New & Noteworthy

Reference Genome Annotation Update R64.3

August 03, 2021

The S. cerevisiae strain S288C reference genome annotation was updated in its first major update since 2014. The new genome annotation is release R64.3, which released on April 21, 2021. Note that the underlying sequence of 16 assembled nuclear chromosomes, plus the mitochondrial genome, remained unchanged in annotation release R64.3.1 (relative to genome sequence release R64.2.1).

This annotation update included:

7 new ORFs: OTO1/YGR227C-A, YHR052C-B, YHR054C-B, YJR107C-A, YKL104W-A, YLR379W-A, YMR008C-A
5 new ncRNAs: GAL10-ncRNA, TBRT/XUT_2F-154, SUT169, PHO84 lncRNA, GAL4 lncRNA
2 new uORFs for ROK1/YGL171W
1 new recombination enhancer: RE
1 new LTR: YELWdelta27
3 ORFs with shifted translation starts: HPA3/YEL066W, YJR012C, LTO1/YNL260C
1 ORF with shifted translation stop plus new intron: LDO45/YMR147W
Changed feature_type (and SO_term) for non-transcribed spacers: NTS1-2, NTS2-1, NTS2-2
New systematic nomenclature system for entire annotated complement of ncRNAs

R64.3 Annotation update details

Chr	Feature	Description of change	Reference
II	YNCB0008W aka GAL10-ncRNA	New ncRNA antisense to GAL10coordinates 276805..280645	Houseley et al 2008 PMID:19061643,Pinskaya et al 2009 PMID:19407817, Geisler et al 2012 PMID:22226051
II	YNCB0014W aka TBRT/XUT_2F-154	New ncRNA antisense to TAT1coordinates 376610..378633	Awasthi et al 2020 PMID:32081726
III	RE/RE301	New recombination enhancercoordinates 29108..29809	Wu and Haber 1996 PMID:8861911
V	YELWdelta27	New Ty1 LTRcoordinates 449274..449626	Nene et al 2018 PMID:29320491
V	HPA3/YEL066W	Moved translation start to Met19old coordinates: 26667..27206new coordinates: 26721..27206	Sampath et al 2013 PMID:23775086
VII	OTO1/YGR227C-A	New ORFcoordinates 949052..949225 Crick	Makanae et al 2015 PMID:25781884
VII	ROK1/YGL171W	Two new uORFscoordinates uORF1: 182286..182407coordinates uORF2: 182291..182329	Jeon and Kim 2010 PMID:20969870
VIII	YHR052C-B	New ORFcoordinates: 212519..212692 Crick	He et al 2018 PMID:29897761
VIII	YHR054C-B	New ORFcoordinates: 214517..214690 Crick	He et al 2018 PMID:29897761
VIII	SUT169/YNCH0011W	New ncRNAcoordinates 378254..379237	Xu et al 2009 PMID:19169243,Geisler et al 2012 PMID:22226051, Huber et al 2016 PMID:27292640, Bunina et al 2017 PMID:28977638
X	YJR012C	Moved start to Met76old coordinates: 459795..460418 Cricknew coordinates: 459795..460193 Crick	Sadhu et al 2018 PMID:29632376
X	YJR107C-A	New ORFcoordinates 628457..628693 Crick	Yagoub et al 2015 PMID:26554900, He et al 2018 PMID:29897761
XI	YKL104W-A	New ORFcoordinates 245032..245286	He et al 2018 PMID:29897761
XII	YLR379W-A	New ORFcoordinates: 877444..877716	Internal reanalysis of results from Song et al 2015 to find and annotate missing S288C ORFs PMID:25781462
XII	NTS1-2, NTS2-1, NTS2-2	Change feature_type/SO_term from SO:0001637 rRNA_gene to SO:0000183 non_transcribed_region
XIII	LDO45/YMR147W	Shift stop to be same as LDO16/YMR148W, add intronold coordinates 559199..559870new coordinates 559199..559780, 560156..560812	Eisenberg-Bord et al 2018 PMID:29187527
XIII	YMR008C-A	New ORFcoordinates 283081..283548 Crick	Internal reanalysis of results from Song et al 2015 to find and annotate missing S288C ORFs PMID:25781462
XIII	YNCM0001W aka PHO84 lncRNA	New ncRNAcoordinates: 23564..26578	Camblong et al 2007 PMID:18022365
XIV	LTO1/YNL260C	Move start to Met37old coordinates: 156859..157455 Cricknew coordinates: 156859..157347 Crick	Paul et al 2015 PMID:26182403
XVI	YNCP0002W aka GAL4 lncRNA	New ncRNAcoordinates: 79562..82648	Geisler et al 2012 PMID:22226051

New systematic nomenclature system for noncoding RNA genes

Chr	Systematic_name	Gene_name	Alias	Feature_type	Coordinates	Strand
I	YNCA0001W	HRA1		ncRNA gene	99305..99868	+
I	YNCA0002W	TRN1	tP(UGG)A, tRNA-Pro	tRNA gene	139152..139254	+
I	YNCA0003W	SNR18	snR18	snoRNA gene	142367..142468	+
I	YNCA0004W	TGA1	tA(UGC)A, tRNA-Ala	tRNA gene	166267..166339	+
I	YNCA0005W	SUP56	tL(CAA)A, tRNA-Leu	tRNA gene	181141..181254	+
I	YNCA0006C		tS(AGA)A, tRNA-Ser	tRNA gene	182522..182603	–
II	YNCB0001W		tL(UAA)B1, tRNA-Leu	tRNA gene	9583..9666	+
II	YNCB0002W		tF(GAA)B, tRNA-Phe	tRNA gene	36398..36488	+
II	YNCB0003W	SNR56	snR56	snoRNA gene	88190..88277	+
II	YNCB0004W		tI(AAU)B, tRNA-Ile	tRNA gene	197494..197567	+
II	YNCB0005C		tG(GCC)B, tRNA-Gly	tRNA gene	197629..197699	–
II	YNCB0006W		tS(AGA)B, tRNA-Ser	tRNA gene	227075..227156	+
II	YNCB0007W		tT(AGU)B, tRNA-Thr	tRNA gene	266378..266450	+
II	YNCB0008W		GAL10-ncRNA	ncRNA gene	276805..280645	+
II	YNCB0009C	SNR161	snR161	snoRNA gene	307185..307345	–
II	YNCB0010W	TLC1		telomerase RNA gene	307587..308887	+
II	YNCB0011C		tV(UAC)B, tRNA-Val	tRNA gene	326792..326865	–
II	YNCB0012W		tL(UAA)B2, tRNA-Leu	tRNA gene	347603..347686	+
II	YNCB0013W		tQ(UUG)B, tRNA-Gln	tRNA gene	350827..350898	+
II	YNCB0014W	TBRT	XUT_2F-154	ncRNA gene	376610..378633	+
II	YNCB0015W		tR(UCU)B, tRNA-Arg	tRNA gene	405878..405949	+
II	YNCB0016W		tD(GUC)B, tRNA-Asp	tRNA gene	405960..406031	+
II	YNCB0017C		tC(GCA)B, tRNA-Cys	tRNA gene	643007..643078	–
II	YNCB0018W		tE(UUC)B, tRNA-Glu	tRNA gene	645167..645238	+
II	YNCB0019C	LSR1		snRNA gene	680688..681862	–
III	YNCC0001C		tE(UUC)C, tRNA-Glu	tRNA gene	82462..82533	–
III	YNCC0002W	SUP53	tL(CAA)C, tRNA-Leu	tRNA gene	90859..90972	+
III	YNCC0003C	SNR43	snR43	snoRNA gene	107504..107712	–
III	YNCC0004C	SUF2	tP(AGG)C, tRNA-Pro	tRNA gene	123577..123648	–
III	YNCC0005W		tN(GUU)C, tRNA-Asn	tRNA gene	127716..127789	+
III	YNCC0006C	SNR33	snR33	snoRNA gene	142364..142546	–
III	YNCC0007C	SUF16	tG(GCC)C, tRNA-Gly	tRNA gene	142701..142771	–
III	YNCC0008W		tM(CAU)C, tRNA-Met	tRNA gene	149920..149991	+
III	YNCC0009C		tK(CUU)C, tRNA-Lys	tRNA gene	151284..151356	–
III	YNCC0010C		tQ(UUG)C, tRNA-Gln	tRNA gene	168301..168372	–
III	YNCC0011W	SNR65	snR65	snoRNA gene	177183..177282	+
III	YNCC0012C	SNR189	snR189	snoRNA gene	178610..178798	–
III	YNCC0013W	SUP61	tS(CGA)C, tRNA-Ser	tRNA gene	227942..228042	+
III	YNCC0014W		tT(AGU)C, tRNA-Thr	tRNA gene	295484..295556	+
IV	YNCD0001W		tG(GCC)D1, tRNA-Gly	tRNA gene	83548..83618	+
IV	YNCD0002C	SNR63	snR63	snoRNA gene	323217..323471	–
IV	YNCD0003W		tK(UUU)D, tRNA-Lys	tRNA gene	359577..359672	+
IV	YNCD0004W		tA(AGC)D, tRNA-Ala	tRNA gene	410379..410451	+
IV	YNCD0005C		tT(AGU)D, tRNA-Thr	tRNA gene	434264..434336	–
IV	YNCD0006W		tS(AGA)D1, tRNA-Ser	tRNA gene	437772..437853	+
IV	YNCD0007C		tV(UAC)D, tRNA-Val	tRNA gene	488797..488870	–
IV	YNCD0008W		tL(UAA)D, tRNA-Leu	tRNA gene	519743..519826	+
IV	YNCD0009W		tQ(UUG)D1, tRNA-Gln	tRNA gene	520972..521043	+
IV	YNCD0010C	SNR47	snR47	snoRNA gene	541602..541700	–
IV	YNCD0011W		tR(UCU)D, tRNA-Arg	tRNA gene	568882..568953	+
IV	YNCD0012W		tD(GUC)D, tRNA-Asp	tRNA gene	568964..569035	+
IV	YNCD0013C		tR(ACG)D, tRNA-Arg	tRNA gene	619969..620041	–
IV	YNCD0014C		tQ(UUG)D2, tRNA-Gln	tRNA gene	645153..645224	–
IV	YNCD0015C		tI(AAU)D, tRNA-Ile	tRNA gene	668007..668080	–
IV	YNCD0016C		tQ(UUG)D3, tRNA-Gln	tRNA gene	802731..802802	–
IV	YNCD0017W		tI(UAU)D, tRNA-Ile	tRNA gene	884361..884493	+
IV	YNCD0018W	SUP2	tY(GUA)D, tRNA-Tyr	tRNA gene	946312..946400	+
IV	YNCD0019C		tS(AGA)D2, tRNA-Ser	tRNA gene	980974..981055	–
IV	YNCD0020W		tG(GCC)D2, tRNA-Gly	tRNA gene	992832..992902	+
IV	YNCD0021C		tE(CUC)D, tRNA-Glu	tRNA gene	1017207..1017278	–
IV	YNCD0022C		tV(CAC)D, tRNA-Val	tRNA gene	1075472..1075544	–
IV	YNCD0023C		tF(GAA)D, tRNA-Phe	tRNA gene	1095370..1095461	–
IV	YNCD0024C		tX(XXX)D	tRNA gene	1150842..1150941	–
IV	YNCD0025W	EMT1	tM(CAU)D, tRNA-Met	tRNA gene	1175829..1175901	+
IV	YNCD0026W		tK(CUU)D1, tRNA-Lys	tRNA gene	1201750..1201822	+
IV	YNCD0027C	SUF3	tG(CCC)D, tRNA-Gly	tRNA gene	1257008..1257079	–
IV	YNCD0028W		tS(AGA)D3, tRNA-Ser	tRNA gene	1305630..1305712	+
IV	YNCD0029C		tK(CUU)D2, tRNA-Lys	tRNA gene	1352466..1352538	–
IV	YNCD0030W	SNR13	snR13	snoRNA gene	1402919..1403042	+
IV	YNCD0031C		tL(CAA)D, tRNA-Leu	tRNA gene	1461715..1461829	–
IV	YNCD0032C	SNR84	snR84	snoRNA gene	1492477..1493026	–
V	YNCE0001C	SNR80	snR80	snoRNA gene	52150..52320	–
V	YNCE0002W	SNR67	snR67	snoRNA gene	61352..61433	+
V	YNCE0003W	SNR53	snR53	snoRNA gene	61699..61789	+
V	YNCE0004C		tG(GCC)E, tRNA-Gly	tRNA gene	61890..61960	–
V	YNCE0005W		tS(AGA)E, tRNA-Ser	tRNA gene	86604..86685	+
V	YNCE0006W	IMT4	tM(CAU)E, tRNA-Met	tRNA gene	100133..100204	+
V	YNCE0007C	RPR1		ncRNA gene	117667..118035	–
V	YNCE0008C		tQ(UUG)E2, tRNA-Gln	tRNA gene	131082..131153	–
V	YNCE0009C		tK(CUU)E1, tRNA-Lys	tRNA gene	135425..135497	–
V	YNCE0010W		tR(UCU)E, tRNA-Arg	tRNA gene	138666..138737	+
V	YNCE0011C	SNR14	snR14	snRNA gene	167427..167586	–
V	YNCE0012W		tE(UUC)E1, tRNA-Glu	tRNA gene	177099..177170	+
V	YNCE0013W		tH(GUG)E1, tRNA-His	tRNA gene	207357..207428	+
V	YNCE0014W		tQ(UUG)E1, tRNA-Gln	tRNA gene	250286..250357	+
V	YNCE0015C	SUP19	tS(UGA)E, tRNA-Ser	tRNA gene	288443..288524	–
V	YNCE0016C		tA(UGC)E, tRNA-Ala	tRNA gene	312023..312095	–
V	YNCE0017W	SRG1		ncRNA gene	322212..322762	+
V	YNCE0018W		tE(UUC)E2, tRNA-Glu	tRNA gene	354934..355005	+
V	YNCE0019W	SNR4	snR4	snoRNA gene	424698..424883	+
V	YNCE0020C	SNR52	snR52	snoRNA gene	431129..431220	–
V	YNCE0021C		tH(GUG)E2, tRNA-His	tRNA gene	434541..434612	–
V	YNCE0022C		tK(CUU)E2, tRNA-Lys	tRNA gene	435752..435824	–
V	YNCE0023W		tV(AAC)E1, tRNA-Val	tRNA gene	438700..438773	+
V	YNCE0024W	SCR1		ncRNA gene	441987..442508	+
V	YNCE0025C		tI(AAU)E1, tRNA-Ile	tRNA gene	443202..443275	–
V	YNCE0026W		tV(AAC)E2, tRNA-Val	tRNA gene	469457..469530	+
V	YNCE0027C		tE(UUC)E3, tRNA-Glu	tRNA gene	487331..487402	–
V	YNCE0028C		tR(ACG)E, tRNA-Arg	tRNA gene	492352..492424	–
V	YNCE0029C		tI(AAU)E2, tRNA-Ile	tRNA gene	551285..551358	–
VI	YNCF0001C	RUF21		ncRNA gene	57815..58521	–
VI	YNCF0002W	SUF9	tP(UGG)F, tRNA-Pro	tRNA gene	101376..101478	+
VI	YNCF0003C	RUF20		ncRNA gene	131061..131503	–
VI	YNCF0004C		tN(GUU)F, tRNA-Asn	tRNA gene	137486..137559	–
VI	YNCF0005C		tF(GAA)F, tRNA-Phe	tRNA gene	157916..158007	–
VI	YNCF0006W	SUF20	tG(GCC)F1, tRNA-Gly	tRNA gene	162228..162298	+
VI	YNCF0007W	SUP11	tY(GUA)F1, tRNA-Tyr	tRNA gene	167437..167525	+
VI	YNCF0008C		tG(GCC)F2, tRNA-Gly	tRNA gene	180974..181044	–
VI	YNCF0009C		tS(GCU)F, tRNA-Ser	tRNA gene	191513..191613	–
VI	YNCF0010C	RUF22		ncRNA gene	199299..199813	–
VI	YNCF0011C		tA(AGC)F, tRNA-Ala	tRNA gene	204924..204996	–
VI	YNCF0012C	SUP6	tY(GUA)F2, tRNA-Tyr	tRNA gene	210619..210707	–
VI	YNCF0013W	RUF23		ncRNA gene	221714..221967	+
VI	YNCF0014C		tK(CUU)F, tRNA-Lys	tRNA gene	226688..226760	–
VII	YNCG0001C	RME3		ncRNA gene	33109..35013	–
VII	YNCG0002C		tV(AAC)G3, tRNA-Val	tRNA gene	73829..73902	–
VII	YNCG0003C		tH(GUG)G1, tRNA-His	tRNA gene	110625..110696	–
VII	YNCG0004W		tK(UUU)G1, tRNA-Lys	tRNA gene	115488..115583	+
VII	YNCG0005W		tK(CUU)G1, tRNA-Lys	tRNA gene	122269..122341	+
VII	YNCG0006C	RME2		ncRNA gene	141898..144120	–
VII	YNCG0007C		tK(CUU)G2, tRNA-Lys	tRNA gene	185714..185786	–
VII	YNCG0008W		tL(CAA)G1, tRNA-Leu	tRNA gene	205521..205634	+
VII	YNCG0009C		tW(CCA)G1, tRNA-Trp	tRNA gene	287350..287455	–
VII	YNCG0010W	SNR82	snR82	snoRNA gene	316788..317055	+
VII	YNCG0011W		tH(GUG)G2, tRNA-His	tRNA gene	319781..319852	+
VII	YNCG0012W	SOE1	tE(UUC)G1, tRNA-Glu	tRNA gene	328583..328654	+
VII	YNCG0013W	SNR10	snR10	snoRNA gene	345986..346230	+
VII	YNCG0014C	SNR39	snR39	snoRNA gene	365163..365251	–
VII	YNCG0015C	SNR39B	snR39B	snoRNA gene	366374..366469	–
VII	YNCG0016C		tE(UUC)G2, tRNA-Glu	tRNA gene	401527..401598	–
VII	YNCG0017W		tR(UCU)G1, tRNA-Arg	tRNA gene	405470..405541	+
VII	YNCG0018C		tV(AAC)G1, tRNA-Val	tRNA gene	412294..412367	–
VII	YNCG0019W	SUP54	tL(CAA)G2, tRNA-Leu	tRNA gene	423092..423205	+
VII	YNCG0020C		tF(GAA)G, tRNA-Phe	tRNA gene	440716..440807	–
VII	YNCG0021W		tD(GUC)G1, tRNA-Asp	tRNA gene	531610..531681	+
VII	YNCG0022W		tE(UUC)G3, tRNA-Glu	tRNA gene	541850..541921	+
VII	YNCG0023C		tD(GUC)G2, tRNA-Asp	tRNA gene	544577..544648	–
VII	YNCG0024W	SNR46	snR46	snoRNA gene	545370..545566	+
VII	YNCG0025C		tS(AGA)G, tRNA-Ser	tRNA gene	561662..561743	–
VII	YNCG0026W	SNR48	snR48	snoRNA gene	609584..609696	+
VII	YNCG0027W		tT(UGU)G1, tRNA-Thr	tRNA gene	661749..661820	+
VII	YNCG0028W		tL(GAG)G, tRNA-Leu	tRNA gene	700675..700756	+
VII	YNCG0029C		tK(UUU)G2, tRNA-Lys	tRNA gene	700953..701048	–
VII	YNCG0030C		tC(GCA)G, tRNA-Cys	tRNA gene	707108..707179	–
VII	YNCG0031W		tN(GUU)G, tRNA-Asn	tRNA gene	731137..731210	+
VII	YNCG0032W		tR(UCU)G3, tRNA-Arg	tRNA gene	736340..736411	+
VII	YNCG0033W		tI(AAU)G, tRNA-Ile	tRNA gene	739122..739195	+
VII	YNCG0034W		tA(AGC)G, tRNA-Ala	tRNA gene	774349..774421	+
VII	YNCG0035W	SUF4	tG(UCC)G, tRNA-Gly	tRNA gene	779616..779687	+
VII	YNCG0036W		tA(UGC)G, tRNA-Ala	tRNA gene	794417..794489	+
VII	YNCG0037W		tV(AAC)G2, tRNA-Val	tRNA gene	823482..823555	+
VII	YNCG0038C		tR(UCU)G2, tRNA-Arg	tRNA gene	828723..828794	–
VII	YNCG0039W		tG(GCC)G1, tRNA-Gly	tRNA gene	845649..845719	+
VII	YNCG0040C		tL(CAA)G3, tRNA-Leu	tRNA gene	857378..857491	–
VII	YNCG0041W		tK(CUU)G3, tRNA-Lys	tRNA gene	876394..876466	+
VII	YNCG0042C		tW(CCA)G2, tRNA-Trp	tRNA gene	878710..878815	–
VII	YNCG0043C		tG(GCC)G2, tRNA-Gly	tRNA gene	930953..931023	–
VII	YNCG0044C	SNR7-L	snR7-L	snRNA gene	939459..939672	–
VII	YNCG0045C	SNR7-S	snR7-S	snRNA gene	939494..939672	–
VII	YNCG0046W		tT(UGU)G2, tRNA-Thr	tRNA gene	1004216..1004287	+
VIII	YNCH0001W		tH(GUG)H, tRNA-His	tRNA gene	62755..62826	+
VIII	YNCH0002C		tV(AAC)H, tRNA-Val	tRNA gene	85298..85371	–
VIII	YNCH0003C		tT(AGU)H, tRNA-Thr	tRNA gene	116107..116179	–
VIII	YNCH0004C		tS(AGA)H, tRNA-Ser	tRNA gene	133026..133107	–
VIII	YNCH0005W		tQ(UUG)H, tRNA-Gln	tRNA gene	134321..134392	+
VIII	YNCH0006C		tA(AGC)H, tRNA-Ala	tRNA gene	146242..146314	–
VIII	YNCH0007W	RUF5-1		ncRNA gene	212409..213118	+
VIII	YNCH0008W	RUF5-2		ncRNA gene	214407..215116	+
VIII	YNCH0009C		tF(GAA)H1, tRNA-Phe	tRNA gene	237848..237939	–
VIII	YNCH0010C		tF(GAA)H2, tRNA-Phe	tRNA gene	358478..358569	–
VIII	YNCH0011W	SUT169		ncRNA gene	378254..379237	+
VIII	YNCH0012W	SNR32	snR32	snoRNA gene	381540..381727	+
VIII	YNCH0013C	SUF8	tP(UGG)H, tRNA-Pro	tRNA gene	388893..388995	–
VIII	YNCH0014W	SNR71	snR71	snoRNA gene	411228..411317	+
VIII	YNCH0015W		tT(UGU)H, tRNA-Thr	tRNA gene	466990..467061	+
VIII	YNCH0016C		tV(CAC)H, tRNA-Val	tRNA gene	475706..475778	–
IX	YNCI0001W	SNR68	snR68	snoRNA gene	97111..97246	+
IX	YNCI0002W		tT(AGU)I1, tRNA-Thr	tRNA gene	175031..175103	+
IX	YNCI0003C		tI(AAU)I1, tRNA-Ile	tRNA gene	183440..183513	–
IX	YNCI0004W		tE(CUC)I, tRNA-Glu	tRNA gene	197592..197663	+
IX	YNCI0005W		tI(AAU)I2, tRNA-Ile	tRNA gene	210665..210738	+
IX	YNCI0006W	SUP17	tS(UGA)I, tRNA-Ser	tRNA gene	248850..248931	+
IX	YNCI0007C		tK(CUU)I, tRNA-Lys	tRNA gene	300228..300300	–
IX	YNCI0008C		tD(GUC)I1, tRNA-Asp	tRNA gene	324303..324374	–
IX	YNCI0009W		tT(AGU)I2, tRNA-Thr	tRNA gene	325748..325820	+
IX	YNCI0010C		tD(GUC)I2, tRNA-Asp	tRNA gene	336349..336420	–
IX	YNCI0011W		tE(UUC)I, tRNA-Glu	tRNA gene	370417..370488	+
IX	YNCI0012	ICR1		ncRNA gene	393884..397082	–
IX	YNCI0013W	PWR1		ncRNA gene	395999..396939	+
X	YNCJ0001C		tT(AGU)J, tRNA-Thr	tRNA gene	59100..59172	–
X	YNCJ0002C		tE(UUC)J, tRNA-Glu	tRNA gene	115939..116010	–
X	YNCJ0003C	SNR128	snR128	snoRNA gene	139566..139691	–
X	YNCJ0004C	SNR190	snR190	snoRNA gene	139761..139950	–
X	YNCJ0005C		tA(AGC)J, tRNA-Ala	tRNA gene	197313..197385	–
X	YNCJ0006W		tD(GUC)J1, tRNA-Asp	tRNA gene	204735..204806	+
X	YNCJ0007C	SNR37	snR37	snoRNA gene	228094..228479	–
X	YNCJ0008W		tR(ACG)J, tRNA-Arg	tRNA gene	233939..234011	+
X	YNCJ0009C	SNR60	snR60	snoRNA gene	349130..349233	–
X	YNCJ0010W	SUP7	tY(GUA)J1, tRNA-Tyr	tRNA gene	354244..354332	+
X	YNCJ0011W		tR(UCU)J1, tRNA-Arg	tRNA gene	355374..355445	+
X	YNCJ0012W		tD(GUC)J2, tRNA-Asp	tRNA gene	355456..355527	+
X	YNCJ0013C		tD(GUC)J3, tRNA-Asp	tRNA gene	374424..374495	–
X	YNCJ0014C		tR(UCU)J2, tRNA-Arg	tRNA gene	374506..374577	–
X	YNCJ0015W		tV(AAC)J, tRNA-Val	tRNA gene	378360..378433	+
X	YNCJ0016C	EMT5	tM(CAU)J1, tRNA-Met	tRNA gene	391043..391115	–
X	YNCJ0017C		tG(GCC)J1, tRNA-Gly	tRNA gene	396726..396796	–
X	YNCJ0018W		tK(CUU)J, tRNA-Lys	tRNA gene	414966..415038	+
X	YNCJ0019C		tW(CCA)J, tRNA-Trp	tRNA gene	415931..416036	–
X	YNCJ0020W	EMT3	tM(CAU)J2, tRNA-Met	tRNA gene	422937..423009	+
X	YNCJ0021C	SUP51	tL(UAA)J, tRNA-Leu	tRNA gene	424432..424515	–
X	YNCJ0022C	IMT3	tM(CAU)J3, tRNA-Met	tRNA gene	517813..517884	–
X	YNCJ0023C		tS(AGA)J, tRNA-Ser	tRNA gene	524012..524093	–
X	YNCJ0024W	SUF23	tG(GCC)J2, tRNA-Gly	tRNA gene	531828..531898	+
X	YNCJ0025W	HSX1	tR(CCU)J, tRNA-Arg	tRNA gene	538555..538626	+
X	YNCJ0026W		tD(GUC)J4, tRNA-Asp	tRNA gene	541508..541579	+
X	YNCJ0027C	SUP4	tY(GUA)J2, tRNA-Tyr	tRNA gene	542956..543044	–
X	YNCJ0028C	IRT1		ncRNA gene	605936..607424	–
X	YNCJ0029W		tL(UAG)J, tRNA-Leu	tRNA gene	617919..618019	+
X	YNCJ0030W	SNR3	snR3	snoRNA gene	663749..663942	+
XI	YNCK0001W	SNR64	snR64	snoRNA gene	38811..38911	+
XI	YNCK0002C	TRT2	tT(CGU)K, tRNA-Thr	tRNA gene	46735..46806	–
XI	YNCK0003W		tN(GUU)K, tRNA-Asn	tRNA gene	74624..74697	+
XI	YNCK0004W		tL(UAA)K, tRNA-Leu	tRNA gene	84208..84291	+
XI	YNCK0005C		tE(UUC)K, tRNA-Glu	tRNA gene	141018..141089	–
XI	YNCK0006C		tR(UCU)K, tRNA-Arg	tRNA gene	162487..162558	–
XI	YNCK0007W		tK(CUU)K, tRNA-Lys	tRNA gene	202999..203071	+
XI	YNCK0008W		tA(AGC)K1, tRNA-Ala	tRNA gene	219895..219967	+
XI	YNCK0009W	SNR38	snR38	snoRNA gene	283185..283279	+
XI	YNCK0010W		tW(CCA)K, tRNA-Trp	tRNA gene	302918..303023	+
XI	YNCK0011C		tV(AAC)K1, tRNA-Val	tRNA gene	308144..308217	–
XI	YNCK0012C		tH(GUG)K, tRNA-His	tRNA gene	313401..313472	–
XI	YNCK0013W	SNR69	snR69	snoRNA gene	364776..364876	+
XI	YNCK0014W		tV(AAC)K2, tRNA-Val	tRNA gene	379680..379753	+
XI	YNCK0015C	SNR87	snR87	snoRNA gene	431030..431138	–
XI	YNCK0016W		tL(CAA)K, tRNA-Leu	tRNA gene	458557..458670	+
XI	YNCK0017W		tR(ACG)K, tRNA-Arg	tRNA gene	490968..491040	+
XI	YNCK0018C		tD(GUC)K, tRNA-Asp	tRNA gene	513332..513403	–
XI	YNCK0019W		tA(AGC)K2, tRNA-Ala	tRNA gene	517988..518060	+
XI	YNCK0020C	SNR42	snR42	snoRNA gene	559016..559366	–
XI	YNCK0021W		tK(UUU)K, tRNA-Lys	tRNA gene	578965..579060	+
XII	YNCL0001W		tP(UGG)L, tRNA-Pro	tRNA gene	92548..92650	+
XII	YNCL0002C		tS(AGA)L, tRNA-Ser	tRNA gene	167944..168025	–
XII	YNCL0003W	SNR30	snR30	snoRNA gene	198784..199389	+
XII	YNCL0004C		tA(UGC)L, tRNA-Ala	tRNA gene	214883..214955	–
XII	YNCL0005C	SNR79	snR79	snoRNA gene	348427..348510	–
XII	YNCL0006W	SNR6	snR6	snRNA gene	366235..366346	+
XII	YNCL0007W		tR(ACG)L, tRNA-Arg	tRNA gene	374355..374427	+
XII	YNCL0008W		tD(GUC)L1, tRNA-Asp	tRNA gene	427132..427203	+
XII	YNCL0009C		tQ(UUG)L, tRNA-Gln	tRNA gene	448650..448721	–
XII	YNCL0010C	RDN37-1		rRNA gene	451575..458432	–
XII	YNCL0011C	ETS2-1		rRNA gene	451575..451785	–
XII	YNCL0012C	RDN25-1		rRNA gene	451786..455181	–
XII	YNCL0013C	ITS2-1		rRNA gene	455182..455413	–
XII	YNCL0014C	RDN58-1		rRNA gene	455414..455571	–
XII	YNCL0015C	ITS1-1		rRNA gene	455572..455932	–
XII	YNCL0016C	RDN18-1		rRNA gene	455933..457732	–
XII	YNCL0017C	ETS1-1		rRNA gene	457733..458432	–
XII	YNCL0018W	RDN5-1		rRNA gene	459676..459796	+
XII	YNCL0019C	ETS2-2		rRNA gene	460712..460922	–
XII	YNCL0020C	RDN37-2		rRNA gene	460712..467569	–
XII	YNCL0021C	RDN25-2		rRNA gene	460923..464318	–
XII	YNCL0022C	ITS2-2		rRNA gene	464319..464550	–
XII	YNCL0023C	RDN58-2		rRNA gene	464551..464708	–
XII	YNCL0024C	ITS1-2		rRNA gene	464709..465069	–
XII	YNCL0025C	RDN18-2		rRNA gene	465070..466869	–
XII	YNCL0026C	ETS1-2		rRNA gene	466870..467569	–
XII	YNCL0027W	RDN5-2		rRNA gene	468813..468931	+
XII	YNCL0028W	RDN5-3		rRNA gene	472465..472583	+
XII	YNCL0029W	RDN5-4		rRNA gene	482045..482163	+
XII	YNCL0030W	RDN5-5		rRNA gene	485697..485815	+
XII	YNCL0031W	RDN5-6		rRNA gene	489349..489469	+
XII	YNCL0032C		tL(UAG)L1, tRNA-Leu	tRNA gene	592519..592619	–
XII	YNCL0033C		tI(UAU)L, tRNA-Ile	tRNA gene	605300..605432	–
XII	YNCL0034W		tL(CAA)L, tRNA-Leu	tRNA gene	628383..628497	+
XII	YNCL0035C		tA(AGC)L, tRNA-Ala	tRNA gene	656934..657006	–
XII	YNCL0036C		tV(AAC)L, tRNA-Val	tRNA gene	687859..687932	–
XII	YNCL0037W		tL(UAG)L2, tRNA-Leu	tRNA gene	732090..732190	+
XII	YNCL0038W		tI(AAU)L1, tRNA-Ile	tRNA gene	734802..734875	+
XII	YNCL0039W		tX(XXX)L	tRNA gene	784354..784453	+
XII	YNCL0040W		tD(GUC)L2, tRNA-Asp	tRNA gene	793918..793989	+
XII	YNCL0041C	SNR61	snR61	snoRNA gene	794486..794575	–
XII	YNCL0042C	SNR55	snR55	snoRNA gene	794697..794794	–
XII	YNCL0043C	SNR57	snR57	snoRNA gene	794937..795024	–
XII	YNCL0044W		tE(UUC)L, tRNA-Glu	tRNA gene	797178..797249	+
XII	YNCL0045W	TRR4	tR(CCG)L, tRNA-Arg	tRNA gene	818609..818680	+
XII	YNCL0046W	SNR44	snR44	snoRNA gene	856710..856920	+
XII	YNCL0047W		tK(UUU)L, tRNA-Lys	tRNA gene	875376..875471	+
XII	YNCL0048W	SNR34	snR34	snoRNA gene	899180..899382	+
XII	YNCL0049C		tL(UAA)L, tRNA-Leu	tRNA gene	962972..963055	–
XII	YNCL0050C		tN(GUU)L, tRNA-Asn	tRNA gene	975983..976056	–
XII	YNCL0051C		tI(AAU)L2, tRNA-Ile	tRNA gene	1052071..1052144	–
XIII	YNCM0001W		PHO84 lncRNA	ncRNA gene	23564..26578	+
XIII	YNCM0002C	SNR85	snR85	snoRNA gene	67768..67938	–
XIII	YNCM0003W	ZOD1		ncRNA gene	91970..92027	+
XIII	YNCM0004C		tR(UCU)M2, tRNA-Arg	tRNA gene	131825..131896	–
XIII	YNCM0005C	SNR54	snR54	snoRNA gene	163535..163620	–
XIII	YNCM0006W	SUP5	tY(GUA)M1, tRNA-Tyr	tRNA gene	168795..168883	+
XIII	YNCM0007C		tG(GCC)M, tRNA-Gly	tRNA gene	183898..183968	–
XIII	YNCM0008C	SUF7	tP(UGG)M, tRNA-Pro	tRNA gene	196068..196170	–
XIII	YNCM0009C		tS(AGA)M, tRNA-Ser	tRNA gene	259158..259239	–
XIII	YNCM0010W		tE(UUC)M, tRNA-Glu	tRNA gene	290801..290872	+
XIII	YNCM0011W	SNR78	snR78	snoRNA gene	297278..297364	+
XIII	YNCM0012W	SNR77	snR77	snoRNA gene	297506..297593	+
XIII	YNCM0013W	SNR76	snR76	snoRNA gene	297725..297833	+
XIII	YNCM0014W	SNR75	snR75	snoRNA gene	297918..298006	+
XIII	YNCM0015W	SNR74	snR74	snoRNA gene	298138..298225	+
XIII	YNCM0016W	SNR73	snR73	snoRNA gene	298307..298412	+
XIII	YNCM0017W	SNR72	snR72	snoRNA gene	298554..298651	+
XIII	YNCM0018C		tA(AGC)M1, tRNA-Ala	tRNA gene	321147..321219	–
XIII	YNCM0019W		tF(GAA)M, tRNA-Phe	tRNA gene	352280..352370	+
XIII	YNCM0020W		tH(GUG)M, tRNA-His	tRNA gene	363064..363135	+
XIII	YNCM0021C		tV(AAC)M1, tRNA-Val	tRNA gene	372445..372518	–
XIII	YNCM0022C		tW(CCA)M, tRNA-Trp	tRNA gene	379303..379408	–
XIII	YNCM0023C		tV(AAC)M2, tRNA-Val	tRNA gene	420588..420661	–
XIII	YNCM0024W		tD(GUC)M, tRNA-Asp	tRNA gene	463554..463625	+
XIII	YNCM0025C		tK(CUU)M, tRNA-Lys	tRNA gene	480621..480693	–
XIII	YNCM0026C	SNR24	snR24	snoRNA gene	499984..500072	–
XIII	YNCM0027W		tL(CAA)M, tRNA-Leu	tRNA gene	504895..505008	+
XIII	YNCM0028C	EMT4	tM(CAU)M, tRNA-Met	tRNA gene	572883..572955	–
XIII	YNCM0029C		tV(AAC)M3, tRNA-Val	tRNA gene	586636..586709	–
XIII	YNCM0030W	SNR83	snR83	snoRNA gene	626349..626654	+
XIII	YNCM0031W	SNR11	snR11	snoRNA gene	652275..652532	+
XIII	YNCM0032C	RNA170		ncRNA gene	667288..667456	–
XIII	YNCM0033C		tR(UCU)M1, tRNA-Arg	tRNA gene	747892..747963	–
XIII	YNCM0034C	SNR86	snR86	snoRNA gene	762110..763113	–
XIII	YNCM0035C		tA(AGC)M2, tRNA-Ala	tRNA gene	768369..768441	–
XIII	YNCM0036C	CDC65	tQ(CUG)M, tRNA-Gln	tRNA gene	808246..808317	–
XIII	YNCM0037W	SUP8	tY(GUA)M2, tRNA-Tyr	tRNA gene	837928..838016	+
XIV	YNCN0001W	SNR40	snR40	snoRNA gene	89210..89306	+
XIV	YNCN0002C	SUF6	tG(UCC)N, tRNA-Gly	tRNA gene	96241..96312	–
XIV	YNCN0003W		tN(GUU)N1, tRNA-Asn	tRNA gene	102716..102789	+
XIV	YNCN0004W		tT(AGU)N1, tRNA-Thr	tRNA gene	104805..104877	+
XIV	YNCN0005C	SNR19	snR19	snRNA gene	230105..230672	–
XIV	YNCN0006W		tF(GAA)N, tRNA-Phe	tRNA gene	374869..374959	+
XIV	YNCN0007W		tL(CAA)N, tRNA-Leu	tRNA gene	443006..443119	+
XIV	YNCN0008C		tD(GUC)N, tRNA-Asp	tRNA gene	519099..519169	–
XIV	YNCN0009W		tP(UGG)N1, tRNA-Pro	tRNA gene	547094..547196	+
XIV	YNCN0010C		tT(AGU)N2, tRNA-Thr	tRNA gene	560693..560765	–
XIV	YNCN0011W		tP(UGG)N2, tRNA-Pro	tRNA gene	568115..568217	+
XIV	YNCN0012C		tI(AAU)N1, tRNA-Ile	tRNA gene	569867..569940	–
XIV	YNCN0013W	NME1		snoRNA gene	585587..585926	+
XIV	YNCN0014W	SNR66	snR66	snoRNA gene	586090..586175	+
XIV	YNCN0015W		tI(AAU)N2, tRNA-Ile	tRNA gene	602312..602385	+
XIV	YNCN0016C	SUF10	tP(AGG)N, tRNA-Pro	tRNA gene	631846..631917	–
XIV	YNCN0017W		tN(GUU)N2, tRNA-Asn	tRNA gene	632599..632672	+
XIV	YNCN0018W	SNR49	snR49	snoRNA gene	716120..716284	+
XIV	YNCN0019C	SNR191	snR191	snoRNA gene	721938..722211	–
XIV	YNCN0020C		tL(UAA)N, tRNA-Leu	tRNA gene	726134..726217	–
XV	YNCO0001C	SUF1	tG(UCC)O, tRNA-Gly	tRNA gene	110962..111033	–
XV	YNCO0002W		tT(AGU)O1, tRNA-Thr	tRNA gene	113802..113874	+
XV	YNCO0003C	SNR58	snR58	snoRNA gene	136088..136183	–
XV	YNCO0004C		tG(GCC)O1, tRNA-Gly	tRNA gene	226611..226681	–
XV	YNCO0005W		tN(GUU)O1, tRNA-Asn	tRNA gene	228331..228404	+
XV	YNCO0006W	SNR81	snR81	snoRNA gene	234346..234546	+
XV	YNCO0007W	SNR50	snR50	snoRNA gene	259489..259578	+
XV	YNCO0008W		tS(GCU)O, tRNA-Ser	tRNA gene	274673..274773	+
XV	YNCO0009W	SUF17	tG(GCC)O2, tRNA-Gly	tRNA gene	282164..282234	+
XV	YNCO0010W	SUP3	tY(GUA)O, tRNA-Tyr	tRNA gene	288192..288280	+
XV	YNCO0011W		tP(UGG)O1, tRNA-Pro	tRNA gene	301097..301198	+
XV	YNCO0012C		tR(ACG)O, tRNA-ARg	tRNA gene	340299..340371	–
XV	YNCO0013C		tT(AGU)O2, tRNA-Thr	tRNA gene	354041..354113	–
XV	YNCO0014C	SNR9	snR9	snoRNA gene	407948..408134	–
XV	YNCO0015C	SNR62	snR62	snoRNA gene	409765..409864	–
XV	YNCO0016W		tK(UUU)O, tRNA-Lys	tRNA gene	438643..438738	+
XV	YNCO0017W	SUF11	tP(UGG)O2, tRNA-Pro	tRNA gene	464450..464551	+
XV	YNCO0018W		tN(GUU)O2, tRNA-Asn	tRNA gene	487439..487512	+
XV	YNCO0019W		tD(GUC)O, tRNA-Asp	tRNA gene	571958..572029	+
XV	YNCO0020C	SUF5	tG(CCC)O	tRNA gene	594354..594425	–
XV	YNCO0021C		tV(AAC)O	tRNA gene	663812..663885	–
XV	YNCO0022C	SNR36	snR36	snoRNA gene	680685..680866	–
XV	YNCO0023W	IMT1	tM(CAU)O1, tRNA-Met	tRNA gene	710201..710272	+
XV	YNCO0024C	SNR35	snR35	snoRNA gene	759326..759529	–
XV	YNCO0025W	SNR17A	snR17a	snoRNA gene	780107..780596	+
XV	YNCO0026W	SNR8	snR8	snoRNA gene	832332..832521	+
XV	YNCO0027C	SNR31	snR31	snoRNA gene	841958..842182	–
XV	YNCO0028W	SNR5	snR5	snoRNA gene	842403..842606	+
XV	YNCO0029C		tA(UGC)O, tRNA-Ala	tRNA gene	854187..854259	–
XV	YNCO0030W	EMT2	tM(CAU)O2, tRNA-Met	tRNA gene	976421..976493	+
XV	YNCO0031W		tP(UGG)O3, tRNA-Pro	tRNA gene	980683..980787	+
XVI	YNCP0001C		tW(CCA)P, tRNA-Trp	tRNA gene	56169..56274	–
XVI	YNCP0002W		GAL4 lncRNA	ncRNA gene	79562..82648	+
XVI	YNCP0003W	SNR59	snR59	snoRNA gene	173827..173904	+
XVI	YNCP0004C		tE(UUC)P, tRNA-Glu	tRNA gene	210192..210263	–
XVI	YNCP0005C	SNR17B	snR17b	snoRNA gene	281056..281517	–
XVI	YNCP0006C	IMT2	tM(CAU)P, tRNA-Met	tRNA gene	338848..338919	–
XVI	YNCP0007C		tC(GCA)P1, tRNA-Cys	tRNA gene	435893..435964	–
XVI	YNCP0008C		tF(GAA)P1, tRNA-Phe	tRNA gene	560198..560289	–
XVI	YNCP0009W		tG(GCC)P1, tRNA-Gly	tRNA gene	572269..572339	+
XVI	YNCP0010W		tK(CUU)P, tRNA-Lys	tRNA gene	582062..582134	+
XVI	YNCP0011C		tF(GAA)P2, tRNA-Phe	tRNA gene	622540..622631	–
XVI	YNCP0012W	SUP16	tS(UGA)P, tRNA-Ser	tRNA gene	689565..689646	+
XVI	YNCP0013C	SNR51	snR51	snoRNA gene	718700..718806	–
XVI	YNCP0014C	SNR70	snR70	snoRNA gene	718887..719050	–
XVI	YNCP0015C	SNR41	snR41	snoRNA gene	719148..719242	–
XVI	YNCP0016W		tT(UGU)P, tRNA-Thr	tRNA gene	744284..744355	+
XVI	YNCP0017C		tK(UUU)P, tRNA-Lys	tRNA gene	769207..769302	–
XVI	YNCP0018C		tC(GCA)P2, tRNA-Cys	tRNA gene	775765..775836	–
XVI	YNCP0019W		tN(GUU)P, tRNA-Asn	tRNA gene	810676..810749	+
XVI	YNCP0020W		tI(AAU)P1, tRNA-Ile	tRNA gene	819529..819602	+
XVI	YNCP0021W	SNR45	snR45	snoRNA gene	821732..821903	+
XVI	YNCP0022W		tA(AGC)P, tRNA-Ala	tRNA gene	856902..856974	+
XVI	YNCP0023W		tG(GCC)P2, tRNA-Gly	tRNA gene	860379..860449	+
XVI	YNCP0024C		tI(AAU)P2, tRNA-Ile	tRNA gene	880296..880369	–
Mito	YNCQ0001W		tP(UGG)Q, tRNA-Pro	tRNA gene	731..802	+
Mito	YNCQ0002W	15S_RRNA	Q0020	rRNA gene	6546..8194	+
Mito	YNCQ0003W		tW(UCA)Q, tRNA-Trp	tRNA gene	9374..9447	+
Mito	YNCQ0004W		tE(UUC)Q, tRNA-Glu	tRNA gene	35373..35444	+
Mito	YNCQ0005W		tS(UGA)Q2, tRNA-Ser	tRNA gene	48201..48290	+
Mito	YNCQ0006W	21S_RRNA	Q0158	rRNA gene	58009..62447	+
Mito	YNCQ0007W		tT(UGU)Q1, tRNA-Thr	tRNA gene	63862..63937	+
Mito	YNCQ0008W		tC(GCA)Q, tRNA-Cys	tRNA gene	64415..64490	+
Mito	YNCQ0009W		tH(GUG)Q, tRNA-His	tRNA gene	64596..64670	+
Mito	YNCQ0010W		tL(UAA)Q, tRNA-Leu	tRNA gene	66095..66179	+
Mito	YNCQ0011W		tQ(UUG)Q, tRNA-Gln	tRNA gene	66210..66285	+
Mito	YNCQ0012W		tK(UUU)Q, tRNA-Lys	tRNA gene	67061..67134	+
Mito	YNCQ0013W		tR(UCU)Q1, tRNA-Arg	tRNA gene	67309..67381	+
Mito	YNCQ0014W		tG(UCC)Q, tRNA-Gly	tRNA gene	67468..67542	+
Mito	YNCQ0015W		tD(GUC)Q, tRNA-Asp	tRNA gene	68322..68396	+
Mito	YNCQ0016W		tS(GCU)Q1, tRNA-Ser	tRNA gene	69203..69288	+
Mito	YNCQ0017W		tR(ACG)Q2, tRNA-Arg	tRNA gene	69289..69362	+
Mito	YNCQ0018W		tA(UGC)Q, tRNA-Ala	tRNA gene	69846..69921	+
Mito	YNCQ0019W		tI(GAU)Q, tRNA-Ile	tRNA gene	70162..70237	+
Mito	YNCQ0020W		tY(GUA)Q, tRNA-Tyr	tRNA gene	70824..70907	+
Mito	YNCQ0021W		tN(GUU)Q, tRNA-Asn	tRNA gene	71433..71503	+
Mito	YNCQ0022W		tM(CAU)Q1, tRNA-Met	tRNA gene	72630..72705	+
Mito	YNCQ0023W		tF(GAA)Q, tRNA-Phe	tRNA gene	77431..77505	+
Mito	YNCQ0024C		tT(UAG)Q2, tRNA-Thr	tRNA gene	78089..78162	–
Mito	YNCQ0025W		tV(UAC)Q, tRNA-Val	tRNA gene	78533..78608	+
Mito	YNCQ0026W		tM(CAU)Q2, tRNA-Met	tRNA gene	85035..85112	+
Mito	YNCQ0027W	RPM1	Q0285	ncRNA gene	85295..85777	+

Various sequence and annotation files are available on SGD’s Downloads site.

Categories: Data updates

SGD Newsletter, Spring 2021

May 27, 2021

About this newsletter:

This is the Spring 2021 issue of the SGD newsletter. The goal of this newsletter is to inform our users about new features in SGD and to foster communication within the yeast community. You can view this newsletter as well as previous newsletters on our Community Wiki.

R64.3 Annotation Update
New Homology Pages
Functional Complementation Data Available on References Pages
YeastMine Updates and New Templates
Textpresso Central Update
Number of Curated Alleles Continues to Grow
Alliance of Genome Resources – Disease Associations for model organisms
Fungal Pathogen Genomics Workshop

R64.3 Annotation Update

SGD curators periodically update the chromosomal annotations of the S. cerevisiae Reference Genome, which is derived from strain S288C.

The R64.3 annotation release, dated 2021-04-21, included various updates and additions:

7 new ORFs: OTO1/YGR227C-A, YHR052C-B, YHR054C-B, YJR107C-A, YKL104W-A, YLR379W-A, YMR008C-A
5 new ncRNAs: GAL10-ncRNA, TBRT/XUT_2F-154, SUT169, PHO84 lncRNA, GAL4 lncRNA
2 new uORFs for ROK1/YGL171W
1 new recombination enhancer: RE
1 new LTR: YELWdelta27
3 ORFs with shifted translation starts: HPA3/YEL066W, YJR012C, LTO1/YNL260C
1 ORF with shifted translation stop plus new intron: LDO45/YMR147W
Changed feature_type (and SO_term) for non-transcribed spacers: NTS1-2, NTS2-1, NTS2-2
New systematic nomenclature system for entire annotated complement of ncRNAs

Various sequence and annotation files are available on SGD’s Downloads site. You can find more update details and read about the new systematic nomenclature system for noncoding RNA genes on the Details of 2021 Reference Genome Annotation Update R64.3 SGD Wiki page.

New Homology Pages

SGD is excited to introduce our new Homology Pages! These pages can be accessed by clicking on the Homology tab in the header of SGD gene pages, as seen below.

The information displayed on the Homology Pages is divided into several sections:

Homologs: Information about known homologs for the gene of interest, such as the species of the homolog, the corresponding Gene ID from the Alliance of Genome Resources, and the name of the homolog.
Functional Complementation: Data about cross-species functional complementation between yeast and other species, curated by SGD and the Princeton Protein Orthology Database (P-POD).
Fungal Homologs: Curated homolog information for 24 additional species of fungi. View the species of the fungal homolog, the database source of the entry, and the Gene ID of the homolog from that database.
External Identifiers: A list of external identifiers for the protein from various database sources.

Functional Complementation Data Available on References Pages

Functional Complementation annotations are now viewable on reference pages for which there is curatable functional complementation data. This information describes cross-species functional complementation between yeast and other species, and is curated by SGD and the Princeton Protein Orthology Database (P-POD).

YeastMine Updates and New Templates

SGD has updated the current Gene–>UTRs YeastMine template with newly calculated 5′ and 3′ UTR sequence/coordinates. Additionally, transcript iso-forms for specific genes from the Pelachano et al., 2013 study can be accessed in YeastMine using the new Gene–>Transcripts template. Both templates can be found under the “Templates” section of YeastMine under the “Expression” category.

Textpresso Central Update

Textpresso has recently been updated with a new system, adopting an overhauled user interface and introducing several new features including:

Search results shown in the context of the full text
Custom corpus creation
Customizable annotation interface
Search terms are highlighted in full-text view

Textpresso Central can also be accessed by clicking on “Full-text Search” under the Literature pull-down menu on the home page of SGD. More information about the changes and types of papers stored in Textpresso can be found in their About Us help section or (from Müller et al., 2018).

Number of Curated Alleles Continues to Grow

SGD now has approximately 13,000 alleles that are either fully or partially curated. To navigate to an allele page, use the search bar to find a specific allele or enter a gene name and select an allele from the autocomplete list. Additionally, these pages can be accessed by clicking on the allele name in a gene’s Phenotype Annotation table. SGD Curators continue to add new alleles or update existing ones as new information becomes available.

You can generate a list of all alleles in our database or find alleles for a specific gene using the Genes –> Alleles template in YeastMine.

Alliance of Genome Resources – Disease Associations for model organisms

Did you know that you can find human disease associations for yeast genes and their orthologs in other key model organisms at the Alliance of Genome Resources?

SGD is a founding member of the Alliance of Genome Resources, which was established to facilitate the use of diverse model organisms in understanding the genetic and genomic bases of human biology, health, and disease. Gene pages for yeast and other model organisms at the Alliance include a section for Disease Associations, including those for orthologous genes. Human diseases are represented using the Disease Ontology (DO).

Fungal Pathogen Genomics Workshop

From May 10th – 14th, Senior Biocuration Scientist Edith Wong, Senior Biocuration Scientist Rob Nash, Senior Biocuration Scientist Marek Skrzypek, Biocuration Scientist Suzi Aleksander, and Associate Biocuration Scientist Micheal Alexander were instructors for the Virtual Fungal Pathogen Genomics Workshop hosted by Wellcome Connecting Science. Our curators helped attendees learn more about the unique tools hosted on our website and provided them the opportunity to learn about other curation tools from FungiDB, EnsemblFungi, CGD, MycoCosm, and JGI.

We would like to thank the Fungal Pathogen Genomics team for facilitating a successful virtual workshop, and for providing excellent training in web-based data mining resources for all attendees.

Categories: Newsletter

SGD Homology Data Now Available On New Homology Pages

March 25, 2021

SGD is excited to introduce our new Homology Pages! These pages can be accessed by clicking on the Homology tab in the header of SGD gene pages, as seen below.

The information displayed on the Homology Pages is divided into several sections:

Homologs: Information about known homologs for the gene of interest, such as the species of the homolog, the corresponding Gene ID from the Alliance of Genome Resources, and the name of the homolog.
Functional Complementation: Data about cross-species functional complementation between yeast and other species, curated by SGD and the Princeton Protein Orthology Database (P-POD).
Fungal Homologs: Curated homolog information for 24 additional species of fungi. View the species of the fungal homolog, the database source of the entry, and the Gene ID of the homolog from that database.
External Identifiers: A list of external identifiers for the protein from various database sources.

If you have any questions or feedback regarding our new Homology Pages, please do not hesitate to contact us at any time.

Categories: Data updates, Homologs, New Data, Yeast and Human Disease

BREWMOR Workshop: Preparing Undergraduate Students for Research Experiences

February 03, 2021

BREWMOR: Bridging Research and Education With Model ORganisms (formerly BREW) will be hosting a virtual workshop titled, “Preparing Undergraduate Students for Research Experiences,” on Friday February 19th, 2021 from 4 – 6:30 PM US Eastern time.

After a very successful virtual BREW (Bridging Research and Education Workshop) in July of 2020 as part of the TAGC meeting, a steering committee was formed to coordinate activities of the BREW community. The name of the community was changed to BREWMOR: Bridging Research and Education With Model ORganisms, to include model organisms beyond yeast.

A micro-BREWMOR event that will be held virtually on Friday February 19th, 2021 from 4-6:30 PM US Eastern time. The main purpose of the event is to provide a forum for social interactions and building a community for support and resource sharing. The theme of this micro-BREWMOR will be “Preparing Undergraduate Students for Research Experiences”. The workshop will include a session related to the event’s main theme and opportunities to connect and collaborate with other undergraduate research mentors and teachers in multiple small breakout rooms focused on various topics.

Please register by February 8th at https://forms.gle/fdBCFxYjWuY38tSG6 . Registration is free.

We hope you can join us at the micro-BREWMOR!

https://brewmor.weebly.com/gatherings.html

Categories: Announcements

Apply Now for the 2021 Fungal Pathogen Genomics (Virtual) Course

January 21, 2021

Fungal Pathogen Genomics is an exciting several day long course that provides experimental biologists working on fungal organisms with hands-on experience in genomic-scale data analysis. Through a collaborative teaching effort between the web-based fungal data mining resources FungiDB, EnsemblFungi, PomBase, SGD, CGD, MycoCosm, and JGI, students will learn how to utilize the unique tools provided by each database, develop testable hypotheses, and analyze various ‘omics’ datasets across multiple databases.

Please note: Due to the ongoing Covid-19 pandemic, the 2021 Fungal Pathogen Genomics course will be delivered in a virtual format.

Daily activities will include individual and group training exercises, supplementary lectures on bioinformatics techniques and tools used by various databases, and presentations by distinguished guest speakers covering the following topics:

Comparative genomics, gene trees, whole-genome alignment
Identification of orthologs and orthology-based inference
Genome browsers and gene pages
RNA-Seq analysis and visualization in VEuPathDB Galaxy
Variant calling analysis and Ensembl Variant Effect Predictor (VEP) tool
Development of advanced biologically relevant queries using FungiDB ‘search strategies’ and mining integrated datasets (proteomics, transcriptomics, phenotypes, etc.)
Genetic interactions, virulence genes, secondary metabolites
Overview of ontology structure, evidence, available tools, slimming and enrichment
Introduction to annotation and curation of fungal genomes (e.g. Apollo in EnsemblFungi, FungiDB, and MycoCosm/JGI)

The application deadline for the Fungal Pathogen Genomics workshop to be held May 10-14, 2021 in virtual format is February 18, 2021.

Don’t miss out – apply now!

Categories: Announcements

SGD Newsletter, Fall 2020

December 08, 2020

About this newsletter:

This is the Fall 2020 issue of the SGD newsletter. The goal of this newsletter is to inform our users about new features in SGD and to foster communication within the yeast community. You can view this newsletter as well as previous newsletters on our community Wiki.

Contents:

New SGD Allele Pages
Interaction Page Updates
Links on SGD gene pages to homolog gene pages at the Alliance of Genome Resources
Alliance of Genome Resources at Version 3.2
Jeremy Thorner Retiring
YeaZ system for microscopy images
In Memoriam: Angelika Amon
Gene Ontology Consortium Meeting
Happy Holidays from SGD!

New SGD Allele Pages

We are pleased to announce that SGD’s brand new Allele Pages are now available on our website. To navigate to an allele page, use the search bar to find a specific allele or enter a gene name and select an allele from the autocomplete list. Additionally, these pages can be accessed by clicking on the allele name in a gene’s Phenotype Annotation table. These pages are still being updated with new information as it becomes available. The type of information that you can find on each allele page includes:

Allele Overview: General information about the allele, such as its name, the affected gene, the type of allele (e.g. missense), and a description of sequence change and/or domain mutated.
Phenotype and Interaction Annotations: Phenotype and Genetic Interaction Annotation tables for the allele.
Shared Alleles: A network diagram depicting shared phenotypes and interactions with other alleles.

If you are interested in viewing all alleles for a specific gene or would like to view a comprehensive list of the alleles that SGD currently has curated, you can use this YeastMine template with your customized parameters.

Interaction Page Updates

SGD has made recent updates to our Gene Interactions Page for improved clarity. Previously, genetic and physical interaction annotations were combined in one table, but now these annotations are recorded in separate annotation tables. The menu in the top left corner can be used to view and navigate to each section of the Interactions page. Additionally, alleles, SGA Scores, and P-values are now included for annotations from the global interactions paper by Costanzo M, et al. (2016) .

Links on SGD gene pages to homolog gene pages at the Alliance of Genome Resources

Previously, the ‘Comparative Info’ section on the Gene Summary page contained a link to the Alliance of Genome Resources if integrated model organism details were available. Now, users will instead find hexagonal buttons representing each model organism (human, mouse, rat, zebrafish, fly, and worm) for which there is homologous gene information at the Alliance of Genome Resources. Clicking on the link will immediately direct the user to the gene page for the selected model organism on the Alliance website.

Alliance of Genome Resources at Version 3.2

The Alliance of Genome Resources , a collaborative effort from SGD and other model organism databases (MOD), released version 3.2 in October. Notable improvements and new features include:

Gene pages now display transgenic allele data under the ‘Transgenic Allele’ section.
Allele and Variant sections on Gene pages have improved formatting and are now downloadable.
“NOT” disease annotations are shown in Disease, Alleles and Variants, and Models sections when an anticipated disease annotation was not found.
Enhanced variant data representation on Allele pages.
High-throughput profiling experiment metadata can be searched and will display in the search results as HTP Dataset Index.
The Alliance User Community discussion forum has been released.

Jeremy Thorner Retiring

Jeremy Thorner, a prolific yeast researcher and outstanding mentor, has announced that his lab is closing. His lab provided the following notice:

“After 47 years at the University of California, Berkeley, the laboratory of Professor Jeremy Thorner will be closing permanently, as of 30 June 2021. After that date, there will be no way to distribute any strains, plasmids, enzymes, or antibodies generated during the course of the studies on Saccharomyces cerevisiae conducted by the Thorner laboratory over those many years.”

YeaZ system for microscopy images

YeaZ is a system for efficiently and accurately segmenting microscopy images of yeast cells. It contains a convolutional neural network, with an underlying training set of high-qual|ty segmented yeast images, as well as a graphical user interface and a web application to employ, test, and expand the system. The system contains a Python based application with graphical user interface available on GitHub , as well as standalone apps for both Windows and Mac based computers, and training sets. Additional information is available in the accompanying Nature Communications paper by Dietler et al., 2020 .

YeaZ was created at École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland. Please contact Sahand Jamal Rahi with questions, or ideas for improvements.

In Memoriam: Angelika Amon

It was with great sadness that we learned that Angelika Amon, cell biologist and Professor of Biology at MIT and a member of the Koch Institute for Integrative Cancer Research, passed away on October 29, 2020. Angelika was widely known for her novel contributions to the field of cell biology and proliferation, with her research focusing on aneuploidy and the consequences of chromosome mis-segregation. At the beginning of Angelika’s career, her work on yeast genetics led to the discovery that cyclins must break down completely before cells progress from mitosis to G1.

Her research has helped shape the current understanding of cell division, and her passion for genetics will live on through her students and colleagues who continue her work. Angelika was a treasured part of the genetics community and will be missed dearly.

The Genetics Society of America has featured a tribute piece in remembrance of Angelika Amon , written by her friend and colleague, Orna Cohen-Fix.

Gene Ontology Consortium Meeting

From October 6th-8th, PI Mike Cherry, Senior Biocuration Scientist Edith Wong, Senior Biocuration Scientist Rob Nash, Senior Biocuration Scientist Marek Skrzypek, Biocuration Scientist Suzi Aleksander, and Associate Biocuration Scientist Micheal Alexander attended the Gene Ontology Consortium meeting. Suzi presented on SGD’s GO display and GO tools, and curators learned more about how other databases utilize GO. SGD Curators also participated in meaningful discussions about improving existing GO resources while also helping with the planning of new GO projects.

We would like to thank The Gene Ontology for facilitating this successful change to a virtual conference and holding an accessible, well received event for the entire model organism community!

Happy Holidays from SGD!

We would like to take this opportunity to recognize that 2020 has brought many changes and challenges for everyone. Our thoughts go out to all those who have been impacted by the unprecedented events of this year.

We wish you and your family, friends, and lab mates the best during the upcoming holidays. Stanford University will be closed for three weeks starting on December 14 and will reopen on January 4th, 2021 . Although SGD staff members will be taking time off, the website will be up and running throughout the winter break, and we will resume responding to user requests and questions in the new year.

Categories: Newsletter

Interactions Page Updates

November 06, 2020

Additionally, alleles, SGA Scores, and P-values are now included for annotations from the global interactions paper by Costanzo M, et al. (2016).

Please be sure to watch our Interactions Page Updates tutorial video for a quick walk-through of the changes:

If you have any questions or feedback about the updates to our Interactions Pages, please do not hesitate to contact us at any time.

Categories: Announcements, Data updates

Explore SGD Allele Data Using New Allele Pages

October 29, 2020

The type of information that you can find on each allele page includes:

Allele Overview: General information about the allele, such as its name, the affected gene, the type of allele (e.g. missense), and a description of sequence change and/or domain mutated.
Phenotype and Interaction Annotations: Phenotype and Genetic Interaction Annotation tables for the allele.
Shared Alleles: A network diagram depicting shared phenotypes and interactions with other alleles.

Start browsing the thousands of alleles we now have yourself, or check out our Allele Pages video for a more detailed walk-through of what you can expect to find on each allele page:

If you have any questions or feedback about the new Allele pages and data, please don’t hesitate to contact us at any time.

Categories: Website changes

Announcement from Jeremy Thorner

October 27, 2020

NOTICE: After 47 years at the University of California, Berkeley, the laboratory of Professor Jeremy Thorner will be closing permanently, as of 30 June 2021. After that date, there will be no way to distribute any strains, plasmids, enzymes, or antibodies generated during the course of the studies on Saccharomyces cerevisiae conducted by the Thorner laboratory over those many years.

Categories: Announcements

SGD Newsletter, Summer 2020

June 08, 2020

About this newsletter:

This is the Summer 2020 issue of the SGD newsletter. The goal of this newsletter is to inform our users about new features in SGD and to foster communication within the yeast community. You can view this newsletter as well as previous newsletters on our community Wiki.

Contents:

Submit Data Form
The Allied Genetics Conference (TAGC 2020)
Explore SGD
SGD Website Trailer
Supplemental Data
26th Anniversary of the SGD Website
A Note on COVID-19

Submit Data Form

Are you away from the bench right now and have a bit of extra time on your hands? SGD can use your help! Authors can submit data and information about their publications by pointing us to novel results, datasets (we appreciate GEO accession IDs!), or other important information, using SGD’s simple “Submit Data” form (https://www.yeastgenome.org/submitData).

The Allied Genetics Conference (TAGC 2020)

Members of the SGD team virtually attended The Allied Genetics Conference in April 2020. Principal investigator Mike Cherry, PhD, gave a virtual workshop on using SGD and highlighted some of the useful tools and resources available to our users. SGD staff interacted with members of the yeast community through the conference Slack channels and also presented posters as part of the virtual poster sessions throughout the week (see below). We would like to thank the GSA for facilitating this successful change to a virtual conference and holding an accessible, well received event for the entire model organism community!

Presenter	Poster Title
Suzi Aleksander	*“The Use of the Gene Ontology to Describe Biological Function at Saccharomyces* Genome Database”**
Micheal Alexander	*“Integration of Macromolecular Complex Data into the Saccharomyces* Genome Database”**
Joanna Argasinska	*“Saccharomyces* Genome Database (SGD) Through the Years”**
Stacia Engel	“SGD & the Alliance of Genome Resources”
Rob Nash	“Yeast-Human Cross-Species Complementation and Associations with Disease-related Genes”

Explore SGD

We recently added the new ‘Explore SGD’ button to the SGD homepage which allows for the exploration of data and pages without an initial search query.

If you select the ‘Explore SGD’ button, you will be redirected to our search results page and can browse all of the information SGD has to offer. The tool is designed for both new and veteran users alike. New users are provided a glimpse into the warehouse of information SGD contains, while seasoned users may discover something new. After clicking on the ‘Explore SGD’ button, be sure to use the categories on the left to navigate through the various pages and examine areas of interest. If you are viewing this page on a mobile device, tap on “Categories” at the top of your screen to see the list of categories.

Additionally, an ‘Explore’ button has been added to the selection of links available in the black bar at the top of every page. This gives users the ability to access the search results page from anywhere on the SGD website.

SGD Website Trailer

What are the basic features of SGD? Watch our new video to learn some of the key features that are available to help users with their research efforts. While this video does not include all of the many tools and resources that SGD has to offer, we have also generated a list of helpful SGD links which can be found on our help pages.

You can find this video, as well as other video tutorials on SGD resources, on our YouTube channel!

Supplemental Data

SGD is now uploading and storing supplemental materials for our yeast papers! We are hosting data from past, present, and future papers on our literature pages. To access these data, simply search SGD with the paper’s PubMed ID and then look for the “Downloadable Files.”

26th Anniversary of the SGD Website

Screen Shot 2020-05-13 at 5.01.28 PM — The SGD Team zoomed in to celebrate the anniversary with cupcakes and fuzzy budders

Happy Birthday (Bud-day!) to Us! May 8, 2020 marked the 26th anniversary of the day the SGD website first went live, bringing yeast genome information to all! In May 1994, the “World Wide Web” had only been in existence for about 22 months, but starting way back then, anyone (especially yeast researchers!) could easily access the “SacchDB” database from our old server “genome-www.stanford.edu” to find information on our favorite model organism, the budding yeast. We’ve grown a lot since then, and have even migrated to the cloud! But as always, we’d like to express our gratitude to all of our users, collaborators, advisors, staff, and anyone else who has supported SGD over the last 26 years. Without such a great community behind us, SGD would not be the fantastic resource it is today.

A Note on COVID-19

We recognize that 2020 has brought many changes and challenges. Our thoughts go out to all those impacted by the novel coronavirus, SARS-CoV-2. Like many of you, we have found ourselves adjusting to these times, and the SGD team is currently working from home for the foreseeable future. Rest assured, we are still working just as hard to maintain the SGD resource and continuing to serve the amazing budding yeast community!

Categories: Newsletter