ZheJiang Academy of Agricultural Sciences

AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425,
\nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981,
\nPeter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826,
\nPatrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376,
\nTakahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294,
\nChris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Alg€ul1164, Mehrdad Alirezaei1198,
\nIraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544,
\nNihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107,
\nGiuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756,
\nAmal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6,
\nUsha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58,
\nShailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007,
\nSaveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, Agustin Aranda456, Jun Araya591,
\nAlexandre Arcaro1472, Esperanza Arias26, Hirokazu Arimoto1225, Aileen R Ariosa1749, Jane L Armstrong1930,
\nThierry Arnould1773, Ivica Arsov2120, Katsuhiko Asanuma675, Valerie Askanas1924, Eric Asselin1867, Ryuichiro Atarashi794,
\nSally S Atherton369, Julie D Atkin713, Laura D Attardi1131, Patrick Auberger1787, Georg Auburger379, Laure Aurelian1727,
\nRiccardo Autelli1992, Laura Avagliano1029,1755, Maria Laura Avantaggiati364, Limor Avrahami1166, Suresh Awale1986,
\nNeelam Azad404, Tiziana Bachetti568, Jonathan M Backer28, Dong-Hun Bae1933, Jae-sung Bae677, Ok-Nam Bae409,
\nSoo Han Bae2117, Eric H Baehrecke1729, Seung-Hoon Baek17, Stephen Baghdiguian1368,
\nAgnieszka Bagniewska-Zadworna2, Hua Bai90, Jie Bai667, Xue-Yuan Bai1133, Yannick Bailly884,
\nKithiganahalli Narayanaswamy Balaji473, Walter Balduini2002, Andrea Ballabio316, Rena Balzan1711, Rajkumar Banerjee239,
\nG abor B anhegyi1052, Haijun Bao2109, Benoit Barbeau1363, Maria D Barrachina2007, Esther Barreiro467, Bonnie Bartel997,
\nAlberto Bartolom e222, Diane C Bassham550, Maria Teresa Bassi1046, Robert C Bast Jr1273, Alakananda Basu1798,
\nMaria Teresa Batista1578, Henri Batoko1336, Maurizio Battino970, Kyle Bauckman2085, Bradley L Baumgarner1909,
\nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336,
\nJ David Beckham1595, Pierre-Andr e B edard749, Patrick J Bednarski301, Thomas J Begley1135, Christian Behl1419,
\nChristian Behrends757, Georg MN Behrens406, Kevin E Behrns1627, Eloy Bejarano26, Amine Belaid490,
\nFrancesca Belleudi1041, Giovanni B enard497, Guy Berchem706, Daniele Bergamaschi983, Matteo Bergami1401,
\nBen Berkhout1441, Laura Berliocchi714, Am elie Bernard1749, Monique Bernard1354, Francesca Bernassola1880,
\nAnne Bertolotti791, Amanda S Bess272, S ebastien Besteiro1351, Saverio Bettuzzi1828, Savita Bhalla913,
\nShalmoli Bhattacharyya973, Sujit K Bhutia838, Caroline Biagosch1159, Michele Wolfe Bianchi520,1378,1381,
\nMartine Biard-Piechaczyk210, Viktor Billes298, Claudia Bincoletto1314, Baris Bingol350, Sara W Bird1128, Marc Bitoun1112,
\nIvana Bjedov1258, Craig Blackstone843, Lionel Blanc1183, Guillermo A Blanco1496, Heidi Kiil Blomhoff1812,
\nEmilio Boada-Romero1297, Stefan B€ockler1464, Marianne Boes1423, Kathleen Boesze-Battaglia1835, Lawrence H Boise286,287,
\nAlessandra Bolino2063, Andrea Boman693, Paolo Bonaldo1823, Matteo Bordi897, J€urgen Bosch608, Luis M Botana1308,
\nJoelle Botti1375, German Bou1405, Marina Bouch e1038, Marion Bouchecareilh1331, Marie-Jos ee Boucher1901,
\nMichael E Boulton481, Sebastien G Bouret1926, Patricia Boya133, Micha€el Boyer-Guittaut1345, Peter V Bozhkov1141,
\nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374,
\nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822,
\nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480,
\nAlain Bruhat486,1339, Patricia Chakur Brum1893, John H Brumell446, Nicola Brunetti-Pierri315,1171,
\nRobert J Bryson-Richardson781, Shilpa Buch1777, Alastair M Buchan1819, Hikmet Budak1022, Dmitry V Bulavin118,505,1789,
\nScott J Bultman1792, Geert Bultynck665, Vladimir Bumbasirevic1470, Yan Burelle1356, Robert E Burke216,217,
\nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24,
\nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700,
\nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983,
\nLavinia Cantoni560, Lizhi Cao116, Allan B Caplan1656, Michele Caraglia1051, Claudio Cardinali1043, Sandra Morais Cardoso1579, Jennifer S Carew208, Laura A Carleton874, Cathleen R Carlin101, Silvia Carloni2002,
\nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318,
\nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462,
\nSusana Castro-Obregon214, Gabriella Cavallini1841, Isabella Ceccherini568, Francesco Cecconi253,555,1884,
\nArthur I Cederbaum459, Valent ın Ce~na199,1281, Simone Cenci1323,2064, Claudia Cerella444, Davide Cervia1996,
\nSilvia Cetrullo1478, Hassan Chaachouay2028, Han-Jung Chae187, Andrei S Chagin634, Chee-Yin Chai626,628,
\nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003,
\nPallavi Chandra548, Chih-Peng Chang818, Raymond Chuen-Chung Chang1653, Ta Yuan Chang345, John C Chatham1434,
\nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783,
\nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514,
\nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172,
\nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113,
\nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135,
\nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702,
\nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703,
\nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308,
\nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290,
\nMario Chiong1285, Gigi NC Chiu878, Dong-Hyung Cho676, Ssang-Goo Cho650, William C Cho982, Yong-Yeon Cho105,
\nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563,
\nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936,
\nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657,
\nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254,
\nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694,
\nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781,
\nMiriam Cnop1366, Eliana M Coccia574, Tiziana Cocco1459, Patrice Codogno1375, J€orn Coers271, Ezra EW Cohen1533,
\nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829,
\nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395,
\nIsabelle Coppens601, Maria Tiziana Corasaniti1387, Marco Corazzari485,1884, Ramon Corbalan1566,
\nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767,
\nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301,
\nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919,
\nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576,
\nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572,
\nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940,
\nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340,
\nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254,
\nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604,
\nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182,
\nRegina Celia Bressan Queiroz de Figueiredo135, Jos e de la Fuente1023, Luisa De Martino1775,
\nAntonella De Matteis1171, Guido RY De Meyer1443, Angelo De Milito631, Mauro De Santi2002,

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

BACKGROUND: Recently, a small population of cancer stem cells in adult and pediatric brain tumors has been identified. Some evidence has suggested that CD133 is a marker for a subset of leukemia and glioblastoma cancer stem cells. Especially, CD133 positive cells isolated from human glioblastoma may initiate tumors and represent novel targets for therapeutics. The gene expression and the drug resistance property of CD133 positive cancer stem cells, however, are still unknown. RESULTS: In this study, by FACS analysis we determined the percentage of CD133 positive cells in three primary cultured cell lines established from glioblastoma patients 10.2%, 69.7% and 27.5%, respectively. We also determined the average mRNA levels of markers associated with neural precursors. For example, CD90, CD44, CXCR4, Nestin, Msi1 and MELK mRNA on CD133 positive cells increased to 15.6, 5.7, 337.8, 21.4, 84 and 1351 times, respectively, compared to autologous CD133 negative cells derived from cell line No. 66. Additionally, CD133 positive cells express higher levels of BCRP1 and MGMT mRNA, as well as higher mRNA levels of genes that inhibit apoptosis. Furthermore, CD133 positive cells were significantly resistant to chemotherapeutic agents including temozolomide, carboplatin, paclitaxel (Taxol) and etoposide (VP16) compared to autologous CD133 negative cells. Finally, CD133 expression was significantly higher in recurrent GBM tissue obtained from five patients as compared to their respective newly diagnosed tumors. CONCLUSION: Our study for the first time provided evidence that CD133 positive cancer stem cells display strong capability on tumor's resistance to chemotherapy. This resistance is probably contributed by the CD133 positive cell with higher expression of on BCRP1 and MGMT, as well as the anti-apoptosis protein and inhibitors of apoptosis protein families. Future treatment should target this small population of CD133 positive cancer stem cells in tumors to improve the survival of brain tumor patients.

Allotetraploid cotton is an economically important natural-fiber-producing crop worldwide. After polyploidization, Gossypium hirsutum L. evolved to produce a higher fiber yield and to better survive harsh environments than Gossypium barbadense, which produces superior-quality fibers. The global genetic and molecular bases for these interspecies divergences were unknown. Here we report high-quality de novo–assembled genomes for these two cultivated allotetraploid species with pronounced improvement in repetitive-DNA-enriched centromeric regions. Whole-genome comparative analyses revealed that species-specific alterations in gene expression, structural variations and expanded gene families were responsible for speciation and the evolutionary history of these species. These findings help to elucidate the evolution of cotton genomes and their domestication history. The information generated not only should enable breeders to improve fiber quality and resilience to ever-changing environmental conditions but also can be translated to other crops for better understanding of their domestication history and use in improvement. High-quality de novo–assembled genomes of two cultivated allotetraploid cotton species and whole-genome comparative analyses provide insights into the evolution of cotton genomes and improvement of fiber quality and resilience to stress.

The draft genome of the pear (Pyrus bretschneideri) using a combination of BAC-by-BAC and next-generation sequencing is reported. A 512.0-Mb sequence corresponding to 97.1% of the estimated genome size of this highly heterozygous species is assembled with 194× coverage. High-density genetic maps comprising 2005 SNP markers anchored 75.5% of the sequence to all 17 chromosomes. The pear genome encodes 42,812 protein-coding genes, and of these, ~28.5% encode multiple isoforms. Repetitive sequences of 271.9 Mb in length, accounting for 53.1% of the pear genome, are identified. Simulation of eudicots to the ancestor of Rosaceae has reconstructed nine ancestral chromosomes. Pear and apple diverged from each other ~5.4-21.5 million years ago, and a recent whole-genome duplication (WGD) event must have occurred 30-45 MYA prior to their divergence, but following divergence from strawberry. When compared with the apple genome sequence, size differences between the apple and pear genomes are confirmed mainly due to the presence of repetitive sequences predominantly contributed by transposable elements (TEs), while genic regions are similar in both species. Genes critical for self-incompatibility, lignified stone cells (a unique feature of pear fruit), sorbitol metabolism, and volatile compounds of fruit have also been identified. Multiple candidate SFB genes appear as tandem repeats in the S-locus region of pear; while lignin synthesis-related gene family expansion and highly expressed gene families of HCT, C3'H, and CCOMT contribute to high accumulation of both G-lignin and S-lignin. Moreover, alpha-linolenic acid metabolism is a key pathway for aroma in pear fruit.

Abstract We synthesized 20 years of research to explain the interrelated processes that determine soil and plant responses to biochar. The properties of biochar and its effects within agricultural ecosystems largely depend on feedstock and pyrolysis conditions. We describe three stages of reactions of biochar in soil: dissolution (1–3 weeks); reactive surface development (1–6 months); and aging (beyond 6 months). As biochar ages, it is incorporated into soil aggregates, protecting the biochar carbon and promoting the stabilization of rhizodeposits and microbial products. Biochar carbon persists in soil for hundreds to thousands of years. By increasing pH, porosity, and water availability, biochars can create favorable conditions for root development and microbial functions. Biochars can catalyze biotic and abiotic reactions, particularly in the rhizosphere, that increase nutrient supply and uptake by plants, reduce phytotoxins, stimulate plant development, and increase resilience to disease and environmental stressors. Meta‐analyses found that, on average, biochars increase P availability by a factor of 4.6; decrease plant tissue concentration of heavy metals by 17%–39%; build soil organic carbon through negative priming by 3.8% (range −21% to +20%); and reduce non‐CO 2 greenhouse gas emissions from soil by 12%–50%. Meta‐analyses show average crop yield increases of 10%–42% with biochar addition, with greatest increases in low‐nutrient P‐sorbing acidic soils (common in the tropics), and in sandy soils in drylands due to increase in nutrient retention and water holding capacity. Studies report a wide range of plant responses to biochars due to the diversity of biochars and contexts in which biochars have been applied. Crop yields increase strongly if site‐specific soil constraints and nutrient and water limitations are mitigated by appropriate biochar formulations. Biochars can be tailored to address site constraints through feedstock selection, by modifying pyrolysis conditions, through pre‐ or post‐production treatments, or co‐application with organic or mineral fertilizers. We demonstrate how, when used wisely, biochar mitigates climate change and supports food security and the circular economy.

Long-term elevated nitrogen (N) input from anthropogenic sources may cause soil acidification and decrease crop yield, yet the response of the belowground microbial community to long-term N input alone or in combination with phosphorus (P) and potassium (K) is poorly understood. We explored the effect of long-term N and NPK fertilization on soil bacterial diversity and community composition using meta-analysis of a global dataset. Nitrogen fertilization decreased soil pH, and increased soil organic carbon (C) and available N contents. Bacterial taxonomic diversity was decreased by N fertilization alone, but was increased by NPK fertilization. The effect of N fertilization on bacterial diversity varied with soil texture and water management, but was independent of crop type or N application rate. Changes in bacterial diversity were positively related to both soil pH and organic C content under N fertilization alone, but only to soil organic C under NPK fertilization. Microbial biomass C decreased with decreasing bacterial diversity under long-term N fertilization. Nitrogen fertilization increased the relative abundance of Proteobacteria and Actinobacteria, but reduced the abundance of Acidobacteria, consistent with the general life history strategy theory for bacteria. The positive correlation between N application rate and the relative abundance of Actinobacteria indicates that increased N availability favored the growth of Actinobacteria. This first global analysis of long-term N and NPK fertilization that differentially affects bacterial diversity and community composition provides a reference for nutrient management strategies for maintaining belowground microbial diversity in agro-ecosystems worldwide.

Genome editing has emerged as a technology with a potential to revolutionize plant breeding. In this study, we report on generating, in less than ten months, Tomelo, a non-transgenic tomato variety resistant to the powdery mildew fungal pathogen using the CRISPR/Cas9 technology. We used whole-genome sequencing to show that Tomelo does not carry any foreign DNA sequences but only carries a deletion that is indistinguishable from naturally occurring mutations. We also present evidence for CRISPR/Cas9 being a highly precise tool, as we did not detect off-target mutations in Tomelo. Using our pipeline, mutations can be readily introduced into elite or locally adapted tomato varieties in less than a year with relatively minimal effort and investment.

Melatonin is a well-known agent that plays multiple roles in animals. Its possible function in plants is less clear. In the present study, we tested the effect of melatonin (N-acetyl-5-methoxytryptamine) on soybean growth and development. Coating seeds with melatonin significantly promoted soybean growth as judged from leaf size and plant height. This enhancement was also observed in soybean production and their fatty acid content. Melatonin increased pod number and seed number, but not 100-seed weight. Melatonin also improved soybean tolerance to salt and drought stresses. Transcriptome analysis revealed that salt stress inhibited expressions of genes related to binding, oxidoreductase activity/process, and secondary metabolic processes. Melatonin up-regulated expressions of the genes inhibited by salt stress, and hence alleviated the inhibitory effects of salt stress on gene expressions. Further detailed analysis of the affected pathways documents that melatonin probably achieved its promotional roles in soybean through enhancement of genes involved in cell division, photosynthesis, carbohydrate metabolism, fatty acid biosynthesis, and ascorbate metabolism. Our results demonstrate that melatonin has significant potential for improvement of soybean growth and seed production. Further study should uncover more about the molecular mechanisms of melatonin's function in soybeans and other crops.

Although the functions of a few effector proteins produced by bacterial and oomycete plant pathogens have been elucidated in recent years, information for the vast majority of pathogen effectors is still lacking, particularly for those of plant-pathogenic fungi. Here, we show that the avirulence effector AvrPiz-t from the rice blast fungus Magnaporthe oryzae preferentially accumulates in the specialized structure called the biotrophic interfacial complex and is then translocated into rice (Oryza sativa) cells. Ectopic expression of AvrPiz-t in transgenic rice suppresses the flg22- and chitin-induced generation of reactive oxygen species (ROS) and enhances susceptibility to M. oryzae, indicating that AvrPiz-t functions to suppress pathogen-associated molecular pattern (PAMP)-triggered immunity in rice. Interaction assays show that AvrPiz-t suppresses the ubiquitin ligase activity of the rice RING E3 ubiquitin ligase APIP6 and that, in return, APIP6 ubiquitinates AvrPiz-t in vitro. Interestingly, agroinfection assays reveal that AvrPiz-t and AvrPiz-t Interacting Protein 6 (APIP6) are both degraded when coexpressed in Nicotiana benthamiana. Silencing of APIP6 in transgenic rice leads to a significant reduction of flg22-induced ROS generation, suppression of defense-related gene expression, and enhanced susceptibility of rice plants to M. oryzae. Taken together, our results reveal a mechanism in which a fungal effector targets the host ubiquitin proteasome system for the suppression of PAMP-triggered immunity in plants.

Soil salinization is a severe abiotic stress that negatively affects plant growth and development, leading to physiological abnormalities and ultimately threatening global food security. The condition arises from excessive salt accumulation in the soil, primarily due to anthropogenic activities such as irrigation, improper land uses, and overfertilization. The presence of Na⁺, Cl−, and other related ions in the soil above normal levels can disrupt plant cellular functions and lead to alterations in essential metabolic processes such as seed germination and photosynthesis, causing severe damage to plant tissues and even plant death in the worst circumstances. To counteract the effects of salt stress, plants have developed various mechanisms, including modulating ion homeostasis, ion compartmentalization and export, and the biosynthesis of osmoprotectants. Recent advances in genomic and proteomic technologies have enabled the identification of genes and proteins involved in plant salt-tolerance mechanisms. This review provides a short overview of the impact of salinity stress on plants and the underlying mechanisms of salt-stress tolerance, particularly the functions of salt-stress-responsive genes associated with these mechanisms. This review aims at summarizing recent advances in our understanding of salt-stress tolerance mechanisms, providing the key background knowledge for improving crops’ salt tolerance, which could contribute to the yield and quality enhancement in major crops grown under saline conditions or in arid and semiarid regions of the world.

BACKGROUND: Microbial interactions shape the structure and function of microbial communities; microbial co-occurrence networks in specific environments have been widely developed to explore these complex systems, but their interconnection pattern across microbiomes in various environments at the global scale remains unexplored. Here, we have inferred an Earth microbial co-occurrence network from a communal catalog with 23,595 samples and 12,646 exact sequence variants from 14 environments in the Earth Microbiome Project dataset. RESULTS: This non-random scale-free Earth microbial co-occurrence network consisted of 8 taxonomy distinct modules linked with different environments, which featured environment specific microbial co-occurrence relationships. Different topological features of subnetworks inferred from datasets trimmed into uniform size indicate distinct co-occurrence patterns in the microbiomes of various environments. The high number of specialist edges highlights that environmental specific co-occurrence relationships are essential features across microbiomes. The microbiomes of various environments were clustered into two groups, which were mainly bridged by the microbiomes of plant and animal surface. Acidobacteria Gp2 and Nisaea were identified as hubs in most of subnetworks. Negative edges proportions ranged from 1.9% in the soil subnetwork to 48.9% the non-saline surface subnetwork, suggesting various environments experience distinct intensities of competition or niche differentiation. Video abstract CONCLUSION: This investigation highlights the interconnection patterns across microbiomes in various environments and emphasizes the importance of understanding co-occurrence feature of microbiomes from a network perspective.

The human body is actually a super-organism that is composed of 10 times more microbial cells than our body cells. Metagenomic study of the human microbiome has demonstrated that there are 3.3 million unique genes in human gut, 150 times more genes than our own genome, and the bacterial diversity analysis showed that about 1000 bacterial species are living in our gut and a majority of them belongs to the divisions of Firmicutes and Bacteriodetes. In addition, most people share a core microbiota that comprises 50-100 bacterial species when the frequency of abundance at phylotype level is not considered, and a core microbiome harboring more than 6000 functional gene groups is present in the majority of human gut surveyed till now. Gut bacteria are not only critical for regulating gut metabolism, but also important for host immune system as revealed by animal studies.

Geminivirus isolates associated with the epidemic of severe cassava mosaic disease in Uganda were studied and compared with virus isolates from the part of Uganda outside the epidemic area, and with African cassava mosaic virus (ACMV) and East African cassava mosaic virus (EACMV). Isolates of a novel type [the Uganda variant (UgV)] were detected in severely affected plants from the epidemic area, whereas those from plants outside the epidemic area were typical of ACMV. The complete nucleotide sequences of DNA-A of UgV (2799 nt) and of a Tanzanian isolate of EACMV (2801 nt) were determined and are extremely similar, except for the coat protein (CP) gene. The CP gene of UgV has three distinct regions: the 5' 219 nt are 99% identical to EACMV (only 79% to ACMV); the following 459 nt are 99% identical to ACMV (75% to EACMV); and the 3' 93 nt are 98% identical to EACMV (76% to ACMV). UgV DNA-A therefore is considered to have arisen by interspecific recombination of EACMV and ACMV. Despite the hybrid nature of their CP, UgV isolates were indistinguishable from ACMV in tests with 20 monoclonal antibodies (MAbs), including seven which reacted with ACMV but not EACMV. The discontinuous epitopes detected by these seven MAbs must involve amino acids which lie in the central part of the CP (residues 74-226) and which differ in ACMV and EACMV. UgV isolates were detected in severely mosaic-affected plants from all 11 widely separated locations sampled. The probable role of recombination in geminivirus evolution in the short to medium term is discussed.

The flavour or fragrance of basmati and jasmine rice is associated with the presence of 2-acetyl-1-pyrroline. A recessive gene (fgr) on chromosome 8 of rice has been linked to this important trait. Here, we show that a gene with homology to the gene that encodes betaine aldehyde dehydrogenase (BAD) has significant polymorphisms in the coding region of fragrant genotypes relative to non-fragrant genotypes. The accumulation of 2-acetyl-1-pyrroline in fragrant rice genotypes may be explained by the presence of mutations resulting in a loss of function of the fgr gene product. The allele in fragrant genotypes has a mutation introducing a stop codon upstream of key amino acid sequences conserved in other BADs. The fgr gene corresponds to the gene encoding BAD2 in rice, while BAD1 is encoded by a gene on chromosome 4. BAD has been linked to stress tolerance in plants. However, the apparent loss of function of BAD2 does not seem to limit the growth of fragrant rice genotypes. Fragrance in domesticated rice has apparently originated from a common ancestor and may have evolved in a genetically isolated population, or may be the outcome of a separate domestication event. This is an example of effective human selection for a recessive trait during domestication.

Plastics have been accumulated offshore and in the deep oceans at an unprecedented scale. Microbial communities have colonized the plastisphere, which has become a reservoir for both antibiotic and metal resistance genes (ARGs and MRGs). This is the first analysis of the diversity, abundance, and co-occurrence of ARGs and MRGs, and their relationships within the microbial community, using metagenomic data of plastic particles observed in the North Pacific Gyre obtained from the National Centre for Biotechnology Information Sequence Read Archive database. The abundance of ARGs and MRGs in microbial communities on the plastics were in the ranges 7.07 × 10 −4 –1.21 × 10 −2 and 5.51 × 10 −3 –4.82 × 10 −2 copies per 16S rRNA, respectively. Both the Shannon-Wiener indices and richness of ARGs and MRGs in plastics microbiota were significantly greater than those of ARGs and MRGs in seawater microbiota in the North Pacific Gyre via one-way analysis of variance. Multidrug resistance genes and multi-metal resistance genes were the main classes of genes detected in plastic microbiota. There were no significant differences in the abundance or diversity of ARGs and MRGs between macroplastics biota and microplastics biota, indicating that particle size had no effect on resistance genes. Procrustes analysis suggested that microbial community composition was the determining factor of the ARG profile but not for MRG. Some ARGs and MRGs had a higher incidence of non-random co-occurrence, suggesting that the co-effects of selection for antibiotic or metal resistance are important factors influencing the resistome of the microbiota on the plastic particles. • Plastic size does not influence the abundance and diversity of resistance genes. • Metal resistance genes had higher abundances than antibiotic resistance genes. • Plastics are a reservoir for metal resistance genes and antibiotic resistance genes. • Bacterial community driving ARG composition but not for MRG profile • Flavobacteriaceae family bacteria are potential host for ARGs and MRGs.

To understand the genetic basis of inbreeding depression and heterosis in rice, main-effect and epistatic QTL associated with inbreeding depression and heterosis for grain yield and biomass in five related rice mapping populations were investigated using a complete RFLP linkage map of 182 markers, replicated phenotyping experiments, and the mixed model approach. The mapping populations included 254 F(10) recombinant inbred lines derived from a cross between Lemont (japonica) and Teqing (indica) and two BC and two testcross hybrid populations derived from crosses between the RILs and their parents plus two testers (Zhong 413 and IR64). For both BY and GY, there was significant inbreeding depression detected in the RI population and a high level of heterosis in each of the BC and testcross hybrid populations. The mean performance of the BC or testcross hybrids was largely determined by their heterosis measurements. The hybrid breakdown (part of inbreeding depression) values of individual RILs were negatively associated with the heterosis measurements of their BC or testcross hybrids, indicating the partial genetic overlap of genes causing hybrid breakdown and heterosis in rice. A large number of epistatic QTL pairs and a few main-effect QTL were identified, which were responsible for >65% of the phenotypic variation of BY and GY in each of the populations with the former explaining a much greater portion of the variation. Two conclusions concerning the loci associated with inbreeding depression and heterosis in rice were reached from our results. First, most QTL associated with inbreeding depression and heterosis in rice appeared to be involved in epistasis. Second, most ( approximately 90%) QTL contributing to heterosis appeared to be overdominant. These observations tend to implicate epistasis and overdominance, rather than dominance, as the major genetic basis of heterosis in rice. The implications of our results in rice evolution and improvement are discussed.

Plants respond to environmental pollutants such as heavy metal(s) by triggering the expression of genes that encode proteins involved in stress response. Toxic metal ions profoundly affect the cellular protein homeostasis by interfering with the folding process and aggregation of nascent or non-native proteins leading to decreased cell viability. However, plants possess a range of ubiquitous cellular surveillance systems that enable them to efficiently detoxify heavy metals toward enhanced tolerance to metal stress. As proteins constitute the major workhorses of living cells, the chelation of metal ions in cytosol with phytochelatins and metallothioneins followed by compartmentalization of metals in the vacuoles as well as the repair of stress-damaged proteins or removal and degradation of proteins that fail to achieve their native conformations are critical for plant tolerance to heavy metal stress. In this review, we provide a broad overview of recent advances in cellular protein research with regards to heavy metal tolerance in plants. We also discuss how plants maintain functional and healthy proteomes for survival under such capricious surroundings.

Climate change has increased the overall impact of abiotic stress conditions such as drought, salinity, and extreme temperatures on plants. Abiotic stress adversely affects the growth, development, crop yield, and productivity of plants. When plants are subjected to various environmental stress conditions, the balance between the production of reactive oxygen species and its detoxification through antioxidant mechanisms is disturbed. The extent of disturbance depends on the severity, intensity, and duration of abiotic stress. The equilibrium between the production and elimination of reactive oxygen species is maintained due to both enzymatic and non-enzymatic antioxidative defense mechanisms. Non-enzymatic antioxidants include both lipid-soluble (α-tocopherol and β-carotene) and water-soluble (glutathione, ascorbate, etc.) antioxidants. Ascorbate peroxidase (APX), superoxide dismutase (SOD), catalase (CAT), and glutathione reductase (GR) are major enzymatic antioxidants that are essential for ROS homeostasis. In this review, we intend to discuss various antioxidative defense approaches used to improve abiotic stress tolerance in plants and the mechanism of action of the genes or enzymes involved.

The plant vacuole is an important organelle for storing excess iron (Fe), though its contribution to increasing the Fe content in staple foods remains largely unexplored. In this study we report the isolation and functional characterization of two rice genes OsVIT1 and OsVIT2, orthologs of the Arabidopsis VIT1. Transient expression of OsVIT1:EGFP and OsVIT2:EGFP protein fusions revealed that OsVIT1 and OsVIT2 are localized to the vacuolar membrane. Ectopic expression of OsVIT1 and OsVIT2 partially rescued the Fe(2+) - and Zn(2+) -sensitive phenotypes in yeast mutant Δccc1 and Δzrc1, and further increased vacuolar Fe(2+) , Zn(2+) and Mn(2+) accumulation. These data together suggest that OsVIT1 and OsVIT2 function to transport Fe(2+) , Zn(2+) and Mn(2+) across the tonoplast into vacuoles in yeast. In rice, OsVIT1 and OsVIT2 are highly expressed in flag leaf blade and sheath, respectively, and in contrast to OsVIT1, OsVIT2 is highly responsive to Fe treatments. Interestingly, functional disruption of OsVIT1 and OsVIT2 leads to increased Fe/Zn accumulation in rice seeds and a corresponding decrease in the source organ flag leaves, indicating an enhanced Fe/Zn translocation between source and sink organs, which might represent a novel strategy to biofortify Fe/Zn in staple foods.