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Table S2. Summary of annotations of the Actinidia chinensis var. chinensis transcriptome. (DOC 66 kb)

Since 2008 Psa ( Pseudomonas syringae pv. actinidiae) has become a threat for kiwifruit plantation in many Countries. A lot of research and trials have been carried out looking for chemicals able to stop the infection, acting directly on the agent of the disease. This study is targeted on the “environment” corner of the disease triangle, with the aim of creating an overall environment unfavorable to Psa development, considering the effect of change not only on the disease, but also on growing parameters. The objective is achievable growing kiwifruit under green house in different structures. Zespri in conjunction with the University of Bologna built up three years of growing experience under covers, so the present work wants to underline the outcomes of it. It has been proved that growing kiwifruit under cover reduces significantly the symptoms of Psa. This is likely linked to lower bacteria’s population, both epiphytic and endophytic. Beside the effect on bacteria’s population, effect on fruit quality was observed. Earlier fruit set was recorded under the cover due to the warmer spring temperature. It also resulted in bigger fruit size at harvest with less blemish. In fact, plastic covers protect the crop from adverse climate events, such as wind and hail. Generally, under cover kiwifruit needs a limited number of chemical treatments, with benefit on soil compaction (fewer sprays and in better soil condition – no wet soil). The controlled climate condition allowed to operate with no weather constrains: this was particularly helpful at pollination time, but also in a Psa safer environment for summer pruning, harvest and so forth, where wounds could get infected. In the other hand, growing kiwifruit under plastic cover showed some constrains. Primary, building a structure that can resist to climate events, like wind storms or hail and snow precipitation is generally highly expensive. In addition, the plastic covers last few years (5-6 years), or at least the light permeability decreases dramatically, requiring to replace it. This implies frequent substitution of the plastic sheet, with extra charge of cost to add to the balance. Data have been collected about change in amount and quality of the light. Although in Italy it is not a big issue during sunny days, it may become a problem when it is cloudy, causing a decrease of the photosynthesis: this can impact dry matter accumulation, resulting in lower fruit quality. Care must be paid to irrigation and nutrition management, since salinity can easily build up in the root area, due to the quality of irrigation water and/or the fertilizer application. In fact, the complete absence of precipitation avoids regular wash off/dilution of the salinity, accumulating in narrow layer compressed by the irrigation volume applied. In conclusion, this paper as result of ongoing monitoring, highlights all the side effects of plastic covers, both positive and negative, on kiwifruit crop

HIV-1 non-B subtypes/circulating recombinant forms (CRFs) are increasing worldwide. Since subtype identification can be clinically relevant, we assessed the added value in HIV-1 subtyping using updated molecular phylogeny (Mphy) and the performance of routinely used automated tools. Updated Mphy (2015 updated reference sequences), used as a gold standard, was performed to subtype 13,116 HIV-1 protease/reverse transcriptase sequences and then compared with previous Mphy (reference sequences until 2014) and with COMET, REGA, SCUEAL, and Stanford subtyping tools. Updated Mphy classified subtype B as the most prevalent (73.4%), followed by CRF02_AG (7.9%), C (4.6%), F1 (3.4%), A1 (2.2%), G (1.6%), CRF12_BF (1.2%), and other subtypes (5.7%). A 2.3% proportion of sequences were reassigned as different subtypes or CRFs because of misclassification by previous Mphy. Overall, the tool most concordant with updated Mphy was Stanford-v8.1 (95.4%), followed by COMET (93.8%), REGA-v3 (92.5%), Stanford-old (91.1%), and SCUEAL (85.9%). All the tools had a high sensitivity (≥98.0%) and specificity (≥95.7%) for subtype B. Regarding non-B subtypes, Stanford-v8.1 was the best tool for C, D, and F subtypes and for CRFs 01, 02, 06, 11, and 36 (sensitivity, ≥92.6%; specificity, ≥99.1%). A1 and G subtypes were better classified by COMET (92.3%) and REGA-v3 (98.6%), respectively. Our findings confirm Mphy as the gold standard for accurate HIV-1 subtyping, although Stanford-v8.1, occasionally combined with COMET or REGA-v3, represents an effective subtyping approach in clinical settings. Periodic updating of HIV-1 reference sequences is fundamental to improving subtype characterization in the context of an effective epidemiological surveillance of non-B strains.

Bacterial canker of kiwifruit, caused by Pseudomonas syringae pv. actinidiae (Psa), has emerged since 2008 and is the most important disease of kiwifruit, threatening its production in the world. Until now, little is known about the molecular interaction between Psa and kiwifruit plants: to elucidate early molecular events of kiwifruits-Psa interaction, Illumina RNA-seq was conducted at 3 h, 24 h and 48 h after Psa inoculation and mock inoculation, both on acibenzolar-S-methyl (ASM)-pretreated and untreated Actinidia chinensis plants. De novo assembly of kiwifruit transcriptome consists of 39,607 transcripts, about 4500 of them were differentially expressed (DE) in the various situations. During infection process, genes modulation caused by Psa in A. chinensis involve about 3000 transcripts modulated that is mainly evident at 3hpi rather than 24hpi or 48hpi. Only few transcripts were common between the three infections time points (1,5%). Moreover, transcripts modulation in infected ASM-untreated plants were higher than in ASM pre-treated infected plants. To investigate transcriptome expression profile during infection process, both in ASM untreated and ASM pre-treated plants, Hierarchical Cluster Analysis (HCA) were performed to reveal the coordinates change of some important gene functional categories. Moreover, MapMan has been shown to be an effective tool to map transcriptome data, to define functional categories and to perform time course analysis in order to identify differentially-represented functional groups. Regulation overview highlight difference in hormonal balance, transcriptional regulation and signaling. For example, seven major families of TF (AP2/ERF, MYB, Myc-bHLH, GATA, NAC, WRKY and GRAS), reported as linked to plant stress responses such as pathogens, were found DE in response to Psa in ASM pretreated plants with respect to the untreated ones. Different TFs were linked also with signaling and hormonal balance and probably involved in the ability of ASM plants to assemble the right defense response against PSA. On the other side, ASM untreated plants try to mount a response at 3 hpi , but not adequate to counteract the infection. Moreover, the RNA-seq technology has permitted to identify novel differentially expressed transcripts of unknown functions but related with infection and ASM treatment. Bacterial canker of kiwifruit, caused by Pseudomonas syringae pv. actinidiae (Psa), has emerged since 2008 and is the most important disease of kiwifruit, threatening its production in the world. Until now, little is known about the molecular interaction between Psa and kiwifruit plants: to elucidate early molecular events of kiwifruits-Psa interaction, Illumina RNA-seq was conducted at 3 h, 24 h and 48 h after Psa inoculation and mock inoculation, both on acibenzolar-S-methyl (ASM)-pretreated and untreated Actinidia chinensis plants. De novo assembly of kiwifruit transcriptome consists of 39,607 transcripts, about 4500 of them were differentially expressed (DE) in the various situations. During infection process, genes modulation caused by Psa in A. chinensis involve about 3000 transcripts modulated that is mainly evident at 3hpi rather than 24hpi or 48hpi. Only few transcripts were common between the three infections time points (1,5%). Moreover, transcripts modulation in infected ASM-untreated plants were higher than in ASM pre-treated infected plants. To investigate transcriptome expression profile during infection process, both in ASM untreated and ASM pre-treated plants, Hierarchical Cluster Analysis (HCA) were performed to reveal the coordinates change of some important gene functional categories. Moreover, MapMan has been shown to be an effective tool to map transcriptome data, to define functional categories and to perform time course analysis in order to identify differentially-represented functional groups. Regulation overview highlight difference in hormonal balance, transcriptional regulation and signaling. For example, seven major families of TF (AP2/ERF, MYB, Myc-bHLH, GATA, NAC, WRKY and GRAS), reported as linked to plant stress responses such as pathogens, were found DE in response to Psa in ASM pretreated plants with respect to the untreated ones. Different TFs were linked also with signaling and hormonal balance and probably involved in the ability of ASM plants to assemble the right defense response against PSA. On the other side, ASM untreated plants try to mount a response at 3 hpi , but not adequate to counteract the infection. Moreover, the RNA-seq technology has permitted to identify novel differentially expressed transcripts of unknown functions but related with infection and ASM treatment.