitive idea is to test whether the treatment and control means are equal. However, Morgan and Rubin5 argued that the baseline equivalence is not guaranteed although the allocation is randomized. Imbalance in baseline covariates could confound the statistical test when comparing ADASFA between the two arms. Ten variables, specifically age, height, weight, gender, education, ethnicity, occupation, centre, drug (whether the patient took a drug for MCI in the past three months), and ADAS1 (the baseline record of ADAS-cog6), were recorded as potential covariates. Table p is the number of covariates. We denote a binary variable xj = 1 to represent the treatment arm and xj = 0 for the control arm. The efficacy can be evaluated by the corresponding coefficient βj 7. Ordinary least squares (OLS) is a general parameter estimation method for simple linear regression which performs as the best linear unbiased estimation when assuming independent identical normally distributed errors:Institute of Clinical Pharmacology at Xiyuan Hospital conducted a phase III randomized clinical trial to evaluate the efficacy of a traditional Chinese prescription on MCI. The double blinded randomized clinical trial was conducted in eight qualified medical centres across China with 216 patients allocated to the treatment arm and 108 retained as control. Two patients dropped out from each arm, resulting in 320 complete observations in the final dataset. Data on the difference between final ADAS-cog score and baseline scores (ADASFA) were recorded for the efficacy study. Previous literatures have used ADASFA in efficacy evaluation of MCI or Alzheimer’s disease8, which is commonly presented in medical studies10. This could lead to inefficient efficacy estimation by using OLS since the contaminated part is not addressed11. A more robust estimation method in linear regression is, therefore, required in such studies.However, the QQ plot in Fig. 12 developed a rank-based estimate in linear regression. Wang et al.13 proposed an robust estimation via least absolute deviation while Wang et al.14 introduced an exponential squared loss (ESL) to select variables robustly. Since the breakdown point of ESL is almost 50%, we adopt it in the MCI efficacy evaluation study. Numerical studies show that the proposed method can achieve a more accurate estimation with a large proportion of contamination in the dataset. Additionally, the estimations are consistent with OLS when contamination proportions are relatively low. Therefore, it can be used as a complementary efficacy evaluation method in real-world clinical studies regardless of the presence or lack of contaminations.Many robust methods have been discussed in literatures. Baon subjects, denoted as yi is the outcome and xi = T is a p-dimensional vector of covariates. A linear regression model is,β is a p-dimensional vector of unknown parameters while εi is independent and identically distributed with some unknown distribution satisfying E(εi) = 0 and εi ╨ xi.Suppose there are 15. Wang et al.14 expanded the use of the ESL function for robust variables selection. We now use it to estimate parameters in linear regression without sparsity. The ESL function is defined ast, and γ, where the latter is a tuning parameter. To estimate model parameters (β), the objective function of ESL is to maximize,The ESL function has been used in AdaBoost for classification problems with successγ controls the degree of robustness of the estimator. With a relatively large γ, the proposed estimator gets close to the OLS estimator while a smaller γ leads to a limited influence of contaminations on the estimator. Since the tuning parameter γ controls the degree of robustness and efficiency of the estimator, a data-driven procedure that yields both high robustness and high efficiency simultaneously is used to select an appropriate γ. The entire calculation process in terms of ESL borrows from the idea proposed in Wang et al.14:Find the pseudo outlier set of the sample. Let Dn = {, …, }. Then, calculate m is the cardinality of Dm set and Dn−m = Dn/Dm.Update the tuning parameterγ. Let γ be the minimiser of det G = {γ:ζ(γ) ∈  of the estimators of our algorithm (ESL) versus those from the ordinary least squares (OLS).xi = T, i = 1, 2, …, n with p = 7 and n = 300. The first six covariates are continuous, that is, xij ~ N for j = 1, 2, …, 6 and xi7 is categorical, selected from {1, 2, …, 4}. Convert xi7 into three binary variables, denoted as zi1, zi2, zi3 where zij represents whether xi7 belongs to the j-th category and zi1 = zi2 = zi3 = 0 means xi7 belongs to the last category. Thus, we have xi = T. Let β = T where β = T. The error term of contamination (outlier) follows t(1) distribution, and the error term of non-outlier follows standard normal distribution, N. The proportion of contamination considered is 10%, 20% and 30%, respectively. For each proportion of contamination, the average mean, bias, standard deviation (SD), and MSE of ESL and OLS over 100 replications is reported in Table Simulate data j’, ‘eslj’, and ‘olsj’ refer to the corresponding parameter j for true value, ELS, and OLS estimations. It can be seen that the widths of error bars using ESL are significantly considerably shorter than those using OLS, which implies that the standard deviation of the ESL estimator in ESL is much smaller than that in of OLS, and our method is more robust.Figure In the MCI study, the linear regression model is conducted as follows:We include these variables in the model based on our clinical experience and existing literatures. In addition, we transform weight and height into a new variable BMI, since there are discussions on whether BMI has an effect on MCI. We exclude ethnicity and marital status from our model mainly because these two variables are extremely unbalanced between the treatment and control arms, and also due to the fact that almost no literature suggests that these two variables have an effect on MCI. Since 11 out of 16 variables are categorical variables, we do not consider interaction effects. The by-centre descriptive analysis is presented in Table ADAS1 and centre 6 have significant influences on ADASFA since their bootstrap confidence intervals do not contain 0. From the medical view, higher ADAS1 means patients are in worse health situation, which can have a positive effect on ADASFA.17, it is verified that ‘age’ has a significant effect on MCI. Prior work has demonstrated that rates of dementia increase exponentially with age19. However, the significant effect of age on MCI does not mean that it also influences the treatment effect.ESL and OLS both show that ADAS1 has a positive effect on decreasing ADAS-cog. For age, ESL shows that age has no effect on decreasing ADAS-cog because its bootstrap confidence interval contains 0 while OLS shows that age has a negative effect on decreasing ADAS-cog. From a medical viewpointThe ESL group coefficient is −0.141 and its bootstrap confidence interval contains 0. This result makes sense because this project is a non-inferiority trial and the treatment group was not worse than the control group.The ESL shows that centres 3, 6, and 7 have significant effects on the outcome. However, OLS shows that centres 3 and 7 have no significant impact but centre 6 has a significant effect on the outcome. According to Table Since we have shown that the data is not normally distributed, we can have greater confidence in the ESL results.Table In this paper, we discuss a method to evaluate efficacy in a randomized control MCI study. As many covariates may influence the outcome, a linear regression model is considered rather than comparing group means using t test or ANOVA. An exponential squared loss function, which is superior to OLS when dealing with non-normal residuals, is introduced in this study. Simulation results show that the ESL model yields more efficient estimation than OLS in non-normal data. The proposed method is also robust in the case of data with outliers. These advantages of the ESL model become more noticeable when the contamination percentage increases. The proposed method does not require the normal distribution assumption, offering new insight in the efficacy evaluation for practical researchers.